diff --git a/.whitesource b/.whitesource new file mode 100644 index 0000000..f056952 --- /dev/null +++ b/.whitesource @@ -0,0 +1,8 @@ +{ + "generalSettings": { + "shouldScanRepo": true + }, + "checkRunSettings": { + "vulnerableCheckRunConclusionLevel": "failure" + } +} \ No newline at end of file diff --git a/README.md b/README.md index e0f40a8..abbb8a2 100644 --- a/README.md +++ b/README.md @@ -6,6 +6,7 @@ - [Comprehensive topic-wise list of Machine Learning and Deep Learning tutorials, codes, articles and other resources](https://github.com/ujjwalkarn/Machine-Learning-Tutorials/blob/master/README.md). ## The Python Language +- [Learn Python Codecademy](https://www.codecademy.com/learn/python#) - [Python 3 in one picture](https://fossbytes.com/wp-content/uploads/2015/09/python-3-in-one-pic.png) - [**Awesome Python**](https://github.com/vinta/awesome-python) - [**Jargon from the functional programming world in simple terms!**](https://github.com/hemanth/functional-programming-jargon) @@ -24,7 +25,7 @@ - [Python Scripting Tutorial](http://www.dreamsyssoft.com/python-scripting-tutorial/intro-tutorial.php) - [Scripting with Python](https://www.schrodinger.com//AcrobatFile.php?type=supportdocs&type2=&ident=404) - [**Can I use Python as a bash replacement?**](http://stackoverflow.com/questions/209470/can-i-use-python-as-a-bash-replacement) - +- [Classic Computer Scinece Problems in Python](https://www.manning.com/books/classic-computer-science-problems-in-python) ## Useful Online Courses - [Learn Python (Codecademy)](https://www.codecademy.com/learn/python#) - [Free Interactive Course: Intro to Python for Data Science (DataCamp)](https://www.datacamp.com/courses/intro-to-python-for-data-science) @@ -178,6 +179,7 @@ - [Unbalanced classification using RandomForestClassifier in sklearn](http://stackoverflow.com/questions/20082674/unbalanced-classification-using-randomforestclassifier-in-sklearn) - [Random Forest with categorical features in sklearn](http://stackoverflow.com/questions/24715230/random-forest-with-categorical-features-in-sklearn) - [How to output RandomForest Classifier from python?](http://stackoverflow.com/questions/23000693/how-to-output-randomforest-classifier-from-python) +- [DataCamp Python Tutorial with Random Forests](https://www.datacamp.com/courses/kaggle-python-tutorial-on-machine-learning) - [Lesson notebook: Ensembling, Bagging, and Random Forests](http://nbviewer.jupyter.org/github/justmarkham/DAT8/blob/master/notebooks/18_ensembling.ipynb) ## Support Vector Machine in Python @@ -189,7 +191,44 @@ - [Linear SVC Machine learning SVM example with Python](https://pythonprogramming.net/linear-svc-example-scikit-learn-svm-python/) - [Understanding Support Vector Machine algorithm from examples (along with code)](http://www.analyticsvidhya.com/blog/2015/10/understaing-support-vector-machine-example-code/) -## NLP / Text Mining in Python + +##Data Science with Python +- [awesome-python](https://github.com/vinta/awesome-python) +- [Intro to Python for Data Science](https://www.datacamp.com/courses/intro-to-python-for-data-science) +- [Python for Data Science: Basic Concepts](https://github.com/gumption/Python_for_Data_Science/blob/master/2_Data_Science_Basic_Concepts.ipynb) +- [Pycon India 2015 Notes](http://www.analyticsvidhya.com/blog/2015/10/notes-impressions-experience-excitement-pycon-india-2015/) +- [**5 important Python Data Science advancements of 2015**](https://medium.com/@elgehelge/the-5-most-important-python-data-science-advancements-of-2015-a136482da89b#.sp2c1la9z) +- [Data Exploration with Numpy cheat sheet](http://www.analyticsvidhya.com/blog/2015/07/11-steps-perform-data-analysis-pandas-python) +- [Querying Craiglist with Python](http://chrisholdgraf.com/querying-craigslist-with-python/?imm_mid=0d8940&cmp=em-data-na-na-newsltr_20150916) +- [**An introduction to Numpy and Scipy**](http://www.engr.ucsb.edu/~shell/che210d/numpy.pdf) +- [Create NBA Shot Charts](http://savvastjortjoglou.com/nba-shot-sharts.html) +- [PythoR- Python meets R](http://nipunbatra.github.io/2016/01/pythor/) +- [**How do I learn data analysis with Python?**](https://www.quora.com/How-do-I-learn-data-analysis-with-Python?redirected_qid=2464720) +- [What are some interesting things to do with Python?](https://www.quora.com/Python-programming-language-What-are-some-interesting-things-to-do-with-Python?redirected_qid=2324227) +- [**Which is better for data analysis: R or Python?**](https://www.quora.com/Which-is-better-for-data-analysis-R-or-Python) +- [**Web scraping in Python**](https://github.com/ujjwalkarn/Web-Scraping) + +##Pandas Library in Python +- [Intro to pandas data structures](http://www.gregreda.com/2013/10/26/intro-to-pandas-data-structures/) +- [10 minutes to Pandas](http://pandas.pydata.org/pandas-docs/stable/10min.html) +- [Timeseries analysis using Pandas](http://nbviewer.jupyter.org/github/twiecki/financial-analysis-python-tutorial/blob/master/1.%20Pandas%20Basics.ipynb) +- [**“Large data” work flows using pandas**](http://stackoverflow.com/questions/14262433/large-data-work-flows-using-pandas) +- Quick Operations on a Pandas DataFrame + - [Renaming Columns in Pandas](http://stackoverflow.com/questions/11346283/renaming-columns-in-pandas) + - [Deleting Columns from pandas DataFrame](http://stackoverflow.com/questions/13411544/delete-column-from-pandas-dataframe) + - [Adding new Column to existing DataFrame](http://stackoverflow.com/questions/12555323/adding-new-column-to-existing-dataframe-in-python-pandas) + - [Add one Row in a pandas.DataFrame](http://stackoverflow.com/questions/10715965/add-one-row-in-a-pandas-dataframe) + - [Changing the order of DataFrame Columns](http://stackoverflow.com/questions/13148429/how-to-change-the-order-of-dataframe-columns) + - [Changing data type of Columns](http://stackoverflow.com/questions/15891038/pandas-change-data-type-of-columns) + - [Getting a list of the column headers from a DataFrame](http://stackoverflow.com/questions/19482970/get-list-from-pandas-dataframe-column-headers) + - [Converting list of dictionaries to Dataframe](http://stackoverflow.com/questions/20638006/convert-list-of-dictionaries-to-dataframe) + - [Getting row count of pandas DataFrame](http://stackoverflow.com/questions/15943769/how-to-get-row-count-of-pandas-dataframe) + - [Most efficient way to loop through DataFrames](http://stackoverflow.com/questions/7837722/what-is-the-most-efficient-way-to-loop-through-dataframes-with-pandas) + - [Deleting DataFrame row based on column value](http://stackoverflow.com/questions/18172851/deleting-dataframe-row-in-pandas-based-on-column-value) + - [Dropping a list of rows from Pandas DataFrame](http://stackoverflow.com/questions/14661701/how-to-drop-a-list-of-rows-from-pandas-dataframe) + + +##Text Mining in Python - [**NLP with Python ORiley Book**](http://www.nltk.org/book_1ed/), [Python 3](http://www.nltk.org/book/) - [Awesome Python - NLP](https://github.com/vinta/awesome-python#natural-language-processing) - [Awesome Python - Text Processing](https://github.com/vinta/awesome-python#text-processing) @@ -205,12 +244,14 @@ - [Twitter-Sentiment-Analysis](https://github.com/ujjwalkarn/Twitter-Sentiment-Analysis) - [Basic Sentiment Analysis with Python](http://fjavieralba.com/basic-sentiment-analysis-with-python.html) - [What is the best way to do Sentiment Analysis with Python?](https://www.quora.com/What-is-the-best-way-to-do-Sentiment-Analysis-with-Python-1) +- [Creating a sentiment analysis model with Scrapy and MonkeyLearn](https://monkeylearn.com/blog/creating-sentiment-analysis-model-with-scrapy/) - [How to Calculate Twitter Sentiment Using AlchemyAPI with Python](http://www.alchemyapi.com/developers/getting-started-guide/twitter-sentiment-analysis) - [Second Try: Sentiment Analysis in Python](http://andybromberg.com/sentiment-analysis-python/) - [Sentiment Analysis with Python NLTK Text Classification](http://text-processing.com/demo/sentiment/) - Codes and Explanation - [**Sentiment Analysis with bag-of-words**](http://ataspinar.com/2016/01/21/sentiment-analysis-with-bag-of-words/) - [**Sentiment Analysis with Naive Bayes**](http://ataspinar.com/2016/02/15/sentiment-analysis-with-the-naive-bayes-classifier/) +- [A comprehensive guide to Sentiment Analysis](https://monkeylearn.com/sentiment-analysis/) ## Pickle: convert a python object into a character stream - [Python serialization - Why pickle?](http://stackoverflow.com/questions/8968884/python-serialization-why-pickle) @@ -247,3 +288,6 @@ - [python github projects - Collect and classify python projects on Github](https://github.com/checkcheckzz/python-github-projects) - [python reference - Useful functions, tutorials, and other Python-related things](https://github.com/rasbt/python_reference) - [pythonidae - Curated decibans of scientific programming resources in Python](https://github.com/svaksha/pythonidae) + +##Azure Machine Learning with HDInsight +- [**How to use Python components in an Apache Storm topology on HDInsight**](https://github.com/Azure-Samples/hdinsight-python-storm-wordcount) diff --git a/basic_commands.py b/basic_commands.py index 8c401fc..33c674a 100644 --- a/basic_commands.py +++ b/basic_commands.py @@ -10,7 +10,7 @@ -#convert a list to string: +#convert a list to string:yes list1 = ['1', '2', '3'] str1 = ''.join(list1) diff --git a/intro_to_sparse_data_and_embeddings.ipynb b/intro_to_sparse_data_and_embeddings.ipynb new file mode 100644 index 0000000..e43d0b2 --- /dev/null +++ b/intro_to_sparse_data_and_embeddings.ipynb @@ -0,0 +1,907 @@ +{ + "nbformat": 4, + "nbformat_minor": 0, + "metadata": { + "colab": { + "name": "intro_to_sparse_data_and_embeddings.ipynb", + "version": "0.3.2", + "provenance": [], + "collapsed_sections": [ + "JndnmDMp66FL", + "mNCLhxsXyOIS", + "eQS5KQzBybTY" + ], + "include_colab_link": true + }, + "kernelspec": { + "name": "python2", + "display_name": "Python 2" + } + }, + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "view-in-github", + "colab_type": "text" + }, + "source": [ + "\"Open" + ] + }, + { + "metadata": { + "id": "JndnmDMp66FL", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "#### Copyright 2017 Google LLC." + ] + }, + { + "metadata": { + "id": "hMqWDc_m6rUC", + "colab_type": "code", + "cellView": "both", + "colab": {} + }, + "cell_type": "code", + "source": [ + "# Licensed under the Apache License, Version 2.0 (the \"License\");\n", + "# you may not use this file except in compliance with the License.\n", + "# You may obtain a copy of the License at\n", + "#\n", + "# https://www.apache.org/licenses/LICENSE-2.0\n", + "#\n", + "# Unless required by applicable law or agreed to in writing, software\n", + "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", + "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", + "# See the License for the specific language governing permissions and\n", + "# limitations under the License." + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "PTaAdgy3LS8W", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "# Intro to Sparse Data and Embeddings\n", + "\n", + "**Learning Objectives:**\n", + "* Convert movie-review string data to a sparse feature vector\n", + "* Implement a sentiment-analysis linear model using a sparse feature vector\n", + "* Implement a sentiment-analysis DNN model using an embedding that projects data into two dimensions\n", + "* Visualize the embedding to see what the model has learned about the relationships between words\n", + "\n", + "In this exercise, we'll explore sparse data and work with embeddings using text data from movie reviews (from the [ACL 2011 IMDB dataset](http://ai.stanford.edu/~amaas/data/sentiment/)). This data has already been processed into `tf.Example` format. " + ] + }, + { + "metadata": { + "id": "2AKGtmwNosU8", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "## Setup\n", + "\n", + "Let's import our dependencies and download the training and test data. [`tf.keras`](https://www.tensorflow.org/api_docs/python/tf/keras) includes a file download and caching tool that we can use to retrieve the data sets." + ] + }, + { + "metadata": { + "id": "jGWqDqFFL_NZ", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "from __future__ import print_function\n", + "\n", + "import collections\n", + "import io\n", + "import math\n", + "\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "import pandas as pd\n", + "import tensorflow as tf\n", + "from IPython import display\n", + "from sklearn import metrics\n", + "\n", + "tf.logging.set_verbosity(tf.logging.ERROR)\n", + "train_url = 'https://download.mlcc.google.com/mledu-datasets/sparse-data-embedding/train.tfrecord'\n", + "train_path = tf.keras.utils.get_file(train_url.split('/')[-1], train_url)\n", + "test_url = 'https://download.mlcc.google.com/mledu-datasets/sparse-data-embedding/test.tfrecord'\n", + "test_path = tf.keras.utils.get_file(test_url.split('/')[-1], test_url)" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "6W7aZ9qspZVj", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "## Building a Sentiment Analysis Model" + ] + }, + { + "metadata": { + "id": "jieA0k_NLS8a", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "Let's train a sentiment-analysis model on this data that predicts if a review is generally *favorable* (label of 1) or *unfavorable* (label of 0).\n", + "\n", + "To do so, we'll turn our string-value `terms` into feature vectors by using a *vocabulary*, a list of each term we expect to see in our data. For the purposes of this exercise, we've created a small vocabulary that focuses on a limited set of terms. Most of these terms were found to be strongly indicative of *favorable* or *unfavorable*, but some were just added because they're interesting.\n", + "\n", + "Each term in the vocabulary is mapped to a coordinate in our feature vector. To convert the string-value `terms` for an example into this vector format, we encode such that each coordinate gets a value of 0 if the vocabulary term does not appear in the example string, and a value of 1 if it does. Terms in an example that don't appear in the vocabulary are thrown away." + ] + }, + { + "metadata": { + "id": "2HSfklfnLS8b", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "**NOTE:** *We could of course use a larger vocabulary, and there are special tools for creating these. In addition, instead of just dropping terms that are not in the vocabulary, we can introduce a small number of OOV (out-of-vocabulary) buckets to which you can hash the terms not in the vocabulary. We can also use a __feature hashing__ approach that hashes each term, instead of creating an explicit vocabulary. This works well in practice, but loses interpretability, which is useful for this exercise. See the tf.feature_column module for tools handling this.*" + ] + }, + { + "metadata": { + "id": "Uvoa2HyDtgqe", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "## Building the Input Pipeline" + ] + }, + { + "metadata": { + "id": "O20vMEOurDol", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "First, let's configure the input pipeline to import our data into a TensorFlow model. We can use the following function to parse the training and test data (which is in [TFRecord](https://www.tensorflow.org/guide/datasets#consuming_tfrecord_data) format) and return a dict of the features and the corresponding labels." + ] + }, + { + "metadata": { + "id": "SxxNIEniPq2z", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "def _parse_function(record):\n", + " \"\"\"Extracts features and labels.\n", + " \n", + " Args:\n", + " record: File path to a TFRecord file \n", + " Returns:\n", + " A `tuple` `(labels, features)`:\n", + " features: A dict of tensors representing the features\n", + " labels: A tensor with the corresponding labels.\n", + " \"\"\"\n", + " features = {\n", + " \"terms\": tf.VarLenFeature(dtype=tf.string), # terms are strings of varying lengths\n", + " \"labels\": tf.FixedLenFeature(shape=[1], dtype=tf.float32) # labels are 0 or 1\n", + " }\n", + " \n", + " parsed_features = tf.parse_single_example(record, features)\n", + " \n", + " terms = parsed_features['terms'].values\n", + " labels = parsed_features['labels']\n", + "\n", + " return {'terms':terms}, labels" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "SXhTeeYMrp-l", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "To confirm our function is working as expected, let's construct a `TFRecordDataset` for the training data, and map the data to features and labels using the function above." + ] + }, + { + "metadata": { + "id": "oF4YWXR0Omt0", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "# Create the Dataset object.\n", + "ds = tf.data.TFRecordDataset(train_path)\n", + "# Map features and labels with the parse function.\n", + "ds = ds.map(_parse_function)\n", + "\n", + "ds" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "bUoMvK-9tVXP", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "Run the following cell to retrieve the first example from the training data set." + ] + }, + { + "metadata": { + "id": "Z6QE2DWRUc4E", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "n = ds.make_one_shot_iterator().get_next()\n", + "sess = tf.Session()\n", + "sess.run(n)" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "jBU39UeFty9S", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "Now, let's build a formal input function that we can pass to the `train()` method of a TensorFlow Estimator object." + ] + }, + { + "metadata": { + "id": "5_C5-ueNYIn_", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "# Create an input_fn that parses the tf.Examples from the given files,\n", + "# and split them into features and targets.\n", + "def _input_fn(input_filenames, num_epochs=None, shuffle=True):\n", + " \n", + " # Same code as above; create a dataset and map features and labels.\n", + " ds = tf.data.TFRecordDataset(input_filenames)\n", + " ds = ds.map(_parse_function)\n", + "\n", + " if shuffle:\n", + " ds = ds.shuffle(10000)\n", + "\n", + " # Our feature data is variable-length, so we pad and batch\n", + " # each field of the dataset structure to whatever size is necessary.\n", + " ds = ds.padded_batch(25, ds.output_shapes)\n", + " \n", + " ds = ds.repeat(num_epochs)\n", + "\n", + " \n", + " # Return the next batch of data.\n", + " features, labels = ds.make_one_shot_iterator().get_next()\n", + " return features, labels" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "Y170tVlrLS8c", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "## Task 1: Use a Linear Model with Sparse Inputs and an Explicit Vocabulary\n", + "\n", + "For our first model, we'll build a [`LinearClassifier`](https://www.tensorflow.org/api_docs/python/tf/estimator/LinearClassifier) model using 50 informative terms; always start simple!\n", + "\n", + "The following code constructs the feature column for our terms. The [`categorical_column_with_vocabulary_list`](https://www.tensorflow.org/api_docs/python/tf/feature_column/categorical_column_with_vocabulary_list) function creates a feature column with the string-to-feature-vector mapping." + ] + }, + { + "metadata": { + "id": "B5gdxuWsvPcx", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "# 50 informative terms that compose our model vocabulary \n", + "informative_terms = (\"bad\", \"great\", \"best\", \"worst\", \"fun\", \"beautiful\",\n", + " \"excellent\", \"poor\", \"boring\", \"awful\", \"terrible\",\n", + " \"definitely\", \"perfect\", \"liked\", \"worse\", \"waste\",\n", + " \"entertaining\", \"loved\", \"unfortunately\", \"amazing\",\n", + " \"enjoyed\", \"favorite\", \"horrible\", \"brilliant\", \"highly\",\n", + " \"simple\", \"annoying\", \"today\", \"hilarious\", \"enjoyable\",\n", + " \"dull\", \"fantastic\", \"poorly\", \"fails\", \"disappointing\",\n", + " \"disappointment\", \"not\", \"him\", \"her\", \"good\", \"time\",\n", + " \"?\", \".\", \"!\", \"movie\", \"film\", \"action\", \"comedy\",\n", + " \"drama\", \"family\")\n", + "\n", + "terms_feature_column = tf.feature_column.categorical_column_with_vocabulary_list(key=\"terms\", vocabulary_list=informative_terms)" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "eTiDwyorwd3P", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "Next, we'll construct the `LinearClassifier`, train it on the training set, and evaluate it on the evaluation set. After you read through the code, run it and see how you do." + ] + }, + { + "metadata": { + "id": "HYKKpGLqLS8d", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "my_optimizer = tf.train.AdagradOptimizer(learning_rate=0.1)\n", + "my_optimizer = tf.contrib.estimator.clip_gradients_by_norm(my_optimizer, 5.0)\n", + "\n", + "feature_columns = [ terms_feature_column ]\n", + "\n", + "\n", + "classifier = tf.estimator.LinearClassifier(\n", + " feature_columns=feature_columns,\n", + " optimizer=my_optimizer,\n", + ")\n", + "\n", + "classifier.train(\n", + " input_fn=lambda: _input_fn([train_path]),\n", + " steps=1000)\n", + "\n", + "evaluation_metrics = classifier.evaluate(\n", + " input_fn=lambda: _input_fn([train_path]),\n", + " steps=1000)\n", + "print(\"Training set metrics:\")\n", + "for m in evaluation_metrics:\n", + " print(m, evaluation_metrics[m])\n", + "print(\"---\")\n", + "\n", + "evaluation_metrics = classifier.evaluate(\n", + " input_fn=lambda: _input_fn([test_path]),\n", + " steps=1000)\n", + "\n", + "print(\"Test set metrics:\")\n", + "for m in evaluation_metrics:\n", + " print(m, evaluation_metrics[m])\n", + "print(\"---\")" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "J0ubn9gULS8g", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "## Task 2: Use a Deep Neural Network (DNN) Model\n", + "\n", + "The above model is a linear model. It works quite well. But can we do better with a DNN model?\n", + "\n", + "Let's swap in a [`DNNClassifier`](https://www.tensorflow.org/api_docs/python/tf/estimator/DNNClassifier) for the `LinearClassifier`. Run the following cell, and see how you do." + ] + }, + { + "metadata": { + "id": "jcgOPfEALS8h", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "##################### Here's what we changed ##################################\n", + "classifier = tf.estimator.DNNClassifier( #\n", + " feature_columns=[tf.feature_column.indicator_column(terms_feature_column)], #\n", + " hidden_units=[20,20], #\n", + " optimizer=my_optimizer, #\n", + ") #\n", + "###############################################################################\n", + "\n", + "try:\n", + " classifier.train(\n", + " input_fn=lambda: _input_fn([train_path]),\n", + " steps=1000)\n", + "\n", + " evaluation_metrics = classifier.evaluate(\n", + " input_fn=lambda: _input_fn([train_path]),\n", + " steps=1)\n", + " print(\"Training set metrics:\")\n", + " for m in evaluation_metrics:\n", + " print(m, evaluation_metrics[m])\n", + " print(\"---\")\n", + "\n", + " evaluation_metrics = classifier.evaluate(\n", + " input_fn=lambda: _input_fn([test_path]),\n", + " steps=1)\n", + "\n", + " print(\"Test set metrics:\")\n", + " for m in evaluation_metrics:\n", + " print(m, evaluation_metrics[m])\n", + " print(\"---\")\n", + "except ValueError as err:\n", + " print(err)" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "cZz68luxLS8j", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "## Task 3: Use an Embedding with a DNN Model\n", + "\n", + "In this task, we'll implement our DNN model using an embedding column. An embedding column takes sparse data as input and returns a lower-dimensional dense vector as output." + ] + }, + { + "metadata": { + "id": "AliRzhvJLS8k", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "**NOTE:** *An embedding_column is usually the computationally most efficient option to use for training a model on sparse data. In an [optional section](#scrollTo=XDMlGgRfKSVz) at the end of this exercise, we'll discuss in more depth the implementational differences between using an `embedding_column` and an `indicator_column`, and the tradeoffs of selecting one over the other.*" + ] + }, + { + "metadata": { + "id": "F-as3PtALS8l", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "In the following code, do the following:\n", + "\n", + "* Define the feature columns for the model using an `embedding_column` that projects the data into 2 dimensions (see the [TF docs](https://www.tensorflow.org/api_docs/python/tf/feature_column/embedding_column) for more details on the function signature for `embedding_column`).\n", + "* Define a `DNNClassifier` with the following specifications:\n", + " * Two hidden layers of 20 units each\n", + " * Adagrad optimization with a learning rate of 0.1\n", + " * A `gradient_clip_norm` of 5.0" + ] + }, + { + "metadata": { + "id": "UlPZ-Q9bLS8m", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "**NOTE:** *In practice, we might project to dimensions higher than 2, like 50 or 100. But for now, 2 dimensions is easy to visualize.*" + ] + }, + { + "metadata": { + "id": "mNCLhxsXyOIS", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "### Hint" + ] + }, + { + "metadata": { + "id": "L67xYD7hLS8m", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "# Here's a example code snippet you might use to define the feature columns:\n", + "\n", + "terms_embedding_column = tf.feature_column.embedding_column(terms_feature_column, dimension=2)\n", + "feature_columns = [ terms_embedding_column ]" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "iv1UBsJxyV37", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "### Complete the Code Below" + ] + }, + { + "metadata": { + "id": "5PG_yhNGLS8u", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "########################## YOUR CODE HERE ######################################\n", + "terms_embedding_column = # Define the embedding column\n", + "feature_columns = # Define the feature columns\n", + "\n", + "classifier = # Define the DNNClassifier\n", + "################################################################################\n", + "\n", + "classifier.train(\n", + " input_fn=lambda: _input_fn([train_path]),\n", + " steps=1000)\n", + "\n", + "evaluation_metrics = classifier.evaluate(\n", + " input_fn=lambda: _input_fn([train_path]),\n", + " steps=1000)\n", + "print(\"Training set metrics:\")\n", + "for m in evaluation_metrics:\n", + " print(m, evaluation_metrics[m])\n", + "print(\"---\")\n", + "\n", + "evaluation_metrics = classifier.evaluate(\n", + " input_fn=lambda: _input_fn([test_path]),\n", + " steps=1000)\n", + "\n", + "print(\"Test set metrics:\")\n", + "for m in evaluation_metrics:\n", + " print(m, evaluation_metrics[m])\n", + "print(\"---\")" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "eQS5KQzBybTY", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "### Solution\n", + "\n", + "Click below for a solution." + ] + }, + { + "metadata": { + "id": "R5xOdYeQydi5", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "########################## SOLUTION CODE ########################################\n", + "terms_embedding_column = tf.feature_column.embedding_column(terms_feature_column, dimension=2)\n", + "feature_columns = [ terms_embedding_column ]\n", + "\n", + "my_optimizer = tf.train.AdagradOptimizer(learning_rate=0.1)\n", + "my_optimizer = tf.contrib.estimator.clip_gradients_by_norm(my_optimizer, 5.0)\n", + "\n", + "classifier = tf.estimator.DNNClassifier(\n", + " feature_columns=feature_columns,\n", + " hidden_units=[20,20],\n", + " optimizer=my_optimizer\n", + ")\n", + "#################################################################################\n", + "\n", + "classifier.train(\n", + " input_fn=lambda: _input_fn([train_path]),\n", + " steps=1000)\n", + "\n", + "evaluation_metrics = classifier.evaluate(\n", + " input_fn=lambda: _input_fn([train_path]),\n", + " steps=1000)\n", + "print(\"Training set metrics:\")\n", + "for m in evaluation_metrics:\n", + " print(m, evaluation_metrics[m])\n", + "print(\"---\")\n", + "\n", + "evaluation_metrics = classifier.evaluate(\n", + " input_fn=lambda: _input_fn([test_path]),\n", + " steps=1000)\n", + "\n", + "print(\"Test set metrics:\")\n", + "for m in evaluation_metrics:\n", + " print(m, evaluation_metrics[m])\n", + "print(\"---\")" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "aiHnnVtzLS8w", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "## Task 4: Convince yourself there's actually an embedding in there\n", + "\n", + "The above model used an `embedding_column`, and it seemed to work, but this doesn't tell us much about what's going on internally. How can we check that the model is actually using an embedding inside?\n", + "\n", + "To start, let's look at the tensors in the model:" + ] + }, + { + "metadata": { + "id": "h1jNgLdQLS8w", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "classifier.get_variable_names()" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "Sl4-VctMLS8z", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "Okay, we can see that there is an embedding layer in there: `'dnn/input_from_feature_columns/input_layer/terms_embedding/...'`. (What's interesting here, by the way, is that this layer is trainable along with the rest of the model just as any hidden layer is.)\n", + "\n", + "Is the embedding layer the correct shape? Run the following code to find out." + ] + }, + { + "metadata": { + "id": "JNFxyQUiLS80", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "**NOTE:** *Remember, in our case, the embedding is a matrix that allows us to project a 50-dimensional vector down to 2 dimensions.*" + ] + }, + { + "metadata": { + "id": "1xMbpcEjLS80", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "classifier.get_variable_value('dnn/input_from_feature_columns/input_layer/terms_embedding/embedding_weights').shape" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "MnLCIogjLS82", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "Spend some time manually checking the various layers and shapes to make sure everything is connected the way you would expect it would be." + ] + }, + { + "metadata": { + "id": "rkKAaRWDLS83", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "## Task 5: Examine the Embedding\n", + "\n", + "Let's now take a look at the actual embedding space, and see where the terms end up in it. Do the following:\n", + "1. Run the following code to see the embedding we trained in **Task 3**. Do things end up where you'd expect?\n", + "\n", + "2. Re-train the model by rerunning the code in **Task 3**, and then run the embedding visualization below again. What stays the same? What changes?\n", + "\n", + "3. Finally, re-train the model again using only 10 steps (which will yield a terrible model). Run the embedding visualization below again. What do you see now, and why?" + ] + }, + { + "metadata": { + "id": "s4NNu7KqLS84", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "\n", + "embedding_matrix = classifier.get_variable_value('dnn/input_from_feature_columns/input_layer/terms_embedding/embedding_weights')\n", + "\n", + "for term_index in range(len(informative_terms)):\n", + " # Create a one-hot encoding for our term. It has 0s everywhere, except for\n", + " # a single 1 in the coordinate that corresponds to that term.\n", + " term_vector = np.zeros(len(informative_terms))\n", + " term_vector[term_index] = 1\n", + " # We'll now project that one-hot vector into the embedding space.\n", + " embedding_xy = np.matmul(term_vector, embedding_matrix)\n", + " plt.text(embedding_xy[0],\n", + " embedding_xy[1],\n", + " informative_terms[term_index])\n", + "\n", + "# Do a little setup to make sure the plot displays nicely.\n", + "plt.rcParams[\"figure.figsize\"] = (15, 15)\n", + "plt.xlim(1.2 * embedding_matrix.min(), 1.2 * embedding_matrix.max())\n", + "plt.ylim(1.2 * embedding_matrix.min(), 1.2 * embedding_matrix.max())\n", + "plt.show() " + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "pUb3L7pqLS86", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "## Task 6: Try to improve the model's performance\n", + "\n", + "See if you can refine the model to improve performance. A couple things you may want to try:\n", + "\n", + "* **Changing hyperparameters**, or **using a different optimizer** like Adam (you may only gain one or two accuracy percentage points following these strategies).\n", + "* **Adding additional terms to `informative_terms`.** There's a full vocabulary file with all 30,716 terms for this data set that you can use at: https://download.mlcc.google.com/mledu-datasets/sparse-data-embedding/terms.txt You can pick out additional terms from this vocabulary file, or use the whole thing via the `categorical_column_with_vocabulary_file` feature column." + ] + }, + { + "metadata": { + "id": "6-b3BqXvLS86", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "# Download the vocabulary file.\n", + "terms_url = 'https://download.mlcc.google.com/mledu-datasets/sparse-data-embedding/terms.txt'\n", + "terms_path = tf.keras.utils.get_file(terms_url.split('/')[-1], terms_url)" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "0jbJlwW5LS8-", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "# Create a feature column from \"terms\", using a full vocabulary file.\n", + "informative_terms = None\n", + "with io.open(terms_path, 'r', encoding='utf8') as f:\n", + " # Convert it to a set first to remove duplicates.\n", + " informative_terms = list(set(f.read().split()))\n", + " \n", + "terms_feature_column = tf.feature_column.categorical_column_with_vocabulary_list(key=\"terms\", \n", + " vocabulary_list=informative_terms)\n", + "\n", + "terms_embedding_column = tf.feature_column.embedding_column(terms_feature_column, dimension=2)\n", + "feature_columns = [ terms_embedding_column ]\n", + "\n", + "my_optimizer = tf.train.AdagradOptimizer(learning_rate=0.1)\n", + "my_optimizer = tf.contrib.estimator.clip_gradients_by_norm(my_optimizer, 5.0)\n", + "\n", + "classifier = tf.estimator.DNNClassifier(\n", + " feature_columns=feature_columns,\n", + " hidden_units=[10,10],\n", + " optimizer=my_optimizer\n", + ")\n", + "\n", + "classifier.train(\n", + " input_fn=lambda: _input_fn([train_path]),\n", + " steps=1000)\n", + "\n", + "evaluation_metrics = classifier.evaluate(\n", + " input_fn=lambda: _input_fn([train_path]),\n", + " steps=1000)\n", + "print(\"Training set metrics:\")\n", + "for m in evaluation_metrics:\n", + " print(m, evaluation_metrics[m])\n", + "print(\"---\")\n", + "\n", + "evaluation_metrics = classifier.evaluate(\n", + " input_fn=lambda: _input_fn([test_path]),\n", + " steps=1000)\n", + "\n", + "print(\"Test set metrics:\")\n", + "for m in evaluation_metrics:\n", + " print(m, evaluation_metrics[m])\n", + "print(\"---\")" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "ew3kwGM-LS9B", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "## A Final Word\n", + "\n", + "We may have gotten a DNN solution with an embedding that was better than our original linear model, but the linear model was also pretty good and was quite a bit faster to train. Linear models train more quickly because they do not have nearly as many parameters to update or layers to backprop through.\n", + "\n", + "In some applications, the speed of linear models may be a game changer, or linear models may be perfectly sufficient from a quality standpoint. In other areas, the additional model complexity and capacity provided by DNNs might be more important. When defining your model architecture, remember to explore your problem sufficiently so that you know which space you're in." + ] + }, + { + "metadata": { + "id": "9MquXy9zLS9B", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "### *Optional Discussion:* Trade-offs between `embedding_column` and `indicator_column`\n", + "\n", + "Conceptually when training a `LinearClassifier` or a `DNNClassifier`, there is an adapter needed to use a sparse column. TF provides two options: `embedding_column` or `indicator_column`.\n", + "\n", + "When training a LinearClassifier (as in **Task 1**), an `embedding_column` in used under the hood. As seen in **Task 2**, when training a `DNNClassifier`, you must explicitly choose either `embedding_column` or `indicator_column`. This section discusses the distinction between the two, and the trade-offs of using one over the other, by looking at a simple example." + ] + }, + { + "metadata": { + "id": "M_3XuZ_LLS9C", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "Suppose we have sparse data containing the values `\"great\"`, `\"beautiful\"`, `\"excellent\"`. Since the vocabulary size we're using here is $V = 50$, each unit (neuron) in the first layer will have 50 weights. We denote the number of terms in a sparse input using $s$. So for this example sparse data, $s = 3$. For an input layer with $V$ possible values, a hidden layer with $d$ units needs to do a vector-matrix multiply: $(1 \\times V) * (V \\times d)$. This has $O(V * d)$ computational cost. Note that this cost is proportional to the number of weights in that hidden layer and independent of $s$.\n", + "\n", + "If the inputs are one-hot encoded (a Boolean vector of length $V$ with a 1 for the terms present and a 0 for the rest) using an [`indicator_column`](https://www.tensorflow.org/api_docs/python/tf/feature_column/indicator_column), this means multiplying and adding a lot of zeros." + ] + }, + { + "metadata": { + "id": "I7mR4Wa2LS9C", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "When we achieve the exact same results by using an [`embedding_column`](https://www.tensorflow.org/api_docs/python/tf/feature_column/embedding_column) of size $d$, we look up and add up just the embeddings corresponding to the three features present in our example input of \"`great`\", \"`beautiful`\", \"`excellent`\": $(1 \\times d) + (1 \\times d) + (1 \\times d)$. Since the weights for the features that are absent are multiplied by zero in the vector-matrix multiply, they do not contribute to the result. Weights for the features that are present are multiplied by 1 in the vector-matrix multiply. Thus, adding the weights obtained via the embedding lookup will lead to the same result as in the vector-matrix-multiply.\n", + "\n", + "When using an embedding, computing the embedding lookup is an $O(s * d)$ computation, which is computationally much more efficient than the $O(V * d)$ cost for the `indicator_column` in sparse data for which $s$ is much smaller than $V$. (Remember, these embeddings are being learned. In any given training iteration it is the current weights that are being looked up.)" + ] + }, + { + "metadata": { + "id": "etZ9qf0kLS9D", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "As we saw in **Task 3**, by using an `embedding_column` in training the `DNNClassifier`, our model learns a low-dimensional representation for the features, where the dot product defines a similarity metric tailored to the desired task. In this example, terms that are used similarly in the context of movie reviews (e.g., `\"great\"` and `\"excellent\"`) will be closer to each other the embedding space (i.e., have a large dot product), and terms that are dissimilar (e.g., `\"great\"` and `\"bad\"`) will be farther away from each other in the embedding space (i.e., have a small dot product)." + ] + } + ] +} \ No newline at end of file diff --git a/mock_bank_data_original.csv b/mock_bank_data_original.csv new file mode 100644 index 0000000..cc8be54 --- /dev/null +++ b/mock_bank_data_original.csv @@ -0,0 +1,1001 @@ +customer_id,name,email,sex,age,state,cheq_balance,savings_balance,credit_score,special_offer +1,Joe Saltmarshe,jsaltmarshe0@cornell.edu,Female,10,FL,7342.26,5482.87,774,TRUE +2,Ody Spadollini,ospadollini1@nationalgeographic.com,Female,14,CA,870.39,11823.74,770,TRUE +3,Barby Vardie,,Male,110,,3343.45,,583,FALSE +4,Klarika Jodrellec,kjodrellec3@1und1.de,Male,0,TX,3282.34,8564.79,605,TRUE +5,Teodora Pinkstone,tpinkstone4@huffingtonpost.com,Female,37,TX,4645.99,12826.76,608,TRUE +,Gilbertina Oddey,goddey5@ucoz.com,Male,,FL,,3493.08,551,FALSE +7,Pammi Castells,pcastells6@pinterest.com,Female,84,CA,7079.05,10845.24,826,FALSE +8,Mei Brumbie,,Male,100,CA,833.73,5229.49,559,FALSE +9,Janeta Corkitt,jcorkitt8@angelfire.com,,57,CA,,13752.86,572,TRUE +10,Kamila Campkin,,Male,,TX,7020.31,2244.34,577,TRUE +11,Isadore Lyosik,ilyosika@howstuffworks.com,Male,119,NY,8486.7,13782.01,598,TRUE +12,Evania Payler,epaylerb@bloglovin.com,Male,,CA,1062.2,16597,647,TRUE +13,Lynne Symington,lsymingtonc@dagondesign.com,,93,TX,2022.79,5392.63,633,FALSE +14,Edgar Gosalvez,,,11,TX,3410.03,7118.9,753,FALSE +15,Veronika MacFaul,vmacfaule@wikipedia.org,Male,74,FL,9353.93,19267.34,756,FALSE +16,Marcela O'Halligan,mohalliganf@github.io,Male,115,TX,9879.92,9171.9,698,FALSE +17,Fiorenze Shalcras,fshalcrasg@wufoo.com,Male,75,FL,7350.74,6870.81,625,FALSE +18,Troy Norree,tnorreeh@theglobeandmail.com,Female,37,FL,8894.22,16585.27,648,TRUE +19,Leah McAnalley,,Female,29,TX,8276.41,10042.24,757,TRUE +20,Artie Colthard,acolthardj@instagram.com,Female,40,FL,4795.99,15345.47,,FALSE +21,Clint Parradine,cparradinek@wordpress.org,Male,108,CA,3204.44,4153.18,723,FALSE +22,Saree Brooke,,Male,2,NY,1629.81,18647.78,789,FALSE +23,Thedrick Grgic,tgrgicm@ted.com,Female,98,TX,3378.08,18791.33,551,TRUE +24,Zacharias Downgate,zdowngaten@wikispaces.com,Male,85,CA,1189.22,2224.97,724,FALSE +25,Andreas Denisovich,adenisovicho@gnu.org,Male,,CA,4790.63,904.89,791,FALSE +26,Arden Dacca,adaccap@nymag.com,Female,83,CA,2815.76,3257.92,573,FALSE +27,Hobart Pikesley,hpikesleyq@google.fr,Female,63,CA,7876.68,11300.72,629,TRUE +28,Nil Pleaden,npleadenr@youku.com,Female,79,FL,7337.46,,697,FALSE +29,Marge Seine,mseines@surveymonkey.com,Male,,FL,4855.05,,770,TRUE +30,Stormi Goose,sgooset@ycombinator.com,Male,39,CA,1323.8,9942.7,673,TRUE +31,Aldridge Crawcour,,Female,96,TX,4124.35,4196.9,699,TRUE +32,Sheree MacAndie,smacandiev@mayoclinic.com,Female,42,TX,6195,12129.24,555,TRUE +33,Iolande Kinnard,,Male,119,NY,3072.57,4602.74,797,TRUE +34,Bartel McGannon,bmcgannonx@vinaora.com,Female,,TX,500.15,10284.84,687,TRUE +,Lilly Nelhams,lnelhamsy@unesco.org,Female,82,CA,9288.83,10897.04,727,FALSE +36,Guy Mattson,,Male,67,FL,3905.45,3502.53,638,FALSE +37,Dodi Ballam,,Female,70,TX,2813.97,6008.25,,FALSE +38,Allina Harvey,,Male,58,CA,2836.62,1255.74,644,FALSE +39,Dorine Feedome,dfeedome12@digg.com,Male,30,TX,601.36,16615.87,823,TRUE +40,Prinz Allan,pallan13@360.cn,Male,104,,2872.86,16269.79,794,TRUE +41,Montague Uccelli,muccelli14@mozilla.org,Female,,FL,6664.57,13784.71,667,FALSE +42,Lorita Metheringham,lmetheringham15@devhub.com,Female,27,CA,2090.05,15601.12,753,FALSE +43,Lewes McNab,lmcnab16@xinhuanet.com,Male,66,TX,1662.23,4134.51,680,FALSE +44,Papagena Wilds,pwilds17@umich.edu,Male,120,FL,9796.55,18958.4,,TRUE +45,Afton Brighty,abrighty18@spiegel.de,Female,20,CA,6433.37,6991.08,671,FALSE +46,Eachelle Gowenlock,,Female,107,FL,9249.48,14654.89,777,FALSE +47,Fredra Syrie,fsyrie1a@microsoft.com,Female,11,NY,5448.87,6126.31,810,TRUE +48,Phaedra Corstan,,Female,59,CA,230.04,12425.36,641,FALSE +49,Kippy Ambrose,kambrose1c@washingtonpost.com,Female,107,CA,9913.96,,603,FALSE +50,Mei Bernardez,,Female,80,FL,3533.27,7131.89,770,FALSE +51,Sabina Larner,slarner1e@youku.com,Female,113,CA,6121.26,11877.87,649,TRUE +52,Eduino Elia,eelia1f@reuters.com,Female,118,CA,3521.02,18851.79,629,FALSE +53,Aloise Whitters,awhitters1g@ebay.com,Male,6,NY,8839.2,12538.69,627,FALSE +54,Deloria Antowski,,Female,2,CA,3067.34,,609,TRUE +55,Rachel Possel,,,84,FL,6202.08,9519.08,759,TRUE +56,Imogen Fyfield,ifyfield1j@huffingtonpost.com,Female,61,CA,1115.01,14264.28,697,FALSE +57,Ned Basil,nbasil1k@answers.com,Female,32,NY,3528.42,15358.83,,TRUE +58,Cully Reville,creville1l@skype.com,Female,65,FL,3232.32,18454.22,694,FALSE +59,Isahella Childrens,ichildrens1m@tiny.cc,Female,50,FL,6908.78,15045.51,717,TRUE +60,Locke Beglin,,Female,66,NY,5279.55,6182.51,752,FALSE +61,Sofie Potkins,spotkins1o@engadget.com,Male,25,CA,7097.85,,674,FALSE +62,Dacey Forge,dforge1p@wsj.com,Female,13,FL,3289.87,7640.07,,FALSE +63,Kirk Popworth,kpopworth1q@is.gd,Male,79,FL,,627.06,694,FALSE +64,Manon MacLleese,mmaclleese1r@geocities.com,Male,20,CA,358.21,10945.28,584,TRUE +65,Modesta Cromley,mcromley1s@opensource.org,Female,,TX,7381.48,10973.58,658,FALSE +66,Milicent Webb-Bowen,mwebbbowen1t@macromedia.com,Female,12,FL,139.21,,826,FALSE +67,Rudolph Ketchaside,,Female,13,TX,6838.32,7775.94,693,FALSE +68,Bank Kivell,bkivell1v@gizmodo.com,,73,TX,7707.21,9930.01,550,TRUE +69,Hube Leydon,hleydon1w@biglobe.ne.jp,Female,98,CA,7605.87,12059.12,623,FALSE +70,Reeva Sully,rsully1x@who.int,Female,81,NY,7324.54,480.13,748,FALSE +71,Clifford Branni,cbranni1y@nba.com,Female,,CA,6939.83,16109.15,606,TRUE +72,Else Jozef,,Female,46,CA,2252.46,,561,FALSE +73,Berta Cussen,bcussen20@blog.com,Male,114,,9384.17,16681.12,769,TRUE +74,Cecilia Ransley,cransley21@4shared.com,Female,12,CA,7740.45,9903.68,671,TRUE +75,Becca Sogg,bsogg22@redcross.org,Female,109,FL,7877.37,4039.07,,TRUE +76,Nero Kipling,nkipling23@livejournal.com,Female,4,TX,4894.43,14261.1,,TRUE +77,Cyrill Surgison,csurgison24@tumblr.com,Female,,FL,295.59,601.83,776,TRUE +78,Franklin Crolly,,Female,24,FL,7100.55,7603.53,731,FALSE +79,Minda Simoneau,msimoneau26@1688.com,Female,85,FL,371.48,9710.72,805,TRUE +80,Elysia Filipic,efilipic27@gravatar.com,Female,67,NY,3419.99,,655,FALSE +81,Vite Jewks,,Male,103,FL,7181.24,13822.06,566,FALSE +82,Helge Hughland,hhughland29@loc.gov,Male,70,FL,6110.27,9740.99,673,FALSE +83,Kassia Yewen,kyewen2a@comcast.net,Female,76,TX,442.77,2665.81,824,FALSE +84,Vinny Grute,vgrute2b@washington.edu,Female,58,FL,5426.56,18283.66,,FALSE +85,Vivianna Cromly,vcromly2c@businessinsider.com,Male,32,FL,774.31,18748.08,774,FALSE +86,Pansy Duligal,pduligal2d@tinypic.com,Female,13,TX,6133.92,3029.89,824,FALSE +87,Dael Dmitrienko,ddmitrienko2e@macromedia.com,Female,49,TX,89.16,11484.86,753,TRUE +88,Rodger Punton,rpunton2f@auda.org.au,Male,95,TX,7709.38,3836.08,810,TRUE +89,Rikki Ridley,rridley2g@netvibes.com,Male,44,CA,1752.6,10706.5,620,FALSE +90,Ash Spadotto,aspadotto2h@istockphoto.com,Male,34,CA,4932.28,14670.79,602,FALSE +91,Colby Brecknell,,Male,8,TX,7287.8,,564,FALSE +92,Gusta France,,Male,27,TX,8091.06,3553.94,662,FALSE +93,Anastasie Kampshell,akampshell2k@rambler.ru,Male,117,FL,2039.81,13244.09,,FALSE +94,Torrance Rubens,,Female,30,FL,4169.36,4649.53,612,FALSE +95,Ossie Searjeant,osearjeant2m@ow.ly,Female,89,CA,7696.05,10669.34,683,FALSE +96,Lorin Iddiens,,,,CA,7739.53,18518.33,822,FALSE +97,Shaw Zuanazzi,szuanazzi2o@redcross.org,Female,95,FL,1224.62,8942.44,609,FALSE +98,Fan Hovert,fhovert2p@wisc.edu,Female,20,CA,4222.45,4151.27,708,FALSE +99,Adara Valenta,avalenta2q@discovery.com,Female,38,CA,4132.96,,657,FALSE +100,Frank Ziemecki,fziemecki2r@ucla.edu,Female,61,CA,7474.8,12791.8,656,TRUE +101,Lamont Langthorn,llangthorn2s@so-net.ne.jp,,2,CA,426.9,15419.89,649,FALSE +102,Bernadina Greenway,bgreenway2t@cocolog-nifty.com,Female,68,NY,1148.96,16678.25,574,TRUE +103,Des Sides,dsides2u@weebly.com,Male,,FL,6495.34,14101.88,724,TRUE +104,Gillian Hindmoor,ghindmoor2v@accuweather.com,Female,62,NY,7471.64,10932.64,614,TRUE +105,Adler Beaston,abeaston2w@bravesites.com,Female,95,CA,8848.69,9055.13,769,TRUE +106,Paulina Lachaize,plachaize2x@timesonline.co.uk,Male,49,FL,6039.49,14657.81,636,FALSE +107,Nomi Lippitt,nlippitt2y@harvard.edu,Female,79,FL,6239.81,8032.66,770,TRUE +108,Sherwynd Alcock,salcock2z@nhs.uk,Male,50,FL,6832.21,10341.51,680,TRUE +109,Lind Pither,lpither30@jigsy.com,Male,76,CA,7393.63,10188.44,568,FALSE +110,Gaspar Lukas,glukas31@zdnet.com,Male,81,TX,5209.87,4719.25,645,TRUE +111,Kirby Binestead,,Male,4,CA,5381.8,19328.07,596,TRUE +112,Terencio Allmen,tallmen33@paginegialle.it,Female,104,TX,3328.16,19236.68,,TRUE +113,Shell Hatherleigh,shatherleigh34@shinystat.com,Female,14,CA,5058.16,10858.21,728,TRUE +114,Arda Lilburn,,Male,86,CA,3418.02,16563.91,550,FALSE +115,Lazaro Took,ltook36@yolasite.com,,37,TX,4199.68,19500.27,672,FALSE +116,Stepha Dowda,sdowda37@merriam-webster.com,Male,11,NY,1967.23,18837.51,794,FALSE +117,Dulcine Valentim,dvalentim38@mit.edu,Female,111,TX,3910.37,4026.26,,FALSE +,Herold Jeness,hjeness39@hud.gov,Female,34,TX,2856.54,16352.89,,TRUE +119,Lock Biskupski,,Female,,FL,7073.32,31.96,720,TRUE +120,Gerrie Rudderham,grudderham3b@shop-pro.jp,Male,92,TX,7977.14,12861.66,629,FALSE +121,Lucien Borsay,lborsay3c@harvard.edu,Male,,TX,2861.5,12171.9,596,TRUE +122,Anastasie Kitlee,akitlee3d@xrea.com,Male,116,CA,846.74,8568.46,675,TRUE +123,Harwell Enion,henion3e@wikia.com,Male,88,CA,1646.66,17118.92,700,TRUE +124,Holly Tire,,Male,86,CA,8511.37,584.57,668,FALSE +125,Gasper Hawtin,ghawtin3g@nydailynews.com,Female,39,CA,4084.58,12288.13,654,FALSE +126,Nerti Standage,nstandage3h@wikimedia.org,Female,106,CA,7734.69,4600.08,567,TRUE +127,Krishna d' Eye,kd3i@squidoo.com,Female,3,CA,5247.97,10355.96,641,TRUE +128,Anet Minister,aminister3j@blogspot.com,Female,9,FL,606.95,4568.96,707,FALSE +129,Stacey Iacovo,siacovo3k@cpanel.net,Female,61,FL,9896.43,1223.61,677,FALSE +130,Alano MacRierie,amacrierie3l@cyberchimps.com,Female,,FL,2672.27,7524.29,651,FALSE +131,Tamas Gimert,tgimert3m@spiegel.de,Female,109,CA,5746.73,11234.34,693,FALSE +132,Fernande Glyssanne,fglyssanne3n@oaic.gov.au,Male,,,1388.4,19304.86,793,FALSE +133,Leland Fludgate,lfludgate3o@narod.ru,Female,62,FL,8094.85,6776.11,707,FALSE +134,Neda Saywood,nsaywood3p@lulu.com,Female,9,CA,2944.03,9486.09,786,FALSE +135,Wright Stanley,wstanley3q@fastcompany.com,Female,33,TX,2238.88,10977.42,759,FALSE +136,Andee Basilone,abasilone3r@bbb.org,Male,61,TX,9418.38,1476.89,633,FALSE +137,Dagmar Stowgill,,Female,47,CA,3184.99,12812.5,563,TRUE +138,Pepita Hallbord,phallbord3t@about.me,Female,86,FL,2288.16,14161.54,695,FALSE +139,Tatum Bree,tbree3u@addtoany.com,Male,110,,1415.99,19168.17,,TRUE +140,Adolph Windley,awindley3v@soup.io,Male,118,FL,6373.4,14510.4,651,FALSE +141,Vachel Dodgson,vdodgson3w@t.co,Male,111,CA,3676.04,17391.83,607,FALSE +142,Louise Cavanagh,,Male,48,,6015.39,19521.46,698,TRUE +143,Arnaldo Robinson,arobinson3y@aol.com,Female,52,NY,5247.21,9902.58,712,FALSE +144,Padriac Cornil,pcornil3z@businessinsider.com,Male,29,NY,3777.54,2674.55,683,FALSE +145,Jerome Kern,jkern40@marketwatch.com,Male,63,NY,3065.35,8462.91,564,TRUE +146,Filippo Gregoli,fgregoli41@cornell.edu,Male,,NY,5488.57,4613.9,625,FALSE +,Hernando Atley,hatley42@symantec.com,Male,69,FL,588.64,14510.25,675,FALSE +148,Olivie Johananoff,ojohananoff43@rambler.ru,Female,51,TX,6061.21,,785,FALSE +149,Mill Todhunter,mtodhunter44@cisco.com,Male,110,TX,5635.04,7510.65,614,TRUE +150,Chrystel Lazer,clazer45@imageshack.us,Male,29,FL,4605.86,7247.14,696,FALSE +151,Jeffry Baskerfield,jbaskerfield46@gmpg.org,Male,,CA,2751.79,2090.52,629,TRUE +152,Jamie Mathan,jmathan47@merriam-webster.com,Male,55,FL,3914.82,4136.64,,FALSE +153,Giusto Sloey,,Male,41,FL,1193.48,12608.65,658,FALSE +154,Sherye Eberlein,,Male,45,FL,2940.29,17765.46,,TRUE +155,Grete Heathcott,,Male,40,,5188.36,7703.86,615,TRUE +156,Philippa Frossell,,,2,NY,,18509.29,605,TRUE +157,Jammal Lilly,jlilly4c@microsoft.com,Female,32,,9981.09,13121.83,,FALSE +158,Laurie Gildersleeve,lgildersleeve4d@ocn.ne.jp,Female,0,TX,6184.92,3767.37,779,TRUE +159,Samantha Took,,Male,,TX,7474.28,4453.42,684,FALSE +160,Maximilianus Hamnet,,Male,,NY,2302.34,3774.76,707,TRUE +161,Elisha Ferries,eferries4g@upenn.edu,Male,92,FL,,17780.33,612,FALSE +162,Rossie Hilhouse,rhilhouse4h@trellian.com,Male,62,FL,8054.54,8284.36,708,TRUE +163,Jacky Dyas,jdyas4i@google.co.uk,Female,98,NY,2297.16,16807.77,,FALSE +164,Hally Outright,houtright4j@cdbaby.com,Female,,TX,4157.83,67.46,561,TRUE +165,Tobye Curedale,tcuredale4k@ox.ac.uk,Male,66,NY,,7371.58,782,FALSE +166,Erich Arnoll,earnoll4l@g.co,Female,32,FL,4016.58,17247.15,576,TRUE +167,Porter Rossoni,prossoni4m@hubpages.com,Male,68,TX,4882.43,3940.78,673,TRUE +168,Corrine Pavlenko,,Female,115,CA,7931.54,6935.72,707,FALSE +169,Rudolph Nottle,rnottle4o@wsj.com,,22,NY,9662.49,6501.54,824,TRUE +170,Marlin Finicj,mfinicj4p@kickstarter.com,Female,20,TX,8072.22,15486.48,650,TRUE +171,Gabbi McCafferky,gmccafferky4q@archive.org,Male,20,FL,5217.54,6721.27,618,TRUE +172,Cherida Fearney,cfearney4r@liveinternet.ru,Female,65,FL,2972.17,15537.3,589,FALSE +173,Britt Bavridge,bbavridge4s@sphinn.com,Male,52,FL,2555.93,7784.19,822,FALSE +174,Tommy Lovelace,tlovelace4t@nba.com,Male,113,NY,3539.79,17125.69,786,FALSE +175,Gabriell Assiter,gassiter4u@usnews.com,Female,,CA,6792.48,9675.13,731,TRUE +176,Guntar Fielden,gfielden4v@reverbnation.com,Female,60,CA,7130.77,5580.47,554,FALSE +177,Rachel Barbrick,rbarbrick4w@surveymonkey.com,,,FL,8288.84,1210.47,560,TRUE +178,Inesita Leask,,Male,32,TX,7644.62,,614,TRUE +179,Lynette Moston,lmoston4y@naver.com,Male,108,TX,1056.76,6432.93,740,FALSE +180,Helli Merrifield,hmerrifield4z@businessweek.com,Female,52,TX,5449.95,3286.08,781,TRUE +181,Guillemette Frenchum,gfrenchum50@is.gd,,49,TX,3301.85,4937.06,791,FALSE +182,Ulrick Puddifer,upuddifer51@apache.org,,3,CA,1768.1,14080.32,815,TRUE +183,Abran Have,ahave52@usatoday.com,Female,29,CA,4630.89,,774,TRUE +184,Fransisco Oxtarby,foxtarby53@newsvine.com,Male,,CA,6456.31,11313.75,,TRUE +185,Meghan Revey,mrevey54@csmonitor.com,Male,69,CA,3849.46,777.07,586,FALSE +186,Archibald Ivchenko,aivchenko55@economist.com,Male,83,,3038.48,3227.05,667,TRUE +187,Marilin Coale,mcoale56@hexun.com,Female,,,3208.87,115.38,635,TRUE +188,Ashton Reiach,areiach57@lulu.com,Female,115,TX,3130.17,,719,FALSE +189,Dunstan Khoter,dkhoter58@imageshack.us,Female,87,TX,3665.8,13216.11,710,TRUE +190,Lancelot Poultney,lpoultney59@wiley.com,Male,,TX,9195.6,5570.64,786,FALSE +191,Don Lucio,,Female,18,CA,6968.58,68.75,607,FALSE +192,Symon McKillop,smckillop5b@cnet.com,Female,82,FL,2187.27,7585.13,576,TRUE +193,Penelopa Pedican,ppedican5c@imdb.com,Female,47,TX,5858.52,11210.78,631,TRUE +194,Katrinka Archell,karchell5d@timesonline.co.uk,Male,48,FL,7579.36,10556.29,751,FALSE +195,Raphael McInerney,rmcinerney5e@ibm.com,Female,44,CA,6437.07,3642.12,603,FALSE +196,Roi Burder,rburder5f@xing.com,Male,96,CA,9853.87,938.66,708,FALSE +197,Loni Byrne,lbyrne5g@jiathis.com,Male,87,TX,3029.87,16304.68,558,TRUE +198,Darrelle Amoss,damoss5h@behance.net,Female,97,CA,2932.48,17489.31,,TRUE +199,Cornelia Pell,cpell5i@prweb.com,Female,116,FL,8492.92,1975.81,677,FALSE +200,Ricky Giurio,rgiurio5j@engadget.com,Female,34,FL,1904.2,,594,FALSE +201,Lyon Tattershaw,ltattershaw5k@e-recht24.de,Female,81,TX,3733.4,17106.61,561,TRUE +202,Aileen Parram,aparram5l@cornell.edu,Female,68,CA,4962.21,14400.23,699,TRUE +203,Manda Moohan,mmoohan5m@forbes.com,Female,57,FL,8692.1,4408.6,734,TRUE +204,Kacie Wreiford,kwreiford5n@nymag.com,Male,87,NY,8981.49,13670.62,630,TRUE +205,Ladonna Ferry,lferry5o@psu.edu,Male,72,TX,6345.9,17427.47,696,TRUE +206,Dionysus McTeer,dmcteer5p@jalbum.net,Male,85,FL,429.83,8172.42,693,FALSE +207,Flem Tregale,,Female,98,NY,1584.27,14552.27,801,TRUE +208,Creight Simioni,csimioni5r@archive.org,Female,50,CA,1939.32,57.1,738,FALSE +209,Nanette Warlawe,nwarlawe5s@ucoz.com,Female,103,FL,8192.78,8799.91,,FALSE +210,Corliss Woollett,cwoollett5t@ustream.tv,Female,90,NY,963.09,,787,FALSE +211,Siegfried Gethyn,sgethyn5u@spiegel.de,Female,100,TX,68.76,,658,FALSE +212,Barbara-anne Chesshyre,bchesshyre5v@vinaora.com,Male,10,TX,9278.43,1156.63,746,FALSE +213,Duke Gealle,dgealle5w@washingtonpost.com,Female,62,FL,2337.35,9839.95,680,FALSE +214,Sherry Gepp,sgepp5x@apple.com,,79,TX,710.59,11670.98,723,TRUE +215,Kassie Braitling,kbraitling5y@mail.ru,Female,106,CA,7483.84,10181.72,628,FALSE +216,Findley Fayer,ffayer5z@cdbaby.com,Male,,CA,3017.09,9391.73,686,FALSE +217,Port Scarlet,pscarlet60@digg.com,Female,39,TX,7984.35,11981.95,568,FALSE +218,Erina Lumly,elumly61@ocn.ne.jp,Male,64,FL,5576.61,13477.23,638,FALSE +219,Marcus Northill,mnorthill62@t-online.de,Female,95,TX,8305.87,7501.1,644,FALSE +220,Sean Drinkall,sdrinkall63@wisc.edu,Female,4,CA,601.13,6809.11,,TRUE +221,Milissent McAusland,mmcausland64@paypal.com,Male,104,CA,5249.31,4067.39,632,TRUE +222,Harbert Koschke,hkoschke65@theglobeandmail.com,Female,,TX,2038.8,15630.64,638,TRUE +223,Lola Putman,lputman66@mapquest.com,Male,1,NY,408.7,12067.04,665,FALSE +224,Daisie Demeter,ddemeter67@geocities.jp,Female,29,NY,5688.24,17422.86,705,FALSE +225,Rosalyn Vollam,,Female,17,NY,8383.49,15097.06,,FALSE +226,Gilligan Alvey,galvey69@census.gov,Female,88,FL,6738.99,10475.65,,FALSE +227,Karissa Gatiss,kgatiss6a@usa.gov,,56,,1963.45,1246.29,635,TRUE +228,Hadleigh Helsby,hhelsby6b@columbia.edu,Male,73,CA,6030.87,17278.25,589,TRUE +229,Corinne Starmont,cstarmont6c@illinois.edu,Female,10,TX,3765.58,407.03,653,TRUE +230,Stephani Kirstein,skirstein6d@fastcompany.com,Female,,CA,5106.8,,823,FALSE +231,Deb Stirgess,dstirgess6e@e-recht24.de,Male,,TX,9276.61,10116.97,720,FALSE +232,Zechariah Sketcher,zsketcher6f@cpanel.net,Male,93,CA,4105.38,10994.4,676,TRUE +,Max Corkett,mcorkett6g@de.vu,Male,115,NY,5982.58,14959.57,829,TRUE +234,Alfie Obee,aobee6h@networksolutions.com,Male,110,FL,3887.33,8213.28,658,TRUE +235,Annecorinne Pottes,apottes6i@sciencedaily.com,Female,15,TX,8151.87,5611.55,611,FALSE +236,Barbey Tedorenko,btedorenko6j@surveymonkey.com,,115,TX,4024.58,16943.88,565,FALSE +237,Nan Daviddi,,Male,17,NY,8176.45,,795,FALSE +238,Beatrice Polding,bpolding6l@hostgator.com,Male,11,FL,4994.63,6880.42,551,TRUE +239,Clareta Birley,cbirley6m@lulu.com,Female,8,TX,5349.32,5047.62,796,FALSE +240,Dolf Borton,dborton6n@mail.ru,Male,21,CA,2150.58,2623.63,639,TRUE +241,Mag Wyrall,mwyrall6o@infoseek.co.jp,Male,4,NY,,2868.69,728,FALSE +242,Hillyer Drei,hdrei6p@bloglines.com,Male,55,FL,6024.35,10539.07,563,TRUE +243,Aldis MacQuist,,Male,116,FL,6086.71,8644.36,571,TRUE +244,Ynez Ellum,yellum6r@amazon.co.jp,Female,,NY,8926.47,18995.48,597,FALSE +,Ettore Antrag,eantrag6s@amazon.co.jp,Male,119,NY,2465.06,5157.75,683,TRUE +246,Stevena Turpie,sturpie6t@ucoz.ru,Female,49,CA,4498.45,2875.6,598,TRUE +247,Bamby Becconsall,,Female,72,FL,2621.55,8386.22,701,FALSE +248,Virge Kippins,vkippins6v@cbslocal.com,,35,NY,5224.39,10403.4,655,TRUE +249,Sherwood Mitro,smitro6w@google.fr,Male,33,TX,1467,15262.27,615,TRUE +250,Engracia Cranmere,ecranmere6x@wikimedia.org,Female,36,CA,7304.33,7284.58,789,FALSE +251,Lalo D'Ambrogi,ldambrogi6y@dyndns.org,Female,109,NY,242.83,4122.83,764,TRUE +252,Georg Westover,gwestover6z@com.com,Male,50,FL,9311.13,14225.43,806,TRUE +253,Debbi Robertson,,Male,47,TX,9546.12,13704.86,722,FALSE +254,Loralie Chart,lchart71@spiegel.de,Male,84,TX,842.82,6076.5,602,FALSE +255,Herc Shoebotham,hshoebotham72@google.co.uk,Male,11,CA,1283.35,18339.15,593,FALSE +256,Drew Dwerryhouse,ddwerryhouse73@arstechnica.com,Male,90,NY,9176.51,5446.7,663,FALSE +257,Perceval Gallehock,pgallehock74@webs.com,,,TX,8905.77,10589.17,590,FALSE +258,Gabbi Siggers,gsiggers75@si.edu,Female,52,FL,559.71,3221.7,745,FALSE +259,Damien Ourry,dourry76@loc.gov,Male,34,TX,,13752.77,588,TRUE +,Gilligan McGhee,gmcghee77@epa.gov,Male,,CA,2982.4,4664.36,761,FALSE +261,Heather Grimston,,,11,TX,3820.13,1569.19,748,TRUE +262,Hollyanne Dod,hdod79@chicagotribune.com,,65,FL,4031.4,203.14,731,TRUE +263,Giavani Libbey,glibbey7a@flavors.me,Male,58,TX,9637.89,12690.87,686,TRUE +264,Lula Vlach,lvlach7b@nps.gov,Female,109,CA,1455.68,12610.28,800,TRUE +265,Nate Inderwick,ninderwick7c@yandex.ru,Male,90,FL,6048.07,3640.29,824,FALSE +266,Emery Eard,,Male,61,TX,1889.1,18214.69,810,FALSE +267,Tana Jobin,,Male,,TX,9505.87,4069.27,804,TRUE +268,Jayson Hinchcliffe,jhinchcliffe7f@addtoany.com,Female,119,CA,3768.49,7779.81,567,FALSE +269,Bradford Leheude,bleheude7g@archive.org,Male,16,TX,5596.11,7350.18,,FALSE +270,Roch Swannack,rswannack7h@fotki.com,Male,68,FL,2244.7,5564.17,696,FALSE +271,Allen Manssuer,amanssuer7i@ehow.com,Male,,TX,3940.54,,739,FALSE +272,Janine Scarfe,jscarfe7j@indiatimes.com,,47,FL,1202.31,16230.86,580,TRUE +273,Emily Dolbey,edolbey7k@opensource.org,Male,6,TX,359.07,11068.52,820,FALSE +274,Rey Kemer,,Female,46,TX,8076.42,14442.67,685,FALSE +275,Herby Huffey,,Male,70,FL,6568.25,,672,FALSE +276,Aubrey Spivie,aspivie7n@auda.org.au,,55,CA,7831.8,4636.58,708,FALSE +277,Mel Stride,mstride7o@elegantthemes.com,Male,32,CA,5267.83,154.36,648,TRUE +278,Brier Hudson,bhudson7p@smh.com.au,Female,,NY,9392.2,17700.51,634,TRUE +279,Gerry Ingerith,gingerith7q@yale.edu,,8,CA,2618.25,16795.77,552,FALSE +280,Anatol Georgi,,Male,38,NY,4580.95,10235.65,755,FALSE +281,Rodrigo Gergler,rgergler7s@comcast.net,,8,FL,9371.26,4201.14,660,FALSE +282,Zelma Higginbottam,zhigginbottam7t@berkeley.edu,Male,45,FL,721.8,9967.38,794,FALSE +283,Christal Digman,cdigman7u@multiply.com,Male,7,TX,9302.67,5058.7,791,TRUE +284,Jerrylee Martinuzzi,jmartinuzzi7v@illinois.edu,Female,67,TX,5817.87,10460.83,693,FALSE +285,Gizela Beevors,gbeevors7w@theatlantic.com,Female,,TX,7775.47,13499.68,575,FALSE +286,Barron Riddle,briddle7x@chronoengine.com,,,CA,2533.68,2206.38,757,TRUE +287,Isabella Garriock,igarriock7y@state.tx.us,Female,40,TX,3842.09,14106.98,586,FALSE +288,Jaynell Stairmand,jstairmand7z@youtube.com,,,TX,2565.51,3623.04,696,TRUE +289,Samaria Restall,srestall80@paginegialle.it,Male,112,TX,8020.59,7137.15,764,TRUE +290,Krishnah de Marco,kde81@elpais.com,Male,17,TX,7698.36,4960.48,733,TRUE +291,Wanda Shelp,wshelp82@economist.com,Female,99,CA,7371.31,,686,FALSE +292,Merle Gavan,mgavan83@vimeo.com,Male,,TX,8824.73,3268.12,701,TRUE +293,Lela Cheston,lcheston84@bigcartel.com,Female,13,CA,281.11,,597,FALSE +294,Stace Clampett,sclampett85@eventbrite.com,Female,0,TX,60.01,15167.44,790,TRUE +295,Lina Doudney,ldoudney86@sourceforge.net,Male,93,FL,7052.19,7907.05,798,TRUE +296,Farrand Brookson,fbrookson87@statcounter.com,Male,37,CA,511.65,9517.72,828,TRUE +297,Xymenes Chad,xchad88@google.co.jp,Male,13,TX,3397.83,13365.76,757,TRUE +298,Darelle L'Archer,,Male,91,FL,371.8,10403.4,586,FALSE +299,Maddie Barnby,mbarnby8a@cbslocal.com,Female,64,TX,5183.19,11988.25,652,TRUE +300,Quent Stavers,qstavers8b@yellowpages.com,,11,CA,3521.78,18388,569,TRUE +301,Dyna Budcock,,Female,24,FL,8624.88,4450.2,699,FALSE +302,Johannes Andren,,Female,57,,257.36,13175.56,688,TRUE +303,Benedicta Bansal,bbansal8e@arizona.edu,Male,1,CA,6359.55,,678,FALSE +,Brendin Giaomozzo,bgiaomozzo8f@yahoo.com,Male,68,FL,5207.32,10735.31,714,TRUE +305,Ricard Eadmead,readmead8g@topsy.com,Female,82,CA,3022.46,8676.21,744,FALSE +306,Merrilee Dulwich,mdulwich8h@naver.com,Male,49,TX,7505.99,11109.88,766,FALSE +307,Natividad Simonich,nsimonich8i@scientificamerican.com,Male,76,NY,2041.97,15333.41,809,FALSE +308,Lainey Giaomozzo,lgiaomozzo8j@bandcamp.com,Female,39,TX,8377.86,4892.88,681,FALSE +309,Seka Beringer,sberinger8k@ucoz.ru,Female,3,TX,6692.06,14391.7,,FALSE +310,Mohandis Rickford,mrickford8l@foxnews.com,Female,26,FL,2708.78,13445.51,813,TRUE +311,Tony Fisby,tfisby8m@webs.com,Female,29,FL,8327.63,14093.97,737,TRUE +312,Bent Moorwood,bmoorwood8n@redcross.org,Female,23,TX,608.86,,575,TRUE +,Marcella Casado,mcasado8o@ning.com,,19,TX,856.04,3496.44,713,FALSE +314,Bettina Mordanti,bmordanti8p@about.me,Male,8,FL,4650.02,9343.1,,TRUE +315,Idelle Halbert,ihalbert8q@wired.com,Female,104,CA,9524.94,,663,FALSE +316,Bea Moyce,bmoyce8r@auda.org.au,,25,TX,8746.92,15939.77,651,TRUE +317,Vivienne Dunge,vdunge8s@bravesites.com,,103,TX,4757.26,12871.63,787,FALSE +318,Wolfie Tucsell,wtucsell8t@privacy.gov.au,Female,48,TX,6136.93,18075.06,765,FALSE +319,Sella Vanyushin,svanyushin8u@soup.io,Female,8,FL,2373.81,19200.11,688,TRUE +320,Kerwinn Dohmann,,,119,TX,7418.93,8228.49,686,FALSE +321,Manolo Fonteyne,mfonteyne8w@princeton.edu,Female,89,CA,9772.82,5704.85,570,FALSE +322,Lou Jancey,,Male,54,CA,5674.8,16405.46,558,TRUE +323,Hamil Forsdyke,hforsdyke8y@ifeng.com,Male,94,TX,8872.75,4839.32,632,TRUE +324,Millisent Raun,,Male,39,TX,5635.52,16303.78,,TRUE +325,Viviana McPake,,Male,7,NY,6878.06,16696.63,802,TRUE +326,Sybilla Cooling,,Female,,CA,6664.19,,592,FALSE +327,Hilda Ovize,hovize92@g.co,Female,83,CA,8741.97,16050.75,734,TRUE +328,Adams Pinks,apinks93@illinois.edu,Male,24,FL,7454.71,7471.7,683,FALSE +329,Marie-jeanne Sturdey,,Female,82,FL,9701.03,280.82,647,FALSE +330,Danyelle Deval,ddeval95@usa.gov,,47,FL,2081.35,,766,TRUE +331,Dante Artiss,dartiss96@bloglines.com,Male,55,CA,2936.71,13062.87,803,TRUE +332,Yolanda Cornewell,ycornewell97@ovh.net,Male,22,TX,3335.51,6393.83,798,FALSE +333,Whittaker Basill,wbasill98@miitbeian.gov.cn,Female,75,TX,2744.97,1982.15,620,FALSE +334,Elicia Bousler,ebousler99@arizona.edu,Female,52,TX,3606.39,17279.07,570,FALSE +335,Zachery Drew-Clifton,zdrewclifton9a@mail.ru,Female,64,CA,6583.29,16927.98,813,FALSE +336,Almeda Mundie,amundie9b@ebay.com,Male,88,TX,2976.66,14072.41,673,FALSE +337,Kassie Hallewell,,Female,67,NY,1730.38,3403.51,722,FALSE +338,Nanine Espie,nespie9d@vkontakte.ru,Male,119,FL,8353.24,,571,FALSE +339,Hamid Swynley,hswynley9e@people.com.cn,Female,87,FL,1245.74,8869.53,643,TRUE +340,Hobie Hartridge,hhartridge9f@tripadvisor.com,Male,76,FL,9656.92,5136.14,608,FALSE +341,Vasili Castlake,,Male,14,CA,6726.33,,808,FALSE +342,Julianna Fretwell,jfretwell9h@dmoz.org,Male,3,CA,3855.86,7367.06,786,TRUE +343,Willy Caldow,wcaldow9i@mapy.cz,Male,120,TX,,18204.08,,FALSE +344,Nichole Brunn,nbrunn9j@odnoklassniki.ru,Male,10,CA,5225.37,10720.66,806,TRUE +345,Gerick Van Haeften,gvan9k@t-online.de,,23,TX,48.76,12708.96,657,FALSE +346,Garvy Vanichkin,,,,FL,7498.61,14974.61,610,FALSE +347,Harriett Beardow,hbeardow9m@ovh.net,Female,61,CA,3999,7019.31,607,FALSE +348,Adena Trowill,atrowill9n@marriott.com,Male,76,TX,7164.68,8414.24,725,FALSE +349,Pat Cowans,pcowans9o@infoseek.co.jp,Male,108,CA,6548.69,16132.99,737,TRUE +350,Domenico de Quincey,,Male,102,TX,3272.47,4931.63,552,FALSE +351,Cortney Lamperd,clamperd9q@dailymail.co.uk,Male,28,CA,7019.81,3187.49,583,TRUE +352,Annaliese Inderwick,ainderwick9r@diigo.com,Male,80,TX,1071.8,,579,FALSE +353,Isadora Yashnov,iyashnov9s@altervista.org,Male,32,TX,8689.49,9465.37,672,TRUE +354,Britt Krug,bkrug9t@cnet.com,Male,,CA,8329.91,12850.4,787,FALSE +355,Hailey Walewicz,hwalewicz9u@youtube.com,Female,,CA,,6940.56,612,FALSE +356,Berky Gozney,bgozney9v@reverbnation.com,,7,TX,2575.59,13497.9,607,FALSE +357,Jeni Keepe,jkeepe9w@cornell.edu,Female,93,CA,2565.61,10581.33,685,FALSE +358,Elisha Camplen,,Male,62,CA,4794.5,1596.55,739,FALSE +359,Finley Dwelling,fdwelling9y@wikipedia.org,Male,54,CA,3014.92,5346.37,817,TRUE +360,Rorke Stallion,rstallion9z@deviantart.com,Female,89,NY,5690.76,13262.81,,FALSE +361,Eadie Flips,eflipsa0@timesonline.co.uk,Female,35,TX,2832.1,19871.77,,FALSE +362,Roselle Ainsby,rainsbya1@reverbnation.com,Male,51,CA,40.23,8387.56,696,TRUE +363,Linn Knapp,lknappa2@reference.com,,33,,1264.59,7558.35,,FALSE +364,Martina MacNelly,mmacnellya3@naver.com,Female,116,FL,2097.18,6842.15,703,TRUE +365,Idelle Cansdell,icansdella4@who.int,Male,105,NY,9351.2,12875.34,583,FALSE +366,Myrle Vanner,mvannera5@nba.com,,108,FL,9487.16,12413.03,651,FALSE +367,Vinson Hatherill,vhatherilla6@meetup.com,,95,CA,9221.82,8307.2,744,FALSE +368,Dame Walkinshaw,dwalkinshawa7@mozilla.org,Female,61,,6841.92,9005.93,686,FALSE +369,Marinna Shine,mshinea8@google.com.au,Male,39,CA,7383.78,9787.25,556,FALSE +370,Cyril Gillbanks,cgillbanksa9@ebay.co.uk,Female,96,TX,6083.74,16451.18,754,FALSE +371,Nicky Gallard,ngallardaa@cnn.com,Male,88,FL,5499.59,1497.56,599,TRUE +372,Yasmin Kensett,ykensettab@indiatimes.com,Female,16,CA,1209.98,5954.73,665,TRUE +373,Ashlen Millbank,amillbankac@mit.edu,Male,1,FL,6240.3,,594,FALSE +374,Ellene Kurten,ekurtenad@nbcnews.com,Female,64,CA,3804.07,,683,TRUE +375,Janifer Sambals,jsambalsae@mysql.com,Male,74,,9880.15,8759.89,744,FALSE +376,Brittaney Dahlen,,Male,22,CA,6947.88,7942.96,761,TRUE +377,Cristine Daddow,cdaddowag@wix.com,Male,109,FL,4925.32,2354.14,716,TRUE +378,Shea Swyndley,sswyndleyah@elpais.com,,56,,5711.28,,829,TRUE +379,Jeffrey Rentoll,jrentollai@studiopress.com,Female,81,NY,8295.89,,635,TRUE +380,Eadith Rubinshtein,erubinshteinaj@opensource.org,Female,18,TX,4276.11,11709.03,773,TRUE +381,Errol Maypowder,emaypowderak@unicef.org,Female,,FL,3596.67,15263.44,726,FALSE +382,Rudd Bassford,,Female,9,FL,8257.61,12856.58,771,TRUE +383,Joline Thombleson,jthomblesonam@patch.com,Female,45,CA,8414.51,4781.24,788,TRUE +384,Hobart Ganforth,hganforthan@histats.com,Male,36,CA,8561.02,3357.25,797,TRUE +385,Marthe Lindholm,mlindholmao@netlog.com,Female,113,NY,2488.29,6032.53,615,TRUE +386,Shayla Kilgannon,skilgannonap@army.mil,Male,,TX,6698.67,11403.09,654,TRUE +387,Pembroke Monsey,pmonseyaq@globo.com,Male,77,CA,6141.26,12840.59,694,TRUE +388,Carlyn Noel,cnoelar@hatena.ne.jp,Female,43,,5058.22,,705,TRUE +389,Sascha Demonge,,Female,47,CA,8607.74,5823.29,660,TRUE +390,Adair Gotch,agotchat@sciencedirect.com,Male,95,FL,4804.14,12462.22,642,TRUE +391,Sheff Melmar,smelmarau@altervista.org,Female,106,CA,619.31,,,FALSE +392,Gretchen Tomasini,gtomasiniav@wired.com,Male,99,CA,5030.83,1561.42,692,TRUE +393,Dmitri Spur,dspuraw@exblog.jp,Female,36,FL,5592.52,14341.57,744,TRUE +394,Daria Podbury,dpodburyax@goodreads.com,Female,46,TX,9891.31,2864.52,554,TRUE +395,Obadiah Littlechild,olittlechilday@wp.com,,37,TX,9575.85,14936.82,620,FALSE +396,Panchito Andreix,pandreixaz@fotki.com,Male,104,NY,563.8,5287.35,679,FALSE +397,Morgan Tilburn,mtilburnb0@exblog.jp,Male,3,FL,9559.22,7691.26,702,FALSE +398,Ailbert Aggis,aaggisb1@foxnews.com,Male,79,TX,5477.38,17889.57,676,FALSE +399,Luise Boult,lboultb2@ezinearticles.com,Female,61,CA,608,6605.41,638,FALSE +400,Teresita Ten Broek,ttenb3@wp.com,Female,8,NY,2664.73,1781.89,565,TRUE +401,Lanae Downse,ldownseb4@seesaa.net,,84,FL,7534.13,1429.8,677,FALSE +402,Cristine Casol,ccasolb5@google.com.au,Male,,FL,2453.92,14947.99,787,FALSE +403,Wenonah Urridge,wurridgeb6@ca.gov,Male,62,TX,4748.3,6618.25,554,FALSE +404,Morty Gothard,mgothardb7@so-net.ne.jp,Male,27,NY,9790.24,13219.56,579,TRUE +405,Darwin Conquest,dconquestb8@washington.edu,Female,76,NY,1755.01,2230.24,740,FALSE +406,Danita Shakle,dshakleb9@telegraph.co.uk,,51,FL,571.38,4082.45,596,TRUE +,Cecily Scriver,cscriverba@mysql.com,Male,103,FL,1013.81,15775.27,,TRUE +408,Goldie Norwich,gnorwichbb@ucla.edu,Female,80,CA,,10513.46,552,TRUE +409,Lammond Norrie,lnorriebc@ning.com,Male,87,FL,4402.62,717.27,732,FALSE +410,Wilt Mewton,wmewtonbd@cam.ac.uk,Female,46,TX,4450.04,12664.57,803,TRUE +411,Ginevra Camamill,gcamamillbe@state.tx.us,Female,98,CA,3685.94,8896.77,608,FALSE +412,Igor Phillput,iphillputbf@cargocollective.com,Female,66,CA,1137.1,17594.6,783,TRUE +413,Nappy Cristofolo,,Female,10,TX,3275.68,13979.24,584,FALSE +414,Jessika Venmore,jvenmorebh@state.gov,Male,90,CA,8919.42,4724.37,757,TRUE +415,Cathryn Chaplin,cchaplinbi@over-blog.com,Female,108,FL,2412.85,16557.43,698,TRUE +416,Mickie Woolaston,,Female,12,TX,8810.33,19863.69,755,TRUE +417,Violet Scryne,vscrynebk@scientificamerican.com,Male,10,NY,,17057.91,756,TRUE +418,Irene Sadlier,isadlierbl@livejournal.com,Female,118,NY,9784.44,9945.72,730,FALSE +419,Brooks Lownsbrough,,Female,35,TX,7621.34,2143.86,756,TRUE +420,Erroll Boarder,eboarderbn@ed.gov,,104,TX,6295.36,17277.95,680,FALSE +421,Delphine Searson,dsearsonbo@rediff.com,Male,1,CA,42.54,12291.81,697,TRUE +422,Dayle Lafuente,dlafuentebp@cam.ac.uk,Female,52,NY,3251.77,9591.84,826,FALSE +423,Miner Cockling,mcocklingbq@cam.ac.uk,Male,,NY,5203.35,5919.49,,TRUE +424,Derby Canner,dcannerbr@sakura.ne.jp,Female,87,TX,2826.8,3947.16,748,FALSE +,Darb Edgar,,Male,36,TX,1354.3,0.41,677,FALSE +426,Darrin Pollett,dpollettbt@dot.gov,Female,87,CA,2758.73,327.63,609,TRUE +427,Minette Annott,,Female,,FL,755.57,4453.23,558,TRUE +428,Prince Bawcock,pbawcockbv@liveinternet.ru,Female,52,FL,4560.55,,629,FALSE +429,Perice Lidgard,plidgardbw@altervista.org,,75,TX,90.73,10186.17,778,FALSE +430,Langston Sweating,lsweatingbx@google.es,Male,85,TX,1874.1,11241.68,739,TRUE +431,Laurice Garwell,lgarwellby@time.com,Male,82,CA,106.69,6987.86,800,FALSE +432,Gaspar Tomanek,gtomanekbz@howstuffworks.com,Male,0,TX,3730.93,17912.79,747,FALSE +433,Nicol Bachanski,nbachanskic0@bluehost.com,Male,95,NY,3208.71,14501.36,768,TRUE +434,Harcourt Blest,hblestc1@ox.ac.uk,Male,63,,360.1,18081.95,823,TRUE +435,Esmaria Benne,ebennec2@bloomberg.com,Male,15,TX,7717.01,3060.33,702,TRUE +436,Alisun Fitchen,afitchenc3@hibu.com,Male,65,NY,1606.99,15601.67,783,FALSE +437,Ogden Ratley,oratleyc4@cbc.ca,Female,,TX,9028.93,,677,FALSE +438,Hildagard Gottschalk,hgottschalkc5@usgs.gov,Female,53,FL,4930.72,5700.94,583,FALSE +439,Sande Soame,ssoamec6@prlog.org,Male,15,FL,8939.77,1219.68,827,FALSE +440,Joy Chadwell,jchadwellc7@sogou.com,Male,80,FL,8748.01,4336.16,,FALSE +441,Page Ivanenkov,pivanenkovc8@java.com,Female,58,TX,1006.85,17276.37,751,FALSE +442,Garv Romaine,gromainec9@ftc.gov,Male,49,TX,6300.22,3094.96,734,FALSE +443,Gibby Tours,,Female,,TX,8236.52,6392.95,583,FALSE +444,Nixie Van Giffen,,Male,58,CA,3537.54,9207.64,628,FALSE +445,Margette MacNeilage,mmacneilagecc@vkontakte.ru,,106,TX,2478.76,3152.84,699,FALSE +446,Annmarie Lasty,alastycd@edublogs.org,Male,20,FL,9874.77,9285.87,694,FALSE +447,Mattias Kingdom,,Male,33,TX,6349.15,4033.27,745,TRUE +448,Janek Christer,jchristercf@netscape.com,,,FL,2687.63,16608.68,812,TRUE +449,Gilles Proppers,gpropperscg@google.fr,Male,80,TX,8183.71,19065.51,580,TRUE +450,Julie Hunt,jhuntch@cargocollective.com,,92,TX,2641.83,516.37,560,TRUE +451,Quintilla Ahlf,qahlfci@dell.com,Female,118,TX,8928.95,18874.83,802,TRUE +452,Taddeusz Aiers,taierscj@elegantthemes.com,Male,109,TX,7254.17,16149.61,584,TRUE +453,Sylvester Tingey,stingeyck@howstuffworks.com,Male,0,CA,75.63,,,FALSE +454,Lea Brigshaw,lbrigshawcl@nhs.uk,,44,TX,755.98,3675.58,822,TRUE +455,Sharyl Chavez,schavezcm@senate.gov,Female,114,NY,8823.02,4716.97,635,FALSE +456,Devora Brockett,dbrockettcn@nhs.uk,Male,27,TX,4456.49,985.72,,TRUE +457,Shandy Hearley,shearleyco@1688.com,Male,88,NY,1790.28,10308.93,689,TRUE +458,Edmund Heers,eheerscp@alexa.com,,32,FL,7935.15,,613,TRUE +459,Emogene Markie,,Female,93,NY,3641.62,12223.52,748,FALSE +460,Leda Nagle,lnaglecr@forbes.com,Female,,,4394.64,19467.09,,TRUE +461,Cart Risbridge,crisbridgecs@joomla.org,Male,78,FL,4802.47,18712.34,611,FALSE +462,Lucina Thomtson,lthomtsonct@last.fm,,105,CA,7986.04,14759.03,,FALSE +463,Nickie Gerding,ngerdingcu@indiegogo.com,,0,TX,6909.22,19411.28,587,TRUE +464,Nikkie Gilbard,,Male,7,NY,4969.56,8138.51,562,FALSE +465,Elihu Zannuto,,,,TX,7942.12,7605.4,552,FALSE +466,Lira Dartan,ldartancx@cafepress.com,Male,13,NY,5438.21,13175.37,764,TRUE +467,Laurence Billiard,lbilliardcy@nasa.gov,Male,64,CA,2398.8,5980.37,560,TRUE +468,Blake Terlinden,bterlindencz@stumbleupon.com,Female,42,NY,205.39,2821.25,746,FALSE +469,Eolanda Osman,eosmand0@google.com.au,,110,TX,7894.35,8604.8,575,FALSE +470,Jaclin Attewill,jattewilld1@newyorker.com,Female,,FL,1515.26,12537.03,589,TRUE +471,Kearney Tripe,ktriped2@godaddy.com,,103,FL,8558.45,7833.86,558,TRUE +472,Marcelline Beckley,mbeckleyd3@unicef.org,,16,CA,6771.29,15351.42,741,FALSE +473,Ileana Biernacki,ibiernackid4@skype.com,Male,69,TX,3424.19,3489.23,724,TRUE +,Rodie Stamper,rstamperd5@sun.com,Male,31,CA,4730.27,15715.34,,TRUE +475,Cecilla Farbrace,,Female,73,CA,6023.66,17112.99,652,TRUE +476,Cordy Crabtree,ccrabtreed7@virginia.edu,Female,23,TX,6774.8,1026.66,632,FALSE +477,Noach O'Brian,nobriand8@dmoz.org,Female,28,TX,7583.34,10510.82,650,TRUE +478,Wade Farmery,wfarmeryd9@fema.gov,Male,13,TX,6803.46,6049.32,560,TRUE +479,Dalli Rochford,drochfordda@liveinternet.ru,Female,,CA,5906.7,14180.47,797,FALSE +480,Lenci Grassett,lgrassettdb@yellowpages.com,Female,77,CA,5392.8,15391.97,610,FALSE +481,Amaleta Tapping,atappingdc@unesco.org,Male,18,CA,6324.76,2070.72,743,FALSE +482,Steffane Showen,sshowendd@dailymotion.com,Male,111,FL,9197.94,1412.74,729,FALSE +483,Linea Mahaddy,lmahaddyde@globo.com,Male,10,NY,5220.51,12893.84,709,FALSE +484,Cad Somerlie,csomerliedf@about.com,Male,24,TX,1698.41,11973.63,,FALSE +485,Joleen Espinazo,jespinazodg@usgs.gov,Male,29,FL,2690.11,17264.16,748,FALSE +486,Roddie Benedito,rbeneditodh@pbs.org,Male,70,CA,5062.92,11440.06,805,TRUE +487,Augustin Petroselli,apetrosellidi@nhs.uk,Female,31,TX,7385.8,14781.91,733,TRUE +488,Cesar Atwel,catweldj@samsung.com,Female,,FL,3391.32,7938.7,733,FALSE +489,Andras Curnokk,acurnokkdk@bbb.org,Female,9,FL,6895.99,15422.04,822,FALSE +490,Lombard Ughini,lughinidl@jalbum.net,Female,70,TX,2969.35,19842.97,567,FALSE +491,Jennine Bullard,,Male,67,FL,5449.23,5401.92,555,TRUE +492,Dorry Sandercock,dsandercockdn@pagesperso-orange.fr,Female,,FL,840.83,2043.21,688,TRUE +493,Bibby Proback,,,17,NY,7220.48,200.94,584,TRUE +494,Carlene Corteney,,,120,TX,7501.74,17565.4,,TRUE +495,Dorene Pedel,dpedeldq@cyberchimps.com,Male,36,FL,4158.85,11429.87,558,TRUE +496,Julie Brierton,jbriertondr@pagesperso-orange.fr,Female,2,CA,3937.39,13435.06,663,TRUE +497,Nicolea Viegas,nviegasds@theguardian.com,,,NY,6082.47,877.54,647,FALSE +498,Madelon Fermoy,mfermoydt@1688.com,Male,91,CA,3389.66,15874.74,646,TRUE +499,Zaccaria Bartul,,Male,71,FL,1621.38,5209.13,674,TRUE +500,Powell Quarton,,Female,92,FL,9721.84,651.35,742,TRUE +501,Lainey Balthasar,,Female,61,FL,6671.94,,735,TRUE +502,Lennie Rowson,,Male,3,CA,8300.05,16648.18,,FALSE +503,Franklin Lythgoe,flythgoedy@behance.net,,52,TX,2653.82,16998.39,570,FALSE +504,Simone Pheasey,spheaseydz@chicagotribune.com,Male,10,FL,6552.49,673.21,676,TRUE +505,Verne Mantha,vmanthae0@4shared.com,Female,77,TX,7144.18,2661.44,802,TRUE +506,Pavia Marzello,pmarzelloe1@mozilla.com,Male,5,FL,3823.23,,743,TRUE +507,Carola Lownds,clowndse2@uTX.edu,Female,96,CA,9767.5,,803,FALSE +508,Chryste Van Vuuren,cvane3@cdbaby.com,Female,100,TX,4378.2,,582,TRUE +509,Karoly Sobczak,ksobczake4@about.com,Female,76,NY,2375.53,2165.45,559,TRUE +510,Roz Tacon,,Male,,,466.86,10112.54,692,FALSE +511,Suellen Whittock,swhittocke6@msn.com,Female,21,TX,2692.74,,773,FALSE +512,Milton Davidovich,mdavidoviche7@symantec.com,Female,80,FL,4118.23,11656.55,605,TRUE +513,Ricard Jenteau,rjenteaue8@boston.com,Male,11,TX,6358.52,11103.15,648,FALSE +514,Laurene Lewisham,llewishame9@google.com.br,,116,TX,2620.65,,767,TRUE +515,Gustav Delahunt,,Male,87,TX,3542.41,,802,FALSE +516,Mirilla Baynard,mbaynardeb@t-online.de,Male,40,CA,4478.55,2865.48,729,FALSE +517,Christan Authers,cauthersec@free.fr,,106,TX,4660.14,,594,FALSE +518,Kaylee Brisset,,Female,28,CA,2191.57,13851.06,669,FALSE +519,Quincey Emerson,,Male,108,NY,419.46,8185.39,643,FALSE +520,Kira Overton,kovertonef@oracle.com,Female,88,TX,4798.9,10584.33,759,FALSE +,Annalise Doorly,adoorlyeg@php.net,,63,TX,1738.92,17831.46,557,FALSE +522,Bellina Bretland,,Male,101,TX,2689.53,8694.38,748,FALSE +523,Baxy Eagling,beaglingei@dell.com,,21,NY,5310.15,19422.66,649,TRUE +524,Loralyn Berndtssen,lberndtssenej@skype.com,Female,90,FL,1098.13,8703.65,,FALSE +525,Gale Phizacklea,gphizackleaek@salon.com,Male,13,NY,7482.9,8146.74,698,FALSE +526,Lurline Eason,leasonel@tumblr.com,Female,69,CA,3004.8,8914.98,588,FALSE +527,Joyann Grimmett,jgrimmettem@hubpages.com,Male,1,CA,,17220.35,772,FALSE +528,Elsa Mattiuzzi,emattiuzzien@tiny.cc,Male,48,TX,5483.32,17700.2,,TRUE +529,Carol-jean Crookall,ccrookalleo@paginegialle.it,Male,91,FL,3365.75,2147.93,693,TRUE +530,Malanie Baily,mbailyep@yandex.ru,Female,5,FL,9413.97,8148.62,605,TRUE +531,Kliment Stango,,Male,,FL,4940.03,11174.48,792,FALSE +532,Eartha Croson,ecrosoner@nps.gov,Female,113,TX,7874.46,13481.26,570,FALSE +533,Gene Huebner,ghuebneres@creativecommons.org,Female,111,NY,2532.1,10677.9,745,TRUE +534,Garrik Solesbury,gsolesburyet@alexa.com,,113,FL,690.92,2769.12,679,FALSE +535,Ofilia Cardoo,ocardooeu@chron.com,Male,,FL,2557.79,4659.64,678,FALSE +536,Aubine Haylor,ahaylorev@ox.ac.uk,Male,49,CA,8837.65,14626.75,568,FALSE +537,Eden Rigg,eriggew@list-manage.com,Female,29,FL,2821.56,9433.8,769,FALSE +538,Catherine Giscken,cgisckenex@xrea.com,Female,114,TX,5803.54,8880.3,558,FALSE +539,Ruthi Braven,rbraveney@wordpress.org,Male,70,TX,3318.88,17827.47,617,FALSE +540,Amelina Windows,awindowsez@1und1.de,Male,12,TX,913.6,4014.12,712,FALSE +541,Olva Ewestace,oewestacef0@addtoany.com,Male,84,TX,8036.8,8644.37,583,TRUE +542,Pansie Heaysman,pheaysmanf1@howstuffworks.com,Male,,FL,9854.39,6163.92,785,TRUE +543,Edythe Scocroft,escocroftf2@nature.com,Female,93,CA,478.94,1257.43,823,FALSE +544,Reena Gilardengo,rgilardengof3@sciencedirect.com,Male,84,CA,3118.57,14092.56,688,FALSE +545,Kevan Bredgeland,,Male,52,NY,8577.95,14707.33,815,TRUE +546,Benedicto Wybourne,bwybournef5@yahoo.com,Female,50,,3795.98,10232.59,724,TRUE +547,Fredelia Kenwyn,fkenwynf6@illinois.edu,,18,TX,6572.68,,668,FALSE +,Gerardo Legging,,Female,100,CA,7476.88,1523.2,768,FALSE +549,Kally Beane,,Female,,NY,,3157.39,797,TRUE +550,Angel Paynes,apaynesf9@reddit.com,,48,CA,9923.61,18034.18,755,TRUE +551,Irma Vowels,,Female,8,TX,6036.51,6636.35,738,TRUE +552,Vinni White,vwhitefb@examiner.com,Male,18,NY,4392.8,,812,TRUE +553,Jesse Ellson,jellsonfc@desdev.cn,Female,51,FL,2631.21,6557.13,738,FALSE +554,Binny Anthonsen,banthonsenfd@google.it,,104,TX,7982.57,18148.09,687,FALSE +555,Ginelle Dupoy,gdupoyfe@nbcnews.com,Female,108,FL,5047.29,466.71,645,FALSE +556,Adelind Amerighi,aamerighiff@washingtonpost.com,Female,40,,7947.35,1569.73,723,FALSE +557,Brewster Imeson,bimesonfg@senate.gov,Male,46,TX,5355.15,11868.52,817,FALSE +558,Kristofer Cockitt,kcockittfh@baidu.com,,,FL,6391.34,14377.03,819,TRUE +559,Vasili Garlant,vgarlantfi@xrea.com,Male,19,TX,6748.48,8415.21,724,TRUE +560,Maxwell Mussotti,mmussottifj@loc.gov,Female,87,CA,,8834.63,676,TRUE +561,Pall Reihill,preihillfk@mozilla.org,Male,115,CA,6781.05,5273.52,796,FALSE +562,Ema MacNeil,emacneilfl@rediff.com,Male,7,TX,6901.62,11703.36,569,TRUE +563,Elayne Ricarde,ericardefm@yellowpages.com,Female,7,CA,466.93,12819.99,776,TRUE +564,Hubey Zelake,hzelakefn@jugem.jp,Female,24,NY,2855.45,19335.86,606,FALSE +565,Ulrica Abramovitch,uabramovitchfo@jalbum.net,Female,113,TX,7911.57,6874.44,707,FALSE +566,Afton Iashvili,aiashvilifp@istockphoto.com,Female,44,TX,9828.66,8939.52,636,FALSE +567,Sauncho Haswall,shaswallfq@t-online.de,Male,51,CA,499.75,4868.27,,TRUE +568,Darell Klimecki,dklimeckifr@dmoz.org,Female,,NY,8488.71,10365.51,653,FALSE +569,Pancho Beri,pberifs@google.fr,Female,,CA,6213.89,4676.49,643,FALSE +570,Gertie Talkington,gtalkingtonft@canalblog.com,Female,52,FL,1482.57,15565.09,,TRUE +571,Nissie Sinnatt,nsinnattfu@yellowpages.com,Female,27,CA,933.09,17728.58,725,TRUE +572,Susan Debling,sdeblingfv@bandcamp.com,Female,,NY,7238.5,9027,734,TRUE +573,Charlton McCarrison,cmccarrisonfw@virginia.edu,Female,44,CA,320.43,17061.71,595,FALSE +574,Lacie Asee,laseefx@statcounter.com,Male,99,CA,6514.59,19776.87,804,FALSE +575,Casey Linsey,clinseyfy@businessweek.com,Male,82,NY,7478.84,841.51,587,FALSE +576,Kynthia Fargie,kfargiefz@paginegialle.it,Male,117,FL,9268.05,14855.68,569,FALSE +577,Cristionna Brownsett,,Female,12,CA,5.83,190.88,654,TRUE +578,Mikael Blucher,,Male,104,CA,8672.5,,673,FALSE +579,Adolphe Hearson,ahearsong2@a8.net,Female,20,CA,2507.9,13983.88,579,FALSE +580,Brocky Creavan,bcreavang3@zdnet.com,Male,101,,5144.76,,606,TRUE +581,Sabra Blanque,sblanqueg4@themeforest.net,Male,35,CA,3980.27,,750,FALSE +582,Avictor McGreal,amcgrealg5@blogs.com,Male,,TX,5301.04,616.25,768,FALSE +583,Elsa Gunton,eguntong6@stanford.edu,Male,88,CA,763.75,11750.65,581,FALSE +584,Dulcine Ellson,dellsong7@disqus.com,Male,,TX,5524.58,,781,FALSE +585,Cleo Glasspoole,cglasspooleg8@nymag.com,Male,44,FL,7897.5,19099.94,693,TRUE +586,Delia Sumpter,dsumpterg9@phpbb.com,Male,61,,6979.8,19650.63,709,TRUE +587,Harris Baldick,hbaldickga@jiathis.com,Female,76,TX,8026.18,17433.31,569,FALSE +588,Cornell Streetfield,cstreetfieldgb@mac.com,Female,35,FL,8447.86,,787,FALSE +589,Orbadiah Wettern,owetterngc@opera.com,Female,,NY,385.13,6949.2,792,TRUE +590,Leora Ogglebie,,Female,100,FL,5966.19,1108.32,,TRUE +591,Lorena Bortolomei,lbortolomeige@chicagotribune.com,Male,57,CA,4211.3,5787.74,605,TRUE +592,Beverlie Rotham,brothamgf@ed.gov,Male,88,CA,2889.84,1570.05,714,FALSE +593,Rad Coomber,rcoombergg@istockphoto.com,Male,77,CA,961.71,,562,TRUE +594,Tait Cammack,tcammackgh@intel.com,Male,20,NY,7435.79,14458.64,787,FALSE +595,Torry Verryan,tverryangi@amazon.de,Female,108,TX,6259.02,3463.52,604,FALSE +596,Murdoch Rose,mrosegj@free.fr,Male,101,NY,5794.86,18237.31,794,FALSE +597,Yelena Champken,ychampkengk@printfriendly.com,,100,CA,7277.75,14572.86,,TRUE +598,Dalli Rubinovitsch,drubinovitschgl@xinhuanet.com,Male,29,NY,1097.11,11671.45,810,FALSE +599,Albert Silmon,asilmongm@epa.gov,Male,76,CA,4908.34,5612.03,649,TRUE +600,Estrellita Saull,esaullgn@themeforest.net,,12,NY,5506.87,324.93,713,FALSE +601,Lanni Divill,ldivillgo@wsj.com,Female,18,NY,1445.26,691.23,,TRUE +602,Tiffanie Lord,tlordgp@youku.com,Female,37,NY,383.71,157.58,579,TRUE +603,Alric Errett,,Female,59,TX,58.04,17742.71,598,TRUE +604,Haley Mc Ilory,,Female,0,FL,9957.82,9787.8,685,FALSE +605,Penni Strowthers,pstrowthersgs@t.co,Male,47,CA,4388.1,11846.46,601,FALSE +606,Heath Daughtery,hdaughterygt@arstechnica.com,Male,55,TX,1447.92,6985.37,558,TRUE +607,Zea Scobbie,,Female,110,TX,3185.21,14635.86,662,TRUE +608,Kelli Paulo,kpaulogv@time.com,Male,62,TX,4859.7,,740,TRUE +609,Normand Dewane,ndewanegw@auda.org.au,Male,62,FL,5055.75,19998.94,628,FALSE +610,Mose Howsam,mhowsamgx@gmpg.org,Male,0,TX,5542.56,11585.45,659,TRUE +611,Elvira Dumbrill,edumbrillgy@ca.gov,Male,9,TX,3069.7,4448.92,800,FALSE +612,Geoffrey Touzey,,Male,,,8458.47,4286.91,745,FALSE +613,Gavra Artindale,gartindaleh0@1688.com,Male,85,FL,7594.48,554.85,736,TRUE +614,Rhody Bamsey,,Male,102,FL,4433.61,6503.83,709,FALSE +615,Wendi Silversmid,wsilversmidh2@businessinsider.com,Female,44,CA,3121.43,1195.23,603,TRUE +616,Luis Spight,lspighth3@woothemes.com,Female,82,FL,9816.71,9247.41,658,FALSE +617,Leeanne Crowthe,lcrowtheh4@digg.com,Female,107,TX,2351.66,929.87,682,FALSE +618,Julieta Maypole,jmaypoleh5@tiny.cc,Male,3,NY,2046.57,6171.91,570,TRUE +619,Fay Bisgrove,fbisgroveh6@wunderground.com,Female,79,FL,1596.39,4335.47,728,FALSE +620,Glenden Jolland,gjollandh7@wikispaces.com,Female,40,CA,3678.81,11228.36,585,FALSE +621,Raddie Herculeson,rherculesonh8@hud.gov,Female,70,,5025.66,3136.12,750,TRUE +622,Britt Kliement,bkliementh9@qq.com,,6,NY,368.08,14551.33,785,FALSE +623,Charita Baldree,cbaldreeha@imageshack.us,Female,107,TX,6164.02,13795.36,824,FALSE +624,Fancie Webbe,fwebbehb@sciencedirect.com,Male,,FL,2608.71,14664.74,565,FALSE +625,Berenice Mendenhall,bmendenhallhc@businesswire.com,Female,18,NY,1958.27,15159.06,725,TRUE +626,Frayda Moultrie,fmoultriehd@nifty.com,Male,38,CA,2865.08,6394.67,821,TRUE +627,Aurel Borland,aborlandhe@dailymail.co.uk,Female,15,TX,6423.81,17012.63,819,TRUE +628,Judas Churchlow,jchurchlowhf@oracle.com,Female,39,FL,7443.61,2382.91,558,FALSE +629,Garvey Haps,ghapshg@miibeian.gov.cn,,102,CA,9838.25,229.62,671,FALSE +630,Brok Gibbie,bgibbiehh@macromedia.com,,61,TX,8412.64,120.4,,FALSE +631,Orbadiah Mc Meekin,omchi@eepurl.com,Female,83,CA,610.22,3084.75,677,FALSE +632,Constanta Eles,celeshj@cnn.com,Female,14,NY,2625.63,12875.07,606,TRUE +633,Reinold Aicken,raickenhk@google.es,Male,115,NY,3189.57,3702.09,822,TRUE +634,Raeann Carwardine,rcarwardinehl@youku.com,,101,CA,2285.06,9991.48,689,FALSE +635,Consuelo Prangle,cpranglehm@ameblo.jp,Female,3,TX,7164.35,12629.54,719,FALSE +636,Kata McNeilley,kmcneilleyhn@cbc.ca,Female,,CA,6186.04,2731.61,,FALSE +637,Vernor Swyn,vswynho@opensource.org,Male,15,CA,858.27,12005,585,FALSE +638,Kit Tampin,ktampinhp@qq.com,Male,108,CA,8013.7,16983.42,615,FALSE +639,Johnna Bole,jbolehq@ask.com,Male,,CA,1739.84,14467.92,597,FALSE +640,Nolie Fulkes,nfulkeshr@google.co.uk,Male,84,TX,1447.24,4391.58,723,TRUE +641,Barny Dudney,bdudneyhs@nhs.uk,Female,50,CA,5435.16,4622.75,730,FALSE +642,Yard Ivermee,yivermeeht@skyrock.com,Male,112,CA,8129.46,15694.24,789,FALSE +643,Marlin Paulisch,mpaulischhu@spiegel.de,Female,23,FL,7355.92,1723.34,619,TRUE +644,Blake Bason,bbasonhv@marriott.com,Male,80,CA,1013.93,6457.08,726,FALSE +645,Christel Eat,ceathw@craigslist.org,Female,56,CA,2767.83,,751,TRUE +646,Delaney Le Sarr,dlehx@umich.edu,Male,107,CA,359.37,7121.92,588,TRUE +647,Cherey Piens,cpienshy@soundcloud.com,Female,16,NY,2303.99,,820,FALSE +648,Harland Sherwin,hsherwinhz@about.me,Female,93,TX,1561.62,8977.67,552,TRUE +649,Lynnell Gillbee,lgillbeei0@admin.ch,Female,,NY,6151.21,11743.04,,FALSE +650,Corry Brumwell,cbrumwelli1@apple.com,Male,80,CA,8888.64,,717,FALSE +651,Alessandra Scotts,,Female,,TX,1996.52,7904.35,644,FALSE +652,Veriee Higgan,vhiggani3@parallels.com,,100,TX,2560.04,6371.61,667,TRUE +653,Velma Latus,vlatusi4@dailymotion.com,Male,103,FL,2716.42,,680,TRUE +654,Luz Coltherd,,Male,16,TX,9740.05,9111.55,637,FALSE +655,Christel Tomik,ctomiki6@macromedia.com,Female,73,TX,3315.14,6496.39,711,TRUE +656,Sholom Blasi,sblasii7@businesswire.com,Male,116,FL,6329.23,16508.24,580,FALSE +657,Harriot Oglethorpe,hoglethorpei8@harvard.edu,Male,54,FL,2052.73,,619,TRUE +658,Cyndie Clibbery,cclibberyi9@examiner.com,Male,24,CA,2560.37,,753,TRUE +659,Serene Buss,,Male,92,NY,8718.13,13314.19,693,TRUE +660,Edgard Boot,ebootib@storify.com,Female,43,FL,9839.03,2439.07,770,FALSE +661,Baron Micheau,bmicheauic@patch.com,Male,66,TX,6522.38,17991.4,797,FALSE +662,Peggy Ricoald,pricoaldid@un.org,Male,74,NY,2572.63,15174.99,679,TRUE +663,Roxy Goosey,rgooseyie@nydailynews.com,Female,112,CA,2700.53,12324.14,745,FALSE +664,Sephira Prine,sprineif@pagesperso-orange.fr,Male,48,FL,5821.88,4635.76,800,FALSE +665,Cammy Malden,cmaldenig@vimeo.com,,,TX,2518.06,964.31,758,TRUE +666,Marys Chong,mchongih@homestead.com,Male,113,CA,8836.96,190.34,,TRUE +667,Mina Carayol,,Male,,CA,9805.37,13291.63,565,FALSE +668,Christiana Slocom,,Female,96,TX,6252.08,1676.66,663,TRUE +669,Lindon Freebury,,Male,72,FL,261.56,19038.61,713,TRUE +670,Gerik Mungane,gmunganeil@disqus.com,Male,62,CA,5578.26,10381.86,636,TRUE +671,Mace Vear,mvearim@netlog.com,Female,78,NY,5149.13,9002.39,759,TRUE +672,Tallulah Gabbitas,tgabbitasin@oracle.com,Female,58,CA,171.31,2848.87,696,FALSE +673,Kirsten Tetsall,ktetsallio@si.edu,Male,,NY,3496.23,1681.11,800,FALSE +674,Vicki Van der Merwe,vvanip@posterous.com,,,NY,8798.87,8947.54,795,FALSE +675,Loy Clawson,lclawsoniq@samsung.com,Male,29,TX,5052.46,7629.13,635,FALSE +676,Katti Apperley,kapperleyir@acquirethisname.com,Male,7,FL,3951.34,15380.43,596,FALSE +677,Janaye Clacson,jclacsonis@etsy.com,Female,16,NY,4184.34,,560,TRUE +678,Georgena Ickovicz,gickoviczit@baidu.com,Female,96,CA,9717.94,19920.79,560,TRUE +679,Jeanine Simnel,jsimneliu@diigo.com,Female,13,,9921.87,5035.05,720,TRUE +,Vilma Leyland,vleylandiv@over-blog.com,Male,93,CA,9608.53,2056.77,,FALSE +681,Kynthia Trittam,ktrittamiw@businessweek.com,Male,100,FL,674.4,12666.57,739,FALSE +682,Reade Jancso,rjancsoix@cam.ac.uk,Female,114,TX,2952.42,9463.51,699,TRUE +683,Sonny Isitt,sisittiy@xinhuanet.com,Female,28,,9677.28,9634.6,633,TRUE +684,Lari Garfield,,Female,87,TX,8762.4,12493.57,621,FALSE +685,Carlyn Stevani,cstevanij0@bizjournals.com,Female,35,TX,7299.19,2652.46,640,FALSE +686,Mayer Regan,mreganj1@nifty.com,Male,98,NY,6460.07,19320.26,583,FALSE +687,Dyan Burchnall,dburchnallj2@sciencedirect.com,Female,64,TX,5213.63,1523.64,646,FALSE +688,Hedwiga Ernke,hernkej3@yahoo.com,Male,72,CA,1395.63,15268.16,729,TRUE +689,Gayel Banbrigge,gbanbriggej4@google.cn,Male,52,CA,5499.36,7813.48,695,FALSE +690,Delphinia Boggs,dboggsj5@shinystat.com,,26,TX,3347.45,5825.18,590,FALSE +691,Frazer Hrihorovich,fhrihorovichj6@chron.com,Male,56,FL,3468.57,5709.07,807,TRUE +692,Munroe Mickan,,Male,20,NY,9744.13,2450.84,617,FALSE +693,Yuri Sigert,ysigertj8@census.gov,Female,59,,6494.05,17356.58,566,TRUE +694,Meaghan Jancic,mjancicj9@msn.com,Male,33,FL,2188.84,16399.46,757,FALSE +695,Mycah Cranmere,,Male,31,FL,8159.84,5255.21,754,TRUE +696,Odella Belin,obelinjb@cam.ac.uk,Male,69,TX,7514.99,17406.28,704,TRUE +697,Pierrette Leckey,,Female,77,TX,8076.33,15644.91,692,FALSE +698,Cordie Acarson,,,0,CA,815.14,8460.57,,TRUE +699,Waldo Jakuszewski,wjakuszewskije@4shared.com,Female,48,TX,978.95,7673.58,736,TRUE +700,Michell Prosek,,Female,43,CA,4447.85,13736.69,612,TRUE +701,Lucille Hurst,lhurstjg@surveymonkey.com,Female,,FL,8666.6,2015.69,727,FALSE +702,Dall Dybell,ddybelljh@joomla.org,,,FL,6866.28,16136.71,598,FALSE +703,Zeb Bence,zbenceji@hud.gov,,71,CA,4451.48,4929.4,576,FALSE +704,Saleem Petrov,spetrovjj@oaic.gov.au,Male,15,FL,2009.81,7484.78,711,FALSE +705,Mitch Berthelet,mbertheletjk@uol.com.br,Male,23,CA,6610.39,6097.16,562,FALSE +706,Lorine Pashler,lpashlerjl@yahoo.co.jp,,81,FL,9413.34,9032.02,612,FALSE +707,Jean Bryceson,jbrycesonjm@seattletimes.com,,116,CA,98.8,6529.95,642,TRUE +708,Tabbitha Putley,,Male,44,TX,6550.1,1064.28,738,FALSE +709,Chaunce Bridgestock,cbridgestockjo@dropbox.com,Female,71,NY,5194.37,30.06,599,TRUE +710,Amanda McAuslene,amcauslenejp@examiner.com,Female,54,FL,5799.9,,685,FALSE +711,Jase Pochon,jpochonjq@delicious.com,Female,,FL,4599.13,13092.32,792,TRUE +712,Sigfrid Tabbernor,stabbernorjr@facebook.com,Male,56,CA,4777.63,3755.95,766,FALSE +713,Bryn Broadwell,bbroadwelljs@statcounter.com,Female,43,TX,1829.05,6361.84,706,TRUE +,Michal Foxall,mfoxalljt@bloomberg.com,Male,77,TX,4579.66,7963.56,,TRUE +715,Torey Larrett,,Male,31,CA,4272.45,2224.28,685,FALSE +716,Olly Rockhall,orockhalljv@tumblr.com,Female,,FL,2494.11,15747.62,636,FALSE +717,Judie Lawranson,jlawransonjw@baidu.com,Female,71,FL,7744.4,3857.53,659,FALSE +718,Eduard Flanders,eflandersjx@yellowbook.com,,75,TX,7019.58,5137.58,690,TRUE +719,Joshuah Lye,jlyejy@yelp.com,Male,72,FL,744.97,14383.12,,TRUE +720,Ollie Tupling,otuplingjz@goo.ne.jp,Female,34,FL,531.46,,815,TRUE +721,Jamey Soame,jsoamek0@globo.com,Male,18,CA,973.16,5521.01,564,FALSE +722,Murial Kincla,mkinclak1@theguardian.com,Female,37,FL,708.92,15268.44,758,TRUE +723,Gennie Carneck,gcarneckk2@timesonline.co.uk,Male,55,TX,7927.83,18784.16,679,FALSE +724,Rosita Sexstone,rsexstonek3@slideshare.net,Male,104,TX,9725.8,514.78,584,FALSE +725,Sophie Marshalleck,smarshalleckk4@opensource.org,Male,28,CA,6675.29,11078.54,805,FALSE +726,Jamesy Pollen,jpollenk5@cargocollective.com,Male,85,NY,7315.3,18147.37,580,FALSE +727,Dorita Featenby,dfeatenbyk6@php.net,Female,118,FL,977.4,8508.94,732,TRUE +728,Mitchell Lintill,mlintillk7@mysql.com,Male,66,CA,3511.6,7776.91,824,TRUE +729,Fremont Foli,ffolik8@google.pl,Male,85,FL,5826.37,17351,568,FALSE +730,Brittni Librey,blibreyk9@examiner.com,Female,15,FL,1618.86,,649,TRUE +731,Sutherlan Roper,sroperka@abc.net.au,Female,101,TX,7646.76,9304.02,690,TRUE +732,Chantal Rushsorth,crushsorthkb@hp.com,Male,,TX,5180.55,2564.59,558,FALSE +733,Coleman Hitzschke,,,,FL,8269.61,,746,TRUE +734,Vick Barrott,vbarrottkd@google.es,Female,31,CA,9786.57,9668.18,585,FALSE +735,Johnny Josling,jjoslingke@va.gov,Female,71,NY,9757.05,,581,TRUE +736,Craggie Tincombe,ctincombekf@barnesandnoble.com,Female,7,CA,4302.75,8210.33,680,TRUE +737,Bealle Keats,bkeatskg@twitter.com,,105,CA,7490.54,19323.66,749,FALSE +738,Fredia Arlott,farlottkh@bbc.co.uk,,,TX,9243.02,1221.89,808,FALSE +739,Earl Viccars,eviccarski@jugem.jp,Female,80,,3702.33,9646.41,818,TRUE +740,Florinda Timbridge,ftimbridgekj@si.edu,Male,93,CA,2837.15,2525.68,653,FALSE +741,Helga Tilby,htilbykk@alibaba.com,,47,FL,6576.99,14709.66,774,TRUE +742,Bianka Culpin,bculpinkl@e-recht24.de,Female,74,CA,,10188.03,806,FALSE +743,Sheryl Paradise,sparadisekm@elpais.com,,78,TX,5587.54,9052.44,757,FALSE +744,Kelvin Skettles,kskettleskn@opera.com,Female,76,NY,4598.6,3666.55,801,FALSE +745,Loraine Staner,lstanerko@constantcontact.com,,,CA,8802.18,8233.12,743,TRUE +746,Spenser Osburn,sosburnkp@sbwire.com,Male,15,TX,3382.57,14066.54,698,TRUE +747,Ezra Fulks,efulkskq@scientificamerican.com,Male,6,TX,8565.05,2013.62,826,FALSE +748,Sandy Duval,sduvalkr@blogger.com,Female,99,CA,4453.99,,560,FALSE +749,Idaline Ayling,,Male,102,TX,9353.31,19121.24,,TRUE +750,Veronike Casali,vcasalikt@tripod.com,Male,112,TX,7659.83,7214.36,740,TRUE +751,Marieann Gladyer,mgladyerku@php.net,Female,61,TX,7051.88,1854.52,688,TRUE +752,Hughie Lyles,hlyleskv@flavors.me,Female,35,,847.11,10066.83,708,FALSE +753,Darlene Denisevich,ddenisevichkw@vinaora.com,Male,,TX,7684.77,17956.8,631,FALSE +754,Annette Nelle,,Male,,FL,7761.14,19170.88,690,TRUE +755,Brnaba Middas,,Female,0,NY,2713.19,15731.67,594,FALSE +756,Bonnie Gallimore,bgallimorekz@1688.com,Male,87,FL,8444.55,,684,TRUE +757,Darbee Aymeric,daymericl0@multiply.com,Male,113,FL,4387.18,16564.81,616,FALSE +758,Judye Adamowitz,,,96,TX,6233.87,10520.05,748,FALSE +759,Davide Sylvaine,dsylvainel2@smh.com.au,Male,22,CA,116.55,6341.44,592,TRUE +760,Raviv Hardeman,rhardemanl3@parallels.com,Male,89,TX,4484.36,15127.01,568,TRUE +761,Letta Pinnell,lpinnelll4@slate.com,,91,CA,5515.63,11214.45,694,TRUE +762,Sunny Amthor,samthorl5@chronoengine.com,Male,68,CA,3849.05,9437.93,813,FALSE +763,Reid Clemmen,,Female,39,CA,172.19,3832.38,602,TRUE +764,Taddeo Hayller,thayllerl7@rakuten.co.jp,Male,13,FL,4309.8,18764.96,620,TRUE +765,Calypso Menhci,cmenhcil8@upenn.edu,Female,52,TX,655.2,13423.88,759,TRUE +766,Logan Vannoort,lvannoortl9@photobucket.com,Male,82,FL,8864.34,5528.74,752,TRUE +767,Kali Feary,,Female,4,FL,9972.65,11114.35,716,FALSE +768,Baily Denning,,Male,76,CA,6517.61,16156.01,669,TRUE +769,Maximilianus Pindar,mpindarlc@cdbaby.com,Female,8,TX,6644.09,1028.29,554,FALSE +770,Marna Oguz,,,33,NY,5100.96,,622,FALSE +771,Rockey McGinnell,,Male,56,FL,9427.31,,715,FALSE +772,Gil Agnolo,gagnololf@sfgate.com,Male,101,,3615.13,,756,TRUE +773,Hephzibah Gilphillan,hgilphillanlg@tripod.com,Female,19,FL,3037.24,4964.11,552,TRUE +774,Coletta Crowson,ccrowsonlh@last.fm,Female,5,TX,2344.35,7901.84,714,FALSE +775,Rosetta Merwood,rmerwoodli@chronoengine.com,Female,101,NY,4432.87,1130.1,721,FALSE +776,D'arcy Sturton,dsturtonlj@last.fm,Female,,TX,3097.36,8694.71,802,FALSE +777,Alvera Weber,aweberlk@exblog.jp,Male,107,FL,4009.99,13811.76,788,TRUE +778,Sim Oxlee,soxleell@youtu.be,Female,47,FL,734.85,17331.35,735,TRUE +779,Ivett Corley,icorleylm@wufoo.com,Female,106,TX,2346.69,133.45,776,FALSE +780,Dalis Blackmore,,Male,6,CA,4581.53,6320.98,805,TRUE +781,Nichol Shuttell,nshuttelllo@epa.gov,Female,,TX,8973.59,4636.71,759,FALSE +782,Ursola Ivison,,Female,66,TX,8474.77,1409.63,714,FALSE +783,Lawton Birkwood,,Female,101,TX,2871.37,15441.65,778,FALSE +784,Birdie Neem,bneemlr@pcworld.com,Male,6,TX,8336.91,13483.48,652,FALSE +785,Danielle Jacques,djacquesls@nature.com,Male,42,FL,479.24,13676.77,,FALSE +,Lydie Stredwick,lstredwicklt@rambler.ru,Female,111,FL,944.73,17412.5,768,TRUE +787,Lothaire Tadlow,ltadlowlu@icq.com,Female,60,CA,6450.68,3266.71,661,TRUE +788,Letisha Steffens,lsteffenslv@sciencedaily.com,Male,63,TX,6831.64,15563.82,558,TRUE +789,Ann Urvoy,aurvoylw@sciencedirect.com,Female,31,TX,9901.18,17526.2,648,TRUE +790,Pete Burnitt,,Male,36,FL,9456.28,19802.37,719,TRUE +791,Orazio Pharrow,opharrowly@quantcast.com,Female,95,TX,,14477.65,584,TRUE +792,Godfrey De Witt,gdelz@arizona.edu,Male,28,TX,1674.42,1218.39,760,TRUE +793,Codi De Vile,cdem0@mayoclinic.com,Male,11,,725.98,796.19,763,FALSE +794,Allegra Mealing,amealingm1@hugedomains.com,Male,76,CA,4560.48,8421.25,607,FALSE +795,Trstram Quogan,tquoganm2@chronoengine.com,Female,65,TX,7392.48,13586.5,685,TRUE +796,Brooke Yockney,,,27,NY,5493.4,14607.74,729,TRUE +797,Boris Townby,btownbym4@fda.gov,Female,59,FL,6456.65,19709.93,599,TRUE +798,Gan Vignal,gvignalm5@soup.io,Male,57,TX,3882.48,,803,FALSE +799,Cullan Gresley,cgresleym6@nymag.com,Male,100,NY,,7779.34,583,FALSE +800,Lancelot LaBastida,llabastidam7@china.com.cn,Male,51,TX,2777.34,,673,FALSE +801,Gerhardine Rykert,grykertm8@vkontakte.ru,Female,32,CA,216.73,374.29,587,TRUE +802,Rozanne Pennrington,,Female,116,CA,61.76,12295.42,674,FALSE +803,Geraldine Hounsham,ghounshamma@cbc.ca,,5,TX,4287.47,248.02,822,TRUE +804,Levin Flaonier,lflaoniermb@taobao.com,Female,68,CA,9319.98,15285.34,612,FALSE +805,Tamarah Portt,,Male,63,TX,8932.28,,643,FALSE +806,Duky MacDonald,dmacdonaldmd@ow.ly,Male,97,NY,5200.1,5375.12,702,TRUE +807,Belia Kubas,,Female,50,TX,5723.13,11931.13,617,FALSE +808,Lisetta Ferrier,lferriermf@unesco.org,Male,,FL,1351.83,1392.74,750,TRUE +809,Garret Phoebe,gphoebemg@elpais.com,,21,TX,673.79,13151.09,725,FALSE +810,Marlo Welsby,mwelsbymh@cbsnews.com,Female,69,FL,1007.14,8607.82,740,TRUE +811,Gay Fridd,gfriddmi@networksolutions.com,Male,36,NY,367.6,16341.57,580,FALSE +812,Salomone Partkya,spartkyamj@xrea.com,Female,,NY,7710.98,15902.15,725,FALSE +813,Benetta Arents,barentsmk@istockphoto.com,Male,37,FL,1810.35,10443.33,563,FALSE +814,Peterus Waterland,pwaterlandml@macromedia.com,Male,8,TX,608.85,14478.22,714,FALSE +815,Donetta Really,dreallymm@google.co.jp,Female,118,CA,,4993.8,714,FALSE +816,Bryanty Wiersma,bwiersmamn@state.gov,Female,92,FL,2698.32,841.85,571,FALSE +817,Patrick Magrannell,pmagrannellmo@salon.com,Male,53,CA,3589.71,5951.59,631,TRUE +818,Ramsey Hastler,rhastlermp@about.com,,12,CA,8072.94,6605.41,829,FALSE +819,Lotty Heikkinen,lheikkinenmq@php.net,Female,19,CA,899.59,11353.95,,TRUE +820,Lizzie Quilligan,lquilliganmr@miibeian.gov.cn,Male,105,TX,5005.68,16818.66,733,FALSE +821,Saxe McCorkell,smccorkellms@pbs.org,Female,112,TX,7248.33,7427.15,789,TRUE +822,Ahmad McAsgill,amcasgillmt@ovh.net,Female,5,FL,211.86,5378.73,650,FALSE +823,Toby Sahnow,tsahnowmu@ox.ac.uk,Female,60,TX,2949.8,,823,TRUE +824,Krishna Trubshaw,,Male,,CA,6353.36,6860.33,723,TRUE +825,Jeth Vernazza,jvernazzamw@nytimes.com,Male,113,CA,1780.91,13528.84,704,FALSE +826,Ximenez Burfoot,xburfootmx@dell.com,Male,,TX,3965.03,10368.75,697,FALSE +827,Caitrin Giovanazzi,cgiovanazzimy@sun.com,Male,120,NY,964.92,18453.91,737,FALSE +828,Elfrieda Brims,ebrimsmz@timesonline.co.uk,Male,26,CA,83.33,19272.31,629,TRUE +829,Renate Crake,rcraken0@bluehost.com,Female,118,CA,1655.94,18990.69,658,FALSE +830,Doyle Badrick,dbadrickn1@illinois.edu,Male,120,FL,3686.01,9455.87,816,FALSE +831,Lanie Dupree,ldupreen2@ca.gov,Male,111,FL,9085.2,1234.73,697,FALSE +832,Herb Kindon,hkindonn3@list-manage.com,Male,51,TX,7415.32,7749.03,608,FALSE +833,Hillary Woolcocks,hwoolcocksn4@deviantart.com,Female,48,CA,9373.82,,780,FALSE +834,Cecily Noyes,cnoyesn5@va.gov,Female,21,,2382.37,18576.59,581,TRUE +835,Michaelina Kares,mkaresn6@livejournal.com,Female,45,NY,3508.49,18506.45,,TRUE +836,Jilli Wabb,jwabbn7@google.de,,42,CA,8464.04,9569.92,630,TRUE +837,Brigit Kiehnlt,bkiehnltn8@cnn.com,Female,38,TX,9883.3,11913,769,TRUE +838,Murdock Streater,mstreatern9@zdnet.com,Female,11,CA,3166.22,,682,FALSE +839,Gradey Fairy,gfairyna@bluehost.com,,6,CA,9917.01,4617.69,644,TRUE +840,Charla Johnsson,cjohnssonnb@addthis.com,Female,17,TX,9782.93,,786,TRUE +841,Davis Schirok,,Male,63,FL,8398.98,,777,TRUE +842,Philly Sommerville,,Female,,CA,2045.18,15081.23,809,FALSE +843,Samuele Bowell,sbowellne@reuters.com,Female,56,FL,2863.93,1814.35,560,TRUE +844,Bettina Dovidian,bdovidiannf@soundcloud.com,Female,8,FL,3045.55,4304.09,801,TRUE +845,Leola Benion,lbenionng@irs.gov,Male,32,FL,6989.16,15930.24,748,FALSE +846,Trev Nockalls,tnockallsnh@telegraph.co.uk,Male,79,TX,8410.56,,557,TRUE +847,Dido Cordey,,Male,78,CA,5486.25,3831.57,773,TRUE +848,Hilda Faulkes,hfaulkesnj@alibaba.com,Female,51,TX,5488.3,16818.71,552,FALSE +849,Daren Siveyer,dsiveyernk@about.me,Male,109,TX,2221.33,16283.58,612,TRUE +850,Levey Orrow,lorrownl@sciencedirect.com,Male,42,FL,2045.9,13602.72,803,TRUE +851,Leonore Dundon,ldundonnm@noaa.gov,Female,74,FL,4457.55,291.2,679,FALSE +852,Elfrida McKennan,,Female,109,CA,4955.9,,631,FALSE +853,Lesli Deverille,ldeverilleno@spotify.com,Female,114,NY,3352.78,7164.25,785,FALSE +854,Johnny Carle,jcarlenp@soup.io,Male,25,TX,651.01,6172.73,551,FALSE +855,Fleming Pendre,fpendrenq@com.com,Female,44,FL,5482.84,1420.58,756,FALSE +856,Rudd Darragon,rdarragonnr@seattletimes.com,Female,64,CA,1767.33,6768.74,594,FALSE +857,Sigfrid Pitrelli,spitrellins@hc360.com,Female,62,CA,924.04,14772.83,785,TRUE +858,Alexandr Bengall,abengallnt@livejournal.com,Female,18,TX,5014.99,5948.45,672,TRUE +859,Valaria Dummett,vdummettnu@stanford.edu,Male,67,CA,6918.91,16405.13,,TRUE +860,Nelli Drescher,ndreschernv@patch.com,Female,47,CA,6972.4,726.99,742,TRUE +861,Frasco Swepson,fswepsonnw@pen.io,Female,73,FL,5265.05,12977.82,827,TRUE +862,Aaren Fullom,afullomnx@hostgator.com,Female,72,CA,623.09,2225.46,728,FALSE +863,Lonnard Hulles,lhullesny@xinhuanet.com,Female,113,FL,1663.91,271.62,561,TRUE +864,Sherri Kershow,skershownz@soundcloud.com,Male,76,,4267.43,12646.23,711,FALSE +865,Rossy Bannerman,,Female,38,FL,1926.84,8339.31,634,TRUE +866,Laney Gookey,lgookeyo1@hao123.com,Male,62,CA,479.33,14790.55,604,FALSE +867,Maxie Filipowicz,mfilipowiczo2@vkontakte.ru,Female,72,TX,7073.16,6563.47,808,FALSE +868,Inness Frosch,ifroscho3@google.ca,Female,92,CA,3474.45,463.86,603,FALSE +869,Gawen Sturley,gsturleyo4@joomla.org,Female,39,,2779.05,207.92,710,TRUE +870,Norton Messingham,nmessinghamo5@msu.edu,Male,60,TX,2143.07,16059.39,607,TRUE +871,Augustina McDonough,amcdonougho6@slate.com,Male,92,CA,6867.93,3542.42,,TRUE +872,Lexine Pattle,lpattleo7@telegraph.co.uk,Male,78,CA,9521.55,4303.44,567,FALSE +873,Torey Rodriguez,trodriguezo8@yellowbook.com,Male,64,NY,8783.72,12094.04,618,FALSE +874,Sarajane Cardello,scardelloo9@eventbrite.com,Female,,FL,5168.48,19435.83,797,TRUE +875,Ernestine McSkeagan,emcskeaganoa@yandex.ru,Male,23,CA,7790.29,2899.66,825,TRUE +876,Isadora Kippins,ikippinsob@nsw.gov.au,,31,CA,6513.75,5887.59,616,TRUE +877,Babette Fido,bfidooc@canalblog.com,Male,22,CA,3249.08,17131.26,551,FALSE +878,Bunny Capeling,bcapelingod@newyorker.com,Male,96,TX,9371.3,16335.17,,TRUE +879,Ambrosi Meineking,ameinekingoe@oracle.com,Female,63,CA,3664.83,2712.21,767,TRUE +880,Glenine Gouch,ggouchof@icio.us,Female,79,NY,9551.13,18902.04,789,FALSE +881,Kaiser Aylen,kaylenog@usda.gov,Female,80,FL,442.2,4153.36,798,TRUE +882,Clemmy Burcher,,Female,13,TX,3940.31,12666.3,664,TRUE +883,Freida Merton,fmertonoi@java.com,Male,107,FL,9992.01,17123.82,737,FALSE +884,Laurella Mozzi,lmozzioj@nifty.com,Male,14,CA,3426.92,,797,FALSE +885,Martie Sydenham,msydenhamok@4shared.com,Male,117,TX,8620.82,627.97,772,TRUE +886,Beale Bompas,,Female,12,TX,1903.1,9046.46,690,TRUE +887,Fraze Giacopetti,fgiacopettiom@webeden.co.uk,Male,,FL,3034.96,19142.36,604,FALSE +888,Hogan Glowach,hglowachon@spotify.com,Female,108,TX,1388.97,5300.21,786,TRUE +889,Adolf Rushmer,,Female,,FL,8651.19,4753.81,679,TRUE +890,Zackariah Thacker,zthackerop@hexun.com,Female,38,TX,7987.6,10950.26,688,FALSE +891,Noll Bilofsky,nbilofskyoq@mtv.com,Male,111,FL,309.3,15014.9,589,FALSE +892,Roxie Monro,rmonroor@kickstarter.com,Male,81,FL,7427.13,13382.94,775,TRUE +893,Bill Bennetts,bbennettsos@diigo.com,Male,47,CA,7537.53,,578,FALSE +894,Merwyn Devinn,,Female,29,FL,4245.03,,650,FALSE +895,Leontine Pasek,lpasekou@bloglines.com,Male,85,TX,5907.76,6910.14,,FALSE +896,Ceciley Barfield,cbarfieldov@smugmug.com,Female,,FL,6665.27,18050.56,605,FALSE +897,Tim Kingswood,tkingswoodow@twitter.com,Male,16,FL,3150.92,14662.33,,TRUE +898,Bronny Kobelt,bkobeltox@washington.edu,Male,34,FL,6124.52,2106,577,FALSE +899,Red Sammars,rsammarsoy@cocolog-nifty.com,Male,82,NY,5998.89,18509.85,753,TRUE +900,Irina Crosser,icrosseroz@ehow.com,Male,62,TX,623.94,16864.35,589,FALSE +901,Alwyn Burnsall,aburnsallp0@answers.com,Female,92,,5221.69,2312.21,,TRUE +902,Tasia Ingry,tingryp1@diigo.com,,32,TX,8615.39,13727.08,726,FALSE +903,Suki Durkin,sdurkinp2@goo.gl,Female,,NY,5996.13,17051.68,653,TRUE +904,Sharity Boome,sboomep3@prlog.org,Male,48,TX,5199.58,8642.53,759,TRUE +905,Cameron Keith,ckeithp4@wp.com,Male,93,NY,9190.54,15397.98,697,TRUE +906,Freeland McCathie,fmccathiep5@nbcnews.com,Male,68,TX,1862.73,19703.94,648,TRUE +907,Marys Owenson,,Female,12,CA,3889.64,7825.37,743,TRUE +908,Dun Cocozza,dcocozzap7@alibaba.com,,77,FL,,6389.41,570,FALSE +909,Marlee Arnolds,marnoldsp8@pcworld.com,Female,101,TX,7339.55,14824.25,668,FALSE +910,Elvira Longbone,elongbonep9@npr.org,,60,CA,7007.78,6845.29,778,TRUE +911,Ailina Espino,aespinopa@omniture.com,Male,57,FL,1624.91,19667.92,578,FALSE +912,Alexander Carlsen,acarlsenpb@sohu.com,Female,119,CA,1543.77,9265.82,611,TRUE +913,Jobyna Jindacek,jjindacekpc@hostgator.com,Female,28,FL,9155.67,7344.09,662,TRUE +914,Tomasine Winton,twintonpd@cargocollective.com,,52,TX,4894.23,1316.04,624,TRUE +915,Ruthy Hickin,rhickinpe@opera.com,Female,93,FL,3277.62,14403.71,,TRUE +916,Melvyn Androsik,mandrosikpf@blog.com,Female,105,CA,9949.32,6854.72,732,FALSE +917,Liuka McDowell,lmcdowellpg@fotki.com,Female,37,NY,419.18,16206.53,,FALSE +918,Cyrille Mennear,cmennearph@livejournal.com,Female,102,NY,5546.75,3862.02,705,TRUE +919,Kimberley Banck,kbanckpi@vinaora.com,Male,104,FL,713.29,11352.79,675,FALSE +920,Christan Lummus,clummuspj@imageshack.us,,58,CA,2658.73,5031.15,717,TRUE +921,Kathye Floyd,kfloydpk@wordpress.org,Male,65,TX,3994.49,6168.5,769,FALSE +922,Benton Vannuccini,,Female,63,,3805.12,15243.75,584,FALSE +923,Ethelbert Lembke,elembkepm@themeforest.net,Female,0,FL,8611.94,5983.85,763,FALSE +924,Xenos Di Baudi,xdipn@360.cn,Female,75,TX,7938.25,13419.31,740,FALSE +925,Judon Ince,jincepo@mozilla.org,Female,57,CA,2870.69,7013.91,,TRUE +926,Jerrylee Screach,jscreachpp@amazon.com,Male,109,NY,9089.71,5103.68,696,FALSE +927,Agnesse Alfwy,aalfwypq@topsy.com,Female,,TX,1238.09,16616.64,697,FALSE +928,Kristal Hanstock,khanstockpr@dailymotion.com,Female,83,FL,3460.16,2823.92,632,FALSE +929,Cymbre Lawrinson,clawrinsonps@chron.com,Male,47,FL,9734.57,18379.37,558,TRUE +930,Mace Laugier,mlaugierpt@geocities.jp,Male,78,NY,8915.23,12623.36,653,FALSE +931,Kissie Ensor,,Female,,CA,766.93,4228.15,648,FALSE +932,Felice Yukhtin,fyukhtinpv@webs.com,Female,43,TX,5659.66,9222.51,551,TRUE +933,Gabriel McIlvoray,gmcilvoraypw@seattletimes.com,Male,104,TX,4244.14,5433.73,645,TRUE +934,Raimund Danzelman,rdanzelmanpx@gov.uk,Female,11,TX,5261.08,8453.2,746,FALSE +935,Alistair Blackborn,,Female,,,4395.08,8760.25,583,TRUE +936,Minette Bernardini,,Male,3,CA,3740.02,5947.46,717,TRUE +937,Elfrida Dayne,edayneq0@yahoo.co.jp,Female,41,FL,9700.29,11840.51,595,TRUE +938,Luther Glenister,lglenisterq1@edublogs.org,Female,1,CA,1837.81,8078.65,,TRUE +939,Garnette MacGruer,gmacgruerq2@jigsy.com,Male,27,CA,9058.77,4851.8,588,FALSE +940,John Donnison,jdonnisonq3@fc2.com,,65,TX,5601.81,9418.45,821,TRUE +941,Vladamir Beales,vbealesq4@addthis.com,Male,42,,1473.28,6538.01,693,FALSE +942,Ailene Szymanzyk,aszymanzykq5@theglobeandmail.com,Female,46,TX,1629.43,1415.11,563,FALSE +943,Benn Abeles,babelesq6@dmoz.org,Female,5,FL,8661.42,3329.2,764,FALSE +944,Oralie O'Neal,,Female,79,TX,8135.58,1331.07,797,FALSE +945,Jose Ambrus,,Female,2,CA,1869.96,2334.43,786,FALSE +946,Tye Gidley,tgidleyq9@cdc.gov,Female,65,NY,9438.6,16186.1,790,FALSE +947,Husein Diggens,hdiggensqa@shop-pro.jp,Female,,TX,4994.13,,558,TRUE +948,Kareem McClintock,kmcclintockqb@wix.com,,88,CA,9308.09,12177.22,,TRUE +949,Connor Gerardet,cgerardetqc@toplist.cz,Female,99,CA,3299.82,6239.96,600,FALSE +950,Brodie Lawly,blawlyqd@cafepress.com,Female,35,FL,3923.58,10156.18,745,TRUE +951,Skipton Mulrean,,Female,114,NY,7665.65,9885.57,,TRUE +952,Mari Cordner,mcordnerqf@economist.com,Male,36,NY,80.81,3778.14,788,TRUE +953,Urson Gerry,ugerryqg@google.cn,Male,61,NY,1998.48,13152.22,748,FALSE +954,Franz McInally,fmcinallyqh@slate.com,Male,65,CA,3036.83,2658.09,623,TRUE +955,Krissie Stollard,kstollardqi@wix.com,Female,112,CA,6193.46,16286.19,590,FALSE +956,Goldarina Amiss,gamissqj@163.com,Female,,CA,7428.87,1284.55,695,FALSE +957,Jen McGeoch,jmcgeochqk@geocities.com,Female,72,CA,7381.54,8476.88,750,FALSE +958,Helaine Arens,harensql@psu.edu,Male,94,NY,2172.71,15325.28,742,FALSE +959,Isak Baudinet,,Male,118,TX,,17024.1,814,FALSE +960,Auberon Guerreiro,aguerreiroqn@google.cn,Female,,CA,9500.62,14589.38,814,FALSE +961,Bevin Spensly,bspenslyqo@tuttocitta.it,Male,75,CA,7474.05,,653,FALSE +962,Robb Fowlestone,rfowlestoneqp@elegantthemes.com,Male,97,NY,4670.52,8101.66,813,FALSE +963,Opalina Aymes,,Female,83,TX,639.22,8315.02,818,FALSE +964,Cecilius Swithenby,cswithenbyqr@cloudflare.com,Female,80,NY,8041.63,7131.43,614,FALSE +965,Toby Malcolm,tmalcolmqs@answers.com,Female,63,NY,4675.24,13879.09,720,TRUE +966,Rusty Adamovitz,radamovitzqt@wp.com,Female,107,TX,,3104.37,653,FALSE +967,Albina Sarra,asarraqu@webnode.com,Male,46,CA,5380.62,12388.26,561,TRUE +968,Alleen Skpsey,askpseyqv@infoseek.co.jp,Male,2,TX,2709.65,,791,TRUE +969,Marielle Coddrington,mcoddringtonqw@1688.com,Female,3,CA,4350.56,4955.52,,FALSE +970,Derril Rego,dregoqx@ihg.com,Female,,TX,1427.95,,665,TRUE +971,Barbaraanne Flitcroft,bflitcroftqy@marriott.com,Male,62,CA,7778.02,9967.24,632,TRUE +972,Jeannette Dunning,jdunningqz@fema.gov,,96,NY,6413.31,17397.09,703,TRUE +,Silvia Rosoni,srosonir0@unc.edu,Male,5,FL,2731.71,6153.71,695,FALSE +974,Charo Falcus,cfalcusr1@altervista.org,Male,108,FL,7713.7,7815.22,756,FALSE +975,Niel Oultram,noultramr2@yellowpages.com,Male,104,TX,109.46,17161.02,795,TRUE +976,Elsinore Florentine,eflorentiner3@delicious.com,Male,4,TX,5631.89,1621.84,663,FALSE +977,Edgard Gilbody,egilbodyr4@dedecms.com,Male,100,CA,260.15,3051.48,633,FALSE +978,Gilles Creenan,gcreenanr5@naver.com,Male,104,FL,7252.68,2804.18,707,FALSE +979,Rea Rainsbury,rrainsburyr6@sphinn.com,Female,95,CA,6855.59,15355.99,718,TRUE +980,Chaunce Vlasyev,cvlasyevr7@mysql.com,Female,55,NY,9173.88,4699.26,748,TRUE +981,Matias Behrens,mbehrensr8@goodreads.com,Male,21,TX,3028.56,16154.42,571,FALSE +982,Alaster Curphey,acurpheyr9@liveinternet.ru,Male,,NY,8491.04,6625.25,592,FALSE +983,Silvain Taunton.,stauntonra@google.ru,Female,104,CA,8302.75,,,TRUE +984,Arielle Aggis,aaggisrb@time.com,Female,114,TX,4144.43,4328.39,555,FALSE +985,Zeke Acum,zacumrc@icio.us,Female,111,FL,3858.68,14449.69,649,TRUE +986,Rosaleen Vowden,rvowdenrd@geocities.jp,Male,103,NY,625.46,12763.95,698,TRUE +987,Lotta Oen,loenre@addtoany.com,Female,87,TX,5968.32,63.24,715,FALSE +988,Amerigo Hadkins,ahadkinsrf@goodreads.com,Female,33,TX,1524.02,14511.27,606,TRUE +989,Urbano Izkovici,uizkovicirg@networkadvertising.org,,,TX,4174.49,,692,TRUE +990,Boony Antoniazzi,bantoniazzirh@w3.org,Male,71,TX,5022.93,2772.32,583,FALSE +991,Land Pamphilon,lpamphilonri@yandex.ru,Male,,FL,52.04,7427.4,672,FALSE +992,Lorette Speirs,lspeirsrj@ted.com,Female,90,CA,,17083.97,624,TRUE +993,Leeland Lewty,llewtyrk@jimdo.com,Female,39,NY,1537.11,11346.58,687,FALSE +994,Sephira Shrawley,sshrawleyrl@joomla.org,Male,96,CA,1519.35,7486.92,,TRUE +995,Allayne Fryman,afrymanrm@ucla.edu,Female,43,NY,4746.33,14921.35,742,FALSE +996,Elihu Fawley,efawleyrn@tumblr.com,,37,NY,9424.85,15674.18,606,FALSE +997,Taylor Trounce,ttrouncero@theglobeandmail.com,Female,61,TX,9613.77,10477.52,,FALSE +998,Demetria Zarb,dzarbrp@netscape.com,Male,82,TX,9463.6,3779.07,672,FALSE +999,Loren Steen,lsteenrq@google.ca,Female,111,FL,765.64,14517.48,646,TRUE +1000,Aridatha Varsey,avarseyrr@rakuten.co.jp,,14,FL,5395.75,,568,FALSE diff --git a/pandas_datapreprocessing_imputation.ipynb b/pandas_datapreprocessing_imputation.ipynb new file mode 100644 index 0000000..5cf295b --- /dev/null +++ b/pandas_datapreprocessing_imputation.ipynb @@ -0,0 +1,308 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Null values by variable:\n", + "------------------------\n" + ] + }, + { + "data": { + "text/plain": [ + "customer_id 18\n", + "name 0\n", + "email 158\n", + "sex 111\n", + "age 113\n", + "state 40\n", + "cheq_balance 23\n", + "savings_balance 96\n", + "credit_score 78\n", + "special_offer 0\n", + "dtype: int64" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "\n", + "# Importing the dataset\n", + "dataset_filename = '/Users/ERexhepa/Downloads/mock_bank_data_original.csv'\n", + "df = pd.read_csv(dataset_filename)\n", + "\n", + "# Summarize missing values\n", + "print 'Null values by variable:'\n", + "print '------------------------'\n", + "df.isnull().sum()" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Null values by variable:\n", + "------------------------\n" + ] + }, + { + "data": { + "text/plain": [ + "customer_id 18\n", + "name 0\n", + "email 158\n", + "sex 111\n", + "age 113\n", + "state 40\n", + "cheq_balance 23\n", + "savings_balance 96\n", + "credit_score 78\n", + "special_offer 0\n", + "dtype: int64" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "\n", + "# Importing the dataset\n", + "dataset_filename = '/Users/ERexhepa/Downloads/mock_bank_data_original.csv'\n", + "df = pd.read_csv(dataset_filename)\n", + "\n", + "# Summarize missing values\n", + "print 'Null values by variable:'\n", + "print '------------------------'\n", + "df.isnull().sum()" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "\n", + "# Load the dataset\n", + "df = pd.read_csv('/Users/ERexhepa/Downloads/mock_bank_data_original.csv')\n", + "\n", + "####################\n", + "### Drop columns ###\n", + "####################\n", + "\n", + "# Drop all rows with NaN in state column\n", + "df = df[pd.notnull(df['state'])]\n", + "\n", + "##################################\n", + "### Replace with column median ###\n", + "##################################\n", + "\n", + "# Replace credit_score NaN with median credit_score\n", + "df['credit_score'] = df['credit_score'].fillna(df['credit_score'].median())\n", + "\n", + "################################\n", + "### Drop unnecessary columns ###\n", + "################################\n", + "\n", + "# Remove custoemr_id, name, and email columns\n", + "for col in ['customer_id', 'name', 'email']:\n", + " df = df.drop(col, axis=1)\n", + "\n", + "################################\n", + "### Save new dataset to file ###\n", + "################################\n", + "\n", + "# Output modified dataset to CSV\n", + "df.to_csv('mock_bank_data_original_PART1.csv', index=False)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Overall cheq_balance mean: 4938.91\n", + "Overall savings_balance mean: 9603.64\n" + ] + } + ], + "source": [ + "print 'Overall cheq_balance mean:', df['cheq_balance'].mean().round(2)\n", + "print 'Overall savings_balance mean:', df['savings_balance'].mean().round(2)\n", + "\n", + "#Overall cheq_balance mean: 4938.91\n", + "#Overall savings_balance mean: 9603.64" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cheq_balance mean by state:\n", + "---------------------------\n" + ] + } + ], + "source": [ + "print 'cheq_balance mean by state:'\n", + "print '---------------------------'\n", + "#print df.groupby(['state']).mean().groupby('state')['cheq_balance'].mean().round(2)\n", + "\n", + "#cheq_balance mean by state:\n", + "#---------------------------\n", + "#state\n", + "#CA 4637.23\n", + "#FL 4993.99\n", + "#NY 4932.80\n", + "#TX 5175.78\n", + "#Name: cheq_balance, dtype: float64" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "savings_balance mean by state:\n", + "------------------------------\n" + ] + } + ], + "source": [ + "print 'savings_balance mean by state:'\n", + "print '------------------------------'\n", + "#print df.groupby(['state']).mean().groupby('state')['savings_balance'].mean().round(2)\n", + "\n", + "#savings_balance mean by state:\n", + "#------------------------------\n", + "#state\n", + "#CA 9174.56\n", + "#FL 9590.59\n", + "#NY 10443.61\n", + "#TX 9611.70\n", + "#Name: savings_balance, dtype: float64" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "# Replace cheq_balance NaN with mean cheq_balance of same state\n", + "df['cheq_balance'] = df.groupby('state').cheq_balance.transform(lambda x: x.fillna(x.mean()))\n", + "df.cheq_balance = df.cheq_balance.round(2)\n", + "\n", + "# Replace savings_balance NaN with mean savings_balance of same state\n", + "df['savings_balance'] = df.groupby('state').savings_balance.transform(lambda x: x.fillna(x.mean()))\n", + "df.savings_balance = df.savings_balance.round(2)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "# Output modified dataset to CSV\n", + "df.to_csv('mock_bank_data_original_PART2.csv', index=False)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 2", + "language": "python", + "name": "python2" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.12" + }, + "toc": { + "colors": { + "hover_highlight": "#DAA520", + "navigate_num": "#000000", + "navigate_text": "#333333", + "running_highlight": "#FF0000", + "selected_highlight": "#FFD700", + "sidebar_border": "#EEEEEE", + "wrapper_background": "#FFFFFF" + }, + "moveMenuLeft": true, + "nav_menu": { + "height": "12px", + "width": "252px" + }, + "navigate_menu": true, + "number_sections": true, + "sideBar": true, + "threshold": 4, + "toc_cell": false, + "toc_section_display": "block", + "toc_window_display": false, + "widenNotebook": false + } + }, + "nbformat": 4, + "nbformat_minor": 1 +}