How to preprocess string data within a Pandas DataFrame?

How to search a value within a Pandas DataFrame row?

Last Updated : 01 Dec, 2021

In this article, we will see how to search a value within Pandas DataFrame row in Python.

Importing Libraries and Data

Here we are going to import the required module and then read the data file as dataframe.

The link to dataset used is here

Python3

# importing pandas as ps
import pandas as pd

# importing data using .read_csv() method
df = pd.read_csv("data.csv")

Output:

Searching a Value

Here we will search the column name with in the dataframe.

Syntax : df[df['column_name'] == value_you_are_looking_for]

where df is our dataFrame

We will search all rows which have a value "Yes" in purchased column.

Python3

df[df["Purchased"] == "Yes"]
# This line of code will print all rows
# which satisfy the condition df["Purchased"] == "Yes"

# In other words df["Purchased"] == "Yes"
# will return a boolean either true or false.

# if it returns true then we will print that
# row otherwise we will not print the row.

Output:

We can also use more than one condition to search a value. Lets see a example to find all rows which have Age value between 35 and 40 inclusive.

Syntax : df[condition]

where df is our dataFrame

Python3

df[(df["Age"] >= 35) & (df["Age"] <= 40)]

# This line of code will return all
# rows which satisfies both the conditions
# ie value of age >= 35 and value of age <= 40

Output:

How to preprocess string data within a Pandas DataFrame?

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