Open In App

Plotting graphs using Python’s plotly and cufflinks module

Last Updated : 04 Sep, 2024
Comments
Improve
Suggest changes
Like Article
Like
Report

plotly is a Python library which is used to design graphs, especially interactive graphs. It can plot various graphs and charts like histogram, barplot, boxplot, spreadplot and many more. It is mainly used in data analysis as well as financial analysis. plotly is an interactive visualization library.

cufflinks connects plotly with pandas to create graphs and charts of dataframes directly.

choropleth is used to describe geographical plotting of USA. choropleth is used in the plotting of world maps and many more. Let’s plot different types of plots like boxplot, spreadplot, etc. using plotly and cufflinks.

Command to install plotly:

pip install cufflinks plotly                                                                                                                                            

Command to install cufflinks:

pip install plotly                                       

Code #1:

Show dataframe

Python
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

%matplotlib inline
from plotly import __version__
import cufflinks as cf

from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot

# to get the connection
init_notebook_mode(connected=True)

# plotly also serves online,
# but we are using just a sample
cf.go_offline()

# creating dataframes
df = pd.DataFrame(np.random.randn(100, 4), columns='A B C D'.split())

df2 = pd.DataFrame({'Category': ['A', 'B', 'C'], 'Values': [32, 43, 50]})
df2.head()


Output:

dataframe2

Code #2:

Normal Plot

Python
# plotly function
df.iplot()

Output:

graph

Code #3:

Scatter Plot

Python
# markers are made to point in the graph
df.iplot(kind ='scatter', x ='A', y ='B', mode ='markers')

Output:

marker

Code #4:

Box Plot

Python
# boxplot
df.iplot(kind ='box')

Output:

box

Code #5:

Plot dataframes

Python
# creating dataframe with three axes
df3 = pd.DataFrame({'x':[1, 2, 3, 4, 5],
                    'y':[10, 20, 30, 20, 10],
                    'z':[5, 4, 3, 2, 1]})

Output:

dataframe

Code #6:

Surface plot

Python
# surface plot
# colorscale:red(rd), yellow(yl), blue(bu)
df3.iplot(kind ='surface', colorscale ='rdylbu')

Output:

graph


Next Article
Article Tags :
Practice Tags :

Similar Reads