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Plotting graphs using Python’s plotly and cufflinks module

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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.

cufflink 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 plotly 

Command to install cufflink:

pip install cufflink

 

Code #1: Show dataframe




# import all necessary libraries
import pandas as pd
import numpy as np
  
% 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




# plotly function
df.iplot()

Output:
graph
 
Code #3: Scatter Plot




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

Output:
marker
 
Code #4: Box Plot




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

Output:
box
 
Code #5: Plot dataframes




# 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




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

Output:
graph


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Last Updated : 06 Sep, 2021
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