Open In App

Python | Geographical plotting using plotly

Improve
Improve
Like Article
Like
Save
Share
Report

Geographical plotting is used for world map as well as states under a country. Mainly used by data analysts to check the agriculture exports or to visualize such data.

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.

Command to install plotly:

pip install plotly 

 

Below is the implementation:




# Python program to plot 
# geographical data using plotly
  
# importing all necessary libraries
import plotly.plotly as py
import plotly.graph_objs as go
import pandas as pd
  
# some more libraries to plot graph
from plotly.offline import download_plotlyjs, init_notebook_mode, iplot, plot
  
# To establish connection
init_notebook_mode(connected = True)
  
  
# type defined is choropleth to
# plot geographical plots
data = dict(type = 'choropleth',
  
            # location: Arizoana, California, Newyork
            locations = ['AZ', 'CA', 'NY'],
              
            # States of USA
            locationmode = 'USA-states',
              
            # colorscale can be added as per requirement
            colorscale = 'Portland',
              
            # text can be given anything you like
            text = ['text 1', 'text 2', 'text 3'],
            z = [1.0, 2.0, 3.0],
            colorbar = {'title': 'Colorbar Title Goes Here'})
              
layout = dict(geo ={'scope': 'usa'})
  
# passing data dictionary as a list 
choromap = go.Figure(data = [data], layout = layout)
  
# plotting graph
iplot(choromap)


Output:
map



Last Updated : 26 Jun, 2018
Like Article
Save Article
Previous
Next
Share your thoughts in the comments
Similar Reads