Open In App

plotly.express.scatter_geo() function in Python

Last Updated : 17 Jul, 2020
Improve
Improve
Like Article
Like
Save
Share
Report

Plotly library of Python can be very useful for data visualization and understanding the data simply and easily. Plotly graph objects are a high-level interface to plotly which are easy to use.

plotly.express.scatter_geo() function

This function is used to plot geographical data onto the maps.

Syntax: plotly.express.scatter_geo(data_frame=None, lat=None, lon=None, locations=None, locationmode=None, color=None, text=None, hover_name=None, hover_data=None, custom_data=None, size=None, title=None, template=None, width=None, height=None)

Parameters:

data_frame: DataFrame or array-like or dict needs to be passed for column names.

lat: This parameter is used to position marks according to latitude on a map.

lon: This parameter is used to position marks according to longitude on a map.

locations: This parameter is interpreted according to locationmode and mapped to longitude/latitude.

locationmode: This parameter determines the set of locations used to match entries in locations to regions on the map.

color: This parameters assign color to marks.

size: This parameter is used to assign mark sizes. It is either a name of a column in data_frame, or a pandas Series or array_like object.

title: This parameter sets the title of the figure.

width: This parameter sets the width of the figure

height: This parameter sets the height of the figure.

Example 1:

Python3




import plotly.express as px
  
  
df = px.data.gapminder().query("year == 2007")
  
plot = px.scatter_geo(df, locations="iso_alpha")
plot.show()


Output:

Example 2: Using the size and color argument

Python3




import plotly.express as px
  
  
df = px.data.gapminder().query("year == 2007")
  
plot = px.scatter_geo(df, locations="iso_alpha",
                      size="gdpPercap",
                      color = "country")
plot.show()


Output:



Like Article
Suggest improvement
Previous
Next
Share your thoughts in the comments

Similar Reads