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:
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
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: