In this article, we will learn how to set colorbar position for a choropleth map in Python using Plotly.
Color bar are gradients that go from bright to dark or the other way round. They are great for visualizing data that go from low to high, like income, temperature, or age. Choropleth maps are used to plot maps with shaded or patterned areas which are colored, shaded or patterned in relation to a data variable. They are composed of colored polygons. They are used for representing spatial variations of a quantity over a geographical area.
Here we will discuss, how to set colorbar position for a choropleth map using different examples to make it more clear.
Syntax: # set colorbar position
- fig.update_layout(coloraxis_colorbar_x = float value)
- fig.update_layout(coloraxis_colorbar_y = float value)
Example 1: Set colorbar position for X-axis
Python3
# importing libraries import plotly.express as px # figure setup using dataset fig = px.choropleth(locations = [ "CA" , "TX" , "NY" ], locationmode = "USA-states" , color = [ 1 , 2 , 3 ], scope = "usa" , title = "GeeksforLazyroar" ) # set colorbar position for X-axis fig.update_layout(coloraxis_colorbar_x = 0.26 ) fig.show() |
Output:
Example 2: Set colorbar position for Y-axis
Python3
# importing packages import plotly.express as px # using gapminder datasheet. df = px.data.gapminder().query( "year==2007" ) # figure setup fig = px.choropleth(df, locations = "iso_alpha" , # lifeExp is a column of gapminder color = "lifeExp" , # column to add to hover information hover_name = "country" , color_continuous_scale = px.colors.sequential.Plasma) # set colorbar position for Y-axis fig.update_layout(coloraxis_colorbar_y = - 0.3 ) fig.show() |
Output:
Example 3: Set color-bar position for X-axis and Y-axis at the same time
Here we can also see that this method is also applicable to another graph too.
Python3
# importing packages import plotly.express as px # using the gapminder dataset data = px.data.gapminder() data_canada = data[data.country = = 'Canada' ] # plotting the bar chart fig = px.scatter(data_canada, x = 'year' , y = 'pop' , hover_data = [ 'lifeExp' , 'gdpPercap' ], color = 'lifeExp' , labels = { 'pop' : 'population of Canada' }, height = 400 , title = "GeeksforLazyroar" ) # set colorbar position for X-axis fig.update_layout(coloraxis_colorbar_x = 0.9 ) # set colorbar position for Y-axis fig.update_layout(coloraxis_colorbar_y = 0.1 ) fig.show() |
Output: