permalink:python/bar-charts/

thumbnail:thumbnail/bar.jpg

title:Bar Charts | plotly

v4upgrade:true

In a bar plot, each row of the DataFrame is represented as a rectangular mark.

importplotly_expressas px

importplotly.expressas px

data_canada= px.data.gapminder().query("country == 'Canada'")

fig= px.bar(data_canada,x='year',y='pop')

fig.show()

The bar plot can be customized using keyword arguments*TODO here link to meta doc page on customizing plotly plots?*.

importplotly_expressas px

importplotly.expressas px

data= px.data.gapminder()

data_canada= data[data.country=='Canada']

When several rows share the same value of`x` (here Female or Male), the rectangles are stacked on top of one another by default.

importplotly_expressas px

importplotly.expressas px

tips= px.data.tips()

fig= px.bar(tips,x="sex",y="total_bill",color='time')

fig.show()

import plotly.expressas px

fig= px.bar(tips,x="sex",y="total_bill",color='smoker',barmode='group',

height=400)

fig.show()

Use the keyword arguments`facet_row` (resp.`facet_col`) to create facetted subplots, where different rows (resp. columns) correspond to different values of the dataframe column specified in`facet_row`.

import plotly.expressas px

fig= px.bar(tips,x="sex",y="total_bill",color="smoker",barmode="group",

facet_row="time",facet_col="day",

category_orders={"day": ["Thur","Fri","Sat","Sun"],