import plotly_expressas px

data= px.data.gapminder()

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

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

fig.show()

### Customize bar chart with plotly express

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

import plotly_expressas px

data= px.data.gapminder()

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

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

hover_data=['lifeExp','gdpPercap'],color='lifeExp',

labels={'pop':'population of Canada'},height=400)

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

hover_data=['lifeExp','gdpPercap'],color='lifeExp',

labels={'pop':'population of Canada'},height=400)

fig.show()

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

import plotly_expressas px

tips= px.data.tips()

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

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

fig.show()

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

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`.

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"],"time": ["Lunch","Dinner"]})

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"],

"time": ["Lunch","Dinner"]})

fig.show()

To learn more, see the*link to px.bar reference page*.

When data are not available aspandas DataFrame, it is also possible to use the more generic`go.Bar` function from`plotly.graph_objs`.

When data are not available astidy dataframes, it is also possible to use the more generic`go.Bar` function from`plotly.graph_objs`.

import plotly.graph_objsas go

animals=['giraffes','orangutans','monkeys']

fig= go.Figure([go.Bar(x=animals,y=[20,14,23])])

fig

fig.show()

go.Bar(name='SF Zoo',x=animals,y=[20,14,23]),

go.Bar(name='LA Zoo',x=animals,y=[12,18,29])

])

fig.update(layout_barmode='group')

go.Bar(name='SF Zoo',x=animals,y=[20,14,23]),

go.Bar(name='LA Zoo',x=animals,y=[12,18,29])

])

fig.update(layout_barmode='stack')

x= ['Product A','Product B','Product C']

y= [20,14,23]

data= [go.Bar(x=x,y=y,

text=['27% market share','24% market share','19% market share'])]

fig= go.Figure(data=data)

fig= go.Figure(data=[go.Bar(x=x,y=y,

text=['27% market share','24% market share','19% market share'])])

fig.update_traces(marker_color='rgb(158,202,225)',marker_line_color='rgb(8,48,107)',

marker_line_width=1.5,opacity=0.6)

fig.update(layout_title_text='January 2013 Sales Report')

fig

fig.show()

x= ['Product A','Product B','Product C']

y= [20,14,23]

data= [go.Bar(

x=x,

y=y,

color='rgb(8,48,107)',

width=1.5),

),

)]

fig= go.Figure(data=data)

fig

fig.show()

)

data= [trace0, trace1]

fig= go.Figure(data=data)

fig= go.Figure(data=[trace0, trace1])

fig.update(layout_barmode='group',layout_xaxis_tickangle=-45)

fig

x=['Feature A','Feature B','Feature C',

'Feature D','Feature E'],

y=[20,14,23,25,22],

marker_color=colors

marker_color=colors# marker color can be a single color value or an iterable

)

fig= go.Figure(data=[trace0])

fig.update(layout_title_text='Least Used Feature')

fig

trace0= go.Bar(

x=[1,2,3,5.5,10],

y=[10,8,6,4,2],

width=[0.8,0.8,0.8,3.5,4]

width=[0.8,0.8,0.8,3.5,4]# customize width here

)

fig= go.Figure(data=[trace0])

fig

fig.show()

*I find this example not very good, because I think I would instead plot negative values for the expenses instead of changing the base. Can we come up with a better idea?*

import plotly.graph_objsas go

years= ['2016','2017','2018']

trace0= go.Bar(x=years,y=[500,600,700],

base=[-500,-600,-700],

base=[-500,-600,-700],

marker_color='red',

name='expenses')

name='expenses')

trace1= go.Bar(x=years,y=[300,400,700],

base=0,

marker_color='blue',

)

fig= go.Figure(data=[trace0, trace1])

fig

fig.show()

In this example several parameters of the layout as customized, hence it is convenient to use directly the`go.Layout(...)` constructor instead of calling`fig.update`.

import plotly.graph_objsas go

),

barmode='group',

bargap=0.15,

bargap=0.15,# gap between bars of adjacent location coordinates.

)

fig= go.Figure(data=data,layout=layout)

fig

fig.show()

fig= go.Figure(data=data,layout=layout)

fig.update_traces(marker_line_width=2)

fig

fig.show()

With "relative" barmode, the bars are stacked on top of one another, with negative values

below the axis, positive values above.

x= [1,2,3,4]

fig= go.Figure(data=data)

fig.update(layout_barmode='relative',layout_title_text='Relative Barmode')

fig