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Interactive Histograms and Distributions

Why interactive distributions

Interactive distributions help you:

  • zoom into interesting ranges
  • inspect outliers
  • compare groups with hover tooltips

Histogram

Histogram
import pandas as pd
import plotly.express as px
 
df = px.data.tips()
 
fig = px.histogram(
    df,
    x="total_bill",
    nbins=30,
    title="Total bill distribution",
)
fig.show()
Histogram
import pandas as pd
import plotly.express as px
 
df = px.data.tips()
 
fig = px.histogram(
    df,
    x="total_bill",
    nbins=30,
    title="Total bill distribution",
)
fig.show()

Histogram by category

Histogram by sex
import plotly.express as px
 
df = px.data.tips()
 
fig = px.histogram(
    df,
    x="total_bill",
    color="sex",
    nbins=25,
    barmode="overlay",
    opacity=0.6,
    title="Total bill distribution by sex",
)
fig.show()
Histogram by sex
import plotly.express as px
 
df = px.data.tips()
 
fig = px.histogram(
    df,
    x="total_bill",
    color="sex",
    nbins=25,
    barmode="overlay",
    opacity=0.6,
    title="Total bill distribution by sex",
)
fig.show()

Box plot (interactive)

Interactive box plot
import plotly.express as px
 
df = px.data.tips()
 
fig = px.box(df, x="day", y="total_bill", color="sex", title="Total bill by day")
fig.show()
Interactive box plot
import plotly.express as px
 
df = px.data.tips()
 
fig = px.box(df, x="day", y="total_bill", color="sex", title="Total bill by day")
fig.show()

Tip

Start with a histogram, then add:

  • category color
  • hover fields
  • facet columns/rows

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