Consider the following toy example:
import pandas as pd
import plotly.express as px
df_test = pd.DataFrame([1,1,1,1,2,2,2,3,3,4,4,4,4,4,5,5,5,5,5,5], columns=[‘Test’])
fig = px.histogram(df_test, x=‘Test’, histnorm=None)
fig.show()
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The y-axis is labeled ‘count’ whatever histnorm parameter chosen. I don’t think that should be the case, especially if histnorm=‘percent’ or histnorm=‘probability’.
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It seems to me that ‘None’ and ‘density’ yield exactly the same graph, can somebody give me an example where it makes a difference? Same for ‘probability’ and ‘probability density’.
Hello @LordFinzenz
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It’s True that it would be better to display the name of the histnorm
, we have an open issue for this https://github.com/plotly/plotly_express/issues/122, please bear with us until this is implemented.
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In your example the bins have a width of 1, hence there is no difference between the two modes (with density
, the count or histfunc is divided by the width of the bin). With the following example you’ll see a difference
import pandas as pd
import plotly.express as px
import numpy as np
np.random.seed(0)
df_test = pd.DataFrame(np.random.random(1000), columns=['Test'])
fig = px.histogram(df_test, x='Test', histnorm=None) # change to 'density' here
fig.show()
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