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Specifying histtype='stepfilled' and normed=True when using plt.hist causes ymax to be set incorrectly #4414
Description
The combination of histtype='stepfilled' and normed=True seem to cause some problems with the max ylimit.
import matplotlib.pyplot as plt
import seaborn.apionly as sns
iris = sns.load_dataset('iris')
plt.figure()
for species, species_df in iris.groupby("species"):
plt.hist(species_df["petal_length"].values, normed=True, histtype="stepfilled")
plt.legend(sorted(iris.species.unique()))
Which is not the case when only using histtype='stepfilled'.
plt.figure()
for species, species_df in iris.groupby("species"):
plt.hist(species_df["petal_length"].values, histtype="stepfilled")
Or when only using normed=True.
plt.figure()
for species, species_df in iris.groupby("species"):
plt.hist(species_df["petal_length"].values, normed=True)
It seems like in the erroneous case above, the max of the yaxis is set by the last plotted distribution, which can be tested by changing the order of when the different histograms are plotted.
plt.figure()
iris.loc[iris.species == 'setosa', 'species'] = 'wsetosa'
for species, species_df in iris.groupby("species"):
plt.hist(species_df["petal_length"].values, normed=True, histtype="stepfilled")
plt.legend(sorted(iris.species.unique()))
Activity
[-]specifying histplt.hist [/-][+]Specifying histtype='stepfilled' and normed=True when using plt.hist causes the ymax to be set incorrectly[/+][-]Specifying histtype='stepfilled' and normed=True when using plt.hist causes the ymax to be set incorrectly[/-][+]Specifying histtype='stepfilled' and normed=True when using plt.hist causes ymax to be set incorrectly[/+]tacaswell commentedon May 7, 2015
I suspect that some place there is a
ax.set_ylim(max(..))call which just needs to be changed to an autoscale/limit call, but given that this ishistone can never be sure.fixed bug for issue matplotlib#4414
Revert "fixed bug for issue matplotlib#4414"
fixed bug for matplotlib#4414
QuLogic commentedon Dec 11, 2016
This was corrected by #7476 and should be fixed in 2.0.0.
