Reputation: 313
I'm fairly new to this, so there might be a very obvious answer to this. My apologies!
I'm plotting two histograms via a groubpy. I'd like my subplots to each have the same x and y labels and a common title. I understood that sharex=True would do the trick, but apparently not if I set the axis only after the df.hist. I've tried various versions of setting the xlabels and am lost now.
import pylab as pl
from pandas import *
histo_survived = df.groupby('Survived').hist(column='Age', sharex=True, sharey=True)
pl.title("Histogram of Ages")
pl.xlabel("Age")
pl.ylabel("Individuals")
So what I end up with is labels only for the subplot.
Out: <matplotlib.text.Text at 0x11a27ead0>
Any idea on how to solve this? (Have to use pandas/python.)
Upvotes: 21
Views: 70626
Reputation: 2726
For those looking for a simple one line solution in matplotlib, just tack on .set_xlabel("your_label")
to the end.
df.col_to_graph.plot.hist(bins=10, alpha=0.5, figsize=(16, 12)).set_xlabel("col_to_graph label")
Upvotes: 0
Reputation: 5982
I came here looking for the same thing, but found it easier to do in plotly
import plotly.express as px
px.histogram(df, x="t_depth", nbins=150).update_layout(
xaxis = dict(dtick=10), bargap=0.2
)
Upvotes: 1
Reputation: 7466
Labels are properties of axes objects, that needs to be set on each of them. Here's an example that worked for me:
frame = pd.DataFrame([np.random.rand(20), np.sign(np.random.rand(20) - 0.5)]).T
frame.columns = ['Age', 'Survived']
# Note that you can let the hist function do the groupby
# the function hist returns the list of axes created
axarr = frame.hist(column='Age', by = 'Survived', sharex=True, sharey=True, layout = (2, 1))
for ax in axarr.flatten():
ax.set_xlabel("Age")
ax.set_ylabel("Individuals")
Upvotes: 38