Plot pandas groupby boxplot and dataframe plot in the same figure

Question

Why the script below does not work? How can I match the groupby boxplot and the DataFrame plot in the same figure?

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

fig, axes = plt.subplots(1, 1, figsize=(15, 15))
n = 480
ts = pd.DataFrame(np.random.randn(n), index=pd.date_range(start="2014-02-01",periods=n,freq="H"))
ts.groupby(lambda x: x.strftime("%Y-%m-%d")).boxplot(subplots=False, rot=90, ax = axes)
ts.plot(ax = axes)
plt.show()

Please describe or show the errors or undesired results to illustrate it does not work which is not helpful for us to understand your issue. — Parfait
– Parfait, Commented Jan 25 at 17:40

rehaqds · Accepted Answer · 2025-01-25 17:26:09Z

1

Reason why you got the boxplots crammed to the left and the line plot crammed to the right:

Matplotlib internally transforms strings/categories on the x-axis to integers starting from 0. But for dates, it transforms them to float values corresponding to the number of days since 01/01/1970. That's why I use 16102 (I added 0.5 to put the box in the middle of the month instead of the beginning).

fig, axes = plt.subplots(1, 1, figsize=(10, 5))
n = 480
ts = pd.DataFrame(np.random.randn(n), index=pd.date_range(start="2014-02-01", periods=n,freq="H"))
g = ts.groupby(lambda x: x.strftime("%Y-%m-%d"))
g.boxplot(subplots=False, ax=axes, positions=np.arange(16102.5, 16122.5))
ts.plot(ax = axes)

# To format the x-tick labels
labels = pd.date_range(start="2014-02-01", periods=20, freq="D")
labels = [t.strftime('%Y-%m-%d') for t in labels]
axes.set_xticklabels(labels=labels, rotation=70)
plt.show()

edited Jan 25 at 17:26

answered Jan 23 at 16:55

rehaqds

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2 Comments

user3046026 Jan 24 at 18:56

Thanks, but it is not quite answering my question. I would like to show the raw timeseries points and the result of the groupby boxplot on the same figure. There is an issue with the x axis format that I can not solve.

rehaqds Jan 25 at 17:27

Yes I underestimated your question ! Hopefully my updated answer is what you were looking for.

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