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I have a dataframe including random data over 7 days and each data point is indexed by DatetimeIndex. I want to plot data of each day on a single plot. Currently my try is the following:

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
n =10000
i = pd.date_range('2018-04-09', periods=n, freq='1min')
ts = pd.DataFrame({'A': [np.random.randn() for i in range(n)]}, index=i)
dates = list(ts.index.map(lambda t: t.date).unique())
for date in dates:
  ts['A'].loc[date.strftime('%Y-%m-%d')].plot()

The result is the following: enter image description here

As you can see when DatetimeIndex is used the corresponding day is kept that is why we have each day back to the next one.

Questions:

1- How can I fix the current code to have an x-axis which starts from midnight and ends next midnight.

2- Is there a pandas way to group days better and plot them on a single day without using for loop?

Saeed
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  • Can you clarify your question? do you want the x axis to start on midnight and end on midnight of a specific date or do you want the lines to overlay each other? – David Jan 06 '22 at 12:02

1 Answers1

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You can split the index into dates and times and unstack the ts into a dataframe:

df = ts.set_index([ts.index.date, ts.index.time]).unstack(level=0)
df.columns = df.columns.get_level_values(1)

then plot all in one chart:

df.plot()

enter image description here

or in separate charts:

axs = df.plot(subplots=True, title=df.columns.tolist(), legend=False, figsize=(6,8))
axs[0].figure.execute_constrained_layout()

enter image description here

Stef
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