Wrong labels when plotting a time series pandas dataframe with matplotlib

Question

I am working with a dataframe containing data of 1 week.

                          y
ds                             
2017-08-31 10:15:00    1.000000
2017-08-31 10:20:00    1.049107
2017-08-31 10:25:00    1.098214
...
2017-09-07 10:05:00   99.901786
2017-09-07 10:10:00   99.950893
2017-09-07 10:15:00  100.000000

I create a new index by combining the weekday and time i.e.

                y
dayIndex             
4 - 10:15    1.000000
4 - 10:20    1.049107
4 - 10:25    1.098214
...
4 - 10:05   99.901786
4 - 10:10   99.950893
4 - 10:15  100.000000

The plot of this data is the following: The plot is correct as the labels reflect the data in the dataframe. However, when zooming in, the labels do not seem correct as they no longer correspond to their original values: What is causing this behavior?

Here is the code to reproduce this:

import datetime
import numpy as np
import pandas as pd

dtnow = datetime.datetime.now()
dindex = pd.date_range(dtnow , dtnow  + datetime.timedelta(7), freq='5T')
data = np.linspace(1,100, num=len(dindex))
df = pd.DataFrame({'ds': dindex, 'y': data})
df = df.set_index('ds')
df = df.resample('5T').mean()
df['dayIndex'] = df.index.strftime('%w - %H:%M')
df= df.set_index('dayIndex')
df.plot()

Demetris · Accepted Answer · 2021-01-27 08:04:14Z

2

"What is causing this behavior?"

The formatter of an axes of a pandas dates plot is a matplotlib.ticker.FixedFormatter (see e.g. print plt.gca().xaxis.get_major_formatter()). "Fixed" means that it formats the ith tick (if shown) with some constant string.

When zooming or panning, you shift the tick locations, but not the format strings.
In short: A pandas date plot may not be the best choice for interactive plots.

Solution

A solution is usually to use matplotlib formatters directly. This requires the dates to be datetime objects (which can be ensured using df.index.to_pydatetime()).

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

dtnow = datetime.datetime.now()
dindex = pd.date_range(dtnow , dtnow  + datetime.timedelta(7), freq='110T')
data = np.linspace(1,100, num=len(dindex))
df = pd.DataFrame({'ds': dindex, 'y': data})
df = df.set_index('ds')
df.index.to_pydatetime()
df.plot(marker="o")


plt.gca().xaxis.set_major_formatter(matplotlib.dates.DateFormatter('%w - %H:%M'))
plt.show()

edited Jan 27, 2021 at 8:04

Demetris

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answered Aug 31, 2017 at 13:30

ImportanceOfBeingErnest

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2 Comments

Demetris Over a year ago

How come the format strings do not shift along with the ticks? Do you know if this is by design, or should this reported as issue? I am referring to my original code. The one you posted works great.

ImportanceOfBeingErnest Over a year ago

The fact that a FixedFormatter fixes the labels such that they are bound to the index of the label is by design (hence the name). Whether or not the fact that pandas datetime plots use a FixedFormatter would be seen as an issue, is probably a matter of taste. It has several advantages, but you ran into a case where it is undesired. I thus wouldn't call it a bug or so, but you may sure report it as a feature request if you like.

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