How to avoid plotting gaps when there's no data between a period

Question

I am currently generating the plot below: plot

with this code:

ax = plt.subplots()
ax.plot(intra.to_pydatetime(), data)
plt.title('Intraday Net Spillover')
fig.autofmt_xdate()

where intra.to_pydatetime() is a: <bound method DatetimeIndex.to_pydatetime of <class 'pandas.tseries.index.DatetimeIndex'> [2011-01-03 09:35:00, ..., 2011-01-07 16:00:00] Length: 390, Freq: None, Timezone: None>

So the dates go from 2011-01-03 09:35:00, increments by 5 minutes until 16:00:00, and then jumps to the next day, 2011-01-04 09:35:00 until 2011-01-04 16:00:00, and so on.

How can I avoid plotting the gaps between 16:00:00 and 9:30:00 on the following day? I don't want to see these straight lines.

UPDATE:

I will try this to see if it works.

I don't know if that's not too complicated, but I did that once by seperating the plotted series into multiple series and plotted each on its own, as I don't know how pandas should know what's a gap and what isn't. — Blutkoete
– Blutkoete, Commented Dec 3, 2014 at 8:48
Addendum: In one plot, but as seperate series, with same colour and linestyle, only giving a legend entry to the first. — Blutkoete
– Blutkoete, Commented Dec 3, 2014 at 8:53
For other users, although question is old, please review my answer and accept it if it worked. — Overdrivr
– Overdrivr, Commented Dec 20, 2015 at 19:32

Overdrivr · Accepted Answer · 2014-12-03 10:28:47Z

8

Simply set the two values defining the line you don't want to see as NaN (Not a Number). Matplotlib will hide the line between the two values automatically.

Check out this example : http://matplotlib.org/examples/pylab_examples/nan_test.html

edited Dec 3, 2014 at 10:28

answered Dec 3, 2014 at 10:14

Overdrivr

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3 Comments

scai Over a year ago

A single float('NaN') is enough to create a gap.

yunfei Over a year ago

this is just hide, but still showing the 'gap'

Philipp Ludwig Over a year ago

That is not true, the gaps are still there.

user16930926 · Accepted Answer · 2021-09-16 18:25:35Z

2

Try to resample your dataframe. For example :

df.plot()

gives me that result : plot

and now with resample:

df = df.resample('H').first().fillna(value=np.nan)

plot after resample

answered Sep 16, 2021 at 18:25

user16930926

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