pandas plot aggregate timestamp index

Question

I have a timeseries of data I would like to plot. In the night, when i do not collect data, I have a gap between 9 pm and 7 am which looks a bit ugly on the chart and makes it hard to read.

here is a little example to understand the issue:

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


df2 = pd.DataFrame({ 'A' : pd.Series(np.random.randn(4),index=list(range(4)),dtype='float32'),
                    'B' : pd.date_range('1/1/2000', periods=4)})




print(df2.to_string())
df2.ix[3,'B'] = pd.to_datetime('2005-01-02')

print(df2.to_string())

df2.index = df2.B
fig = plt.figure()
ax = fig.add_subplot(111)

ax.plot(df2.index, df2["A"])
plt.show()

the graph from 1/1/2000 to 1/3/2000 is almost unreadable, because the plot is scaled to show also the data from 2005. is there a way to eliminate that the indices (?) from 1/3/2000 to 1/3/2005?

Thanks and cheers, E.

you can eliminate it if the x-axis is a string type.. so your example above you'll do df2.index = df2.index.astype(str) — gyx-hh
– gyx-hh, Commented Nov 1, 2018 at 13:14
Hi and thanks. This throws me an error ValueError: could not convert string to float: '2005-01-02' .. cheers, E. — Ele
– Ele, Commented Nov 1, 2018 at 13:16
your index is already a string? can we see a sample of your actual data ? The above works for the example you provided where the index B is a datetime — gyx-hh
– gyx-hh, Commented Nov 1, 2018 at 13:19
oh I mean I get an error with the above example ... I'll check again — Ele
– Ele, Commented Nov 1, 2018 at 13:20
@gyx-hh where would i put that line? I guess after assignen B to the index, but then ax.plot complains — Ele
– Ele, Commented Nov 1, 2018 at 13:23

Scott Boston · Accepted Answer · 2018-11-01 13:43:30Z

4

IIUC, let me create a sample set and bad outcome.

np.random.seed(0)
df = pd.DataFrame(np.random.random(500), index=pd.date_range('2018-11-25 07:00:00', periods=500, freq='10T'))
df2 = df[(df.index.hour >= 7) & (df.index.hour < 21)]
df2.plot()

Output:

However, we can eliminate those flatline sections like this:

np.random.seed(0)
df = pd.DataFrame(np.random.random(500), index=pd.date_range('2018-11-25 07:00:00', periods=500, freq='10T'))

df2 = df[(df.index.hour >= 7) & (df.index.hour < 21)]

df2.index = df2.index.strftime('%Y-%m-%d')

fig, ax = plt.subplots()
_ = df2.plot(ax=ax)
skip = df2.shape[0]//7 + 1
label = [i for i in df2.index[::skip]]
_ = plt.xticks(np.arange(0,df2.shape[0],skip),label,rotation=45)

Output:

answered Nov 1, 2018 at 13:43

Scott Boston

154k15 gold badges160 silver badges207 bronze badges

Sign up to request clarification or add additional context in comments.

Collectives™ on Stack Overflow

pandas plot aggregate timestamp index

1 Answer 1

Comments

Your Answer

Linked

Hot Network Questions

Collectives™ on Stack Overflow

1 Answer 1

Comments

Your Answer

Sign up or log in

Post as a guest

Linked

Related