Pandas: plot multiple time series DataFrame into a single plot

Question

I have the following pandas DataFrame:

     time      Group      blocks
0     1        A           4
1     2        A           7
2     3        A           12
3     4        A           17
4     5        A           21 
5     6        A           26
6     7        A           33
7     8        A           39
8     9        A           48
9     10       A           59
    ....        ....          ....
36     35      A           231
37     1       B           1
38     2       B           1.5
39     3       B           3
40     4       B           5
41     5       B           6
    ....        ....          ....
911    35      Z           349

This is a dataframe with multiple time series-ques data, from min=1 to max=35. Each Group has a time series like this.

I would like to plot each individual time series A through Z against an x-axis of 1 to 35. The y-axis would be the blocks at each time.

I was thinking of using something like an Andrews Curves plot, which would plot each series against one another. Each "hue" would be set to a different group. (Other ideas are welcome.)

My problem: how do you format this dataframe to plot multiple series? Should the columns be GroupA, GroupB, etc.?

How do you get the dataframe to be in the format:

time GroupA blocksA GroupsB blocksB GroupsC blocksC....

Is this the correct format for an Andrews plot as shown?

EDIT

If I try:

df.groupby('Group').plot(legend=False)

the x-axis is completely incorrect. All time series should be plotted from 0 to 35, all in one series.

How do I solve this?

To call andrews_curves on a dataframe you have to mark values you want to group by. Try andrews_curves(df, 'Group') to group by columns Group. — Serenity
– Serenity, Commented Jul 5, 2016 at 8:04
@Serenity This is a mess. The x-axis is not from 1 to 35, and I'm not sure what the y-axis is. How do you change this? — ShanZhengYang
– ShanZhengYang, Commented Jul 5, 2016 at 8:06
Andrews' curves are between [-pi; +pi]. Read this: fedc.wiwi.hu-berlin.de/xplore/tutorials/mvahtmlnode9.html — Serenity
– Serenity, Commented Jul 5, 2016 at 8:25

Michael Thomas · Accepted Answer · 2018-11-14 19:42:28Z

13

You can re-structure the data as a pivot table:

df.pivot_table(index='time',columns='Group',values='blocks',aggfunc='sum').plot()

answered Nov 14, 2018 at 19:42

Michael Thomas

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Serenity · Accepted Answer · 2016-07-05 08:38:25Z

12

Look at this variants. The first is Andrews' curves and the second is a multiline plot which are grouped by one column Month. The dataframe data includes three columns Temperature, Day, and Month:

import pandas as pd
import statsmodels.api as sm
import matplotlib.pylab as plt
from pandas.tools.plotting import andrews_curves

data = sm.datasets.get_rdataset('airquality').data
fig, (ax1, ax2) = plt.subplots(nrows = 2, ncols = 1)
data = data[data.columns.tolist()[3:]] # use only Temp, Month, Day

# Andrews' curves
andrews_curves(data, 'Month', ax=ax1)

# multiline plot with group by
for key, grp in data.groupby(['Month']): 
    ax2.plot(grp['Day'], grp['Temp'], label = "Temp in {0:02d}".format(key))
plt.legend(loc='best')    
plt.show()

When you plot Andrews' curve your data salvaged to one function. It means that Andrews' curves that are represented by functions close together suggest that the corresponding data points will also be close together.

edited Jul 5, 2016 at 8:38

answered Jul 5, 2016 at 8:33

Serenity

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2 Comments

ShanZhengYang Over a year ago

See edit above; I have problems with the 'groupby' plot

Ramon Over a year ago

I use this code to my data and got the error below. Can anyone help me on this? TypeError: ufunc 'true_divide' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''

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