Multiple multi-line plots group wise in Python

Question

I have a pandas dataframe like this - (Creating a random dataframe)

from random import randint
from random import random
import random
import pandas as pd

x = [randint(1,20) for i in range(20)]
y1 = [random() for i in range(20)]
y2 = [random() for i in range(20)]
y3 = [random() for i in range(20)]
y4 = [random() for i in range(20)]
g = ['a', 'b', 'c']

group = [random.choice(g) for i in range(20)]
data = {'Group': group, 'x': x, 'y1':y1, 'y2':y2, 'y3':y3, 'y4':y4}

df = pd.DataFrame(data)
df.sort_values('Group')

The dataframe is like this -

>>> df.sort_values('Group')
   Group   x        y1        y2        y3        y4
17     a   9  0.400730  0.242629  0.858307  0.799613
16     a  14  0.644299  0.952255  0.257262  0.376845
5      a   3  0.784374  0.800639  0.753612  0.441645
18     a   3  0.988016  0.739003  0.741000  0.299011
11     a  18  0.672816  0.232951  0.763451  0.762478
0      b   7  0.670889  0.785928  0.604563  0.620951
15     b   3  0.838479  0.286988  0.374546  0.013822
4      b   4  0.495855  0.159839  0.984262  0.882428
13     b   3  0.756058  0.979226  0.423426  0.297381
8      b  13  0.835705  0.374927  0.492676  0.939113
12     b  17  0.643511  0.156267  0.248037  0.316526
14     c  13  0.303215  0.177303  0.980071  0.705428
9      c  16  0.829414  0.173755  0.992532  0.398509
7      c   9  0.774353  0.082118  0.089582  0.587679
6      c  14  0.551595  0.737882  0.127206  0.985017
3      c   4  0.072765  0.497016  0.634819  0.149798
2      c   1  0.971598  0.254215  0.325086  0.588159
1      c  14  0.467277  0.631844  0.927199  0.051251
10     c  13  0.346592  0.384929  0.185384  0.330408
19     c  16  0.790785  0.449498  0.176042  0.036896

Using this dataframe I intend to plot multiple graphs group wise (in this case 3 graphs as there are only 3 groups). Each graph is a multi line graph with x on x-axis and [y1, y2, y3, y4] on y-axis

How can I achieve this, I can plot a single multiline graph, but unable to plot multiple plots group -wise.

Quang Hoang · Accepted Answer · 2021-03-02 14:45:57Z

1

You can use groupby:

fig, axes = plt.subplots(1, 3, figsize=(10,3))
for (grp, data), ax in zip(df.groupby('Group'), axes.flat):
    data.plot(x='x', ax=ax)

Output:

Note: You don't really need to sort by group.

answered Mar 2, 2021 at 14:45

Quang Hoang

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4 Comments

heisenbug29 Over a year ago

Instead of giving axes.flat how can I specify columns?

Quang Hoang Over a year ago

What do you mean by specifying columns? That doesn’t seem to be listed in your question.

heisenbug29 Over a year ago

Apart from y1,y2,y3 and y4 I have more columns in the df - but I guess I will just drop them and do this. I am having trouble with the grid layout as there are usually just not 3 groups. Sometimes the groups can be around 20 or sometimes even 40. So how can I arrange the layout?

Quang Hoang Over a year ago

Pass 'y=['y1',...]` to .plot. You would need to know how many groups with len(df['Group'].unique()) and set the layout. You can also use seaborn as alternative for groupby.

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