Plotting different groups of a dataframe in different subplots

Question

I want to plot 4 different scatter subplots in one main plot. The data are coming from a grouped dataframe which is read from a .csv file. The initial dataframe looks like this:

df.to_csv("File.csv", index=False)

df:

	Category1	Category2	X	Y
0	A	x	4	5.1
1	B	x	3	4.2
2	A	y	2	7.1
3	A	z	9	6.1
...	...	...	...	...
97	A	z	4	5.1
98	A	w	3	4.2
99	B	y	2	7.1
100	B	z	9	6.1

As you can see, category1 has only two kinds of values (A,B) while category2 has 4 kinds of values (x,y,z,w). the X and Y values are random and for display purpose only.

The grouped df was created using following command:

dfGrouped = df.groupby(["Category1 ","Category2"])

dfGrouped:

		X	Y
A	x	4	5.1
A		7	9.1
	y	3	4.2
		3	4.2
		3	4.2
	z	2	7.1
	w	9	6.1
...	...	...	...
B	x	4	5.1
	y	3	4.2
	z	2	7.1
		2	7.1
	w	9	6.1

I tried to plot them individually, but it didn't work:

fig, ax = plt.subplots(figsize=(8, 6))
ax.margins(0.05)
for name, group in dfGrouped:
    ax.plot(group.X, group.Y, marker='o', linestyle='', ms=2, label=name)

I even tried to call the groups using get_group but I was not successful.

dfGrouped= dfGrouped.get_group(("A","x"))

Is there any way to plot 4 different scatter subplots (Based on "category2": x,y,z,w) in one main plot in a way that each plot contains 2 sets values with 2 different colors(Based on "Category1": A, B)?

What variables are you interested in plotting for each group? X and Y? — liorr
– liorr, Commented Aug 30, 2021 at 18:35

mozway · Accepted Answer · 2021-08-30 20:30:54Z

1

You could use seaborn.relplot:

import numpy as np
import seaborn as sns
# dummy data
df = pd.DataFrame({'Category1': np.random.choice(['A','B'], size=100),
                   'Category2': np.random.choice(['w','x', 'y', 'z'], size=100),
                   'x': np.random.random(size=100),
                   'y': np.random.random(size=100),
                   })
# plot
sns.relplot(data=df, x='x', y='y', col='Category2', col_wrap=2, hue='Category1')

Output: seaborn relplot

answered Aug 30, 2021 at 20:30

mozway

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Comments

Priya · Accepted Answer · 2021-08-30 21:43:58Z

0

I used scatter plot, below is another alternative:

**DataFrame**   

       col1     val1    val2    col2
  0     A      1000     5000     w
  1     A      3000     4000     w
  2     A      7000     5000     w
  3     A      3000     4000     w
  4     A      5000     6000     x
  5     A      5000     4000     x
  6     A      5000     9000     x
  7     A      6000     10000    x
  8     B      5000     6000     y
  9     B      5000     4000     y
  10    B      5000     9000     y
  11    A      6000     10000    y
  12    A      5000     6000     z
  13    B      5000     4000     z
  14    B      5000     9000     z
  15    A      6000     10000    z

Function

def plot_grouped_data():
  fig = plt.figure()
  fig.subplots_adjust(hspace=0.4, wspace=0.4)
  i=0
  for label, df in new.groupby('col2'):
    ax = fig.add_subplot(2,2,i+1)
    # print(label)
    sns.scatterplot(data=df,x= 'val1', y='val2', hue='col1', ax=ax)
    plt.title(f'Title={label}')
    plt.legend(loc="upper right")
    i += 1
  plt.show()

plot_grouped_data()

Output

answered Aug 30, 2021 at 21:43

Priya

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2 Comments

Amir Ghorbani Over a year ago

it works, thanks, but CPU consuming, right?

Priya Over a year ago

might be...since for loop is involved. Just an other answer!

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Plotting different groups of a dataframe in different subplots

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Hot Network Questions

	Category1	Category2	X	Y
0	A	x	4	5.1
1	B	x	3	4.2
2	A	y	2	7.1
3	A	z	9	6.1
...	...	...	...	...
97	A	z	4	5.1
98	A	w	3	4.2
99	B	y	2	7.1
100	B	z	9	6.1

		X	Y
A	x	4	5.1
A		7	9.1
	y	3	4.2
		3	4.2
		3	4.2
	z	2	7.1
	w	9	6.1
...	...	...	...
B	x	4	5.1
	y	3	4.2
	z	2	7.1
		2	7.1
	w	9	6.1

	Category1	Category2	X	Y
0	A	x	4	5.1
1	B	x	3	4.2
2	A	y	2	7.1
3	A	z	9	6.1
...	...	...	...	...
97	A	z	4	5.1
98	A	w	3	4.2
99	B	y	2	7.1
100	B	z	9	6.1

		X	Y
A	x	4	5.1
A		7	9.1
	y	3	4.2
		3	4.2
		3	4.2
	z	2	7.1
	w	9	6.1
...	...	...	...
B	x	4	5.1
	y	3	4.2
	z	2	7.1
		2	7.1
	w	9	6.1

Collectives™ on Stack Overflow

2 Answers 2

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Related

	Category1	Category2	X	Y
0	A	x	4	5.1
1	B	x	3	4.2
2	A	y	2	7.1
3	A	z	9	6.1
...	...	...	...	...
97	A	z	4	5.1
98	A	w	3	4.2
99	B	y	2	7.1
100	B	z	9	6.1

		X	Y
A	x	4	5.1
A		7	9.1
	y	3	4.2
		3	4.2
		3	4.2
	z	2	7.1
	w	9	6.1
...	...	...	...
B	x	4	5.1
	y	3	4.2
	z	2	7.1
		2	7.1
	w	9	6.1