Plotting multiple lines, in different colors, with pandas dataframe

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Question :

Plotting multiple lines, in different colors, with pandas dataframe

I have a dataframe that looks like the following

   color  x   y
0    red  0   0
1    red  1   1
2    red  2   2
3    red  3   3
4    red  4   4
5    red  5   5
6    red  6   6
7    red  7   7
8    red  8   8
9    red  9   9
10  blue  0   0
11  blue  1   1
12  blue  2   4
13  blue  3   9
14  blue  4  16
15  blue  5  25
16  blue  6  36
17  blue  7  49
18  blue  8  64
19  blue  9  81

I ultimately want two lines, one blue, one red. The red line should essentially be y=x and the blue line should be y=x^2

When I do the following:

df.plot(x='x', y='y')

The output is this:

Is there a way to make pandas know that there are two sets? And group them accordingly. I’d like to be able to specify the column color as the set differentiator

Asked By: sedavidw

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Answer #1:

Another simple way is to use the pivot function to format the data as you need first.

df.plot() does the rest

df = pd.DataFrame([
    ['red', 0, 0],
    ['red', 1, 1],
    ['red', 2, 2],
    ['red', 3, 3],
    ['red', 4, 4],
    ['red', 5, 5],
    ['red', 6, 6],
    ['red', 7, 7],
    ['red', 8, 8],
    ['red', 9, 9],
    ['blue', 0, 0],
    ['blue', 1, 1],
    ['blue', 2, 4],
    ['blue', 3, 9],
    ['blue', 4, 16],
    ['blue', 5, 25],
    ['blue', 6, 36],
    ['blue', 7, 49],
    ['blue', 8, 64],
    ['blue', 9, 81],
], columns=['color', 'x', 'y'])

df = df.pivot(index='x', columns='color', values='y')

df.plot()

result

pivot effectively turns the data into:

enter image description here

Answered By: sedavidw

Answer #2:

You could use groupby to split the DataFrame into subgroups according to the color:

for key, grp in df.groupby(['color']):

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

df = pd.read_table('data', sep='s+')
fig, ax = plt.subplots()

for key, grp in df.groupby(['color']):
    ax = grp.plot(ax=ax, kind='line', x='x', y='y', c=key, label=key)

plt.legend(loc='best')
plt.show()

yields
enter image description here

Answered By: MrE

Answer #3:

If you have seaborn installed, an easier method that does not require you to perform pivot:

import seaborn as sns

sns.lineplot(data=df, x='x', y='y', hue='color')
Answered By: unutbu

Answer #4:

You can use this code to get your desire output

import pandas as pd
import matplotlib.pyplot as plt
df = pd.DataFrame({'color': ['red','red','red','blue','blue','blue'], 'x': [0,1,2,3,4,5],'y': [0,1,2,9,16,25]})
print df

  color  x   y
0   red  0   0
1   red  1   1
2   red  2   2
3  blue  3   9
4  blue  4  16
5  blue  5  25

To plot graph

a = df.iloc[[i for i in xrange(0,len(df)) if df['x'][i]==df['y'][i]]].plot(x='x',y='y',color = 'red')
df.iloc[[i for i in xrange(0,len(df)) if df['y'][i]== df['x'][i]**2]].plot(x='x',y='y',color = 'blue',ax=a)

plt.show()

Output
The output result will look like this

Answered By: Cheng

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