如何从长度不均匀的列表中创建分组条 plot

Question

I am trying to plot groups of data which have different length of data. Do you have any idea how I can visualize a female list containing only two objects without filling up the rest of them with zeros to get the length of the male list?

This is the code, which I got so far:

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

labels = ['G1', 'G2', 'G3', 'G4']
male = [1, 3, 10, 20]
female = [2, 7]

x = np.arange(len(labels))  # the label locations
width = 0.35  # the width of the bars

fig, ax = plt.subplots()
rects1 = ax.bar(x - width/2, male, width, label='male')
rects2 = ax.bar(x + width/2, female, width, label='female')

# Add some text for labels, title and custom x-axis tick labels, etc.
ax.set_xticks(x)
ax.set_xticklabels(labels)
ax.legend()

fig.tight_layout()
plt.show()

Answer 1

You can make two different array for the x-positions:

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

labels = ['G1', 'G2', 'G3', 'G4']
male = [1, 3, 10, 20]
female = [2, 7]

x_male = np.arange(len(male))
x_female = np.arange(len(female))

offset_male = np.zeros(len(male))
offset_female = np.zeros(len(female))

shorter = min(len(x_male), len(x_female))

width = 0.35  # the width of the bars

offset_male[:shorter] = width/2
offset_female[:shorter] = width/2

fig, ax = plt.subplots()
rects1 = ax.bar(x_male - offset_male, male, width, label='male')
rects2 = ax.bar(x_female + offset_female, female, width, label='female')

That said, this solution only works when values are missing at the end of the shorter list. For values missing within the list, it would be better to use None, or np.nan, as suggested by @desert_ranger.

Answer 2

If you don't want to fill them up with zeros, you could assign NAN values to them -

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

labels = ['G1', 'G2', 'G3', 'G4']
male = [1, 3, 10, 20]
female = [2, 7,np.nan,np.nan]

x = np.arange(len(labels))  # the label locations
width = 0.35  # the width of the bars

fig, ax = plt.subplots()
ax.bar(x - width/2, male, width, label='male')
ax.bar(x + width/2, female, width, label='female')

# Add some text for labels, title and custom x-axis tick labels, etc.
ax.set_xticks(x)
ax.set_xticklabels(labels)
ax.legend()

fig.tight_layout()
plt.show()

Answer 3

• Use pandas and plot with pandas.DataFrame.plot.bar
• Tested in python 3.8.11 , pandas 1.3.1 , and matplotlib 3.4.2

Option 1

• Column data must be the same length when creating a dataframe, therefore use itertools.zip_longest to zip lists of unequal length, which fills the missing data with a fillvalue .

import pandas as pd
import matplotlib.pyplot as plt
from itertools import zip_longest

# data
labels = ['G1', 'G2', 'G3', 'G4']
male = [1, 3, 10, 20]
female = [2, 7]

# zip lists together
data = zip_longest(male, female)

# create dataframe from data
df = pd.DataFrame(data, columns=['male', 'female'], index=labels)

    male  female
G1     1     2.0
G2     3     7.0
G3    10     NaN
G4    20     NaN

# plot
p = df.plot.bar(rot=0)
plt.show()

Option 2

• Row do not need to be the same length to add to the dataframe

import pandas as pd
import matplotlib.pyplot as plt

# data
labels = ['G1', 'G2', 'G3', 'G4']
male = [1, 3, 10, 20]
female = [2, 7]

# create a dataframe from the lists
df = pd.DataFrame([male, female], columns=labels, index=['male', 'female'])

        G1  G2    G3    G4
male     1   3  10.0  20.0
female   2   7   NaN   NaN

# plot
p = df.plot.bar(rot=0)