带有多个标签的条形图

Question

以下代码仅显示主要类别['one','two','three','four','five','six']作为x轴标签.有没有办法显示子类别['A','B','C','D']作为辅助x轴标签？

df = pd.DataFrame(np.random.rand(6, 4),
                 index=['one', 'two', 'three', 'four', 'five', 'six'],
                 columns=pd.Index(['A', 'B', 'C', 'D'], 
                 name='Genus')).round(2)


df.plot(kind='bar',figsize=(10,4))

Answer 1

这是一个解决方案.您可以获得条形图的位置并相应地设置一些较小的xticklabels.

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

df = pd.DataFrame(np.random.rand(6, 4),
                 index=['one', 'two', 'three', 'four', 'five', 'six'],
                 columns=pd.Index(['A', 'B', 'C', 'D'], 
                 name='Genus')).round(2)


df.plot(kind='bar',figsize=(10,4))

ax = plt.gca()
pos = []
for bar in ax.patches:
    pos.append(bar.get_x()+bar.get_width()/2.)


ax.set_xticks(pos,minor=True)
lab = []
for i in range(len(pos)):
    l = df.columns.values[i//len(df.index.values)]
    lab.append(l)

ax.set_xticklabels(lab,minor=True)
ax.tick_params(axis='x', which='major', pad=15, size=0)
plt.setp(ax.get_xticklabels(), rotation=0)

plt.show()

Answer 2

这是一个可能的解决方案(我有很多乐趣!):

df = pd.DataFrame(np.random.rand(6, 4),
                 index=['one', 'two', 'three', 'four', 'five', 'six'],
                 columns=pd.Index(['A', 'B', 'C', 'D'],
                 name='Genus')).round(2)

ax = df.plot(kind='bar',figsize=(10,4), rot = 0)

# "Activate" minor ticks
ax.minorticks_on()

# Get location of the center of each rectangle
rects_locs = map(lambda x: x.get_x() +x.get_width()/2., ax.patches)
# Set minor ticks there
ax.set_xticks(rects_locs, minor = True)


# Labels for the rectangles
new_ticks = reduce(lambda x, y: x + y, map(lambda x: [x] * df.shape[0], df.columns.tolist()))
# Set the labels
from matplotlib import ticker
ax.xaxis.set_minor_formatter(ticker.FixedFormatter(new_ticks))  #add the custom ticks

# Move the category label further from x-axis
ax.tick_params(axis='x', which='major', pad=15)

# Remove minor ticks where not necessary
ax.tick_params(axis='x',which='both', top='off')
ax.tick_params(axis='y',which='both', left='off', right = 'off')

这是我得到的: