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Balkendiagramm mit mehreren Etiketten

Der folgende Code zeigt nur die Hauptkategorie ['Eins', 'Zwei', 'Drei', 'Vier', 'Fünf', 'Sechs'] als Beschriftungen der X-Achse. Gibt es eine Möglichkeit, die Unterkategorie ['A', 'B', 'C', 'D'] als sekundäre X-Achsenbeschriftungen anzuzeigen?  enter image description here

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))
17
Meng

Hier eine mögliche Lösung (ich hatte ziemlich viel Spaß!):

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')

Folgendes bekomme ich:

 enter image description here

7
FLab

Hier ist eine Lösung. Sie können die Position der Bars ermitteln und einige kleinere Xticklabels entsprechend einstellen. 

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()

 enter image description here

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

def subcategorybar(X, vals,als, width=0.8):
    n = len(vals)
    _X = np.arange(len(X))
    plt.figure(figsize=(14,9))
    for i in range(n):
        plt.bar(_X - width/2. + i/float(n)*width, vals[i], 
                width=width/float(n), align="Edge")
        for j in _X:
            plt.text([_X - width/2. + i/float(n)*width][0][j],vals[i][j]+0.01*vals[i] 
                     [j],str(als[i][j]))
    plt.xticks(_X, X)

### data
X = ['a','b','c','d','f']
A1 = [1,2,3,4,5]
A2= [1,7,6,7,8]
A3 = [3,5,6,8,9]
A4= [4,5,6,7,3]
A5 = [5,6,7,8,5]

##labels
A1_al = ['da','dd',5,6,3]
A2_al = np.random.random_integers(20,size=5)
A3_al = np.random.random_integers(20,size=5)
A4_al = np.random.random_integers(20,size=5)
A5_al = np.random.random_integers(20,size=5)

subcategorybar(X, [A1,A2,A3,A4],[A1_al,A2_al,A3_al,A4_al],width=0.8)

plt.show()
0
Naresh Kumar