如何使用pandas plot获得两个图例，一个用于堆叠条的颜色，另一个用于条的图案填充？

Question

我一直在试图理解this post的答案，以便填充两个不同的传说

我为每个条创建了一个带有不同图案填充的聚集堆叠条形图，下面的代码与前面文章的答案略有不同

但我还并没有弄清楚如何得到一个带有颜色的图例和一个带有图案填充的图例

颜色图例应对应于A、B、C、D、E，如果条带阴影，则阴影图例应显示“带”，如果未带阴影，则应显示“不带”

import matplotlib.pyplot as plt
from matplotlib.colors import LinearSegmentedColormap as coloring

# copy the dfs below and use pd.read_clipboard() to reproduce
df_1
     A   B   C   D   E
Mg  10  15  23  25  27
Ca  30  33   0  20  17

df_2
     A   B   C   D   E
Mg  20  12   8  40  10
Ca   7  26  12  22  16

hatches=(' ', '//')
colors_ABCDE=['tomato', 'gold', 'greenyellow', 'forestgreen', 'palevioletred']
dfs=[df_1,df_2]

for each_df, df in enumerate(dfs):
    df.plot(ax=plt.subplot(111), kind="barh", \
            stacked=True, hatch=hatches[each_df], \
            colormap=coloring.from_list("my_colormap", colors_ABCDE), \
            figsize=(7,2.5), position=len(dfs)-each_df-1, \
            align='center', width=0.2, edgecolor="darkgrey")

plt.legend(loc='center left', bbox_to_anchor=(1.0, 0.5), fontsize=12)

我得到的图是：

有没有办法创建两个传说，然后一个挨着另一个或一个放在另一个下面？提前感谢^ ^

Answer 1

由于在{{CD1>}中添加传奇是一个复杂的、广泛的步骤，请考虑使用@ jjjc与function solution引用的非常链接。不过，您需要根据水平条形图的需要调整该函数。具体而言：

• 为颜色映射和DataFrame.plot调用添加一个参数
• 对于水平版本，将条形图从kind='bar'调整为kind='barh'
• 将x交换为y行：rect.set_y(rect.get_y() + 1 / float(n_df + 1) * i / float(n_col))
• 在rect.set_height(1 / float(n_df + 1))行中用width交换height
• 调整axe.set_xticks和axe.set_xticklabels的np.arange(0, 120, 20)值

功能

import numpy as np
import pandas as pd
import matplotlib.cm as cm
import matplotlib.pyplot as plt
from matplotlib.colors import LinearSegmentedColormap as coloring

def plot_clustered_stacked(dfall, labels=None, title="multiple stacked bar plot", H="//",
                            colors_ABCDE=['tomato', 'gold', 'greenyellow', 'forestgreen', 'palevioletred'], **kwargs):
    """
       CREDIT: @jrjc (https://stackoverflow.com/a/22845857/1422451)

       Given a list of dataframes, with identical columns and index, create a clustered stacked bar plot. 
       labels is a list of the names of the dataframe, used for the legend
       title is a string for the title of the plot
       H is the hatch used for identification of the different dataframe
    """

    n_df = len(dfall)
    n_col = len(dfall[0].columns) 
    n_ind = len(dfall[0].index)
    axe = plt.subplot(111)

    for df in dfall : # for each data frame
        axe = df.plot(kind="barh",
                      linewidth=0,
                      stacked=True,
                      ax=axe,
                      legend=False,
                      grid=False,
                      colormap=coloring.from_list("my_colormap", colors_ABCDE),
                      edgecolor="darkgrey",
                      **kwargs)  # make bar plots

    h,l = axe.get_legend_handles_labels() # get the handles we want to modify
    for i in range(0, n_df * n_col, n_col): # len(h) = n_col * n_df
        for j, pa in enumerate(h[i:i+n_col]):
            for rect in pa.patches: # for each index
                rect.set_y(rect.get_y() + 1 / float(n_df + 2) * i / float(n_col))
                rect.set_hatch(H * int(i / n_col)) #edited part     
                rect.set_height(1 / float(n_df + 2))

    axe.set_xticks(np.arange(0, 125, 20))
    axe.set_xticklabels(np.arange(0, 125, 20).tolist(), rotation = 0)
    axe.margins(x=0, tight=None)
    axe.set_title(title)

    # Add invisible data to add another legend
    n=[]        
    for i in range(n_df):
        n.append(axe.bar(0, 0, color="gray", hatch=H * i, edgecolor="darkgrey"))

    l1 = axe.legend(h[:n_col], l[:n_col], loc=[1.01, 0.5])
    if labels is not None:
        l2 = plt.legend(n, labels, loc=[1.01, 0.1]) 
    axe.add_artist(l1)
    return axe

呼叫

plt.figure(figsize=(10, 4))
plot_clustered_stacked([df_1, df_2],["df_1", "df_2"])
plt.show()

plt.clf()
plt.close()

输出