我一直試圖理解這篇文章的答案，以便填充兩個不同的傳說。我為每個條創建了一個帶有不同陰影的聚集堆積條圖，下面的代碼與上述帖子的答案有點不同。但是我無法弄清楚如何獲得一個帶有顏色的圖例和一個帶有陰影的圖例。顏色圖例應對應于 A、B、C、D、E，并且陰影圖例應指示“有”如果條帶陰影線，“無”如果沒有陰影線。import matplotlib.pyplot as pltfrom matplotlib.colors import LinearSegmentedColormap as coloring# copy the dfs below and use pd.read_clipboard() to reproducedf_1 A B C D EMg 10 15 23 25 27Ca 30 33 0 20 17df_2 A B C D EMg 20 12 8 40 10Ca 7 26 12 22 16hatches=(' ', '//')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)我設法得到的情節是：任何想法如何創建兩個圖例并將它們放在另一個旁邊或一個在另一個下面？提前謝謝^_^
2 回答
白豬掌柜的
TA貢獻1893條經驗 獲得超10個贊
由于添加圖例matplotlib是一個復雜而廣泛的步驟，因此請考慮使用您引用的 @jrjc函數解決方案的鏈接。但是，您需要根據水平條形圖的需要調整功能。具體來說：
為顏色圖和
DataFrame.plot調用添加參數將條形圖從
kind='bar'到調整kind='barh'為水平版本將 x 換成 y 行：
rect.set_y(rect.get_y() + 1 / float(n_df + 1) * i / float(n_col))換線
width：heightrect.set_height(1 / float(n_df + 1))調整
axe.set_xticks和axe.set_xticklabels值np.arange(0, 120, 20)_
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
稱呼
plt.figure(figsize=(10, 4))
plot_clustered_stacked([df_1, df_2],["df_1", "df_2"])
plt.show()
plt.clf()
plt.close()
輸出
慕慕森
TA貢獻1856條經驗 獲得超17個贊
我認為@jrjc 的這個功能解決方案對我的理解來說相當令人困惑，因此，我更愿意稍微改變我自己的東西并進行調整。
所以，我花了一些時間才明白，當為情節創建第二個圖例時，python 會自動刪除第一個圖例，這是add_artist()必須使用的時候。
添加第二個圖例的另一個先決條件是命名圖并將 .add_artist() 方法應用于該特定圖，以便 python 知道將新部分粘貼在哪里。
簡而言之，這就是我設法創建我想到的情節的方式，我希望這些評論能讓它更清晰，對任何人都有用。
import matplotlib.pyplot as plt
from matplotlib.colors import LinearSegmentedColormap as coloring
import matplotlib.patches as mpatches
# 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):
#I name the plot as "figure"
figure=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", \
legend=False) #I had to False the legend too
legend_1=plt.legend(df_1.columns, loc='center left', bbox_to_anchor=(1.0, 0.5), fontsize=12)
patch_hatched = mpatches.Patch(facecolor='beige', hatch='///', edgecolor="darkgrey", label='hatched')
patch_unhatched = mpatches.Patch(facecolor='beige', hatch=' ', edgecolor="darkgrey", label='non-hatched')
legend_2=plt.legend(handles=[patch_hatched, patch_unhatched], loc='center left', bbox_to_anchor=(1.15, 0.5), fontsize=12)
# as soon as a second legend is made, the first disappears and needs to be added back again
figure.add_artist(legend_1) #python now knows that "figure" must take the "legend_1" along with "legend_2"
有兩個傳說的情節
我很確定它可以更加優雅和自動化。
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