我正在學習 python 中的乳腺癌分類資料集。我正在嘗試為每個特征繪制直方圖，如何將這些直方圖分成三組？像下面的截圖：
我想要達到的目標
這是我使用的代碼：
from sklearn.datasets import load_breast_cancer # sample data
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
data = load_breast_cancer()
# Turn the feature data into a dataframe
df = pd.DataFrame(data.data, columns = data.feature_names)
# Add the target columns, and fill it with the target data
df["target"] = data.target
# display(df.head())
mean radius mean texture mean perimeter mean area mean smoothness mean compactness mean concavity mean concave points mean symmetry mean fractal dimension radius error texture error perimeter error area error smoothness error compactness error concavity error concave points error symmetry error fractal dimension error worst radius worst texture worst perimeter worst area worst smoothness worst compactness worst concavity worst concave points worst symmetry worst fractal dimension target
0 17.99 10.38 122.80 1001.0 0.11840 0.27760 0.3001 0.14710 0.2419 0.07871 1.0950 0.9053 8.589 153.40 0.006399 0.04904 0.05373 0.01587 0.03003 0.006193 25.38 17.33 184.60 2019.0 0.1622 0.6656 0.7119 0.2654 0.4601 0.11890 0
1 20.57 17.77 132.90 1326.0 0.08474 0.07864 0.0869 0.07017 0.1812 0.05667 0.5435 0.7339 3.398 74.08 0.005225 0.01308 0.01860 0.01340 0.01389 0.003532 24.99 23.41 158.80 1956.0 0.1238 0.1866 0.2416 0.1860 0.2750 0.08902 0
2 19.69 21.25 130.00 1203.0 0.10960 0.15990 0.1974 0.12790 0.2069 0.05999 0.7456 0.7869 4.585 94.03 0.006150 0.04006 0.03832 0.02058 0.02250 0.004571 23.57 25.53 152.50 1709.0 0.1444 0.4245 0.4504 0.2430 0.3613 0.08758 0
3 11.42 20.38 77.58 386.1 0.14250 0.28390 0.2414 0.10520 0.2597 0.09744 0.4956 1.1560 3.445 27.23 0.009110 0.07458 0.05661 0.01867 0.05963 0.009208 14.91 26.50 98.87 567.7 0.2098 0.8663 0.6869 0.2575 0.6638 0.17300 0
4 20.29 14.34 135.10 1297.0 0.10030 0.13280 0.1980 0.10430 0.1809 0.05883 0.7572 0.7813 5.438 94.44 0.011490 0.02461 0.05688 0.01885 0.01756 0.005115 22.54 16.67 152.20 1575.0 0.1374 0.2050 0.4000 0.1625 0.2364 0.07678 0
# plotting
plotnumber = 1
fig = plt.figure(figsize=(20, 20))
for column in df.drop('target', axis=1):
if plotnumber <= 30:
plt.subplot(5, 6, plotnumber)
sns.distplot(df[df['target'] == 0][column], label = 'malignant')
sns.distplot(df[df['target'] == 1][column], label = 'benign')
plt.legend()
plt.title(column)
plotnumber = 1
fig.tight_layout()
到目前為止我所擁有的
我想將它們分為三組：“平均”組、“錯誤”組和“最差”組。每組包括 10 個地塊（5 行 2 列）
這些不能回答問題
使用默認圖例繪制
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