How to create groups of subplots in a single figure-CodePudding

I am learning the breast cancer classification dataset in python. I am trying to plot histograms for each features, how am I able to arrange those histograms into three groups? Like the following screenshot:

What I am trying to achieve

Here is the code I used:

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()