将多个图分组到一张图中Python

我的函数返回 28 个图（图），但我需要将它们分组在一个图上，这是我生成 28 个图的代码

for cat in df.ASS_ASSIGNMENT.unique() :
    a = df.loc[df['ASS_ASSIGNMENT'] == cat]
    dates = a['DATE']
    prediction = a['CSPL_RECEIVED_CALLS']
    plt.plot(dates,prediction)  
    plt.ylabel("nmb_app")
    plt.legend([cat.decode('utf-8')],loc='best')
    plt.xlabel(cat.decode('utf-8'))

Use plt.subplots。例如，

import numpy as np
import matplotlib.pyplot as plt

fig, axes = plt.subplots(ncols=7, nrows=4)

for i, ax in enumerate(axes.flatten()):
    x = np.random.randint(-5, 5, 20)
    y = np.random.randint(-5, 5, 20)
    ax.scatter(x, y)
    ax.set_title('Axis {}'.format(i))

plt.tight_layout()

更深入一点，正如 Mauve 指出的那样，这取决于您是否想要在一个图中的单个图中包含 28 条曲线，或者在一个图中包含 28 个单独的图，每个图都有自己的轴。

假设你有一个数据框，df，有 28 列，您可以使用以下命令将所有 28 条曲线放在单个图中的单个图上plt.subplots像这样，

fig1, ax1 = plt.subplots()
df.plot(color=colors, ax=ax1)
plt.legend(ncol=4, loc='best')

如果您想要 28 个单独的轴都在一个图中，您可以使用plt.subplots这边走

fig2, axes = plt.subplots(nrows=4, ncols=7)
for i, ax in enumerate(axes.flatten()):
    df[df.columns[i]].plot(color=colors[i], ax=ax)
    ax.set_title(df.columns[i])

Here df好像

In [114]: df.shape
Out[114]: (15, 28)

In [115]: df.head()
Out[115]: 
         IYU        ZMK        DRO       UIC       DOF       ASG       DLU  \
0   0.970467   1.026171  -0.141261  1.719777  2.344803  2.956578  2.433358   
1   7.982833   7.667973   7.907016  7.897172  6.659990  5.623201  6.818639   
2   4.608682   4.494827   6.078604  5.634331  4.553364  5.418964  6.079736   
3   1.299400   3.235654   3.317892  2.689927  2.575684  4.844506  4.368858   
4  10.690242  10.375313  10.062212  9.150162  9.620630  9.164129  8.661847   

         BO1       JFN       S9Q    ...          X4K       ZQG       2TS  \
0   2.798409  2.425745  3.563515    ...     7.623710  7.678988  7.044471   
1   8.391905  7.242406  8.960973    ...     5.389336  5.083990  5.857414   
2   7.631030  7.822071  5.657916    ...     2.884925  2.570883  2.550461   
3   6.061272  4.224779  5.709211    ...     4.961713  5.803743  6.008319   
4  10.240355  9.792029  8.438934    ...     6.451223  5.072552  6.894701   

        RS0       P6T       FOU       LN9       CFG       C9D       ZG2  
0  9.380106  9.654287  8.065816  7.029103  7.701655  6.811254  7.315282  
1  3.931037  3.206575  3.728755  2.972959  4.436053  4.906322  4.796217  
2  3.784638  2.445668  1.423225  1.506143  0.786983 -0.666565  1.120315  
3  5.749563  7.084335  7.992780  6.998563  7.253861  8.845475  9.592453  
4  4.581062  5.807435  5.544668  5.249163  6.555792  8.299669  8.036408  

并由以下人员创建

import pandas as pd
import numpy as np
import string
import random

m = 28
n = 15

def random_data(m, n):
    return np.cumsum(np.random.randn(m*n)).reshape(m, n)

def id_generator(number, size=6, chars=string.ascii_uppercase + string.digits):
    sequence = []
    for n in range(number):
        sequence.append(''.join(random.choice(chars) for _ in range(size)))
    return sequence

df = pd.DataFrame(random_data(n, m), columns=id_generator(number=m, size=3))

颜色定义为

import seaborn as sns
colors = sns.cubehelix_palette(28, rot=-0.4)