Pandas.plot（subplots = True），每个子图中有3列

I have a DataFrame with 700 rows and 6 columns:

我有一个包含700行和6列的DataFrame：

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

df = pd.DataFrame(np.random.rand(700,6))

I can plot all columns in a single plot by calling:

我可以通过调用以下方式在一个图中绘制所有列：

df.plot()

And I can plot each column in a single plot by calling:

我可以通过调用以下内容在单个图中绘制每个列：

df.plot(subplots=True)

How can I have two subplots with three columns each from my DataFrame?!

如何从我的DataFrame中获得两个包含三列的子图？

1 个解决方案

#1

Here's a general approach to plot a dataframe with n columns in each subplot:

这是绘制每个子图中具有n列的数据帧的一般方法：

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

df = pd.DataFrame(np.random.rand(700,6))

col_per_plot = 3
cols = df.columns.tolist()
# Create groups of 3 columns
cols_splits = [cols[i:i+col_per_plot] for i in range(0, len(cols), col_per_plot)]  

# Define plot grid.
# Here I assume it is always one row and many columns. You could fancier...
fig, axarr = plt.subplots(1, len(cols_splits))
# Plot each "slice" of the dataframe in a different subplot
for cc, ax in zip(cols_splits, axarr):
    df.loc[:, cc].plot(ax = ax)

This gives the following picture:

这给出了以下图片：

#1