pandas 使用子图绘制熊猫数据框（子图 = True）：放置图例并使用紧密布局
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Plot pandas dataframe with subplots (subplots=True): Place legend and use tight layout
提问by Cord Kaldemeyer
I really like pandas to handle and analyze big datasets. So far, I have mostly used matplotlib for plotting but now want to use pandas own plot functionalities (based on matplotlib) since it needs less code and seems to be sufficient for me in most cases. Especially the subplots to have a guick glance at big dataframes like in the following example..
我真的很喜欢用Pandas来处理和分析大数据集。到目前为止，我主要使用 matplotlib 进行绘图，但现在想使用 Pandas 自己的绘图功能（基于 matplotlib），因为它需要的代码较少，并且在大多数情况下对我来说似乎已经足够了。特别是子图可以快速浏览大数据框，如下例所示..
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
# Generate random data
df = pd.DataFrame(np.random.randn(96,12),
columns=['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J',
'K', 'L'])
# Plotting
df.plot(kind='line', subplots=True, grid=True, title="Sample Data (Unit)",
layout=(4, 3), sharex=True, sharey=False, legend=True,
style=['r', 'r', 'r', 'g', 'g', 'g', 'b', 'b', 'b', 'r', 'r', 'r'],
xticks=np.arange(0, len(df), 16))
..which brings me to my questions:
..这让我想到了我的问题：
1.) How can I place all legends in the subplots at the same place (e. g. centered, outside, topright)?
1.) 如何将子图中的所有图例放置在同一位置（例如居中、外部、顶部）？
2.) Can I somehow use matplotlibs "Tight Layout" (http://matplotlib.org/users/tight_layout_guide.html) for the plot?
2.) 我可以以某种方式使用 matplotlibs“紧密布局”( http://matplotlib.org/users/tight_layout_guide.html) 来绘制情节吗？
Thanks in advance!
提前致谢！
回答by tmdavison
You can have all the legends in the same place, but you would have to create them in a separate step.
# Plotting df.plot(kind='line', subplots=True, grid=True, title="Sample Data (Unit)", layout=(4, 3), sharex=True, sharey=False, legend=False, style=['r', 'r', 'r', 'g', 'g', 'g', 'b', 'b', 'b', 'r', 'r', 'r'], xticks=np.arange(0, len(df), 16)) [ax.legend(loc=1) for ax in plt.gcf().axes]Sure. just use
plt.tight_layout()before youshoworsavefig. Compare the two examples below created with and withouttight_layout.
您可以将所有图例放在同一位置，但您必须在单独的步骤中创建它们。
# Plotting df.plot(kind='line', subplots=True, grid=True, title="Sample Data (Unit)", layout=(4, 3), sharex=True, sharey=False, legend=False, style=['r', 'r', 'r', 'g', 'g', 'g', 'b', 'b', 'b', 'r', 'r', 'r'], xticks=np.arange(0, len(df), 16)) [ax.legend(loc=1) for ax in plt.gcf().axes]当然。只
plt.tight_layout()在你show或之前使用savefig。比较下面使用和不使用tight_layout.
Without tight_layout():
没有tight_layout()：
With tight_layout():
与tight_layout()：
