使用 Pandas 在同一图中绘制分组数据 [英] Plotting grouped data in same plot using Pandas

问题描述

在 Pandas 中，我正在做:

In Pandas, I am doing:

bp = p_df.groupby('class').plot(kind='kde')

p_df 是一个 dataframe 对象.

然而，这会产生两个图，每个类一个.如何在同一情节中强制两个班级的情节?

However, this is producing two plots, one for each class. How do I force one plot with both classes in the same plot?

推荐答案

Version 1:

您可以创建轴，然后使用 DataFrameGroupBy.plot 将所有内容添加到这些轴:

Version 1:

You can create your axis, and then use the ax keyword of DataFrameGroupBy.plot to add everything to these axes:

import matplotlib.pyplot as plt

p_df = pd.DataFrame({"class": [1,1,2,2,1], "a": [2,3,2,3,2]})
fig, ax = plt.subplots(figsize=(8,6))
bp = p_df.groupby('class').plot(kind='kde', ax=ax)

结果如下:

不幸的是，图例的标签在这里没有太大意义.

Unfortunately, the labeling of the legend does not make too much sense here.

另一种方法是遍历组并手动绘制曲线:

Another way would be to loop through the groups and plot the curves manually:

classes = ["class 1"] * 5 + ["class 2"] * 5
vals = [1,3,5,1,3] + [2,6,7,5,2]
p_df = pd.DataFrame({"class": classes, "vals": vals})

fig, ax = plt.subplots(figsize=(8,6))
for label, df in p_df.groupby('class'):
    df.vals.plot(kind="kde", ax=ax, label=label)
plt.legend()

这样您就可以轻松控制图例.结果如下:

This way you can easily control the legend. This is the result:

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