如何在一个图形中绘制多个折线图(覆盖/分组) [英] How to plot several line charts in one figure (overlay/groupby)

问题描述

我想说明我的数据中几个人的一个变量随时间的变化.我在这里遇到一些基本命令的问题.

I would like to illustrate the change in one variable for several persons in my data over time. I have several issues with basic commands here.

这是我的数据:

import pandas as pd
df = pd.DataFrame({'year': ['1988', '1989', '1990', '1988', '1989', '1990', '1988', '1989', '1990'],
                   'id': ['1', '1', '1', '2', '2', '2', '3', '3', '3'],
                   'money': ['5', '7', '8', '8', '3', '3', '7', '8', '10']}).astype(int)

df.info()
df

我尝试使用matplotlib并开始为我的每个唯一ID循环.我是这个包的新手.首先，如何为每个图指定一条线仅连接3个点，而不是全部?其次，如何将这些图叠加到一个图中?

I tried to make use of matplotlib and started to loop for each of my unique IDs. I'm new to this package. First, how can I specify for each plot that only 3 points are connected for a line, not all? Second, how can I overlay those plots in one figure?

import matplotlib.pyplot as plt

for i in df.id.unique():
        df.plot.line(x='year', y='money')

推荐答案

由于已标记matplotlib，因此一种解决方案是在循环遍历DataFrame之前检查id，然后使用df[df['id']==i]进行绘制.

Since you have tagged matplotlib, one solution is to check for the id while looping through the DataFrame before plotting using df[df['id']==i].

要在一个图形中叠加这些图，请创建一个图形对象，并将轴ax传递给df.plot()函数.

To overlay those plots in one figure, create a figure object and pass the axis ax to the df.plot() function.

import matplotlib.pyplot as plt
import pandas as pd
df = pd.DataFrame({'year': ['1988', '1989', '1990', '1988', '1989', '1990', '1988', '1989', '1990'],
                   'id': ['1', '1', '1', '2', '2', '2', '3', '3', '3'],
                   'money': ['5', '7', '8', '8', '3', '3', '7', '8', '10']}).astype(int)

fig, ax = plt.subplots()

for i in df.id.unique():
    df[df['id']==i].plot.line(x='year', y='money', ax=ax, label='id = %s'%i)
plt.xticks(np.unique(df.year),rotation=45)    

Pandas解决方案如下所示.在这里，您以后必须修改图例.

Pandas solution using groupby would look like following. Here you will have to modify the legends later.

df.groupby('id').plot(x='year', y='money',legend=True, ax=ax)

h,l = ax.get_legend_handles_labels()
ax.legend(h, df.id.unique(), fontsize=12)
plt.xticks(np.unique(df.year), rotation=45)

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