使用matplotlib的线图/时间序列上的多条线 [英] Multiple lines on line plot/time series with matplotlib

问题描述

我如何在matplotlib或Python上的plot.ly上绘制由分类变量表示的多条迹线?我正在尝试从R复制geom_line(aes(x = Date，y = Value，color = Group)函数.

How do I plot multiple traces represented by a categorical variable on matplotlib or plot.ly on Python? I am trying to replicate the geom_line(aes(x=Date,y=Value,color=Group) function from R.

有没有办法在 Python 上实现这一点，而无需将组放在单独的列中?我是否必须不可避免地重组数据?

Is there a way to achieve this on Python without the need to have the groups in separate columns? Do I have to restructure the data inevitably?

假设我有以下数据:

Date    Group   Value
1/01/2015   A   50
2/01/2015   A   60
1/01/2015   B   100
2/01/2015   B   120
1/01/2015   C   40
2/01/2015   C   55
1/01/2015   D   36
2/01/2015   D   20

我想在x轴上显示日期，在y轴上显示值，并用不同的彩色线条/迹线表示组类别.

I would like date on the x axis, value on the y axis, and the group categories represented by different coloured lines/traces.

谢谢.

推荐答案

假设您的数据位于pandas数据框 df 中，则在没有分组位于单独列中的情况下很难进行绘制，实际上，很容易一步就完成了这一步，

Assuming your data is in a pandas dataframe df, it would be hard to plot it without the groups being in separate columns, but that is actually a step very easily done in one line,

df.pivot(index="Date", columns="Group", values="Value").plot()

完整示例:

u = u"""Date    Group   Value
1/01/2015   A   50
2/01/2015   A   60
1/01/2015   B   100
2/01/2015   B   120
1/01/2015   C   40
2/01/2015   C   55
1/01/2015   D   36
2/01/2015   D   20"""

import io
import pandas as pd
import matplotlib.pyplot as plt

df = pd.read_csv(io.StringIO(u), delim_whitespace=True)
df["Date"] = pd.to_datetime(df["Date"])

df.pivot(index="Date", columns="Group", values="Value").plot()

plt.show()

这篇关于使用matplotlib的线图/时间序列上的多条线的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！