Python 将 x 和 y 标签添加到熊猫图中

Add x and y labels to a pandas plot

提问by Everaldo Aguiar

Suppose I have the following code that plots something very simple using pandas:

假设我有以下代码使用 Pandas 绘制一些非常简单的内容：

import pandas as pd
values = [[1, 2], [2, 5]]
df2 = pd.DataFrame(values, columns=['Type A', 'Type B'], 
                   index=['Index 1', 'Index 2'])
df2.plot(lw=2, colormap='jet', marker='.', markersize=10, 
         title='Video streaming dropout by category')

How do I easily set x and y-labels while preserving my ability to use specific colormaps? I noticed that the plot()wrapper for pandas DataFrames doesn't take any parameters specific for that.

如何轻松设置 x 和 y 标签，同时保留使用特定颜色图的能力？我注意到plot()pandas DataFrames的包装器没有采用任何特定于此的参数。

采纳答案by TomAugspurger

The df.plot()function returns a matplotlib.axes.AxesSubplotobject. You can set the labels on that object.

该df.plot()函数返回一个matplotlib.axes.AxesSubplot对象。您可以在该对象上设置标签。

ax = df2.plot(lw=2, colormap='jet', marker='.', markersize=10, title='Video streaming dropout by category')
ax.set_xlabel("x label")
ax.set_ylabel("y label")

Or, more succinctly: ax.set(xlabel="x label", ylabel="y label").

或者，更简洁地说：ax.set(xlabel="x label", ylabel="y label").

Alternatively, the index x-axis label is automatically set to the Index name, if it has one. so df2.index.name = 'x label'would work too.

或者，索引 x 轴标签会自动设置为索引名称（如果有）。所以df2.index.name = 'x label'也会起作用。

回答by jesukumar

You can use do it like this:

你可以像这样使用它：

import matplotlib.pyplot as plt 
import pandas as pd

plt.figure()
values = [[1, 2], [2, 5]]
df2 = pd.DataFrame(values, columns=['Type A', 'Type B'], 
                   index=['Index 1', 'Index 2'])
df2.plot(lw=2, colormap='jet', marker='.', markersize=10,
         title='Video streaming dropout by category')
plt.xlabel('xlabel')
plt.ylabel('ylabel')
plt.show()

Obviously you have to replace the strings 'xlabel' and 'ylabel' with what you want them to be.

显然，您必须将字符串 'xlabel' 和 'ylabel' 替换为您想要的字符串。

回答by shoyer

If you label the columns and index of your DataFrame, pandas will automatically supply appropriate labels:

如果您标记 DataFrame 的列和索引，pandas 将自动提供适当的标签：

import pandas as pd
values = [[1, 2], [2, 5]]
df = pd.DataFrame(values, columns=['Type A', 'Type B'], 
                  index=['Index 1', 'Index 2'])
df.columns.name = 'Type'
df.index.name = 'Index'
df.plot(lw=2, colormap='jet', marker='.', markersize=10, 
        title='Video streaming dropout by category')

In this case, you'll still need to supply y-labels manually (e.g., via plt.ylabelas shown in the other answers).

在这种情况下，您仍然需要手动提供 y 标签（例如，通过plt.ylabel其他答案中显示的方式）。

回答by Selah

For cases where you use pandas.DataFrame.hist:

对于您使用的情况pandas.DataFrame.hist：

plt = df.Column_A.hist(bins=10)

Note that you get an ARRAY of plots, rather than a plot. Thus to set the x label you will need to do something like this

请注意，您会得到一组图，而不是图。因此，要设置 x 标签，您需要执行以下操作

plt[0][0].set_xlabel("column A")

回答by Serenity

It is possible to set both labels together with axis.setfunction. Look for the example:

可以将两个标签与axis.set功能一起设置。查找示例：

import pandas as pd
import matplotlib.pyplot as plt
values = [[1,2], [2,5]]
df2 = pd.DataFrame(values, columns=['Type A', 'Type B'], index=['Index 1','Index 2'])
ax = df2.plot(lw=2,colormap='jet',marker='.',markersize=10,title='Video streaming dropout by category')
# set labels for both axes
ax.set(xlabel='x axis', ylabel='y axis')
plt.show()

回答by Dr. Arslan

pandasuses matplotlibfor basic dataframe plots. So, if you are using pandasfor basic plot you can use matplotlib for plot customization. However, I propose an alternative method here using seabornwhich allows more customization of the plot while not going into the basic level of matplotlib.

pandas使用matplotlib基本数据帧图。因此，如果您pandas用于基本绘图，则可以使用 matplotlib 进行绘图自定义。但是，我在这里提出了一种替代方法，seaborn它允许在不进入matplotlib.

Working Code:

工作代码：

import pandas as pd
import seaborn as sns
values = [[1, 2], [2, 5]]
df2 = pd.DataFrame(values, columns=['Type A', 'Type B'], 
                   index=['Index 1', 'Index 2'])
ax= sns.lineplot(data=df2, markers= True)
ax.set(xlabel='xlabel', ylabel='ylabel', title='Video streaming dropout by category') 

回答by Dror Hilman

what about ...

关于什么 ...

import pandas as pd
import matplotlib.pyplot as plt

values = [[1,2], [2,5]]

df2 = pd.DataFrame(values, columns=['Type A', 'Type B'], index=['Index 1','Index 2'])

(df2.plot(lw=2,
          colormap='jet',
          marker='.',
          markersize=10,
          title='Video streaming dropout by category')
    .set(xlabel='x axis',
         ylabel='y axis'))

plt.show()