从Pandas DataFrame绘图时注释数据点 [英] Annotate data points while plotting from Pandas DataFrame

问题描述

我想在数据点旁边标注数据点的值.我发现的示例仅将x和y作为向量处理.但是，我想对包含多个列的pandas DataFrame进行此操作.

I would like to annotate the data points with their values next to the points on the plot. The examples I found only deal with x and y as vectors. However, I would like to do this for a pandas DataFrame that contains multiple columns.

ax = plt.figure().add_subplot(1, 1, 1)
df.plot(ax = ax)
plt.show()

为多列DataFrame注释所有点的最佳方法是什么?

What is the best way to annotate all the points for a multi-column DataFrame?

推荐答案

是否要使用其他列之一作为注释的文本?这是我最近所做的.

Do you want to use one of the other columns as the text of the annotation? This is something I did recently.

从一些示例数据开始

In [1]: df
Out[1]: 
           x         y val
 0 -1.015235  0.840049   a
 1 -0.427016  0.880745   b
 2  0.744470 -0.401485   c
 3  1.334952 -0.708141   d
 4  0.127634 -1.335107   e

绘制点.在此示例中，我将y与x作图.

Plot the points. I plot y against x, in this example.

ax = df.set_index('x')['y'].plot(style='o')

编写一个在x，y和值上循环的函数，以便在该点旁边进行注释.

Write a function that loops over x, y, and the value to annotate beside the point.

def label_point(x, y, val, ax):
    a = pd.concat({'x': x, 'y': y, 'val': val}, axis=1)
    for i, point in a.iterrows():
        ax.text(point['x'], point['y'], str(point['val']))

label_point(df.x, df.y, df.val, ax)

draw()

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