散点对坐标的 plot，用 pandas DataFrame 标签的索引名称注释

Question

For a two-column pandas DataFrame, whose rows contain a pair of two values that belong to one another as xy coordinates, how can a 2D plot be generated such that each pair of coordinates are given an annotated text label equal to the index name for那一排？

例如，坐标 ( 0.983801 , 0.0155373 ) 应在 plot 中显示为单个点，并使用AXP进行注释。 与其余行类似，每个行都唯一命名

DataFrame 由两个一维 numpy arrays a和b构造而成，而标签是两者长度相等的列表：

#columns labeled on next line since the transpose of index arg is columns
df = pd.DataFrame(np.vstack((a,b)),index=['pe','jsc']).T 
df.index = labels #row labels

Answer 1

尝试这样的事情：

# sample data
df = pd.DataFrame(np.random.rand(4,2), columns=['pe','jsc'], index=list('abcd'))

plt.scatter(df['pe'], df['jsc'])
for idx, row in df.iterrows(): 
    plt.text(row['pe'], row['jsc'], idx)

Output：