pandas DataFrame(5)-合并DataFrame与Series

之前已经学过DataFrame与DataFrame相加,Series与Series相加,这篇介绍下DataFrame与Series的相加:

import pandas as pd

s = pd.Series([1, 2, 3, 4])
df = pd.DataFrame({
    0: [10, 20, 30, 40],
    1: [50, 60, 70, 80],
    2: [90, 100, 110, 120],
    3: [130, 140, 150, 160]
})

print df + s

    0   1    2    3
0  11  52   93  134
1  21  62  103  144
2  31  72  113  154
3  41  82  123  164

首先将Series的索引值和DataFrame的索引值相匹配, s[0] 是 1 , df[0] 是 [10,20,30,40]

然后相当于向量化运算:  [10,20,30,40] + 1 ,得到: [11,21,31,41]

无论索引值怎么变化,都是按照这个套路来进行运算:

s = pd.Series([1, 2, 3, 4])
df = pd.DataFrame({0: [10], 1: [20], 2: [30], 3: [40]})

print df + s

    0   1   2   3
0  11  22  33  44

s = pd.Series([1, 2, 3, 4])
df = pd.DataFrame({0: [10, 20, 30, 40]})

print df + s

原文地址：https://www.cnblogs.com/liulangmao/p/9356116.html