如下所示：
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>>> import pandas as pd
>>> import numpy as np
# 生成模拟数据
>>> df = pd.DataFrame({'a':np.random.randint(1, 100, 10),\
'b':np.random.randint(1, 100, 10)},\
index=map(str, range(10)))
>>> df
a b
0 21 54
1 53 28
2 18 87
3 56 40
4 62 34
5 74 10
6 7 78
7 58 79
8 66 80
9 30 21
# 纵向一阶差分，当前行减去上一行
>>> df.diff()
a b
0 NaN NaN
1 32.0 -26.0
2 -35.0 59.0
3 38.0 -47.0
4 6.0 -6.0
5 12.0 -24.0
6 -67.0 68.0
7 51.0 1.0
8 8.0 1.0
9 -36.0 -59.0
# 横向一阶差分，当前列减去左边的列
>>> df.diff(axis=1)
a b
0 NaN 33.0
1 NaN -25.0
2 NaN 69.0
3 NaN -16.0
4 NaN -28.0
5 NaN -64.0
6 NaN 71.0
7 NaN 21.0
8 NaN 14.0
9 NaN -9.0
# 纵向二阶差分
>>> df.diff(periods=2)
a b
0 NaN NaN
1 NaN NaN
2 -3.0 33.0
3 3.0 12.0
4 44.0 -53.0
5 18.0 -30.0
6 -55.0 44.0
7 -16.0 69.0
8 59.0 2.0
9 -28.0 -58.0
# 纵向二阶差分，丢弃空值
>>> df.diff(periods=2).dropna()
a b
2 -3.0 33.0
3 3.0 12.0
4 44.0 -53.0
5 18.0 -30.0
6 -55.0 44.0
7 -16.0 69.0
8 59.0 2.0
9 -28.0 -58.0
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以上这篇Python使用pandas对数据进行差分运算的方法就是小编分享给大家的全部内容了，希望能给大家一个参考，也希望大家多多支持服务器之家。
原文链接：https://blog.csdn.net/oh5W6HinUg43JvRhhB/article/details/78349014