如何计算 pandas 中的多行差异？

Question

I want to calculate difference between each row and the next 5 rows and return the maximum of all those values (non Nan only) and repeat the same operation for all the rows in pandas dataframe and finally print the values in a new column. I have tried .shift(1) function and tried doing it iteratively for all the rows, but it seems very slow.

A'  B'  Output
AA  1   4
BB  2   3
CC  3   2
DD  4   1
EE  5   0

Answer 1

Have you try diff ?

import pandas as pd
df = pd.DataFrame({'a': [1,2,3,4,5,0,5,1,4,3,2]})
col_n = []
diff_r = 5
for i in range(1, diff_r+1):
  col_n.append('d_'+str(i))
  df['d_'+str(i)] = df['a'].diff(i).shift(periods=-i)
df['d_abs_max'] = df[col_n].abs().max(axis=1)
df['d_max'] = df[col_n].max(axis=1)
print(df)

    a  d_1  d_2  d_3  d_4  d_5  d_abs_max  d_max
0   1  1.0  2.0  3.0  4.0 -1.0        4.0    4.0
1   2  1.0  2.0  3.0 -2.0  3.0        3.0    3.0
2   3  1.0  2.0 -3.0  2.0 -2.0        3.0    2.0
3   4  1.0 -4.0  1.0 -3.0  0.0        4.0    1.0
4   5 -5.0  0.0 -4.0 -1.0 -2.0        5.0    0.0
5   0  5.0  1.0  4.0  3.0  2.0        5.0    5.0
6   5 -4.0 -1.0 -2.0 -3.0  NaN        4.0   -1.0
7   1  3.0  2.0  1.0  NaN  NaN        3.0    3.0
8   4 -1.0 -2.0  NaN  NaN  NaN        2.0   -1.0
9   3 -1.0  NaN  NaN  NaN  NaN        1.0   -1.0
10  2  NaN  NaN  NaN  NaN  NaN        NaN    NaN