如何将 pandas fillna NaN 与下一行值的负值一起使用

Question

我有 table 城市的每日（时间序列）降雨。 pandas同城次日雨的负数如何用pandas填NaN？谢谢你。

import pandas as pd
import numpy as np
rain_before = pd.DataFrame({'date':Date*2,'city':list('aaaaabbbbb'),'rain':[6,np.nan,1,np.nan,np.nan,4,np.nan,np.nan,8,np.nan]})

# after fillna, the table should look like this. 
rain_after_fillna = pd.DataFrame({'date':Date*2,'city':list('aaaaabbbbb'),'rain':[6,-1,1,np.nan,np.nan,4,np.nan,-8,8,np.nan]})

Answer 1

你可以移动和填充

rain_before['rain'].fillna(rain_before.groupby('city')['rain']
                           .transform(lambda x: -x.shift(-1)))

0    6.0
1   -1.0
2    1.0
3   NaN 
4   NaN 
5    4.0
6   NaN 
7   -8.0
8    8.0
9   NaN 
Name: rain, dtype: float64

Answer 2

使用shift(-1)*-1的系列。没有样本数据集，所以我综合了但不包括城市。同样的方法可以用于城市，需要考虑排序

import datetime as dt
import random
df = pd.DataFrame({"Date":pd.date_range(dt.date(2021,1,1), dt.date(2021,1,10))
             ,"rainfall":[i*random.randint(0,1) for i in range(10)]}).replace({0:np.nan})

df["rainfall_nan"] = df["rainfall"].fillna(df["rainfall"].shift(-1)*-1)

输出

      Date  rainfall  rainfall_nan
2021-01-01       NaN          -1.0
2021-01-02       1.0           1.0
2021-01-03       2.0           2.0
2021-01-04       3.0           3.0
2021-01-05       NaN          -5.0
2021-01-06       5.0           5.0
2021-01-07       6.0           6.0
2021-01-08       7.0           7.0
2021-01-09       NaN          -9.0
2021-01-10       9.0           9.0

如何将 pandas fillna NaN 与下一行值的负值一起使用

how to use pandas fillna NaN with the negative of the next row value

python

pandas

fillna

输出