计算 pandas 数据框中多列的变化率

Question

附件图像是一个测试数据，其中包含多列缺失值。

我需要通过计算前 12 个月的变化率来填补缺失值

例如：在附加的数据集中，我在第 23 行和第 24 行中缺少 weight_a、weight_b、weight_c 列中的缺失值，以填充第 23 行中的缺失值，weight_a 列我需要做 =(B22-B10)/12 + B22 来填充我需要做的第24行weight_a列的缺失值=(B23-B11)/12 + B23

to fill the missing value in row 23, weight_b column I need to do =(C22-C10)/12 + C22
to fill the missing value in row 24, weight_b column I need to do =(C23-C11)/12 + C23 

依此类推...对 weight_c 列重复（并且真实数据集对多个列有很多缺失值）

我如何编写 python 代码来为 dataframe 中的所有缺失值实现这个？

Answer 1

计算值然后手动更新它们：

result_23=[1,2,3] # calculate real value instead of [1,2,3]
result_24=[1,2,3] # calculate real value instead of [1,2,3]

#Calculate them in this way, Based on what you want
#(df.iloc[22]["B"]-df.iloc[10]["B"]/12)+df.iloc[22]["B"]

df.loc[df.index==23,["weight_a","weight_b","weight_c"]]=result_23
df.loc[df.index==24,["weight_a","weight_b","weight_c"]]=result_24