需要在每次迭代中循环 pandas df 两个连续列名的集合，以在不同的 excel 工作表中创建单独的数据透视表

Question

输入方向：

df = pd.DataFrame({
    'DATE':['200701','200702','200703','200704'],
    'A':['35','42','43','25'],'B':['33','40','39','28'],
    'DIFFERENCE OF A&B':['2','2','4','-3'],
    'C':['26','28','24','19'],'D':['20','25','30','25'],
    'DIFFERENCE OF C&D':['6','3','-6','-6']
})

预期输出：

迭代 1 枢轴：

pivot1 = pd.pivot_table(df,index=['DATE'],values=['A','B','DIFFERENCE OF A&B'],aggfunc='sum')

迭代 2 枢轴：

pivot2 = pd.pivot_table(df,index=['DATE'],values=['C','D','DIFFERENCE OF C&D'],aggfunc='sum')

依此类推接下来的 2 个连续列的数据透视值。

请帮助我，我很挣扎。

Answer 1

pivot_table() 函数似乎对您提供的数据框示例没有任何作用，但是，也许这会起作用。查看内联评论。

df = pd.DataFrame({
    'DATE':['200701','200702','200703','200704'],
    'A':['35','42','43','25'],'B':['33','40','39','28'],
    'DIFFERENCE OF A&B':['2','2','4','-3'],
    'C':['26','28','24','19'],'D':['20','25','30','25'],
    'DIFFERENCE OF C&D':['6','3','-6','-6']
})

df.set_index('DATE', inplace=True) # set the index to DATE

for i in range(0, len(df.columns), 3): # assumes your columns are multiple of 3
    print(df.iloc[: , i:i+3 ]) # find the dataset for successive three columns
    # the next line gives the same output as previous line
    # print(pd.pivot_table(df.iloc[: , i:i+3 ],index=df.iloc[: , i:i+3 ].index,values=df.iloc[: , i:i+3 ].columns.to_list(),aggfunc='sum'))

需要在每次迭代中循环 pandas df 两个连续列名的集合，以在不同的 excel 工作表中创建单独的数据透视表

Need to loop over pandas df set of two consecutive column names in each iteration to create separate pivots in different excel sheets

python

excel

pivot

for-loop

pandas