如何在for循环中堆叠几个pandas DataFrame

Question

Since I have multiple pandas DataFrames, I want to run the .stack() method on all of them using a for loop. Other methods like labeling columns and setting indexes work, but for some reason the stack method doesn't lead to any changes:

for df in [df1, df2, df3, df4]:
    df = df.stack()

Result:

print(df1.head())

        Q1 1990  Q2 1990  Q3 1990   ...     Q2 2018  Q3 2018  Q4 2018
EC                                  ...                              
C13840      NaN      NaN      NaN   ...         NaN      NaN      NaN
C28525      NaN      NaN      NaN   ...     8480.00  8125.00      NaN
C06541      NaN      NaN      NaN   ...         NaN      NaN      NaN
C51345      NaN      NaN      NaN   ...       13.75    15.00      NaN
C44265      NaN      NaN      NaN   ...      141.90   129.54   133.44

Expected result:

print(df1.head(10))

EC             
C13840  Q1 1990   NaN
        Q2 1990   NaN
        Q3 1990   NaN
        Q4 1990   NaN
        Q1 1991   NaN
        Q2 1991   NaN
        Q3 1991   NaN
        Q4 1991   NaN
        Q1 1992   NaN
        Q2 1992   NaN
        ...
        ...

Thank you.

Answer 1

Assign output to new list od Series , because stack not working inplace:

dfs = [df.stack() for df in [df1, df2, df3, df4]]

And then if need assign back:

df1, df2, df3, df4 = dfs

Or join together:

df = pd.concat(dfs, axis=1)

Answer 2

If I understand correctly you want to modify your dfs in place however stack is not an inplace operator but returns a new df as the output

df = pd.DataFrame({'a': [1,2], 'b': [3,4]})
df1 = pd.DataFrame({'a': [5,6], 'b': [7,8]})


new_dfs = list(map(pd.DataFrame.stack, [df, df1]))