sklearn MinMaxScaler that save rows and columns headers python

Question

I am trying to normalize the df and saving the columns and rows index/headers.

      Sym1 Sym2 Sym3 Sym4
1     1    1    1    2
8     1    3    3    2
9     1    2    2    2
24    4    2    4    1


scaler = MinMaxScaler(feature_range=(0, 1), copy=True)
scaler.fit(df)
normData = pd.DataFrame(scaler.transform(df))

But i get countinus rows and coulmns:

      0    1    2    3
0     0    0    0    0.8
1     0    1    0.65 0.8
2     0    0.24 0.5  0.2
3     0.5  0.5  0.5  0.25

and i want a dataframe like this:

      Sym1 Sym2 Sym3 Sym4
1     0    0    0    0.8
8     0    1    0.65 0.8
9     0    0.24 0.5  0.2
24    0.5  0.5  0.5  0.25

what can I do?

Answer 1

转换为DataFrame时，需要指定所需的列和索引。

normData = pd.DataFrame(scaler.transform(df), index=df.index, columns=df.columns)