Insert row into dataframe based on value in a specified column

Question

Not sure if this is even possible, but i am trying to insert the header of my dataframe into a new row when the value in the 'Strategy' column changes.

Current Output:

Amount Code Strategy
1,000 Fund_1 A
2,000 Fund_2 A
3,000 Fund_1 B
4,000 Fund_2 B
5,000 Fund_1 C
6,000 Fund_2 C

Desired Output:

Amount Code Strategy
1,000 Fund_1 A
2,000 Fund_2 A
Amount Code Strategy
3,000 Fund_1 B
4,000 Fund_2 B
Amount Code Strategy
5,000 Fund_1 C
6,000 Fund_2 C

Is there an easy way to do this?

Answer 1

Here's one way you could achieve this effect using reindexing and pandas.concat :

d = {x:x for x in df.columns}

header_rows = df.drop_duplicates('Strategy').drop(0).assign(**d)
header_rows.index -= 0.5

df_new = pd.concat([df, header_rows]).sort_index().reset_index(drop=True)
print(df_new)

   Amount    Code  Strategy
0   1,000  Fund_1         A
1   2,000  Fund_2         A
2  Amount    Code  Strategy
3   3,000  Fund_1         B
4   4,000  Fund_2         B
5  Amount    Code  Strategy
6   5,000  Fund_1         C
7   6,000  Fund_2         C