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Let´s say I have a DataFrame df_a and another one df_b.

I want to replace lines 42 to 51 of df_a with the corresponding rows of df_b (same number of rows, but more columns as df_a).

My current code is

df_a.loc[45:52,:] = df_b.loc[45:52,"Column A":"Column D"]

where "Column A":"Column D" matches the total number of columns of df_a.

I´m getting an unintented result where all selected terms in df_a get replaced by nan instead of df_b values. Does anyone know an easy way to do it?

Matheus Mansour
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1 Answers1

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df_1 = pd.DataFrame({"a" : (1,2,3,4), "b" : (5,4,6,7)})
df_2 = pd.DataFrame({"a" : (1,2,3,5), "b" : (2,3,6,3), "c" : (10,11,12,13)})
print(df_1)
   a  b
0  1  5
1  2  4
2  3  6
3  4  7
print(df_2)
    a   b   c
0   1   2   10
1   2   3   11
2   3   6   12
3   5   3   13
df_1.iloc[2,] = df_2.iloc[3,1:3].values
   a   b
0  1   5
1  2   4
2  3  13
3  4   7

In this example I replaced the values of the 3rd row of df_1 with the last 2 values of the 4th row of df_2

domiziano
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  • Thank you so much! Apparently I was just missing the ".values" at the end. I´m new to pandas, but I assumed the right-hand side of my original statement would already be fetching the actual "values". Thanks once again! – Matheus Mansour May 05 '21 at 16:04