convert datatype after add row end of the dataframe with loc

September 5, 2022

I have this dataframe.

data = {"score":[10, 54, 65, 23, 94, 40, 79, 89], "code":[2, 6, 8, 6, 4, 9, 1, 5], "percentage":[0.12, 0.65, 0.03, 0.96, 0.43, 0.76, 0.23, 0.93]}
df = pd.DataFrame(data)
print(df)

Output:

   score  code  percentage
0     10     2        0.12
1     54     6        0.65
2     65     8        0.03
3     23     6        0.96
4     94     4        0.43
5     40     9        0.76
6     79     1        0.23
7     89     5        0.93

dataframe have been changed datatype to float after add row end of the dataframe with loc

df.loc[len(df)] = [43, 9, 0.55]
print(df)

Output:

   score  code  percentage
0   10.0   2.0        0.12
1   54.0   6.0        0.65
2   65.0   8.0        0.03
3   23.0   6.0        0.96
4   94.0   4.0        0.43
5   40.0   9.0        0.76
6   79.0   1.0        0.23
7   89.0   5.0        0.93
8   43.0   9.0        0.55

why? can any one help me?

>Solution :

This assignment handles your list as Series, which has a unique dtype. Thus the 0.55 forces the whole row to be float.

You can use concat:

pd.concat([df, pd.DataFrame([[43, 9, 0.55]], columns=df.columns, index=[len(df)])])

output:

   score  code  percentage
0     10     2        0.12
1     54     6        0.65
2     65     8        0.03
3     23     6        0.96
4     94     4        0.43
5     40     9        0.76
6     79     1        0.23
7     89     5        0.93
8     43     9        0.00