Inserting value to pandas DataFrame to specific cell without deleting other values in column

I have a DataFrame df with roughly this format:

I want to insert a new value where alpha == 0.5 in the result-column. When I try that, however, the existing values in that column are deleted.

To insert the value, I tried this code:

import pandas as pd

df = pd.read_excel(file, engine="openpyxl")
df_index = df.index[df['alpha_loss'] == 0.5]
df.loc[df_index, 'result'] = 0.2

I’ve also tried replacing the last line with this:
df.at[df_index, 'result'] = 0.2
but get the same result.

The DataFrame I was expecting is:

Instead, this is the result:

What is the problem here? Why does this remove the other values in my column?
I am using pandas2.0.3 and python3.9

Edit:
It was my own fault, I mistyped the column name, but did not see it, since I was trying to write to the last column and print(df) only showed the last one. The actual result was something like this:
| alpha | result | result2 |
| ——– | ——– | ——– |
| 0.5 | NaN | 0.2 |
| 1 | 0.89 | NaN |
| 1.5 | NaN | NaN |

>Solution :

You code should work with a default range index. However, the second line is not needed. Directly use boolean indexing:

df.loc[df['alpha_loss'] == 0.5, 'result'] = 0.2

Output:

   alpha  result
0    0.5    0.20
1    1.0    0.89
2    1.5     NaN

Your code might fail if you have duplicated indices in the index, while boolean indexing is independent of the index.