Python DataFrame: How to replace Nan with value on one specific position

One method you can try is without using replace. When you know the index just assign the value you want Code:

Data.gender[2956]='F'

Try this

    Data.loc[[2956]]["gender"].replace(None, "F",inplace = True)

Dataframe.replace isn't meant to replace a value at a single position to begin with, but to replace all the values that correspond to something. So in your example, by using replace the best result you could have is having 'Scout Schultz' and 'Tk Tk' 's genders set to 'F'.

Since you know that the row 2956 has NaN in 'gender' column, you can do something like

data.loc[2956, 'gender'] = 'F'

When you get the value using column and row, you take the value, not that position in the dataframe. And you can't use replace() for a single value.

You can just change the value using:

 Data["gender"].loc[[2956]] = 'F'

You could just do this.

df.loc[2956,'gender'] = 'F'