Changing categorical data to binary data is not reflected on the dataset
You need to transform your independent variables into numeric values. Normally for binary variables, we use the 0-1-encoding. Introduce a new variable called is_female. If the observation is a male person then give the variable the value $0$ and if the observation is a female person give the observation the value $1$.

If you have categorical variables like a city with three categories you will need to create additional variables. Imagine we have the possible values ["New York", "London", "Moskau"]. Then you create three variables is_new_york, is_london, is_moskau.
If we have an observation from New York this will result in is_new_york=1, is_london=0, is_moskau=0. If we have an observation from London then the values will be is_new_york=0, is_london=1, is_moskau=0 and if we have an observation from Moskau then the values will be is_new_york=0, is_london=0, is_moskau=1. This type of encoding is called one-hot encoding. You can also have multiple cities. For example, if a person lives in Moskau and London then you can use is_new_york=0, is_london=1, is_moskau=1.