Please help with assignment. It is Python code in a Jupyter notebook file.

Please help with the remaing code needed based on the Python code I have provided in the screen shots below

I need the following completed please (given the above code):

7) Do string encoding (i.e, encode string values to integers)

Second, modeling:

8) Split the data into training and testing sets (80-20)

9) Build different machine learning models like Decision Tree, Support Vector Machine, and Naive Bayes. Show the performance of the model (f1, accuracy, precision, and recall).

After completion please explain which learning model used above is the best? and why?

Thank you!

1000 rows 83 columns In [50]: 12#totalnumberofmissingvaluesinallvariablesprint("totalnumbersofmissingvalue:",df.isnull().sum().sum()) totalnumbersofmissingvalue:6741 In [62]: 1 \#the total number of missing values again in all variables. \#Now, after missing value imputation, it should be print(df. isnull(). sum()sum())