The answer by pcko1 is correct in the sense that it will make the code run. But what you exactly require to do is one hot encoding. I say that because if encoding the categorical variables that are nominal with increasing numbers like 1, 2, 3 etc. does not make sense. Have a look at this question.

You need to encode all the categorical variables as 0-1. By that I mean, attach one column for each categorical variable in the data set, denoting its presence by a 1 and absence by a 0 in the respective rows of the data set.

#I don't know why he did this one

That has been done to have a separate data set for testing the model after it has been trained over the training set.

Just a reminder.

I am trying to copy a code from a video to do a decision tree program, which will predict if a student will pass or not depending on 30 parameters given.

The correct term should be variables not parameters.

The answer by pcko1 is useful in the sense that it will make the code run. But what you exactly require to do is one hot encoding. I say that because encoding the categorical variables that are nominal with increasing numbers like 1, 2, 3 etc. does not make sense. Have a look at this question.

You need to encode all the categorical variables as 0-1. By that I mean, attach one column for each categorical variable in the data set, denoting its presence by a 1 and absence by a 0 in the respective rows of the data set.

#I don't know why he did this one

That has been done to have a separate data set for testing the model after it has been trained over the training set.

Just a reminder.

I am trying to copy a code from a video to do a decision tree program, which will predict if a student will pass or not depending on 30 parameters given.

The correct term should be variables not parameters.

The answer by pcko1 is correct in the sense that it will make the code run. But what you exactly require to do is one hot encoding. Have a look at this question.

You need to encode all the categorical variables as 0-1. By that I mean, attach one column for each categorical variable in the data set, denoting its presence by a 1 and absence by a 0 in the respective rows of the data set.

#I don't know why he did this one

That has been done to have a separate data set for testing the model after it has been trained over the training set.

Just a reminder.

I am trying to copy a code from a video to do a decision tree program, which will predict if a student will pass or not depending on 30 parameters given.

The correct term should be variables not parameters.

The answer by pcko1 is correct in the sense that it will make the code run. But what you exactly require to do is one hot encoding. I say that because if encoding the categorical variables that are nominal with increasing numbers like 1, 2, 3 etc. does not make sense. Have a look at this question.

You need to encode all the categorical variables as 0-1. By that I mean, attach one column for each categorical variable in the data set, denoting its presence by a 1 and absence by a 0 in the respective rows of the data set.

#I don't know why he did this one

That has been done to have a separate data set for testing the model after it has been trained over the training set.

Just a reminder.

I am trying to copy a code from a video to do a decision tree program, which will predict if a student will pass or not depending on 30 parameters given.

The correct term should be variables not parameters.