Predicting Customer Activity Absence
First issue in your model building method is that you have data in the binary form for each month and you are trying to predict into a 6 month time period. You gotta define what will be considered active in the next 6 months?


Active in 6 months  = Active in each individual months?
or 
Active in 6 months = Active in any given month?


If you want to first predict for individual months, you can use logistic regression. It is useful for a binary classification of this kind.

Use LogisticRegression from sklearn.linear_model to train and fit the data.
Then, use confusion matrix and classification_report from sklearn.metrics to test the performance of your model.

After having predictions for next 6 months, you can create a new column that checks if there are any 1's in the last 6 months and stores 1 else stores 0