Data Sources
The location of the parked cars was extracted from the AutoTel website, every two minutes for several weeks. The raw data was saved in CSV format. In this lab, there are 6 csv files provided:
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car_location_training.csv
: Contains the training data that you need. These are the raw data collected from the AutoTel website. In this lab, we will process these raw data step by step and use it for forecasting the daily car rental demand.
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car_location_testing_daily_withoutLable.csv
: Contains the data that you need to predict. It has more column then the training set as we have aggrated t the data as daily records and provided the number of parking spots in the new car station. The prediction results need to be submitted for the in-class competition.
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tel_aviv_neighborhood.csv
: Contains the data that you need for visualization.
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sample_submission.csv
: A sample of what you should upload for the competition. The sample submission file contains the results from a dummy model.
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intermediate_results_df_test.csv
: The intermediate results of df_test we generated to save your time in Step 2. You will need to import this if you can't finish Part 2 before the break.
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intermediate_results_df_train_daily.csv
: The intermediate results of df_train_daily we generated to save your time in Step 2. You will need to import this if you can't finish Part 2 before the break.