{
  "fetched_at": "2026-10-19T07:22:28Z",
  "source_url": "https://www.kaggle.com/competitions/bgurcoursefall2020/data",
  "pages": [
    {
      "name": "data-description",
      "content": "<p>This page shows up underneath the data files. We have provided: train, test and an example for a submission file. The train data includes the parameters described below. Your goal is to predict the instant air temperature. The instant air temperature is the value measured at the given time. The test file does not include the instant air temperature it is for you to predict. The test data also includes an id for each observation. The id will be used in the submission file. The submission file will include two columns, the first is the id of the observation and the second is the predicted value for the  instant air temperature</p>\n\n<p>\n\n\n<ul>\n<li><strong>train.csv</strong> - the training set</li>\n<li><strong>test.csv</strong> - the test set</li>\n<li><strong>submission_example\n.csv</strong> - a sample submission file in the correct format</li>\n\n</ul><h2>Data fields</h2>\n<ul>\n\n</p><h2>The climate parameters include: </h2>\n<ul>\n\n<li>Relative Humidity of Air (%)</li>\n<li>Maximum Relative Air Humidity (%)</li>\n<li>Minimum Relative Air Humidity (%) </li>\n<li>Instant Dew Point (Celsius degrees) </li>\n<li>Maximum Dew Point (Celsius degrees)  </li>\n<li>Minimum Dew Point Temperature (Celsius degrees) </li>\n<li>Instant Air Atmospheric Pressure (millibars)</li>\n<li>Maximum Air Atmospheric Pressure (millibars)</li>\n<li>Minimum Air Atmospheric Pressure (millibars) </li>\n<li>Instant Wind Speed (meters per second)  </li>\n<li> Wind Direction (radius degrees)</li>\n<li>Wind Gust Intensity (meters per second)  </li>\n<li>Solar radiation   </li>\n<li>Precipitation (millimeters)   </li>\n</strong></ul><strong>\n\n<p>\nThe data was taken hourly from different weather stations in South America. Therefore information regarding the time, date and location of the station is also available.  </p>\n</ul>",
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      "name": "Description",
      "content": "Use the available climate variables, measured from different weather stations, to predict the Instant Air Temperature at a given time.\n\nThe data was taken hourly from different weather stations in South America. Therefore information regarding the time, date and location of the station is also available.\n\nThe data is incomplete, some of it was omitted or not recorded, meaning teams will have make use of data-cleaning methods and procedures available through use of the R programming language.\n\nYou can submit up to 2 predictions a day. The public score is the RMSE of 30% of the test data. An example for a submission is presented in the data section.\n\nAs you progress through the course, you will learn more methods for data cleaning, exploratory analysis and model building - try coming back to the data from week to week and use what you have learned! Your team could win first place!",
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    {
      "name": "rules",
      "content": "This is a page where you can include rules that participants must accept before joining. You may wish to include rules like:\n\n -  Only 2 submissions can be uploaded daily.\n - Top 3 teams will present their work during the last class of the semester.\n- Try to have fun!",
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