GTFS Import
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      Filtering Network Imports by Date

      Filtering by date lets transport planners focus on specific time frames relevant to their analysis or project scope.

      After Selecting the Geographies to Import, you can filter your import by date.

      Network feeds often contain data spanning extensive time periods, sometimes including seasonal variations, special event schedules, or planned future changes. Filtering by date allows transit planners to focus on specific time frames relevant to their analysis or project scope. This can be particularly useful when examining service patterns for a typical week or comparing services across different seasons.

      Options

      1. All: Consider all calendar dates and calendars in the network feed.
      2. Date Range: Filter the feed to include only calendars, calendar dates, and trips active within a selected date range.

      Reconstruct Calendars and Dates

      • No: Includes all dates in the calendars and calendar_dates (after any date range filter is applied).
      • Busiest Week: Identifies the week with the most trips and includes only those dates. The calendars are rewritten to use regular operating days, and calendar_dates are removed.

      The "Busiest Week" option addresses a common challenge in network data analysis. Many feeds use a combination of calendar entries and exception dates, which can make it difficult to identify regular service patterns. By reconstructing the calendar to focus on the busiest week, planners can more easily analyze and visualize the most representative service levels, streamlining the process of understanding complex transit networks.

        When you select "Busiest Week", Podaris analyzes the GTFS data to:

        1. Identify the week with the highest number of scheduled trips.
        2. Extract the service patterns for that week.
        3. Reconstruct the calendar data to represent a typical week of service.
        4. Remove exception dates (calendar_dates) to provide a cleaner, more consistent view of service.

        Some things to consider:

        • Filtering by date range may exclude important seasonal variations or special event services.
        • The "Busiest Week" option provides a snapshot of maximum service levels but may not represent year-round operations.
        • Calendar reconstruction can simplify analysis but might obscure nuances in service patterns, especially for networks with complex scheduling.
        Next step: Network Import Options