This app gives information about vechiles crossing the United States’ Borders with Mexico and Canada. It creates an interactive display that allows users to explore what types of personal and commercial vechiles are crossing US borders and which ports of entry they are crossing at.
The use can toggle the data used by which border(s) is included, vechile type, and date range.

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The data used in this application comes from Kaggle.
This dataset includes: - the method of crossing (truck, train, pedestrian, etc.) - which border it was - the port of entry - latitude and longitude of the crossing - other information on the crossings

This application does not currently use all of the information alvailable in this dataset. Below is a snippet of the processed data used:

            Border       Date                     Measure             Location
1 US-Mexico Border 2019-02-01      Truck Containers Empty        Naco, Arizona
2 US-Mexico Border 2019-02-01 Personal Vehicle Passengers Columbus, New Mexico
3 US-Mexico Border 2019-02-01                 Pedestrians Columbus, New Mexico
4 US-Mexico Border 2019-02-01      Truck Containers Empty      Progreso, Texas
5 US-Mexico Border 2019-02-01                      Trucks       El Paso, Texas
6 US-Mexico Border 2019-02-01 Personal Vehicle Passengers  Andrade, California
     lat      lng
1 31.335 -109.948
2 31.827 -107.639
3 31.827 -107.639
4 26.062  -97.949
5 31.759 -106.486
6 32.739 -114.634

The application contains an interactive leaflet map that shows the loaction of the ports of entry included in the data that the user has selected. When a user clicks on one of the markers, text will come up telling them the name of that port of entry. Below is a sample of that map:

An interactive Plotly bar graph of the count of vechile types that have crossed the border in the given time period:

• Monitoring economic movement and trade across North America
• Track tourists and other pedestian/private crossings
• Report activity at various ports of entry

• Include data points further into the past
• Improve data feed for more up to date information
• Take adavtage of other available fields (i.e. the Value field)