Update readme and requirements.txt

Author: ray310

README.md

@@ -1,8 +1,10 @@
 # Analyzing New York City Motor Vehicle Collisions
- 
+#### [https://ray310.github.io/NYC-Vehicle-Collisions/](https://ray310.github.io/NYC-Vehicle-Collisions/)
+
 In this project, we analyze motor vehicle collisions in New York City (NYC) to:
 - Understand the magnitude of the problem they represent
 - Determine when and where collisions occur
+- Evaluate when collisions are elevated relative to traffic levels
 - Make it easier to see where serious collisions (collisions with deaths and injuries) are occurring
 - Suggest causes and interventions to investigate
 - Highlight problematic locations and areas that may not be obvious
@@ -12,16 +14,43 @@ In this project, we analyze motor vehicle collisions in New York City (NYC) to:
 [https://ray310.github.io/NYC-Vehicle-Collisions/](https://ray310.github.io/NYC-Vehicle-Collisions/)
 <br><br>
 
+### Supplemental Analysis
+__Vehicle Activity Index__
+
+- The vehicle activity index is constructed to identify when collisions are
+ elevated relative to the level of driving.
+- The index is based on traffic volumes in the Metropolitan
+ Transit Authority (MTA) Bridge and Tunnel dataset.
+- Yearly, monthly, weekly, and daily traffic patterns in the MTA dataset were profiled
+- Relationships between toll crossings was evaluated using cross-correlation and
+ by examining the weekly traffic pattern of select crossings.
+ patterns was performed
+- Gaps were identified in the MTA dataset and imputed using XGBoost regression.
+- Please see the following notebooks:
+  - [1b-profiling-mta-traffic-index.ipynb](https://nbviewer.org/github/ray310/NYC-Vehicle-Collisions/blob/main/1b-profiling-mta-traffic-index.ipynb)
+  - [2a-preparing-mta-data-xgboost.ipynb](https://nbviewer.org/github/ray310/NYC-Vehicle-Collisions/blob/main/2a-preparing-mta-data-xgboost.ipynb)
+
+__Cycling Activity Index__
+
+- The cycling activity index is constructed to identify when collisions with cyclists
+ are elevated relative to the level of cycling.
+- The index is based on cycling volumes at several bicycle counters throughout NYC in
+ the NYC Bicycle Counts dataset
+- The 30+ bicycle counters were reviewed for completeness of data
+- The index was constructed using a composite of counters to provide a consistent index
+ going back to 2015
+- Yearly, monthly, weekly, and daily traffic patterns in the cycling index were profiled
+- Please see the following notebooks:
+  - [1c-profiling-nyc-bike-counter-data.ipynb](https://nbviewer.org/github/ray310/NYC-Vehicle-Collisions/blob/main/1c-profiling-nyc-bike-counter-data.ipynb)
+
 ### To Directly View Notebooks with Full Content
 Project notebooks with maps can best be viewed using Jupyter's nbviewer.  
-[View project notebooks with nbviewer](https://nbviewer.org/github/ray310/NYC-Vehicle-Collisions/tree/main/) 
+[View project notebooks with nbviewer](https://nbviewer.org/github/ray310/NYC-Vehicle-Collisions/tree/main/)
 
 _Note that some notebooks may be slow to display or may not display well on mobile devices_
 <br><br>
 
 ### Data Sources
-Collision data and NYPD precinct shapefiles were obtained from NYC OpenData
-
 NYC Collisions <br>
 https://data.cityofnewyork.us/Public-Safety/Motor-Vehicle-Collisions-Crashes/h9gi-nx95
 
@@ -31,18 +60,24 @@ https://data.cityofnewyork.us/Public-Safety/Police-Precincts/78dh-3ptz
 MTA Bridge and Tunnel Toll Data <br>
 https://data.ny.gov/Transportation/Hourly-Traffic-on-Metropolitan-Transportation-Auth/qzve-kjga/about_data
 
+NYC Bicycle Counts <br>
+https://data.cityofnewyork.us/Transportation/Bicycle-Counts/uczf-rk3c/about_data
+
+NYC Bicycle Counters <br>
+https://data.cityofnewyork.us/Transportation/Bicycle-Counters/smn3-rzf9/about_data
+
 NYC City Council District Shapefiles <br>
 https://data.cityofnewyork.us/City-Government/City-Council-Districts/yusd-j4xi
 <br><br>
 
 ### Reproducing Processed Data and Analysis
 1) Clone repo
 2) Download and save data to local directory, e.g. `/data/raw`
-3) Create and activate project virtual environment 
+3) Create and activate project virtual environment
    - Python 3.12.3 is used
    - Virtual environment can be created from either
    `conda_environment.yaml` or `requirements.txt`
 4) Update data input and output parameters in `process_raw_data.py` as appropriate
 5) Run `process_raw_data.py` (this script may take a while)
 6) To obtain City Council point of contact information, run `src/scrape_city_council.py` with required command line arguments
-7) Run notebooks
+7) Run notebooks

requirements.txt

@@ -23,3 +23,4 @@ scipy==1.13.1
 seaborn==0.13.2
 shapely==2.0.1
 statsmodels==0.14.2
+xgboost==2.0.3