Add coordinates for missing lat/lon

### Overview
We need to add lat/long coordinates to the data set we get from the city so that a higher % of parking violations and summary statistics display on the map.

### Details
Around 15% of data points do not have coordinates. Analyze these missing data points and identify what % we could reliably tag.

### Action items
- [x] Download the data and remove the data with lat/long to make the new data set
- [ ] Analyze dataset and missing coordinate records
- [ ] Geocode using address information in batches to avoid paid tier
- [ ] Save code and analysis as Jupyter notebook in Notebooks folder of citation analysis branch
- [ ] Save dataset to Google Drive (add Drive link in Resource section below)
- [ ] Map the data
- [ ] Identify which addresses did not get properly geocoded
- [ ] Discuss results with the team

### Resources/Instructions

- Citation analysis branch for getting access to Lucky Parking's cleaned data README: https://github.com/hackforla/lucky-parking/tree/citation-analysis
- Notebooks folder: https://github.com/hackforla/lucky-parking/tree/citation-analysis/notebooks
- Google Drive Folder for Lat / Long analysis: https://drive.google.com/drive/u/0/folders/1IgPOBy86s3kcDJ5cG3afqoTz4BtRwjdX
- Possible package to use: https://geocoder.readthedocs.io/
- Tutorial: https://towardsdatascience.com/geocode-with-python-161ec1e62b89