Minor improvements

README.md

@@ -1,7 +1,7 @@
 gtfs-realtime-performance
 ==============================
 
-This library makes it easy to calculate transity performance statistics (e.g., segment speeds, bus bunching) using archival GTFS-realtime data. It is intended to be used in conjuction with the GTFS-realtime archiving tool being developed in [gtfs-realtime-capsule](https://github.com/tsdataclinic/gtfs-realtime-capsule). 
+This library makes it easy to calculate transit performance statistics (e.g., segment speeds, bus bunching) using archival GTFS-realtime data. It is intended to be used in conjunction with the GTFS-realtime archiving tool being developed in [gtfs-realtime-capsule](https://github.com/tsdataclinic/gtfs-realtime-capsule). 
 
 ### Project Organization
 
@@ -14,6 +14,6 @@ We have also included a number of utility functions to simplify the process of w
 
 ### Notebooks
 
-This repository contains a number of notebooks that contain figures, tables, and maps created using our speed estimates. Some of these are old and messy - I'd reccommend looking at `notebooks/basic_plots_and_mta.ipynb` for comparisons of our speeds to speeds published by the MTA and at `notebooks/holidays.ipynb` to see bus speed comparisons on holidays.
+This repository contains a number of notebooks that contain figures, tables, and maps created using our speed estimates. Some of these are old and messy - I'd recommend looking at `notebooks/basic_plots_and_mta.ipynb` for comparisons of our speeds to speeds published by the MTA and at `notebooks/holidays.ipynb` to see bus speed comparisons on holidays.
 
 <p><small>Project based on the <a target="_blank" href="https://drivendata.github.io/cookiecutter-data-science/">cookiecutter data science project template</a>. #cookiecutterdatascience</small></p>

requirements.txt

@@ -8,3 +8,15 @@ coverage
 awscli
 flake8
 python-dotenv>=0.5.1
+pandas
+geopandas
+shapely
+requests
+numpy
+tqdm
+contextily
+matplotlib
+plotnine
+geopy
+xyzservices
+statsmodels

src/gtfs_segments.py

@@ -1,15 +1,10 @@
-import os 
 import pandas as pd
 import os
 os.chdir("/home/canyon/Bus-Weather-Impacts")
-import numpy as np
 import geopandas as gpd
-import numpy as np
-from shapely.ops import nearest_points
 pd.options.mode.chained_assignment = None
 from shapely.geometry import Point, LineString
 import src.api as api
-from shapely.ops import linemerge
 from shapely.ops import substring
 
 class GTFS_shape_processor:

src/process_batch.py

@@ -2,9 +2,6 @@
 os.chdir("/home/canyon/Bus-Weather-Impacts")
 from src.utils import *
 import pandas as pd
-import numpy as np
-import geopandas as gpd
-import numpy as np
 pd.options.mode.chained_assignment = None
 from src.api import parse_zipped_gtfs
 from src.gtfs_segments import GTFS_shape_processor

src/speeds.py

@@ -4,7 +4,6 @@
 from shapely.ops import linemerge
 import bisect
 from tqdm import tqdm
-import logging
 
 class BusSpeedCalculator:
     """

src/utils.py

@@ -1,13 +1,8 @@
 import requests
-import gzip
 import pandas as pd
 import tempfile
-import shutil
 import os
-import geopandas as gpd
-import numpy as np
 import tarfile
-import traceback
 
 def read_parquet_from_tar_gz(url):
     """