Day 2: Lines

For today’s prompt I decided to map a new favorite dataset. Back in April, the City of Raleigh’s bike share program, Citrix Cycle, launched. I haven’t used as I prefer riding my own bike, but by all accounts it’s a great service. My interest is in the data collected when the bikes are in use. I stumbled upon the live feed for Citrix Cycle rides on ArcGIS Online. There’s a lot one can do with this dataset and I suspect I’ll use it for other map in this challenge. For Day 2, however, I’ve just let the geometries speak for themselves.

I did some preprocessing with Python, the ArcGIS Python API, and geopandas to access and clean up the data.

from datetime import datetime
import geopandas as gpd
from arcgis.gis import GIS
gis = GIS()

# Accessed the data using the ArcGIS Python API
cc_item = gis.content.get('4d4930c1981f41fc864e26616193e64f')
cc_flayer = cc_item.layers[0]
cc_fset = cc_flayer.query()

# I prefer geopandas for working with data in Python so I did this silly step of converting the ArcGIS feature set into a GeoDataFrame.
cc_gdf = gpd.read_file(cc_fset.to_geojson)

# I am not good at working with time, so I converted the unlockedAt timestamps into the a column containing just the name of the month when each ride took place
cc_gdf["Month"] = cc_gdf.apply(lambda x: datetime.fromtimestamp(int(str(x["unlockedAt"])[:-3])).strftime('%B'), axis = 1)

# Reduced the number of fields to some that might be interesting to have around and export to GeoJSON 
cc_reduced_gdf = cc_gdf[['OBJECTID', 'startStationName', 'endStationName', 'unlockedAt', 'lockedAt', 'duration', 'Month', 'geometry']]
cc_reduced_gdf.to_file('cc_30DayMapChallenge.geojson', driver = 'GeoJSON')

I loaded the data into QGIS where I made 6 copies of the routes layer, each filtered by month and layed out in a sort of nod to small multiples. I love QGIS’s feature and layer rendering modes. By adding some opacity to each feature and applying a Screen blending mode to each feature, the areas of heavy cycle traffic emerge in a bright white.

On to Day 3!