Location data visualization on Map using Python

python
geopandas
map
Author

Pankaj Chejara

Published

September 23, 2023

First time plotting coordintes on Map using Python

This tutorial will show you how to work with geospatial data using Python with library geoPandas. For this exercise, I have used Boston Bike Sharing dataset which is available here. I have recently started learning and using Map library with Python and this tutorial is the reflection of things I have learned so far. I hope it will be helpful for those learning the same first time.

Loading the dataset

We start first loading our dataset. There are two CSV files, hubway_trips.csv and hubway_station.csv. The first data file contains information all bike trips (e.g., bike number, start and end time of the trip, start and end station of the trip, user information, etc). The second data file hubway_station.csv contains information about the bike stations (e.g., longitude, lattitude, municipality).

import pandas as pd

# Bike trip data
trips = pd.read_csv('hubway_trips.csv')
trips.head()
seq_id hubway_id status duration start_date strt_statn end_date end_statn bike_nr subsc_type zip_code birth_date gender
0 1 8 Closed 9 7/28/2011 10:12:00 23.0 7/28/2011 10:12:00 23.0 B00468 Registered '97217 1976.0 Male
1 2 9 Closed 220 7/28/2011 10:21:00 23.0 7/28/2011 10:25:00 23.0 B00554 Registered '02215 1966.0 Male
2 3 10 Closed 56 7/28/2011 10:33:00 23.0 7/28/2011 10:34:00 23.0 B00456 Registered '02108 1943.0 Male
3 4 11 Closed 64 7/28/2011 10:35:00 23.0 7/28/2011 10:36:00 23.0 B00554 Registered '02116 1981.0 Female
4 5 12 Closed 12 7/28/2011 10:37:00 23.0 7/28/2011 10:37:00 23.0 B00554 Registered '97214 1983.0 Female 
# Bike station data [seperator in this file is ';']
stations = pd.read_csv('hubway_stations.csv',sep=';')
stations.head()
id terminal station municipal lat lng status
0 3 B32006 Colleges of the Fenway Boston 42.340021 -71.100812 Existing
1 4 C32000 Tremont St. at Berkeley St. Boston 42.345392 -71.069616 Existing
2 5 B32012 Northeastern U / North Parking Lot Boston 42.341814 -71.090179 Existing
3 6 D32000 Cambridge St. at Joy St. Boston 42.361285 -71.065140 Existing
4 7 A32000 Fan Pier Boston 42.353412 -71.044624 Existing

Joining the data

We will first join the data to have a single file with lattitude and longitude information for start station of bike trip. For that we will perform join operation on start_statn in trips and id in stations.

# we exclude status column because it is present in both data file and will cause an error on join operation.
stations_non_status = stations[['id','lat','lng','station','municipal']]

# combined data with start station geo spatial information
trips_stations = trips.join(stations_non_status.set_index('id'),on='strt_statn')

trips_stations = trips_stations.loc[trips_stations['municipal'] == 'Boston',:]
trips_stations.head()
seq_id hubway_id status duration start_date strt_statn end_date end_statn bike_nr subsc_type zip_code birth_date gender lat lng station municipal geometry
0 1 8 Closed 9 7/28/2011 10:12:00 23.0 7/28/2011 10:12:00 23.0 B00468 Registered '97217 1976.0 Male 42.359677 -71.059364 Mayor Thomas M. Menino - Government Center Boston POINT (-71.05936 42.35968)
1 2 9 Closed 220 7/28/2011 10:21:00 23.0 7/28/2011 10:25:00 23.0 B00554 Registered '02215 1966.0 Male 42.359677 -71.059364 Mayor Thomas M. Menino - Government Center Boston POINT (-71.05936 42.35968)
2 3 10 Closed 56 7/28/2011 10:33:00 23.0 7/28/2011 10:34:00 23.0 B00456 Registered '02108 1943.0 Male 42.359677 -71.059364 Mayor Thomas M. Menino - Government Center Boston POINT (-71.05936 42.35968)
3 4 11 Closed 64 7/28/2011 10:35:00 23.0 7/28/2011 10:36:00 23.0 B00554 Registered '02116 1981.0 Female 42.359677 -71.059364 Mayor Thomas M. Menino - Government Center Boston POINT (-71.05936 42.35968)
4 5 12 Closed 12 7/28/2011 10:37:00 23.0 7/28/2011 10:37:00 23.0 B00554 Registered '97214 1983.0 Female 42.359677 -71.059364 Mayor Thomas M. Menino - Government Center Boston POINT (-71.05936 42.35968)

Working with GeoPandas library

Now we will move towards setting up our dataset to have geospatial data required by GeoPandas library. GeoPandas is a python library with extends capability of Pandas by including GeoSpatial data processing and plotting functionality.

First install GeoPandas library if you don’t have it on your computer.

# Installing Geopandas
#! pip3 install geopandas
import geopandas as gpd
from shapely import Point, Polygon
geo_column = [Point(lng,lat) for lng, lat in zip(trips_stations['lng'],trips_stations['lat'])]

What we did in above code was created a list with a Point object for each record in our joined data file. This Point object will provide geospatial data information to GeoPandas to work with.

Now we will create our GeoPandas dataframe which will have our data with geospatial information.

crs={'init':'epsg:4326'}
gdf = gpd.GeoDataFrame(trips_stations,crs=crs,geometry=geo_column)

Now, we created a geopandas dataframe which have all our records from trips_stations dataframe and all those records are associated with a geometric point (e.g., geospatial data).

Each geopandas dataframe requires one geometry column which has information of geospatial data.

Plot Geospatial data

gdf.plot('strt_statn')

The above plot does not show Boston’s map. In order to do that we would need Map files for Boston.

boston = gpd.read_file('./City_of_Boston_Boundary/')
boston = boston.to_crs({'init': 'epsg:4326'})
boston.plot()
/Users/htk/opt/anaconda3/lib/python3.9/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6
  in_crs_string = _prepare_from_proj_string(in_crs_string)

Plotting geospatial data over Boston’s map

Now we will plot the data of start station of bike trip on the map of Boston.

import matplotlib.pyplot as plt
fig, ax = plt.subplots(figsize=(10,8))
boston.plot(ax=ax)
gdf.plot(ax=ax,color='red',marker='+',alpha=.5)

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