I’ve written a number of spatial Python posts over the past few months; I’ll cap off this series with a short one on using PyProj to convert coordinates from one spatial reference system to another. PyProj is Python’s interface to PROJ, a library of coordinate system functions that power projection handling in many open source GIS and spatial packages.

A few months back I geocoded a large batch addresses against the Rhode Island DOT’s geocoding API, which returns coordinates in the local state plane system in feet. I decided to run the non-matching addresses against the Census Bureau’s Batch Geocoder, which returns coordinates in NAD 83 longitude and latitude. You can upload a CSV file of 10k addresses and get nearly instant results (one of my students recently wrote a tutorial on how to use it). So I split the unmatched records from my original CSV, uploaded it to the Census geocoder, and got matches.

Next, I needed to get the results from both processes into the same spatial reference system back in one unified file. The kludgy way to do this would be to plot each file separately in their respective systems in QGIS or ArcGIS, convert the NAD 83 plot to the state plane system, and merge the two vector files together. I used PyProj instead, to convert the NAD 83 coordinate data in the CSV to state plane, added that data to my main address CSV file, and plotted them all at once in the state plane system.

PyProj’s Transformer function does the job. I pass the EPSG / WKID codes for the input and output systems (4269 for NAD 83 and 3438 for NAD 83 RI State Plane ft-US) to Transformer.from_crs, and specify that I’m working with XY coordinates. I open the CSV file that contains the results from the Census Geocoder and read it in as a nested list, with each record as a sublist. Here are some sample records:

[["42221","1720 Victory Hwy, Glendale, RI, ","Match","Exact","1720 VICTORY HWY, GLENDALE, RI, 02826","-71.63746768099998,41.96913042600005","647200684","L","44","007","013002","1083"],
["44882","129 SHORE RD, Riverside, RI, ","No_Match"]]

Then I iterate through the records; in my example any record with less than 3 variables was a non-match, so I skip those. The Census geocoder returns longitude and latitude in the 5th position, in the same field separated with a comma (notice quotes around the coordinates in the example above, indicating that these are part of the same field so the comma is not used as a delimiter). I split this value on the comma, read the longitude as x1 and latitude as y1. The output of the transformer function returns coordinates x2 and y2 in the new system. I tack these new coordinates on to the existing record. Once the loop is finished, I write the result out as a new CSV; I used the name of the input file and tacked “stateplane” plus today’s date to the end. Here are the results for the same records:

[["42221","1720 Victory Hwy, Glendale, RI, ","Match","Exact","1720 VICTORY HWY, GLENDALE, RI, 02826","-71.63746768099998,41.96913042600005","647200684","L","44","007","013002","1083","290699.10687381076","322797.1874965105"],
["44882","129 SHORE RD, Riverside, RI, ","No_Match"]]

That’s it! I took the resulting CSV and tacked it to end of my primary CSV, which contained the successful matches from the RIDOT geocoder, in such a way that matching fields lined up. I can still identify which results came from what geocoder, as a few of the fields are different.

import csv
from datetime import date
from pyproj import Transformer

reproject = Transformer.from_crs(4269,3438,always_xy=True)

records=[]

addfile='GeocodeResults.csv'
with open(addfile,'r') as infile:
    reader = csv.reader(infile)
    for row in reader:
        records.append(row)

for r in records:
    if len(r)>3:
        x1,y1=r[5].split(',')
        x2,y2=reproject.transform(float(x1),float(y1))
        r.extend([str(x2),str(y2)])

today=str(date.today())        

outfile=addfile.split('.')[0]+'_stateplane_'+today+'.csv'
with open(outfile, 'w', newline='') as writefile:
    writer = csv.writer(writefile, quoting=csv.QUOTE_ALL, delimiter=',')
    writer.writerows(records)

print('Done')