The development of the area around Canada Line is explored by looking at the number of business licences issued at different areas along the track over time.
R 3.2.2
(with the checkpoint library)QGIS 2.12.0-Lyon
(with the NNJoin and Table Manager plugins installed)Python 2.7
(with the virtualenv package)
- Google Maps API secret key in the environmental variable
GOOGLE_MAPS_SECRET
Install the checkpoint
package and run src/requires.R
.
# start in the src/ directory
virtualenv .proj
. .proj/bin/activate
pip install -r requirements.txt
- Open as an RStudio project and run
requires.R
(this will take a while) - Run
s1_business_data_download.R
- Run
s2_transit_selection.R
- Run
# start in the data directory
touch geocoded_02_08_14.txt
./geocode.py addresses.txt geocoded_02_08_14.txt
(with the virtualenv
activated). The output file geocoded_02_08_14.txt
is imported in the next step.
5. Run s3_import_geocoded.R
6. Perform instructions from the Prepare the Spatial data section
7. Run s4_combine_geocoded_with_rest_of_data.R
Run s5_graphics.Rmd
for the report graphics, s5_table.R
for the table
statistics and s5_graphics.R
for the presentation graphics
Additional datasets required:
- Local Area Boundary
- Rapid Transit Lines
- Rapid Transit Stations
- Import the Rapid Transit Line
RTL
file into QGIS. - Select Canada Line from the
RTL
layer - Reproject the dataset into UTM Z10N (EPSG 32610) using the selected feature and save it disk (I'll call it
CanLine
)
- Import the Rapid Transit Stations
RTS
file into QGIS. - Select all Canada Line stations from the
RTS
layer - Reproject the dataset into UTM Z10N (EPSG 32610) using the selected feature and save it disk (I'll call it
CanStations
)
- Import the Local Area Boundary
RTS
file into QGIS. - Reproject the dataset into UTM Z10N (EPSG 32610) using the selected feature and save it disk (I'll call it
LocalArea
)
- Import the
data/stage3.csv
file into QGIS (should have been produced after runnings3_import_geocoded.R
) - Reproject the dataset into UTM Z10N (EPSG 32610) using the selected feature and save it disk (I'll call it
Stage3
)
- Create a 1km buffer around Canada Line using Geoprocessing Tools
- Save it and call it
CanLineBuffer
Select business licences from Stage3
that interesect CanLineBuffer
and call it Stage3InBuffer
- Use NNJoin (input layer:
Stage3InBuffer
and join layerCanLine
). Use Table Manager to delete all columns beginning with "join_", rename the "distance" column to "d_to_track" and call the outputPart2Stage3InBuffer
- Use NNJoin (input layer:
Part2Stage3InBuffer
and join layerCanStaions
). Use Table Manager to delete all columns beginning with "join_", rename the "distance" column to "d_to_stat" and call the outputPart3Stage3InBuffer
- Export
Part3Stage3InBuffer
as a csv file (call itdist.csv
and place it in thedata
directory for use in step 7 of the reproduce the graphs section)
- Import
data/complete.txt
into QGIS and reproject it UTM Z10N (call itBusinessLicences
) - Add styles to
BusinessLicences
,CanLineBuffer
,CanStations
andCanLine
to match the final maps shown in thegraphics
directory. - Use QGIS print composer to add the scale bars and projection information export the results
filtering the
BusinessLicenses
layer to the year 2002 and 2014 respectively.