Movies and Television shows filmed in Toronto but based elsewhere…

by Alexander Pardy
Geovis Class Project @RyersonGeo, SA8905, Fall 2017

Data and Data Cleaning:

To obtain my data I used and selected Toronto  the website displays a map that shows locations in the Greater Toronto Area  where movies and television shows were filmed. The point locations are overlaid on top of Google Maps imagery.

If you use the inspect element tool in internet explorer, you can find a single line of JavaScript code within the map section of the webpage that contains the latitude and longitude of every single point.

The data is in a similar format to python code. The entire line of JavaScript code was inputted into a Python script.  The python script writes the data into a CSV file that can then easily be opened in Microsoft Excel. Once the file was opened in Excel, Google was used to search for the setting of each and every single movie or television show, using the results of various different websites such as fan websites, IMDB, or Wikipedia. Some locations take place in fictional towns and cities, in this case locations were approximated using best judgement to find a similar location to the setting. All the information was than saved into a CSV file. Python was then used to delete out any duplicates in the CSV file and was used to give a count of each unique location value. This gives the total number of movies and television shows filmed at each different geographical location. The file was than saved out of python back into a CSV file. The latitude and longitude coordinates for each location was than obtained from Google and inputted into the CSV file.  An example is shown below.

Geospatial Work:

The CSV file was inputted into QGIS as a delimited text layer with the coordinate system WGS 84. The points were than symbolized using a graduated class method based on a classified count of the number of movies or television shows filmed in Toronto. A world country administrative shape file was obtained from the Database of Global Administrative Areas (GADM). There was a slight issue with this shapefile,  the shapefile had too much data and every little island on the planet was represented in this shapefile. Since we are working at a global scale the shapefile contained too much detail for the scope of this project.

Using WGS 84 the coordinate system positions the middle of the map at the prime meridian and the equator. Since a majority of the films and television shows are based in North America,  a custom world projection was created. This was accomplished in QGIS by going into Settings, Custom CRS, and selecting World Robinson projection. The parameters of this projection was then changed to change the longitude instead of being the prime meridian at 0 degrees, it was changed to -75 degrees to better center North America in the middle of the map. An issue came up after completing this is that a shapefile cannot be wrapped around a projection in QGIS.

After researching how to fix this, it was found that it can be accomplished by deleting out the area where the wrap around occurs. This can be accomplished by deleting the endpoints of where the occurrence happens. This is done by creating a text file that says:

This text box defines the corners of a polygon we wish to create in QGIS.  A layer  can now be created from the delimited text file, using custom delimiters set to semi colon and well-known text. It creates a polygon on our map, which is a very small polygon that looks like a line. Then by going into Vector, Geoprocessing Tools, Difference and selecting the input layer as the countries layer and the difference layer as the polygon that was created. Once done it gives a new country layer with a very thin part of the map deleted out (this is where the wrap around occurred). Now the map wraps around fine and is not stretched out. There is still a slight problem in Antarctica so it was selected and taken out of the map.


The shapefile background was made grey with white hairlines to separate the countries. The count and size of the locations was kept the same. The locations were made 60% transparent. Since there was not a lot of  different cities the  symbols were classified to be in 62 classes, therefore each time the number increased, the size of the point would increase.  The map is now complete. A second map was added in the print composer section to show a zoomed in section of North America. Labels and lines were then added into the map using Illustrator.

Story Map:

I felt that after the map was made a visualization should also be created to help covey the map that was created by being able to tell a story of the different settings of films and television shows that were filmed in Toronto.  I created a ESRI story map that can be found Here .

The Story Map shows 45 points on a world map, these are all based on the setting of television shows and movies that were filmed in the City of Toronto. The points on the map are colour coded. Red point locations had 4-63 movie and television shows set around the points. Blue point locations had 2-3 movie and television shows set around the points. Green point locations had 1 movie or television show set around the point. When you click on a point it brings you to a closer view of the city the point is located in. It also brings up a description that tells you the name of the place you are viewing and the number of movies and television shows whose settings takes place in that location. You also have the option to play a selected movie or television show trailer from YouTube in the story map to give you an idea of what was filmed in Toronto but is conveyed by the media industry to be somewhere else.

Map Animation of Toronto’s Watermain Breaks (2015)

Audrey Weidenfelder
Geovis Project Assignment @RyersonGeo, SA8905, Fall 2016

For my geo-viz project, I wanted to create a map animation.  I decided to use CARTO, a web mapping application.


CARTO is an open source web application software built on PostGIS and PostgreSQL open source spatial databases.  Users can manage data, run spatial analysis and design custom maps.  Within CARTO, there is an interface where SQL can be used to manipulate data, and a CartoCSS editor (a cartography language) to symbolize data.

CARTO has a tool called Torque that allows you to ‘bring your data to life’.  It’s good for mapping large data sets that have a time and/or date reference.  CARTO is well documented, and they offer guides and tutorials to assist users in their web mapping projects.  You can sign up for a free account here.  The free account is limited to 250Mb of storage after which charges apply.

The Process:  Connect to data, create new data set, add new column, symbolize

To create a map animation, simply connect to your data set either by dragging and dropping or browsing to your file.  If you don’t have data, you can search CARTO’s data library.  I had a file that I downloaded from the Toronto Open Data Catalogue.  I wanted to test CARTO’s claim that it can ‘bring large data sets to life’.  The file contained over 35,000 records of the city’s watermain breaks from 1990 to 2015.  I brought it into CARTO through the file browser, and in about 40 seconds all 35,000 point locations appeared in the map viewer.  From here, I explored the data, experimented with all the different visualization tools, and practised with CartoCSS to symbolize the data.

I decided to animate the 1,353 watermain breaks for 2015.  I had to filter the data set using a SQL statement to create a new data set containing only the 2015 breaks.  It’s easy to do using SQL.  You select from your table and column:

Select * from Breaks where Break_Year = 2015

CARTO asks if you wish to create a new data set from your selection – select ‘Yes’.  A new data set is created.  It will transfer your selected data into a new table along with the attributes associated with the selection.  You can keep the default table name or change the name of your table.  I re-named the table to ‘Watermain Breaks 2015’

From here, I wanted to organize the data by the seasons:  Spring, Summer, Winter and Fall.  This required creating a new column, selecting data according to the months and days of the season, entering the selected data into the column, and reassigning it a new name.

In data view, select ‘Add Column’ from the table designer, give it a name and a data type.  In this case I called it ‘Season’ and selected ‘String’ as the data type for text.  The next step was to update the column ‘Season’ based on values from the ‘Break_Date’ column that contained the dates of all breaks.  This was accomplished through the SQL Query editor, as so:

Update Watermain_Breaks _2015 set Season = ‘Spring’
where Break_Date >= ‘2015-03-21’ and Break_Date <= ‘2015-06-20’

The value of ‘Spring’ replaced the selected date range in the new column.  This was repeated for summer, fall and winter, substituting the appropriate date range for each season.

I then switched to the Category Wizard to symbolize this map layer.  Here you select the column you wish to symbolize.  I wasn’t pleased with the CARTO default symbolization, and there are were few options to choose from, so I used the CartoCSS editor to modify:

/** category visualization */
#breaks {
Marker-fill-opacity: 0.9;
Marker-placement: point;
Marker-type: ellipse;
Marker-width: 8;
Marker-allow-overlap: true;

#breaks[season=”Fall”] {
Marker-fill: #FF9900;
Marker-line-color: #FF9900

#breaks[season=”Spring”] {
Marker-fill: #229A00;
Marker-line-color: #229A00;

And so on …

To make the map layer interactive, I used the Infowindow designer in map view.  Here you can create pop-up windows based on a column in the table.  Options are available for a hover window or a clickable window.

Adding Layers

To add more interest to the map, I added the City of Toronto Neighbourhood boundaries so that the number of breaks per neighbourhood could be viewed.  I downloaded the shapefile from Toronto Open Data, connected the data set to my map and added it as a second layer.  I added info pop-ups, and changed the default symbolization with CartoCSS editor:

/** simple visualization */  #neighbourhoods_wgs84{
Polygon-fill: #FF6600;
Polygon-opacity: 0;
Line-color: #000000;
Line-width: 0.5;
Line-opacity: 1;


CARTO only allows animation on one map layer, and it does not permit info windows.  You also cannot copy a layer.  As such, I added a new layer by connecting to the watermain breaks data table, and then used the Torque Cat Wizard to animate the layer.

Animation is based on the column that contains either a date or time.  I selected the Break_Date column, and used CartoCSS editor to set the number of frames, duration of the animation, data aggregation to cumulative so that the points remained on the map, and then symbolized the data points to match the original watermain breaks layer.  A legend was then added to this layer.

CARTO has the option to add elements such as title, text boxes and images.  I added a title and a text box containing some facts about the city’s watermain breaks and pipe distribution.

The map animation can be viewed here .  Zoom in, pan around, find your neighbourhood, move the date slider, and select from the visible layers.

Note:  CARTO does not function well in Microsoft Edge