The next step in the process is to sketch out the layout of the infographic (with paper and pen works well). We could have used different variables in this census profile (there are many) or other datasets, such as real estate prices and availability, for example, to tell our story in this infographic. Note: This is a simplified example of finding a story in the data. We'll also include some context at the beginning of the infographic to set the stage for the story, so including information on population and location within Canada. So let's go with using the data on the number of people living in single-detached houses vs condos, as well as the median value of dwellings in our infographic as some ways to compare the cities' housing landscape. Note: Normally, I would make comparisons of categories within the same question, but I feel pretty safe in my assumption that single-detached houses are not condos, so there's no overlap, and I can make these comparisons. These two data files will also be used in our infographic. Based on a quick visual scan, I can see that Toronto has a pretty even mix of housing types, but for Vancouver there’s a higher percentage of people living in condos vs. I have separated some of the relevant housing-related census data into two new excel files called TorontoHousingMix.xls and VancouverHousingMix.xls and calculated the percentages. Not what is available, but where people live. Going back to the condo/non-condo question information, it might also be useful to describe the housing mix in both cities - condos vs houses (i.e., single-detached houses).
There's a big story there - median values for Vancouver are much higher when compared to Toronto! So that will be the climax of our story. That will be useful.įurther in the file (around row 1619), there is more data on household characteristics, such as home type (condo vs non-condo).Īnd median value of a home, as estimated by the resident. You can see that 269,675 people in Toronto and 41,330 people in Vancouver live in single-detached houses. You can see, for example, that starting at row 43 there’s data on what type of housing people live in, with different categories such as single-detached house or apartment. Most questions start with a “total” that describes the question and then the indented information are the subcategories that people fall under. You can see that these answers are categorized by general topic. This is census profile data from the latest census (2016) for the cities of Toronto and Vancouver.įrom this file, you can see that there is information about how many people fall into many different demographic categories, based on how they answered particular questions in the census. In particular, you should see 3 Excel files – let’s check out CensusProfile.csv first. The result should be a number of files that will be referred to throughout this tutorial. You will need to unzip/extract the file using a tool like 7-zip. - normally by right clicking on the file and selecting extract or unzip from the menu. Having logged in, you should end up in your account dashboard screen (yours is likely to be fairly empty).īefore we start working with Piktochart, we need to gather our data, come up with our story, and design our infographic. When you first set up an account, you may be asked a few questions about yourself. This link should take you to the log in screen where you can then log in. Once you receive that email, just click on the Confirm email button. Piktochart should send you a confirmation email. If creating an account, fill in your name, email and choose a password. Note that at this point you can choose to create an account or sign in through an existing Gmail/ Facebook account. To begin, go to the Piktochart website: ( Click on the sign up button on the top right.