DataHero recently added new sample datasets to make learning the ropes of DataHero easier and faster. Now, when you sign up as a new user, you can directly import datasets from Quandl on topics ranging from NFL stats to energy prices. This blog will demonstrate the basics of DataHero’s analytical features using one of Quandl’s sample datasets.
In this post you’ll learn how to:
The dataset in this post includes real estate prices from various US metropolises by year, allowing you to compare prices by state or home size over time.
To analyze a sample dataset, select Quandl in the datasource navigation menu on the left-hand menu and click Import Data. Choose the Real Estate dataset and DataHero will import it from Quandl, automatically categorizing the different data types (like date and currency, for example).
Many questions you have about the dataset are already answered for you in the suggested charts. DataHero creates suggested charts based on the patterns in the data, as you see pictured below. Click one of the suggested charts to export as is or adapt it to your needs.
Each time you add an attribute to the chart canvas, DataHero will show you the best way to visualize that data. For example, the column chart below was created by dragging Date and Number of Homes for Sale onto the canvas. This is a chart for number of homes for sale in all US states by year.
When you drag on an attribute, you will automatically see the sum of that attribute, but you can adjust this easily by going to the In Your Chart Tab and get the minimum, maximum or average values or more from the drop down menu.
Create a filter by simply dragging on the attribute you’d like filtered onto the bottom portion of the chart canvas into the “Create a Filter” drop zone . For example, if you’d like to see the number of homes for sale in California, drag State into the filter drop zone and select California. You’ll then have a graph of number of homes for sale by year in only California, instead of all states.
Adjust time period in a couple of clicks, just go to the “In Your Chart” tab in the navigational menu on the left, and click the date grouping dropdown menu. Change the time period grouping based on your needs, and even see your data using groupings like month of year or day of week to uncover trends. In the graph below we can see that historically October is the month with the highest number of homes for sale.
DataHero creates a chart automatically based on your data types. However, if you want to change the chart type to an area graph for example, just click the Type button in the top left corner.
DataHero’s analysis features allow you to answer questions like “how have the number of homes for sale changed year over year in various states?” The small buttons in the top left and right corners of the chart canvas can be used to create cumulative charts, comparison charts and percentage charts.
Create a similar graph to the one above. Drag Date, Number of Homes For Sale and State onto the chart canvas. In the left rail, select only AZ, CA and CO to see how these states compare to one another in homes for sale. You’ll see the graph depicted below.
Click the cumulative graph button in the top right of the chart canvas see each state’s total homes for sale each year dating back to 2008.
A comparison chart shows you the change in number of homes for sale. As you can see, beginning in 2011, each state saw fewer homes for sale each year. California sees the largest decrease in homes for sale.
Rate of Change (Percentage and Comparison Graphs) allow you to see how the number homes for sale has changed year over year as a percentage. For example, California’s number of homes for sale decreased by 50% from 2012 to 2013. However, California’s percentage decreases are fairly close to Arizona and Colorado’s percentage decreases in homes for sale.
To create a percentage graph (for more information on when to use which graphs check this post), let’s focus on just California’s number of homes for sale. Then, drag on number of homes for rent and create a stacked column chart. Now click the Percentage button. This will give you an idea of the percentage of homes for sale or for rent by year and allow you to easily spot the market trending toward rental housing.
Now that you have the answers you need, share your findings with your team using DataHero’s export button and you’ll download a PNG file to your computer.
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