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Community Data Science Course (Spring 2017)/Day 7 Notes
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'''A bit of vocabulary: types of data''' * Categorical: data that takes a qualitative value. For instance, city, weather condition (icy, rainy, sunny). * Ordinal: data that can be used to order things. Generally, the important thing about ordinal data is that 'scale' isn't important. * Cardinal: data that counts something. Examples: age, temperature, GDP. ''Do this:'' Find two examples of each kind of variable in the SDOT crash data. '''Plotting:''' # Pick your x-axis variable. # Pick your plot type. ## 'cardinal' and 'cardinal': Scatter ## 'categorical' and 'cardinal': Bar or histogram. ## 'categorical' and 'categorical' and 'cardinal': We'll see some examples of this in python, but a pivot table with color is often useful. ## 'ordinal' and 'cardinal': Bar, line chart, or histogram. # Pick your y-axis variable. ''Do this:'' Make the following plots (for each figure out which kind) # Count accidents by road conditions # Build a plot of number of people involved and injury count. # Build a plot of accidents by date. # Use a stacked plot to see if speeding is more associated with some weather conditions. '''General Advice''' * Don't overthink it! Excel has dozens of fancy plots, and there is a good reason to use all them. However, don't introduce a more complicated plot where a simple one will do.
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