Editing Community Data Science Course (Spring 2023)/Week 7 coding challenges
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# Take a look at the "RecordType" column which describes the kinds of complaints that come in. What are the types of categories? How many are in each category? Show both with numbers and with a simple visualization (a histogram, perhaps?). For each category, print out the "Description" of several examples. What kinds of things are included? | # Take a look at the "RecordType" column which describes the kinds of complaints that come in. What are the types of categories? How many are in each category? Show both with numbers and with a simple visualization (a histogram, perhaps?). For each category, print out the "Description" of several examples. What kinds of things are included? | ||
# Build a new dataset that includes only the "RecordType" | # Build a new dataset that includes only the "RecordType" and "OriginalZip" columns. | ||
# Use this second dataset to filter the dataset down to just rows from your zipcode. If you don't live in Seattle, you can just use my zip code (98112) which covers north Capitol Hill and Montlake or you can pick an area you think is interesting from [https://www.usmapguide.com/washington/seattle-zip-code-map/ this map]. | # Use this second dataset to filter the dataset down to just rows from your zipcode. If you don't live in Seattle, you can just use my zip code (98112) which covers north Capitol Hill and Montlake or you can pick an area you think is interesting from [https://www.usmapguide.com/washington/seattle-zip-code-map/ this map]. | ||
## Now look at the number and proportion of different types of records in this subset. | ## Now look at the number and proportion of different types of records in this subset. | ||
## Be ready to explain if the distribution in this zipcode different than the distribution in Seattle overall? If not, how is it different? | ## Be ready to explain if the distribution in this zipcode different than the distribution in Seattle overall? If not, how is it different? | ||
## Once again, print out the "Description" of several examples from each category. What kinds of things are included? | ## Once again, print out the "Description" of several examples from each category. What kinds of things are included? | ||
# Use pandas to write out the | # Use pandas to write out the two-column dataset to TSV (with ''tabs'' instead of commas). | ||
== It's about time == | == It's about time == |