- [Instructor] In the previous video,…I created a coefficient for use in forecasting…educational attainment by age and gender.…In this video, I'll apply that coefficient…to the forecasted populations as found in the dataset…for California Populations from 2010 to 2060.…The SQL for this solution…is found in the chapter six exercise files.…We can create a new tab and open those files.…Go navigate to that exercise files chapter six.…
We want create demand for 2015 plus.sql.…Now, again this is pretty standard SQL…except for this case statement in line five.…Let's take a look at what that's doing.…If we look at the educational attainment data,…the ages are stored as ranges 00 to 17,…18 to 64, 65 to 80 plus.…
However, if we look at the population data,…this dataset stores ages as integers…17, 18, 19, 20, 21.…This case statement starting in line five…allows us to join between those two datasets…based on a lookup value.…Here's how it works.…Here's the join statement that's in line four…so we're joining demographicSplit ON DRU.Gender and…
- Strengths and weaknesses of SQLite
- Creating a database
- Joining data sets
- Calculations with SQLite and Python
- Searching a database
- Subqueries and queries in SQLite
- CRUD operations in SQLite with R
Skill Level Intermediate
1. SQLite in Five Minutes
2. Create a Database
3. Join Two Datasets
4. Search a Database
5. Create, Read, Update, and Delete Operations
6. Averages and Calculations
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