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The following database project will create an educational attainment “demand” forecast for the state of California for years greater than 2010. The demand forecast is the expected number of population who have obtained a certain level of education. The population is divided into age groups and education attainment is divided into different levels. The population of each group is estimated for each year up to year 2050. Implement the following steps to obtain and educational demand forecast for the state of California. The files can be downloaded below.

  1. Create a ca_pop schema in your MySQL database.
  2. Using your ca_pop schema, create an educational_attainment table which columns match the columns in the Excel spreadsheet ca_pop_educational_attainment.csv.
  3. Using your ca_pop schema, create a pop_proj table which columns match the columns in the Excel spreadsheet pop_proj_1970_2050.csv.
  4. Using the data loading technique for a csv file you learned in Module 1, load the data in ca_pop_educational_attainment.csv into the table educational_attainment.
  5. Using the data loading technique for a csv file you learned in Module 1, load the data in pop_proj_1970_2050.csv into the table pop_proj.
  6. Write a query to select the total population in each age group.
  7. Use the query from Step 6 as a subquery to find each type of education attained by the population in that age group and the fraction of the population of that age group that has that educational attainment. Label the fraction column output as coefficient.For instance, the fraction of the population in age group 00 - 17 who has an education attainment of Bachelor's degree or higher is 0.0015, which is the coefficient.
  8. Create a demographics table from the SQL query from Step 7.
  9. Create a query on the pop_proj table which shows the population count by date_year and age.
  10. Use that query from Step 9 as a subquery and join it to the demographics table using the following case statement:
  11. demographics.age = 
                    case
                            when  temp_pop.age < 18 then '00 to 17'
                            when  temp_pop.age > 64 then '65 to 80+'
                            else  '18 to 64'
                            end

    “temp_pop” is an alias for the subquery. Use the following calculation for the demand output:

    round(sum(temp_pop.total_pop * demographics.coefficient)) as demand

    Output the demand grouped by year and education level

THE BELOW TABLES ARE PORTIONS OF THE CSV FILE FOR QUESTION 3 AND 4. UNABLE TO UPLOAD THE ENTIRE FILES

ca pop educational attainment table

Year Age Gender Educational Attainment Personal Income Population Count
1/1/2008 0:00 00 to 17 Male Children under 15 No Income
1/1/2008 0:00 00 to 17 Male No high school diploma No Income 650889
1/1/2008 0:00 00 to 17 Male No high school diploma $5,000 to $9,999 30152
1/1/2008 0:00 00 to 17 Male No high school diploma $10,000 to $14,999 7092
1/1/2008 0:00 00 to 17 Male No high school diploma $15,000 to $24,999 3974
1/1/2008 0:00 00 to 17 Male No high school diploma $25,000 to $34,999 2606
1/1/2008 0:00 00 to 17 Male No high school diploma $35,000 to $49,999 2227
1/1/2008 0:00 00 to 17 Male High school or equivalent No Income

pop_proj table

fips county year age pop_female pop_male pop_total
6001 ALAMEDA 1970 0 8533 8671 17204
6001 ALAMEDA 1970 1 8151 8252 16403
6001 ALAMEDA 1970 2 7753 8015 15768
6001 ALAMEDA 1970 3 8018 8412 16430
6001 ALAMEDA 1970 4 8551 8648 17199
6001 ALAMEDA 1970 5 9012 9208 18220
6001 ALAMEDA 1970 6 9637 9636 19273
6001 ALAMEDA 1970 7 9561 9713 19274
6001 ALAMEDA 1970 8 9648 10008 19656
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