*********************************************************************;
*Question 1 (20 pts);
**** For the two datasets below,
     1a. use a data step to merge, and
     1b. use a PROC sql to join.
     1c. Do you get the same results? If no, update your proc sql to make the result the same;
;

data one;
   input x $;
   datalines;
cat
catnap
catnip
;
data two;
   input x $3. y ;
   datalines;
cat 111
dog 222
;


*Q2: bookstore datasets from Canvas classroom.
*Q2a (15 pts) – Check the variables contained in each individual data table below:
           customers, items, list, orders, prices and salesrep.
    The purpose of this exercise is to identify the match keys across the data sets for merging.
     create a dataset that stores the list of variable names in each table. Each column lists the
     variable names for one dataset. e.g. a column called customers with values being the variable
     names of the dataset customers.
      hint: use the option OUT= in PROC CONTENTS to save dataset information in another dataset for
      additional processing.;


*Q2b (15 pts) – Create a table using PROC SQL to join the tables orders, items, and list, and
*    –include all columns from orders, the author and bookid columns from list;
*    –Include only rows that match across all three data sets , and
*    –Create a variable YEARSOLD for the year that the books was ordered;


*Q2c(10 pts) in Q2b above, all the requested columns are available in two tables: orders and list.
     Can you join only these two tables without the third table items? why or why not?;



*Q2d(15 pts) – Join the data sets orders and customers containing only the order numbers between
     45520 and 45570;
*    — include all vars in the ORDERS table;
*    — include no variables from the customers table, and
*    — add a variable containing the name of the customer as “first name, exactly one space,
     last name”. e.g. John Smith;


*Q2e(15 pts) – Join the data to create a table including the variables
       order number,
       date shipped,
       ID of the sales rep and
       last name of sales rep.  ;
  
    
*Q2f(10 pts) – use the table you created in Q2e above, use PROC SQL step(s) to figure out which rep
     sold the most;