Statistics and Causal Inference
Acknowledgement
1
joins
1.1
joining
1.2
Set Operations
1.2.1
UNION
Operator
1.2.2
UNION ALL
Operator
1.2.3
INTERSECT
Operator
1.2.4
MINUS
(or
EXCEPT
) Operator
2
Basics
2.1
Order of Execution
3
Creatind Tables
3.1
Date Functions
4
FILTERING
4.1
Wildcards
4.2
DISTINCT keyword
4.3
Advanced Filtering
4.3.1
HAVING
Clause
4.3.2
QUALIFY
Clause
5
MOST USED FUNCTIONS
5.1
string functions
5.2
Aggregate Functions:
5.3
Non-Aggregate Functions:
5.4
Window Functions
5.5
Functions comparing columns:
5.6
Some Advanced Functions
5.6.1
LISTAGG
5.6.2
LATERAL
5.6.3
UPDATE
5.6.4
ALTER
5.6.5
DELETE ROWS
5.6.6
INSERT
6
Adhoc solutions
6.1
DATA QA EFFORTS
6.1.1
COUNTS
6.2
Balancing Weights
6.3
Weighted Sampling
6.3.1
Solution
6.4
Demographic Distribution
6.5
Risky Projects
6.5.1
tables
6.5.2
SOLUTION 1
6.5.3
SOULTION 2
6.6
How many users have applied to the same companies they have applied before the past year?
7
[Coding] Can you provide the solutions to (A) using Python or R?
8
Sample Solutions
8.1
Datalemur 20 Solved SQL
8.1.1
Repeated transactions
8.1.2
Describe how recursive queries work in SQL.
8.1.3
Median Google Search Frequency
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Chapter 7
[Coding] Can you provide the solutions to (A) using Python or R?