- [Instructor] Starting with PGM in open…select the data sci database…and within that the public schema.…Next click on the tools menu at the top of the screen…and select Query Tool.…This will open a sequel window.…We'll do most of our work in query windows like this.…The top window has an area where we enter sequel commands.…The results of our queries will appear in the bottom panel.…Let's type a simple select command in the query window.…Select, star, from, staff.…
I'm just going to move the results pain down slightly.…Click on the execute button…which has the lightening bolt icon.…This will execute the query.…Notice the query result rows appear in the lower pane.…You can scroll through to see the rows.…One thing that I like to do when I'm checking a table…is to just return the first several rows…instead of retrieving all of them.…This is especially useful when working with large tables.…So I'll add a limit clause…and restrict it to the first 10 rows.…
I'll then click the query execution command…and you'll notice that we have rows down here.…
The course begins with a brief overview of SQL. Then the five major topics a data scientist should understand when working with relational databases: basic statistics in SQL, data preparation in SQL, advanced filtering and data aggregation, window functions, and preparing data for use with analytics tools.
- Data manipulation
- ANSI standards
- SQL and variations
- Statistical functions in SQL
- String, numeric, and regular expression functions in SQL
- Advanced filtering techniques
- Advanced aggregation techniques
- Windowing functions for working with ordered data sets
Skill Level Advanced
1. SQL as a Tool for Data Science
SQL data definition features5m 32s
2. Basic Statistics with SQL
3. Data Munging with SQL
4. Filtering, Joins, and Aggregation
5. Window Functions and Ordered Data
6. Preparing Data for Analytics Tools
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