- [Instructor] Now I have pgAdmin started,…and I'm going to click on the Tools menu,…and select Query Tool.…This will open a query window.…Notice, in the blue bar in the query window,…it says data_sci on postgres.…That means we're working with the data_sci database,…which is what we want.…So now, let's open a script file.…And if you have access to the exercise files,…you'll want to open the mock_staff.sql file,…which I have in my user directory, and I will open that,…mock_staff, and I will select that.…
And what you'll notice here, mock_'s staff table…includes a series of create table statements…and insert statements, and this will create the schema…and the data that we'll need for our exercises.…So I'm going to go up to the Execute button,…and I will execute this statement.…And that has finished executing.…Now let's Control click on the Tables item…in the hierarchical navigation,…or right-click if you're using Windows.…And let's select Refresh.…And now let's open the Tables again.…What you'll notice is we have three tables,…
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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