Join Dan Sullivan for an in-depth discussion in this video Creating a view, part of Advanced SQL for Data Scientists.
- [Narrator] We can group data in a variety…of ways using Sequel.…Now we'll be working with data from the staff,…company divisions and company regence table.…So let's create a view using a select statement…with the appropriate joins.…This will save us from having to type long…joined statements repeatedly.…So lets start by defining the select…statement that we want.…So I'll start by saying, select.…I want to select all of the columns…from the staff table.…And I want to select company division.…And I want to select company region,…and I want to select this from the staff table,…which we'll alias as s.…
And, we'll left join on the company divisions table,…and we'll do this on the staff table department.…And, company divisions department.…And we'll left join company regions.…On, staff, region id and the company regions.…Region id.…And before I run this, it looks like I missed the s…at the end of the cr.company_regions column.…And, what we have here is a select statement…that uses two left joins and it selects all…the rows from the staff table,…
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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