10 SQL Tricks Every Data Scientist Should Know - Part 1 | Data Talks with Kat

SQL is probably one of the most commonly used yet underappreciated tools in your day-to-day work. Unfortunately, many data scientists consider SQL merely a middleman between the "boring data" and "cool work." Well, not really~ Knowing SQL, especially some hidden but useful tricks, will deepen your understanding of the data structure and significantly increase your work efficiency.

This "Part 1 of the 10 SQL tricks series" will discuss four useful SQL tricks that every data scientist should know. They are summarized as below:

Trick #1: Handling Missing Value using Coalesce() - 3:26
Trick #2: Running Total and Cumulative Frequency - 6:19
Trick #3: Finding Records with Extreme Values without Self-joining - 11:38
Trick #4: Conditional WHERE clause - 14:45

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Hi, I'm Kat Li. Welcome to my channel, "Data Talks with Kat," where I will share my own experience with data science and its applications. If that sounds like it could be helpful for you, please join me by subscribing to my channel.

📧 Business inquiries: yilistats[at]outlook[dot]com.

The following are Amazon affiliate links. That means if you purchase through the links below, I will get a small % from Amazon, but there is no premium added to your purchase price. Thank you for your support :)

#SQL #datascience #datascientist #career

[JorgeEscobarMX]

1:39 "SQL is way more than SELECT JOIN ORDER BY statements" amen to that.

[leanhphan]

Hi, do you offer SQL tutorial course? I really like your way of explanation.

[Riteshsawantplays]

Hi quick question,
Cant we use the PERCENT_RANK() or CUME_DIST() functions to get the cumulative frequencies for the Amount?

[DataTalksWithKat]

Let me know what is your favorite SQL tricks by commenting below!

[txreal]

Thank you so much! I just learned DATE_TRUNC, and DATE_PART in school.
Can you show us more datetime manipulations (CAST, CONVERT, ... ) with GROUP BY, ORDER BY, ?