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- 🤓 Dip your toe in some Hydrology Datasets 💦
🤓 Dip your toe in some Hydrology Datasets 💦
The Query
September 07, 2023
Read Time: 3 minutes
Hey crunchers! The Query here — the data newsletter that's like an XLOOKUP for your data career, connecting you directly with the career insights that make a difference.
Cody is on vacation, so this week’s edition is 100% brought to you by me! (Kyle)
Here’s what I’ve got for you today:
Data Analyst Guide reminder
Hydrology datasets (and Livestream Announcement) 💦
How to check for divisibility in SQL
A doggone meme 🐶
def learn_data_analysis(👨💻):
1. Full Guide to Becoming a Data Analyst
In case you missed it, last week we officially launched our complete guide to becoming a data analyst!
Many hours of work and thought went into creating this, so we hope you get value from it. ❤️
The guide is broken up into 4 chapters:
Chapter 1: Is the Data Analyst Career Right For You?
Chapter 2: How to Approach Learning Data Analytics
Chapter 3: A 6-month Roadmap to Learn the Data Analyst Skillset
Chapter 4: How to Interview and Get a Data Analyst Job
select * from dataset-of-the-week
If you want to get your feet wet with some beginner-friendly data, check out these datasets on US rivers and watersheds 💦:
Here are a few questions to look into:
How does water discharge (cubic feet per second) compare along the same river at different monitoring locations (e.g., Colorado River near Rocky Mountain National Park vs near the Grand Canyon)?
When did rivers start to run dry? Is there a time-frame that seems important?
How is the health of your local watershed over the past 5 years? What variables can you use to determine this?
🚨 Livestream Announcement:
Tomorrow morning around 8 CST, I will be attempting a livestream on Youtube.
The topic is Waterfowl Migration.
Every year millions of ducks, geese, and other waterfowl migrate south for the winter, many through my home state of Kansas.
There is a lot of data that affects waterfowl numbers and migration time — weather, rainfall, crop yields, etc.
Tomorrow we’ll be starting to dig into this data and see if we can create a cool project around it.
If you would like to attend or see the replay after here is the link to our Youtube channel.
class MiniLesson:
Check Divisibility with MOD
As a data analyst, you may encounter situations where you need to determine if a number is divisible by another number.
This can be useful for a lot of things like checking if a number is odd or even.
In SQL, the MOD function can be a useful tool for achieving this goal.
The MOD function returns the remainder of a division operation, making it easy to check for divisibility.
It takes two arguments: the dividend and the divisor.
If the result is 0, it indicates that the dividend is divisible by the divisor.
Let's consider an example where we have a table named numbers with the following data.
We want to find the numbers in the table that are divisible by 5.
In this case, we can use the MOD function in combination with a WHERE clause.
In this example, the query uses the MOD function to filter the rows where the value is divisible by 5 (i.e., the remainder of the division by 5 is 0).
As a result, we get a list of numbers in our dataset that meet this condition, which are 20, 25, and 30.
Using the MOD function in SQL is handy tool for working with numerical data.
It allows you to quickly identify and filter rows based on divisibility, which can be helpful for various data analysis tasks, such as generating reports, identifying trends, or performing calculations on specific subsets of your data.
import memes as 😂
What it’s like to learn Python for the first time…
On a personal note, I (Kyle) got a puppy this weekend! He is a standard poodle named Reuben. Isn’t he cute? Now, back to The Query…
Our Content & Resources 🤓
1. Download our SQL Cheatsheet as a PDF and desktop wallpaper here.
3. Courses: Our course on showcasing your data portfolio is live!
4. Become a Data Analyst Guide: Our full guide on what it takes to land a job as a data analyst.
That’s it for today.
Stay crunchin’ folks and see you next week!
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