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Hello fellow data cruncher!

The Query here 👋

Here’s what we have for you today:

• The job market for data analysts is heating up 🔥

• Ever wondered the difference between SQL and Pandas? 📊

• Two convenient SQL functions for rounding numbers 👨‍💻

• Hilarious memes 🤣

→ Looking to become a Data Analyst? START HERE.

select * from data-jobs

remote, data jobs

When refreshing the job board this week, I noticed A LOT more data analyst job openings this past week compared to prior weeks.

If you’re open to exploring new data jobs, now might be a good time!

→ Check out the Job Board and this week’s featured jobs here.

1. Data Analyst @ Statara Solutions — $60-70k per year

2. Analytics Lead @ Scan.com — $160-170k per year

3. Senior Analytics Consultant @ Focus Strategies — $115-135k per year

freelance gigs

Need work experience? Get real experience with real projects.

1. Build Tableau reports — $2,500 fixed price (apply here)

2. Marketing and Sales Analyst — $35-50 per hour (apply here)

3. Google Analytics Dashboard — $100 fixed price (apply here)

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def content_spotlight(🔦):

I have been doing data analysis for a decade.

At first, I had shiny object syndrome when it came to tools.

I thought, “to be a real data analyst, we need to learn [insert tool name].”

The truth is, you can do most analysis within Excel.

The question is, “What’s the best tool for the job?”

Regarding Python’s Pandas library and SQL, it’s tough to know which tool is better in which situation.

If you’re a bit more advanced reader of The Query, give this article a read.

You’ll learn about:

• the performance difference between SQL and Pandas

• how to do more complex tasks in both SQL and Pandas

• and more!

It’s a great piece because it shows 2 approaches (SQl vs Pandas) to solving the same problems.

class SQLMiniLesson:

A simple way to round numbers in SQL

Kyle here 👋 — As data analysts, working with numerical data often requires rounding numbers.

In SQL there are a handful of different ways to do this.

Today, we’ll be discussing two useful functions for rounding numbers: CEILING and FLOOR.

These functions allow you to round numbers up or down, respectively, to the nearest integer.

CEILING: This function rounds up a given number to the smallest integer that is greater than or equal to the number.

It can be useful when you need to round up quantities, prices, or other numerical values in your dataset.

FLOOR: This function rounds down a given number to the largest integer that is less than or equal to the number.

It can be beneficial for rounding down numerical values to ensure conservative estimations.

Let's consider an example where we have a table named product_prices with the following data:

We want to calculate the rounded prices for each product, using the CEILING and FLOOR functions.

In this case, we can use the following SQL query:

In this example, the query uses the CEILING and FLOOR functions to round the prices up and down, respectively.

As a result, we can see the rounded prices for each product in our dataset.

As a data analyst, understanding how to use the CEILING and FLOOR functions in SQL will undoubtedly come in handy when you need to use them!

import memes as 😂 

Tip for enhancing your resume bullet points 🤣:

content & resources 🤓 

1. YouTube Channel: Click here for videos on SQL and data analytics.

2. Become a Data Analyst Guide: Our full guide on what it takes to land a job as a data analyst.

3. Open Data Analyst Jobs: Find your next data job here!

4. Download our SQL Cheatsheet as a PDF and desktop wallpaper here.

5. LinkedIn: I regularly post data content on LinkedIn.

That’s it for today.

Stay crunchin’ folks and see you next week!

— Kyle

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