Data visualization

Why should I do it?

▶ ︎ What materials do you get at a glance?

You can identify correlations between data faster with a heatmap chart than tabulated data.

Not because it's so pretty, To work efficiently we use visualizationI will. This is because using vision to view heatmaps is more efficient than using cognitive functions to understand table numbers.

Charts can also be used as Excel

I can make it, but...

▶ ︎ The screen stopped when I tried to chart 150,000 pieces of data

There are limitations like these.

• Insufficient capacity: Excel is difficult to process large amounts of data. Click and wait for half a day... Sometimes the screen freezes and everything just blows away. ()
• Limited visualization features: There are few types of charts that can be created. It's a great tool for creating simple reports rather than looking for a variety of insights.

Using Python

Is there a reason?

It's also a perfect tool for Python itself.

• Efficiency: More than 100,000 rows of high-volume data can be visualized in 1 second. (For those dealing with process data pouring out in seconds, data visualization using Python will be revolutionary.)
• Variety of techniques: After learning basic graphs, Library pageFind the graph you need in and apply it to the field of practice you are dealing with. (I've included this course separately in the Tip lesson!)
• Fine-grained option settings: Just showing this is the very chart drawn in my head that seems like the game is over! We'll help you visualize it as it is through a variety of options.

There's also a bonus advantage.

• Big data analysis/machine learning/artificial intelligence It can be linked to. (More than 80 percent of data analysts use Python tools.)

With other data analysis classes

What's different?

• This course is one of the steps in big data analysis Exploratory Data Analysis (Exploratory Data Analysis)This is a course for.
• It's about “scouring through data like an explorer” to find insights.
• There are common indicators to show when creating a dashboard for simple management analysis, but EDA I need to be able to visualize everything I'm curious about I will. Let's find out the difference between the two? 😉

Above “Status of employees' reasons for leaving the company” This is a generic visualization created to report. If these visualizations are grouped around various indicators, it's a dashboard. It's good to understand information intuitively.

However, this time in the HR department High turnover rateThe problem caused by has become a hot topic, and I want to determine the cause.

• If so, don't you get an answer if you first group the top 4 cases in red, such as “decreased immersion” and “dissatisfaction with compensation,” and look at their characteristics?

Voila, I separated the data and first looked at the duties of those personnel,

“Production Technician (Production Technician)”There are a lot of strange things.

• I think there's something wrong with this job.
• Or maybe it's simply a company with absolutely many engineers, so it came out high, right? (Because I only have strong hair.)
• For confirmation, you should also plot a graph as a ratio to the total number of people.
• What if they are drawn in proportion and are equally high? We need to go deeper and find the cause.

These are the processes of EDA Startup steps It's. Do you see a difference? In this class, you will learn basic skills and libraries to do this freely. In addition, we have designed it so that you can enjoy basic EDA courses through practical data.

So that the analysis is not difficult

I'll let you know in detail!

“What kind of visualization should I do with this data?”

“I did visualization, but... How do you find insights here? '

Based on the grievances I experienced while working as a data analyst from Moon and native data analysts, and questions I received during lectures I'll be your own data analysis mentor so that you can become a 'visual analytic' looking for insights beyond simple visualization!

We'll give you the code

Just bring your curiosity!

• It provides visualization codes that can be applied directly to practice. Complete a high-quality visualization right away by replacing only the data and variables in the provided code.
• At first, it was so easy for me (?) I did it. If it's fun, you'll study more on your own!

If you only have small visualization skills, you can gain wings and create your own strengths.

Let's all work together to find meaningful insights in the zero and one data world!