Data analysis overview python

This time, I will write it as an output of studying machine learning.

Contents

・ Glossary ・ Tools and how to use them

What is data analysis?

Using data such as customer information and charts that are often used for investment, past information is visualized with graphs to grasp trends, and regression is used to predict the future of data.

Commonly used tools and their characteristics

Jupyter notebook is often used as a tool often used in data analysis. The characteristics are as follows. ・ Start on the browser ・ Interactive (interactive) ・ Data can be easily visualized

For data analysis

Things to keep in mind when analyzing data ・ Understanding the outer frame (overview) of data ・ If the data is too clean, doubt the data ・ It is important to go steady (hurry up)

Basic usage of jupyter notebook

jupyter notebook is divided into command mode and edit mode Command mode: No cell (field for entering code) is selected You can refer to help by pressing "h" in this mode Edit mode: A cell is selected, a program can be entered. Press "b" to create a new cell You can delete the selected cell by pressing "d" twice. Execute with "shift + Enter" From the column next to the keyboard in the menu above the cell If you select markdown, you can write notes like commenting out

About basic analysis

Basic analysis is to get a rough idea of the data. For details ・ Take a quick look at the data ・ Let's dig a little deeper into the data ・ Graph ・ Check the defective area ・ Examine the relationship of data (correlation)

If you neglect the basic analysis

・ Due to lack of data, everything may be redone ・ Insert wrong data and the result will be different from the original result.

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