Next to Excel, for the time being, jupyter notebook

This blog is the entry for the first day of jupyter notebook Advent Calendar 2016.

Excuse me first. I'm not feeling well, so I won't write a decent article. I'm halfway through, but please forgive me.

Purpose of this article

I want many people to use jupyter notebook (a programming environment that allows trial and error)

Expected readers of this article

Those who feel that data analysis using Excel is the limit
Large data (CSV) can be provided
I think I can't go without studying programming, but I'm wondering what to study
I want to get data from the Web (scraping)

1. Those who feel that data analysis using Excel is the limit

Read this article Many benefits found by changing business data analysis from EXCEL to Python-centric. It says python, but it's effectively a jupyter notebook.

In the above article, I list four advantages of performing data analysis with Python.

Enables data analysis that Excel cannot do in the first place
Human error due to erroneous operation is drastically reduced
Raise the team level and improve the code reuse rate by visualizing the logic
To get better people

As for my own feeling, 2. It seems that the merit of drastically reducing human error due to erroneous operation is great. It is quite advantageous to make a jupyter notebook for work that is prone to mistakes.

Well, the original items 2,3,4

jupyter notebook I will briefly introduce it as recommended.

For installation, see For windows.
For example, this is Get immigration data You can use it as it is. If you want to bring government statistics and use them at hand, please remodel them.

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