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What is Python

and why use it?

Winny de Jong @ GIJC 2021

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Hi! 👋🏾 This is presentation was originally created by me, Winny de Jong, for my #GIJC21 talk called ‘What is Python & Why use it?’. Before you continue, it’s good to know that some of the links and information are not in/on the slides, but in the speakers notes.

Every Sunday I sent out a data-driven journalism related listicle. Since you’re here for these slides, I think you’ll like this too. It’s free and fun, subscribe here if you’d like: https://ddj.news�

One last thing: if you’re about to start learning Python, please be kind to yourself. Whatever you do, simply keep going: trust the process, do the work, stay awesome and get better. Good luck! Best, Winny

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Nice to meet you! 👋🏾

About Python
Examples
Now what?

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What is Python anyway?

Python is an interpreted high-level general-purpose programming language.

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Readability zen

Image by XKCD

It was mainly developed for emphasis on code readability, and its syntax allows programmers to express concepts in fewer lines of code. Readability counts.

The Zen of Python�https://www.python.org/dev/peps/pep-0020/

Beautiful is better than ugly.

Explicit is better than implicit.

Simple is better than complex.

Complex is better than complicated.

Flat is better than nested.

Sparse is better than dense.

Readability counts.

Special cases aren't special enough to break the rules.

Although practicality beats purity.

Errors should never pass silently.

Unless explicitly silenced.

In the face of ambiguity, refuse the temptation to guess.

There should be one-- and preferably only one --obvious way to do it.

Although that way may not be obvious at first unless you're Dutch.

Now is better than never.

Although never is often better than *right* now.

If the implementation is hard to explain, it's a bad idea.

If the implementation is easy to explain, it may be a good idea.

Namespaces are one honking great idea -- let's do more of those!

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Readability zen

Simple is better than complex.

Complex is better than complicated.

It was mainly developed for emphasis on code readability, and its syntax allows programmers to express concepts in fewer lines of code.

The Zen of Python

Beautiful is better than ugly.

Explicit is better than implicit.

Simple is better than complex.

Complex is better than complicated.

Flat is better than nested.

Sparse is better than dense.

Readability counts.

Special cases aren't special enough to break the rules.

Although practicality beats purity.

Errors should never pass silently.

Unless explicitly silenced.

In the face of ambiguity, refuse the temptation to guess.

There should be one-- and preferably only one --obvious way to do it.

Although that way may not be obvious at first unless you're Dutch.

Now is better than never.

Although never is often better than *right* now.

If the implementation is hard to explain, it's a bad idea.

If the implementation is easy to explain, it may be a good idea.

Namespaces are one honking great idea -- let's do more of those!

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Readability zen

Explicit is better than implicit.

Errors should never pass silently.

It was mainly developed for emphasis on code readability, and its syntax allows programmers to express concepts in fewer lines of code.

The Zen of Python

Beautiful is better than ugly.

Explicit is better than implicit.

Simple is better than complex.

Complex is better than complicated.

Flat is better than nested.

Sparse is better than dense.

Readability counts.

Special cases aren't special enough to break the rules.

Although practicality beats purity.

Errors should never pass silently.

Unless explicitly silenced.

In the face of ambiguity, refuse the temptation to guess.

There should be one-- and preferably only one --obvious way to do it.

Although that way may not be obvious at first unless you're Dutch.

Now is better than never.

Although never is often better than *right* now.

If the implementation is hard to explain, it's a bad idea.

If the implementation is easy to explain, it may be a good idea.

Namespaces are one honking great idea -- let's do more of those!

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Data Science

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Ok. But how about R?

Image + more info here

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Python for data driven journalism

collect
clean
analyse
visualise

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Be smart about it

Millions of rows? Consider SQL

If time is of the essence - isn’t it always? - consider time.

collect data: Python is good for scraping;
create a reproducible workflow - makes fact-checking and verification easy, also nice for follow ups and reusability of code;
do data analysis;
make charts (personally I use Python for charts for myself not for publication);
reuse code from others - in packages but also from stackoverflow. Packages and libraries are life.

Fun side note:

For a story on how thin you need to be, to become a high fashion model, I scraped 1000+ models sizes from various website. Of 25+ scrapers, only a few (2 or 3) were written in Python. Time was of the essence, and out of the box tool Outwit Hub was faster. Pick the tool that suits your stories needs best - not the one that boosts your ego most. This story ended up winning the 2019 Public Choice Data Journalism award. :D

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XKCD

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Let’s look at

examples…

Oh and 1 little thing about work environment

The example stories and the code I wrote to get the stories are not in this file.

However, I’ve added a couple of stories I made using Python. �

YEAR: title + link using Google Translate, my contribution using Python.

2021: Social housing? In at least a quarter of the municipalities you wait more than 7 years, analysed data with Pandas;
2020: KLM, NS and Booking.com are the largest recipients of NOW wage support, ripped data from PDF’s using PDFPlumber and analysed said data with Pandas - all in a Jupyter Notebook;
2020: A third of students at a level other than school advice after three years, scraped data from website with education data + analysis with Pandas;
2019: These websites violate your privacy unsolicited, analysis with Pandas;
2018: Details of pets and their owners on the street, scraped data to prove the leak.

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Pixabay

about my work environment - it’s similar to painting.

When you paint a wall in your living room but can’t put the sofa elsewhere, you end up covering most things with plastic and taping everything up. Next you’ll get out your tools - brushes, paint, and start working.

When programming, you want to spare your computer like your sofa. So you create a seperate taped up space to work in - it’s called an ‘virtual environment’. It’s your workspace. There many ways to set such an environmnet up, I use anaconda. https://www.anaconda.com/products/individual More on this in the first part of Python for Journalists, https://datajournalism.com/watch/python-for-journalists.

Once in said environment, I get out my tools - also known as Python packages and libraries. Like a special brush to paint corners, most packages are good at 1 thing only: Pandas for spreadsheet like data analysis; requests well, for requesting websites; Beautiful Soup for breaking up HTML, etc.

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Ok, I’m in. Now

what do I do?

Here’s a collection of learn Python resources

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Tools I like

Other than Python ;-)