Welcome to Pylenin Weekly #17, a newsletter dedicated to improving the lives of my fellow peers through knowledge sharing in the field of programming and data.
I would say that I have made up for my slack the last few weeks!
I would like to share some really interesting articles that I have written on Python and Data Engineering topics.
A generator is a special type of function which returns an iterator object with a sequence of values. In a generator function, a yield statement is used rather than a return statement.
Learn in-depth about Python generators!
How efficient are Python generators?
I had posted my article on Python generators on Reddit. That post got a humongous response from the community members.
However, some of the members also asked a very obvious question!
What would be a real life example of generator application? And, are they really useful?
This encouraged me to write an article on demonstrating the true powers of Python generators by running a performance comparison with the return statement.
And the results are just fab!
Learn about the entire experiment in this article!
How many ways can you write if else statements?
I can write them 3 ways!
The first way is the obvious way!
The second is a bit shorter!
The third is really short!!
Check out all the 3 ways in this article.
Data Engineering articles
I recently started blogging about Data Engineering with Python on my new blog - 100 days of data. Go ahead and give it some love!
Python File I/O
This article is an introduction to performing various file operations in Python. It covers -
- How to open files in read-only mode?
- How to write to files?
- How to append to a file?
- How to close a file?
- How to read and write to a file at the same time?
- Commonly used file methods in Python
This is one of those fundamental topics that you really need to grasp before moving on to more advanced data engineering applications in Python.
Check out this article here!
Data Analysis of Kaggle's Titanic dataset from a CSV in Python
CSV files are very common. If you ever want to work as a Data Analyst, you should be skilled in the business of working with huge CSV files.
In this article, you will learn the ins and out of working with CSV files in Python using both the
You will also perform data analysis on the Kaggle's famous Titanic dataset.
Check out this article here!
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