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News & links about Python programming.
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Intro to Regexes & Strong Password Detection in Python

Build a Password Detector from Scratch

https://medium.com/analytics-vidhya/intro-to-regexes-strong-password-detection-in-python-2138fc3cf8bf
Bar Chart Race in Python with Matplotlib

~In roughly less than 50 lines of code

https://towardsdatascience.com/bar-chart-race-in-python-with-matplotlib-8e687a5c8a41
Java vs. Python: A Comparison of Features and Usage

Knowing when, not just how, to use a programming…

https://medium.com/better-programming/java-vs-python-a-comparison-of-features-and-usage-6f3629c723f4
Demystifying hypothesis testing with simple Python examples

Hypothesis testing is the bread and butter…

https://towardsdatascience.com/demystifying-hypothesis-testing-with-simple-python-examples-4997ad3c5294
How to create a simple ETL Job locally with PySpark, PostgreSQL and Docker

https://itnext.io/how-to-create-a-simple-etl-job-locally-with-pyspark-postgresql-and-docker-ea53cd43311d
Multiprocessing vs. Threading in Python: What Every Data Scientist Needs to Know

Sooner or later, every data science project faces an inevitable challenge: speed. Working with ...

https://blog.floydhub.com/multiprocessing-vs-threading-in-python-what-every-data-scientist-needs-to-know/
Beating the Dealer with Simple Statistics

Simulating Thousands of Blackjack Card Counting Strategies…

https://towardsdatascience.com/beating-the-dealer-with-simple-statistics-71b5e3701638
Understanding Python's asyncio

by Reuven M. Lerner

How to get ...

https://www.linuxjournal.com/content/understanding-pythons-asyncio
Python List Comprehension in 3 Minutes and 3 Reasons why you should use it

Let´s create our own animal…

https://towardsdatascience.com/python-list-comprehension-in-3-minutes-and-3-reasons-why-you-should-use-it-bf398654caf9
donnemartin /



data-science-ipython-notebooks


Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

https://github.com/donnemartin/data-science-ipython-notebooks