Category: Tips & Tricks
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Python Regex Match: A Comprehensive Guide for Pattern Matching with Regular Expressions & re module
Master the art of pattern matching in Python with our comprehensive guide on Python RegEx Match. Explore re.match(), re.search(), and other RegEx functions, understand the Match object, and learn advanced techniques with practical examples. Unlock the full potential of regular expressions in text processing and data extraction.
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How to Merge Dictionaries in Python – Definitive Guide – 8 methods and code including clean single expression one line options
Discover how to merge dictionaries in Python with this comprehensive guide. Explore standard and advanced techniques, including the update() method, dictionary unpacking, Python 3.9’s union operators, ChainMap, and more. Learn to handle duplicate keys, nested pairs, and merge multiple dictionaries with ease.
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How to Read CSV Files in Python (Module, Pandas, & Jupyter Notebook Examples)
We all experienced the pain to work with CSV and read csv in python. We will discuss how to import, Load, Read, and Write CSV using Python code and Pandas in Jupyter Notebook; and expose some best practices for working with CSV file objects. We will assume that installing pandas is a prerequisite for the…
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Citi Bike NYC Deep Dive: All-in-One Data Notebook From Data Analytics to Data Science
Citi Bike is a convenient solution for quick trips around the City. Users could unlock a bike at any station and ride wherever they want.
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Are Jupyter Notebooks a Semantic Layer?
Jupyter Notebooks as a semantic layer bring consistency to your analysis by providing a way to document and track the lineage of your code. This helps ensure that your analysis is reproducible, transparent, and well-documented.
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Master Python Lists – How to Create, Append, Reverse, Sort, Slice a list in Python
Explained with Code – How to create, update, append, filter, remove, pop and other list methods for Python lists.
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The Most Common Python Libraries for Data Visualization
Data visualization is important because it helps us understand complex data, communicate information effectively, improve decision-making, provide insights, and save time.
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Object Oriented Programming in Python for Data Science | Python OOP for Data Scientists
Basics of Object Oriented Programming (OOP) for data scientists. Learn how to write high quality code that is scalable, modular, reusable and maintainable.
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Python JSON Loads – 4 Faster Alternatives to json.loads in Python | Ojrson Ujson Pandas Msgspec
json loads too slow? Get up to 100x faster json loading with these 4 alternatives to the standard json library in Python.
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Clickstream Data Analytics
Funnels are everywhere. They’re so common that you might say we live in a world of funnels. But working with funnel data can be a hassle.