Python is an interpreted, general-purpose object-oriented programming language. It’s designed to have better code readability and has a gentler learning curve compared to other languages. Its formatting is visually uncluttered, and it often uses English keywords where other languages use punctuation. Following are our tutorials on python:
Python for Data Science
Data Science is the practice of extracting meaningful and actionable insights from data. Python, R, Jupyter, Spider, etc are just tools that enable us to do that. Python is preferred by a number of data science practitioners because of its power and support of a number of open-sourced libraries like numpy, pandas, scipy, scikit-learn for accomplishing almost any data-related tasks. Also, it has an easier learning curve for beginners.
Here’s the complete list of articles of our five-part tutorial series on Python for Data Science:
Python Strings
Strings in python are immutable sequences of Unicode characters. Python has a number of in-built functions for working with strings. Also note that strings implement all common sequence operations like membership tests, slices, etc.
Tutorials on python strings:
- Python – Trim Whitespace Characters from Strings
- Python – Reverse a String with Examples
- Python – Remove Character From String
- Python – Frequency of each word in String
- Python – Convert List to a String
- Python String Count – With Examples
- New String Functions in Python 3.9
- Python String Find – With Examples
- Python String Startswith – With Examples
- Python String Endswith – With Examples
- Python String Split – With Examples
- Python String Join – With Examples
- Python String Concatenation – With Examples
- Python String Replace – With Examples
- Python String Uppercase – With Examples
- Python String Lowercase – With Examples
- Python String Strip – With Examples
Python List
Lists are used to store an ordered collection of items. These items can be any type of object from numbers to strings or even another list. This makes lists are one of the most versatile data structures in python to store a collection of objects.
Tutorials on python lists:
- Python – Check if an element is in a list
- Python – Iterate over multiple lists in parallel using zip()
- Python – Flatten a list of lists to a single list
- Pandas DataFrame to a List in Python
- Python – Convert List to a String
- Convert Numpy array to a List – With Examples
- Python List Comprehension – With Examples
- Python List Index – With Examples
- Python List Count Item Frequency
- Python List Length
- Python Sort a list – With Examples
- Python Reverse a List – With Examples
- Python Remove Duplicates from a List
- Python list append, extend and insert functions.
- Python list remove, pop and clear functions.
Python Dictionary
Dictionaries are used to store key to value mappings in python. Unlike sequences (example, lists, tuples) which are indexed by a range of numbers, dictionaries are indexed by keys. Dictionaries are mutable but you can only use immutable types as their keys.