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01_python_introduction

Learn the basics of Python. These tutorials are for Python beginners. so even if you have no prior knowledge of Python, you won’t face any difficulty understanding these tutorials.

02_python_datatypes

Data types specify the different sizes and values that can be stored in the variable. For example, Python stores numbers, strings, and a list of values using different data types. Learn different types of Python data types along with their respective in-built functions and methods.

03_python_flow_control

Flow control is the order in which statements or blocks of code are executed at runtime based on a condition. Learn Conditional statements, Iterative statements, and Transfer statements

04_python_functions

The function is a block of code defined with a name. We use functions whenever we need to perform the same task multiple times without writing the same code again. It can take arguments and returns the value.

05_python_files

Python too supports file handling and allows users to handle files i.e., to read and write files, along with many other file handling options, to operate on files. The concept of file handling has stretched over various other languages, but the implementation is either complicated or lengthy, but like other concepts of Python, this concept here is also easy and short. Python treats files differently as text or binary and this is important.

07_python_advanced_topics

You'll learn about Iterators, Generators, Closure, Decorators, Property, and RegEx in detail with examples.

08_python_date_time_module

Time is undoubtedly the most critical factor in every aspect of life. Therefore, it becomes very essential to record and track this component. In Python, date and time can be tracked through its built-in libraries. This article on Date and time in Python will help you understand how to find and modify the dates and time using the time and datetime modules.

09_python_numpy_module

Numpy is a general-purpose array-processing package. It provides a high-performance multidimensional array object and tools for working with these arrays. It is the fundamental package for scientific computing with Python. Besides its obvious scientific uses, Numpy can also be used as an efficient multi-dimensional container of generic data.

10_python_pandas_module

Pandas is a high-level data manipulation tool developed by Wes McKinney. It is built on the Numpy package and its key data structure is called the DataFrame. DataFrames allow you to store and manipulate tabular data in rows of observations and columns of variables.

93_python_assignments_1854

clustering-datasets

This repository contains the collection of UCI (real-life) datasets and Synthetic (artificial) datasets (with cluster labels).