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Class 11 XI Python and Computer Fundamental
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Top 10 reasons to learn python
This file tells why one should consider python as it first programming language and explains the top ten reasons for its popularity.
kaushal shah
yash pal
Discovery of python
Python is an interpreted, high-level, general-purpose programming language. Created by Guido van Rossum and first released in 1991, Python's design philosophy emphasizes code readability with its notable use of significant whitespace. Its language constructs and object-oriented approach aim to help programmers write clear, logical code for small and large-scale projects.[27]PythonParadigmMulti-paradigm: functional, imperative, object-oriented, reflectiveDesigned byGuido van RossumDeveloperPython Software FoundationFirst appeared1990; 29 years ago[1]Stable release3.7.4 / 8 July 2019; 2 months ago[2]2.7.16 / 4 March 2019; 6 months ago[3]Typing disciplineDuck, dynamic, gradual (since 3.5)[4]LicensePython Software Foundation LicenseFilename extensions.py, .pyc, .pyd, .pyo (prior to 3.5),[5] .pyw, .pyz (since 3.5)[6]Websitewww.python.org
Dipesh Bhatiya
Python Language Basics
This PDF contains all the basics of Python Language. The notes in this pdf is for beginners. Anyone Can start python coding from this pdf.
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Python Function and Classes
This PDF is all about the built-in function in Python Language. This PDf also contains the basics of function and classes in python .
NumPy Basics for Data Analysis
This PDF is for those who want to learn NumPy for Data Analysis . NumPy is Python Library used for Data Analysis. All the Basics for Data Analysis are available in this PDF.
Data Agregation With Pandas (Python)
This PDF contains basics of Data Aggregation . In this PDF,Pandas library of Python Is used for data aggregation with examples.
Data Analysis Examples
This PDF contains some Data Analysis Example with Soltuions. Data Analysis is done using Pandas and Python so you should have some basic knowledge of Python and pandas .
Data Cleaning with Pandas(Python)
This PDF is about Data Cleaning using Pandas (Python).