Q.E. Reviewer - AST01-AST15-part-6.pdf

AST06 - Astronomical Programming I (Python) Introduction What is Python? Python is a high-level, interpreted, interactive and object-oriented scripting language. Created by Guido van Rossum in nearly 90's Influenced by the language ABC, Modula-3, C, C++, Algol-68, SmallTalk, and U...

AST06 - Astronomical Programming I (Python) Introduction What is Python? Python is a high-level, interpreted, interactive and object-oriented scripting language. Created by Guido van Rossum in nearly 90's Influenced by the language ABC, Modula-3, C, C++, Algol-68, SmallTalk, and Unix shell and other scripting languages Python was conceived in the late 1980s and its implementation was started in December 1989 Guido Van Rossum is a fan of 'Monty Python's Flying Circus, this is a famous TV show in the Netherlands Named after Monty Python Open-sourced from the beginning Why was Python created in the first place? The original motivation for creating Python was the perceived need for a higher level language in the Amoeba [Operating Systems] project. Guido van Rossum realized that the development of system administration utilities in C was taking too long. Moreover, doing these things in the Bourne shell wouldn't work for a variety of reasons. There was a need for a language that would bridge the gap. Installing Python GUI It is pre-installed on most Unix systems, including Linux and MAC OS X, but for Windows Operating Systems user can download from the https://www.python.org/downloads/. IDEs or Platforms you can download and install, or whichever you prefer: Anaconda (Platform for Python Data Science): https://www.anaconda.com/products/individual Miniconda: https://docs.conda.io/en/latest/miniconda.html PyCharm: https://www.jetbrains.com/pycharm/download/#section=windows Spyder: https://www.spyder-ide.org For Linux installation of Python3: https://docs.python-guide.org/starting/install3/linux/ Coding Apps For Android 1. DataCamp 2. SoloLearn 3. Mimo 4. Grasshopper Overview of Data Visualization Computational Packages in Python SciPy It is an open-source library used for solving mathematical, scientific, engineering, and technical problems. It allows users to manipulate the data and visualize the data using a wide range of high-level Python commands. SciPy is built on the Python NumPy extension. SciPy is also pronounced as "Sigh Pi." Python commands are built on extensions. NumPy It is a fundamental package for scientific computing in Python. It is a Python library that provides a multidimensional array object, various derived objects (such as masked arrays and matrices), and an assortment of routines for fast operations on arrays, including mathematical, logical, shape manipulation, sorting, selecting, I/O, discrete Fourier transforms, basic linear algebra, basic statistical operations, random simulation Natural Language Natural language processing (NLP) is about developing applications and services that are able to understand human languages. Some Practical examples of NLP are speech recognition for eg: google voice search, understanding what the content is about or sentiment analysis. Libraries for Natural Language Program: Statsmodel - a Python module that provides classes and functions for the estimation of many different statistical models, as well as for conducting statistical tests, and statistical data exploration. Spacy - Built using Python and Cython Gensim - memory-independent implementation capabilities for several popular algorithms such as Latent Dirichlet Allocation (LDA), Random Projections (RP), Latent Semantic Analysis (LSA/LSI/LVD) and Hierarchical Dirichlet Process (HDP). Gensim is the NumPy and Scipy packages for getting it to work Google Colab Modules **can be viewed using your institutional email** **make a copy of the file if you want to edit** Python Computational Packages https://drive.google.com/file/d/14rATLMV9Zb20BsQHBWmJz3lkK9EIFGHZ/view?usp=sharing Module 2 and 3 - Some Basic Python Commands https://drive.google.com/file/d/1nK8-fkovRopx9TYFLjT8YetyStMQfQ1W/view?usp=sharing Module 4 - List Methods and Functions https://drive.google.com/file/d/1IbwUwEhXV1MUIydXzbmES9RhlNt0U5Wv/view?usp=sharing Module 5 - Python Conditions and Switch Statements https://drive.google.com/file/d/1_qpk8yRtPgj9PVcPHAN7bCGQFKTpj52f/view?usp=sharing Module 6 - Python Loops https://drive.google.com/file/d/1f57c2qcaPc-TEcQay8nt9b592GmDj6V-/view?usp=sharing Module 7 - Reading and Writing Files https://drive.google.com/file/d/1xXlrhruXOLCiQCYBPQ5vbOI1GxvlGGCi/view?usp=sharing Module 8 - Data Visualization https://drive.google.com/file/d/1EyhDttSR8cfNYSsBpfP-CV7fU1YPODR_/view?usp=sharing Module 9 - Python Computational Packages https://drive.google.com/file/d/14rATLMV9Zb20BsQHBWmJz3lkK9EIFGHZ/view?usp=sharing