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Book
A python data analyst's toolkit : learn python and python-based libraries with applications in data analysis and statistics
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ISBN: 9781484263990 9781484264003 9781484263983 Year: 2020 Publisher: Apress

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Abstract

Explore the fundamentals of data analysis, and statistics with case studies using Python. This book will show you how to confidently write code in Python, and use various Python libraries and functions for analyzing any dataset. The code is presented in Jupyter notebooks that can further be adapted and extended.This book is divided into three parts - programming with Python, data analysis and visualization, and statistics. You'll start with an introduction to Python - the syntax, functions, conditional statements, data types, and different types of containers. You'll then review more advanced concepts like regular expressions, handling of files, and solving mathematical problems with Python.The second part of the book, will cover Python libraries used for data analysis. There will be an introductory chapter covering basic concepts and terminology, and one chapter each on NumPy(the scientific computation library), Pandas (the data wrangling library) and visualization libraries like Matplotlib and Seaborn. Case studies will be included as examples to help readers understand some real-world applications of data analysis.The final chapters of book focus on statistics, elucidating important principles in statistics that are relevant to data science. These topics include probability, Bayes theorem, permutations and combinations, and hypothesis testing (ANOVA, Chi-squared test, z-test, and t-test), and how the Scipy library enables simplification of tedious calculations involved in statistics.What You'll Learn:Further your programming and analytical skills with PythonSolve mathematical problems in calculus, and set theory and algebra with PythonWork with various libraries in Python to structure, analyze, and visualize dataTackle real-life case studies using PythonReview essential statistical concepts and use the Scipy library to solve problems in statisticsWho This Book Is For:Professionals working in the field of data science interested in enhancing skills in Python, data analysis and statistics.bron : https://www.standaardboekhandel.be/p/a-python-data-analysts-toolkit-9781484263983


Book
Python 3 Text Processing with NLTK 3 Cookbook
Author:
ISBN: 1782167862 9781782167860 1782167854 9781782167853 9781782167853 Year: 2014 Publisher: Birmingham Packt Publishing Ltd

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Over 80 practical recipes on natural language processing techniques using Python's NLTK 3.0 In Detail This book will show you the essential techniques of text and language processing. Starting with tokenization, stemming, and the WordNet dictionary, you'll progress to part-of-speech tagging, phrase chunking, and named entity recognition. You'll learn how various text corpora are organized, as well as how to create your own custom corpus. Then, you'll move onto text classification with a focus on sentiment analysis. And because NLP can be computationally expensive on large bodies of text, you'll try a few methods for distributed text processing. Finally, you'll be introduced to a number of other small but complementary Python libraries for text analysis, cleaning, and parsing. This cookbook provides simple, straightforward examples so you can quickly learn text processing with Python and NLTK. What You Will Learn Tokenize text into sentences, and sentences into words Look up words in the WordNet dictionary Apply spelling correction and word replacement Access the built-in text corpora and create your own custom corpus Tag words with parts of speech Chunk phrases and recognize named entities Grammatically transform phrases and chunks Classify text and perform sentiment analysis


Book
Mastering Python Regular Expressions
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ISBN: 1783283165 9781783283163 9781783283156 1783283157 Year: 2014 Publisher: Birmingham Packt Publishing Ltd

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A short and straight to the point guide that explains the implementation of Regular Expressions in Python.This book is aimed at Python developers who want to learn how to leverage Regular Expressions in Python. Basic knowledge of Python is required for a better understanding.

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