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Python: End-to-end Data Analysis
Python: End-to-end Data Analysis

Python: End-to-end Data Analysis: Leverage the power of Python to clean, scrape, analyze, and visualize your data

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Profile Icon Magnus Vilhelm Persson Profile Icon Phuong Vo.T.H Profile Icon Martin Czygan Profile Icon Luiz Felipe Martins Profile Icon Ivan Idris +1 more Show less
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Course May 2017 931 pages 1st Edition
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Profile Icon Magnus Vilhelm Persson Profile Icon Phuong Vo.T.H Profile Icon Martin Czygan Profile Icon Luiz Felipe Martins Profile Icon Ivan Idris +1 more Show less
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Course May 2017 931 pages 1st Edition

Key benefits

  • Clean, format, and explore your data using the popular Python libraries and get valuable insights from it
  • Analyze big data sets; create attractive visualizations; manipulate and process various data types using NumPy, SciPy, and matplotlib; and more
  • Packed with easy-to-follow examples to develop advanced computational skills for the analysis of complex data

Description

Data analysis is the process of applying logical and analytical reasoning to study each component of data present in the system. Python is a multi-domain, high-level, programming language that offers a range of tools and libraries suitable for all purposes, it has slowly evolved as one of the primary languages for data science. Have you ever imagined becoming an expert at effectively approaching data analysis problems, solving them, and extracting all of the available information from your data? If yes, look no further, this is the course you need! In this course, we will get you started with Python data analysis by introducing the basics of data analysis and supported Python libraries such as matplotlib, NumPy, and pandas. Create visualizations by choosing color maps, different shapes, sizes, and palettes then delve into statistical data analysis using distribution algorithms and correlations. You’ll then find your way around different data and numerical problems, get to grips with Spark and HDFS, and set up migration scripts for web mining. You’ll be able to quickly and accurately perform hands-on sorting, reduction, and subsequent analysis, and fully appreciate how data analysis methods can support business decision-making. Finally, you will delve into advanced techniques such as performing regression, quantifying cause and effect using Bayesian methods, and discovering how to use Python’s tools for supervised machine learning. The course provides you with highly practical content explaining data analysis with Python, from the following Packt books: 1. Getting Started with Python Data Analysis. 2. Python Data Analysis Cookbook. 3. Mastering Python Data Analysis. By the end of this course, you will have all the knowledge you need to analyze your data with varying complexity levels, and turn it into actionable insights.

Who is this book for?

This course is for developers, analysts, and data scientists who want to learn data analysis from scratch. This course will provide you with a solid foundation from which to analyze data with varying complexity. A working knowledge of Python (and a strong interest in playing with your data) is recommended.

What you will learn

  • Understand the importance of data analysis and master its processing steps
  • Get comfortable using Python and its associated data analysis libraries such as Pandas, NumPy, and SciPy
  • Clean and transform your data and apply advanced statistical analysis to create attractive visualizations
  • Analyze images and time series data
  • Mine text and analyze social networks
  • Perform web scraping and work with different databases, Hadoop, and Spark
  • Use statistical models to discover patterns in data
  • Detect similarities and differences in data with clustering
  • Work with Jupyter Notebook to produce publication-ready figures to be included in reports

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : May 31, 2017
Length: 931 pages
Edition : 1st
Language : English
ISBN-13 : 9781788394697
Category :
Languages :
Concepts :
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Product Details

Publication date : May 31, 2017
Length: 931 pages
Edition : 1st
Language : English
ISBN-13 : 9781788394697
Category :
Languages :
Concepts :
Tools :

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Table of Contents

5 Chapters
1. Module 1 Chevron down icon Chevron up icon
2. Module 2 Chevron down icon Chevron up icon
3. Module 3 Chevron down icon Chevron up icon
A. Bibliography Chevron down icon Chevron up icon
Index Chevron down icon Chevron up icon
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