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After learning this set of Python data analysis tutorial, I am stable in the big factory!

編輯:Python

Preface

Gold three silver four job hopping season , What position is the most popular ?

have a look byte 、 tencent Such as the salary offered by big manufacturers to their own data analysts , You know how hot this position is .

The salary of data analysts is so high , Is it really because it's difficult to do data analysis ? Of course not. ! Compared to writing code , The skill threshold for data analysts is much lower , Even if you only need to be proficient in a few analysis tools , You can get to the big factory offer. For example, others make a visual chart and hold it for a long time , And you use Tableau In a few minutes ; Others analyze website data , The results of half a day's analysis may not be accurate , And you use Python Issue a professional report quickly ; Data that others haven't queried for hours , Do you use SQL In a few seconds, the execution is complete .

How to analyze zero basic learning data ?

This is also one of the most concerned issues that many people want to switch to data analysis , For zero based people who want to change careers in data analysis , There is a certain degree of difficulty , But it's not impossible .

Today, , Big data has been extended to all walks of life , The demand for talents in the field of big data has increased significantly , High pay , Good treatment , Attracted a lot of people , Among them, big data analysis , Is a very good choice , So what skills do you need to engage in big data analysis ?

The abilities required for data analysis are

1、 The data processing 、 Data processing

2、 Business translation 、 Is to put the business needs 、 Business objectives are translated into data modeling methods

3、 programing language 、 master SQL、python、SAS、R, etc.

The books I want to share with you here are 《Python Basic course of data analysis :NumPy Learning Guide ( The first 2 edition )》, According to Xiaobian for many years python Development experience , This book is the first choice for zero basic introduction data analysis .

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The book is NumPy Getting started with , This paper mainly introduces NumPy And related Python Scientific Computing Library , Such as SciPy and Matplotlib.《Python Basic course of data analysis :NumPy Learning Guide ( The first 2 edition )》 Content covered NumPy install 、 Array objects 、 Common functions 、 Matrix operations 、 linear algebra 、 Financial functions 、 Window function 、 The quality control 、Matplotlib mapping 、SciPy Introduction and Pygame The content such as , It covers a wide range . in addition ,Ivan Idris A brief and clear example is given for each knowledge point , And give a practical scenario for most of the examples ( Such as stock data analysis ), While helping beginners get started , It improves the readability of the book .

The reason why it is recommended is that the book is based on actual combat and supplemented by theory . Start with a very simple concept , Gradually integrate various examples of hands-on practice .

Don't talk much , Show it directly :

The first 1 Chapter NumPy Quick start

  • Python
  • Hands-on practice : Install... On different operating systems Python
  • Windows
  • Hands-on practice : stay Windows Installation on NumPy、Matplotlib、 SciPy and IPython
  • Linux
  • Hands-on practice : stay Linux Installation on NumPy、Matplotlib、SciPy and IPython

The first 2 Chapter NumPy Basics

  • NumPy Array objects
  • Hands-on practice : Create multidimensional arrays
  • Hands-on practice : Create custom data type
  • Index and slice of one-dimensional array
  • Hands-on practice : Slicing and indexing of multidimensional arrays

The first 3 Chapter Common functions

  • File read and write
  • Hands-on practice : Read and write files
  • CSV file
  • Hands-on practice : Read in CSV
  • Volume weighted average price (VWAP)

The first 4 Chapter Convenient functions

  • The correlation
  • Hands-on practice : Stock correlation analysis
  • Hands-on practice : Polynomial fitting
  • Net volume
  • Hands-on practice : Calculation OBV

The first 5 Chapter Matrices and general functions

  • matrix
  • Hands-on practice : Create a matrix
  • Create a new matrix from an existing matrix
  • Hands-on practice : Create a new matrix from an existing matrix
  • The generic function
  • Hands-on practice : Create generic functions

The first 6 Chapter Learn more NumPy modular

  • linear algebra
  • Hands-on practice : Calculate the inverse matrix
  • Solve linear equations
  • Hands-on practice : Solve linear equations
  • Eigenvalues and eigenvectors
  • Hands-on practice : Solve eigenvalues and eigenvectors

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The first 7 Chapter Special functions

  • Sort
  • Hands-on practice : Sort by dictionary order
  • The plural
  • Hands-on practice : Sort complex numbers
  • Search for
  • Hands-on practice : Use searchsorted function

The first 8 Chapter The quality control

  • Assertion function
  • Hands-on practice : Use assert_almost_equal Assert approximate equality
  • Approximately equal
  • Hands-on practice : Use assert_approx_equal Assert approximate equality
  • Approximate equality of arrays
  • Hands-on practice : Assert that arrays are approximately equal

The first 9 Chapter Use Matplotlib mapping

  • Simple drawing
  • Hands-on practice : Draw polynomial function
  • Format string
  • Hands-on practice : Drawing polynomial function and its derivative
  • Subgraphs
  • Hands-on practice : Drawing polynomial function and its derivative

The first 10 Chapter NumPy An extension of :SciPy

  • MATLAB and Octave
  • Hands-on practice : Save and load .mat file
  • Statistics
  • Hands-on practice : Analyze random numbers
  • Sample comparison and SciKits
  • Hands-on practice : Comparative stock log return
  • signal processing

The first 11 Chapter Get along well with Pygame

  • Pygame
  • Hands-on practice : install Pygame
  • Hello World
  • Hands-on practice : Make simple games
  • Animation
  • Hands-on practice : Use NumPy and Pygame Making animated objects

Because the space is limited , I don't want to show them all here , If you need a friend, you can Click here Free collection !.

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