/data-analysis

Follow along of the book Python Data Analysis (Third Edition)

Primary LanguageJupyter Notebook

Chapter 1

Installation of python, anaconda. Difference between data analyst and data scientist and the various technologies/domain they work with.

Chapter 2

1. Numpy

  • Creating array
  • Array Data Types
  • Manipulating array shapes
  • Stacking of numpy arrays
  • Partioning numpy arrays
  • Numpy views and copies
  • Slicing and Indexing
  • Broadcasting Arrays

2. Pandas

  • Creating dataframes
  • Creating series
  • Reading data using Quandl
  • Grouping and joining in Dataframes
  • Working with missing values
  • Creating pivot tables
  • Dealing with dates

Chapter 3

Statistics

  • Types of attributes
  • Measuring central tendency
  • Measuring dispersion
  • Skewness and kurtosis
  • Covariance and correlation
  • Parametric and non-parametric tests