Python Data Analysis and Visualization – Week Zero/Prepare for Data Analysis


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  • Numpy ndarray
  • Matplotlib pyplot
  • Pandas series DataFrame
  • Single data, single meaning.
  • A series of data, one or more meanings.
  • This is about to to understand the meaning of data.
  • Abstract:extract feature of data with some loss
    • Basic statics(including sort)
    • Distributed/accumulated statics
    • Data features
      • dependency, periodicity and so on
    • Data mining


  • Anaconada IDE(Integrated Development Environment)
  • conda Spyder IPython


  • Coordinate system
  • Pie chart
  • Histogram
  • Polar coordinate diagram
  • Scatter diagram
  • Project 1:Image with hand-painted effect
  • Project 2:Plot gravitational wave
  • Project 3:Analyse factors concerning housing price
  • Project 4:Trend curve of stock

Basic Usage of Anaconada IDE

  • Free, open source
  • Support 800 libraries
  • Includes many popular tools
  • Suitable for development of data computing
  • Cross platforms
  • Stem from conda
    • Package manage and environment manage
    • Similar to pip
    • Run python with different versions, switch versions flexibly
    • anaconda:One collection including conda、python、and a batch of libraries
  • Environment: root. we can create new conda environment
  • Coding and debugging:Spyder
  • anaconda3/bin/anaconda-navigator
  • spyder
  • Interactive programming environment:IPython
    • Suitable for data visualization and GUI applications
    • add ? after function or variable to get general info
    • %run to run .py file in an empty namespace
commands explanation
%magic show all commands
%hist show input history
%reset delete all variables or name
%who show all variables defined
%time statement show execution time of codes, statement means several lines of codes
%timeit statement run several times and calculate the mean time


  • Stem from conda, including translator-editor Spyder and interactive environment IPython

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