Elements of Structured Data

• Most common forms of structured data is a table with rows and columns.
• There are two basic types of structured data
  • Numerical: Comes in two forms
    • Continuous
    • Discrete
  • Categorical: Takes only a fixed set of values:
    • Examples:
      • Types of TV Screens (plasma, LED, LCD etc)
      • State Names (Telangana, Andhra Pradesh, Tamil Nadu, Karnataka, Kerala)
    • Binary data is an important special case of categorical value which takes one out two values (0/2, yes/no, true/false)
    • Another form of categorical data is ordinal data i.e. categories which are ordered
      • Example: Ratings (1/5, 2/5, 3/5, 4/5, 5/5)
        

Rectangular Data

• This is the general term for two-dimensional matirx with rows indicating records (cases) and columns indicating features (variables).
• Dataframe is the format which we generally use in python (pandas) and R
  

Estimates of Location

• Variables with measured or count data might have thousands of distinct values.
• A basic step in exploring your data is getting a typical value for each feature: an estimated of where most of the data is located (i.e its central tendency)
  
• Refer Here
• Exercise: Try to take a dataset from kaggle Refer Here to calculate mean, median, weighted mean of total with ratings as weight and trimmed mean with any trim percentage.