## 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.

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