Selecting rows
Selecting a combination of rows and columns
Creating new columns
Generating random numbers and their usage
Various methods for generating random numbers
Seeding a random number
Generating random numbers following probability distributions
Probability density function
Cumulative density function
Uniform distribution
Normal distribution
Using the Monte-Carlo simulation to find the value of pi
Geometry and mathematics behind the calculation of pi
Generating a dummy data frame
Grouping the data – aggregation, filtering, and transformation
Aggregation
Filtering
Transformation
Miscellaneous operations
Random sampling – splitting a dataset in training and testing datasets
Method 1 – using the Customer Churn Model
Method 2 – using sklearn
Method 3 – using the shuffle function
Concatenating and appending data
Merging/joining datasets
Inner Join
Left Join
Right Join
An example of the Inner Join
An example of the Left Join
An example of the Right Join
Summary of Joins in terms of their length
Summary
4. Statistical Concepts for Predictive Modelling
Random sampling and the central limit theorem
Hypothesis testing
Null versus alternate hypothesis
Z-statistic and t-statistic
Confidence intervals, significance levels, and p-values
Different kinds of hypothesis test
A step-by-step guide to do a hypothesis test
An example of a hypothesis test
Chi-square tests
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