Data Wrangling Essentials Exercise Solutions in Python
Preface
1
Programming
1.1
Programming basics
1.2
Functions, Packges, and Getting help
2
Data frames
2.1
Data frames
2.2
Reading csv files and other delimited data
2.3
More challenging csv and deliminated files
3
Visual Exploration of data
3.1
Preparatory exercises
3.2
Relationship between two continuous variables
3.3
Relationships between continuous and categorical variables
3.4
Relationship between more than two variables
4
Cleaning
4.1
Preparatory exercises
4.2
Naming variables
4.3
Copying data sets
4.4
Dropping unneeded variables
4.5
Dropping unneeded observations
4.6
Subsets of a data frame
4.7
Coding missing values
4.8
Coding missing values - part 2
4.9
Duplicate observations
5
Transforming variables
5.1
Preparatory exercises
5.2
Character variables
5.3
Numeric variables
5.4
Factors and Indicators
5.5
Date and time variables
5.6
Related observations
5.7
Relationships between columns
6
Transforming variables
6.1
Preparatory exercises
6.2
Tidy data
6.3
Aggregating data
Data Wrangling Essentials - Exercise Solutions in Python
Supporting Statistical Analysis for Research
2
Data frames
Supporting Statistical Analysis for Research