Ch. 1 - Ticket Sales Data

Importing the data

Examining the data

Summarizing the data

Removing redundant info

Information not worth keeping

Separating columns

Dealing with warnings

Identifying dates

More warnings!

Combining columns

Ch. 2 - MBTA Ridership Data

Using readxl

Examining the data

Removing unnecessary rows and columns

Observations are stored in columns

Type conversions

Variables are stored in both rows and columns

Separating columns

Do your values seem reasonable?

Dealing with entry error

Ch. 3 - World Food Facts

Importing the data

Examining the data

Inspecting variables

Removing duplicate info

Removing useless info

Finding columns

Replacing missing values

Dealing with messy data

Ch. 4 - School Attendance Data

Importing the data

Examining the data

Removing unnecessary rows

Removing useless columns

Splitting the data

Replacing the names

Cleaning up extra characters

Some final type conversions

About Michael Mallari

Michael is a hybrid thinker and doer—a byproduct of being a StrengthsFinder “Learner” over time. With nearly 20 years of engineering, design, and product experience, he helps organizations identify market needs, mobilize internal and external resources, and deliver delightful digital customer experiences that align with business goals. He has been entrusted with problem-solving for brands—ranging from Fortune 500 companies to early-stage startups to not-for-profit organizations.

Michael earned his BS in Computer Science from New York Institute of Technology and his MBA from the University of Maryland, College Park. He is also a candidate to receive his MS in Applied Analytics from Columbia University.

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