Data wrangling, is the process of importing, cleaning and transforming raw data into actionable information for analysis. It is a time-consuming process which is estimated to take about 60-80% of analyst’s time. In this series we will go through this process. It will be a brief series with goal to craft the reader’s skills on […]

# Exercises (intermediate)

## Working with air quality and meteorological data Exercises (Part-1)

Atmospheric air pollution is one of the most important environmental concerns in many countries around the world, and it is strongly affected by meteorological conditions. Accordingly, in this set of exercises we use openair package to work and analyze air quality and meteorological data. This packages provides tools to directly import data from air quality […]

## Sending Emails from R Exercises

When monitoring a data source, model, or other automated process, it’s convienent to have method for easily delivering performance metrics and notifying you whenever something is amiss. One option is to use a dashboard; however, this requires active time and effort to grab numbers and catch errors. An alternative approach is to send an email […]

## Hacking statistics or: How I Learned to Stop Worrying About Calculus and Love Stats Exercises (Part-6)

Statistics are often taught in school by and for people who like Mathematics. As a consequence, in those class emphasis is put on leaning equations, solving calculus problems and creating mathematics models instead of building an intuition for probabilistic problems. But, if you read this, you know a bit of R programming and have access […]

## More string Hacking with Regex and Rebus

For a begineer in R or any language,regular expression might seem like a daunting task . Rebus package in R gives a lowers the barrier for common regular expression tasks and is useful for a begineer or even for advanced users for most of the common regex skills in a more intuitive yet verbose way […]

## Soccer data sparring: Scraping, merging and analyzing exercises

While understanding and spending time improving specific techniques, and strengthening indvidual muscles is important, occasionally it is necessary to do some rounds of actual sparring to see your flow and spot weaknesses. This exercise set forces you to use all that you have practiced: to scrape links, download data, regular expressions, merge data and then […]

## Data wrangling : Transforming (3/3)

Data wrangling is a task of great importance in data analysis. Data wrangling, is the process of importing, cleaning and transforming raw data into actionable information for analysis. It is a time-consuming process which is estimated to take about 60-80% of analyst’s time. In this series we will go through this process. It will be […]

## Hacking statistics or: How I Learned to Stop Worrying About Calculus and Love Stats Exercises (Part-5)

Statistics are often taught in school by and for people who like Mathematics. As a consequence, in those class emphasis is put on leaning equations, solving calculus problems and creating mathematics models instead of building an intuition for probabilistic problems. But, if you read this, you know a bit of R programming and have access […]

## Hacking Strings with stringi

In the last set of exercises, we worked on the basic concepts of string manipulation with stringr. In this one we will go further into hacking strings universe and learn how to use stringi package.Note that stringi acts as a backend of stringr but have many more useful string manipulation functions compared to stringr and […]

## Data wrangling : Transforming (2/3)

Data wrangling is a task of great importance in data analysis. Data wrangling, is the process of importing, cleaning and transforming raw data into actionable information for analysis. It is a time-consuming process which is estimated to take about 60-80% of analyst’s time. In this series we will go through this process. It will be […]