Data Manipulation with pandas
Use the world’s most popular Python data science package to manipulate data and calculate summary statistics.
Curriculum Architect at DataCamp
Richie runs the Content Quality team at DataCamp. He has been using R since 2004, in the fields of proteomics, debt collection, and chemical health and safety. He has released almost 30 R packages on CRAN and Bioconductor – most famously the assertive suite of packages – as well as creating and contributing to many others. He also has written two books on R programming, Learning R and Testing R Code.
Use the world’s most popular Python data science package to manipulate data and calculate summary statistics.
An introduction to data visualization with no coding involved.
Master sampling to get more accurate statistics with less data.
Expand your spreadsheets vocabulary by diving deeper into data types, including numeric data, logical data, and missing data.
Take your R skills up a notch by learning to write efficient, reusable functions.
Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regression analysis in R.
Learn how and when to use common hypothesis tests like t-tests, proportion tests, and chi-square tests.
Manage the complexity in your code using object-oriented programming with the S3 and R6 systems.
Learn how to analyze huge datasets using Apache Spark and R using the sparklyr package.
Learn to perform linear and logistic regression with multiple explanatory variables.
Write functions to forecast time series of food prices in Rwanda.
Visualize the rise of COVID-19 cases globally with ggplot2.
Write functions to forecast time series of food prices in Rwanda.
Use SQL data manipulation and joins to discover the oldest businesses around the world.