100% Off Udemy Course Coupon Code Data Manipulation With Dplyr in R Course Free: A straightforward tutorial in data wrangling with one of the most powerful R packages – dplyr. As a data analyst, you will spend a vast amount of your time preparing or processing your data. The goal of data preparation is to convert your raw data into a high-quality data source, suitable for analysis. Udemy free online courses with certificates. More often than not, this process involves a lot of work. The dplyr package contains the tools that can make this work much easier. The first section covers the five core dplyr commands. These commands are: filter, select, mutate, arrange, and summarise. You will need these commands practically every time when you work with dplyr.
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They are used to subset data frames, compute new variables, sort data frames, compute statistical indicators, and so on. The fourth section is about joining data frames with dplyr. This is a very important topic because many times your data will be found in several data frames. So you will need to join these data frames into only one, suitable for your analyses. We are going to look at five join types available in dplyr: inner_join, semi_join, left_join, anti_join, and full_join. We are going to examine the output of each join type using a simple example.
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Learn About:
- Filter data frames using various conditions
- Select and remove data frame columns (variables)
- Sort data frames by column values
- Create new variables from the existing ones
- Compute summary statistics for our data frame
- Other useful operations (count data fame rows, select top rows, select rows at random, etc.)
- Chaining dplyr commands to write powerful data manipulation code
- Joining data frames (five joining types)
- Combining dplyr with ggplot2 to create meaningful charts
Requirements:
- Basic R programming knowledge
