Mastering the Tidyverse: 23 Advanced Techniques for Effective Data Wrangling

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The Tidyverse is a collection of R packages designed for data science that share a common philosophy and grammar, making it easier to learn and use them together. Key packages in the Tidyverse include dplyr, ggplot2, tidyr, purrr, and others.

I. Advanced Data Cleaning with tidyr:

1. Handling missing data with complete() and drop_na().

library(tidyr)

# Complete missing combinations of variables
complete(df, group_var1, group_var2)

# Drop rows with missing values
df %>%
  drop_na()

2. Advanced pivoting and gathering with pivot_longer() and pivot_wider().

library(tidyr)

# Pivot longer with multiple columns
pivot_longer(df, cols = starts_with("value"), names_to = "variable", values_to = "value")

# Pivot wider with multiple columns
pivot_wider(df_long, names_from = "variable", values_from = "value")

II. Advanced Data Transformation with dplyr:

3. Window functions for advanced grouping and summarization.

library(dplyr)

# Calculate rolling mean using window…