In this post, we will learn how to use dplyr’s rows_update() function with examples. dplyr’s rows_update() function is a useful function to modify or update specific rows in a data frame based on a matching values in key column. It takes in two dataframes x and y, updates existing rows in the target data frame… Continue reading dplyr rows_update(): Modify existing rows
Category: dplyr
dplyr n_distinct(): count unique elements or rows
In this post, we will learn how to use dplyr’s n_distinct() function to count the number of unique or distinct values in one or more vectors or columns of a dataframe. dplyr’s n_distinct() is very useful when you are working with a dataframe and need to know how many unique or distinct values or combinatons… Continue reading dplyr n_distinct(): count unique elements or rows
How to select top and bottom rows by a column simultaneously
In this tutorial, we will learn how to select top and bottom rows of a dataframe based on the values of a column with tidyverse in R. Here we will see a specific approach to get top and bottom rows when the values of the column of interest has both positive and negative values. This… Continue reading How to select top and bottom rows by a column simultaneously
How to convert a list to a dataframe
In this tutorial, we will learn 3 different ways to convert a list object into a dataframe in R. First we will show how to use the base R function as.data.frame() to convert a list to a dataframe. Then we will show examples using map_df() function in purrr package in tidyverse and bind_rows() function in… Continue reading How to convert a list to a dataframe
dplyr’s anti_join() to find rows based on presence or absence in a dataframe
In this tutorial, we will learn how to use dplyr’s anti_join() function to filter rows from one dataframe based on the presence or absence of matches in another dataframe. dplyr’s anti_join() function is extremely useful for cases when we want to find what row is present or missing in a dataframe when compared to another… Continue reading dplyr’s anti_join() to find rows based on presence or absence in a dataframe