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Learn R Programming Tips & Tricks for Statistics and Data Science

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dplyr select()

How to remove columns with all NAs

rstats101 · October 14, 2022 ·

Learn to remove columns with all NAs using two approaches

In this tutorial, we will learn how to drop columns with values that are all NAs. We will use two approaches to remove columns with all NAs. First, we will use tidyverse approach, where we perform column-wise operation to see all values are NAs and select columns that are not all … [Read more...] about How to remove columns with all NAs

Filed Under: apply(), dplyr select() Tagged With: remove columns with all NAs

How to select one or more columns from a dataframe

rstats101 · May 20, 2022 ·

In this tutorial we will learn how to select one or more columns/variables from a data frame in R. We first learn how to select the columns of interest with dplyr's select() function by using their name and then we will learn how to select columns using base R approach. Let … [Read more...] about How to select one or more columns from a dataframe

Filed Under: dplyr, dplyr select() Tagged With: select columns base R, select columns tidyverse

How to select only numeric columns in a dataframe

rstats101 · May 12, 2022 ·

How to select all numerical columns from a dataframe

In this tutorial, we will learn how to select the columns that are numeric from a dataframe containing columns of different datatype. We will use dplyr's select() function in combination with where() and is.numeric() functions to select the numeric columns. Let us first load … [Read more...] about How to select only numeric columns in a dataframe

Filed Under: dplyr select() Tagged With: select numerical columns dplyr

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%in% arrange() as.data.frame as_tibble built-in data R colSums() R cor() in R data.frame dplyr dplyr across() dplyr group_by() dplyr rename() dplyr rowwise() dplyr row_number() dplyr select() dplyr slice_max() dplyr slice_sample() drop_na R duplicated() gsub head() impute with mean values is.element() linear regression matrix() function na.omit R NAs in R near() R openxlsx pivot_longer() prod() R.version replace NA replace NAs tidyverse R Function rstats rstats101 R version scale() sessionInfo() t.test() tidyr tidyselect tidyverse write.xlsx

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