Removing Missing values in R-Quick Guide
Removing Missing values in R, To return values in R that are not NA values, use the following syntax.
Removing Missing values in R
Only values that aren’t NA are returned.
x <- x[!is.na(x)]
The examples below demonstrate how to utilize this syntax in R with both vectors and data frames.
Line types in R: Ultimate Guide For R Baseplot and ggplot » finnstats
Approach 1: Return Values in a Vector That Aren’t NA
The code below shows how to return non-NA values from a vector.
make a vector first,
x <- c(139, 254, 456,NA, 46, NA, 79,NA)
To return only values that are not NA
x <- x[!is.na(x)] x
[1] 139 254 456 46 79
Approach 2: Return Rows that are Not NA in One Column of Data Frame
The code below explains how to get the rows in a data frame that don’t have a NA value in a certain column.
Feature Scaling in Machine Learning-Introduction » finnstats
create a data frame
df <- data.frame(team=c('Q1', 'Q2', 'Q3', 'Q4', 'Q5'),
kick=c(13, NA, 31, 32, 14),
pass=c(32, NA, NA, 34, 35))
dfteam kick pass 1 Q1 13 32 2 Q2 NA NA 3 Q3 31 NA 4 Q4 32 34 5 Q5 14 35
Rows containing NA in the ‘pass’ column should be removed.
df <- df[!(is.na(df$pass)), ] df
Now we can view the data frame
team kick pass 1 Q1 13 32 4 Q4 32 34 5 Q5 14 35
Approach 3: Return Rows that are Not NA in Several Columns
The code below explains how to return the rows in a data frame that do not have a NA value in one of the multiple columns.
Introduction to Deep Learning » finnstats
set up a data frame first,
df <- data.frame(team=c('Q1', 'Q2', 'Q3', 'Q4', 'Q5'),
kick=c(13, NA, 31, 32, 14),
pass=c(32, NA, NA, 34, 35))
dfview the data frame
team kick pass 1 Q1 13 32 2 Q2 NA NA 3 Q3 31 NA 4 Q4 32 34 5 Q5 14 35
Let’s remove rows with NA in the kick and pass column
df <- df[!(is.na(df$kick)) & !(is.na(df$pass)), ]
Yes, view the data frame
df
team kick pass 1 Q1 13 32 4 Q4 32 34 5 Q5 14 35
Approach 4: Return Rows that are Not NA in Any Column
The following code returns the rows in a data frame that have no NA value in any column.
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Start with data frame
df <- data.frame(team=c('Q1', NA, 'Q3', 'Q4', 'Q5'),
kick=c(13, NA, 31, 32, 14),
pass=c(32, NA, NA, 34, 35))
dfteam kick pass 1 Q1 13 32 2 <NA> NA NA 3 Q3 31 NA 4 Q4 32 34 5 Q5 14 35
Now remove rows with NA in any column
df <- na.omit(df) df
team kick pass 1 Q1 13 32 4 Q4 32 34 5 Q5 14 35
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