# Median function in R – median()

Median function in R – median() calculates the sample median. The median is the value at the middle when the data is sorted in ascending order. Median of a group can also calculated using median() function in R by providing it inside the aggregate function. with median() function we can also find row wise median using dplyr package and also column wise median lets see an example of each.

• Median of the list of vector elements with NA values
• Median of a particular column of the dataframe in R
• column wise median of the dataframe using median() function
• Median of the group in R dataframe using aggregate() and dplyr package
• Row wise median of the dataframe in R using median() function

#### Syntax for median function in R:

median(x, na.rm = FALSE, …)
• x – numeric vector
• rm- whether NA should be removed, if not, NA will be returned

#### Example of Median function in R with odd observation:

```# R median function with 7(odd) observation

x <-c(1.234,2.342,3.4,-4.562,5.671,12.345,-14.567)
median(x)
```

There are 7 observations in above examples. When arranged in ascending order 4th value is the median value so the output will be

 2.342

#### Example of Median function in R with even observation:

```# R median function with 6(even) observation

x <-c(1.234,2.342,-4.562,5.671,12.345,-14.567)
median(x)
```

There are 6 observations in above example. So the median will be average of 3rd and 4th value when arranged in ascending order. So the output will be (1.234+2.342)/2

##### output:
 1.788

Example of Median function with NA:

Median function doesn’t give desired output, If NAs are present in the vector. so it has to be handled by using na.rm=TRUE in median() function

```# R median function for input vector which has NA.

x <-c(1.234,2.342,-4.562,5.671,12.345,-14.567,NA)
median(x,na.rm=TRUE)
```
 1.788

#### Example of median() function in R dataframe:

Lets create the data frame to demonstrate median function – median() in r

```### create the dataframe
Price = c(100,80,80,90,65,70,60,70,25,60,40,35,50,120),
MRP = c(101,85,85,96,67,73,65,71,33,64,45,36,54,123))
```

so the resultant dataframe will be #### Median of a column in R data frame using median() function : median() function takes the column name as argument and finds the median of that particular column

```# median() function in R : median of a column in data frame

```

so the resultant median of “Price” column will be

output:

 67.5

#### column wise median using median() function:

median() function is applied to the required column through mapply() function, so that it  calculates the meidan of required column as shown below.

```
# median() function in R : median of multiple column in data frame

```

so the resultant median of “Price” and “MRP” columns will be #### Median of the column by group using median() function

aggregate() function along with the median() function calculates the median of a group. here median of “Price” column, for “Item_Group” is calculated.

```##### Median of the column by group
FUN=median)
```

Item_group has three groups “Dairy”,”Fruit” & “Vegetable”. median of price for each group is calculated as shown below #### median of the column by group  and populate it by using median() function:

group_by() function along with the median() function calculates the median of a group. here median of “Price” column, for “Item_Group” is calculated and populated across as shown below

```#### median of the column by group and populate it using dplyr

library(dplyr)

group_by(ITEM_GROUP) %>%
mutate(median_by_group = median(Price))
```

Item_group has three groups “Dairy”,”Fruit” & “Vegetable”. median of price for each group is calculated and populated as shown below #### Row wise median using median() function along with dplyr

Row wise median is calculated with the help rowwise() function of dplyr package  and median() function as shown below

```## row wise median using dplyr
library(dplyr)

rowwise() %>%
mutate(
Median_price = median(c(Price,MRP))
)
```

row wise median of “Price” and “MRP” is calculated and  populated for each row as shown below For further understanding of median() function in R using dplyr one can refer the dplyr documentation

## Author

• With close to 10 years on Experience in data science and machine learning Have extensively worked on programming languages like R, Python (Pandas), SAS, Pyspark.