# How to Group Data by Month in R (With Example)

You can use the floor_date() function from the lubridate package in R to quickly group data by month.

This function uses the following basic syntax:

```library(tidyverse)

df %>%
group_by(month = lubridate::floor_date(date_column, 'month')) %>%
summarize(sum = sum(value_column))```

The following example shows how to use this function in practice.

### Example: Group Data by Month in R

Suppose we have the following data frame in R that shows the total sales of some item on various dates:

```#create data frame
df <- data.frame(date=as.Date(c('1/4/2022', '1/9/2022', '2/10/2022', '2/15/2022',
'3/5/2022', '3/22/2022', '3/27/2022'), '%m/%d/%Y'),
sales=c(8, 14, 22, 23, 16, 17, 23))

#view data frame
df

date sales
1 2022-01-04     8
2 2022-01-09    14
3 2022-02-10    22
4 2022-02-15    23
5 2022-03-05    16
6 2022-03-22    17
7 2022-03-27    23```

We can use the following code to calculate the sum of sales, grouped by month:

```library(tidyverse)

#group data by month and sum sales
df %>%
group_by(month = lubridate::floor_date(date, 'month')) %>%
summarize(sum_of_sales = sum(sales))

# A tibble: 3 x 2
month      sum_of_sales

1 2022-01-01           22
2 2022-02-01           45
3 2022-03-01           56
```

From the output we can see:

• A total of 22 sales were made in January.
• A total of 45 sales were made in February.
• A total of 56 sales were made in March.

We can also aggregate the data using some other metric.

For example, we could calculate the max sales made in one day, grouped by month:

```library(tidyverse)

#group data by month and find max sales
df %>%
group_by(month = lubridate::floor_date(date, 'month')) %>%
summarize(max_of_sales = max(sales))

# A tibble: 3 x 2
month      max_of_sales

1 2022-01-01           14
2 2022-02-01           23
3 2022-03-01           23
```

From the output we can see:

• The max sales made in one day in January was 14.
• The max sales made in one day in February was 23.
• The max sales made in one day in March was 23.

Feel free to use whatever metric you’d like within the summarize() function.