To calculate summary statistics in R, you can use two different function in R.

The following methods show how you can do it with syntax.

**Method 1: Use summary() Function**

```
summary(data)
```

**Method 2: Use summarize() Function from dplyr Package**

```
library(dplyr)
summary <- df %>%
summarize(
Mean = mean(colum1),
Median = median(colum1),
Min = min(colum1),
Max = max(colum1),
StdDev = sd(colum1),
Variance = var(colum1),
)
```

The following examples show how use this methods to calculate summary statistics in R.

## Use summary() Function

Let’s see how we can use **summary()** function to calculate summary statistics of dataframe.

```
# Create dataframe
df <- data.frame(Start_date=as.Date(c("2000-05-21","2000-05-22","2000-05-23","2000-05-24","2000-05-25","2000-05-26")),
Machine_name = c("Machine1","Machine2","Machine1","Machine3","Machine2","Machine3"),
Value = c(108,120,135,95,98,105),Reading= c(110,97,91,89,80,85))
# Calculate summary statistics of dataframe
d <- summary(df)
# Show summary statistics of dataframe
print(d)
```

Output:

```
Start_date Machine_name Value Reading
Min. :2000-05-21 Length:6 Min. : 95.00 Min. : 80.0
1st Qu.:2000-05-22 Class :character 1st Qu.: 99.75 1st Qu.: 86.0
Median :2000-05-23 Mode :character Median :106.50 Median : 90.0
Mean :2000-05-23 Mean :110.17 Mean : 92.0
3rd Qu.:2000-05-24 3rd Qu.:117.00 3rd Qu.: 95.5
Max. :2000-05-26 Max. :135.00 Max. :110.0
```

Here the output shows summary statistics of numeric columns of dataframe.

## Use summarize() Function from dplyr

Let’s see how we can use **summarize()** function from **dplyr** package to calculate summary statistics:

```
# Import library
library(dplyr)
# Create dataframe
df <- data.frame(Start_date=as.Date(c("2000-05-21","2000-05-22","2000-05-23","2000-05-24","2000-05-25","2000-05-26")),
Machine_name = c("Machine1","Machine2","Machine1","Machine3","Machine2","Machine3"),
Value = c(108,120,135,95,98,105),Reading= c(110,97,91,89,80,85))
# Get statistical values
summary_reading <- df %>%
summarize(
Mean_reading = mean(Reading),
Median_reading = median(Reading),
Min_reading = min(Reading),
Max_reading = max(Reading),
StdDev_reading = sd(Reading),
Variance_reading = var(Reading),
)
# Print statistical values
print(summary_reading)
```

Output:

```
Mean_reading Median_reading Min_reading Max_reading StdDev_reading Variance_reading
1 92 90 80 110 10.50714 110.4
```

As the output shows statistics values for **Reading** column of dataframe.