Introduction
2. Function describe
Grouping
Summary

## Instruction

Good! Once we have created our DataFrame, we can use the describe() function:

players.describe()

For each numerical column, describe() will show some basic statistics:

year_born height titles aces
count 10 10 10 10
mean 1989.2 191.4 24.5 3841.5
std 4.442222 7.589466 33.317496 2829.734744
min 1981 180 4 1370
25.00% 1986.5 185 4.5 1689.25
50.00% 1989 191 8.5 3062
75.00% 1991.75 198 20 5277.5
max 1997 203 97 10414

The describe() function returns basic statistics for each column in our dataset, including:

• count - number of non-empty values,
• mean - arithmetic mean,
• std - standard deviation,
• min - minimum value,
• 25% - 1st quartile,
• 50% - 2nd quartile (median),
• 75% - 3rd quartile,
• max - maximum value.

Don't worry if you don't know what these metrics are. We'll explain them over the next few exercises.

## Exercise

Run the describe() function for the movies DataFrame.

As you can see, there are just two numerical columns in the DataFrame: rating and box_office.

### Stuck? Here's a hint!

Simply add:

movies.describe()