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()