In the previous chapter, we applied the `mean()` function, but I want to share with you other commonly used methods.

|Function title|Implementation|Syntax|
|-----|-----|-----|
|`mean()`|Finds the mean value of all values in column that relates to one group|`DataFrame.groupby().mean()`|
|`median()`|Finds the median value of all values in column that relates to one group|`DataFrame.groupby().median()`|
|`sum()`|Finds the sum of all values in column that relates to one group|`DataFrame.groupby().sum()`|
|`count()`|Finds the amount of values in column that relates to one group|`DataFrame.groupby().count()`|
|`min()`|Finds the minimum value of all values in column that relates to one group|`DataFrame.groupby().min()`|
|`max()`|Finds the maximim value of all values in column that relates to one group|`DataFrame.groupby().max()`|

In the task you will work with the dataset:

This course will teach you the necessary skills to manage simple analytical tasks. You are going to learn Python and its libraries, such as pandas and NumPy. Besides, you will deal with real-life analytical tasks such as calculating vitally important marketing metrics.

Here, we will face challenges related to data types in python. In this section, we will learn the Python syntax necessary for each person who wants to work with this language. After the section, we will undoubtedly be able to cope with simple Python tasks.

This section will teach you simple Python functions. We will be able to work with if/else statements and loops. Such skills are necessary for everyone who wants to start programming and doing fascinating Python tasks.

This section is the most complicated than the previous one, but it is gripping. Here, we will manage the most commonly used pandas function to help we do essential operations with data. Also, we will learn the basics of the NumPy library.

This section allows you to become a real analyst. Let's go!

Function title	Implementation	Syntax
`mean()`	Finds the mean value of all values in column that relates to one group	`DataFrame.groupby().mean()`
`median()`	Finds the median value of all values in column that relates to one group	`DataFrame.groupby().median()`
`sum()`	Finds the sum of all values in column that relates to one group	`DataFrame.groupby().sum()`
`count()`	Finds the amount of values in column that relates to one group	`DataFrame.groupby().count()`
`min()`	Finds the minimum value of all values in column that relates to one group	`DataFrame.groupby().min()`
`max()`	Finds the maximim value of all values in column that relates to one group	`DataFrame.groupby().max()`

Introduction to Python for Data Analysis

Dive Deeper into Grouping Data

Fill the gaps to cope with the tasks. Group by experience_level using .min() function to find the minimum salaries for each experience level.