Get started with the basics of analytics in Python, the language of choice for data science.

Python Data Analysis and Visualization

Get started with the basics of analytics in Python, the language of choice for data science using Python data structures,  descriptive statistics, and much more.

Data Analysis and Visualization

## Detect outliers

In this exercise, we will use the same data frame as read in from the [Reading Data exercise](https://www.educative.io/courses/python-data-analysis-and-visualization/exercise-reading-auto-mpg-dataset).

We will then create an additional function `outlier_detection` that takes a data frame `df` and returns 2 numbers in a list:

+ The 90th percentile for every column
+ The 10th percentile for every column

Try to implement the function below. Feel free to view the solution, after giving it a few shots. Good Luck!

# Detect outliers

In this exercise, we will use the same data frame as read in from the [Reading Data exercise](https://www.educative.io/courses/python-data-analysis-and-visualization/exercise-reading-auto-mpg-dataset).

We will then create an additional function `outlier_detection` that takes a data frame `df` and returns 2 numbers in a list:

+ The 90th percentile for every column
+ The 10th percentile for every column

Try to implement the function below. Feel free to view the solution, after giving it a few shots. Good Luck!

This exercise will test a simple way to start investigating potential outliers.

Exercise: Cleaning Auto MPG Dataset

Detect outliers #