List the poorest and richest countries worldwide
The values of numerical variables are numbers. They can be described by measures of central tendency, or the most typical value in a dataset, and dispersion, which represents the spread of a distribution.
In the next few exercises, you will use these statistics to explore the data in 'per_capita_income.csv', which contains the average income earned per person in a given country. The first step in analyzing aspects of the global income distribution is to inspect and familiarize yourself with the data.
pandas has been imported as pd.
This exercise is part of the course
Importing and Managing Financial Data in Python
Exercise instructions
- Load the
'per_capita_income.csv'file intoincome. No additional arguments other than the file name are needed. (Note that this is a csv file.) - Inspect the column names and data types with
.info(). - Using
.sort_values(), sort (in descending order) theincomeDataFrame by the column which contains the income information. - Display the first five rows of
incomeusing.head()and the last five rows using.tail().
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Import the data
income = ____
# Inspect the result
income.info()
# Sort the data by income
income = income.sort_values('Income per Capita', ____)
# Display the first and last five rows
print(income.____())
print(income.____())