: country_map_df = pd.read_csv('https://raw.githubusercontent.com/Explore-AI/Publ ic-Data/master/AnalyseProject/country_code_map.csv', index_col='Country Code') population_df = pd.read_csv('https://raw.githubusercontent.com/Explore-AI/Publi c-Data/master/Analyse Project/world_population.csv', index_col='Country Code') meta_df = pd.read_csv('https://raw.githubusercontent.com/Explore-AI/Public-Dat a/master/AnalyseProject/metadata.csv', index_col='Country Code') DataFrame specifications: The DataFrames provide information about the population of the world for various years. Some things to note: • All DataFrames have a Country Code as an index, which is a three-letter code referring to a country. • The country_map_df data maps the Country Code to a Country Name. • The population_df data contains information on the population for a given country between the years 1960 and 2017. • The meta_df data contains meta-information about each country, including its geographical region, its income group, and a comment on the country as a whole. Question 6 Write a function that will return a list of countries for a specified region and income group. If the specified region and income group do not return a country, return None as the value. Function specifications Argument(s): region (string) → the region you want to query. income_group (string) → the income group you want to query. . Return:
: country_map_df = pd.read_csv('https://raw.githubusercontent.com/Explore-AI/Publ ic-Data/master/AnalyseProject/country_code_map.csv', index_col='Country Code') population_df = pd.read_csv('https://raw.githubusercontent.com/Explore-AI/Publi c-Data/master/Analyse Project/world_population.csv', index_col='Country Code') meta_df = pd.read_csv('https://raw.githubusercontent.com/Explore-AI/Public-Dat a/master/AnalyseProject/metadata.csv', index_col='Country Code') DataFrame specifications: The DataFrames provide information about the population of the world for various years. Some things to note: • All DataFrames have a Country Code as an index, which is a three-letter code referring to a country. • The country_map_df data maps the Country Code to a Country Name. • The population_df data contains information on the population for a given country between the years 1960 and 2017. • The meta_df data contains meta-information about each country, including its geographical region, its income group, and a comment on the country as a whole. Question 6 Write a function that will return a list of countries for a specified region and income group. If the specified region and income group do not return a country, return None as the value. Function specifications Argument(s): region (string) → the region you want to query. income_group (string) → the income group you want to query. . Return:
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
Related questions
Question
![Function specifications
Argument(s):
region (string) → the region you want to query.
income_group (string) → the income group you want to query.
Return:
In [ ]:
• countries (list) → return a list of countries that match the search criteria or None if no
countries are found.
In [ ]: ### START FUNCTION
def find_countries_by_region_and_income (region, income_group):
# Your code here.
return countries
### END FUNCTION
In [ ]: countries = find_countries_by_region_and_income ('Sub-Saharan Africa', 'Upper mid
dle income')
countries
Expected output
find_countries_by_region_and_income
find_countries_by_region_and_income
e')==['Tajikistan']
('South Asia', 'High income')==None
('Europe & Central Asia', 'Low incom
find_countries_by_region_and_income('Sub-Saharan
Africa','Upper middle i
ncome') == ['Botswana', 'Gabon', 'Equatorial Guinea', 'Mauritius', 'Namibi
a', 'South Africa']](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F26ac2813-c076-4660-8fde-590b42b2383a%2Fcae7f647-ddd0-472f-8308-aea818f18f24%2Fm33daro_processed.png&w=3840&q=75)
Transcribed Image Text:Function specifications
Argument(s):
region (string) → the region you want to query.
income_group (string) → the income group you want to query.
Return:
In [ ]:
• countries (list) → return a list of countries that match the search criteria or None if no
countries are found.
In [ ]: ### START FUNCTION
def find_countries_by_region_and_income (region, income_group):
# Your code here.
return countries
### END FUNCTION
In [ ]: countries = find_countries_by_region_and_income ('Sub-Saharan Africa', 'Upper mid
dle income')
countries
Expected output
find_countries_by_region_and_income
find_countries_by_region_and_income
e')==['Tajikistan']
('South Asia', 'High income')==None
('Europe & Central Asia', 'Low incom
find_countries_by_region_and_income('Sub-Saharan
Africa','Upper middle i
ncome') == ['Botswana', 'Gabon', 'Equatorial Guinea', 'Mauritius', 'Namibi
a', 'South Africa']
![In [ ]: country_map_df = pd.read_csv('https://raw.githubusercontent.com/Explore-AI/Publ
ic-Data/master/AnalyseProject/country_code_map.csv', index_col='Country Code')
population_df = pd.read_csv('https://raw.githubusercontent.com/Explore-AI/Publi
c-Data/master/Analyse Project/world_population.csv', index_col='Country Code')
meta_df = pd.read_csv('https://raw.githubusercontent.com/Explore-AI/Public-Dat
a/master/AnalyseProject/metadata.csv', index_col='Country Code')
DataFrame specifications:
The DataFrames provide information about the population of the world for various years. Some
things to note:
• All DataFrames have a Country Code as an index, which is a three-letter code referring to a
country.
• The country_map_df data maps the Country Code to a Country Name.
• The population_df data contains information on the population for a given country
between the years 1960 and 2017.
• The meta_df data contains meta-information about each country, including its geographical
region, its income group, and a comment on the country as a whole.
Question 6
Write a function that will return a list of countries for a specified region and income group. If the
specified region and income group do not return a country, return None as the value.
Function specifications
Argument(s):
region (string) → the region you want to query.
income_group (string) → the income group you want to query.
Return:](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F26ac2813-c076-4660-8fde-590b42b2383a%2Fcae7f647-ddd0-472f-8308-aea818f18f24%2Fxwpl5qp_processed.png&w=3840&q=75)
Transcribed Image Text:In [ ]: country_map_df = pd.read_csv('https://raw.githubusercontent.com/Explore-AI/Publ
ic-Data/master/AnalyseProject/country_code_map.csv', index_col='Country Code')
population_df = pd.read_csv('https://raw.githubusercontent.com/Explore-AI/Publi
c-Data/master/Analyse Project/world_population.csv', index_col='Country Code')
meta_df = pd.read_csv('https://raw.githubusercontent.com/Explore-AI/Public-Dat
a/master/AnalyseProject/metadata.csv', index_col='Country Code')
DataFrame specifications:
The DataFrames provide information about the population of the world for various years. Some
things to note:
• All DataFrames have a Country Code as an index, which is a three-letter code referring to a
country.
• The country_map_df data maps the Country Code to a Country Name.
• The population_df data contains information on the population for a given country
between the years 1960 and 2017.
• The meta_df data contains meta-information about each country, including its geographical
region, its income group, and a comment on the country as a whole.
Question 6
Write a function that will return a list of countries for a specified region and income group. If the
specified region and income group do not return a country, return None as the value.
Function specifications
Argument(s):
region (string) → the region you want to query.
income_group (string) → the income group you want to query.
Return:
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