Question 1: Population Growth The world population data spans from 1960 to 2017. We'd like to build a predictive model that can give us the best guess at what the population growth rate in a given year might be. We will calculate the population growth rate as follows:- The formula to use in calculating the growth rate is as below:- Growth_rate =( Current_year_ population - Previous_year_population) / Previous_year_population
population_df = pd.read_csv('https://raw.githubusercontent.com/Explore-
Question 1: Population Growth
The world population data spans from 1960 to 2017. We'd like to build a predictive model that can give us the best guess at what the population growth rate in a given year might be. We will calculate the population growth rate as follows:-
The formula to use in calculating the growth rate is as below:-
Growth_rate =( Current_year_ population - Previous_year_population) / Previous_year_population
As such, we can only calculate the growth rate for the year 1961 onwards.
Write a function that takes the population_df and a country_code as input and computes the population growth rate for a given country starting from the year 1961. This function must return a return a 2-d numpy array that contains the year and corresponding growth rate for the country.
Function Specifications:
- Should take a population_df and country_code string as input and return a numpy array as output.
- The array should only have two columns containing the year and the population growth rate, in other words, it should have a shape (?, 2) where ? is the length of the data.
The current code given below did not work because it does not take care of the formula above.
def get_population_growth_rate_by_country_year(df,country_code):
# your code here
data = df.loc[country_code, '1960':'2017']
data = data.T.reset_index()
data.columns = ['year', 'population']
data['year'] = data['year'].astype(float)
data['growth_rate'] = data['population'].pct_change()
data = data.iloc[1:]
return data[['year', 'growth_rate']].to_numpy()
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