Beispiel #1
0
def merge_by_year(dataframe1, dataframe2, year):
	'''function to merge the countries and income data sets for any given year.'''

	if RepresentsInt(year) == True:   #this part same as one in display_distribution
		if int(year) > 2012 or int(year) < 1800:
			raise invalid_year()
		else:
			year_distribution = dataframe1.ix[year,:]
			year_distribution.name = 'Income'   
			year_distribution.index.name = 'Country'
			region_distribution = pd.merge(pd.DataFrame(year_distribution), dataframe2, left_index = True, right_on = 'Country', how = 'inner')
			region_distribution_dropna = region_distribution.dropna()   #drop the nan value
			return region_distribution_dropna
	else:
		raise invalid_input()
Beispiel #2
0
def display_distribution(year, dataframe):
	'''function to display the distribution of income per person across all countries in the world for the given year.'''
	
	if RepresentsInt(year) == True:   #check if input year can be converted to an integer
		if int(year) >2012 or int(year) < 1800:   #check if input year in the right range
			raise invalid_year()
		else:
			year_distribution = dataframe.ix[int(year),:]   #select the data in the given year
			plt.figure(figsize = (8, 8))
			year_distribution.dropna().hist()   #drop the nan value and sort by the value
			plt.xlabel('Income per person')
			plt.ylabel('Frequency')
			plt.yticks(fontsize = 10)
			plt.title('Income distribution of per person in ' + str(year))
			plt.show()
	else:
		raise invalid_input()