def setUp( self ): # To load the data for testing and create a class of income distribution country_by_region_data = pd.read_csv('../countries.csv') gdp_by_year = pd.read_excel( '../indicator gapminder gdp_per_capita_ppp.xlsx') self.test_inputs = income_distribution() self.test_inputs.set_Data(country_by_region_data, gdp_by_year)
def loop(): loop_trial = 'y' try: country_by_region_data = pd.read_csv('countries.csv') gdp_by_year = pd.read_excel( 'indicator gapminder gdp_per_capita_ppp.xlsx') # Loading the data cntry_cls = income_distribution() # Create a class for country class cntry_cls.set_Data( country_by_region_data, gdp_by_year) # To assign the data for the class variables print('The head of the transposed gdp_by_year data is :') print(cntry_cls.display_head()) # For question no 4 (display head) print( 'Instructions: \nPlease enter the year for which you want to see the graphical distribution of income per person across all countries in the world' ) print('Note: Enter years only between 1800 and 2012 (inclusive)' ) #Instructions yr = input('>>') while (yr != 'finish'): cntry_cls.check_valid_year(yr, 1) if cntry_cls.valid_input == 1: cntry_cls.all_countries_graph_by_year(yr) print('Enter another year (or finish to quit)') yr = input('>>') # After the user enters finish, Histogram and Boxplots for the years 2007 - 2012 is generated: logging.basicConfig(format='%(asctime)s : %(levelname)s : %(message)s', level=logging.INFO) logging.info("Generating histograms and boxplots for 2007-2012") print( '\nThe Histogram and Boxplots for the years 2007 - 2012 has been appended in the pdf file located in the same path' ) list_years = np.arange(2007, 2013, 1) explore = exploratory_analysis( ) # To create a class for exploration to access the histogram and boxplot functions for i in list_years: merged_data = cntry_cls.merge_by_year( i ) # Get the merged data for a particular year using the function in country class and perform exploration explore.plt_Histogram(merged_data, i) explore.plt_Boxplot(merged_data, i) except KeyboardInterrupt: print("Keyboard Exit! Quitting..") sys.exit()
def loop(): loop_trial = 'y' try: country_by_region_data = pd.read_csv('countries.csv') gdp_by_year = pd.read_excel('indicator gapminder gdp_per_capita_ppp.xlsx') # Loading the data cntry_cls = income_distribution() # Create a class for country class cntry_cls.set_Data(country_by_region_data, gdp_by_year) # To assign the data for the class variables print('The head of the transposed gdp_by_year data is :') print(cntry_cls.display_head()) # For question no 4 (display head) print('Instructions: \nPlease enter the year for which you want to see the graphical distribution of income per person across all countries in the world') print('Note: Enter years only between 1800 and 2012 (inclusive)') #Instructions yr = input('>>') while(yr != 'finish'): cntry_cls.check_valid_year(yr, 1) if cntry_cls.valid_input == 1: cntry_cls.all_countries_graph_by_year(yr) print('Enter another year (or finish to quit)') yr = input('>>') # After the user enters finish, Histogram and Boxplots for the years 2007 - 2012 is generated: logging.basicConfig(format='%(asctime)s : %(levelname)s : %(message)s', level=logging.INFO) logging.info("Generating histograms and boxplots for 2007-2012") print('\nThe Histogram and Boxplots for the years 2007 - 2012 has been appended in the pdf file located in the same path') list_years = np.arange(2007,2013,1) explore = exploratory_analysis() # To create a class for exploration to access the histogram and boxplot functions for i in list_years: merged_data = cntry_cls.merge_by_year(i) # Get the merged data for a particular year using the function in country class and perform exploration explore.plt_Histogram(merged_data, i) explore.plt_Boxplot(merged_data, i) except KeyboardInterrupt: print("Keyboard Exit! Quitting..") sys.exit()
def setUp(self): # To load the data for testing and create a class of income distribution country_by_region_data = pd.read_csv('../countries.csv') gdp_by_year = pd.read_excel('../indicator gapminder gdp_per_capita_ppp.xlsx') self.test_inputs = income_distribution() self.test_inputs.set_Data(country_by_region_data, gdp_by_year)