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)
