Homework Answers
Net official development assistance
It is a initiative designed to promote economic development and welfare of developing countries.It consists of loan disbursed on concessional terms and grants by official agencies of the members of the Development Assistance Committee. It excludes loans and credits for military purpose.
It has direct affect on the Human resource as well he economy
On human resource and economic front - The loan taken is utilised for development purpose which significantly increase the GDP level of the company and affect economy in good way creating more Jobs in the country. However there could be negative impact too on the per capita income as the Aid taken can affect the income of the developing countries.
The Aid can be utilised for below purposes
- Support global peace
- Development efforts
- Increase employment
- humanitarian assistance
Add Answer to:
how
does net official development assistance received of a country
affect human/economic development?
Venezuela, 32.5 310...
how does foreign investment net inflow affect human economic development use examples 13. Foreign direct investment,...
how
does foreign investment net inflow affect human economic
development use examples
13. Foreign direct investment, net inflows (% of GDP) 2017 2018 1.2 0.2 0.8 0.4 0.7 0.6 0.71 0.6 0 7.7 0.9) 1.6 Column1 2016 Saudi Arabia, Japan, South Africa, Sweden, Nigeria, China, India, US, France, Indonesia Mexico, Egypt, Brazil, Costa Rica Ethiopia, Honduras Nicaragua 2.6 1.8 0.5 3.3 st 6.8 5.61 2.71 14. Private capital flows (% of GDP)
how does concentration index (exports)(value) affect human economic development use examples 7. Concentration Index (exports) (value)...
how
does concentration index (exports)(value) affect human economic
development use examples
7. Concentration Index (exports) (value) Column1 2015 Sweden, France, China, US India, South Africa Mexico Japan, Egypt, Indonesia Brazil Nicaragua Honduras Costa Rica Ethiopia, Saudi Arabia, Venezuela, Nigeria, 2016 0.089 0.098 0.104 0.097 0.12 0.122 0.122 0.135 0.142 0.138 0.128 0.226 0.231 0.228 0.301 0.549 0.739 0.736 2017 0.091 0.09 0.098 0.092 0.105 0.096 0.099 0.097 0.12 0.122 0.121 0.128 0.124 0.132 0.141 0.139 0.153 0.142 0.128 0.142 0.126...
22 Use data_Americas. Plot year vs gdpPercap. Scale gdpPercap by log10. Color the data by country....
22 Use data_Americas. Plot year vs gdpPercap. Scale gdpPercap by log10. Color the data by country. 23 Use data_Americas. Plot year vs gdpPercap. Scale gdpPercap by log10. Color the data by country and size by pop. Looking for the answers in R command codes. 1952 1957 1962 1967 1972 1977 1982 1987 1992 1997 2002 2007 142 142 142 142 142 142 142 142 142 142 142 142 > table(gapminder$country) Afghanistan Albania Algeria 12 12 12 Angola Argentina Australia 12...
12 Use data_2002. Use ggplot. Plot gdpPercap vs lifeExp. 13 Use data_2002. Use ggplot. Plot gdpPercap...
12 Use data_2002. Use ggplot. Plot gdpPercap vs lifeExp. 13 Use data_2002. Use ggplot. Plot gdpPercap vs lifeExp by continent (color) 14 Use data_2002. Use ggplot. Plot gdpPercap vs lifeExp by continent and pop (color and size) 15 Get data for Europe in 2002. Call it data_Europe Looking for these problems in R command code answers. 1952 1957 1962 1967 1972 1977 1982 1987 1992 1997 2002 2007 142 142 142 142 142 142 142 142 142 142 142 142...
ccode country lrgdppc proc_exp malaria lsettlr_mort AGO Angola 7.77 5.36 1 5.63479 ARG Argentina 9.13 6.39 0 4.232656 AUS Australia 9.9 9.32 0 2.145931 BFA Burkina Faso 6.85 4.45 1 5.63479...
ccode country lrgdppc proc_exp malaria lsettlr_mort AGO Angola 7.77 5.36 1 5.63479 ARG Argentina 9.13 6.39 0 4.232656 AUS Australia 9.9 9.32 0 2.145931 BFA Burkina Faso 6.85 4.45 1 5.63479 BGD Bangladesh 6.88 5.14 0.158 4.268438 BOL Bolivia 7.93 5.64 0.00528 4.26268 BRA Brazil 8.73 7.91 0.1935 4.26268 CAN Canada 9.99 9.73 0 2.778819 CHL Chile 9.34 7.82 0 4.232656 CIV Cote d'Ivoire 7.44 7 1 6.504288 CMR Cameroon 7.5 6.45 1 5.63479 COG Congo 7.42 4.68 1 5.480639...
Will reward thumbs up 100% if works. thank you Pickling with Python code and Pandas code Do both ...
Will reward thumbs up 100% if works. thank you Pickling with Python code and Pandas code Do both pickling assignment in one Jupyter Notebook file. Python Pickle steps: Download the CSV file. Load into a Pandas DataFrame. Make the column ‘country’ the index. Print the header. Using Python code, pickle the DataFrame and name the file: PythonPickle. Load back the PythonPickle data into the DataFrame. Print the header. (Note both printed headers should match.) Pandas Pickle steps: Download the CSV...
DATA: # happy2.py import csv def main(): happy_dict = make_happy_dict() print_sorted_dictionary(happy_dict) def make_happy_dict(): filename = "happiness.csv"...
DATA:
# happy2.py
import csv
def main():
happy_dict = make_happy_dict()
print_sorted_dictionary(happy_dict)
def make_happy_dict():
filename = "happiness.csv"
happy_dict={}
with open(filename, 'r') as infile:
csv_happy = csv.reader(infile)
infile.readline()
for line in csv_happy:
happy_dict[line[0]] = line[2]
return happy_dict
def lookup_happiness_by_country(happy_dict):
return
def print_sorted_dictionary(D):
if type(D) != type({}):
print("Dictionary not found")
return
print("Contents of dictionary sorted by key.")
print("Key","Value")
for key in sorted(D.keys()):
print(key, D[key])
main()
"happines.csv"
Country,Year of Estimate,Happiness Index
Afghanistan,2018,2.694303274
Albania,2018,5.004402637
Algeria,2018,5.043086052
Angola,2014,3.794837952
Argentina,2018,5.792796612
Armenia,2018,5.062448502
Australia,2018,7.17699337
Austria,2018,7.396001816
Azerbaijan,2018,5.167995453
Bahrain,2017,6.227320671
Bangladesh,2018,4.499217033...
how
does foreign investment net inflow affect human economic
development use examples
13. Foreign direct investment, net inflows (% of GDP) 2017 2018 1.2 0.2 0.8 0.4 0.7 0.6 0.71 0.6 0 7.7 0.9) 1.6 Column1 2016 Saudi Arabia, Japan, South Africa, Sweden, Nigeria, China, India, US, France, Indonesia Mexico, Egypt, Brazil, Costa Rica Ethiopia, Honduras Nicaragua 2.6 1.8 0.5 3.3 st 6.8 5.61 2.71 14. Private capital flows (% of GDP)
how
does concentration index (exports)(value) affect human economic
development use examples
7. Concentration Index (exports) (value) Column1 2015 Sweden, France, China, US India, South Africa Mexico Japan, Egypt, Indonesia Brazil Nicaragua Honduras Costa Rica Ethiopia, Saudi Arabia, Venezuela, Nigeria, 2016 0.089 0.098 0.104 0.097 0.12 0.122 0.122 0.135 0.142 0.138 0.128 0.226 0.231 0.228 0.301 0.549 0.739 0.736 2017 0.091 0.09 0.098 0.092 0.105 0.096 0.099 0.097 0.12 0.122 0.121 0.128 0.124 0.132 0.141 0.139 0.153 0.142 0.128 0.142 0.126...
DATA:
# happy2.py
import csv
def main():
happy_dict = make_happy_dict()
print_sorted_dictionary(happy_dict)
def make_happy_dict():
filename = "happiness.csv"
happy_dict={}
with open(filename, 'r') as infile:
csv_happy = csv.reader(infile)
infile.readline()
for line in csv_happy:
happy_dict[line[0]] = line[2]
return happy_dict
def lookup_happiness_by_country(happy_dict):
return
def print_sorted_dictionary(D):
if type(D) != type({}):
print("Dictionary not found")
return
print("Contents of dictionary sorted by key.")
print("Key","Value")
for key in sorted(D.keys()):
print(key, D[key])
main()
"happines.csv"
Country,Year of Estimate,Happiness Index
Afghanistan,2018,2.694303274
Albania,2018,5.004402637
Algeria,2018,5.043086052
Angola,2014,3.794837952
Argentina,2018,5.792796612
Armenia,2018,5.062448502
Australia,2018,7.17699337
Austria,2018,7.396001816
Azerbaijan,2018,5.167995453
Bahrain,2017,6.227320671
Bangladesh,2018,4.499217033...
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