HI, I need help with this question. Please answer in details. The data set is found below for each countries sugar consumption. Thanks!
Philippines,19.4,2357.570924,Asia Poland, 40.6,13384.78217,Europe Portugal,21.7,22532.50772, Europe Romania,18.9,9063.676031, Europe Russia, 42.4,13324.28784, Europe Serbia,25.7, 6047.73788,Europe Slovenia, 17,24478.31997,Europe South Africa, 30.3,7830.505168,Africa South Korea, 17.4,24155.8293,Asia Spain, 21.5,31117.89747,Europe Sweden, 33.7,56724.36224, Europe Switzerland, 49.2,83270.24474, Europe Tajikistan,16.4,834.6586566,Asia Thailand, 35.5,5192.118907,Asia Turkey,27.3,10604.5524,Asia Turkmenistan,7.3,5724.541586,Asia Ukraine, 39.6,3575.490646, Europe United Kingdom, 35.8,38927.06931, Europe USA, 28.1,49854.52267,North America Uzbekistan, 9.3,1544.827773,Asia Venezuela, 34.8,10727.98209, South America Vietnam,9.6,1543.02695,Asia
Question 1: Describe your dataset by stating its n, the individual, your variables and whether or not they are categorical or quantitative. Justify your answers
Homework Answers
Add Answer to:
HI, I need help with this question. Please answer in details. The data set is found below for eac...
HI, I need help with answering these questions. Please explain and answer all parts. Data for all...
HI, I need help with answering these questions. Please explain
and answer all parts. Data for all the countries and then the
question at the bottom.
Sugar Consumption Per Capita.csv Country Albania Argentina Armenia Australia Austria Azerbaijan Belarus Belgium Bosnia and Herzegovina 13.4 4754.197861 Europe Brazil Canada Chile China Colombia Czech Republic Denmark Egypt Estonia Finland France Georgia Germany Ghana Greece Hungary Iceland India Indonesia Iran Sugar GDP Continent 15.3 4556.144342 Europe 38.1 13693.70379 South America 33.2 3421.704509 Europe 34.1...
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...
ONLY ANSWER THE QUESTIONS AT THE BOTTOM Case Description Corporations with international operations need to assess...
ONLY ANSWER THE QUESTIONS AT THE BOTTOM
Case Description
Corporations with international operations need to assess the
risks associated with setting up and maintaining operations in
different regions of the world. Consideration of the risks include
considering such issues as political and economic stability. One
indicator of the healthcare and quality of life in a country or
region that is considered correlated with the risk and stability in
the region is the child mortality rate. As a result, the healthcare...
8 AutoSave D The Home Data Review View Help Power Pivot Formulas Insert Draw Page Layout...
8 AutoSave D The Home Data Review View Help Power Pivot Formulas Insert Draw Page Layout ES - per capita GDP 1 Country Name 2 Central African Republic 3 Myanmar 4 Congo, Dem. Rep. 5 South Sudan 6 Madagascar 7 Burundi 8 Ethiopia 9 Guinea 10 Malawi 11 Niger 12 Gambia, The 13 Bangladesh 14 Guinea-Bissau 15 Lao PDR 16 Benin 17 Pakistan 18 Chad 19 Nepal 20 Mozambique 21 uberia 22 Kenya 23 Senegal 24 Burkina Faso 25 Mauritania...
HI, I need help with answering these questions. Please explain
and answer all parts. Data for all the countries and then the
question at the bottom.
Sugar Consumption Per Capita.csv Country Albania Argentina Armenia Australia Austria Azerbaijan Belarus Belgium Bosnia and Herzegovina 13.4 4754.197861 Europe Brazil Canada Chile China Colombia Czech Republic Denmark Egypt Estonia Finland France Georgia Germany Ghana Greece Hungary Iceland India Indonesia Iran Sugar GDP Continent 15.3 4556.144342 Europe 38.1 13693.70379 South America 33.2 3421.704509 Europe 34.1...
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...
ONLY ANSWER THE QUESTIONS AT THE BOTTOM
Case Description
Corporations with international operations need to assess the
risks associated with setting up and maintaining operations in
different regions of the world. Consideration of the risks include
considering such issues as political and economic stability. One
indicator of the healthcare and quality of life in a country or
region that is considered correlated with the risk and stability in
the region is the child mortality rate. As a result, the healthcare...
8 AutoSave D The Home Data Review View Help Power Pivot Formulas Insert Draw Page Layout ES - per capita GDP 1 Country Name 2 Central African Republic 3 Myanmar 4 Congo, Dem. Rep. 5 South Sudan 6 Madagascar 7 Burundi 8 Ethiopia 9 Guinea 10 Malawi 11 Niger 12 Gambia, The 13 Bangladesh 14 Guinea-Bissau 15 Lao PDR 16 Benin 17 Pakistan 18 Chad 19 Nepal 20 Mozambique 21 uberia 22 Kenya 23 Senegal 24 Burkina Faso 25 Mauritania...
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