Write a Java program that will read in this XLS file and store them in an ArrayList or LinkedList or HashMap
Ask user to input what country they wish to search for and then output the country population.
Also ask user which other countries they wish to
compare. then compare the two countries by outputting both country
population
NOTE: THIS IS AN XLS FILE

import java.io.File;
import java.io.FileInputStream;
import java.io.FileOutputStream;
import java.io.IOException;
import java.sql.Date;
import java.util.HashMap;
import java.util.Iterator;
import java.util.Map;
import java.util.Set;
import java.util.Scanner;
import org.apache.poi.ss.usermodel.Row;
import org.apache.poi.ss.usermodel.Cell;
import org.apache.poi.xssf.usermodel.XSSFWorkbook;
importorg.apache.poi.xssf.usermodel.XSSFSheet;
public class XLSReader {
public static void main(String[] args) {
int arr[][]= new int[100][2];
int i=0,j;
try {
File excel = new File("C://user/Country.xls");
FileInputStream fis = new FileInputStream(excel);
XSSFWorkbook book =new XSSFWorkbook(fis);
XSSFSheet sheet = book.getSheetAt(0);
Iterator<Row> itr = sheet.iterator();
// Iterating over Excel file in Java
while (itr.hasNext()) {
Row row = itr.next();
Iterator<Cell> cellIterator = row.cellIterator();
while (cellIterator.hasNext()) {
Cell cell = cellIterator.next();
switch (cell.getCellType()) {
case Cell.CELL_TYPE_STRING: a[i][1]=cell.getStringCellValue();
break;
case Cell.CELL_TYPE_NUMERIC:
a[i][2]=cell.getNumericCellValue();
break;
}
i++;
}
}
book.close();
Scanner scan = new Scanner(System.in);
System.out.print(“Enter the name of the country”);
String s=scan.nextLine();
for(j=0;j<i;j++)
if(s.compareTo(a[i][1]==0)
System.out.println(“ Population is” + a[i][2]);
}
}
}
Write a Java program that will read in this XLS file and store them in an...
Carbon dioxide (CO2) emissions are widely believed to be a
driver of global climate change. In this problem set you will use
cross-section data to test what drives countries’ “carbon
footprints,” that is, their CO2 emissions. Is it population, or is
income the bigger culprit?
The data set “CO2 by country 2010 sh S17” contains data on a
sample of countries’ CO2 emissions, in kilotons; population, in
millions; and gross national income (GNI), in millions of US
dollars, for the...
Country Continent GDP (millions of US$) Afghanistan Asia 18,181 Albania Europe 12,847 Algeria Africa 190,709 Angola Africa 100,948 Argentina South America 447,644 Australia Oceania 1,488,221 Austria Europe 419,243 Azerbaijan Europe 62,321 Bahrain Asia 26,108 Bangladesh Asia 113,032 Belarus Europe 55,483 Belgium Europe 513,396 Bolivia Africa 24,604 Bosnia and Herzegovina Europe 17,965 Botswana Africa 17,570 Brazil South America 2,492,908 Brunei Asia 15,533 Bulgaria Europe...
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"
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...
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...
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...
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...
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...
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
and quality of care as measured by...
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...