Answer:
The answer of this question is given below into explanation section
Explanation:
answer (a)
I visited the carrerbuilder dot com and search for data entry job. The link of the posting is given below
https://www.careerbuilder.com/jobs?utf8=%E2%9C%93&keywords=data+entry&location=
answer(B)-Requirements of the the job
- Previous office experience (data entry experience a plus)
- Proficient with a computer and computer software (Excel knowledge required)
- Excellent verbal and written communication skills
- The ability to multi-task and work in a team-oriented environment
- High School Diploma / G.E.D.
- Ability to meet background check and drug screening requirements
answer(C)-Tasks of the job
- Open, sort, and scan documents
- Track all incoming supplies and samples
- Data entry of samples that come in
- Assist with documentation and maintaining of data
- Prepare and label information for processing
- Review and correct any data entry error or missing information
answer (d)
I have 3 years of experience in organization administration where I managed the organization data, generated reports and communicated verbally and written within the organization efficiently.
Answer:
import pandas as pd #importing pandas library as pd
import matplotlib.pyplot as plt #importing matplotlib.pyplot as plt
pop=pd.read_csv('nycHistPop.csv') #reading the csv file
borough=input('Enter borough name:') #asking the user for borough namme
# image=input('Enter image name:')
# pop['Fraction']=pop[borough]/pop['Total']
# pop.plot(x='Year', y='Fraction')
print("Minimum population",pop[borough].min()) #printing the minimum population of borough
print("Maximum population",pop[borough].max()) #printing the maximum population of borough
print("Average population",pop[borough].mean()) #printing the average population of borough
print("Standard deviation",pop[borough].std()) #printing the standard deviation of borough
# fig=plt.gcf()
# fig.savefig(image)
Explanation:
Inspect them and make sure that they are exact copies then delete one if they are the same.
