Values Skills: Data pre-processing, descriptive statistics, Python

The manager invited you to a meeting to introduce you to the company's international expansion project. He asks you to do an exploratory analysis to see if the education data of the World Bank can inform the academy's expansion project.Here are the questions you have been asked to explore:
● Which countries have a high customer potential for our services?
● For each of these countries, what will be the evolution of this customer potential?
● In which countries should one set up first?

Google collab - To perform the data analysis

pip install pandas 
pip install matplotlib
pip install -U wbdat #Api for accessing the world bank data

import pandas as pd
import matplotlib.pyplot as plt
import wbdata

Fetching the data

wbdata.get_source() #data source available in world bank data 
wbdata.get_source(12) #the source required for this project 12 = Education Statistics
wbdata.get_indicator(source=12)
df = wbdata.get_dataframe(indicator, country=(list of country),convert_date=False )

• School enrollment, secondary, private (% of total secondary)
• Secondary education, teachers
• Pupil-teacher ratio, secondary
• Secondary education, general pupils
• Secure Internet servers (per 1 million people)
• Government expenditure on education, total (% of government expenditure)
• Expenditure on secondary education (% of government expenditure on education)

df_country.head(16)

plot1(["IN",'BD'],internet_ind,"internet acces per million")
#the following function takes in input as(country, indicator,title for graph) and provides a line graph over years 2009-2019 as per the data available.

onecon(['BD'],"Bangladesh Graphs")#the following functions takes in the parameter(one country alpha code as list, title)and provides the variation of each parameters over years 

google Collab link

• From the above exploration we can note that after considering some of the major features like internet and other sub features we can say in Asia the best countries would be Bangladesh, China and India.

• From the above exploration it can been seen that Brazil and USA in America.

• From the above exploration it can been seen that Poland, Britain and Finland in Europe.

world bank api library documentation

Accesing data through its api example using python and R

Accesing data through its api example in kaggle

Api git link

world bank Education Statistics (EdStats)

world bank country list

world banck indicators

country name and alpha codes

World Bank Country and Lending Groups