Answer to Question #306138 in Python for johnie

Question

1. Open and read the countrycities.csv file.

2. Count and display the number of cities per country.

3. Count and display the country which is a member of the EU (EU = yes) and not a member of the EU (EU = no).

4. Find and display the country with the highest and lowest total population.

5. Count and display the country with a coastline (coastline = yes) and without a coastline (coastline = no).

THIS IS THE LINK OF countrycities if you can help me with this i badly need this, i am just a student : https://drive.google.com/drive/folders/1dFoUHbPrBo3hiOJY_PTccdlQXSM4YJ4s?usp=sharing

Answer 1

#Import library
import  pandas as pd
#Navigate to the folder
#Open and read the countrycities.csv file
df=pd.read_csv("C:/Max/Q306138/countrycities.csv")

df.nunique()
#. Count and display the number of cities per country.
df.groupby('country')['city'].nunique()

#Count and display the country which is a member of the EU (EU = yes) and not a member of the EU (EU = no).
df[df['EU'] == 'yes']['country']
df[df['EU'] == 'yes']['country'].count()

#3.Find and display the country with the highest and lowest total population.
df[df['population'] == df['population'].max()]['country']
df[df['population'] == df['population'].min()]['country']

#5. Count and display the country with a coastline (coastline = yes) and without a coastline (coastline = no).
#With a coastline
df[df['coastline'] == 'yes']['country']
df[df['coastline'] == 'yes']['country'].count()
#Without a coastline

df[df['coastline'] == 'no']['country']
df[df['coastline'] == 'no']['country'].count()