In PYTHON please Ive attached example code from car$\_$info.csv

A CSV file $($car$\_$info.csv$)$ has been provided which contains information about different cars manufactured between $1970$ and $1982.$ Write a python program that:

Reads the csv file into a Pandas DataFrame object. Print the shape of that dataframe.

Print the names of the japanese cars having v$6$ engines

Print the car names for which the horsepower data is missing.

Print the number of cars having $mpg20.$

Print the name of the car which have the highest mpg$.$

Print the maximum, minimum, and average of the car weights.

Drop the rows from the dataframe which have any missing value. Print the shape of the resulting dataframe.

Create a pie chart showing proportion of cars manufactured in different countries.

Create a plot containing two subplots placed vertically. Each subplot should include separate xlabels, ylabels, and legends.

i$.$ a scatter plot showing mpg vs$.$ weight.

ii$.$ a line plot showing mpg vs displacement.

Expected Output:

If your implementation is correct, the output should be similar to the following$-$

Shape of the dataframe: $(398,9)$

Japanese v$6$ cars: $[\text{'}$toyota mark ii$\text{'},$ 'toyota mark ii$\text{'},$ 'datsun $810\text{'},$ 'datsun $280-$zx$\text{'},$ 'toyota cressida', 'datsun $810$ maxima'$]$

Cars with missing horsepower data: $[\text{'}$ford pinto', 'ford maverick', 'renault lecar deluxe', 'ford mustang cobra', 'renault $18$i$\text{'},$ 'amc concord dl$\text{'}]$

Number of cars having mpg $20$:$247$

Most fuel$-$efficient car: $[\text{'}$mazda glc$\text{'}]$

minimum weight: $1613,$ maximum weight: $5140,$ average weight: $2970\mathrm{.}42$

Shape after removing the missing values: $(392,9)$

A pie chart should be displayed as described.

The corresponding subplots should be displayed within a single figure.