In Python: The Broadway dataset contains data for Broadway shows' Capacity (percentage of the theatre filled) and Gross Potential (maximum amount that can be earned) for multiple shows in a specific month and year. Given a CSV file name read from user input, write a program that performs the following tasks: Read in the CSV file as a dataframe. Insert a new column labelled "Size" at the end of the dataframe. The "Size" column contains values in column "Gross Potential" divided by 2. Output the dataframe using the print() function. Create a scatter plot of "Gross Potential" vs "Capacity" with the following marker styling parameters: markers: 'x' color: orange size: values in column "Size" Add the x-label ("Capacity", fontsize = 10), y-label ("Gross Potential", fontsize = 10), and title ("Gross Potential vs Capacity", fontsize = 16) to the figure. Add gridlines to the figure using '--' as linestyle. Save the figure as output_fig.png. Click here to view Input and Output Example

Please write the code in c

There is a csv file called Air_Quality.csv. It has 12 columns and 17,000 rows. One column titled 'Name' which has a various emissions listed in it. Another column titled 'Geo Place Name' has a list of cities. Write a code (in the most basic Python) which finds an emission called Traffic Density within the column and prints out which city has the most Traffic Density based on a column called 'Data Value' Below is a picture of a small chunk of the csv file.

My Python program analyzes data from a CSV file that is all numbers. This program is designed to find the median and standard deviation  I'm trying to figure out a part where if the last column of the file contains zeros, it finds where the numbers are in the same row indexes of the other columns. It then calculates the average of these numbers. However, my program calculates them by columns first, not by rows. How could this be fixed? For example, if the last column had a zero and another column had a three in the same row index and another with 4, those numbers would be calculated.   # Lucas Conklin# 5772707import csvimport statistics def readCSVIntoDictionary(f_name):    data = []    with open(f_name) as f:        reader = csv.reader(f)        for row in reader:            if not data:                for index in range(len(row)):                    data.append([])            for index in range(len(row)):                data[index].append(float(row[index]))        f.close()    return…