python script

INSS 611

This assignment covers knowledge about chapter 7. Please write Python scripts to solve the questions. There may have multiple solutions for the same questions. You will get the grades if your scripts can be successfully run and solve the questions. Please read the instructions at the beginning of each question carefully before diving into the questions.

The questions in this assignment will be based on the given data frame below, containing customers’ names, ages, locations, and email addresses. Please copy the following codes to your notebook. Remember to check quotations if they cannot be run.

import pandas as pd

import numpy as np

from numpy import nan as NA

import re

customer = pd.DataFrame.from_dict({ ‘Name’: [‘James, Nik’, ‘Marry, Kate’, ‘John, Evan’, ‘Connie, Kyra’, ‘Dim, Thompson’, NA], ‘Age’: [33, NA, 40, 57, 33, NA], ‘Location’: [‘Toronto’, ‘London’, ‘New York’, ‘Atlanta’, NA, NA], ‘Email Address’: [‘+)@*’, ‘’, ‘&^%$’, ‘#^*@(’, ‘|}{.,’, NA] })



  1. Drop the rows in “customer” that have all missing values using the “dropna()” function and pass the “how= ‘all’” argument. Print the updated “customer”.

Hint: Refer to question 1.3 in exercise 6.


  1. Fill the missing values in “customer”. Specifically, fill in the column Age’s missing values with its mean and the column Location’s missing values with “Paris”. Print the updated “customer”.

Hint: Refer to question 2.1 in exercise 6.


  1. Clean the “Email Address” column in “customer” by removing all the special characters and spaces in front of the emails. Print the updated “customer”.

Hint: Refer to question 3.1 in exercise 6 for the email pattern. Refer to page 221, subsection Vectorized String Functions in pandas, IN[176], on how to manipulate strings in a column of a data frame. To update a column in a data frame, you need to call the column by its name and assign it with updated values. For example, customer[‘Email Address’] = <updated emails>.


  1. (Bonus 2 points) Include two new columns, “First Name” and “Last Name”, by splitting the “Name” column into the “customer” data frame. Drop the previous “Name” column. Print out the new “customer”.



Put your answers in one Jupyter notebook. Please use “Markdown” to specify the question numbers and any necessary explanations. To add a markdown in a notebook, click to select an input box and change the type from “code” to “markdown,” as the following screenshot shows.


Once you have all the questions answered, run all the cells and ensure they all have output boxes. Then, save and download your notebook as an HTML file by clicking on the “File” and “Download as.” Then, select the “HTML (.html)” option, “as the screenshot shows. Once you download it, rename it as “Assignment 6 [your full name].” Before submitting the HTML file to Sakai, double-check if every cell has an output box shown. If you don’t run the cells and get the output boxes, your downloaded HTML file won’t display the outputs, so I cannot grade your submissions.


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