Data Sourcing and Download the attached Jupyter Notebook. Prior to beginning your solution, I recommend that you review the Project Rubric document. The rubric will lend clarity regarding project expectations and consequently my evalution of your projec

Download the attached Jupyter Notebook. Prior to beginning your solution, I recommend that you review the Project Rubric document. The rubric will lend clarity regarding project expectations and consequently my evalution of your project solution.

Complete the activities and questions as directed in the project JNB. Once you have completed the JNB activities, test your solution as direct in the Deliverables section of the project JNB. Once you have completed your testing, save and close your notebook.

Upload your saved notebook to this assessment item. YOU MAY SUBMIT AS MANY TIME AS YOU WISH. ONLY YOUR LAST SUBMISSION WILL BE GRADED.

Attachments

• ISYS613_Project_v7.ipynbDownload ISYS613_Project_v7.ipynb
• author_key_file.csv

• Project_Rubric.pdfDownload Project_Rubric.pdf

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ISYS613
Course Project Rubric
Fall 2023
Student: «FirstName» «LastName»
RUBRIC: Source 1 – Tasks 1.2, 1.3, 1.4
Possible Points (30)
Program Requirements:
Correctly scrapes author Full Name
Correctly scrapes author Date of Birth
Correctly scrapes author Birth Location
Total
10
10
10
30
RUBRIC: Source 1 – Task 1.5
Possible Points (10)
Program Requirements:
Construct a Pandas DataFrame containing the scraped attributes
Total
10
10
RUBRIC: Source 2 – Task 2.1, 2.2
Possible Points (40)
Program Requirements:
Open and ingest CSV file
Merge CSV key attribute into Pandas DF
Merge CSV gender attribute into Pandas DF
Key column converted to row index
Total
5
15
15
5
40
RUBRIC: Source 3 – Task 3.1
Possible Points (40)
Program Requirements:
Open and ingest XML file
Construct Pandas DF using XML attributes
Merge XML attributes into previous Pandas dataframe resulting in 50 observations
Total
10
20
10
40
RUBRIC: Source 4 – Task 3.1
Possible Points (40)
Program Requirements:
Iterate the existing dataframe for each observation
Invoke API using q or geofilter.distance parameters with rounded (lat,lon) and 10k
meters for each author
Parse returned JSON data
Correctly determines closest city and zip from returned data
Incorporates city and zip into existing dataframe
Total
5
10
5
10
10
40
ISYS613
Course Project Rubric
Fall 2023
Student: «FirstName» «LastName»
RUBRIC: PoC – Question 1
Possible Points (10)
Program Requirements:
Uses agg method to find sqft_living mean and standard deviation by bedrooms
Total
10
10
RUBRIC: PoC – Question 2
Possible Points (20)
Program Requirements:
Calculate sqft_lot mean and standard deviation
Filter dataframe for sqft_lot > (mean + std)
Group by gender
Display count results for sqft_lot only
Total
5
8
2
5
20
RUBRIC: PoC – Question 3
Possible Points (20)
Program Requirements:
Discretize price into 3 bins using DataFrame.cut()
Display count of results for each resulting bin
Total
15
5
20