AcF 351b代做、Python/SQL语言程序代写
- 首页 >> C/C++编程 DEPARTMENT OF ACCOUNTING AND FINANCE
AcF 351b Career Skills in Accounting and Finance
Python for Data Analysis
Stream Assignment
1. Overview
Python for Data Analysis stream is designed to provide introductory programming knowledge to
students who have no or little prior programming experience. Throughout the ten sessions, this
module has covered Python language basics, scientific computing and SQL packages and introduction
to corporate bond markets. The assignment therefore is intended to give students the opportunity to
practice on what have learned from the course and encourage students to do independent work
towards writing code scripts to download and analyze data in the fields of accounting and finance.
This document sets out the details of the stream coursework requirements along with some
instructions and tips.
2. Coursework Submission
o Submission Deadline: Monday 13th January (2025), 12 pm
o Submission Location: online via Moodle
o Submission Documents:
• A Jupyter Notebook named AcF_351b_Python_Stream_Final_Exam.ipynb
• A Python file named submission.py (in the folder named py_format).
• A PDF version of the Jupyter Notebook after execution.
The project consists of three sections. Detailed instructions are in the Jupyter Notebook.
Section 1 primarily assesses the basic skills to process data in Python. You are asked to analyze
a dataset and answer questions regarding WiFi hotspot locations in NYC; Section 2 assesses
the generic programming skills, e.g., loops and conditionals, and basic data structures of
Python including lists, tuples and dictionaries; Section 3 evaluates the skills of analyzing and
interpreting the financial dataset. It requires both Python coding skills and a good
understanding of bond markets. The Jupyter Notebook walks you through a dataset of US and
UK corporate bond transactions between Jan 2015 to Dec 2017, and asks you to finish the
coding scripts as specified. After completing the Jupyter Notebook, you are required to
analyze the acquired dataset and answer questions regarding British bonds and Brexit. Note
that answers to short questions that exceed the maximum word limit will be SEVERELY
PENALIZED.
To generate the required PDF file, first run the entire Jupyter Notebook. Then, go to “File” -
>Print Preview -> Ctrl+P and print the page to PDF.
o Deliverables:
• Three files as specified above.
o Surgery sessions/office hours:
Week 5-10: Charles Carter C13 (appointment-only)
AcF 351b Career Skills in Accounting and Finance
Python for Data Analysis
Stream Assignment
1. Overview
Python for Data Analysis stream is designed to provide introductory programming knowledge to
students who have no or little prior programming experience. Throughout the ten sessions, this
module has covered Python language basics, scientific computing and SQL packages and introduction
to corporate bond markets. The assignment therefore is intended to give students the opportunity to
practice on what have learned from the course and encourage students to do independent work
towards writing code scripts to download and analyze data in the fields of accounting and finance.
This document sets out the details of the stream coursework requirements along with some
instructions and tips.
2. Coursework Submission
o Submission Deadline: Monday 13th January (2025), 12 pm
o Submission Location: online via Moodle
o Submission Documents:
• A Jupyter Notebook named AcF_351b_Python_Stream_Final_Exam.ipynb
• A Python file named submission.py (in the folder named py_format).
• A PDF version of the Jupyter Notebook after execution.
The project consists of three sections. Detailed instructions are in the Jupyter Notebook.
Section 1 primarily assesses the basic skills to process data in Python. You are asked to analyze
a dataset and answer questions regarding WiFi hotspot locations in NYC; Section 2 assesses
the generic programming skills, e.g., loops and conditionals, and basic data structures of
Python including lists, tuples and dictionaries; Section 3 evaluates the skills of analyzing and
interpreting the financial dataset. It requires both Python coding skills and a good
understanding of bond markets. The Jupyter Notebook walks you through a dataset of US and
UK corporate bond transactions between Jan 2015 to Dec 2017, and asks you to finish the
coding scripts as specified. After completing the Jupyter Notebook, you are required to
analyze the acquired dataset and answer questions regarding British bonds and Brexit. Note
that answers to short questions that exceed the maximum word limit will be SEVERELY
PENALIZED.
To generate the required PDF file, first run the entire Jupyter Notebook. Then, go to “File” -
>Print Preview -> Ctrl+P and print the page to PDF.
o Deliverables:
• Three files as specified above.
o Surgery sessions/office hours:
Week 5-10: Charles Carter C13 (appointment-only)