Question 1

The dataset used in this assignment contains information about shop customer information(which can be downloaded from Canvas), and its data dictionary is provided in Appendix 1.

For each question, Python codes in text format in Monospaced font (for example, Courier New, Lucida Sans Typewriter) must be provided as part of the answer in the main report. Screenshots or other formats of the codes are not permitted and doing so will attract a 10-mark deduction.

(a) Explain how to read the dataset and identify the dimensions of the dataset with Python program. State the answer and discuss the rationale. [No more than 200 words (including in-text citation, excluding Python code)]

(b) Discuss why it is necessary to handle missing values. Use Python program to identify the variables with missing values in the given dataset. [No more than 200 words (including in-text citation, excluding Python code)]

(c) Propose ways to treat the missing data with Python and explain rationale(s) of the treatment(s). [No more than 200 words (including in-text citation, excluding Python code)]

(d) After missing data treatment in Question 1(c), analyse the dataset by providing three (3) charts and their corresponding tables using Python. Describe the insight  and highlight any interesting observations. Each chart and its corresponding table, Python codes and insights collectively carry 20 marks. The charts, tables and Python codes are to be provided as part of the answer in the main report. [No more than 500 words (including in-text citation, excluding Python code)]

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