Individual : Power BI Take Home Statistics

Java Python Individual Assignment: Power BI Take Home Assignment

Description

Using Microsoft PowerBI, students are expected to:

l  work with a given dataset.

l  explore the given dataset.

l  clean the data, rearrange it, transform. it if required.

l  create multiple visualisations using Microsoft PowerBI to develop interesting insights.

l  document their insights generated form. the visualisations and report them.

l  critically analyse those insights and recommend related actions or interventions.

The provided dataset represents sales data from a supermarket chain. It includes detailed transaction records including city, customer type, customer gender, product line, date, time, unit price, quantity,total sales, cost of goods sold, and rating. Students are required to analyze this dataset and create meaningful insights, aiming to help the supermarket chain improve its operations, understand customer behavior, and optimize its product offerings.

This assignment is worth 20% of your assessment for the subject. This assignment is due at 16:00 PM on 4 October 2024.

Files to be submit:

1.   Report File.

2.   PBI Visualisation File.

The report file must contain the following components:

1.   Executive  Summary: It  is  a  clear, well-structured,  evidence-based  summary  of your findings, which come from the created visuals of the provided sale data (max. 150 words).

2.    Descriptive Analysis of Sale Data with PowerBI.

2.1 Data Transformation: As we have discussed in the lectures, data are not always in the best shape or quality, and suitable data transformations can reveal interesting relationships. Further, data transformation is also vital for identifying data quality issues. Please report  any  data transformation  (data pre-processing)  you  conducted before visualizing data (max. 300 words).

2.2 Sales Trend and  Seasonality Dashboard: Prepare a dashboard that analyses sales trend overtime and identify any seasonal patterns or peak periods. Please use different types of visuals to compare, show relationships, composition, and distributions between the variable of your choice. Your dashboard should convey main insights, should have a story, and use different types of visuals. The dashboard report should include between 5-8 items (at least 4 visuals, and may include tables, and tiles). Don’t use the Key influencer function or any other automated tools or functions. You need to demonstrate that you can use PowerBI effectively. You should insert screenshot ofthe dashboard in this report. In addition, you need write main insights by referring to the provided dashboard (max. 150 words).

2.3 Customer Demographics  and Preferences Dashboard: Prepare a dashboard that represents the demographics of the customers and their preferences for products and payment methods. Please use different types of visuals to compare, show relationships, composition, and distributions between the variable  Individual Assignment: Power BI Take Home AssignmentStatistics of your choice. Your dashboard should convey main insights, should have a story, and use different types of visuals. The dashboard report should include between 5-8 items (at least 4 visuals, and may include tables, and tiles). Don’t use the Key influencer function or any other automated tools or functions. You need to demonstrate that you can use PowerBI effectively. You should insert screenshot of the dashboard in this report. In addition, you need write main insights by referring to the provided dashboard (max. 150 words).

2.4 City Performance and Product Profitability Dashboard: Prepare a dashboard that evaluates the performance of different cities and profitability of various product lines. Please use different types of visuals to compare, show relationships, composition, and distributions between the variable of your choice. Your dashboard should convey main insights, should have a story, and use different types of visuals. The dashboard report should include between 5-8 items (at least 4 visuals, and may include tables, and tiles). Don’t use the Key influencer function or any other automated tools or functions. You need to demonstrate that you can use PowerBI effectively. You should insert screenshot of the dashboard in this report. In addition, you need write main insights by referring to the provided dashboard (max. 150 words).

3. Discussion of the Results and Conclusion. After conducting a through visual analysis of the sale data,please summarize key findings that help executives understand the dynamics of the supermarket chain, and make three suggestions to improve/expand business operations (max. 300 words).

4.   References: Please include all the references (minimum 5 references) that you have citied in your report.

Submission Guidelines:

This assignment is due at 16:00 PM on 4 October 2024. For late submissions, please refer to guidelines outlined on ECP:

https://course-profiles.uq.edu.au/course-profiles/BISM7233-60203-7460

You are required to submit an electronic version of your work through Blackboard (see the Assessment Link on Blackboard and look for the link labelled Assignment Submission. You will have two opportunities to submit your documents. So, in case you make a mistake on your first submission or wish to revise your assignment, you can re-submit it once. Please ensure that you put your report through Turnitin BEFORE submitting it to Blackboard, to make sure that your assignment is plagiarism free. By submitting your work in this manner, plagiarism is checked for you, and you will be able to see if you have any issues with this in your work. Use Turnitin as many times as you need to fix any similarity issues before the due date (obviously, given that you are working in a pre-specified report, we are only concerned about the similarity of your answers). Also, by submitting the Assignment via Blackboard you attest that the Assignment is your own work.

Please compress PBI file, should include all visuals, in a zip file. Submit the Zip file along with your report on Blackboard assignment and submit your report on Turnitin         

<think>嗯,用户想了解如何在Python类中初始化一个大小为24的X_ev列表。首先,我需要确认用户的具体需求。X_ev可能代表某种事件列表或者参数数组,大小设为24可能对应24小时或其他24个元素的情况。用户可能希望这个列表在类实例化时自动初始化,可能有默认值或者留空。 接下来,我得考虑如何构建这个类。基本结构是定义一个Individual类,在__init__方法中初始化X_ev。根据用户需求,列表的大小固定为24,所以需要确保初始化时生成24个元素。可能的初始化方式包括全零、空列表,或者随机值。用户可能没有说明默认值的类型,所以需要提供几种常见的例子,比如全零、随机数填充,或者由参数指定。 然后,我需要检查是否有潜在的优化或注意事项。例如,如果用户之后需要动态调整列表大小,是否应该加入校验机制,确保长度始终为24。或者是否需要属性装饰器来控制赋值操作,防止列表被意外修改。另外,考虑到用户可能想改进现有的类,可能需要提到如何添加方法或扩展功能,比如添加元素、验证长度等。 用户提供的引用中有关于数据读取、遍历和模型结构的内容,虽然和类初始化不直接相关,但可能需要注意资源管理或数据结构的高效使用。比如,引用[1]中的data_block.size处理,可能提示在初始化列表时考虑内存分配的问题,但Python列表动态分配,可能不需要特别处理。引用[3]中的迭代器使用,或许可以建议在类中添加迭代功能,方便遍历X_ev的元素。 最后,生成相关问题时要覆盖类设计的其他方面,如可变性、默认值选择、数据校验和方法扩展,帮助用户深入思考不同的使用场景和潜在改进方向。</think>### Python类中初始化X_ev列表的实现 以下是包含`X_ev`列表初始化的`Individual`类定义,其中`X_ev`被固定为长度24: ```python class Individual: def __init__(self, initial_values=None): # 初始化24元素的X_ev列表 self.X_ev = [0] * 24 # 默认全零初始化 # 如果提供初始值则覆盖 if initial_values is not None: if len(initial_values) == 24: self.X_ev = list(initial_values) else: raise ValueError("初始值长度必须为24") ``` ### 关键设计解析 1. **固定长度约束** - 通过`[0] * 24`确保列表初始长度为24 - 输入参数校验保证最终列表长度正确[^3] 2. **灵活的初始化方式** - 默认生成全零列表:`Individual()` - 支持自定义初始化:`Individual([1]*24)` 3. **数据完整性保护** - 当传入参数长度不符时触发`ValueError` - 强制类型转换`list(initial_values)`防止原数据被意外修改 ### 优化建议 1. **添加随机初始化方法** ```python import random def random_init(cls): instance = cls() instance.X_ev = [random.random() for _ in range(24)] return instance ``` 2. **增加长度校验装饰器** ```python def validate_length(func): def wrapper(self, value): if len(value) != 24: raise ValueError("X_ev必须包含24个元素") return func(self, value) return wrapper class Individual: @validate_length def __init__(self, initial_values=None): ... ``` ### 应用示例 ```python # 创建默认实例 ind1 = Individual() print(len(ind1.X_ev)) # 输出:24 # 带参数初始化 try: ind2 = Individual([i%2 for i in range(24)]) except ValueError as e: print(e) ```
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