Python数据分析代写 | Assessment 3 and 4 overarching outline


Assessment 3 and 4 overarching outline:
The goal of these projects is the implementation of a full data analysis workflow using python with the combination of
SQLite database persistence.
You are asked to select a domain of interest to you. You may re-use some of the datasets from the previous assignment.
Research what kinds of data sources are available for your selected domain. Subsequently, you are asked to (1) formulate
questions that you would like answered, (2) acquire datasets from at least two different sources (at least one source must
be dynamic, i.e. is web-scraped or is retrieved from a web API), (3) wrangle the data into an usable format and perform
EDA, (4) integrate datasets into one, (5) persist the data into a SQLite relational database with a suitable schema, (6)
perform group-by queries, pivot tables, cross-tabulation of the data to answer your research questions, together with a rich
set of visualisations.

Links to various dataset and web API repositories are provided on Stream. The analysis workflow you are asked to
perform is illustrated in the diagram
Data Acquisition Data Wrangling Data Integration Data Persistence Data Analysis
Static dataset Transform Concatenation SQLite Group-by
Web API Clean Merging csv Pivot tables
Web Scraping Impute DB Schema Cross-tabulation
Other(?) User-defined functions Visualisation

Assessment 4 Requirements:
Your research report must be in a Jupyter Notebook format and thus executable and repeatable. Clearly introduce your
problem domain, articulate your research questions and provide an executive summary at the beginning.

You must document and explain the reasoning behind the coding steps you are taking and provide explanations of all your
graphs and tables as is appropriate. Make sure you label all aspects of your graphs.

The activities listed under the five stages in the workflow diagram above are a guide only. This means that operations like
group-by statements as well as pivot tables could be a part of the ‘Data Wrangling’ phase as EDA, and not only a part of
the data analysis phase. Finally, please run your report through an external spell checker.



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