Question

I'm doing a project on gender wage gap for data science, and I need help writing my outline for the code part of the project (not the actual code but just an outline of what I'll be doing, and I just need to help get that structured.
I'm using 2 data sets to find the highest and lowest gender wage gap in countries and which jobs in the US have the highest to lowest wage gap to help women find what jobs might be best money wise.

this is the outline were suppose to follow I just need help figuring out how to put the outline together.

• Determine Data Source-

• Import to analyze- use pandas to import the mind the gender wage gap (https://www.kaggle.com/datasets/mpwolke/cusersmarildownloadsgapcsv) source for countries and USA stats.)and (https://data.census.gov/cedsci/table?q=b24122&tid=ACSDT1Y2019.B24122)

• Clean up the the data

• Remove invalid and unnecessary data

• Structure data for effective analysis and reading

• Tool 1 (remember to think about what this actually entails)

• Analyze variables x and y for correlation, regression, outliers, patterns, etc.

• Commands

• Graph to illustrate information in an easy-to-read format

• Commands

• Summarize findings

• Tool 2

• Tool 3

• Comparison of results

Answer 1

I'll help

Answer 2

Hi and welcome to QuestionCove!

The outline provided with the assignment seems helpful. You say you need help with forming an outline for the code, yes? In that case, we'll need to figure out what it is you want your code to do.
It looks like you have your data sources, which is also good. In general, if we know how we want to analyze and use the data, that should help inform what your code will look like; that might be a good place to start

Like gamerboyy234 said, we'll try to help :)

Answer 3

Outline for Gender Wage Gap Project:

I. Introduction
A. Background information on gender wage gap
B. Purpose of the project
C. Objectives of the project

II. Data Collection
A. Determine Data Source
B. Import Data
1. Use pandas to import the data from the two sources: Mind the Gender Wage Gap (https://www.kaggle.com/datasets/mpwolke/cusersmarildownloadsgapcsv) for countries and USA stats and https://data.census.gov/cedsci/table?q=b24122&tid=ACSDT1Y2019.B24122 for job data.
C. Data Cleaning
1. Remove invalid and unnecessary data
2. Structure data for effective analysis and reading

III. Data Analysis
A. Tool 1
1. Analyze variables x and y for correlation, regression, outliers, patterns, etc.
2. Commands
3. Graph to illustrate information in an easy-to-read format
4. Commands
5. Summarize findings
B. Tool 2
C. Tool 3

IV. Comparison of Results
A. Compare results of Tool 1, Tool 2, and Tool 3
B. Identify the highest and lowest gender wage gap in countries
C. Identify which jobs in the US have the highest to lowest wage gap.

V. Conclusion
A. Summary of findings
B. Implications of the research
C. Recommendations for future research

VI. References