#Exploratory Data Analysis (EDA) report

#Project Title: World Women Empowerment: Demystifying Preconceptions About Women's Roles in Society Subtitle: A Global Analysis of Female Representation in Top Positions and its Socio-Economic Impact (2004-2020)

#Project Overview This EDA explores the representation of women in top positions worldwide, using a vast dataset from The World Bank Group's Gender Statistics database. The dataset is from 2004 to 2023 and includes 103 key indicators related to women's empowerment, education and socio-economic factors across various countries.

#Audience Business leaders General public Women in Tech

This analysis is intended for Business leaders that are interested in understanding the business case for gender diversity and its impact on organizational performance, promoting and giving more opportunities for women to join important desicion making positions; and for the public in general, because it's also for the ones interested in global gender equality promotion and the socio-economic implications of women's representation in leadership, helping fighting preconcepts about the role of women in society Finally, it is intended to be particularly usefull or inspiring for women like us trying to thrive in a male-dominated tech world, and understand how valuable we are and how impactfull we can be in leadership roles.

#Data Description In this EDA, the dataset used was retreived from The World Bank Group (WBG) - World bank open data - https://data.worldbank.org/

It can be dowloaded here: https://databank.worldbank.org/reports.aspx?ReportId=153622&Type=Table

It was built with a selection of 103 women data related indicators, available in the Gender Statistics database, from the year 2004 until 2023.

With such a big quantity of available data about women in all the countries of the world, there are opportunities for a comprehensive and meaningful global analysis about who are women in each contry and about Women Empowerement. It consists in a rich dataset with multiple socio-economic factors with a broader context for gender equality, and with opportunities for in-depth analysis.

The dataset includes the following key variables from 2004 to 2023 for various countries, categorized as follows:

1 - Female representation metrics:

Number and share of female directors, business owners, sole proprietors. Female share of employment in senior and middle management. Proportion of women in ministerial level positions. Firms with female participation in ownership. Firms with female top managers.

2 - Socio-economic indicators:

GDP (current US$ and constant 2015 US$), GDP per capita. GNI per capita, Gini index. Government expenditure on education (% of GDP). Human Capital Index (HCI), for total population, female, and male.

3 - Education metrics:

High Educational levels(Bachelor's, Master's, Doctoral) for female, male, and total population. Female share of graduates in various fields (STEM, Business, Arts, etc.). Gross graduation ratio for tertiary education (female, male, total). School enrollment rates (tertiary) and gender parity index.

4 - Labor force and employment:

Employment to population ratio (female, male, total). Labor force participation rate (female, male, total). Labor force with advanced education (female, male, total). Self-employed individuals (female, male, total). Vulnerable employment rates (female, male, total).

5 - Business and legal environment:

Cost of business start-up procedures (% of GNI per capita). Start-up procedures to register a business. Women Business and the Law Index Score.

#Case description First analyse the perception of the role of the women per country, as we have a generous quantity of relevant data that can tell the story about women in each country. This will lead to a broader analyze of the representation of women in top positions globally and examine how this representation influences socio-economic factors, human capital indices, and overall country development. The project also aims to address and fight common misconceptions about the role of women in society by providing data-driven insights.

#Goal:

In this EDA we are going to focus on the following questions:

Potential research questions: 1- Which countries have the highest and lowest representation of women in top positions? 2 - Is there a correlation between GDP and the percentage of women in top positions?

#File organization: 1 - Report Overview - Introduction to the project, its objectives, and audience. 2 - Data Overview - Detailed description of the dataset, its sources, and the variables analyzed. 3 - Data cleaning and preparation - Steps taken to clean and preprocess the data for analysis. 4 - Visualization - Presentation of key findings through visualizations such as charts, graphs, and maps. 5 - Conclusions - Summary of key findings and insights derived from the analysis. Discussion of implications for gender diversity, socio-economic development, and future research directions.