Data Analysis - Final Project

Research Notes

• Data sources

  • Gender Statistics (World Bank): https://databank.worldbank.org/source/gender-statistics

  • ESG Data (World Bank): https://databank.worldbank.org/source/environment-social-and-governance-(esg)-data

• Key variables of interest (Will add more in the next steps)

  • Access to Electricity (EG.ELC.ACCS.ZS)

  • GDP Growth (NY.GDP.MKTP.KD.ZG)

  • Ratio of female to male labor force participation rate (SL.TLF.CACT.FM.ZS)

• Key Regions of Interest

  • South Asia (IDA & IBRD) –> Country code: TSA

  • Sub-Saharan Africa (excluding high income) –> Country code: SSA

Basic Data Visualization

Attaching package: 'dplyr'

The following objects are masked from 'package:stats':

    filter, lag

The following objects are masked from 'package:base':

    intersect, setdiff, setequal, union

── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ forcats   1.0.0     ✔ readr     2.1.5
✔ lubridate 1.9.3     ✔ tibble    3.2.1
✔ purrr     1.0.2     
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

Percentage of Population with Access to Electricity:

South Asia (IDA & IBRD) and Sub-Saharan Africa (excluding high income)

Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
ℹ Please use `linewidth` instead.

Access to electricity and Labor Force Participation Rate