Our project for Data Visualisation created on Tableau, during our second year of engineering as part of our Data Science and Analytics Honours It is a detailed case study on Global School Dropout rates. This repository contains the Tableau file, the preprocessed dataset used in this case study, and screenshots regarding the visualisation
- School dropout rate, as the name suggests, is the percentage or rate of students failing to complete a particular schooL due to various reasons.
- Our Dataset consists of students dropping out globally, in their upper secondary i.e. 9th-12th standards.
- We have analyzed 106 countries which have been segragted in 3 groups based on their development:
- Least Developed (41)
- Less developed (57)
- More Developed (8)
- Our dataset has been taken from Kaggle
- It was curated by Komal Khetani and the data was sourced from various household surveys conducted by the UNICEF in various countries, in the past years.
- Link: https://www.kaggle.com/komalkhetlani/out-of-school-rates-global-data?select=Upper+Secondary.csv
- Niger has the highest total school dropout rate, female dropout rate and male dropout rate.
- Most countries have higher dropout rates in rural areas compared to urban areas. Some Exceptions are Eswatini, Kenya and South Africa.
- 63% of countries have more female dropouts than male dropouts. Some exceptions are Kiribati, Mongolia, Philippines, Moldova, Serbia, Thailand, Palestine and Tonga.
- India has a relatively low drop our rate i.e. 23 %. Female Dropout rate is 5% more than Male Dropout rate and Dropout rate in Rural Areas is 9% more than the dropout rate in Urban Areas.
| Sr No. | Name | git-profile | Roll No. | |
|---|---|---|---|---|
| 1. | Varshaah Karkala | varshaah.k@somaiya.edu | varshaah2407 | 16010120193 |
| 2. | Shruti Tyagi | shruti.tyagi@somaiya.edu | shrutityagi4102 | 16010120202 |
