Project_gender_biases: An analysis to figure out if TED Talks reinforce gender biases or work against it
This repository contains one of the projects delivered during the Data Analytics bootcamp, at Ironhack Barcelona (March,2021). The students had no pre assigned theme.
This project consists in analysing all of the TED Talks database, and figure out if TED helps to reinforce, or to fight against gender biases. Gender biases are "unintentional and automatic mental associations, stemming from traditions, norms, values, culture and/or experience". Basically, it is was makes people (ang google) associate certain professions/occupations with men/women. My analysys consists in findig out if TED talks have enough women talking about topics usually perceived as masculin, and how is this proportion portraited over time. For the analysis, I had to find the data, clean it, create new columns and delete some others, and perform the analysis. Tableau was also used, for data visualization.
A more detailed explanation pf the project and process can be found in the following article: https://marianadonabella.medium.com/are-ted-talks-contributing-to-enforce-gender-biases-e8d2baf25925
The general workflow can be splitted into 5 main steps:
First step: deciding topic and exploring information Second step: gathering dataset Third step: exploring data with Pandas and Tableau Fourth step: creating column "gender", and columns of topics Fifth step: analysis and visualization
In this repository you'll find:
- Folder "data": data used for bulding the analysis
- Folder "code": document "main" with main analysis