Contains a jupyter notebook that answers the following questions:
- Which country had the highest mean meat consumption in tons? Which country had the highest mean meat consumption per capita?
- In what year was the most beef per capita consumed worldwide? What is the median worldwide beef consumption per capita? In what year was beef consumption closest to the worldwide median?
- Based on our data, what is the average Brazilians preferred meat?
- What type of meat has seen the greatest rise in consumption? Which has seen the lowest?
- How well can we predict the beef consumption by kg per capita?
- China consumed the most meat in tons while the United States consumed the most meat per capita.
- The most beef per capita worldwide was consumed in 2007. The median yearly beef consumption per capita worldwide was 6.682 kg/capita. World beef consumption per capita approximated the median in 2002 and 2004.
- The average Brazilian's preferred meat between 1990 and 2019 was poultry.
- Poultry has seen the greatest rise in consumption and beef has seen a slight decline in consumption worldwide.
- The model used predicted beef consumption with an R2 of 0.66728 against the training data and an R2 of 0.65868 against the test data. Not bad!
The data was sourced from the Organization for Economic Co-operation and Development (OECD) website: https://data.oecd.org/agroutput/meat-consumption.htm
This repository was created to satisfy the Udacity Data Science Nanodegree Project 1 requirement.
- Udacity_Project_1.ipynb : a Jupyter Notebook containing the analysis
- .ipynb_checkpoints/ : a directory containing the jupyter notebook saves
- meat_consumption.csv : data
- Python 3.8.3
- Python Packages (i.e. numpy, pandas, seaborn, matplotlib, sklearn.linear_model, sklearn.model_selection, and sklearn.metrics)
- Jupyter notebook
- Organization for Economic Co-operation and Development (OECD) website for dataset: https://data.oecd.org/agroutput/meat-consumption.htm