Source
https://www.kaggle.com/code/sarmaz/global-food-prices-data-analysis-and-visualize/data
Project
In this project, you will perform EDA, visualize and make calculations from African food prices data using matplotlib, seaborn, and pandas. The dataset values were obtained from the Source above.
Information
Data includes country, locality, market, goods purchased, price & currency used, quantity exchanged, and month/year of purchase.
Column Description
adm0_id: country id
adm0_name: country name
adm1_id: locality id
adm1_name: locality name
mkt_id: market id
mkt_name: market name
cm_id: commodity purchase id
cm_name: commodity purchased
cur_id: currency id
cur_name: name of currency
pt_id: market type id
pt_name: market type (Retail/Wholesale/Producer/Farm Gate)
um_id: measurement id
um_name: unit of goods measurement
mp_month: month recorded
mpyear: year recorded
mpprice: price paid
mp_commoditysource: Source supplying price information
Task
- Perform Data Cleaning and Transformation
- Perform EDA on the dataset
- List 5 research questions from the dataset
- Analyze the trends in the dataset to answer the questions listed
- Visualize the trends in the dataset
- All steps should be clearly described in your notebook
- Be sure to use the full range of analytics options learnt in class
Submission
Upload the completed notebook to your personal github account, thereafter send the link with your Full Name, and Title to the submission email: jonathanogwumike@gmail.com
Bonus: Create a streamlit App at the end of your analysis and share in a separate github repository