Coffee Market Analysis

Data manipulation scripts to support my Tableau vizualization of coffee market data from the International Coffee Organization.

The /src/data folder within this repo contains two python scripts:

1. etl_functions.py contains functions that reshape and manipulate excel data.
2. make_dataset.py utilizes the functions in etl_functions.py to transform the raw excel spreadsheet data into a tidy format for use in Tableau.

Project Organization

├── LICENSE
├── Makefile           <- Makefile with commands like `make data` or `make train`
├── README.md          <- The top-level README for developers using this project.
├── data
│   ├── external       <- Data from third party sources.
│   ├── interim        <- Intermediate data that has been transformed.
│   ├── processed      <- The final, canonical data sets for modeling.
│   └── raw            <- The original, immutable data dump.
│
│
├── references         <- Data reference document from the ICO, links to data sources.
│
├── requirements.txt   <- The requirements file for reproducing the analysis environment, e.g.
│                         generated with `pip freeze > requirements.txt`
│
├── setup.py           <- makes project pip installable (pip install -e .) so src can be imported
├── src                <- Source code for use in this project.
│   ├── __init__.py    <- Makes src a Python module
│   │
│   └── data           <- Scripts to download or generate data
│       ├── etl_functions.py
|       └── make_dataset.py
│
└── tox.ini            <- tox file with settings for running tox; see tox.readthedocs.io

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Project based on the cookiecutter data science project template. #cookiecutterdatascience