As a coffee lover, I have always been interested i learning new things about coffee, such as use new methods to do my coffe, try different spices, experiment new flavors...
When I was looking for a new dataset to practice my skills I found a data from the "Great American Coffee Taste Test" and I falled in love with it, so I decided to use this to discover interesting things about other coffee drinkers.
Bellow there are some things that I have learned and consider important.
"As it’s thought that coffee originated in Ethiopia, it’s also believed it made its way north, across the red sea into Yemen in the 15th Century. It then started to be grown here in the Yemeni district of Arabia, and by the 16th century it was known in Persia, Egypt, Syria, and Turkey.
It was immensely popular for its qualities to help improve alertness and wakefulness, allowing people to devote more time to spiritual matters and praying.
The world’s first coffee house was opened in Constantinople in 1475, now known as Istanbul. Coffee was drunk at home as part of the daily routine, as well as to show hospitality to guests. Outside of the home, people visited coffee houses to not only drink coffee but to engage in conversation, listen to music, watch performers, play chess, gossip and catch up on news. Without the modern technologies we have today, coffee houses quickly became the epicentre for exchanging and gaining information. They were often referred to as “Schools of the Wise.”
And with thousands of pilgrims visiting Mecca each year from all over the world, knowledge of this “wine of Araby”, which it quickly became referred to, began to spread."
Investigate and discover common coffee preferences.
The dataset was obtained at Kaggle, after downloading I started to clean and manipulate all the data with python and some librarys like Pandas, Numpy and Matplotlib to ease visualization and get better results.
Downloaded a dataset from Kaggle.
Availabel at: https://www.kaggle.com/datasets/joebeachcapital/coffee-taste-test
The data was very dirty so it wouldn't be efficient to use her without a proper change to prepare it for graphics and visualization.
After cleaning the data it's important to load the updated version, only then we can start to use visualization tools