This *intermediate* level data set has 214 rows and 10 columns.
The data set provides details about 6 types of glass, defined in terms of their oxide content (i.e. Na, Fe, K, etc).
This data set is recommended for learning and practicing your skills in **exploratory data analysis**, **data visualization**, and **classification modelling techniques**.
Feel free to explore the data set with multiple **supervised** and **unsupervised** learning techniques. The Following data dictionary gives more details on this data set:
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### Data Dictionary
| Column Position | Atrribute Name | Definition | Data Type | Example | % Null Ratios |
| 10 | Fe | Fe: Iron (unit measurement: weight percent in corresponding oxide) | Quantitative | 0.11, 0.14, 0.00 | 0 |
| 11 | Type of Glass | Glas Type (1: building_windows_float_processed, 2: building_windows_non_float_processed, 3: vehicle_windows_float_processed, 4: vehicle_windows_non_float_processed, 5: containers, 6: tableware, 7: headlamps) | Quantitative | 2, 5, 7 | 0 |
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### Acknowledgement
This data set has been sourced from the Machine Learning Repository of University of California, Irvine [Glass Identification Data Set (UC Irvine)](https://archive.ics.uci.edu/ml/datasets/Glass+Identification).
The UCI page mentions USA Forensic Science Service as the following as the original source of the data set.
