This repository is an insightful Capstone project - T51_capstone project VII.ipynb created by Chayada.
The project uses the UsArrests.csv dataset, sourced from Kaggle, to delve into Exploratory Data Analysis (EDA), preprocessing, Principal Component Analysis (PCA), and clustering techniques.
The UsArrests dataset presents 50 rows and 5 columns, including variables such as city name (object data type), murder and rape (float), assault (numeric), and urban population (numeric).
In this project, I performed an analysis of the data, utilizing various visualization tools such as histograms, scatterplots, boxplots, and a correlation heatmap to gain a deeper understanding of the dataset.
To further enhance the analysis, I applied standardization, PCA, and biplot, and employed both Hierarchical and KMeans clustering techniques. The analysis results also provide valuable insights into the relationships and patterns present within the data.
If you're interested in exploring advanced data analysis techniques and their applications, this repository is the perfect starting point!