Today was a day of deep dives. I got my hands dirty with implementing the Random Forest regression model on our U.S. counties’ health metrics data. The objective was clear: to make sense of the complex relationships between various health indicators like diabetes rates, obesity levels, and physical inactivity. But…
The analysis begins with data cleaning and standardization, followed by k-means clustering to group counties based on their health metrics. The optimal number of clusters was determined to be four. Various visualizations were created to explore these clusters. Key Findings 1. Cluster-wise Box Plots Box plots were used to visualize…
After exploring the states with the highest and lowest rates of diabetes, obesity, and physical inactivity, I delved deeper to understand how states could be grouped based on these health metrics. Through clustering analysis, I found some intriguing patterns that might offer valuable insights for public health interventions. The Power…
I analyzed data from the Centers for Disease Control and Prevention (CDC) for the year 2018 to identify states that are most affected by these conditions. My Findings on Geographic Variations: Top 5 States with the Highest Rates of Diabetes: Through my analysis, I found that the states most affected…
This post aims to provide a statistical overview of that dataset, offering insights into the average rate of diabetes, its variability, and the range of percentages across counties. Key Statistical Findings: Count: A total of 3,142 counties were surveyed in 2018. Mean: The average rate of diabetes was approximately 8.72%…
In today’s analysis, I begins with an introduction to the analysis and focuses on exploring relationships between diabetes, obesity, and inactivity rates. The data is loaded from an Excel file, and necessary libraries are imported. Step 1: Uploading the Excel File The analysis starts by prompting the user to upload…
Hey, guys! So, let’s talk about something we all encounter but might not always understand—data and numbers! I know, I know, just hearing terms like “multi-linear regression” or “R-squared” might make you want to run for the hills. But trust me, they’re not as scary as they sound. In fact,…
Today, I took a close look at the 2018 health data from the CDC, focusing on rates of Diabetes, Obesity, and Inactivity across different U.S. counties. First, I got a sense of the average rates and how much they vary from place to place. Next, I looked at how “out…
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