Data_analytics_immersion

This repository contains Jupyter Notebooks from Achievement 6: Advanced Analytics and Dashboard Design. It also includes links to Portafolio and to Tableau Storytelling. The dataset "Conditions Contributing to COVID-19 Deaths, by State and Age, Provisional 2020-2023" from the CDC includes detailed records of COVID-19 deaths and contributing conditions, segmented by age group and state. In the analysis, I cleaned and prepared the data by handling missing values, filtering out non-informative rows, and converting data types for accuracy and efficiency. The analysis explored demographic and geographic patterns in COVID-19 death rates and contributing conditions, examined temporal trends, and identified key variables affecting mortality rates. These insights inform public health strategies and enable predictive modeling to target high-risk populations effectively. Jupyter Notebooks This repository contains Jupyter noteboos used in the Data Analysis exercises in chapter 6

Exercises includes the following activities:

Data cleaning:

• Handling missing Values
• Removing Duplicates
• Datatype Issues

Correlation Charts:

• Correlation Matrix

Geographic Visualization:

• Data wrangling
• Data cleaning -Ploting and Choropleth

Regression:

• Regression with differents variables

Machine Learning Part 2:

• The elbow technique
• k-means clustering

Sourcing & Analyzing Time-Series Data:

• Subsetting, wrangling, and cleaning time-series data -Time series analysis: decomposition -Testing for stationarity -Stationarizing the Federal Reserve Economic Data

Link to Data Visualization

Tableau Link

Portafolio

PDF File contains the Portafolio

Sourcing Open Data

Please Read PDF file "Exercise 6.1.pdf"