Contains projects needed to complete Udacity's Data Analyst Nanodegree Program
The first project is analyzing bike rental data. Data Wrangling, Exploratory Data Analysis, and Data Visualizations were performed on Bay Area Bike Share data to come up with conclusions about bike usage.
- Project: Analyze Bay Area Bike Share Analysis
Use descriptive statistics and a statistical test to analyze the Stroop effect, a classic result of experimental psychology. A good intuition for the data was provided and use of statistical inference to draw a conclusion based on the results was performed.
- Project: Testing a Perceptual Phenomenon
The Titanic dataset was investigated using NumPy and Pandas. The entire data analysis process was completed by first posing a question and finishing by sharing my findings.
- Project: Investigate a Data Set
OpenStreetMap data for Washington, DC USA was used to apply data munging techniques, such as assessing the quality of the data for validity, accuracy, completeness, consistency and uniformity, for cleaning purposes. SQL was used.
- Project: Wrangle OpenStreetMap Data
Use R and apply exporatory data analysis to explore The Wine Quality for White Wines dataset created by Paulo Cortez. This dataset contains quantitative variables such as acidity and density and the qualitative variable of quality as judged by wine experts.
Play detective and put your machine learning skills to use by building an algorithm to identify Enron Employees who may have committed fraud based on the public Enron financial and email dataset.
- Project: Identify Fraud from Enron Email
Create a data visualization from a data set that tells a story or highlights trends or patterns in the data. Use d3.js to create the visualization. Work should be a reflection of the theory and practice of data visualization, such as visual encodings, design principles, and effective communication.