Projects for my Udacity Data Analyst Nanodegree
P1: Test a Perceptual Phenomenon
Analyzed the Stroop effect using descriptive statistics to provide an intuition about the data, and inferential statistics to draw a conclusion based on the results.
P2: Investigate a Dataset
Used NumPy and Pandas to analyze the Relative Age Effect in the american baseball.
P3: Wrangle OpenStreetMap Data
Used Python and MongoDB to wrangle a dataset extracted from https://www.openstreetmap.org, applying data munging techniques to assess the quality of the data for validity, accuracy, completeness, consistency and uniformity.
P4: Exploratory Data Analysis
Used R and exploratory data analysis (EDA) techniques to investigated the consumers business complaints in Brazil, exploring both single variables and relationships between variables.
P5: Identify Fraud from Enron Email
Used machine learning techniques to identify which Enron employees are more likely to have committed fraud based on public Enron financial and email dataset.
P6: Make Effective Data Visualization
Used Dimple.js to create polished data visualization from the consumer business complains dataset (used in the project P4). Applied the theory and practice of data visualization, such as visual encodings, design principles, and effective communication.
