My Projects (Data Analysis)
The above projects are parts of my Data Analyst Nanodegree (Bertelsmann Udacity Data Science Scholarship Program), and here is a short description of each one:
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Explore Weather Trends:
- In this project, I analyzed local and global temperature data and compared the temperature trends of a city to overall global temperature trends. I used SQL to extract data from the temperatures database, created visualizations (using Excel) and prepared a write up describing the similarities and differences between global temperature trends and temperature trends in the closest big city to where I live.
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Bike Share Analysis:
- In this project, I explored data related to bikeshare systems for three major bikeshare systems in the United States: New York City, Chicago, and Washington, DC, performed data wrangling to unify the format of data from the three systems, wrote code to compute descriptive statistics and used visualization as part of the exploration. In this analysis, we answered several questions such as: Which city has the highest number of trips? Which city has the highest proportion of trips made by subscribers? Which city has the highest proportion of trips made by short-term customers? What is the average trip length for each city? What proportion of rides made in each city are longer than 30 minutes?...
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Investigate a Dataset:
- In this project, I conducted my own data analysis using a random dataset (data regarding 100,000 medical appointments in Brazil). I started by taking a look at the dataset and brainstorming what questions I could answer using it. Then used pandas, NumPy and Matplotlib to answer the questions I am most interested in, and created a report sharing the answers. This analysis highlighted several factors, which will help in predicting if a patient will show up for his/her scheduled appointment? I went through the data analysis process: Asking questions, Wrangling the data, Performing EDA, Drawing conclusions and Communicating the results.