In this project, analyze local and global temperature data and compare the temperature trends to where you live to overall global temperature trends. The goal will be to create a visualization and prepare a write up describing the similarities and differences between global temperature trends and temperature trends in the closest big city to where you live.

Report

In this project, use Python to explore data related to bike share systems for three major cities in the United States—Chicago, New York City, and Washington. Write code to import the data and answer interesting questions about it by computing descriptive statistics. Also write a script that takes in raw input to create an interactive experience in the terminal to present these statistics.

Python Code

In this project, conduct your own data analysis and create a file to share that documents your findings. You should start by taking a look at your dataset and brainstorming what questions you could answer using it. Then you should use pandas and NumPy to answer the questions you are most interested in, and create a report sharing the answers. You will not be required to use inferential statistics or machine learning to complete this project, but you should make it clear in your communications that your findings are tentative. This project is open-ended in that we are not looking for one right answer.

Dataset used: No-Show Appointments

In this project we have analyzed the data associated with the medical appointments in Brazil and the focus is on question whether or not patients show up for their appointments. Also, we were interested in finding the factors that were important for us to know in order to predict if a patient will show up for their scheduled appointment.

Jupyter Notebook

For this project, you will be working to understand the results of an A/B test run by an e-commerce website. The company has developed a new web page in order to try and increase the number of users who "convert," meaning the number of users who decide to pay for the company's product. The goal is to work through this notebook to help the company understand if they should implement this new page, keep the old page, or perhaps run the experiment longer to make their decision.

Jupyter Notebook

In this project, investigate a classic phenomenon from experimental psychology called the Stroop Effect. You will learn a little bit about the experiment, create a hypothesis regarding the outcome of the task, then go through the task yourself. You will then look at some data collected from others who have performed the same task and will compute some statistics describing the results. Finally, you will interpret your results in terms of your hypotheses.

Jupyter Notebook

In this project, use R and apply exploratory data analysis techniques in a selected dataset to discover relationships among multiple variables, and create explanatory visualizations illuminating distributions, outliers, and anomalies.

R File

In this project, the tasks are as follows:

• Data wrangling, which consists of:
  • Gathering data (downloadable file in the Resources tab in the left most panel of your classroom and linked in step 1 below).
  • Assessing data
  • Cleaning data
• Storing, analyzing, and visualizing your wrangled data
• Reporting on 1) your data wrangling efforts and 2) your data analyses and visualizations

Wrangling Report
Analysis Report

For the final project, create an explanatory data visualization from a data set that communicates a clear finding or that highlights relationships or patterns in a data set. Your work should be a reflection of the theory and practice of data visualization, and your final deliverable will be a write up along with a Tableau Public workbook.

Report