In this respository, I showcase projects in which I worked on in my Udacity Data Analyst Nanodegree Course.
In this course, I developed good proficiency in Python and it's data analysis libraries (such as NumPy, Pandas, Matplotlib) and SQL. Also, I learnt the act of organizing data, uncovering patterns and insights, drawing meaningful conclusions and clearly communicating ciritical findings. A summary of the projects is given below:
In this project, I was introduced to SQL and how to download data from a database. As such, I analyzed local (Helsinki, Madrid, Milan) and global temperature. Making comparisons between the choosen local temperature and the overall global temperature trends.
In this project, my task is to investigate the dataset and posed questions that can be that could be answered by the available data, and investigated it using NumPy and pandas. Then created a report to provide answer to questions.
In this project, I worked on the result of an A/B test run by an e-commerce website, cleaned the data and applied statistical techniques (such as probability, hypothesis testing, regression approach etc.) to answer question about the data. THe result from this statistical technique would give an insight to understand if the company should implement a newly lunched web page, keep the existing page or run the experiment for a longer time to make their decision.
Using Python and its libraries, I gathered data for WeRateDogs Twitter archive from a variety of sources and in a variety of formats. Query the Twitter API for each tweet's JSON data using Python's Tweepy library and store each tweet's entire set of JSON data in a file called tweet_json.txt file. Thereafter, assessed its quality and tidiness, then clean it and produced visualization to gain insight from the dataset.
For this project, I downloaded the Bay Wheels's trip data from their website cleaned the data and used Python's data visualization tools to systematically explore the dataset for its properties and relationships between variables.Then, a created a slide deck to communicate the findings.
Here is a link to a detailed content of the course syllabus.