CAROLINE WANJIKU:
MY PROJECTS PORTFOLIO

In this project, I explore the COVID-19 dataset, sourced from (ourworldindata.org). Using SQL server, I transfrom the raw data into meaningful formats through SQL-Scripting. I employ a combination of SQL queries and techniques to delve into the dataset so as to extract meaningful information from the raw data. These are the key steps included in the project; Data cleaning to handle duplicates and ensure accuracy, Exploratory Queries, Joins & Merges,Grouping & Aggregation, among others.

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After exploring the Covid-19 Dataset, in this project I create an interactive dashboard in Tableau, using the Covid-19 Vaccinations Dataset. Through this visualization, I uncover the global trends of the Vaccinations and most importantly, derive insigtful conclusions on how the Vaccinations were embraced accross the globe.

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This Excel data analysis project provides a comprehensive examination of the coffee sale trends over the years and also gives a holistic view of the global perfomance of different coffee types. Through out the project, I gather and examine the product data, sourced from kaggle.com, using Xlookup and Index Match. I also employ a combination of pivot tables and charts to show insights and forcast visualization, to end up with an interactive and dynamic Excel Dashboard.

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In this project, I utilize the power of data analysis and visualization to gain valuable insights in the perfomance and the average income of different data professionals accross different regions.The project involves transforming the data in Power Query, joining data from Multiple Sources. I also, incorporate geographical data to visualize the differences in salaries accross regions, identifying the professions with the highest pay based on their countries of residence; and finally building an interactive Bi-Dashboard from this data.

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In this project I scrape crucial data (Information on the Top Rated-250 movies) from the IMDB movies website using BeautifulSoup, Requests Module and Pandas library. The project includes my written Python code that I use to scrape the IMDB website, pulling in the data and finally loading it into a CSV file.

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This is a Python project in which I explore a crime dataset sourced from kaggle.com. The project, in it's entirety, involves sourcing this data, writing a python code on Jupyter Notebook, loading the data into a Python Pandas dataframe, and manipulating it accordingly. Finally, I build simple but interactive visualizations from this data using Matplotlib and Python Seaborn library.

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