This project was done on Jupyter Notebook, mainly based on Python. In this project, I've found some correlations between different fields of the given dataset.
- Data was taken from the movie dataset.
- The dataset: movies.csv.zip
- The project is mainly based on pandas(for data cleaning), numpy(for statistics), seaborn and matplotlib(for data visualization).
- Some of the visualizations from the project:
This is the first project I did for my portfolio, where I built dashboards using a masculinity dataset.
- Data was taken from the masculinitysurvey dataset.
- The dataset: Masculinity survey.zip
- Cleaned dataset: Cleaned_masculinity_dataset.csv, mainly this dataset was used.
- A portion of Cleaned dataset was used while building the project.
- This is how my dashboards look like:
Do check it out!
This project consists of well-organised dashboard where I tried to visualize the avg. moving rides in London in different climatic conditions such as Temperature, Windspeed and weather.
- Total Rides between the selected range where dashboard automatically detect the min. and max. range for months and display visualization accordingly.
- Tried to pullout the use of "Tooltips" with finese so that whenever you hover over the timeline graph, you'll see two nice and clean barcharts for the selected range.
- Applied clear filters, so just play with it and enjoy!!!
- Dataset: London Bike rides Dataset (From Kaggle)
You can download the required dataset from the following website-> https://ourworldindata.org/covid-deaths
- In this file, I've dropped some unnecessary fields from the .csv file by using pandas.
- Divided the original dataset into two .csv files:
- CovidDeaths.csv
- CovidVaccinations.csv
You can find these datasets here- Divided covid datasets.zip.
Since I love python, I used Jupyter Notebook here. You can directly execute this step using MS-Excel.
- Performed some basic operations and functions so that data can be easily explored and visualized by Tableau.
- Extracted 4 sub .csv files
- Table1_GlobalNumbers.csv,
- Table2_DeathsInContinent.csv,
- Table3_HighestInfectionRateComparedPopulation.csv and
- Table4_HighestInfectionRateComparedPopulationpt2.csv
- By using the 4 csv files extracted by SQL, I've visualized them on a single dashboard. Explore and play around with it. Thank you!
- Glimpse to that dashboard->
- Dataset: Nashville Housing Data for Data Cleaning.xlsx.zip
- Cleaned this dataset by using MySQL.
- Used CTE's.
- Atlast, deleted unused columns in the given dataset.
The aim for this project is to find out the Daily avg. House Sales in King County, Washington between the May 2014 and May 2015. I have tried to categorize the house as per the views such as excellent, good, fair, etc. and conditions such as Fair-Badly worn, poor-worn out etc. with the help filters, in different zip codes.
- Dataset:- HouseData.xlsx
- Developed a Tableau dashboard to visualize Daily avg. House sales at specific zip codes.
- Distributed the house price, Bedrooms and Bathrooms using histograms followed by their views and conditions heatmap filtered by yr built, sqft. living and a nice calendar.