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About Devanshu Gupta's portfolio

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: image image

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:

image image image

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)

image image

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:
  1. CovidDeaths.csv
  2. 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
  1. Table1_GlobalNumbers.csv,
  2. Table2_DeathsInContinent.csv,
  3. Table3_HighestInfectionRateComparedPopulation.csv and
  4. 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-> image

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.

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