- Source: http://www.ign.com/reviews/games
- Pretty clean data
- Packages Used: ggplot2, dplyr, grid
- Source: https://www.kaggle.com/jboysen/injured-workers
- Packages Used: highcharter, plotly
- Acknowledgement: https://www.osha.gov/severeinjury/index.html
- Blog link: https://ashishtele1992.wordpress.com/2018/05/15/the-dangerous-places-to-work-in-the-usa/
- Source: https://www.kaggle.com/START-UMD/gtd
- Data from 1970 to 2016
- Packages Used for visualization: ggplot2, highcharter
- Packages used for text analysis: tm, tidytext
- Analysis is focused around India
- Acknowledgemet: http://start.umd.edu/gtd/about/GTDTeam.aspx
- Source: https://www.kaggle.com/caicell/zomato-india-restaurants-eda
- Zomato Restaurants data
- Data analysis for strategic implementation (India)
- Still working on the dataset
- Source: http://archive.ics.uci.edu/ml/datasets.html?task=cla&area=&type=&view=list
- Gender classification
- Tweet text analysis (WIP)
- Source: https://takeout.google.com/settings/takeout?pli=1
- Data collected from my devices
- Blog link 1: https://ashishtele1992.wordpress.com/google-knows-more-about-you-than-you-think-part-1/
- Blog link 2: https://ashishtele1992.wordpress.com/google-knows-more-about-you-than-you-think-part-2/
- Source: https://volcano.si.edu/list_volcano_holocene.cfm
- Acknowledgement: http://www.makeovermonday.co.uk/data/
- Make over Monday (week 27)
- Source: https://www.whatsthecap.com/nba/salary-cap/
- Acknowledgement: http://www.makeovermonday.co.uk/data/
- Make over Monday (week 29)
- Source: https://volcano.si.edu/list_volcano_holocene.cfm
- Acknowledgement: http://www.makeovermonday.co.uk/data/
- Make over Monday (week 28)
- Source: https://www.kaggle.com/payel58/dataset-for-hotels-in-indian-cities
- Packages used: dtplyr, ggplot etc
- Interactive Power BI report for quick analysis
- Packages used: forecast, dplyr, Xgboost etc.
Thank you!!