View on GitHub

Instagram-Behavioural-Analysis

Python module for scraping and analysing Instagram.

Analysis

The charts below show info about the categories of stories made between Sat Oct 19 19:00:00 2019 and Sat Oct 26 19:00:00 in twenty cities.

This table shows for each city the number of stories, users and locations retrieved
City Stories Users Locations
London, United Kingdom 90680 60171 14376
New York, New York 74987 50591 13698
Paris, France 80702 50174 10994
Miami, Florida 30117 19217 4602
Barcelona, Spain 40968 25850 6439
Los Angeles, California 43804 32473 7518
Chicago, Illinois 34405 23008 6540
Toronto,Ontario 31517 20485 6547
Berlin, Germany 40832 25914 6654
Las Vegas, Nevada 25654 16092 3828
Madrid, Spain 44637 29453 7298
Amsterdam, Netherlands 36975 24460 3815
Sydney, Australia 15511 11512 2839
San Francisco, California 20263 14093 3775
San Diego, California 26467 17718 4829
Boston, Massachussetts 13125 9716 2219
Rome, Italy 72199 46650 10394
Rio de Janeiro, Rio de Janeiro 82296 56865 15028
Vancouver, British Columbia 9229 6460 2351
Milan, Italy 70329 46487 7736

Top categories

Select a number of categories, a period, day or week, and eventually a day. Then select one or more locations over the first chart to show the most popular categories in those locations during the week (or day), and select one location over the second chart to show the most popular categories in that location during the week (or day).



Checkins progress

Select one or more locations, a format, day or week, one or more categories (and eventually a day) to show the number of stories for those categories realized during the week (or day) in those locations. In addition you can set normalized mode showing values from 0 to 1, depending on the total number of stories made in a location