Skip to main content

///

Project description

Final-Project-JEM207

Final project for JEM207 Data Processing with Python We scrape from oscars.org site historical datasets of every nominees for the following 4 awards:

Best Picture (1927-2021) Best Director (1927-2021) Best Actor (1927-2021) Best Actress (1927-2021)

Each dataset would be indexed by year and category.

The sources used for the following datas are: oscars.org and tmdb.com's API

Firstly we scrape the data for nominees and winners for each selected year for all the selected categories. Then, we will use these datas to aks tmdb's API for more informations about the movie. However, given that there may be multiple films and persons with the same name, we are selecting from the API's response only relevant informations.

These are afterwards processed and added to our dataframe, which is later stored for the future use.

User can through easy GUI select categories and years in which he is interested and for each of his selection, new dataset stored in csv file is created, permitting easy creation of multiple datasets with different searches.

Notes from WIP:

string familiarity library python

json save the progress + raise Error pour Scrapping

focus to the end :

full documentation !! executable project: one script executable jupyter is good for exploratory + presentation, but "professional" = script executable MAKE IT INSTALLABLE : PYTHON PACKAGE

File that is an example of the use of the project documentation information in lecture 9

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

OscarScrapper-0.0.5.tar.gz (10.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

OscarScrapper-0.0.5-py3-none-any.whl (11.1 kB view details)

Uploaded Python 3

File details

Details for the file OscarScrapper-0.0.5.tar.gz.

File metadata

  • Download URL: OscarScrapper-0.0.5.tar.gz
  • Upload date:
  • Size: 10.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.4 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.0 CPython/3.9.6

File hashes

Hashes for OscarScrapper-0.0.5.tar.gz
Algorithm Hash digest
SHA256 a6c56cf2d9e241f9523b571188ff3a4aacbf2261072eece3e0b3af9f1cd66ff6
MD5 ce45017fac08a8bbe135fd8618656c23
BLAKE2b-256 45b1c688a1c754833f744b8ab1662956697f2e6e8929c7f62fb54d199d13a5df

See more details on using hashes here.

File details

Details for the file OscarScrapper-0.0.5-py3-none-any.whl.

File metadata

  • Download URL: OscarScrapper-0.0.5-py3-none-any.whl
  • Upload date:
  • Size: 11.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.4 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.0 CPython/3.9.6

File hashes

Hashes for OscarScrapper-0.0.5-py3-none-any.whl
Algorithm Hash digest
SHA256 e082719887cc7efc8ce958f07b1f2c8897330232d85bf59fc01ba9bc00258df6
MD5 4b34226bba9bf399e98e042c43ba0155
BLAKE2b-256 e939351b16e70e77f1141dae6ec0a24edceb113ae84d9d8321bd49e6668e71a3

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page