{"repo":"matheusfacure/python-causality-handbook","free":true,"listed":false,"github":"https://github.com/matheusfacure/python-causality-handbook","clone":"git clone https://github.com/matheusfacure/python-causality-handbook.git","description":"Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.","language":"Jupyter Notebook","stars":3437,"topics":["causal-inference","python","causality","data-science","econometrics","impact-estimation","harmless-econometrics"],"license":"MIT","category":"machine-learning","readme_excerpt":"Causal Inference for The Brave and True A light-hearted yet rigorous approach to learning impact estimation and sensitivity analysis. All in Python and with as many memes as I could find. Check out the book here! If you want to read the book in Brazilian Portuguese, @rdemarqui made this awesome translation: Inferência Causal para os Corajosos e Verdadeiros If you want to read the book in French, Arthur Mello put a lot of effort into this beautiful translation: L'Inférence Causale pour les Courageux et les Vrais If you want to read the book in Chinese, @xieliaing was very kind to make a translation (Chapters 1-21): 因果推断：从概念到实践 There is also a more recent Chinese tralsation by 黄文喆（Wenzhe Huang) and 许文立（Wenli Xu) (All Chapters): 因果推断：献给求真敢为者 If you want to read the book in Spanish, @donelianc was very kind to make a translation: Inferencia Causal para los Valientes y Verdaderos If you want to read it in Korean, @jsshin2019 has put up a team to make the that translation possible: Python으로 하는 인과추론 : 개념부터 실습까지 Also, some really kind folks (@vietecon, @dinhtrang24 and @anhpham52) also translated this content into Vietnamese: Nhân quả Python I like to think of this entire series as a tribute to Joshua Angrist, Alberto Abadie and Christopher Walters for their amazing Econometrics class. Most of the ideas here are taken from their classes at the American Economic Association. Watching them is what is keeping me sane during this tough year of 2020. Cross-Section Econometrics Mastering M","default_branch":null,"files":null,"tree":[],"storefront":"/r/matheusfacure","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/matheusfacure/python-causality-handbook/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}