{"payload":{"header_redesign_enabled":false,"results":[{"id":"161334564","archived":false,"color":"#DA5B0B","followers":306,"has_funding_file":false,"hl_name":"advaitsave/Introduction-to-Time-Series-forecasting-Python","hl_trunc_description":"Introduction to time series preprocessing and forecasting in Python using AR, MA, ARMA, ARIMA, SARIMA and Prophet model with forecast eva…","language":"Jupyter Notebook","mirror":false,"owned_by_organization":false,"public":true,"repo":{"repository":{"id":161334564,"name":"Introduction-to-Time-Series-forecasting-Python","owner_id":44766784,"owner_login":"advaitsave","updated_at":"2018-12-11T13:08:18.262Z","has_issues":true}},"sponsorable":false,"topics":["python","time-series","arma","forecasting","preprocessing","arima","dickey-fuller","seasonality","time-series-forecasting","stationarity","sarima","forecast-evaluation","prophet-model","series-forecasting-python","series-preprocessing"],"type":"Public","help_wanted_issues_count":0,"good_first_issue_issues_count":0,"starred_by_current_user":false}],"type":"repositories","page":1,"page_count":1,"elapsed_millis":59,"errors":[],"result_count":1,"facets":[],"protected_org_logins":[],"topics":null,"query_id":"","logged_in":false,"sign_up_path":"/signup?source=code_search_results","sign_in_path":"/login?return_to=https%3A%2F%2Fgithub.com%2Fsearch%3Fq%3Drepo%253Aadvaitsave%252FIntroduction-to-Time-Series-forecasting-Python%2B%2Blanguage%253A%2522Jupyter%2BNotebook%2522","metadata":null,"csrf_tokens":{"/advaitsave/Introduction-to-Time-Series-forecasting-Python/star":{"post":"p1TgJxJf6EAsZUi1ZLJSDR-qWtPdHwdGZkjQLWBI9eDIOHhOOCCJ4DPbgW0HoU95MsR_R8xwFmy1o8extQwrTA"},"/advaitsave/Introduction-to-Time-Series-forecasting-Python/unstar":{"post":"p6ksLfawaL0BdJdwhLz18C9J8eE7ZWxhb-TdWOY-zW8b3Xs9M3339Bh12ybGDF7-TZdEUockgAtTLBkfAyhq0A"},"/sponsors/batch_deferred_sponsor_buttons":{"post":"oDQf3tqOrwpZX5maBFDoC1PSLDU_R7SZkA1VvHVmQ4TglqBeKse7uS4Xu4F0UuaisrrRDyxS8t0_yoIalHZI1w"}}},"title":"Repository search results"}