--- configs: - config_name: default data_files: - split: train path: data/train-* dataset_info: features: - name: Id dtype: string - name: PostTypeId dtype: string - name: AcceptedAnswerId dtype: string - name: ParentId dtype: string - name: Score dtype: string - name: ViewCount dtype: string - name: Body dtype: string - name: Title dtype: string - name: ContentLicense dtype: string - name: FavoriteCount dtype: string - name: CreationDate dtype: string - name: LastActivityDate dtype: string - name: LastEditDate dtype: string - name: LastEditorUserId dtype: string - name: OwnerUserId dtype: string - name: Tags sequence: string splits: - name: train num_bytes: 566804417 num_examples: 411232 download_size: 311064786 dataset_size: 566804417 language: - code - en task_categories: - question-answering - text-generation - text2text-generation tags: - code --- # Cross Validated / stats.stackexchange.com ## Dataset Summary This dataset contains all posts submitted to stats.stackexchange.com before the 30th of August 2023 formatted as **Markdown text**.
The data is sourced from [Internet Archive StackExchange Data Dump](https://archive.org/download/stackexchange) and follows the format by [mikex86/stackoverflow-posts](https://huggingface.co/datasets/mikex86/stackoverflow-posts) ## Dataset Structure Each record corresponds to one post of a particular type. Original ordering from the data dump is not exactly preserved due to parallelism in the script used to process the data dump. The markdown content of each post is contained in the `Body` field. The license for a particular post is contained in the `ContentLicense` field. ### Data Fields ```typescript { Id: long, PostTypeId: long, // 1=Question, 2=Answer, 3=Orphaned tag wiki, 4=Tag wiki excerpt, 5=Tag wiki, 6=Moderator nomination, 7=Wiki Placeholder, 8=Privilige Wiki AcceptedAnswerId: long | null, // only present if PostTypeId=1 ParentId: long | null, // only present if PostTypeId=2 Score: long, ViewCount: long | null, Body: string | null, Title: string | null, ContentLicense: string | null, FavoriteCount: long | null, CreationDate: string | null, LastActivityDate: string | null, LastEditDate: string | null, LastEditorUserId: long | null, OwnerUserId: long | null, Tags: array | null } ``` Also consider the [StackExchange Datadump Schema Documentation](https://meta.stackexchange.com/questions/2677/database-schema-documentation-for-the-public-data-dump-and-sede), as all fields have analogs in the original dump format. ## How to use? ```python from datasets import load_dataset # predownload full dataset ds = load_dataset('theblackcat102/crossvalidated-posts', split='train') # dataset streaming (will only download the data as needed) ds = load_dataset('theblackcat102/crossvalidated-posts', split='train', streaming=True) for sample in iter(ds): print(sample["Body"]) ``` ## How is the text stored? The original Data Dump formats the "Body" field as HTML, using tags such as ``, `

`, `
    `, etc. This HTML format has been converted to Markdown following [mikex86/stackoverflow-posts](https://huggingface.co/datasets/mikex86/stackoverflow-posts) conversion rule. **Example:** After differencing I saw that my constant/intercept is not statistically significant. Does anybody know how to fit the same model without the const term? im using statsmodels.tsa.arima.model To give a relative example I have: `ARIMA(data, order=(3,0,0))` an AR(3) model and say it that the second coefficient is insignificant. I can get rid of it by typing ``` ARMA(data,order=([1, 3], 0, 0) ``` but how can I get rid of coefficient??