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Series exploration, analysis \u0026 modelling. This includes -\n\n\nAs of now, this libray is in pre-alpha phase, i.e there is a lot of work still left before its first stable release.\n\n### TSMAD - Time Series Mini Analysis DashBoard.\nFunctionalities Include\n\n    - A mini Dashboard for Time Series Analysis, with multiple variations to each kind of analysis\n    - Inbuilt Freqency Variation analysis\n    - Intervention Analysis (In Future) \n    \n\n### TSSTATS - Time Series Statistical \u0026 Modelling Functions\nFunctionalities Include:\n\n    - Rolling Origin Framework (Currently Supports - statsmodels, sklearn, sklearn) for both multi-variate and uni-variate\n    - Residual Diagnostics\n    - Statistical Tests\n    - Entropy Calculations\n    - Intervention Analysis (In Future)\n\n## Example\n****\n\u003cimg style=\"float: right;\" src=\"examples/example_gif.gif\"  width='100%'\u003e\n\n## Installation\n****\nInstallation \n```py\npip install tseuler\n```\n## Usage\n****\n- ### Instantiating a DashBoard\n    \n    ```py\n    import pandas as pd\n    import tseuler as tse\n    # Read the Time Series DataFrame\n    dataDF = pd.read_csv('Raw Data/stocks_data.csv', index_col=0)\n    tsmadObj = tse.TSMAD(tsdata = dataDF, data_desc = 'Stocks Data',\n                     target_columns = ['close'], categorical_columns = ['Name'],\n                     dt_format = '%Y-%m-%d', dt_freq = 'B',\n                     how_aggregate = {'open':'first', 'high':'max', 'low':'min', 'close':'last'},\n                     force_interactive = True)\n    tsmadObj.get_board()\n    ```\n\n`tseuler` has been built upon:-\n****\n- pandas\n- numpy\n- panel\n- altair\n- matplotlib\n- statsmodels\n\n\n\n## History\n****\n\u003cu\u003ev0.0.4dev0 : Development Package\u003c/u\u003e\n- Added TSMAD\n- Added TSSTATS\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fag-ds-bubble%2Ftseuler","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fag-ds-bubble%2Ftseuler","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fag-ds-bubble%2Ftseuler/lists"}