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    "info": {
        "author": "Alpha x1",
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            "License :: OSI Approved :: Apache Software License",
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        "description": "# x1\n|                |                                                                                                                                                 |\n| -------------- | ----------------------------------------------------------------------------------------------------------------------------------------------- |\n| Latest Release | [![PyPI version](https://img.shields.io/pypi/v/xone.svg)](https://badge.fury.io/py/xone)                                                        |\n|                | [![PyPI version](https://img.shields.io/pypi/pyversions/xone.svg)](https://badge.fury.io/py/xone)                                               |\n| Docs           | [![Documentation Status](https://readthedocs.org/projects/xone/badge/?version=latest)](https://xone.readthedocs.io/en/latest)                   |\n| Build          | [![Travis CI](https://img.shields.io/travis/alpha-xone/xone/master.svg?label=Travis%20CI)](https://travis-ci.com/alpha-xone/xone)               |\n| Coverage       | [![codecov](https://codecov.io/gh/alpha-xone/xone/branch/master/graph/badge.svg)](https://codecov.io/gh/alpha-xone/xone)                        |\n| Quality        | [![Codacy Badge](https://api.codacy.com/project/badge/Grade/eb3d11949a1343d9aa4806a31f3fcc41)](https://www.codacy.com/app/alpha-xone/xone)      |\n|                | [![CodeFactor](https://www.codefactor.io/repository/github/alpha-xone/xone/badge)](https://www.codefactor.io/repository/github/alpha-xone/xone) |\n| License        | [![GitHub license](https://img.shields.io/github/license/alpha-xone/xone.svg)](https://github.com/alpha-xone/xone/blob/master/LICENSE)          |\n\nFrequently used functions for financial data analysis\n\n## Installation\n\n```cmd\npip install xone\n```\n\n## Utilities\n\n```python\nIn[1]: from xone import utils\n```\n\nConvert anything to list.\n\n- If the input is clean, use `tolist()` directly.\n  Some functions requires `list` as input, `tolist()` is to standardize all inputs for them.\n\n```python\nIn[2]: ticker = 'BHP AU'\nIn[3]: list_of_tickers = tolist(ticker)\nIn[4]: list_of_tickers\n```\n\n```python\nOut[4]: ['BHP AU']\n```\n\n```pydocstring\nIn[5]: raw_price = [31.08, 31.10, 31.11, 31.07, 31.04, 31.04]\nIn[6]: price = utils.tolist(raw_price)\nIn[7]: price\n```\n\n```pydocstring\nOut[7]: [31.08, 31.10, 31.11, 31.07, 31.04, 31.04]\n```\n\n- If the input is list of tuples / lists / any weird combination, use `flatten()`:\n\n```python\nIn[8]: raw_volume = [(10166, 69981), [14343, 10096], 11506, 9718]\nIn[9]: volume = utils.flatten(raw_volume)\nIn[10]: volume\n```\n\n```pydocstring\nOut[10]: [10166, 69981, 14343, 10096, 11506, 9718]\n```\n\nOrder preserving DataFrame construction from list of `dict`.\n\nPrior to Python 3.7, `dict` is not ordered like `OrderedDict`. \nPassing `dict` directly to DataFrame constructor will make the columns sorted by alphabets.\n\n```python\nIn[11]: import pandas as pd\n\nIn[12]: data_list = [\n            dict(sid=1, symbol='1 HK', price=88.8),\n            dict(sid=700, symbol='700 HK', price=350.),\n        ]\nIn[13]: pd.DataFrame(data_list)\n```\n\n```pydocstring\nOut[13]:\n   price  sid  symbol\n0  88.80    1    1 HK\n1 350.00  700  700 HK\n```\n\n`to_frame` makes sure the order of inputs will be kept:\n\n```python\nIn[14]: utils.to_frame(data_list)\n```\n\n```pydocstring\nOut[14]:\n   sid  symbol  price\n0    1    1 HK  88.80\n1  700  700 HK 350.00\n```\n\n## Files\n\n```python\nIn[15]: from xone import files\n```\n\nAutomatic check and create path and save files:\n\n```python\nIn[16]: DATA_PATH = '/data/Bloomberg'\nIn[17]: data_file = f'{DATA_PATH}/{ticker.split()[-1]}/{ticker}/2018-09-10.parq'\n\nIn[18]: sample = pd.DataFrame(\n            data=dict(price=price, volume=volume),\n            index=pd.DatetimeIndex(\n                start='2018-09-10T10:10:00', periods=6, freq='min'\n            ).tz_localize('Australia/Sydney'),\n        )\nIn[19]: sample\n```\n\n```pydocstring\nOut[19]: \n                           price  volume\n2018-09-10 10:10:00+10:00  31.08   10166\n2018-09-10 10:11:00+10:00  31.10   69981\n2018-09-10 10:12:00+10:00  31.11   14343\n2018-09-10 10:13:00+10:00  31.07   10096\n2018-09-10 10:14:00+10:00  31.04   11506\n2018-09-10 10:15:00+10:00  31.04    9718\n```\n\n`create_folder` checks folder existence and create all parent folders for the target folder.\n\n```python\nIn[20]: files.create_folder(data_file, is_file=True)\nIn[21]: sample.to_parquet(data_file)\n```\n\n## Logs\n\n\n",
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