Metadata-Version: 2.1
Name: xone
Version: 0.0.7
Summary: Frequently used functions for financial data analysis
Home-page: https://github.com/alpha-xone/xone
Author: Alpha x1
Author-email: alpha.xone@outlook.com
License: Apache
Platform: UNKNOWN
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Description-Content-Type: text/markdown
Requires-Dist: python-dateutil (>=2.7.5)
Requires-Dist: pytz (>=2018.7)
Requires-Dist: matplotlib (>=3.0.2)
Requires-Dist: numpy (>=1.15.0)
Requires-Dist: pandas (>=0.23.4)
Requires-Dist: pyarrow (>=0.11.1)
Requires-Dist: pytest (>=4.0.1)
Requires-Dist: scipy (>=1.1.0)
Requires-Dist: xdoctest (>=0.6.1)

# x1

[![PyPI version](https://badge.fury.io/py/xone.svg)](https://badge.fury.io/py/xone)
[![Documentation Status](https://readthedocs.org/projects/xone/badge/?version=latest)](https://xone.readthedocs.io/en/latest)

Frequently used functions for financial data analysis

## Installation

```
pip install xone
```

## Common Utilities

## Files

Automatic check and create path and save files:

```python
import pandas as pd
from xone import files

DATA_PATH = '/data/Bloomberg'

ticker = 'BHP AU Equity'
data_file = f'{DATA_PATH}/{ticker.split()[-1]}/{ticker}/2018-09-10.parq'
sample = pd.DataFrame(
    data=dict(
        price=[31.08, 31.10, 31.11, 31.07, 31.04, 31.04],
        volume=[10166, 69981, 14343, 10096, 11506, 9718],
    ),
    index=pd.DatetimeIndex(
        start='2018-09-10T10:10:00', periods=6, freq='min'
    ).tz_localize('Australia/Sydney'),
)

files.create_folder(data_file, is_file=True)
sample.to_parquet(data_file)
```

## Calendar

## Logs


