pandas_talib
纯Pandas实现的指标库,用于技术分析(目前只有常用指标)。
- 兼容pandas 0.19
- 跑通了所有ta-lib的对比测试,确保计算结果的正确。
A Python Pandas implementation of technical indicators (Currently only common indicators)
- Compatible with pandas 0.19
- Pass all comparison test with the TA-Lib to ensure that the results are correct.
Usage
Copy pandas_talib folder to your project path.
import pandas as pd from pandas_talib import * df = pd.read_csv('./data/AAPL.csv') df = EMA(df, ['Close', 'Volume'], n=20, join=['Close_EMA20', 'Volume_EMA20']) df.tail()
Output:
Date Open High Low Close Volume Ex-Dividend \ 9149 2017-03-27 139.39 141.22 138.62 140.88 23374772.0 0.0 9150 2017-03-28 140.91 144.04 140.62 143.80 33193535.0 0.0 9151 2017-03-29 143.68 144.49 143.19 144.12 28979571.0 0.0 9152 2017-03-30 144.19 144.50 143.50 143.93 21064727.0 0.0 9153 2017-03-31 143.72 144.27 143.01 143.71 19228867.0 0.0 Split Ratio Adj. Open Adj. High Adj. Low Adj. Close Adj. Volume \ 9149 1.0 139.39 141.22 138.62 140.88 23374772.0 9150 1.0 140.91 144.04 140.62 143.80 33193535.0 9151 1.0 143.68 144.49 143.19 144.12 28979571.0 9152 1.0 144.19 144.50 143.50 143.93 21064727.0 9153 1.0 143.72 144.27 143.01 143.71 19228867.0 Close_EMA20 Volume_EMA20 9149 139.153709 2.483257e+07 9150 139.596213 2.562885e+07 9151 140.027050 2.594797e+07 9152 140.398759 2.548290e+07 9153 140.714115 2.488728e+07
Run unit tests
Run all unit tests
$ nosetests -s -v