| Name | tapy JSON |
| Version |
1.10.0
JSON |
| download |
| home_page | None |
| Summary | Technical Indicators for the Pandas' Dataframes |
| upload_time | 2024-07-04 08:24:52 |
| maintainer | None |
| docs_url | None |
| author | Dmitrii K |
| requires_python | <4,>=3.10 |
| license | MIT |
| keywords |
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# tapy
Technical Indicators for the Pandas' Dataframes
Documentation: https://pandastechindicators.readthedocs.io/en/latest/
## Installation
```
pip install -U tapy
```
## Example
```
>>> import pandas as pd
>>> from tapy import Indicators
>>> df = pd.read_csv('EURUSD60.csv')
>>> i= Indicators(df)
>>> i.accelerator_oscillator(column_name='AC')
>>> i.sma()
>>> df = i.df
>>> df.tail()
Date Time Open High Low Close Volume AC sma
3723 2019.09.20 16:00 1.10022 1.10105 1.10010 1.10070 2888 -0.001155 1.101296
3724 2019.09.20 17:00 1.10068 1.10193 1.10054 1.10184 6116 -0.000820 1.101158
3725 2019.09.20 18:00 1.10186 1.10194 1.10095 1.10144 3757 -0.000400 1.101056
3726 2019.09.20 19:00 1.10146 1.10215 1.10121 1.10188 3069 0.000022 1.101216
3727 2019.09.20 20:00 1.10184 1.10215 1.10147 1.10167 1224 0.000388 1.101506
```
## Available Indicators
1. Accelerator Oscillator (AC)
2. Accumulation/Distribution (A/D)
3. Alligator
4. Average True Range (ATR)
5. Awesome Oscillator (AO)
6. Bears Power
7. Bollinger Bands
8. Bulls Power
9. Commodity Channel Index (CCI)
10. DeMarker (DeM)
11. Exponential Moving Average (EMA)
12. Force Index (FRC)
13. Fractals
14. Gator Oscillator
15. Ichimoku Kinko Hyo
16. Market Facilitation Index (BW MFI)
17. Momentum
18. Money Flow Index (MFI)
19. Moving Average Convergence/Divergence (MACD)
20. Simple Moving Average (SMA)
21. Smoothed Moving Average (SMMA)
Raw data
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"description": "# tapy\nTechnical Indicators for the Pandas' Dataframes\n\nDocumentation: https://pandastechindicators.readthedocs.io/en/latest/\n\n## Installation\n```\npip install -U tapy\n```\n\n## Example\n```\n>>> import pandas as pd\n>>> from tapy import Indicators\n>>> df = pd.read_csv('EURUSD60.csv')\n>>> i= Indicators(df)\n>>> i.accelerator_oscillator(column_name='AC')\n>>> i.sma()\n>>> df = i.df\n>>> df.tail()\n Date Time Open High Low Close Volume AC sma\n3723 2019.09.20 16:00 1.10022 1.10105 1.10010 1.10070 2888 -0.001155 1.101296\n3724 2019.09.20 17:00 1.10068 1.10193 1.10054 1.10184 6116 -0.000820 1.101158\n3725 2019.09.20 18:00 1.10186 1.10194 1.10095 1.10144 3757 -0.000400 1.101056\n3726 2019.09.20 19:00 1.10146 1.10215 1.10121 1.10188 3069 0.000022 1.101216\n3727 2019.09.20 20:00 1.10184 1.10215 1.10147 1.10167 1224 0.000388 1.101506\n```\n\n## Available Indicators\n\n1. Accelerator Oscillator (AC)\n2. Accumulation/Distribution (A/D)\n3. Alligator\n4. Average True Range (ATR)\n5. Awesome Oscillator (AO)\n6. Bears Power\n7. Bollinger Bands\n8. Bulls Power\n9. Commodity Channel Index (CCI)\n10. DeMarker (DeM)\n11. Exponential Moving Average (EMA)\n12. Force Index (FRC)\n13. Fractals\n14. Gator Oscillator\n15. Ichimoku Kinko Hyo\n16. Market Facilitation Index (BW MFI)\n17. Momentum\n18. Money Flow Index (MFI)\n19. Moving Average Convergence/Divergence (MACD)\n20. Simple Moving Average (SMA)\n21. Smoothed Moving Average (SMMA)\n",
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