### A Python Package for Point & Figure Charting
[](#license)
[](https://pypi.org/project/pypnf/)
[](https://pypi.org/project/pypnf/)
[](https://pypi.org/project/pypnf/)
<hr>
### Installation
```python
pip install pypnf
```
<hr>
### Usage
#### Quickstart using integrated time-series example
```python
from pypnf import PointFigureChart
from pypnf import dataset
symbol = 'AAPL' # or 'MSFT'
ts = dataset(symbol)
pnf = PointFigureChart(ts=ts, method='cl', reversal=2, boxsize=5, scaling='abs', title=symbol)
print(pnf)
```
```
Point & Figure (abs|cl) 5 x 2 | AAPL
--- - - - - - - - ---
135 . . . . . . X 135
130 . . X . . . X 130
125 . . X O . . X 125
120 . . X O X . X 120
115 . . X O X O X 115
110 . . X O . O . 110
105 . . X . . . . 105
100 . . X . . . . 100
95 . . X . . . . 95
90 . . X . . . . 90
85 . . X . . . . 85
80 X . X . . . . 80
75 X O X . . . . 75
70 . O X . . . . 70
65 . O X . . . . 65
60 . O . . . . . 60
--- - - - - - - - ---
printed 7/7 columns.
```
##### Plotting Point&Figure Charts
```python
from pypnf import PointFigureChart
from testdata import dataset
data = dataset('^SPX')
pnf = PointFigureChart(ts=data, method='h/l', reversal=2, boxsize=50, scaling='abs', title='^SPX')
pnf.bollinger(5, 2)
pnf.donchian(8,2)
pnf.psar(0.02, 0.2)
pnf.show()
```
#### Quickstart using time-series data loaded via the external package yfinance
If the yfinance and/or pandas package is not yet installed use:
```python
pip install pandas
pip install yfinance
```
In order to process the downloaded data with the PointFigureChart-class the time-series data needs to be prepared.
```python
import yfinance as yf
symbol = 'AAPL'
data = yf.Ticker(symbol)
ts = data.history(start='2018-01-01', end='2018-06-30')
# reset index
ts.reset_index(level=0, inplace=True)
# convert pd.timestamp to string
ts['Date'] = ts['Date'].dt.strftime('%Y-%m-%d')
# select required keys
ts = ts[['Date','Open','High','Low','Close']]
# convert DataFrame to dictionary
ts = ts.to_dict('list')
```
Initiate the PointFigureChart object with the prepared data and chart parameter,
get the trendlines and print the resulting Point and Figure Chart.
```python
from pypnf import PointFigureChart
pnf = PointFigureChart(ts=ts, method='cl', reversal=3, boxsize=2, scaling='abs', title='AAPL')
pnf.get_trendlines()
print(pnf)
```
```
Point & Figure (abs|cl) 2 x 3 | AAPL
-- - - - - - - - - - - - --
90 . . . . . . . . . . X 90
88 . . . . . . . . . . X 88
86 . . . . . . . . . . X 86
84 . . . . . . . . . . X 84
82 . . . . . . . . . . X 82
80 . . . . X . . . . . X 80
78 . . . . X O . . . . X 78
76 . . . . X O . . . . X 76
74 . . . . X O X . . . X 74
72 . . . . X O X O . . X 72
70 . . . . X O X O . . X 70
68 . . . . X O . O X . X 68
66 . . . . X . . O X O X 66
64 . . . . X . . O X O X 64
62 . . . . X . . O . O X 62
60 . . . . X . . . . O X 60
58 * . . . X . . . . O X 58
56 X * . . X . . . . O . 56
54 X O * . X . . . . . . 54
52 X O . * X . . . . . * 52
50 X O X . X . . . . * . 50
48 X O X O X . . . * . . 48
46 X O X O X . . * . . . 46
44 X O X O . . * . . . . 44
42 X O X . . * . . . . . 42
40 X O X . * . . . . . . 40
38 . O X * . . . . . . . 38
36 . O * . . . . . . . . 36
-- - - - - - - - - - - - --
last trendline: bullish support line of length 10
printed 11/11 columns.
```
<hr>
<h3>Literature</h3>
**Weber, Zieg (2003)** The Complete Guide to Point-and-Figure Charting - The new science of an old art. <i>Harriman House</i>, ISBN: 1-897-5972-82<br>
**du Plessis (2012)** The Definitive Guide to Point and Figure: A Comprehensive Guide to the Theory and Practical Use of the Point and Figure Charting Method. 2nd Edition. <i>Harriman House</i>, ISBN: 978-0857192455<br>
**du Plessis (2015)** 21st Century Point and Figure - New and advanced techniques for using Point and Figure charts. <i>Harriman House</i>, ISBN: 978-0857194428<br>
**Shah (2018)** Trading the Markets the Point & Figure way : become a noiseless trader and achieve consistent success in markets. <i>Notion Press</i>, ISBN: 978-1642492248<br>
<hr>
<h3>Copyright</h3>
pyPnF is licensed under a GNU General Public License v2 (GPLv2).
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"description": "\n\n\n### A Python Package for Point & Figure Charting\n\n[](#license)\n[](https://pypi.org/project/pypnf/)\n[](https://pypi.org/project/pypnf/)\n[](https://pypi.org/project/pypnf/)\n\n<hr>\n\n### Installation\n```python\npip install pypnf\n```\n\n<hr>\n\n### Usage\n\n#### Quickstart using integrated time-series example\n\n\n```python\nfrom pypnf import PointFigureChart\nfrom pypnf import dataset\n\nsymbol = 'AAPL' # or 'MSFT'\n\nts = dataset(symbol)\n\npnf = PointFigureChart(ts=ts, method='cl', reversal=2, boxsize=5, scaling='abs', title=symbol)\n\nprint(pnf)\n```\n\n```\nPoint & Figure (abs|cl) 5 x 2 | AAPL\n--- - - - - - - - ---\n135 . . . . . . X 135\n130 . . X . . . X 130\n125 . . X O . . X 125\n120 . . X O X . X 120\n115 . . X O X O X 115\n110 . . X O . O . 110\n105 . . X . . . . 105\n100 . . X . . . . 100\n 95 . . X . . . . 95\n 90 . . X . . . . 90\n 85 . . X . . . . 85\n 80 X . X . . . . 80\n 75 X O X . . . . 75\n 70 . O X . . . . 70\n 65 . O X . . . . 65\n 60 . O . . . . . 60\n--- - - - - - - - ---\nprinted 7/7 columns.\n```\n\n##### Plotting Point&Figure Charts\n\n```python\nfrom pypnf import PointFigureChart\nfrom testdata import dataset\n\ndata = dataset('^SPX')\n\npnf = PointFigureChart(ts=data, method='h/l', reversal=2, boxsize=50, scaling='abs', title='^SPX')\npnf.bollinger(5, 2)\npnf.donchian(8,2)\npnf.psar(0.02, 0.2)\npnf.show()\n```\n\n\n#### Quickstart using time-series data loaded via the external package yfinance\n\nIf the yfinance and/or pandas package is not yet installed use:\n\n```python\npip install pandas\npip install yfinance\n```\n\nIn order to process the downloaded data with the PointFigureChart-class the time-series data needs to be prepared.\n\n```python\nimport yfinance as yf\n\nsymbol = 'AAPL'\n\ndata = yf.Ticker(symbol)\nts = data.history(start='2018-01-01', end='2018-06-30')\n\n# reset index\nts.reset_index(level=0, inplace=True)\n\n# convert pd.timestamp to string\nts['Date'] = ts['Date'].dt.strftime('%Y-%m-%d')\n\n# select required keys\nts = ts[['Date','Open','High','Low','Close']]\n\n# convert DataFrame to dictionary\nts = ts.to_dict('list')\n```\n\nInitiate the PointFigureChart object with the prepared data and chart parameter, \nget the trendlines and print the resulting Point and Figure Chart.\n\n```python\nfrom pypnf import PointFigureChart\n\npnf = PointFigureChart(ts=ts, method='cl', reversal=3, boxsize=2, scaling='abs', title='AAPL')\npnf.get_trendlines()\nprint(pnf)\n```\n\n```\nPoint & Figure (abs|cl) 2 x 3 | AAPL\n-- - - - - - - - - - - - --\n90 . . . . . . . . . . X 90\n88 . . . . . . . . . . X 88\n86 . . . . . . . . . . X 86\n84 . . . . . . . . . . X 84\n82 . . . . . . . . . . X 82\n80 . . . . X . . . . . X 80\n78 . . . . X O . . . . X 78\n76 . . . . X O . . . . X 76\n74 . . . . X O X . . . X 74\n72 . . . . X O X O . . X 72\n70 . . . . X O X O . . X 70\n68 . . . . X O . O X . X 68\n66 . . . . X . . O X O X 66\n64 . . . . X . . O X O X 64\n62 . . . . X . . O . O X 62\n60 . . . . X . . . . O X 60\n58 * . . . X . . . . O X 58\n56 X * . . X . . . . O . 56\n54 X O * . X . . . . . . 54\n52 X O . * X . . . . . * 52\n50 X O X . X . . . . * . 50\n48 X O X O X . . . * . . 48\n46 X O X O X . . * . . . 46\n44 X O X O . . * . . . . 44\n42 X O X . . * . . . . . 42\n40 X O X . * . . . . . . 40\n38 . O X * . . . . . . . 38\n36 . O * . . . . . . . . 36\n-- - - - - - - - - - - - --\nlast trendline: bullish support line of length 10\nprinted 11/11 columns.\n```\n\n<hr>\n\n<h3>Literature</h3>\n\n**Weber, Zieg (2003)** The Complete Guide to Point-and-Figure Charting - The new science of an old art. <i>Harriman House</i>, ISBN: 1-897-5972-82<br>\n\n**du Plessis (2012)** The Definitive Guide to Point and Figure: A Comprehensive Guide to the Theory and Practical Use of the Point and Figure Charting Method. 2nd Edition. <i>Harriman House</i>, ISBN: 978-0857192455<br> \n\n**du Plessis (2015)** 21st Century Point and Figure - New and advanced techniques for using Point and Figure charts. <i>Harriman House</i>, ISBN: 978-0857194428<br>\n\n**Shah (2018)** Trading the Markets the Point & Figure way : become a noiseless trader and achieve consistent success in markets. <i>Notion Press</i>, ISBN: 978-1642492248<br> \n\n<hr>\n\n<h3>Copyright</h3>\npyPnF is licensed under a GNU General Public License v2 (GPLv2).\n\n",
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