A python package to calculate trends in stock markets.
To install stable version from pypi, run
pip install stocktrendsTo install latest code from github, run
pip install git+https://github.com/chillaranand/stocktrendsThe following code from demo.py file shows how to construct dataframe from a csv file and then plot Renko, Line Break and PnF charts.
"""
Sample data from tests/HDFCLIFE.csv file.
Date,Symbol,Series,Prev Close,Open,High,Low,Last,Close,VWAP,Volume,Turnover,Trades,Deliverable Volume,%Deliverble
2017-11-17,HDFCLIFE,EQ,290.0,310.0,369.0,307.0,343.9,344.6,327.26,168836552,5525288229115000.0,1177530,82044782,0.48590000000000005
2017-11-20,HDFCLIFE,EQ,344.6,344.7,358.9,344.0,355.0,355.35,353.18,14650240,517410581605000.0,166263,6761287,0.4615
2017-11-21,HDFCLIFE,EQ,355.35,356.4,418.9,352.5,386.9,385.3,389.24,43078194,1676786001315000.0,450090,11584111,0.26890000000000003
2017-11-22,HDFCLIFE,EQ,385.3,388.0,408.0,386.9,394.0,395.2,397.38,15227642,605123098895000.0,166870,3475999,0.22829999999999998
"""
import pandas as pd
from stocktrends import indicators
df = pd.read_csv('tests/HDFCLIFE.csv')
df.columns = [i.lower() for i in df.columns]
rows = 5
pnf = indicators.PnF(df)
pnf.box_size = 10
pnf.reversal_size = 3
print('\n\nPnF BAR data - based on "close" column')
data = pnf.get_bar_ohlc_data(source='close')
print(data.head(rows))
print('\n\nPnF BOX data - based on "close" column')
pnf_data = pnf.get_ohlc_data(source='close')
print(pnf_data.head(rows))
print('\n\nPnF BOX data - based on "high"/"low" columns')
data = pnf.get_bar_ohlc_data(source='hl')
print(data.head(rows))
renko = indicators.Renko(df)
print('\n\nRenko box calcuation based on periodic close')
renko.brick_size = 2
renko.chart_type = indicators.Renko.PERIOD_CLOSE
data = renko.get_ohlc_data()
print(data.tail(rows))
# print('\n\nRenko box calcuation based on price movement')
# renko.chart_type = indicators.Renko.PRICE_MOVEMENT
# data = renko.get_ohlc_data()
# print(data.tail(rows))
lb = indicators.LineBreak(df)
print('\n\nLine break chart')
lb.line_number = 3
data = lb.get_ohlc_data()
print(data.tail(rows))