### Install StockTrends from PyPI

Source: https://github.com/chillaranand/stocktrends/blob/master/README.rst

Use this command to install the stable version of the stocktrends package from the Python Package Index.

```shell
pip install stocktrends
```

--------------------------------

### Install StockTrends from GitHub

Source: https://github.com/chillaranand/stocktrends/blob/master/README.rst

Use this command to install the latest development version of the stocktrends package directly from its GitHub repository.

```shell
pip install git+https://github.com/chillaranand/stocktrends
```

--------------------------------

### Generate Renko Charts

Source: https://github.com/chillaranand/stocktrends/blob/master/README.rst

Generates Renko charts from a Pandas DataFrame. Supports calculation based on periodic close prices. Requires the 'stocktrends' library.

```python
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

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))
```

--------------------------------

### Generate Line Break Charts

Source: https://github.com/chillaranand/stocktrends/blob/master/README.rst

Generates Line Break charts from a Pandas DataFrame, configurable by the number of lines. Requires the 'stocktrends' library.

```python
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


lb = indicators.LineBreak(df)

print('\n\nLine break chart')
lb.line_number = 3
data = lb.get_ohlc_data()
print(data.tail(rows))
```

--------------------------------

### Generate PnF Charts

Source: https://github.com/chillaranand/stocktrends/blob/master/README.rst

Constructs a Pandas DataFrame from a CSV file and generates Point and Figure (PnF) charts based on 'close', 'high'/'low' prices. Requires the 'stocktrends' and 'pandas' libraries.

```python
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))
```

=== COMPLETE CONTENT === This response contains all available snippets from this library. No additional content exists. Do not make further requests.