text: Title: Lacking Documentation
  Body: Could you please add somewhere in the doc a minimal working example on how to exactly use a `strategy` - ideally leveraging `Python classes` in order to be modular with the strategies?
  
  My first assumption was that running a strategy on a given `dataset` would filter out the rows and keep only the complying ones but that does not appear to be the case.
  
  Please confirm if a strategy simply adds the relevant technical indicators to a dataset.
  
  This is an example of what I have tried, and nothing happened:
  
  ```python
          df = fetch_bars(exchange, args.symbol, limit=1)
  
          NonMPStrategy = ta.Strategy(
              name="EMAs, BBs, and MACD",
              description="Non Multiprocessing Strategy by rename Columns",
              ta=[
                  {"kind": "ema", "length": 8},
                  {"kind": "ema", "length": 21},
                  {"kind": "bbands", "length": 20, "col_names": ("BBL", "BBM", "BBU")},
                  {"kind": "macd", "fast": 8, "slow": 21, "col_names": ("MACD", "MACD_H", "MACD_S")}
              ]
          )
  
          df.ta.strategy(ta.CommonStrategy, verbose=True)
  
          print(df)
  ```
  
  Also, what about the `signals`, are they `Booleans` to indicate buy/sell signals?
  
  I am a bit lost with this lib... more documentation and examples would be great!