diff --git a/pandas_ta/volatility/atr.py b/pandas_ta/volatility/atr.py
index 08e92da..dc275bb 100644
--- a/pandas_ta/volatility/atr.py
+++ b/pandas_ta/volatility/atr.py
@@ -3,15 +3,15 @@ from pandas_ta.overlap import ema, rma
 from .true_range import true_range
 from pandas_ta.utils import get_drift, get_offset, verify_series
 
-
-def atr(high, low, close, length=None, mamode=None, drift=None, offset=None, **kwargs):
+def atr(high, low, close, length=None, mamode='sma', drift=None, offset=None, **kwargs):
     """Indicator: Average True Range (ATR)"""
     # Validate arguments
     high = verify_series(high)
     low = verify_series(low)
     close = verify_series(close)
     length = int(length) if length and length > 0 else 14
-    mamode = mamode.lower() if mamode else "ema"
+    mamode = str(mamode).lower()
+
     drift = get_drift(drift)
     offset = get_offset(offset)
 
@@ -48,13 +48,10 @@ def atr(high, low, close, length=None, mamode=None, drift=None, offset=None, **k
 
 atr.__doc__ = \
 """Average True Range (ATR)
-
 Averge True Range is used to measure volatility, especially
 volatility caused by gaps or limit moves.
-
 Sources:
     https://www.tradingview.com/wiki/Average_True_Range_(ATR)
-
 Calculation:
     Default Inputs:
         length=14, drift=1, percent=False
@@ -66,24 +63,20 @@ Calculation:
         ATR = EMA(tr, length)
     else:
         ATR = SMA(tr, length)
-
     if percent:
         ATR *= 100 / close
-
 Args:
     high (pd.Series): Series of 'high's
     low (pd.Series): Series of 'low's
     close (pd.Series): Series of 'close's
     length (int): It's period. Default: 14
-    mamode (str): Two options: None or 'ema'. Default: 'ema'
+    mamode (str): Two options: 'sma' or 'ema'. Default: 'sma'
     drift (int): The difference period. Default: 1
     offset (int): How many periods to offset the result. Default: 0
-
 Kwargs:
     percent (bool, optional): Return as percentage. Default: False
     fillna (value, optional): pd.DataFrame.fillna(value)
     fill_method (value, optional): Type of fill method
-
 Returns:
     pd.Series: New feature generated.
 """