# Source code for pandas_ta.overlap.wcp

```# -*- coding: utf-8 -*-
from pandas_ta import Imports
from pandas_ta.utils import get_offset, verify_series

[docs]def wcp(high, low, close, talib=None, offset=None, **kwargs):
"""Indicator: Weighted Closing Price (WCP)"""
# Validate Arguments
high = verify_series(high)
low = verify_series(low)
close = verify_series(close)
offset = get_offset(offset)
mode_tal = bool(talib) if isinstance(talib, bool) else True

# Calculate Result
if Imports["talib"] and mode_tal:
from talib import WCLPRICE
wcp = WCLPRICE(high, low, close)
else:
wcp = (high + low + 2 * close) / 4

# Offset
if offset != 0:
wcp = wcp.shift(offset)

# Handle fills
if "fillna" in kwargs:
wcp.fillna(kwargs["fillna"], inplace=True)
if "fill_method" in kwargs:
wcp.fillna(method=kwargs["fill_method"], inplace=True)

# Name & Category
wcp.name = "WCP"
wcp.category = "overlap"

return wcp

wcp.__doc__ = \
"""Weighted Closing Price (WCP)

Weighted Closing Price is the weighted price given: high, low
and double the close.

Sources:
https://www.fmlabs.com/reference/default.htm?url=WeightedCloses.htm

Calculation:
WCP = (2 * close + high + low) / 4

Args:
high (pd.Series): Series of 'high's
low (pd.Series): Series of 'low's
close (pd.Series): Series of 'close's
talib (bool): If TA Lib is installed and talib is True, Returns the TA Lib
version. Default: True
offset (int): How many periods to offset the result. Default: 0

Kwargs:
fillna (value, optional): pd.DataFrame.fillna(value)
fill_method (value, optional): Type of fill method

Returns:
pd.Series: New feature generated.
"""
```