# Source code for pandas_ta.statistics.median

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

[docs]def median(close, length=None, offset=None, **kwargs):
"""Indicator: Median"""
# Validate Arguments
length = int(length) if length and length > 0 else 30
min_periods = int(kwargs["min_periods"]) if "min_periods" in kwargs and kwargs["min_periods"] is not None else length
close = verify_series(close, max(length, min_periods))
offset = get_offset(offset)

if close is None: return

# Calculate Result
median = close.rolling(length, min_periods=min_periods).median()

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

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

# Name & Category
median.name = f"MEDIAN_{length}"
median.category = "statistics"

return median

median.__doc__ = \
"""Rolling Median

Rolling Median of over 'n' periods. Sibling of a Simple Moving Average.

Sources:
https://www.incrediblecharts.com/indicators/median_price.php

Calculation:
Default Inputs:
length=30
MEDIAN = close.rolling(length).median()

Args:
close (pd.Series): Series of 'close's
length (int): It's period. Default: 30
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.
"""
```