Added missing batch/agg functions

[Aergonus]

This is also in support of the summarize function #837

Basically ported over https://github.com/grafana/metrictank/blob/master/expr/seriesaggregators.go

Also removed panics since they all return math.NaN

median
def safeMedian(values):
  safeValues = [v for v in values if v is not None]
  if safeValues:
    sortedVals = sorted(safeValues)
    mid = len(sortedVals) // 2
    if len(sortedVals) % 2 == 0:
      return float(sortedVals[mid-1] + sortedVals[mid]) / 2
    else:
      return sortedVals[mid]

diff
def safeDiff(values):
  safeValues = [v for v in values if v is not None]
  if safeValues:
    values = list(map(lambda x: x*-1, safeValues[1:]))
    values.insert(0, safeValues[0])
    return sum(values)

stddev
def safeStdDev(a):
  sm = safeSum(a)
  ln = safeLen(a)
  avg = safeDiv(sm,ln)
  if avg is None: return None
  sum = 0
  safeValues = [v for v in a if v is not None]
  for val in safeValues:
     sum = sum + (val - avg) * (val - avg)
  return math.sqrt(sum/ln)

range
  'range': lambda row: safeSubtract(safeMax(row), safeMin(row)),

multiply
  'multiply': lambda row: safeMul(*row),
def safeMul(*factors):
  if None in factors:
    return None

  factors = [float(x) for x in factors]
  product = reduce(lambda x,y: x*y, factors)
  return product

[Dieterbe]

term is the terminology for sum, when it's multiplication they're called factors.

[Dieterbe]

why not just return term.Val here and skip all the other stuff

[Dieterbe]

confusing name. it's not one total deviation that is squared. it's the sum of squares of deviations.

[Dieterbe]

could turn this into an early return and reduce the needed indentation

[Dieterbe]

can speed this function up by only looping once

[Dieterbe]

LGTM. thanks @Spellchaser