Series([client, index_pattern, name, …])
Series
pandas.Series like API that proxies into Elasticsearch index(es).
Axes
Series.index
Return eland index referencing Elasticsearch field to index a DataFrame/Series
Series.shape
Return a tuple representing the dimensionality of the Series.
Series.name
Series.empty
Determines if the Series is empty.
Series.head(self[, n])
Series.head
Series.tail(self[, n])
Series.tail
Series.add(self, right)
Series.add
Return addition of series and right, element-wise (binary operator add).
Series.sub(self, right)
Series.sub
Return subtraction of series and right, element-wise (binary operator sub).
Series.mul(self, right)
Series.mul
Return multiplication of series and right, element-wise (binary operator mul).
Series.div(self, right)
Series.div
Return floating division of series and right, element-wise (binary operator truediv).
Series.truediv(self, right)
Series.truediv
Series.floordiv(self, right)
Series.floordiv
Return integer division of series and right, element-wise (binary operator floordiv //).
Series.mod(self, right)
Series.mod
Return modulo of series and right, element-wise (binary operator mod %).
Series.pow(self, right)
Series.pow
Return exponential power of series and right, element-wise (binary operator pow).
Series.radd(self, left)
Series.radd
Return addition of series and left, element-wise (binary operator add).
Series.rsub(self, left)
Series.rsub
Return subtraction of series and left, element-wise (binary operator sub).
Series.rmul(self, left)
Series.rmul
Return multiplication of series and left, element-wise (binary operator mul).
Series.rdiv(self, left)
Series.rdiv
Return division of series and left, element-wise (binary operator div).
Series.rtruediv(self, left)
Series.rtruediv
Series.rfloordiv(self, left)
Series.rfloordiv
Return integer division of series and left, element-wise (binary operator floordiv //).
Series.rmod(self, left)
Series.rmod
Return modulo of series and left, element-wise (binary operator mod %).
Series.rpow(self, left)
Series.rpow
Return exponential power of series and left, element-wise (binary operator pow).
Series.describe(self)
Series.describe
Generate descriptive statistics that summarize the central tendency, dispersion and shape of a dataset’s distribution, excluding NaN values.
Series.max(self[, numeric_only])
Series.max
Return the maximum of the Series values
Series.mean(self[, numeric_only])
Series.mean
Return the mean of the Series values
Series.min(self[, numeric_only])
Series.min
Return the minimum of the Series values
Series.sum(self[, numeric_only])
Series.sum
Return the sum of the Series values
Series.nunique(self)
Series.nunique
Series.value_counts(self[, es_size])
Series.value_counts
Return the value counts for the specified field.
Series.rename(self, new_name)
Series.rename
Rename name of series.
Series.hist(self[, by, ax, grid, …])
Series.hist
Draw histogram of the input series using matplotlib.
Series.to_string(self[, buf, na_rep, …])
Series.to_string
Render a string representation of the Series.
Series.to_numpy(self)
Series.to_numpy
Not implemented.
Series.info_es(self)
Series.info_es