Series

Constructor

Series(es_client, es_index_pattern, name, …)

pandas.Series like API that proxies into Elasticsearch index(es).

Attributes and Underlying Data

Series.index	Return eland index referencing Elasticsearch field to index a DataFrame/Series
Series.dtype	Return the dtype object of the underlying data.
Series.dtypes	Return the pandas dtypes in the DataFrame.
Series.shape	Return a tuple representing the dimensionality of the Series.
Series.name
Series.empty	Determines if the Series is empty.
Series.ndim	Returns 1 by definition of a Series
Series.size	Return an int representing the number of elements in this object.

Indexing, Iteration

Series.head(n)
Series.tail(n)
Series.sample(n, frac, random_state)

Binary Operator Functions

Series.add(right)	Return addition of series and right, element-wise (binary operator add).
Series.sub(right)	Return subtraction of series and right, element-wise (binary operator sub).
Series.subtract(right)	Return subtraction of series and right, element-wise (binary operator sub).
Series.mul(right)	Return multiplication of series and right, element-wise (binary operator mul).
Series.multiply(right)	Return multiplication of series and right, element-wise (binary operator mul).
Series.div(right)	Return floating division of series and right, element-wise (binary operator truediv).
Series.divide(right)	Return floating division of series and right, element-wise (binary operator truediv).
Series.truediv(right)	Return floating division of series and right, element-wise (binary operator truediv).
Series.floordiv(right)	Return integer division of series and right, element-wise (binary operator floordiv //).
Series.mod(right)	Return modulo of series and right, element-wise (binary operator mod %).
Series.pow(right)	Return exponential power of series and right, element-wise (binary operator pow).
Series.radd(left)	Return addition of series and left, element-wise (binary operator add).
Series.rsub(left)	Return subtraction of series and left, element-wise (binary operator sub).
Series.rsubtract(left)	Return subtraction of series and left, element-wise (binary operator sub).
Series.rmul(left)	Return multiplication of series and left, element-wise (binary operator mul).
Series.rmultiply(left)	Return multiplication of series and left, element-wise (binary operator mul).
Series.rdiv(left)	Return division of series and left, element-wise (binary operator div).
Series.rdivide(left)	Return division of series and left, element-wise (binary operator div).
Series.rtruediv(left)	Return division of series and left, element-wise (binary operator div).
Series.rfloordiv(left)	Return integer division of series and left, element-wise (binary operator floordiv //).
Series.rmod(left)	Return modulo of series and left, element-wise (binary operator mod %).
Series.rpow(left)	Return exponential power of series and left, element-wise (binary operator pow).

Computations / Descriptive Stats

Series.describe()	Generate descriptive statistics that summarize the central tendency, dispersion and shape of a dataset’s distribution, excluding NaN values.
Series.max([numeric_only])	Return the maximum of the Series values
Series.mean([numeric_only])	Return the mean of the Series values
Series.min([numeric_only])	Return the minimum of the Series values
Series.sum([numeric_only])	Return the sum of the Series values
Series.median([numeric_only])	Return the median of the Series values
Series.mad([numeric_only])	Return median absolute deviation for a Series
Series.std([numeric_only])	Return standard deviation for a Series
Series.var([numeric_only])	Return variance for a Series
Series.nunique()	Return the number of unique values in a Series
Series.value_counts(es_size)	Return the value counts for the specified field.
Series.mode(es_size)	Calculate mode of a series

Reindexing / Selection / Label Manipulation

Series.rename(new_name)	Rename name of series.
Series.isna()	Detect missing values.
Series.notna()	Detect existing (non-missing) values.
Series.isnull()	Detect missing values.
Series.notnull()	Detect existing (non-missing) values.
Series.isin(other, pandas.core.series.Series])
Series.filter(items, like, regex, axis, str, …)	Subset the dataframe rows or columns according to the specified index labels.

Plotting

Series.hist([by, ax, grid, xlabelsize, …])

Draw histogram of the input series using matplotlib.

Serialization / IO / Conversion

Series.to_string([buf, na_rep, …])	Render a string representation of the Series.
Series.to_numpy()	Not implemented.
Series.to_pandas(show_progress)

Elasticsearch Functions

Series.es_info()
Series.es_match(text, *, match_phrase, …)	Filters data with an Elasticsearch match or match_phrase query depending on the given parameters.
Series.es_dtype	Return the Elasticsearch type of the underlying data.
Series.es_dtypes	Return the Elasticsearch dtypes in the index

eland.DataFrame.to_pandas eland.Series