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.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). 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). 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). Return division of series and left, element-wise (binary operator div). 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¶

 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 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 Series.quantile(q, float, List[int], …) Used to calculate quantile for a given Series.

Reindexing / Selection / Label Manipulation¶

 Series.rename(new_name) Rename name of series. Detect missing values. Detect existing (non-missing) values. Detect missing values. 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. Not implemented. Series.to_pandas(show_progress)

Elasticsearch Functions¶

 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