Series.mul(other, level=None, fill_value=None, axis=0) [source] Multiplication of series and other, element-wise (binary operator mul). Equivalent to series * other, but with support to substitute a fill_value for missing data in one of the inputs. Parameters: other: Series or scalar value fill_value : None or float value, default None (NaN) Fill missing (NaN) values with this value. If both Series are missing, the result will be missing level : int or name Broadcast across a level, mat

Panel.to_msgpack(path_or_buf=None, encoding='utf-8', **kwargs) [source] msgpack (serialize) object to input file path THIS IS AN EXPERIMENTAL LIBRARY and the storage format may not be stable until a future release. Parameters: path : string File path, buffer-like, or None if None, return generated string append : boolean whether to append to an existing msgpack (default is False) compress : type of compressor (zlib or blosc), default to None (no compression)

DataFrameGroupBy.quantile(q=0.5, axis=0, numeric_only=True, interpolation='linear') Return values at the given quantile over requested axis, a la numpy.percentile. Parameters: q : float or array-like, default 0.5 (50% quantile) 0 <= q <= 1, the quantile(s) to compute axis : {0, 1, ?index?, ?columns?} (default 0) 0 or ?index? for row-wise, 1 or ?columns? for column-wise interpolation : {?linear?, ?lower?, ?higher?, ?midpoint?, ?nearest?} New in version 0.18.0. This optional par

CategoricalIndex.sortlevel(level=None, ascending=True, sort_remaining=None) [source] For internal compatibility with with the Index API Sort the Index. This is for compat with MultiIndex Parameters: ascending : boolean, default True False to sort in descending order level, sort_remaining are compat parameters Returns: sorted_index : Index

Series.eq(other, level=None, fill_value=None, axis=0) [source] Equal to of series and other, element-wise (binary operator eq). Equivalent to series == other, but with support to substitute a fill_value for missing data in one of the inputs. Parameters: other: Series or scalar value fill_value : None or float value, default None (NaN) Fill missing (NaN) values with this value. If both Series are missing, the result will be missing level : int or name Broadcast across a level, matching I

MultiIndex.truncate(before=None, after=None) [source] Slice index between two labels / tuples, return new MultiIndex Parameters: before : label or tuple, can be partial. Default None None defaults to start after : label or tuple, can be partial. Default None None defaults to end Returns: truncated : MultiIndex

Resampler.apply(arg, *args, **kwargs) [source] Apply aggregation function or functions to resampled groups, yielding most likely Series but in some cases DataFrame depending on the output of the aggregation function Parameters: func_or_funcs : function or list / dict of functions List/dict of functions will produce DataFrame with column names determined by the function names themselves (list) or the keys in the dict Returns: Series or DataFrame See also transform Notes agg is an ali

Panel.asof(where, subset=None) [source] The last row without any NaN is taken (or the last row without NaN considering only the subset of columns in the case of a DataFrame) New in version 0.19.0: For DataFrame If there is no good value, NaN is returned. Parameters: where : date or array of dates subset : string or list of strings, default None if not None use these columns for NaN propagation Returns: where is scalar value or NaN if input is Series Series if input is DataFrame wher

GroupBy.count() [source] Compute count of group, excluding missing values See also pandas.Series.groupby, pandas.DataFrame.groupby, pandas.Panel.groupby

Panel.kurt(axis=None, skipna=None, level=None, numeric_only=None, **kwargs) [source] Return unbiased kurtosis over requested axis using Fisher?s definition of kurtosis (kurtosis of normal == 0.0). Normalized by N-1 Parameters: axis : {items (0), major_axis (1), minor_axis (2)} skipna : boolean, default True Exclude NA/null values. If an entire row/column is NA, the result will be NA level : int or level name, default None If the axis is a MultiIndex (hierarchical), count along a particu