DataFrame.kurtosis(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 : {index (0), columns (1)} 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 particular level,

Series.first(offset) [source] Convenience method for subsetting initial periods of time series data based on a date offset. Parameters: offset : string, DateOffset, dateutil.relativedelta Returns: subset : type of caller Examples ts.first(?10D?) -> First 10 days

Series.str.match(pat, case=True, flags=0, na=nan, as_indexer=False) [source] Deprecated: Find groups in each string in the Series/Index using passed regular expression. If as_indexer=True, determine if each string matches a regular expression. Parameters: pat : string Character sequence or regular expression case : boolean, default True If True, case sensitive flags : int, default 0 (no flags) re module flags, e.g. re.IGNORECASE na : default NaN, fill value for missing values. as_ind

Panel.prod(axis=None, skipna=None, level=None, numeric_only=None, **kwargs) [source] Return the product of the values for the requested axis 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 particular level, collapsing into a DataFrame numeric_only : boolean, default No

Series.str.find(sub, start=0, end=None) [source] Return lowest indexes in each strings in the Series/Index where the substring is fully contained between [start:end]. Return -1 on failure. Equivalent to standard str.find(). Parameters: sub : str Substring being searched start : int Left edge index end : int Right edge index Returns: found : Series/Index of integer values See also rfind Return highest indexes in each strings

DataFrame.round(decimals=0, *args, **kwargs) [source] Round a DataFrame to a variable number of decimal places. New in version 0.17.0. Parameters: decimals : int, dict, Series Number of decimal places to round each column to. If an int is given, round each column to the same number of places. Otherwise dict and Series round to variable numbers of places. Column names should be in the keys if decimals is a dict-like, or in the index if decimals is a Series. Any columns not included in de

Panel4D.to_clipboard(excel=None, sep=None, **kwargs) [source] Attempt to write text representation of object to the system clipboard This can be pasted into Excel, for example. Parameters: excel : boolean, defaults to True if True, use the provided separator, writing in a csv format for allowing easy pasting into excel. if False, write a string representation of the object to the clipboard sep : optional, defaults to tab other keywords are passed to to_csv Notes Requirements for your pl

Series.str.contains(pat, case=True, flags=0, na=nan, regex=True) [source] Return boolean Series/array whether given pattern/regex is contained in each string in the Series/Index. Parameters: pat : string Character sequence or regular expression case : boolean, default True If True, case sensitive flags : int, default 0 (no flags) re module flags, e.g. re.IGNORECASE na : default NaN, fill value for missing values. regex : bool, default True If True use re.search, otherwise use Python

Series.str.get_dummies(sep='|') [source] Split each string in the Series by sep and return a frame of dummy/indicator variables. Parameters: sep : string, default ?|? String to split on. Returns: dummies : DataFrame See also pandas.get_dummies Examples >>> Series(['a|b', 'a', 'a|c']).str.get_dummies() a b c 0 1 1 0 1 1 0 0 2 1 0 1 >>> Series(['a|b', np.nan, 'a|c']).str.get_dummies() a b c 0 1 1 0 1 0 0 0 2 1 0 1

DataFrame.pivot(index=None, columns=None, values=None) [source] Reshape data (produce a ?pivot? table) based on column values. Uses unique values from index / columns to form axes of the resulting DataFrame. Parameters: index : string or object, optional Column name to use to make new frame?s index. If None, uses existing index. columns : string or object Column name to use to make new frame?s columns values : string or object, optional Column name to use for populating new frame?s va