Series.mad(axis=None, skipna=None, level=None) [source] Return the mean absolute deviation of the values for the requested axis Parameters: axis : {index (0)} 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 scalar numeric_only : boolean, default None Include only float, int, boolean columns. If

Series.loc Purely label-location based indexer for selection by label. .loc[] is primarily label based, but may also be used with a boolean array. Allowed inputs are: A single label, e.g. 5 or 'a', (note that 5 is interpreted as a label of the index, and never as an integer position along the index). A list or array of labels, e.g. ['a', 'b', 'c']. A slice object with labels, e.g. 'a':'f' (note that contrary to usual python slices, both the start and the stop are included!). A boolean array

Series.lt(other, level=None, fill_value=None, axis=0) [source] Less than of series and other, element-wise (binary operator lt). 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, matchin

Series.last_valid_index() [source] Return label for last non-NA/null value

Series.le(other, level=None, fill_value=None, axis=0) [source] Less than or equal to of series and other, element-wise (binary operator le). 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 l

Series.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)} 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

Series.last(offset) [source] Convenience method for subsetting final periods of time series data based on a date offset. Parameters: offset : string, DateOffset, dateutil.relativedelta Returns: subset : type of caller Examples ts.last(?5M?) -> Last 5 months

Series.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 : {index (0)} 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 sc

Series.keys() [source] Alias for index

Series.ix A primarily label-location based indexer, with integer position fallback. .ix[] supports mixed integer and label based access. It is primarily label based, but will fall back to integer positional access unless the corresponding axis is of integer type. .ix is the most general indexer and will support any of the inputs in .loc and .iloc. .ix also supports floating point label schemes. .ix is exceptionally useful when dealing with mixed positional and label based hierachical indexe