DatetimeIndex.is_year_start Logical indicating if first day of year (defined by frequency)

Series.ffill(axis=None, inplace=False, limit=None, downcast=None) [source] Synonym for NDFrame.fillna(method=?ffill?)

DatetimeIndex.reshape(*args, **kwargs) [source] NOT IMPLEMENTED: do not call this method, as reshaping is not supported for Index objects and will raise an error. Reshape an Index.

TimedeltaIndex.drop(labels, errors='raise') [source] Make new Index with passed list of labels deleted Parameters: labels : array-like errors : {?ignore?, ?raise?}, default ?raise? If ?ignore?, suppress error and existing labels are dropped. Returns: dropped : Index

Panel.dtypes Return the dtypes in this object.

Index.asof(label) [source] For a sorted index, return the most recent label up to and including the passed label. Return NaN if not found. See also get_loc asof is a thin wrapper around get_loc with method=?pad?

Index.str() [source] Vectorized string functions for Series and Index. NAs stay NA unless handled otherwise by a particular method. Patterned after Python?s string methods, with some inspiration from R?s stringr package. Examples >>> s.str.split('_') >>> s.str.replace('_', '')

DatetimeIndex.shift(n, freq=None) [source] Specialized shift which produces a DatetimeIndex Parameters: n : int Periods to shift by freq : DateOffset or timedelta-like, optional Returns: shifted : DatetimeIndex

HDFStore.select(key, where=None, start=None, stop=None, columns=None, iterator=False, chunksize=None, auto_close=False, **kwargs) [source] Retrieve pandas object stored in file, optionally based on where criteria Parameters: key : object where : list of Term (or convertable) objects, optional start : integer (defaults to None), row number to start selection stop : integer (defaults to None), row number to stop selection columns : a list of columns that if not None, will limit the return c

DataFrameGroupBy.all(axis=None, bool_only=None, skipna=None, level=None, **kwargs) Return whether all elements are True over requested axis 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, collapsing into a Series bool_only : boolean, default None Include only boolean c