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

GroupBy.apply(func, *args, **kwargs) [source] Apply function and combine results together in an intelligent way. The split-apply-combine combination rules attempt to be as common sense based as possible. For example: case 1: group DataFrame apply aggregation function (f(chunk) -> Series) yield DataFrame, with group axis having group labels case 2: group DataFrame apply transform function ((f(chunk) -> DataFrame with same indexes) yield DataFrame with resulting chunks glued together ca

DatetimeIndex.append(other) [source] Append a collection of Index options together Parameters: other : Index or list/tuple of indices Returns: appended : Index

classmethod Series.from_array(arr, index=None, name=None, dtype=None, copy=False, fastpath=False) [source]

Index.delete(loc) [source] Make new Index with passed location(-s) deleted Returns: new_index : Index