Series.dot(other) [source] Matrix multiplication with DataFrame or inner-product with Series objects Parameters: other : Series or DataFrame Returns: dot_product : scalar or Series

TimedeltaIndex.nbytes return the number of bytes in the underlying data

TimedeltaIndex.dtype_str = None

Series.dt.normalize(*args, **kwargs) [source] Return DatetimeIndex with times to midnight. Length is unaltered Returns: normalized : DatetimeIndex

Series.get_ftype_counts() [source] Return the counts of ftypes in this object.

DataFrame.get(key, default=None) [source] Get item from object for given key (DataFrame column, Panel slice, etc.). Returns default value if not found. Parameters: key : object Returns: value : type of items contained in object

Resampler.aggregate(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

Index.get_values() [source] return the underlying data as an ndarray

GroupBy.std(ddof=1, *args, **kwargs) [source] Compute standard deviation of groups, excluding missing values For multiple groupings, the result index will be a MultiIndex Parameters: ddof : integer, default 1 degrees of freedom See also pandas.Series.groupby, pandas.DataFrame.groupby, pandas.Panel.groupby

GroupBy.ohlc() [source] Compute sum of values, excluding missing values For multiple groupings, the result index will be a MultiIndex See also pandas.Series.groupby, pandas.DataFrame.groupby, pandas.Panel.groupby