class pandas.DatetimeIndex [source] Immutable ndarray of datetime64 data, represented internally as int64, and which can be boxed to Timestamp objects that are subclasses of datetime and carry metadata such as frequency information. Parameters: data : array-like (1-dimensional), optional Optional datetime-like data to construct index with copy : bool Make a copy of input ndarray freq : string or pandas offset object, optional One of pandas date offset strings or corresponding objects

TimedeltaIndex.is_floating() [source]

Series.nonzero() [source] Return the indices of the elements that are non-zero This method is equivalent to calling numpy.nonzero on the series data. For compatability with NumPy, the return value is the same (a tuple with an array of indices for each dimension), but it will always be a one-item tuple because series only have one dimension. See also numpy.nonzero Examples >>> s = pd.Series([0, 3, 0, 4]) >>> s.nonzero() (array([1, 3]),) >>> s.iloc[s.nonzero()[0]]

Series.dt.floor(*args, **kwargs) [source] floor the index to the specified freq Parameters: freq : freq string/object Returns: index of same type Raises: ValueError if the freq cannot be converted

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

Index.sortlevel(level=None, ascending=True, sort_remaining=None) [source] For internal compatibility with with the Index API Sort the Index. This is for compat with MultiIndex Parameters: ascending : boolean, default True False to sort in descending order level, sort_remaining are compat parameters Returns: sorted_index : Index

DataFrame.reset_index(level=None, drop=False, inplace=False, col_level=0, col_fill='') [source] For DataFrame with multi-level index, return new DataFrame with labeling information in the columns under the index names, defaulting to ?level_0?, ?level_1?, etc. if any are None. For a standard index, the index name will be used (if set), otherwise a default ?index? or ?level_0? (if ?index? is already taken) will be used. Parameters: level : int, str, tuple, or list, default None Only remove

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

TimedeltaIndex.dtype_str = None

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