CategoricalIndex.holds_integer()

CategoricalIndex.holds_integer() [source]

Panel.ge()

Panel.ge(other, axis=None) [source] Wrapper for comparison method ge

TimedeltaIndex.sortlevel()

TimedeltaIndex.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

Index.summary()

Index.summary(name=None) [source]

Panel.to_sparse()

Panel.to_sparse(*args, **kwargs) [source] NOT IMPLEMENTED: do not call this method, as sparsifying is not supported for Panel objects and will raise an error. Convert to SparsePanel

DataFrame.keys()

DataFrame.keys() [source] Get the ?info axis? (see Indexing for more) This is index for Series, columns for DataFrame and major_axis for Panel.

TimedeltaIndex.data

TimedeltaIndex.data return the data pointer of the underlying data

Panel.to_json()

Panel.to_json(path_or_buf=None, orient=None, date_format='epoch', double_precision=10, force_ascii=True, date_unit='ms', default_handler=None, lines=False) [source] Convert the object to a JSON string. Note NaN?s and None will be converted to null and datetime objects will be converted to UNIX timestamps. Parameters: path_or_buf : the path or buffer to write the result string if this is None, return a StringIO of the converted string orient : string Seriesdefault is ?index? allowed valu

Series.ftypes

Series.ftypes return if the data is sparse|dense

DatetimeIndex.holds_integer()

DatetimeIndex.holds_integer() [source]