MultiIndex.is_monotonic alias for is_monotonic_increasing (deprecated)

MultiIndex.is_mixed() [source]

CategoricalIndex.has_duplicates

This section covers indexing with a MultiIndex and more advanced indexing features. See the Indexing and Selecting Data for general indexing documentation. Warning Whether a copy or a reference is returned for a setting operation, may depend on the context. This is sometimes called chained assignment and should be avoided. See Returning a View versus Copy Warning In 0.15.0 Index has internally been refactored to no longer sub-class ndarray but instead subclass PandasObject, similarly to the

pandas.io.json.json_normalize(data, record_path=None, meta=None, meta_prefix=None, record_prefix=None) [source] ?Normalize? semi-structured JSON data into a flat table Parameters: data : dict or list of dicts Unserialized JSON objects record_path : string or list of strings, default None Path in each object to list of records. If not passed, data will be assumed to be an array of records meta : list of paths (string or list of strings), default None Fields to use as metadata for each

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

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

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

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

TimedeltaIndex.astype(dtype, copy=True) [source] Create an Index with values cast to dtypes. The class of a new Index is determined by dtype. When conversion is impossible, a ValueError exception is raised. Parameters: dtype : numpy dtype or pandas type copy : bool, default True By default, astype always returns a newly allocated object. If copy is set to False and internal requirements on dtype are satisfied, the original data is used to create a new Index or the original Index is return