Series.reindex(index=None, **kwargs) [source] Conform Series to new index with optional filling logic, placing NA/NaN in locations having no value in the previous index. A new object is produced unless the new index is equivalent to the current one and copy=False Parameters: index : array-like, optional (can be specified in order, or as keywords) New labels / index to conform to. Preferably an Index object to avoid duplicating data method : {None, ?backfill?/?bfill?, ?pad?/?ffill?, ?near

CategoricalIndex.view(cls=None) [source]

pandas.notnull(obj) [source] Replacement for numpy.isfinite / -numpy.isnan which is suitable for use on object arrays. Parameters: arr : ndarray or object value Object to check for not-null-ness Returns: isnulled : array-like of bool or bool Array or bool indicating whether an object is not null or if an array is given which of the element is not null. See also pandas.isnull boolean inverse of pandas.notnull

MultiIndex.equals(other) [source] Determines if two MultiIndex objects have the same labeling information (the levels themselves do not necessarily have to be the same) See also equal_levels

CategoricalIndex.is_type_compatible(kind) [source]

TimedeltaIndex.sym_diff(*args, **kwargs) [source]

DataFrame.iat Fast integer location scalar accessor. Similarly to iloc, iat provides integer based lookups. You can also set using these indexers.

TimedeltaIndex.inferred_freq = None

Series.kurtosis(axis=None, skipna=None, level=None, numeric_only=None, **kwargs) [source] Return unbiased kurtosis over requested axis using Fisher?s definition of kurtosis (kurtosis of normal == 0.0). Normalized by N-1 Parameters: axis : {index (0)} skipna : boolean, default True Exclude NA/null values. If an entire row/column is NA, the result will be NA level : int or level name, default None If the axis is a MultiIndex (hierarchical), count along a particular level, collapsing into

The pandas I/O API is a set of top level reader functions accessed like pd.read_csv() that generally return a pandas object. read_csv read_excel read_hdf read_sql read_json read_msgpack (experimental) read_html read_gbq (experimental) read_stata read_sas read_clipboard read_pickle The corresponding writer functions are object methods that are accessed like df.to_csv() to_csv to_excel to_hdf to_sql to_json to_msgpack (experimental) to_html to_gbq (experimental) to_stata to_clipboard to_