Series.plot.hist()

Series.plot.hist(bins=10, **kwds) [source] Histogram New in version 0.17.0. Parameters: bins: integer, default 10 Number of histogram bins to be used **kwds : optional Keyword arguments to pass on to pandas.Series.plot(). Returns: axes : matplotlib.AxesSubplot or np.array of them

Series.imag

Series.imag

CategoricalIndex.ravel()

CategoricalIndex.ravel(order='C') [source] return an ndarray of the flattened values of the underlying data See also numpy.ndarray.ravel

CategoricalIndex.union()

CategoricalIndex.union(other) [source] Form the union of two Index objects and sorts if possible. Parameters: other : Index or array-like Returns: union : Index Examples >>> idx1 = pd.Index([1, 2, 3, 4]) >>> idx2 = pd.Index([3, 4, 5, 6]) >>> idx1.union(idx2) Int64Index([1, 2, 3, 4, 5, 6], dtype='int64')

Index.astype()

Index.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 returned. New

Index.get_duplicates()

Index.get_duplicates() [source]

DatetimeIndex.flags

DatetimeIndex.flags

Panel4D.head()

Panel4D.head(n=5) [source]

CategoricalIndex.equals()

CategoricalIndex.equals(other) [source] Determines if two CategorialIndex objects contain the same elements.

Index.difference()

Index.difference(other) [source] Return a new Index with elements from the index that are not in other. This is the set difference of two Index objects. It?s sorted if sorting is possible. Parameters: other : Index or array-like Returns: difference : Index Examples >>> idx1 = pd.Index([1, 2, 3, 4]) >>> idx2 = pd.Index([3, 4, 5, 6]) >>> idx1.difference(idx2) Int64Index([1, 2], dtype='int64')