Panel.describe(percentiles=None, include=None, exclude=None) [source] Generate various summary statistics, excluding NaN values. Parameters: percentiles : array-like, optional The percentiles to include in the output. Should all be in the interval [0, 1]. By default percentiles is [.25, .5, .75], returning the 25th, 50th, and 75th percentiles. include, exclude : list-like, ?all?, or None (default) Specify the form of the returned result. Either: None to both (default). The result will i

CategoricalIndex.symmetric_difference(other, result_name=None) [source] Compute the symmetric difference of two Index objects. It?s sorted if sorting is possible. Parameters: other : Index or array-like result_name : str Returns: symmetric_difference : Index Notes symmetric_difference contains elements that appear in either idx1 or idx2 but not both. Equivalent to the Index created by idx1.difference(idx2) | idx2.difference(idx1) with duplicates dropped. Examples >>> idx1 = Ind

Index.memory_usage(deep=False) [source] Memory usage of my values Parameters: deep : bool Introspect the data deeply, interrogate object dtypes for system-level memory consumption Returns: bytes used See also numpy.ndarray.nbytes Notes Memory usage does not include memory consumed by elements that are not components of the array if deep=False

Panel4D.rename(items=None, major_axis=None, minor_axis=None, **kwargs) [source] Alter axes input function or functions. Function / dict values must be unique (1-to-1). Labels not contained in a dict / Series will be left as-is. Extra labels listed don?t throw an error. Alternatively, change Series.name with a scalar value (Series only). Parameters: items, major_axis, minor_axis : scalar, list-like, dict-like or function, optional Scalar or list-like will alter the Series.name attribute, a

DatetimeIndex.factorize(sort=False, na_sentinel=-1) [source] Encode the object as an enumerated type or categorical variable Parameters: sort : boolean, default False Sort by values na_sentinel: int, default -1 Value to mark ?not found? Returns: labels : the indexer to the original array uniques : the unique Index

Panel.convert_objects(convert_dates=True, convert_numeric=False, convert_timedeltas=True, copy=True) [source] Deprecated. Attempt to infer better dtype for object columns Parameters: convert_dates : boolean, default True If True, convert to date where possible. If ?coerce?, force conversion, with unconvertible values becoming NaT. convert_numeric : boolean, default False If True, attempt to coerce to numbers (including strings), with unconvertible values becoming NaN. convert_timedelta

Series.dt.ceil(*args, **kwargs) [source] ceil 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.skew(axis=None, skipna=None, level=None, numeric_only=None, **kwargs) [source] Return unbiased skew over requested axis 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 a scalar numeric_only : boolean, default None Include only float, int, bo

StataWriter.write_file() [source]

DatetimeIndex.searchsorted(key, side='left', sorter=None) [source] Find indices where elements should be inserted to maintain order. Find the indices into a sorted DatetimeIndex self such that, if the corresponding elements in v were inserted before the indices, the order of self would be preserved. Parameters: key : array_like Values to insert into self. side : {?left?, ?right?}, optional If ?left?, the index of the first suitable location found is given. If ?right?, return the last su