Panel4D.drop(labels, axis=0, level=None, inplace=False, errors='raise') [source] Return new object with labels in requested axis removed. Parameters: labels : single label or list-like axis : int or axis name level : int or level name, default None For MultiIndex inplace : bool, default False If True, do operation inplace and return None. errors : {?ignore?, ?raise?}, default ?raise? If ?ignore?, suppress error and existing labels are dropped. New in version 0.16.1. Returns: drop

Panel4D.divide(other, axis=0) [source] Floating division of series and other, element-wise (binary operator truediv). Equivalent to panel / other. Parameters: other : Panel or Panel4D axis : {labels, items, major_axis, minor_axis} Axis to broadcast over Returns: Panel4D See also Panel4D.rtruediv

Panel4D.div(other, axis=0) [source] Floating division of series and other, element-wise (binary operator truediv). Equivalent to panel / other. Parameters: other : Panel or Panel4D axis : {labels, items, major_axis, minor_axis} Axis to broadcast over Returns: Panel4D See also Panel4D.rtruediv

Panel4D.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

Panel4D.cumsum(axis=None, skipna=True, *args, **kwargs) [source] Return cumulative sum over requested axis. Parameters: axis : {labels (0), items (1), major_axis (2), minor_axis (3)} skipna : boolean, default True Exclude NA/null values. If an entire row/column is NA, the result will be NA Returns: cumsum : Panel

Panel4D.cumprod(axis=None, skipna=True, *args, **kwargs) [source] Return cumulative product over requested axis. Parameters: axis : {labels (0), items (1), major_axis (2), minor_axis (3)} skipna : boolean, default True Exclude NA/null values. If an entire row/column is NA, the result will be NA Returns: cumprod : Panel

Panel4D.cummin(axis=None, skipna=True, *args, **kwargs) [source] Return cumulative minimum over requested axis. Parameters: axis : {labels (0), items (1), major_axis (2), minor_axis (3)} skipna : boolean, default True Exclude NA/null values. If an entire row/column is NA, the result will be NA Returns: cummin : Panel

Panel4D.cummax(axis=None, skipna=True, *args, **kwargs) [source] Return cumulative max over requested axis. Parameters: axis : {labels (0), items (1), major_axis (2), minor_axis (3)} skipna : boolean, default True Exclude NA/null values. If an entire row/column is NA, the result will be NA Returns: cummax : Panel

Panel4D.count(axis='major') [source] Return number of observations over requested axis. Parameters: axis : {?items?, ?major?, ?minor?} or {0, 1, 2} Returns: count : DataFrame

Panel4D.copy(deep=True) [source] Make a copy of this objects data. Parameters: deep : boolean or string, default True Make a deep copy, including a copy of the data and the indices. With deep=False neither the indices or the data are copied. Note that when deep=True data is copied, actual python objects will not be copied recursively, only the reference to the object. This is in contrast to copy.deepcopy in the Standard Library, which recursively copies object data. Returns: copy : typ