Panel.conform()

Panel.conform(frame, axis='items') [source] Conform input DataFrame to align with chosen axis pair. Parameters: frame : DataFrame axis : {?items?, ?major?, ?minor?} Axis the input corresponds to. E.g., if axis=?major?, then the frame?s columns would be items, and the index would be values of the minor axis Returns: DataFrame

Panel.consolidate()

Panel.consolidate(inplace=False) [source] Compute NDFrame with ?consolidated? internals (data of each dtype grouped together in a single ndarray). Mainly an internal API function, but available here to the savvy user Parameters: inplace : boolean, default False If False return new object, otherwise modify existing object Returns: consolidated : type of caller

Panel.clip_lower()

Panel.clip_lower(threshold, axis=None) [source] Return copy of the input with values below given value(s) truncated. Parameters: threshold : float or array_like axis : int or string axis name, optional Align object with threshold along the given axis. Returns: clipped : same type as input See also clip

Panel.clip_upper()

Panel.clip_upper(threshold, axis=None) [source] Return copy of input with values above given value(s) truncated. Parameters: threshold : float or array_like axis : int or string axis name, optional Align object with threshold along the given axis. Returns: clipped : same type as input See also clip

Panel.compound()

Panel.compound(axis=None, skipna=None, level=None) [source] Return the compound percentage of the values for the requested axis Parameters: axis : {items (0), major_axis (1), minor_axis (2)} 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 DataFrame numeric_only : boolean, default None Include o

Panel.blocks

Panel.blocks Internal property, property synonym for as_blocks()

Panel.bool()

Panel.bool() [source] Return the bool of a single element PandasObject. This must be a boolean scalar value, either True or False. Raise a ValueError if the PandasObject does not have exactly 1 element, or that element is not boolean

Panel.clip()

Panel.clip(lower=None, upper=None, axis=None, *args, **kwargs) [source] Trim values at input threshold(s). Parameters: lower : float or array_like, default None upper : float or array_like, default None axis : int or string axis name, optional Align object with lower and upper along the given axis. Returns: clipped : Series Examples >>> df 0 1 0 0.335232 -1.256177 1 -1.367855 0.746646 2 0.027753 -1.176076 3 0.230930 -0.679613 4 1.261967 0.570967 >>> d

Panel.between_time()

Panel.between_time(start_time, end_time, include_start=True, include_end=True) [source] Select values between particular times of the day (e.g., 9:00-9:30 AM). Parameters: start_time : datetime.time or string end_time : datetime.time or string include_start : boolean, default True include_end : boolean, default True Returns: values_between_time : type of caller

Panel.bfill()

Panel.bfill(axis=None, inplace=False, limit=None, downcast=None) [source] Synonym for NDFrame.fillna(method=?bfill?)