Panel.skew(axis=None, skipna=None, level=None, numeric_only=None, **kwargs) [source] Return unbiased skew over requested axis Normalized by N-1 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

Series.dt.daysinmonth The number of days in the month New in version 0.16.0.

Index.duplicated(*args, **kwargs) [source] Return boolean np.ndarray denoting duplicate values Parameters: keep : {?first?, ?last?, False}, default ?first? first : Mark duplicates as True except for the first occurrence. last : Mark duplicates as True except for the last occurrence. False : Mark all duplicates as True. take_last : deprecated Returns: duplicated : np.ndarray

CategoricalIndex.rename_categories(*args, **kwargs) [source] Renames categories. The new categories has to be a list-like object. All items must be unique and the number of items in the new categories must be the same as the number of items in the old categories. Parameters: new_categories : Index-like The renamed categories. inplace : boolean (default: False) Whether or not to rename the categories inplace or return a copy of this categorical with renamed categories. Returns: cat :

Index.get_loc(key, method=None, tolerance=None) [source] Get integer location for requested label Parameters: key : label method : {None, ?pad?/?ffill?, ?backfill?/?bfill?, ?nearest?}, optional default: exact matches only. pad / ffill: find the PREVIOUS index value if no exact match. backfill / bfill: use NEXT index value if no exact match nearest: use the NEAREST index value if no exact match. Tied distances are broken by preferring the larger index value. tolerance : optional Maximum d

MultiIndex.get_locs(tup) [source] Given a tuple of slices/lists/labels/boolean indexer to a level-wise spec produce an indexer to extract those locations Parameters: key : tuple of (slices/list/labels) Returns: locs : integer list of locations or boolean indexer suitable for passing to iloc

DataFrame.plot.barh(x=None, y=None, **kwds) [source] Horizontal bar plot New in version 0.17.0. Parameters: x, y : label or position, optional Coordinates for each point. **kwds : optional Keyword arguments to pass on to pandas.DataFrame.plot(). Returns: axes : matplotlib.AxesSubplot or np.array of them

Index.is_(other) [source] More flexible, faster check like is but that works through views Note: this is not the same as Index.identical(), which checks that metadata is also the same. Parameters: other : object other object to compare against. Returns: True if both have same underlying data, False otherwise : bool

DatetimeIndex.indexer_between_time(start_time, end_time, include_start=True, include_end=True) [source] Select values between particular times of day (e.g., 9:00-9:30AM). Return values of the index between two times. If start_time or end_time are strings then tseres.tools.to_time is used to convert to a time object. Parameters: start_time, end_time : datetime.time, str datetime.time or string in appropriate format (?%H:%M?, ?%H%M?, ?%I:%M%p?, ?%I%M%p?, ?%H:%M:%S?, ?%H%M%S?, ?%I:%M:%S%p?,

Series.to_hdf(path_or_buf, key, **kwargs) [source] Write the contained data to an HDF5 file using HDFStore. Parameters: path_or_buf : the path (string) or HDFStore object key : string indentifier for the group in the store mode : optional, {?a?, ?w?, ?r+?}, default ?a? 'w' Write; a new file is created (an existing file with the same name would be deleted). 'a' Append; an existing file is opened for reading and writing, and if the file does not exist it is created. 'r+' It is