Styler.render() [source] Render the built up styles to HTML New in version 0.17.1. Returns: rendered: str the rendered HTML Notes Styler objects have defined the _repr_html_ method which automatically calls self.render() when it?s the last item in a Notebook cell. When calling Styler.render() directly, wrap the result in IPython.display.HTML to view the rendered HTML in the notebook.

Series.as_matrix(columns=None) [source] Convert the frame to its Numpy-array representation. Parameters: columns: list, optional, default:None If None, return all columns, otherwise, returns specified columns. Returns: values : ndarray If the caller is heterogeneous and contains booleans or objects, the result will be of dtype=object. See Notes. See also pandas.DataFrame.values Notes Return is NOT a Numpy-matrix, rather, a Numpy-array. The dtype will be a lower-common-denominator

DataFrame.to_timestamp(freq=None, how='start', axis=0, copy=True) [source] Cast to DatetimeIndex of timestamps, at beginning of period Parameters: freq : string, default frequency of PeriodIndex Desired frequency how : {?s?, ?e?, ?start?, ?end?} Convention for converting period to timestamp; start of period vs. end axis : {0 or ?index?, 1 or ?columns?}, default 0 The axis to convert (the index by default) copy : boolean, default True If false then underlying input data is not copied

DataFrameGroupBy.resample(rule, *args, **kwargs) [source] Provide resampling when using a TimeGrouper Return a new grouper with our resampler appended See also pandas.Series.groupby, pandas.DataFrame.groupby, pandas.Panel.groupby

Panel4D.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

DatetimeIndex.get_indexer(target, method=None, limit=None, tolerance=None) [source] Compute indexer and mask for new index given the current index. The indexer should be then used as an input to ndarray.take to align the current data to the new index. Parameters: target : Index 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

Panel.swaplevel(i=-2, j=-1, axis=0) [source] Swap levels i and j in a MultiIndex on a particular axis Parameters: i, j : int, string (can be mixed) Level of index to be swapped. Can pass level name as string. Returns: swapped : type of caller (new object) Changed in version 0.18.1: The indexes i and j are now optional, and default to the two innermost levels of the index.

DatetimeIndex.get_values() [source] return the underlying data as an ndarray

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

Panel.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 s