Panel4D.asfreq(freq, method=None, how=None, normalize=False) [source] Convert TimeSeries to specified frequency. Optionally provide filling method to pad/backfill missing values. Parameters: freq : DateOffset object, or string method : {?backfill?/?bfill?, ?pad?/?ffill?}, default None Method to use for filling holes in reindexed Series (note this does not fill NaNs that already were present): ?pad? / ?ffill?: propagate last valid observation forward to next valid ?backfill? / ?bfill?: use

Styler.set_table_styles(table_styles) [source] Set the table styles on a Styler. These are placed in a <style> tag before the generated HTML table. New in version 0.17.1. Parameters: table_styles: list Each individual table_style should be a dictionary with selector and props keys. selector should be a CSS selector that the style will be applied to (automatically prefixed by the table?s UUID) and props should be a list of tuples with (attribute, value). Returns: self : Styler

Series.ge(other, level=None, fill_value=None, axis=0) [source] Greater than or equal to of series and other, element-wise (binary operator ge). Equivalent to series >= other, but with support to substitute a fill_value for missing data in one of the inputs. Parameters: other: Series or scalar value fill_value : None or float value, default None (NaN) Fill missing (NaN) values with this value. If both Series are missing, the result will be missing level : int or name Broadcast across

Series.ne(other, level=None, fill_value=None, axis=0) [source] Not equal to of series and other, element-wise (binary operator ne). Equivalent to series != other, but with support to substitute a fill_value for missing data in one of the inputs. Parameters: other: Series or scalar value fill_value : None or float value, default None (NaN) Fill missing (NaN) values with this value. If both Series are missing, the result will be missing level : int or name Broadcast across a level, matchi

CategoricalIndex.remove_unused_categories(*args, **kwargs) [source] Removes categories which are not used. Parameters: inplace : boolean (default: False) Whether or not to drop unused categories inplace or return a copy of this categorical with unused categories dropped. Returns: cat : Categorical with unused categories dropped or None if inplace. See also rename_categories, reorder_categories, add_categories, remove_categories, set_categories

Series.irow(i, axis=0) [source] DEPRECATED. Use .iloc[i] or .iat[i] instead

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

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

Panel4D.iloc Purely integer-location based indexing for selection by position. .iloc[] is primarily integer position based (from 0 to length-1 of the axis), but may also be used with a boolean array. Allowed inputs are: An integer, e.g. 5. A list or array of integers, e.g. [4, 3, 0]. A slice object with ints, e.g. 1:7. A boolean array. A callable function with one argument (the calling Series, DataFrame or Panel) and that returns valid output for indexing (one of the above) .iloc will raise

DataFrame.kurt(axis=None, skipna=None, level=None, numeric_only=None, **kwargs) [source] Return unbiased kurtosis over requested axis using Fisher?s definition of kurtosis (kurtosis of normal == 0.0). Normalized by N-1 Parameters: axis : {index (0), columns (1)} 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, coll