CategoricalIndex.order(return_indexer=False, ascending=True) [source] Return sorted copy of Index DEPRECATED: use Index.sort_values()

Panel.mean(axis=None, skipna=None, level=None, numeric_only=None, **kwargs) [source] Return the mean 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

MultiIndex.get_loc(key, method=None) [source] Get integer location, slice or boolean mask for requested label or tuple. If the key is past the lexsort depth, the return may be a boolean mask array, otherwise it is always a slice or int. Parameters: key : label or tuple method : None Returns: loc : int, slice object or boolean mask

DataFrame.sortlevel(level=0, axis=0, ascending=True, inplace=False, sort_remaining=True) [source] Sort multilevel index by chosen axis and primary level. Data will be lexicographically sorted by the chosen level followed by the other levels (in order) Parameters: level : int axis : {0 or ?index?, 1 or ?columns?}, default 0 ascending : boolean, default True inplace : boolean, default False Sort the DataFrame without creating a new instance sort_remaining : boolean, default True Sort by t

Series.str.isalnum() [source] Check whether all characters in each string in the Series/Index are alphanumeric. Equivalent to str.isalnum(). Returns: is : Series/array of boolean values

Series.truncate(before=None, after=None, axis=None, copy=True) [source] Truncates a sorted NDFrame before and/or after some particular index value. If the axis contains only datetime values, before/after parameters are converted to datetime values. Parameters: before : date Truncate before index value after : date Truncate after index value axis : the truncation axis, defaults to the stat axis copy : boolean, default is True, return a copy of the truncated section Returns: truncate

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

Series.reset_index(level=None, drop=False, name=None, inplace=False) [source] Analogous to the pandas.DataFrame.reset_index() function, see docstring there. Parameters: level : int, str, tuple, or list, default None Only remove the given levels from the index. Removes all levels by default drop : boolean, default False Do not try to insert index into dataframe columns name : object, default None The name of the column corresponding to the Series values inplace : boolean, default Fals

DataFrame.iterrows() [source] Iterate over DataFrame rows as (index, Series) pairs. Returns: it : generator A generator that iterates over the rows of the frame. See also itertuples Iterate over DataFrame rows as namedtuples of the values. iteritems Iterate over (column name, Series) pairs. Notes Because iterrows returns a Series for each row, it does not preserve dtypes across the rows (dtypes are preserved across columns for DataFrames). For example, >>> df = pd.Data

Panel4D.mad(axis=None, skipna=None, level=None) [source] Return the mean absolute deviation of the values for the 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 level : int or level name, default None If the axis is a MultiIndex (hierarchical), count along a particular level, collapsing into a Panel numeric_only : boolean, default None