DataFrame.rmul(other, axis='columns', level=None, fill_value=None) [source] Multiplication of dataframe and other, element-wise (binary operator rmul). Equivalent to other * dataframe, but with support to substitute a fill_value for missing data in one of the inputs. Parameters: other : Series, DataFrame, or constant axis : {0, 1, ?index?, ?columns?} For Series input, axis to match Series index on fill_value : None or float value, default None Fill missing (NaN) values with this value.

DataFrameGroupBy.boxplot(grouped, subplots=True, column=None, fontsize=None, rot=0, grid=True, ax=None, figsize=None, layout=None, **kwds) [source] Make box plots from DataFrameGroupBy data. Parameters: grouped : Grouped DataFrame subplots : False - no subplots will be used True - create a subplot for each group column : column name or list of names, or vector Can be any valid input to groupby fontsize : int or string rot : label rotation angle grid : Setting this to True will show th

MultiIndex.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. The mask determines whether labels are found or not in the current index Parameters: target : MultiIndex or Index (of tuples) method : {?pad?, ?ffill?, ?backfill?, ?bfill?} pad / ffill: propagate LAST valid observation forward to next valid bac

Expanding.count(**kwargs) [source] expanding count of number of non-NaN observations inside provided window. Returns: same type as input See also pandas.Series.expanding, pandas.DataFrame.expanding

DataFrame.sem(axis=None, skipna=None, level=None, ddof=1, numeric_only=None, **kwargs) [source] Return unbiased standard error of the mean over requested axis. Normalized by N-1 by default. This can be changed using the ddof argument 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 particu

Series.median(axis=None, skipna=None, level=None, numeric_only=None, **kwargs) [source] Return the median of the values for the requested axis Parameters: axis : {index (0)} 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 scalar numeric_only : boolean, default None Include only float, int, bool

pandas.test = > [source] Run tests for module using nose. Parameters: label : {?fast?, ?full?, ??, attribute identifier}, optional Identifies the tests to run. This can be a string to pass to the nosetests executable with the ?-A? option, or one of several special values. Special values are: ?fast? - the default - which corresponds to the nosetests -A option of ?not slow?. ?full? - fast (as above) and slow tests as in the ?no -A? option to nosetests - this is the same as ??. None or ??

Expanding.cov(other=None, pairwise=None, ddof=1, **kwargs) [source] expanding sample covariance Parameters: other : Series, DataFrame, or ndarray, optional if not supplied then will default to self and produce pairwise output pairwise : bool, default None If False then only matching columns between self and other will be used and the output will be a DataFrame. If True then all pairwise combinations will be calculated and the output will be a Panel in the case of DataFrame inputs. In th

DataFrame.combineMult(other) [source] DEPRECATED. Use DataFrame.mul(other, fill_value=1.) instead. Multiply two DataFrame objects and do not propagate NaN values, so if for a (column, time) one frame is missing a value, it will default to the other frame?s value (which might be NaN as well) Parameters: other : DataFrame Returns: DataFrame See also DataFrame.mul

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