DataFrame.mod(other, axis='columns', level=None, fill_value=None) [source] Modulo of dataframe and other, element-wise (binary operator mod). Equivalent to dataframe % other, 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. If both Da

Panel4D.mul(other, axis=0) [source] Multiplication of series and other, element-wise (binary operator mul). Equivalent to panel * other. Parameters: other : Panel or Panel4D axis : {labels, items, major_axis, minor_axis} Axis to broadcast over Returns: Panel4D See also Panel4D.rmul

Series.dt.week The week ordinal of the year

GroupBy.first() [source] Compute first of group values See also pandas.Series.groupby, pandas.DataFrame.groupby, pandas.Panel.groupby

Series.sort_values(axis=0, ascending=True, inplace=False, kind='quicksort', na_position='last') [source] Sort by the values along either axis New in version 0.17.0. Parameters: axis : {0, ?index?}, default 0 Axis to direct sorting ascending : bool or list of bool, default True Sort ascending vs. descending. Specify list for multiple sort orders. If this is a list of bools, must match the length of the by. inplace : bool, default False if True, perform operation in-place kind : {?qu

DatetimeIndex.indexer_at_time(time, asof=False) [source] Select values at particular time of day (e.g. 9:30AM) Parameters: time : datetime.time or string Returns: values_at_time : TimeSeries

DataFrame.dot(other) [source] Matrix multiplication with DataFrame or Series objects Parameters: other : DataFrame or Series Returns: dot_product : DataFrame or Series

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

Series.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

Series.rename(index=None, **kwargs) [source] Alter axes input function or functions. Function / dict values must be unique (1-to-1). Labels not contained in a dict / Series will be left as-is. Extra labels listed don?t throw an error. Alternatively, change Series.name with a scalar value (Series only). Parameters: index : scalar, list-like, dict-like or function, optional Scalar or list-like will alter the Series.name attribute, and raise on DataFrame or Panel. dict-like or functions are