Series.rolling(window, min_periods=None, freq=None, center=False, win_type=None, on=None, axis=0) [source] Provides rolling window calculcations. New in version 0.18.0. Parameters: window : int, or offset Size of the moving window. This is the number of observations used for calculating the statistic. Each window will be a fixed size. If its an offset then this will be the time period of each window. Each window will be a variable sized based on the observations included in the time-per

Series.dt.dayofyear The ordinal day of the year

Series.round(decimals=0, *args, **kwargs) [source] Round each value in a Series to the given number of decimals. Parameters: decimals : int Number of decimal places to round to (default: 0). If decimals is negative, it specifies the number of positions to the left of the decimal point. Returns: Series object See also numpy.around, DataFrame.round

Panel.rename(items=None, major_axis=None, minor_axis=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: items, major_axis, minor_axis : scalar, list-like, dict-like or function, optional Scalar or list-like will alter the Series.name attribute, and

Panel4D.cumsum(axis=None, skipna=True, *args, **kwargs) [source] Return cumulative sum over 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 Returns: cumsum : Panel

DataFrame.plot(x=None, y=None, kind='line', ax=None, subplots=False, sharex=None, sharey=False, layout=None, figsize=None, use_index=True, title=None, grid=None, legend=True, style=None, logx=False, logy=False, loglog=False, xticks=None, yticks=None, xlim=None, ylim=None, rot=None, fontsize=None, colormap=None, table=False, yerr=None, xerr=None, secondary_y=False, sort_columns=False, **kwds) [source] Make plots of DataFrame using matplotlib / pylab. New in version 0.17.0: Each plot kind has

Panel.divide(other, axis=0) [source] Floating division of series and other, element-wise (binary operator truediv). Equivalent to panel / other. Parameters: other : DataFrame or Panel axis : {items, major_axis, minor_axis} Axis to broadcast over Returns: Panel See also Panel.rtruediv

MultiIndex.memory_usage(deep=False) [source] Memory usage of my values Parameters: deep : bool Introspect the data deeply, interrogate object dtypes for system-level memory consumption Returns: bytes used See also numpy.ndarray.nbytes Notes Memory usage does not include memory consumed by elements that are not components of the array if deep=False

Index.holds_integer() [source]

DataFrame.shift(periods=1, freq=None, axis=0) [source] Shift index by desired number of periods with an optional time freq Parameters: periods : int Number of periods to move, can be positive or negative freq : DateOffset, timedelta, or time rule string, optional Increment to use from the tseries module or time rule (e.g. ?EOM?). See Notes. axis : {0 or ?index?, 1 or ?columns?} Returns: shifted : DataFrame Notes If freq is specified then the index values are shifted but the data is