Series.dt.daysinmonth The number of days in the month New in version 0.16.0.

Series.dt.ceil(*args, **kwargs) [source] ceil the index to the specified freq Parameters: freq : freq string/object Returns: index of same type Raises: ValueError if the freq cannot be converted

DatetimeIndex.daysinmonth The number of days in the month New in version 0.16.0.

DatetimeIndex.floor(freq) [source] floor the index to the specified freq Parameters: freq : freq string/object Returns: index of same type Raises: ValueError if the freq cannot be converted

DatetimeIndex.drop(labels, errors='raise') [source] Make new Index with passed list of labels deleted Parameters: labels : array-like errors : {?ignore?, ?raise?}, default ?raise? If ?ignore?, suppress error and existing labels are dropped. Returns: dropped : Index

Panel4D.cummax(axis=None, skipna=True, *args, **kwargs) [source] Return cumulative max 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: cummax : Panel

DataFrame.at Fast label-based scalar accessor Similarly to loc, at provides label based scalar lookups. You can also set using these indexers.

pandas.pivot(index, columns, values) [source] Produce ?pivot? table based on 3 columns of this DataFrame. Uses unique values from index / columns and fills with values. Parameters: index : ndarray Labels to use to make new frame?s index columns : ndarray Labels to use to make new frame?s columns values : ndarray Values to use for populating new frame?s values Returns: DataFrame Notes Obviously, all 3 of the input arguments must have the same length

Resampler.asfreq() [source] return the values at the new freq, essentially a reindex with (no filling)

Series.unique() [source] Return np.ndarray of unique values in the object. Significantly faster than numpy.unique. Includes NA values. The order of the original is preserved. Returns: uniques : np.ndarray