Series.add_prefix(prefix) [source] Concatenate prefix string with panel items names. Parameters: prefix : string Returns: with_prefix : type of caller

DatetimeIndex.base return the base object if the memory of the underlying data is shared

Series.dt.microsecond The microseconds of the datetime

DatetimeIndex.nanosecond The nanoseconds of the datetime

DatetimeIndex.is_normalized = None

DataFrame.to_excel(excel_writer, sheet_name='Sheet1', na_rep='', float_format=None, columns=None, header=True, index=True, index_label=None, startrow=0, startcol=0, engine=None, merge_cells=True, encoding=None, inf_rep='inf', verbose=True) [source] Write DataFrame to a excel sheet Parameters: excel_writer : string or ExcelWriter object File path or existing ExcelWriter sheet_name : string, default ?Sheet1? Name of sheet which will contain DataFrame na_rep : string, default ?? Missing

Series.tshift(periods=1, freq=None, axis=0) [source] Shift the time index, using the index?s frequency if available. Parameters: periods : int Number of periods to move, can be positive or negative freq : DateOffset, timedelta, or time rule string, default None Increment to use from the tseries module or time rule (e.g. ?EOM?) axis : int or basestring Corresponds to the axis that contains the Index Returns: shifted : NDFrame Notes If freq is not specified then tries to use the fre

Series.cat() [source] Accessor object for categorical properties of the Series values. Be aware that assigning to categories is a inplace operation, while all methods return new categorical data per default (but can be called with inplace=True). Examples >>> s.cat.categories >>> s.cat.categories = list('abc') >>> s.cat.rename_categories(list('cab')) >>> s.cat.reorder_categories(list('cab')) >>> s.cat.add_categories(['d','e']) >>> s.cat.r

DatetimeIndex.symmetric_difference(other, result_name=None) [source] Compute the symmetric difference of two Index objects. It?s sorted if sorting is possible. Parameters: other : Index or array-like result_name : str Returns: symmetric_difference : Index Notes symmetric_difference contains elements that appear in either idx1 or idx2 but not both. Equivalent to the Index created by idx1.difference(idx2) | idx2.difference(idx1) with duplicates dropped. Examples >>> idx1 = Index(

Series.searchsorted(v, side='left', sorter=None) [source] Find indices where elements should be inserted to maintain order. Find the indices into a sorted Series self such that, if the corresponding elements in v were inserted before the indices, the order of self would be preserved. Parameters: v : array_like Values to insert into self. side : {?left?, ?right?}, optional If ?left?, the index of the first suitable location found is given. If ?right?, return the last such index. If there