Series.to_hdf(path_or_buf, key, **kwargs) [source] Write the contained data to an HDF5 file using HDFStore. Parameters: path_or_buf : the path (string) or HDFStore object key : string indentifier for the group in the store mode : optional, {?a?, ?w?, ?r+?}, default ?a? 'w' Write; a new file is created (an existing file with the same name would be deleted). 'a' Append; an existing file is opened for reading and writing, and if the file does not exist it is created. 'r+' It is

Series.to_frame(name=None) [source] Convert Series to DataFrame Parameters: name : object, default None The passed name should substitute for the series name (if it has one). Returns: data_frame : DataFrame

Series.to_dict() [source] Convert Series to {label -> value} dict Returns: value_dict : dict

Series.to_dense() [source] Return dense representation of NDFrame (as opposed to sparse)

Series.to_csv(path=None, index=True, sep=', ', na_rep='', float_format=None, header=False, index_label=None, mode='w', encoding=None, date_format=None, decimal='.') [source] Write Series to a comma-separated values (csv) file Parameters: path : string or file handle, default None File path or object, if None is provided the result is returned as a string. na_rep : string, default ?? Missing data representation float_format : string, default None Format string for floating point number

Series.to_clipboard(excel=None, sep=None, **kwargs) [source] Attempt to write text representation of object to the system clipboard This can be pasted into Excel, for example. Parameters: excel : boolean, defaults to True if True, use the provided separator, writing in a csv format for allowing easy pasting into excel. if False, write a string representation of the object to the clipboard sep : optional, defaults to tab other keywords are passed to to_csv Notes Requirements for your pla

Series.tolist() [source] Convert Series to a nested list

Series.take(indices, axis=0, convert=True, is_copy=False, **kwargs) [source] return Series corresponding to requested indices Parameters: indices : list / array of ints convert : translate negative to positive indices (default) Returns: taken : Series See also numpy.ndarray.take

Series.tail(n=5) [source] Returns last n rows

Series.T return the transpose, which is by definition self