Series.to_xarray() [source] Return an xarray object from the pandas object. Returns: a DataArray for a Series a Dataset for a DataFrame a DataArray for higher dims Notes See the xarray docs Examples >>> df = pd.DataFrame({'A' : [1, 1, 2], 'B' : ['foo', 'bar', 'foo'], 'C' : np.arange(4.,7)}) >>> df A B C 0 1 foo 4.0 1 1 bar 5.0 2 2 foo 6.0 >>> df.to_xarray() <xarray.Dataset> Dimensions: (inde

Series.transpose(*args, **kwargs) [source] return the transpose, which is by definition self

Series.to_timestamp(freq=None, how='start', copy=True) [source] Cast to datetimeindex of timestamps, at beginning of period Parameters: freq : string, default frequency of PeriodIndex Desired frequency how : {?s?, ?e?, ?start?, ?end?} Convention for converting period to timestamp; start of period vs. end Returns: ts : Series with DatetimeIndex

Series.to_string(buf=None, na_rep='NaN', float_format=None, header=True, index=True, length=False, dtype=False, name=False, max_rows=None) [source] Render a string representation of the Series Parameters: buf : StringIO-like, optional buffer to write to na_rep : string, optional string representation of NAN to use, default ?NaN? float_format : one-parameter function, optional formatter function to apply to columns? elements if they are floats default None header: boolean, default Tru

Series.to_sql(name, con, flavor=None, schema=None, if_exists='fail', index=True, index_label=None, chunksize=None, dtype=None) [source] Write records stored in a DataFrame to a SQL database. Parameters: name : string Name of SQL table con : SQLAlchemy engine or DBAPI2 connection (legacy mode) Using SQLAlchemy makes it possible to use any DB supported by that library. If a DBAPI2 object, only sqlite3 is supported. flavor : ?sqlite?, default None DEPRECATED: this parameter will be remov

Series.to_pickle(path) [source] Pickle (serialize) object to input file path. Parameters: path : string File path

Series.to_period(freq=None, copy=True) [source] Convert Series from DatetimeIndex to PeriodIndex with desired frequency (inferred from index if not passed) Parameters: freq : string, default Returns: ts : Series with PeriodIndex

Series.to_sparse(kind='block', fill_value=None) [source] Convert Series to SparseSeries Parameters: kind : {?block?, ?integer?} fill_value : float, defaults to NaN (missing) Returns: sp : SparseSeries

Series.to_msgpack(path_or_buf=None, encoding='utf-8', **kwargs) [source] msgpack (serialize) object to input file path THIS IS AN EXPERIMENTAL LIBRARY and the storage format may not be stable until a future release. Parameters: path : string File path, buffer-like, or None if None, return generated string append : boolean whether to append to an existing msgpack (default is False) compress : type of compressor (zlib or blosc), default to None (no compression)

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