pyspark.pandas.Series.to_string#

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.

Note

This method should only be used if the resulting pandas object is expected to be small, as all the data is loaded into the driver’s memory. If the input is large, set max_rows parameter.

Parameters

bufStringIO-like, optional: buffer to write to
na_repstring, optional: string representation of NAN to use, default ‘NaN’
float_formatone-parameter function, optional: formatter function to apply to columns’ elements if they are floats default None
headerboolean, default True: Add the Series header (index name)
indexbool, optional: Add index (row) labels, default True
lengthboolean, default False: Add the Series length
dtypeboolean, default False: Add the Series dtype
nameboolean, default False: Add the Series name if not None
max_rowsint, optional: Maximum number of rows to show before truncating. If None, show all.

Returns

formattedstring (if not buffer passed)

Examples

>>> df = ps.DataFrame([(.2, .3), (.0, .6), (.6, .0), (.2, .1)], columns=['dogs', 'cats'])
>>> print(df['dogs'].to_string())
0    0.2
1    0.0
2    0.6
3    0.2

>>> print(df['dogs'].to_string(max_rows=2))
0    0.2
1    0.0