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