Pyspark: spark data frame column width configuration in Jupyter Notebook

Question

I have the following code in Jupyter Notebook:

import pandas as pd
pd.set_option('display.max_colwidth', 80)
my_df.select('field_1','field_2').show()

I want to increase the column width so I could see the full value of field_1 and field_2. I know we can use pd.set_option('display.max_colwidth', 80) for pandas data frame, but it doesn't seem to work for spark data frame.

Is there a way to increase the column width for the spark data frame like what we did for pandas data frame? Thanks!

Solution 1

I don't think you can set a specific width, but this will ensure your data is not cutoff no matter the size

my_df.select('field_1','field_2').show(10, truncate = False)

Solution 2

This should give you what you want

import pandas as pd
pd.set_option('display.max_colwidth', 80)
my_df.select('field_1','field_2').limit(100).toPandas()