Practice. In this article, we are going to display the data of the PySpark dataframe in table format. We are going to use show () function and toPandas function to display the dataframe in the required format. show (): Used to display the dataframe. Syntax: dataframe.show ( n, vertical = True, truncate = n) where, dataframe is the input dataframe. I can view all of the columns by scrolling left/right. However, this is a bit inconvenient and I was wondering if there was an elegant way to display the table with "foldover": To generate the above, I manually chopped up the dataframe into chunks and displayed each chunk (which is why the spacing/etc is not perfect). Display all dataframe columns in a Jupyter Python Notebook. 42. Print Visually Pleasing DataFrames in For Loop in Jupyter Notebook Pandas. 0. 6. 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 I want to view all the columns of my dataframe. It has 30 columns. While trying to view a specific row, it gets truncated. I can change the global printing option pd.set_option('display.max_column # assuming df is your dataframe pd.set_option('display.max_columns', df.columns.size) # to reset this pd.reset_option('display.max_columns') Method-4: source # assuming df is your dataframe pd.set_option('max_columns', df.columns.size) # to reset this pd.reset_option('max_columns') To not wrap the output into multiple lines do this. source To explicitly reset the value use pd.reset_option(‘all’) method has to be used to revert the changes. Syntax : pandas.set_option(pat, value) Example: This code modifies global pandas display options to show all rows and columns with unlimited width and precision for the given DataFrame (df). It then resets the options to their default 1 Answer. Sorted by: 2. Notebook output shows the result of the last expression. You can explicitly print things you want to see: print (2+3) print (7+8) Or you roll multiple values into one expression, like a tuple. ( 2+3, 7+8 ) Share. If that is the content of the code cell in Jupyter, it won't display anything. However, if I add foo on a separate line afterward, it will display "This is foo!". Is there a way to configure Jupyter so that putting foo on a separate line isn't necessary for it to be displayed? There are various methods to drop one or multiple columns in Pandas Dataframe, we are discussing some generally used methods for dropping one or multiple columns in Pandas Dataframe which are the following : Using df.drop () Method. Using iloc [] Method. Using df.ix () method. Using df.loc [] Method. w0aL.