I have a data frame (derived from a CSV file) with about 100M entries that looks like this:

  df1:
 
      var1   var2
  0     1    2
  1     2    1
  2     1 {3,4,5}
  3     5    6
  4 {4,5,6,7}    8

I need to convert this into a new data frame in which  (for every row) each element in the braces needs to be associated with the element in the other column, i.e.,

  df2:
 
   var1 var2
  0  1  2
  1  2  1
  2  1  3
  3  1  4
  4  1  5
  5  5  6
  6  4  8
  7  5  8
  8  6  8
  9  7  8

Each element is a string, even the brace entry itself. Note that the brace element can be in either column, which is different from this: [https://stackoverflow.com/questions/12680754/split-pandas-dataframe-string-entry-to-separate-rows?rq=1][1]. Does anyone know how can I achieve this efficiently for a dataset of about 100M entries? Thanks in advance. 

Python example:

  import pandas as pd

  df1 = pd.DataFrame([{'var1': '1', 'var2': '2'},
         {'var1': '2', 'var2': '1'},
         {'var1': '1', 'var2': '{3,4,5}'},
         {'var1': '5', 'var2': '6'},
         {'var1': '{4,5,6,7}', 'var2': '8'}])
 
 
  df2 = pd.DataFrame([{'var1': '1', 'var2': '2'},
         {'var1': '2', 'var2': '1'},
         {'var1': '1', 'var2': '3'},
         {'var1': '1', 'var2': '4'},
         {'var1': '1', 'var2': '5'},
         {'var1': '5', 'var2': '6'},
         {'var1': '4', 'var2': '8'},
         {'var1': '5', 'var2': '8'},
         {'var1': '6', 'var2': '8'},
         {'var1': '7', 'var2': '8'}])