Split (explode) pandas dataframe string entry to separate rows

Question

I have a pandas dataframe in which one column of text strings contains comma-separated values. I want to split each CSV field and create a new row per entry (as

Answer 1

Pandas >= 0.25

Series and DataFrame methods define a .explode() method that explodes lists into separate rows. See the docs section on Exploding a list-like column.

Since you have a list of comma separated strings, split the string on comma to get a list of elements, then call explode on that column.

df = pd.DataFrame({'var1': ['a,b,c', 'd,e,f'], 'var2': [1, 2]})
df
    var1  var2
0  a,b,c     1
1  d,e,f     2

df.assign(var1=df['var1'].str.split(',')).explode('var1')

  var1  var2
0    a     1
0    b     1
0    c     1
1    d     2
1    e     2
1    f     2

Note that explode only works on a single column (for now).

---

NaNs and empty lists get the treatment they deserve without you having to jump through hoops to get it right.

df = pd.DataFrame({'var1': ['d,e,f', '', np.nan], 'var2': [1, 2, 3]})
df
    var1  var2
0  d,e,f     1
1            2
2    NaN     3

df['var1'].str.split(',')

0    [d, e, f]
1           []
2          NaN

df.assign(var1=df['var1'].str.split(',')).explode('var1')

  var1  var2
0    d     1
0    e     1
0    f     1
1          2  # empty list entry becomes empty string after exploding 
2  NaN     3  # NaN left un-touched

This is a serious advantage over ravel + repeat -based solutions (which ignore empty lists completely, and choke on NaNs).