Splitting a List inside a Pandas DataFrame

Question

I have a csv file that contains a number of columns. Using pandas, I read this csv file into a dataframe and have a datetime index and five or six other columns.

One of

Answer 1

The way I did it was split the list into seperate columns, and then melted it to put each timestamp in a separate row.

In [48]: df = pd.DataFrame([[1,2,[1,2,4]],[4,5,[1,3]],],columns=['a','b','TimeStamp'])
    ...: df
Out[48]: 
   a  b  TimeStamp
0  1  2  [1, 2, 4]
1  4  5     [1, 3]

You can convert the column to a list and then back to a DataFrame to split it into columns:

In [53]: TScolumns = pd.DataFrame(df.TimeStamp.tolist(), )
    ...: TScolumns
Out[53]: 
   0  1   2
0  1  2   4
1  1  3 NaN

And then splice it onto the original dataframe

In [90]: df = df.drop('TimeStamp',axis=1)
In [58]: split = pd.concat([df, TScolumns], axis=1)
    ...: split
Out[58]: 
   a  b  0  1   2
0  1  2  1  2   4
1  4  5  1  3 NaN

Finally, use melt to get it into the shape you want:

In [89]: pd.melt(split, id_vars=['a', 'b'], value_name='TimeStamp')
Out[89]: 
   a  b variable  TimeStamp
0  1  2        0          1
1  4  5        0          1
2  1  2        1          2
3  4  5        1          3
4  1  2        2          4
5  4  5        2        NaN