Divide rows of python pandas DataFrame

Question

I have a pandas DataFrame df like this

   mat  time
0  101   20
1  102    7
2  103   15

I need to divide the rows so the column of time doesn't have any values higher than t=10 to have something like this

   mat  time
0  101   10
2  101   10
3  102    7
4  103   10
5  103    5

the index doesn't matter

If I'd use groupby('mat')['time'].sum() on this df I would have the original df, but I need like an inverse of the groupby func.

Is there any way to get the ungrouped DataFrame with the condition of time <= t?

I'm trying to use a loop here but it's kind of 'unPythonic', any ideas?

Answer 1

Use an apply function that loops until all are less than 10.

def split_max_time(df):
    new_df = df.copy()
    while new_df.iloc[-1, -1] > 10:
        temp = new_df.iloc[-1, -1]
        new_df.iloc[-1, -1] = 10
        new_df = pd.concat([new_df, new_df])
        new_df.iloc[-1, -1] = temp - 10
    return new_df


print df.groupby('mat', group_keys=False).apply(split_max_time)

   mat  time
0  101    10
0  101    10
1  102     7
2  103    10
2  103     5