Pandas dataframe: How to export a list of lists of values grouped by value in another column-CodePudding

So given a df like:

    timestamp   x_1  y_1   x_2  y_2
0  1649010310     1    4     7    7
1  1649010310     7    8     0    1
2  1649010310     5    1     0    0
3  1649010311     2    0     1    6
4  1649010311     8    4     2    7

I'd like to export a list of the x_1, y_1, x_2, y_2 coordinates grouped by the timestamp

Is there a faster way than using a for loop through the df to export a list of lists like:

[[[1, 4, 7, 7],
  [7, 8, 0, 1],
  [5, 1, 0, 0]],
 [[2, 0, 1, 6],
  [8, 4, 2, 7]]]

Of course we can loop over the df using something like:

for i in range(len(df)):
    # create list of lists

But, I was wondering if there was something that was more efficient in pandas (or numpy?) that could make this process faster.

CodePudding user response：

Yes, you can use groupby and apply methods.

grouped = df.groupby('timestamp')
result = grouped[['x_1', 'y_1', 'x_2', 'y_2']].apply(lambda x: x.values.tolist())
result = result.tolist()