Question: I'm looking to transform a dataframe containing [[1, 2, 3], [4, 5, 6], [7, 8, 9], [10, 11, 12]] into [[1, 2, 3, []], [4, 5, 6, [1, 2, 3, 4, 5, 6]], [7, 8, 9, [4, 5, 6, 7, 8, 9]], [10, 11, 12, [7, 8, 9, 10, 11, 12]]] So far the only working solution I've come up with is: import pandas as pd import numpy as np # Create the DataFrame df = pd.DataFrame(np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9], [10, 11, 12]])) # Initialize an empty list to store the result result = [] # Iterate over the rows in the DataFrame for i in range(len(df)): # If it's the first row, append the row with an empty list if i == 0: result.append(list(df.iloc[i]) + [[]]) # If it's not the first row, concatenate the current and previous row else: current_row = list(df.iloc[i]) previous_row = list(df.iloc[i-1]) concatenated_row = current_row + [previous_row + current_row] result.append(concatenated_row) # Print the result print(result)  Is there no build in Pandas function that can roll a window, and add the results to current row, like the above can?

Answer: This doesn't need windowing, IIUC, you can use df.shift: x = df.apply(lambda x: x.tolist(), axis=1) df[3] = (x.shift() + x)  Output:  0 1 2 3 0 1 2 3 NaN 1 4 5 6 [1, 2, 3, 4, 5, 6] 2 7 8 9 [4, 5, 6, 7, 8, 9] 3 10 11 12 [7, 8, 9, 10, 11, 12]  Adding window sizing: import pandas as pd import numpy as np from functools import reduce df = pd.DataFrame(np.arange(99).reshape(-1,3)) x = df.apply(lambda x: x.tolist(), axis=1) #change window size here window_size = 3 df[3] = reduce(lambda x, y: x+y, [x.shift(i) for i in range(window_size,-1,-1)]) df  Output:  0 1 2 3 0 0 1 2 NaN 1 3 4 5 NaN 2 6 7 8 NaN 3 9 10 11 [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11] 4 12 13 14 [3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14] 5 15 16 17 [6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17] 6 18 19 20 [9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20] 7 21 22 23 [12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23] 8 24 25 26 [15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26] 9 27 28 29 [18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29] 10 30 31 32 [21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32] 11 33 34 35 [24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35] 12 36 37 38 [27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38] 13 39 40 41 [30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41] 14 42 43 44 [33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44] 15 45 46 47 [36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47] 16 48 49 50 [39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50] 17 51 52 53 [42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53] 18 54 55 56 [45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56] 19 57 58 59 [48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59] 20 60 61 62 [51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62] 21 63 64 65 [54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65] 22 66 67 68 [57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68] 23 69 70 71 [60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71] 24 72 73 74 [63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74] 25 75 76 77 [66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77] 26 78 79 80 [69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80] 27 81 82 83 [72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83] 28 84 85 86 [75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86] 29 87 88 89 [78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89] 30 90 91 92 [81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92] 31 93 94 95 [84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95] 32 96 97 98 [87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98]