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?
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]