CODEWITHSUNDEEP
pythonpython-2.7numpy
Condo_programmer
Condo_programmer

Reputation: 236

python read 2d in to a 1d array

I have a 2D txt file:

[[1406], [1408], [1402], [1394, 102462], [1393], [20388], [20387, 20386], [1386], [1443, 1446, 766], [1432, 1438, 1430, 1416], [1442], [1434], [1430, 1416, 1417, 1419, 3446], [1429], [20011], [20015], [4435], [4441], [4443], [4444], [4448], [2433, 1413, 1418], [4450], [3444], [2478, 823, 3447], [3447], [2481, 1425, 942, 2476, 4449], [2482, 120, 3444], [13512], [3446], [13528]]

Is there any way that I can read this file into python? I tried with:

from numpy import genfromtxt
con2 = genfromtxt('muti.txt', delimiter=',')
con2 = con2.astype(np.int64)

And the result shows like:

nan
nan
nan
nan
nan
nan
nan
1413.0
nan
nan
nan
nan
823.0
nan
nan
nan
1425.0
942.0
2476.0
nan
nan
120.0
nan
nan
nan
nan

A lot of nan within the array. Could someone please help me with it?

Upvotes: 1

Views: 439

Answers (2)

tglaria
tglaria

Reputation: 5866

If this is just text, then just replace/remove the brackets, split, an cast to int.

txt = "[[1406], [1408], [1402], [1394, 102462], [1393], [20388], [20387, 20386], [1386], [1443, 1446, 766], [1432, 1438, 1430, 1416], [1442], [1434], [1430, 1416, 1417, 1419, 3446], [1429], [20011], [20015], [4435], [4441], [4443], [4444], [4448], [2433, 1413, 1418], [4450], [3444], [2478, 823, 3447], [3447], [2481, 1425, 942, 2476, 4449], [2482, 120, 3444], [13512], [3446], [13528]]"
data = [int(t) for t in txt.replace("]","").replace("[","").split(',')]

[1406,
1408,
1402,
1394,
...
13512,
3446,
13528]

Upvotes: 1

senshin
senshin

Reputation: 10350

I don't know what functionality numpy has for this, but since your text file happens to be valid JSON, you could just load it as JSON, flatten it, and then convert the result to a numpy array.

>>> import json
>>> import numpy as np
>>> with open('muti.txt', 'r') as f: arr = json.load(f)
>>> np_arr = np.array([n for subarr in arr for n in subarr]).astype(np.int64)
>>> np_arr
array([  1406,   1408,   1402,   1394, 102462,   1393,  20388,  20387,
        20386,   1386,   1443,   1446,    766,   1432,   1438,   1430,
         1416,   1442,   1434,   1430,   1416,   1417,   1419,   3446,
         1429,  20011,  20015,   4435,   4441,   4443,   4444,   4448,
         2433,   1413,   1418,   4450,   3444,   2478,    823,   3447,
         3447,   2481,   1425,    942,   2476,   4449,   2482,    120,
         3444,  13512,   3446,  13528], dtype=int64)

Upvotes: 3

Related Questions