# How to print the full NumPy array without any truncation in the output?

NumPy module in Python is extensively used while working with arrays. When you are working on large arrays, if you try to print the elements of the array, you see that the output is being truncated. For example, consider the following code snippet:

import numpy as np

arr=np.arange(1001)
print(arr)

Output :

[ 0 1 2 ... 998 999 1000]

As you can see from the output, the elements after the 3rd element are being truncated and the last few elements are being shown. This happens when the elements in the array exceed 1000 elements. While this might not be a problem most of the time, in certain cases you might want to inspect every element of the array. Also, when you’re trying to output the array into the log files, the truncation of the array might be an issue.

In the article today,  let’s learn different ways to print the full NumPy Arrays without truncating the output.

## Method 1: Using numpy.set_printoptions() method

NumPy has a method set_printoptions() to determine the way the NumPy array object should be displayed.

By default, NumPy summarizes the elements in the array when the array elements cross 1000.

You can do one of the following to print all the elements of the array :

• Change the default threshold value to the size you want.
• Set the threshold to sys.maxsize or numpy.inf

### Changing the default threshold value to the size you want.

If you are expecting an array of size <= 1500 elements, and want to view all the elements of this array, then you can set the new threshold as 1500.

import numpy as np

np.set_printoptions(threshold=1500)
arr=np.arange(1500)
print(arr)

Output:

[   0    1    2    3    4    5    6    7    8    9   10   11   12   13
14   15   16   17   18   19   20   21   22   23   24   25   26   27
28   29   30   31   32   33   34   35   36   37   38   39   40   41
42   43   44   45   46   47   48   49   50   51   52   53   54   55
56   57   58   59   60   61   62   63   64   65   66   67   68   69
70   71   72   73   74   75   76   77   78   79   80   81   82   83
84   85   86   87   88   89   90   91   92   93   94   95   96   97
98   99  100  101  102  103  104  105  106  107  108  109  110  111
112  113  114  115  116  117  118  119  120  121  122  123  124  125
126  127  128  129  130  131  132  133  134  135  136  137  138  139
140  141  142  143  144  145  146  147  148  149  150  151  152  153
154  155  156  157  158  159  160  161  162  163  164  165  166  167
168  169  170  171  172  173  174  175  176  177  178  179  180  181
182  183  184  185  186  187  188  189  190  191  192  193  194  195
196  197  198  199  200  201  202  203  204  205  206  207  208  209
210  211  212  213  214  215  216  217  218  219  220  221  222  223
224  225  226  227  228  229  230  231  232  233  234  235  236  237
238  239  240  241  242  243  244  245  246  247  248  249  250  251
252  253  254  255  256  257  258  259  260  261  262  263  264  265
266  267  268  269  270  271  272  273  274  275  276  277  278  279
280  281  282  283  284  285  286  287  288  289  290  291  292  293
294  295  296  297  298  299  300  301  302  303  304  305  306  307
308  309  310  311  312  313  314  315  316  317  318  319  320  321
322  323  324  325  326  327  328  329  330  331  332  333  334  335
336  337  338  339  340  341  342  343  344  345  346  347  348  349
350  351  352  353  354  355  356  357  358  359  360  361  362  363
364  365  366  367  368  369  370  371  372  373  374  375  376  377
378  379  380  381  382  383  384  385  386  387  388  389  390  391
392  393  394  395  396  397  398  399  400  401  402  403  404  405
406  407  408  409  410  411  412  413  414  415  416  417  418  419
420  421  422  423  424  425  426  427  428  429  430  431  432  433
434  435  436  437  438  439  440  441  442  443  444  445  446  447
448  449  450  451  452  453  454  455  456  457  458  459  460  461
462  463  464  465  466  467  468  469  470  471  472  473  474  475
476  477  478  479  480  481  482  483  484  485  486  487  488  489
490  491  492  493  494  495  496  497  498  499  500  501  502  503
504  505  506  507  508  509  510  511  512  513  514  515  516  517
518  519  520  521  522  523  524  525  526  527  528  529  530  531
532  533  534  535  536  537  538  539  540  541  542  543  544  545
546  547  548  549  550  551  552  553  554  555  556  557  558  559
560  561  562  563  564  565  566  567  568  569  570  571  572  573
574  575  576  577  578  579  580  581  582  583  584  585  586  587
588  589  590  591  592  593  594  595  596  597  598  599  600  601
602  603  604  605  606  607  608  609  610  611  612  613  614  615
616  617  618  619  620  621  622  623  624  625  626  627  628  629
630  631  632  633  634  635  636  637  638  639  640  641  642  643
644  645  646  647  648  649  650  651  652  653  654  655  656  657
658  659  660  661  662  663  664  665  666  667  668  669  670  671
672  673  674  675  676  677  678  679  680  681  682  683  684  685
686  687  688  689  690  691  692  693  694  695  696  697  698  699
700  701  702  703  704  705  706  707  708  709  710  711  712  713
714  715  716  717  718  719  720  721  722  723  724  725  726  727
728  729  730  731  732  733  734  735  736  737  738  739  740  741
742  743  744  745  746  747  748  749  750  751  752  753  754  755
756  757  758  759  760  761  762  763  764  765  766  767  768  769
770  771  772  773  774  775  776  777  778  779  780  781  782  783
784  785  786  787  788  789  790  791  792  793  794  795  796  797
798  799  800  801  802  803  804  805  806  807  808  809  810  811
812  813  814  815  816  817  818  819  820  821  822  823  824  825
826  827  828  829  830  831  832  833  834  835  836  837  838  839
840  841  842  843  844  845  846  847  848  849  850  851  852  853
854  855  856  857  858  859  860  861  862  863  864  865  866  867
868  869  870  871  872  873  874  875  876  877  878  879  880  881
882  883  884  885  886  887  888  889  890  891  892  893  894  895
896  897  898  899  900  901  902  903  904  905  906  907  908  909
910  911  912  913  914  915  916  917  918  919  920  921  922  923
924  925  926  927  928  929  930  931  932  933  934  935  936  937
938  939  940  941  942  943  944  945  946  947  948  949  950  951
952  953  954  955  956  957  958  959  960  961  962  963  964  965
966  967  968  969  970  971  972  973  974  975  976  977  978  979
980  981  982  983  984  985  986  987  988  989  990  991  992  993
994  995  996  997  998  999 1000 1001 1002 1003 1004 1005 1006 1007
1008 1009 1010 1011 1012 1013 1014 1015 1016 1017 1018 1019 1020 1021
1022 1023 1024 1025 1026 1027 1028 1029 1030 1031 1032 1033 1034 1035
1036 1037 1038 1039 1040 1041 1042 1043 1044 1045 1046 1047 1048 1049
1050 1051 1052 1053 1054 1055 1056 1057 1058 1059 1060 1061 1062 1063
1064 1065 1066 1067 1068 1069 1070 1071 1072 1073 1074 1075 1076 1077
1078 1079 1080 1081 1082 1083 1084 1085 1086 1087 1088 1089 1090 1091
1092 1093 1094 1095 1096 1097 1098 1099 1100 1101 1102 1103 1104 1105
1106 1107 1108 1109 1110 1111 1112 1113 1114 1115 1116 1117 1118 1119
1120 1121 1122 1123 1124 1125 1126 1127 1128 1129 1130 1131 1132 1133
1134 1135 1136 1137 1138 1139 1140 1141 1142 1143 1144 1145 1146 1147
1148 1149 1150 1151 1152 1153 1154 1155 1156 1157 1158 1159 1160 1161
1162 1163 1164 1165 1166 1167 1168 1169 1170 1171 1172 1173 1174 1175
1176 1177 1178 1179 1180 1181 1182 1183 1184 1185 1186 1187 1188 1189
1190 1191 1192 1193 1194 1195 1196 1197 1198 1199 1200 1201 1202 1203
1204 1205 1206 1207 1208 1209 1210 1211 1212 1213 1214 1215 1216 1217
1218 1219 1220 1221 1222 1223 1224 1225 1226 1227 1228 1229 1230 1231
1232 1233 1234 1235 1236 1237 1238 1239 1240 1241 1242 1243 1244 1245
1246 1247 1248 1249 1250 1251 1252 1253 1254 1255 1256 1257 1258 1259
1260 1261 1262 1263 1264 1265 1266 1267 1268 1269 1270 1271 1272 1273
1274 1275 1276 1277 1278 1279 1280 1281 1282 1283 1284 1285 1286 1287
1288 1289 1290 1291 1292 1293 1294 1295 1296 1297 1298 1299 1300 1301
1302 1303 1304 1305 1306 1307 1308 1309 1310 1311 1312 1313 1314 1315
1316 1317 1318 1319 1320 1321 1322 1323 1324 1325 1326 1327 1328 1329
1330 1331 1332 1333 1334 1335 1336 1337 1338 1339 1340 1341 1342 1343
1344 1345 1346 1347 1348 1349 1350 1351 1352 1353 1354 1355 1356 1357
1358 1359 1360 1361 1362 1363 1364 1365 1366 1367 1368 1369 1370 1371
1372 1373 1374 1375 1376 1377 1378 1379 1380 1381 1382 1383 1384 1385
1386 1387 1388 1389 1390 1391 1392 1393 1394 1395 1396 1397 1398 1399
1400 1401 1402 1403 1404 1405 1406 1407 1408 1409 1410 1411 1412 1413
1414 1415 1416 1417 1418 1419 1420 1421 1422 1423 1424 1425 1426 1427
1428 1429 1430 1431 1432 1433 1434 1435 1436 1437 1438 1439 1440 1441
1442 1443 1444 1445 1446 1447 1448 1449 1450 1451 1452 1453 1454 1455
1456 1457 1458 1459 1460 1461 1462 1463 1464 1465 1466 1467 1468 1469
1470 1471 1472 1473 1474 1475 1476 1477 1478 1479 1480 1481 1482 1483
1484 1485 1486 1487 1488 1489 1490 1491 1492 1493 1494 1495 1496 1497
1498 1499]

Now, 1500 is set as the new threshold. When the elements are more than 1500, numpy would start summarizing again. Look at the below example.

import numpy as np

np.set_printoptions(threshold=1500)
arr=np.arange(1501)
print(arr)

Output:

[   0    1    2 ... 1498 1499 1500]

### Setting the threshold to sys.maxsize or numpy.inf

If you want to display all the elements of the array always, respective of the array size, you can either set threshold=sys.maxsize or threshold=np.inf

Example-1 : Using threshold=sys.maxsize

import numpy as np
import sys

np.set_printoptions(threshold=sys.maxsize)
arr=np.arange(1001)
print(arr)

Example-2 : Using threshold=np.inf

import numpy as np

np.set_printoptions(threshold=np.inf)
arr=np.arange(1001)
print(arr)

## Method 2: Using numpy.printoptions() with context managers

You might want to print the full array just occasionally. Let’s say, in the program, you want to display the full array just once or twice. In other cases, you are ok if the array summarises, if this is the case, you can use the numpy.printoptions() along with the with clause.

Doing so, only the print statements within the with clause will be printed fully. The print statements outside the with clause will still have the default behavior.

You can either specify threshold=sys.maxsize or threshold=np.inf

import sys
import numpy as np

arr=np.arange(1001)
with np.printoptions(threshold= sys.maxsize):
print(arr)

## Method 3: Converting the array to the list using numpy.ndarray.tolist()

You can even convert the NumPy array to a list using np.tolist(). This way all the elements of the array can be displayed.

Example 1: If you have a 1D array, you can convert it to the array as shown below.

import numpy as np

arr=np.arange(1000)
print(arr.tolist())

Example 2: If you have a 2D array with size 100*10, you can convert it to the array as shown below.

import numpy as np

arr=np.arange(1000).reshape((100,10))
print(arr.tolist())

## Conclusion

This brings us to the end of this short tutorial. We hope this article has been informative. Kindly comment and let us know if you loved reading this. Please come back to us for more interesting content.