Data Block
119 122 140 141 155 163 170 179 203 226 232 233 238 243 244 245 247 248 253 254 255 256 257 261 262 263 264 265 266 270 272 273 275 278 279 281 287 288 289 801 802 808 863 865 1103 1115 1117 1118 1120 1747 1770 1772 1773 1854 1855 6301 6304 6305 6311 6319 6321 6323 6324 6327 6328 6331 6332 6334 6335 6340 6346 6349 6350 6351 6357 6361 6363 6364 6365 6367 6368 6369 6371 6374 6375 6377 6380 6851 6853 6864 6865 6869 6890 6921 6932 6935 6936 6951 6959 6974 8446 8447 8472 8528 8531 8926 8929 8954
Output separated rows
119
------
122
------
140
------
141
-------
155
------
163
Firs select cell and use data -> text to columns, and split data as columns, than copy the columns and paste special and select transpose check.
Related
im relatively new to Dataframes in Python and running into an Issue I cant find.
im having a Dataframe with the following column layout
print(list(df.columns.values)) returns:
['iccid', 'system', 'last_updated', '01.01', '02.01', '03.01', '04.01', '05.01', '12.01', '18.01', '19.01', '20.01', '21.01', '22.01', '23.01', '24.01', '25.01', '26.01', '27.01', '28.01', '29.01', '30.01', '31.01']
normally i should have a column for each day in a specific month. in the example above its December 2022. Sometimes Days are missing which isnt an issue.
i tried to first get all given columns that are relevant by filtering them:
# Filter out the columns that are not related to the data
data_columns = [col for col in df.columns if '.' in col]
Now comes the issue:
Sometimes the column "system" could also be empty so i need to put the iccid inside the system value:
df.loc[df['system'] == 'Nicht benannt!', 'system'] = df.loc[df['system'] == 'Nicht benannt!', 'iccid'].iloc[0]
df.loc[df['system'] == '', 'system'] = df.loc[df['system'] == '', 'iccid'].iloc
grouped = df.groupby('system').sum(numeric_only=False)
then i tried to create that needed 'data_usage' column.
grouped['data_usage'] = grouped[data_columns[-1]]
grouped.reset_index(inplace=True)
By that line i should normally only get the result of the last column in the dataframe (which was a workaround that also didnt work as expected)
Now what im trying to get is the sum of all columns which contain a date in their name and add this sum to a new column named data_usage.
the issue im having here is im getting results for systems which dont have an initial system value which have a data_usage of 120000 (which is just value that represents the megabytes used) and if i check the sqlite file the system in total only used 9000 mb in that particular month.
For Example:
im having this column in the sqlite file:
iccid
system
last_updated
06.02
08.02
8931080320014183316
Nicht benannt!
2023-02-06
1196
1391
and in the dataframe i get the following result:
8931080320014183316 48129.0
I cant find the issue and would be very happy if someone can point me into the right direction.
Here are some example data as requested:
iccid
system
last_updated
01.12
02.12
03.12
04.12
05.12
06.12
07.12
08.12
09.12
10.12
11.12
12.12
13.12
14.12
15.12
16.12
17.12
18.12
19.12
20.12
21.12
22.12
23.12
28.12
29.12
30.12
31.12
8945020184547971966
U-O-51
2022-12-01
2
32
179
208
320
509
567
642
675
863
1033
1055
1174
2226
2277
2320
2466
2647
2679
2713
2759
2790
2819
2997
3023
3058
3088
8945020855461807911
L-O-382
2022-12-01
1
26
54
250
385
416
456
481
506
529
679
772
802
832
858
915
940
1019
1117
1141
1169
1193
1217
1419
1439
1461
1483
8945020855461809750
C-O-27
2022-12-01
1
123
158
189
225
251
456
489
768
800
800
800
800
800
800
2362
2386
2847
2925
2960
2997
3089
3116
3448
3469
3543
3586
8931080019070958450
L-O-123
2022-12-02
0
21
76
313
479
594
700
810
874
1181
1955
2447
2527
2640
2897
3008
3215
3412
3554
3639
3698
3782
3850
4741
4825
4925
5087
8931080453114183282
Nicht benannt!
2022-12-02
0
6
45
81
95
98
101
102
102
102
102
102
102
103
121
121
121
121
149
164
193
194
194
194
194
194
194
8931080894314183290
C-O-16 N
2022-12-02
0
43
145
252
386
452
532
862
938
1201
1552
1713
1802
1855
2822
3113
3185
3472
3527
3745
3805
3880
3938
4221
4265
4310
4373
8931080465814183308
L-O-83
2022-12-02
0
61
169
275
333
399
468
858
1094
1239
1605
1700
1928
2029
3031
4186
4333
4365
4628
4782
4842
4975
5265
5954
5954
5954
5954
8931082343214183316
Nicht benannt!
2022-12-02
0
52
182
506
602
719
948
1129
1314
1646
1912
1912
1912
1912
2791
3797
3944
4339
4510
4772
4832
5613
5688
6151
6482
6620
6848
8931087891314183324
L-O-119
2022-12-02
0
19
114
239
453
573
685
800
1247
1341
1341
1341
1341
1341
1341
1341
1341
1341
1341
1341
1341
1341
1423
2722
3563
4132
4385
I'm attempting to reverse engineer an SVG animation in JavaScript to better understand the animation and I'm seeing the following SVG code representing an "Up" motion in JavaScript. However the SVG itself doesn't look like any typical SVG code I am used to using. Can you help identify how this SVG is structured? Or how I can adjust the follwing code so I can open it in an image editing software?
d 601 9aAaAaAnBkNnUaNaN"/D 18 10bAaAnAnBuXaN"/F 22 10W7AaAaBaEaGiAW-6NiNnXaNbUaNaNaN"/D 30 10bAaEuUnU"/D 114 10bAaAnAnBuXaN"/F 117 10W7AaAaBaBaAaGkAn0NkNnKaNaNaUaNaU"/D 125 10eAaGnAnUnUnU"/D 66 12eBnAnAnNnUaN"/F 70 12W6AaAaAbEaGkAn2NuKaNaUaNaNaNaN"/D 76 12gEuNnNnN"/D 593 12eBnAnAuKaN"/F 596 12eAaAeUbAnEbKeAnAbJnAiAxNxAkAnUaXnNbNaNaU"/D 604 13bEuK"/D 166 14eEnAkKaN"/D 608 14aAnN"/F 169 15eAeAaAaBaAaAnAnBn0NkNnNnKbNgNaU"/D 222 15aAbBaGxKnKaN"/D 175 16gEnAnUnNnN"/D 308 16aAaAaAaBuAnAnEaAaAaEnAuNnNuNnUnNaUbw-7bN"/D 314 16gAaGkNuX"/D 268 17eAaAaAaAaAaGnBnNuUuUaUiNaNaU"/D 501 17bAaAuAnAnKaN"/D 548 17eAnAnAnAnKaN"/F 552 17jEW-6AkNaNaNbN"/D 557 17gExK"/D 209 18bAaEeAaBnAuAeAW8NnNnKgGnBn1NkGaAuNnNnXaUnw-6aN"/F 216 18jAaEgAxEaAaAW-8NkNbNaUnNkUaAeK"/D 260 18eAaBnAuAnEaBnAnBeAaEnAkNnXnNnNnXaNbXaNaN"/D 364 18eAaBuNkNaN"/D 509 18bAaBnAaEnAeAaAaBnAaEnAxXaNuNuNW-8AnAuUaUaNbNW6AeKnNnUaN"/D 159 19bAaBaAaAeAa0UaNaNeGnAnAnAiNn3NnNnNnXaN"/F 213 19aAnN"/D 214 19bBkNaN"/D 356 19eAnAnAnAnBbNW9NeAaAbAaAaBaBnBkBxUnNaNeUaNnUuNW-9AkAnAnEaAeAaBnAkUkNnXaNaNaw-6aNaN"/D 460 19eAaBuAnNnK"/F 502 19W6BaAaEkNW-6AuAnUaUaNaNaN"/F 312 20gAgAnAnBnAaAaEaAaNaGuAkAW-7NuNnKaAbNaKnNnNnKaNaNbN"/F 358 20W8AbAaAkAW-9AuUaNaNaN"/D 403 20eBnBnNnK"/F 407 20jAbAaAaAaGnAkAW-8NnNnUaUaUaNaN"/D 412 20gEnNnNuN"/D 451 20gAnAnAnBnI"/F 455 20jBaAaEbNaNaGuAnAn1NnXaUaNaNaN"/D 551 20W6AeAaAaAaEnNuNuNW-9AuAnKaNaNeN"/F 557 20gAaBnNnNkN"/D 17 21jAW6NjAaAaBaw6nJnBnAxNnUnNaNbNaNaKnKnNnNW-8AuAnAnGaBbAaAbAnAuAuNnNnw-7nIaUaN"/D 113 21eAa0NeAaAaBaBnEuKnNuNW-7AuAnBnBnBaAaAeBnAnAxNnw-6nNnKaKaUaU"/F 263 21W8BnBbBnNuEbNaNbAaBnNuAnEaBnAW-9NaKnNkUaNaBeUnNnAnUnKaNbN"/D 320 21ew9uAnNnKnNnNaUaNaN"/F 511 21aAnN"/D 596 21gAgNjAbBaEaBnBnJnBuAuNnNnXaNbNbNbNnNnNnNnNkNW-8AuAuKaNeN"/D 65 22aAa2NeAaBaw6uUnUnNuNW-6AkAnAnAnBuw-6aUaN"/F 462 22bAuN"/D 462 23bAaAnAuK"/F 464 23aAnN"/F 512 23aEuNaU"/F 21 24W8AaAaEaEnAnAuAW-7NnNuUnXaNaNbN"/D 417 24aAaBaAnBnAiAW-9NuNnKaNaBaAaAW8NeNaX"/F 549 24W9AbAbAaBxAnBnAW-6NuNuUnKaNbN"/F 596 24W8AeAaAaAaAaAuAuAuAnExNuNuNnNnNnKnUbNbN"/F 71 25W6AbAaBaBaAnAnAnAkAiNkNnNnNnKaNaNaNeN"/F 119 25W7AbAaEaBnAuAnAkAxNkNnNnUaUaUaNbN"/D 265 25bAuN"/F 359 25W9AbBaAnBkAnAaBuAW-7NaUnNkNnKaNaNeN"/D 403 25aAnN"/D 449 25bGaAa1NaNbNaAbJnNuNW-6AW-8NnNnNnX"/D 269 26bAaAnAuK"/D 361 26bAuN"/D 365 26bAaAnAuK"/F 161 27a3AgGnBuAkAW-6NkNnNnXnNaN"/D 262 27aAaBkUaN"/D 357 27bAaBnAuUnNaN"/F 497 27aAnN"/F 211 28eAa1GnBnNnAkAxNkNnNaNnX"/F 500 28W8AbAbAnGkAW-6NuNnNnUnNbNaN"/D 592 28aEaAaAaAbEnAkNnNnw-8"/D 158 29eGaAuNuX"/D 272 29bAaAaAnAnAuNnKaN"/D 546 29aBbAbEnAuNnNnI"/D 559 29gJnAxNnUaUaN"/F 418 30aGuAkAW-8NuKW9NjN"/F 403 31aAnN"/F 460 31W6AbAuAuAxAiNuNnUW8N"/D 65 32aAaAaAeAnAnAuNuI"/D 81 32aGnBxNnUeNaNaN"/D 129 32aEnAnAxNnNeNaNbN"/D 177 32aw6uAuNnNnUeNbU"/F 275 32aAnN"/F 274 33aAnN"/D 222 34aBnAkUeN
I have multiple measurements per 'Subject' in file 1. I only want to use the highest quality, singular measurement per Subject. In my second file I have the exact list of which measurement is the best for each Subject. This information is contained in the column 'seriesnumber'. The number in the 'seriesnumber' column in file 2 corresponds to the best measurement for a Subject. I Need to extract only these rows from my file 1.
I have tried to use awk, join, and merge to try and accomplish this but came up with errors and strange incomplete files.
join code:
join -j2 file1 file2
awk code:
awk ' FILENAME=="file1" {arr[$2]=$0; next}
FILENAME=="file2" {print arr[$2]} ' file1 file2 > newfile
File 1 Example
Subject Seriesnumber
19-1-1001 2 8655 661 15250 60747 8005 3919 7393 2264 1479 1663 22968 4180 1712 689 781 4255 90 1260 7233 154 15643 63421 7361 4384 6932 2062 4526 1742 686 4575 100 1684 0 1194 0 0 5 0 0 147 699 315 305 317 565 1361200 1338210 1338690 304258 308180 612438 250614 255920 506534 66645 802424 1206450 1187010 1185180 1816840 1 1 21 17 38 1765590
19-1-1001 10 8992 507 15722 64032 8728 3929 7208 2075 1529 1529 22503 3993 1819 710 764 3870 87 1247 7361 65 16128 66226 8165 4384 6669 1805 4405 1752 779 4039 103 1705 0 1280 0 0 10 0 0 186 685 300 318 320 598 1370490 1347160 1347520 306588 307188 613775 251704 256521 508225 65808 808802 1208880 1189150 1187450 1827880 1 1 22 26 48 1778960
19-1-1103 2 3303 317 12146 57569 7008 3617 6910 2018 811 1593 18708 4708 1429 408 668 3279 14 1289 2351 85 13730 60206 6731 4137 7034 2038 4407 1483 749 3576 85 1668 0 948 0 0 7 0 0 129 602 288 291 285 748 1250030 1238540 1238820 301810 301062 602872 215029 218080 433108 61555 781150 1107360 1098510 1097220 1635560 1 1 32 47 79 1555850
19-1-1103 9 3236 286 12490 59477 7000 3558 6782 2113 894 1752 19338 4818 1724 387 649 3345 56 1314 2077 133 13885 60414 6628 4078 7063 2031 4269 1709 610 3707 112 1947 0 990 0 0 8 0 0 245 604 279 280 284 693 1269820 1258050 1258320 306856 309614 616469 215658 220876 436534 61859 796760 1124870 1115990 1114510 1630740 1 1 32 42 74 1556790
19-10-1010 2 3344 608 14744 59165 8389 4427 6962 2008 716 1496 21980 4008 1474 769 652 3715 61 1400 3049 1072 15767 61919 8325 4824 7117 1936 4001 1546 684 3935 103 1434 0 1624 0 0 3 0 0 316 834 413 520 517 833 1350760 1337040 1336840 311985 312592 624577 246800 251133 497933 65699 809736 1200320 1189410 1188280 1731270 1 1 17 13 30 1606700
19-10-1010 6 3242 616 15205 61330 8019 4520 6791 2093 735 1558 22824 3981 1546 653 614 3672 96 1227 2992 1070 16450 64189 8489 4407 6953 2099 4096 1668 680 4116 99 1449 0 2161 0 0 19 0 0 263 848 387 525 528 824 1339090 1325830 1325780 309464 311916 621380 239958 244616 484574 65493 810887 1183120 1172600 1171430 1720000 1 1 16 26 42 1587100
File 2 Example
Subject seriesnumber
19-10-1010 2
19-10-1166 2
19-102-10005 2
19-102-10006 2
19-103-10009 2
19-103-10010 2
19-104-10013 11
19-104-10014 2
19-105-10017 6
19-105-10018 6
The desired output would like something like this:
Where I no longer have duplicate entries per subject. The second column will look different because the preferred series number will differ per subject.
19-10-1010 2 3344 608 14744 59165 8389 4427 6962 2008 716 1496 21980 4008 1474 769 652 3715 61 1400 3049 1072 15767 61919 8325 4824 7117 1936 4001 1546 684 3935 103 1434 0 1624 0 0 3 0 0 316 834 413 520 517 833 1350760 1337040 1336840 311985 312592 624577 246800 251133 497933 65699 809736 1200320 1189410 1188280 1731270 1 1 17 13 30 1606700
19-10-1166 2 3699 312 15373 61787 8026 4248 6385 1955 608 2194 21394 4260 1563 886 609 3420 25 1101 3415 417 16909 63040 7236 4264 5933 1852 4156 1213 654 4007 53 1336 5 1597 0 0 18 0 0 110 821 300 514 466 854 1193020 1179470 1179420 282241 273236 555477 204883 203228 408111 61343 740736 1036210 1026080 1024910 1563950 1 1 39 40 79 1415890
19-102-10005 2 8733 514 13024 50735 7729 3775 4955 1575 1045 1141 20415 3924 1537 990 651 3515 134 1259 8571 232 13487 51374 7150 4169 5192 1664 3760 1620 596 3919 189 1958 0 1479 0 0 36 0 0 203 837 459 409 439 1072 1224350 1200010 1200120 287659 290445 578104 216976 220545 437521 57457 737161 1095770 1074440 1073050 1637570 1 1 31 22 53 1618600
19-102-10006 2 8347 604 13735 42231 7266 3836 6473 2057 1099 1007 18478 3769 1351 978 639 3332 125 1197 8207 454 13774 43750 6758 4274 6148 1921 3732 1584 614 3521 180 1611 0 1241 0 0 25 0 0 254 813 410 352 372 833 1092800 1069450 1069190 244104 245787 489891 202201 205897 408098 59170 634640 978807 958350 957462 1485600 1 1 19 19 38 1472020
19-103-10009 2 4222 596 14702 52038 7428 4065 6598 2166 835 1854 22613 3397 1387 879 568 3729 93 1315 3414 222 14580 52639 7316 3997 6447 1986 4067 1529 596 3778 113 1689 0 2097 0 0 23 0 0 260 761 326 400 359 772 1204670 1190100 1189780 256560 260381 516941 237316 243326 480642 60653 681040 1070620 1059370 1058440 1605990 1 1 25 23 48 1593730
19-103-10010 2 5254 435 14688 47120 7772 3130 5414 1711 741 1912 20643 3594 1449 882 717 3663 41 999 6465 605 14820 49390 6361 3826 5527 1523 3513 1537 639 3596 80 1261 0 1475 0 0 18 0 0 283 827 383 414 297 627 1135490 1117320 1116990 243367 245896 489263 221809 227084 448893 55338 639719 1009370 994519 993639 1568140 1 1 14 11 25 1542210
19-104-10013 2 7276 341 11836 53018 7912 3942 6105 2334 795 2532 21239 4551 1258 1176 430 3636 83 1184 8811 396 12760 53092 7224 4361 6306 1853 4184 1278 543 3921 175 1814 0 2187 0 0 8 0 0 266 783 381 382 357 793 1011640 987712 987042 206633 228397 435031 170375 191222 361597 61814 601948 879229 859619 859103 1586150 1 1 224 162 386 1557120
19-104-10014 2 5964 355 13297 55439 8599 4081 5628 1730 970 1308 20196 4519 1363 992 697 3474 62 1232 6830 472 14729 59478 7006 4443 6156 1825 4492 1726 827 4017 122 1804 0 1412 0 0 17 0 0 259 672 299 305 319 779 1308470 1288970 1288910 284018 285985 570003 258525 257355 515880 62485 746108 1166160 1149700 1148340 1826660 1 1 33 24 57 1630580
19-105-10017 2 7018 307 13848 53855 8345 3734 6001 2095 899 1932 20712 4196 1349 645 823 4212 72 1475 3346 1119 13970 55202 7411 3975 5672 1737 3778 1490 657 4089 132 1689 0 1318 0 0 23 0 0 234 745 474 367 378 760 1122360 1104380 1104520 235806 233881 469687 217939 220736 438675 61471 639143 985718 970903 969619 1583800 1 1 51 51 102 1558470
19-105-10018 2 16454 1098 12569 52521 8215 3788 5858 1805 788 1147 21028 3496 1492 665 634 3796 39 1614 10700 617 12813 52098 8091 3901 5367 1646 3544 1388 723 3938 47 1819 0 1464 0 0 42 0 0 330 832 301 319 400 788 1148940 1114080 1113560 225179 227218 452397 237056 237295 474351 59172 614884 1019300 986820 986144 1607900 1 1 19 28 47 1591480
19-105-10020 2 4096 451 13042 48597 7601 3228 5665 1582 778 1670 19769 3612 1187 717 617 3672 103 962 2627 467 13208 48466 6619 3461 5217 1360 3575 1388 718 3783 90 1370 0 862 0 0 6 0 0 216 673 386 439 401 682 1081580 1068850 1068890 233290 235396 468686 209666 214472 424139 54781 619447 958522 948737 947554 1493740 1 1 16 11 27 1452900
For file1 containing (I removed long useless lines):
Subject Seriesnumber
19-1-1001 2 8655 661 15250 60747 800
19-1-1001 10 8992 507 15722 64032 872
19-1-1103 2 3303 317 12146 57569 700
19-1-1103 9 3236 286 12490 59477 700
19-10-1010 2 3344 608 14744 59165 838
19-10-1010 6 3242 616 15205 61330 801
and file2 containig:
Subject seriesnumber
19-10-1010 2
19-10-1166 2
19-102-10005 2
19-102-10006 2
19-103-10009 2
19-103-10010 2
19-104-10013 11
19-104-10014 2
19-105-10017 6
19-105-10018 6
The following awk will output:
$ awk 'NR==FNR{a[$1, $2];next} ($1, $2) in a' file2 file1
19-10-1010 2 3344 608 14744 59165 838
Note that the first file argument to awk is file2 not file1 (small optimization)! How it works:
NR == FNR - if line number is file line number. Ie. choose only first file passed to awk.
a[$1, $2] - remember index $1,$2 in associative array a
next - do not parse rest of script and restart with next line
($1, $2) in a - check if $1, $2 is in associative array a
because of next this is run only for the second file as passed to awk
if this expression returns with true, then the line will be printed (this is how awk works).
Alternatively you could do the follow, but it will store the whole file1 in memory, which is... memory consuming..., the code above only stores $1, $2 indexes in memory.
awk 'NR==FNR{arr[$1, $2]=$0} NR!=FNR{print arr[$1, $2]}' file1 file2
Hi I have a list of facilities ID starting from cell E8 and the number of facilities on cell E2. I want to get random Facility IDs from column E8 and
transfer to column F (Facility ID PICKED) starting from cell F8. I want this to be automatically if possible, so everytime there is a new desired number(in this case 61) then
the random facilities get picked automatically. I was using a formula
but then I realized it was bringing me duplicate IDs. I only one each to be picked once.
Please any help will be very appreciated! :)
No facilities: 61
Facility ID Facility ID PICKED
37
47
71
73
77
86
90
96
103
109
111
113
121
130
132
140
161
166
195
206
275
285
353
368
374
384
390
431
449
455
463
467
471
494
503
506
528
533
561
572
576
579
582
584
586
591
608
610
613
615
630
634
648
655
681
699
701
703
715
750
752
756
761
768
778
813
834
850
853
856
862
879
882
885
907
908
942
947
950
960
978
994
1012
1044
1054
1081
1095
1108
1124
1127
1149
1163
1193
1204
1216
1239
1250
1265
1267
1305
1321
1329
1341
1616
1649
1659
1681
1711
1715
1724
1738
1753
1754
1781
1795
1831
1848
1850
1859
1875
1881
1902
1912
1922
1925
1930
1965
1982
1998
2008
2013
2031
2039
2089
2094
2105
2108
2114
2122
2123
2127
2128
2135
2137
2138
2142
2146
2179
2181
2185
2199
2201
2209
2220
2222
2233
2241
2268
2357
2399
2405
2406
2411
2426
2436
2444
2465
2468
2479
2500
2501
2530
2582
2618
2628
2660
2671
2692
2705
2729
2738
2740
2755
2758
2761
2775
2823
2826
2832
2854
2873
2877
2887
2888
2889
2894
2910
2953
2964
2979
2985
2987
2990
2991
3050
3120
3127
3134
3147
3173
3175
3186
3213
3222
3228
3236
3240
3241
3264
3265
3276
3277
3288
3296
3307
3315
Put this in F8 and copy down the list.
=IF(ROW(1:1)<=$E$2,AGGREGATE(15,6,$E$8:$E$233/(COUNTIF($F$7:F7,$E$8:$E$233)=0),RANDBETWEEN(1,COUNTA($E$8:$E$233)-ROW(1:1)+1)),"")
I'm currently generating an extremely large data set on a remote HPC (high performace computer). We are talking about 3 TB at the moment, and it could reach up to 10 TB once I'm done.
Each of the 450 000 files ranges from a few KB to about 100 MB and contains lines of integers with no repetitive/predictable patterns. Moreover they are split among 150 folders (I use the path to classify them according to the input parameters). Now that could be fine, but my research group is technically limited to 1TB of disk space on the remote server, although the admin are willing to close their eyes until the situation gets sorted out.
What would you recommend to compress such a dataset?
A limitation is that tasks can't run more than 48 hours at a time on this computer. So long but efficient compression methods are possible only if 48 hours is enough... I really have no other options as neither me, neither my group own enough disk space on other machines.
EDIT: Just to clarify, this a remote computer that runs on some variation of linux. All standard compression protocols are available. I don't have super user rights.
EDIT2: As request by Sergio, here is a sample output (first 10 lines of a files)
27 42 46 63 95 110 205 227 230 288 330 345 364 367 373 390 448 471 472 482 509 514 531 533 553 617 636 648 667 682 703 704 735 740 762 775 803 813 882 915 920 936 939 942 943 979 1018 1048 1065 1198 1219 1228 1513 1725 1888 1944 2085 2190 2480 5371 5510 5899 6788 7728 9514 10382 11946 13063 13808 16070 23301 23511 24538
93 94 106 143 157 164 168 181 196 293 299 334 369 372 439 457 508 527 547 557 568 570 573 592 601 668 701 704 799 838 848 870 875 882 890 913 953 959 1022 1024 1037 1046 1169 1201 1288 1615 1684 1771 2043 2204 2348 2387 2735 3149 4319 4890 4989 5321 5588 6453 7475 9277 9649 9654 11433 16966
1463
183 469 514 597 792
25 50 143 152 205 244 253 424 433 446 461 476 486 545 552 570 632 642 647 665 681 682 718 735 746 772 792 811 830 851 891 903 925 1037 1115 1147 1171 1612 1979 2749 3074 3158 6042 12709 20571 20859
24 30 86 312 726 875 1023 1683 1799
33 36 42 65 110 112 122 227 241 262 274 284 305 328 353 366 393 414 419 449 462 488 489 514 635 690 732 744 767 772 812 820 843 844 855 889 893 925 936 939 981 1015 1020 1060 1064 1130 1174 1304 1393 1477 1939 2004 2200 2205 2208 2216 2234 3284 4456 5209 6810 6834 8067 10811 10895 12771 15291
157 761 834 875 1001 2492
21 141 146 169 181 256 266 337 343 367 397 402 405 433 454 466 513 527 656 684 708 709 732 743 811 883 913 938 947 986 987 1013 1053 1190 1215 1288 1289 1333 1513 1524 1683 1758 2033 2684 3714 4129 6015 7395 8273 8348 9483 23630
1253
All integers are separated by one whitespace, and each line corresponds to a given element. I use implicit line numbers to store this information, because my data is assosiative i.e. the 0th element is associated to elements 27 42 46 63 110.. etc. I believe that there is no extra information whatsoever.
A few points that may help:
It looks like your numbers are sorted. If this is always the case, then it will be more efficient to compress the differences between adjacent numbers rather than the numbers themselves (since the differences will be somewhat smaller on average)
There are good ways of encoding small integer values in binary format, that are probably better than encoding them in text format. See the technique used by Google in their protocol buffers: (https://developers.google.com/protocol-buffers/docs/encoding)
Once you have applied the above techniques, then zipping / some standard form of compression should improve everything even further.
There is some research done at this LINK that breaks down the pro/cons of using gzip, bzip2, and lzma. Hopefully this can let you make an informed decision on your best approach.
All your numbers seem to be increasing in size (each line). A rather common approach in database technology would be to only store the size difference, making a line like
24 30 86 312 726 875 1023 1683 1799
to something like
6 56 226 414 149 148 660 116
Other lines of your example would even show more benefit, as the differences are smaller. This also works when the numbers decrease in-between, but you have to be able to deal with negative differences then.
Second thing to do would be changing the encoding. While compression will reduce this overhead, you're currently using 8 bit per digit, whereas you only need 4 bit of those (0-9, space as divisor). Implementing your own "4 bit character set" will already cut your storage requirements to half of the current size! In the end, this would be some kind of binary encoding of numbers of arbitrary length.