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1420 1421 1422 1423 1424 1425 1426 1427 1428 1429 1430 1431 1432 | {
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "08971b87-edf9-4d12-81a2-8185f8812fb1",
"metadata": {
"jupyter": {
"source_hidden": true
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"✅ mode_0 = 2,684,921\n",
"✅ mode_1 = 804,489\n",
"✅ mode_2 = 258,189\n",
"📊 合計 = 3,747,599\n"
]
}
],
"source": [
"import re\n",
"from pathlib import Path\n",
"\n",
"raw = \"\"\"\n",
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"PatNo_ID_1577042911.csv: mode_0=27667 (66.04%) | mode_1=11298 (26.97%) | mode_2=195 (0.47%)\n",
"PatNo_ID_1577124974.csv: mode_0=5273 (18.61%) | mode_1=19050 (67.22%) | mode_2=496 (1.75%)\n",
"PatNo_ID_1577487284.csv: mode_0=1009 (43.03%) | mode_1=1139 (48.57%) | mode_2=197 (8.40%)\n",
"PatNo_ID_1577645326.csv: mode_0=18395 (93.44%) | mode_1=1273 (6.47%) | mode_2=1 (0.01%)\n",
"PatNo_ID_1577708619.csv: mode_0=2458 (87.26%) | mode_1=0 (0.00%) | mode_2=209 (7.42%)\n",
"PatNo_ID_1578338796.csv: mode_0=805 (81.40%) | mode_1=26 (2.63%) | mode_2=155 (15.67%)\n",
"PatNo_ID_1578400260.csv: mode_0=3928 (13.57%) | mode_1=20820 (71.91%) | mode_2=2702 (9.33%)\n",
"PatNo_ID_1578467432.csv: mode_0=0 (0.00%) | mode_1=0 (0.00%) | mode_2=86 (100.00%)\n",
"PatNo_ID_1578629310.csv: mode_0=552 (93.40%) | mode_1=0 (0.00%) | mode_2=0 (0.00%)\n",
"PatNo_ID_1578784257.csv: mode_0=10861 (32.02%) | mode_1=16811 (49.57%) | mode_2=886 (2.61%)\n",
"PatNo_ID_1578807904.csv: mode_0=36261 (71.57%) | mode_1=13581 (26.81%) | mode_2=823 (1.62%)\n",
"PatNo_ID_1578889218.csv: mode_0=5848 (95.92%) | mode_1=0 (0.00%) | mode_2=0 (0.00%)\n",
"PatNo_ID_1579061219.csv: mode_0=10658 (89.26%) | mode_1=1141 (9.56%) | mode_2=142 (1.19%)\n",
"PatNo_ID_1579198603.csv: mode_0=749 (36.61%) | mode_1=1149 (56.16%) | mode_2=148 (7.23%)\n",
"PatNo_ID_1579498177.csv: mode_0=650 (3.00%) | mode_1=18016 (83.07%) | mode_2=3022 (13.93%)\n",
"PatNo_ID_1579704532.csv: mode_0=20725 (74.26%) | mode_1=5059 (18.13%) | mode_2=2038 (7.30%)\n",
"PatNo_ID_1579707571.csv: mode_0=6912 (60.64%) | mode_1=2944 (25.83%) | mode_2=1542 (13.53%)\n",
"PatNo_ID_1579818203.csv: mode_0=1877 (99.84%) | mode_1=0 (0.00%) | mode_2=0 (0.00%)\n",
"PatNo_ID_1580062580.csv: mode_0=1954 (45.44%) | mode_1=78 (1.81%) | mode_2=2268 (52.74%)\n",
"PatNo_ID_1580096720.csv: mode_0=1054 (37.03%) | mode_1=1362 (47.86%) | mode_2=430 (15.11%)\n",
"PatNo_ID_1580107637.csv: mode_0=2174 (40.29%) | mode_1=100 (1.85%) | mode_2=3122 (57.86%)\n",
"PatNo_ID_1580133301.csv: mode_0=948 (14.31%) | mode_1=2454 (37.05%) | mode_2=2980 (44.99%)\n",
"PatNo_ID_1580244614.csv: mode_0=2789 (52.84%) | mode_1=1055 (19.99%) | mode_2=22 (0.42%)\n",
"PatNo_ID_1580385702.csv: mode_0=79 (3.69%) | mode_1=555 (25.95%) | mode_2=6 (0.28%)\n",
"PatNo_ID_1580766093.csv: mode_0=10247 (56.71%) | mode_1=7604 (42.08%) | mode_2=219 (1.21%)\n",
"PatNo_ID_1580788380.csv: mode_0=3466 (69.39%) | mode_1=1259 (25.21%) | mode_2=270 (5.41%)\n",
"PatNo_ID_1581003248.csv: mode_0=3751 (48.24%) | mode_1=2653 (34.12%) | mode_2=262 (3.37%)\n",
"PatNo_ID_1581019504.csv: mode_0=2044 (7.25%) | mode_1=17170 (60.94%) | mode_2=1519 (5.39%)\n",
"PatNo_ID_1581039196.csv: mode_0=3960 (99.12%) | mode_1=0 (0.00%) | mode_2=0 (0.00%)\n",
"PatNo_ID_1581126892.csv: mode_0=11180 (64.35%) | mode_1=5589 (32.17%) | mode_2=604 (3.48%)\n",
"PatNo_ID_1581385752.csv: mode_0=50 (5.28%) | mode_1=852 (89.97%) | mode_2=45 (4.75%)\n",
"PatNo_ID_1581633231.csv: mode_0=10933 (68.35%) | mode_1=3562 (22.27%) | mode_2=143 (0.89%)\n",
"PatNo_ID_1581692973.csv: mode_0=2617 (96.11%) | mode_1=0 (0.00%) | mode_2=106 (3.89%)\n",
"PatNo_ID_1581985786.csv: mode_0=2504 (36.96%) | mode_1=3932 (58.05%) | mode_2=245 (3.62%)\n",
"PatNo_ID_1582001742.csv: mode_0=638 (18.99%) | mode_1=2314 (68.89%) | mode_2=407 (12.12%)\n",
"PatNo_ID_1582042088.csv: mode_0=4997 (72.18%) | mode_1=1618 (23.37%) | mode_2=308 (4.45%)\n",
"PatNo_ID_1582416035.csv: mode_0=5310 (63.30%) | mode_1=0 (0.00%) | mode_2=2794 (33.31%)\n",
"PatNo_ID_1582452511.csv: mode_0=5196 (100.00%) | mode_1=0 (0.00%) | mode_2=0 (0.00%)\n",
"PatNo_ID_1582618048.csv: mode_0=15650 (100.00%) | mode_1=0 (0.00%) | mode_2=0 (0.00%)\n",
"PatNo_ID_1582635996.csv: mode_0=4317 (33.09%) | mode_1=8620 (66.07%) | mode_2=109 (0.84%)\n",
"PatNo_ID_1582743918.csv: mode_0=2135 (92.11%) | mode_1=0 (0.00%) | mode_2=0 (0.00%)\n",
"PatNo_ID_1582830724.csv: mode_0=5612 (45.21%) | mode_1=2335 (18.81%) | mode_2=164 (1.32%)\n",
"PatNo_ID_1582849900.csv: mode_0=4269 (57.60%) | mode_1=2616 (35.30%) | mode_2=526 (7.10%)\n",
"PatNo_ID_1582893941.csv: mode_0=1040 (3.01%) | mode_1=27244 (78.75%) | mode_2=6313 (18.25%)\n",
"PatNo_ID_1582937076.csv: mode_0=18744 (78.13%) | mode_1=1795 (7.48%) | mode_2=3431 (14.30%)\n",
"PatNo_ID_1583387776.csv: mode_0=4529 (99.96%) | mode_1=0 (0.00%) | mode_2=0 (0.00%)\n",
"PatNo_ID_1583528783.csv: mode_0=2868 (51.21%) | mode_1=2441 (43.59%) | mode_2=271 (4.84%)\n",
"PatNo_ID_1584158973.csv: mode_0=2683 (93.10%) | mode_1=1 (0.03%) | mode_2=198 (6.87%)\n",
"PatNo_ID_1584165013.csv: mode_0=3385 (37.04%) | mode_1=4944 (54.09%) | mode_2=811 (8.87%)\n",
"PatNo_ID_1584204828.csv: mode_0=1637 (100.00%) | mode_1=0 (0.00%) | mode_2=0 (0.00%)\n",
"PatNo_ID_1584397376.csv: mode_0=638 (100.00%) | mode_1=0 (0.00%) | mode_2=0 (0.00%)\n",
"PatNo_ID_1585186701.csv: mode_0=37796 (78.02%) | mode_1=9713 (20.05%) | mode_2=482 (0.99%)\n",
"PatNo_ID_1585393385.csv: mode_0=6656 (100.00%) | mode_1=0 (0.00%) | mode_2=0 (0.00%)\n",
"PatNo_ID_1586091346.csv: mode_0=29431 (45.21%) | mode_1=24989 (38.39%) | mode_2=10674 (16.40%)\n",
"PatNo_ID_1586172659.csv: mode_0=30842 (79.99%) | mode_1=7639 (19.81%) | mode_2=78 (0.20%)\n",
"PatNo_ID_1586498429.csv: mode_0=1523 (88.39%) | mode_1=0 (0.00%) | mode_2=0 (0.00%)\n",
"PatNo_ID_1586696634.csv: mode_0=789 (22.11%) | mode_1=1711 (47.94%) | mode_2=4 (0.11%)\n",
"PatNo_ID_1586749510.csv: mode_0=1330 (31.76%) | mode_1=0 (0.00%) | mode_2=124 (2.96%)\n",
"PatNo_ID_1586808038.csv: mode_0=25143 (100.00%) | mode_1=0 (0.00%) | mode_2=0 (0.00%)\n",
"PatNo_ID_1586897008.csv: mode_0=3484 (52.10%) | mode_1=3037 (45.42%) | mode_2=134 (2.00%)\n",
"PatNo_ID_1586988835.csv: mode_0=3397 (100.00%) | mode_1=0 (0.00%) | mode_2=0 (0.00%)\n",
"PatNo_ID_1587490083.csv: mode_0=35708 (79.02%) | mode_1=7236 (16.01%) | mode_2=2242 (4.96%)\n",
"PatNo_ID_1587626346.csv: mode_0=11847 (100.00%) | mode_1=0 (0.00%) | mode_2=0 (0.00%)\n",
"PatNo_ID_1587845484.csv: mode_0=6891 (59.35%) | mode_1=4052 (34.90%) | mode_2=408 (3.51%)\n",
"PatNo_ID_1588466952.csv: mode_0=4505 (92.94%) | mode_1=0 (0.00%) | mode_2=336 (6.93%)\n",
"PatNo_ID_1588632604.csv: mode_0=1410 (54.06%) | mode_1=1189 (45.59%) | mode_2=9 (0.35%)\n",
"PatNo_ID_1588673465.csv: mode_0=0 (0.00%) | mode_1=6250 (62.02%) | mode_2=35 (0.35%)\n",
"PatNo_ID_1588794796.csv: mode_0=9376 (100.00%) | mode_1=0 (0.00%) | mode_2=0 (0.00%)\n",
"PatNo_ID_1588957997.csv: mode_0=10163 (92.68%) | mode_1=248 (2.26%) | mode_2=555 (5.06%)\n",
"PatNo_ID_1589018086.csv: mode_0=7268 (53.95%) | mode_1=495 (3.67%) | mode_2=5687 (42.21%)\n",
"PatNo_ID_1589027950.csv: mode_0=3532 (46.27%) | mode_1=1657 (21.71%) | mode_2=900 (11.79%)\n",
"PatNo_ID_1589034524.csv: mode_0=31704 (63.31%) | mode_1=18298 (36.54%) | mode_2=79 (0.16%)\n",
"PatNo_ID_1589324603.csv: mode_0=1383 (33.03%) | mode_1=2475 (59.11%) | mode_2=254 (6.07%)\n",
"PatNo_ID_1589509384.csv: mode_0=16855 (95.45%) | mode_1=482 (2.73%) | mode_2=105 (0.59%)\n",
"⚠️ 跳過 PatNo_ID_1589918099.csv (mode 欄位不存在)\n",
"PatNo_ID_1589998647.csv: mode_0=8040 (69.31%) | mode_1=0 (0.00%) | mode_2=3560 (30.69%)\n",
"PatNo_ID_1590099697.csv: mode_0=895 (33.50%) | mode_1=0 (0.00%) | mode_2=1777 (66.50%)\n",
"PatNo_ID_1590136310.csv: mode_0=5294 (94.87%) | mode_1=0 (0.00%) | mode_2=13 (0.23%)\n",
"PatNo_ID_1590616537.csv: mode_0=6201 (43.64%) | mode_1=7275 (51.20%) | mode_2=732 (5.15%)\n",
"PatNo_ID_1590854576.csv: mode_0=15879 (100.00%) | mode_1=0 (0.00%) | mode_2=0 (0.00%)\n",
"PatNo_ID_1590996429.csv: mode_0=55639 (76.54%) | mode_1=7943 (10.93%) | mode_2=7493 (10.31%)\n",
"PatNo_ID_1591139996.csv: mode_0=2903 (100.00%) | mode_1=0 (0.00%) | mode_2=0 (0.00%)\n",
"PatNo_ID_1591575781.csv: mode_0=824 (22.22%) | mode_1=2533 (68.29%) | mode_2=352 (9.49%)\n",
"PatNo_ID_1591609798.csv: mode_0=35624 (100.00%) | mode_1=0 (0.00%) | mode_2=0 (0.00%)\n",
"PatNo_ID_1592044724.csv: mode_0=3687 (54.10%) | mode_1=2370 (34.78%) | mode_2=758 (11.12%)\n",
"PatNo_ID_1592114062.csv: mode_0=13635 (99.03%) | mode_1=0 (0.00%) | mode_2=117 (0.85%)\n",
"PatNo_ID_1592258381.csv: mode_0=3020 (70.78%) | mode_1=1242 (29.11%) | mode_2=5 (0.12%)\n",
"PatNo_ID_1592560504.csv: mode_0=18052 (100.00%) | mode_1=0 (0.00%) | mode_2=0 (0.00%)\n",
"PatNo_ID_1593087886.csv: mode_0=21301 (88.16%) | mode_1=2105 (8.71%) | mode_2=733 (3.03%)\n",
"PatNo_ID_1593203352.csv: mode_0=9357 (98.54%) | mode_1=0 (0.00%) | mode_2=0 (0.00%)\n",
"PatNo_ID_1593386732.csv: mode_0=1210 (100.00%) | mode_1=0 (0.00%) | mode_2=0 (0.00%)\n",
"PatNo_ID_1593416100.csv: mode_0=1866 (56.07%) | mode_1=1233 (37.05%) | mode_2=229 (6.88%)\n",
"PatNo_ID_1593472048.csv: mode_0=5340 (64.88%) | mode_1=903 (10.97%) | mode_2=4 (0.05%)\n",
"PatNo_ID_1593562809.csv: mode_0=79008 (90.36%) | mode_1=7616 (8.71%) | mode_2=8 (0.01%)\n",
"PatNo_ID_1593593586.csv: mode_0=17012 (90.10%) | mode_1=1868 (9.89%) | mode_2=2 (0.01%)\n",
"PatNo_ID_1593691014.csv: mode_0=55 (3.68%) | mode_1=1263 (84.48%) | mode_2=177 (11.84%)\n",
"PatNo_ID_1593720818.csv: mode_0=3622 (92.61%) | mode_1=0 (0.00%) | mode_2=288 (7.36%)\n",
"PatNo_ID_1593838524.csv: mode_0=2162 (99.27%) | mode_1=0 (0.00%) | mode_2=0 (0.00%)\n",
"PatNo_ID_1593907744.csv: mode_0=21537 (99.76%) | mode_1=0 (0.00%) | mode_2=0 (0.00%)\n",
"PatNo_ID_1594027022.csv: mode_0=21952 (100.00%) | mode_1=0 (0.00%) | mode_2=0 (0.00%)\n",
"PatNo_ID_1594125250.csv: mode_0=11117 (78.31%) | mode_1=1339 (9.43%) | mode_2=1 (0.01%)\n",
"PatNo_ID_1594173718.csv: mode_0=344 (100.00%) | mode_1=0 (0.00%) | mode_2=0 (0.00%)\n",
"PatNo_ID_1594190584.csv: mode_0=61493 (93.83%) | mode_1=3912 (5.97%) | mode_2=129 (0.20%)\n",
"PatNo_ID_1594212248.csv: mode_0=4415 (100.00%) | mode_1=0 (0.00%) | mode_2=0 (0.00%)\n",
"PatNo_ID_1594227270.csv: mode_0=11268 (99.30%) | mode_1=44 (0.39%) | mode_2=0 (0.00%)\n",
"PatNo_ID_1594294180.csv: mode_0=12747 (69.53%) | mode_1=0 (0.00%) | mode_2=5587 (30.47%)\n",
"PatNo_ID_1594305136.csv: mode_0=12688 (67.93%) | mode_1=1713 (9.17%) | mode_2=4207 (22.52%)\n",
"PatNo_ID_1594309746.csv: mode_0=2392 (63.87%) | mode_1=1161 (31.00%) | mode_2=192 (5.13%)\n",
"PatNo_ID_1594319286.csv: mode_0=3989 (97.13%) | mode_1=0 (0.00%) | mode_2=0 (0.00%)\n",
"PatNo_ID_1594320763.csv: mode_0=2275 (93.58%) | mode_1=0 (0.00%) | mode_2=156 (6.42%)\n",
"PatNo_ID_1594322594.csv: mode_0=5380 (100.00%) | mode_1=0 (0.00%) | mode_2=0 (0.00%)\n",
"PatNo_ID_1594323385.csv: mode_0=8146 (100.00%) | mode_1=0 (0.00%) | mode_2=0 (0.00%)\n",
"PatNo_ID_1594334768.csv: mode_0=63870 (59.23%) | mode_1=34092 (31.62%) | mode_2=5468 (5.07%)\n",
"PatNo_ID_1594335109.csv: mode_0=5116 (100.00%) | mode_1=0 (0.00%) | mode_2=0 (0.00%)\n",
"PatNo_ID_1594423683.csv: mode_0=2233 (44.46%) | mode_1=2585 (51.46%) | mode_2=186 (3.70%)\n",
"PatNo_ID_1594437309.csv: mode_0=8750 (87.19%) | mode_1=863 (8.60%) | mode_2=326 (3.25%)\n",
"PatNo_ID_1594439781.csv: mode_0=3212 (41.76%) | mode_1=1321 (17.18%) | mode_2=3158 (41.06%)\n",
"PatNo_ID_1594441887.csv: mode_0=7414 (72.66%) | mode_1=2675 (26.22%) | mode_2=114 (1.12%)\n",
"PatNo_ID_1594448501.csv: mode_0=654 (12.81%) | mode_1=4050 (79.32%) | mode_2=402 (7.87%)\n",
"PatNo_ID_1594455578.csv: mode_0=105 (40.08%) | mode_1=0 (0.00%) | mode_2=157 (59.92%)\n",
"PatNo_ID_1594461482.csv: mode_0=33274 (100.00%) | mode_1=0 (0.00%) | mode_2=0 (0.00%)\n",
"PatNo_ID_1594464829.csv: mode_0=957 (23.93%) | mode_1=307 (7.67%) | mode_2=2675 (66.88%)\n",
"PatNo_ID_1594465597.csv: mode_0=4793 (73.77%) | mode_1=1233 (18.98%) | mode_2=309 (4.76%)\n",
"PatNo_ID_1594467719.csv: mode_0=1018 (39.77%) | mode_1=294 (11.48%) | mode_2=1 (0.04%)\n",
"PatNo_ID_1594471407.csv: mode_0=11282 (98.68%) | mode_1=0 (0.00%) | mode_2=0 (0.00%)\n",
"PatNo_ID_1594473688.csv: mode_0=19325 (99.60%) | mode_1=78 (0.40%) | mode_2=0 (0.00%)\n",
"PatNo_ID_1594479330.csv: mode_0=3727 (100.00%) | mode_1=0 (0.00%) | mode_2=0 (0.00%)\n",
"PatNo_ID_1594511911.csv: mode_0=2553 (46.52%) | mode_1=0 (0.00%) | mode_2=2902 (52.88%)\n",
"PatNo_ID_1594511914.csv: mode_0=1161 (11.95%) | mode_1=7752 (79.78%) | mode_2=763 (7.85%)\n",
"PatNo_ID_1594528842.csv: mode_0=2282 (91.61%) | mode_1=133 (5.34%) | mode_2=0 (0.00%)\n",
"PatNo_ID_1594533379.csv: mode_0=781 (75.83%) | mode_1=0 (0.00%) | mode_2=237 (23.01%)\n",
"PatNo_ID_1594735845.csv: mode_0=32802 (61.69%) | mode_1=6258 (11.77%) | mode_2=14112 (26.54%)\n",
"PatNo_ID_1594796566.csv: mode_0=49 (3.74%) | mode_1=0 (0.00%) | mode_2=1261 (96.26%)\n",
"PatNo_ID_1594802957.csv: mode_0=2560 (46.70%) | mode_1=249 (4.54%) | mode_2=2673 (48.76%)\n",
"PatNo_ID_1594845806.csv: mode_0=2630 (62.46%) | mode_1=1320 (31.35%) | mode_2=261 (6.20%)\n",
"PatNo_ID_1594857190.csv: mode_0=23252 (99.93%) | mode_1=0 (0.00%) | mode_2=0 (0.00%)\n",
"PatNo_ID_1594862135.csv: mode_0=2543 (18.52%) | mode_1=2 (0.01%) | mode_2=9707 (70.71%)\n",
"PatNo_ID_1594862572.csv: mode_0=2835 (35.90%) | mode_1=5048 (63.93%) | mode_2=13 (0.16%)\n",
"PatNo_ID_1594862905.csv: mode_0=59708 (92.88%) | mode_1=3487 (5.42%) | mode_2=1093 (1.70%)\n",
"PatNo_ID_1594879195.csv: mode_0=2403 (28.65%) | mode_1=4650 (55.44%) | mode_2=1334 (15.91%)\n",
"PatNo_ID_1594886956.csv: mode_0=7280 (42.31%) | mode_1=8692 (50.51%) | mode_2=931 (5.41%)\n",
"PatNo_ID_1594888142.csv: mode_0=39090 (99.63%) | mode_1=0 (0.00%) | mode_2=0 (0.00%)\n",
"PatNo_ID_1594900319.csv: mode_0=1181 (90.08%) | mode_1=130 (9.92%) | mode_2=0 (0.00%)\n",
"PatNo_ID_1594904742.csv: mode_0=24503 (84.70%) | mode_1=3168 (10.95%) | mode_2=1039 (3.59%)\n",
"PatNo_ID_1594912862.csv: mode_0=12745 (100.00%) | mode_1=0 (0.00%) | mode_2=0 (0.00%)\n",
"PatNo_ID_1594926122.csv: mode_0=18085 (100.00%) | mode_1=0 (0.00%) | mode_2=0 (0.00%)\n",
"PatNo_ID_1594959115.csv: mode_0=702 (70.84%) | mode_1=95 (9.59%) | mode_2=157 (15.84%)\n",
"PatNo_ID_1594969804.csv: mode_0=3522 (97.35%) | mode_1=96 (2.65%) | mode_2=0 (0.00%)\n",
"PatNo_ID_1594970427.csv: mode_0=458 (21.82%) | mode_1=1171 (55.79%) | mode_2=468 (22.30%)\n",
"PatNo_ID_1594978835.csv: mode_0=1606 (100.00%) | mode_1=0 (0.00%) | mode_2=0 (0.00%)\n",
"PatNo_ID_1595012967.csv: mode_0=14126 (62.23%) | mode_1=7732 (34.06%) | mode_2=796 (3.51%)\n",
"PatNo_ID_1595023326.csv: mode_0=919 (72.31%) | mode_1=0 (0.00%) | mode_2=352 (27.69%)\n",
"PatNo_ID_1595051455.csv: mode_0=2419 (62.11%) | mode_1=1215 (31.19%) | mode_2=247 (6.34%)\"\"\"\n",
"\n",
"# 抓 mode 數字\n",
"pairs = re.findall(r\"mode_0=(\\d+).+?mode_1=(\\d+).+?mode_2=(\\d+)\", raw)\n",
"\n",
"total_0 = sum(int(a) for a,b,c in pairs)\n",
"total_1 = sum(int(b) for a,b,c in pairs)\n",
"total_2 = sum(int(c) for a,b,c in pairs)\n",
"\n",
"print(f\"✅ mode_0 = {total_0:,}\")\n",
"print(f\"✅ mode_1 = {total_1:,}\")\n",
"print(f\"✅ mode_2 = {total_2:,}\")\n",
"print(f\"📊 合計 = {total_0 + total_1 + total_2:,}\")"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "e103c3ce-2089-4d00-82f9-3f80866f72ce",
"metadata": {
"jupyter": {
"source_hidden": true
},
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"🚀 啟動 SVV 統計任務 (useable==1) | 20251106_204844\n"
]
},
{
"name": "stderr",
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]
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" df = pd.read_csv(path)\n",
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"掃描檔案: 80%|████████ | 212/264 [00:10<00:02, 19.27file/s]"
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"/tmp/ipykernel_621010/304996257.py:55: DtypeWarning: Columns (4) have mixed types. Specify dtype option on import or set low_memory=False.\n",
" df = pd.read_csv(path)\n",
"掃描檔案: 83%|████████▎ | 218/264 [00:11<00:02, 17.24file/s]"
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"/tmp/ipykernel_621010/304996257.py:55: DtypeWarning: Columns (15) have mixed types. Specify dtype option on import or set low_memory=False.\n",
" df = pd.read_csv(path)\n",
"掃描檔案: 86%|████████▋ | 228/264 [00:11<00:01, 21.73file/s]"
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"/tmp/ipykernel_621010/304996257.py:55: DtypeWarning: Columns (8,9,10,11,12,13,14,15,16) have mixed types. Specify dtype option on import or set low_memory=False.\n",
" df = pd.read_csv(path)\n",
"掃描檔案: 90%|████████▉ | 237/264 [00:11<00:01, 25.32file/s]"
]
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"掃描檔案: 92%|█████████▏| 243/264 [00:12<00:00, 28.97file/s]"
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"PatNo_ID_1594511914.csv: 三欄>0=5,087 (57.2%) | 兩欄>0=3,807 (42.8%) | 一欄>0=3 (0.0%) | 都不>0或空=0 (0.0%) | 總筆數=8,897\n",
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"name": "stderr",
"output_type": "stream",
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"掃描檔案: 94%|█████████▎| 247/264 [00:12<00:00, 30.32file/s]"
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},
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"name": "stdout",
"output_type": "stream",
"text": [
"PatNo_ID_1594857190.csv: 三欄>0=0 (0.0%) | 兩欄>0=23,247 (100.0%) | 一欄>0=0 (0.0%) | 都不>0或空=0 (0.0%) | 總筆數=23,247\n",
"PatNo_ID_1594862135.csv: 三欄>0=2 (0.1%) | 兩欄>0=2,541 (99.8%) | 一欄>0=2 (0.1%) | 都不>0或空=0 (0.0%) | 總筆數=2,545\n",
"PatNo_ID_1594862572.csv: 三欄>0=0 (0.0%) | 兩欄>0=2,822 (35.8%) | 一欄>0=5,056 (64.1%) | 都不>0或空=4 (0.1%) | 總筆數=7,882\n"
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"name": "stderr",
"output_type": "stream",
"text": [
"/tmp/ipykernel_621010/304996257.py:55: DtypeWarning: Columns (4,14,15,16) have mixed types. Specify dtype option on import or set low_memory=False.\n",
" df = pd.read_csv(path)\n",
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"output_type": "stream",
"text": [
"PatNo_ID_1594862905.csv: 三欄>0=0 (0.0%) | 兩欄>0=56,429 (94.1%) | 一欄>0=3,510 (5.9%) | 都不>0或空=0 (0.0%) | 總筆數=59,939\n",
"PatNo_ID_1594879195.csv: 三欄>0=0 (0.0%) | 兩欄>0=6,798 (99.9%) | 一欄>0=7 (0.1%) | 都不>0或空=0 (0.0%) | 總筆數=6,805\n",
"PatNo_ID_1594886956.csv: 三欄>0=3,309 (20.7%) | 兩欄>0=12,663 (79.3%) | 一欄>0=0 (0.0%) | 都不>0或空=0 (0.0%) | 總筆數=15,972\n"
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{
"name": "stderr",
"output_type": "stream",
"text": [
"/tmp/ipykernel_621010/304996257.py:55: DtypeWarning: Columns (2,3,4,8,9,10,11,12,13,14,15,16) have mixed types. Specify dtype option on import or set low_memory=False.\n",
" df = pd.read_csv(path)\n",
"掃描檔案: 97%|█████████▋| 257/264 [00:12<00:00, 19.03file/s]"
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{
"name": "stdout",
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"text": [
"PatNo_ID_1594888142.csv: 三欄>0=0 (0.0%) | 兩欄>0=38,073 (100.0%) | 一欄>0=0 (0.0%) | 都不>0或空=1 (0.0%) | 總筆數=38,074\n",
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{
"name": "stderr",
"output_type": "stream",
"text": [
"掃描檔案: 100%|██████████| 264/264 [00:12<00:00, 20.39file/s]"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"PatNo_ID_1594959115.csv: 三欄>0=0 (0.0%) | 兩欄>0=90 (12.9%) | 一欄>0=605 (87.1%) | 都不>0或空=0 (0.0%) | 總筆數=695\n",
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"PatNo_ID_1594970427.csv: 三欄>0=1,167 (71.7%) | 兩欄>0=460 (28.3%) | 一欄>0=0 (0.0%) | 都不>0或空=0 (0.0%) | 總筆數=1,627\n",
"PatNo_ID_1594978835.csv: 三欄>0=0 (0.0%) | 兩欄>0=1,600 (99.7%) | 一欄>0=5 (0.3%) | 都不>0或空=0 (0.0%) | 總筆數=1,605\n",
"PatNo_ID_1595012967.csv: 三欄>0=0 (0.0%) | 兩欄>0=15,746 (72.8%) | 一欄>0=5,880 (27.2%) | 都不>0或空=0 (0.0%) | 總筆數=21,626\n",
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"PatNo_ID_1595051455.csv: 三欄>0=837 (23.0%) | 兩欄>0=2,795 (76.9%) | 一欄>0=0 (0.0%) | 都不>0或空=2 (0.1%) | 總筆數=3,634\n",
"\n",
"=== 全域統計 (useable==1) ===\n",
"三欄>0=262,215 (8.2%)\n",
"兩欄>0=2,766,826 (86.9%)\n",
"一欄>0=153,591 (4.8%)\n",
"都不>0或空=48 (0.0%)\n",
"總筆數=3,182,680\n",
"📄 詳細記錄：/home/jovyan/phase_1/v1/data_1/logs/run_svv_valid_useable1_20251106_204844.txt\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n"
]
}
],
"source": [
"# /home/jovyan/phase_1/v1/code/stat_svv_valid_useable1_pct.py\n",
"# -*- coding: utf-8 -*-\n",
"\"\"\"\n",
"目標：\n",
"- 掃描 /home/jovyan/phase_1/v1/data_1/v1.1.4/ 內所有 CSV\n",
"- 只針對 useable == 1 的列，統計 sponvt / vti / vte > 0 的四類筆數：\n",
" ① 三欄皆 > 0 ② 任兩欄 > 0 ③ 只有一欄 > 0 ④ 全部 ≤ 0 或 (null)\n",
"- 每檔與全域：同時輸出「筆數」與「佔比 (%)」\n",
"- 所有 print()/tqdm.write() 輸出同步寫入 LOG\n",
"\n",
"Log：/home/jovyan/phase_1/v1/data_1/logs/run_svv_valid_useable1_YYYYMMDD_HHMMSS.txt\n",
"\"\"\"\n",
"\n",
"import os, sys, time, pandas as pd\n",
"from tqdm import tqdm\n",
"\n",
"# ===== 路徑設定 =====\n",
"DATA_DIR = \"/home/jovyan/phase_1/v1/data_1/v1.1.4/\"\n",
"LOG_DIR = \"/home/jovyan/phase_1/v1/data_1/logs/\"\n",
"os.makedirs(LOG_DIR, exist_ok=True)\n",
"run_ts = time.strftime(\"%Y%m%d_%H%M%S\")\n",
"LOG_PATH = os.path.join(LOG_DIR, f\"run_svv_valid_useable1_{run_ts}.txt\")\n",
"\n",
"# ===== Tee：把 print 同步寫到 Console 與 Log =====\n",
"class TeeLogger:\n",
" def __init__(self, logfile):\n",
" self.log = open(logfile, \"a\", encoding=\"utf-8\")\n",
" self.stdout = sys.stdout\n",
" def write(self, message):\n",
" self.stdout.write(message)\n",
" self.log.write(message)\n",
" self.log.flush()\n",
" def flush(self):\n",
" self.stdout.flush()\n",
" self.log.flush()\n",
"sys.stdout = TeeLogger(LOG_PATH) # 攔截 print\n",
"# (備註) tqdm 進度條仍寫 stderr；但 tqdm.write() 走 stdout，會被 TeeLogger 同步進 log\n",
"\n",
"def pct(n, d):\n",
" \"\"\"回傳 0~100 的百分比（小數點 1 位）；d<=0 時回傳 0.0\"\"\"\n",
" if d and d > 0:\n",
" return round((n / d) * 100.0, 1)\n",
" return 0.0\n",
"\n",
"def main():\n",
" print(f\"🚀 啟動 SVV 統計任務 (useable==1) | {run_ts}\")\n",
" files = sorted([f for f in os.listdir(DATA_DIR) if f.lower().endswith(\".csv\")])\n",
"\n",
" # 全域加總\n",
" G3 = G2 = G1 = G0 = GT = 0\n",
"\n",
" for f in tqdm(files, desc=\"掃描檔案\", unit=\"file\"):\n",
" path = os.path.join(DATA_DIR, f)\n",
" try:\n",
" df = pd.read_csv(path)\n",
"\n",
" # 欄位檢查\n",
" if \"useable\" not in df.columns:\n",
" print(f\"⚠️ 缺少 useable 欄位：{f}\")\n",
" continue\n",
" cols = [\"sponvt\", \"vti\", \"vte\"]\n",
" if not all(c in df.columns for c in cols):\n",
" print(f\"⚠️ 缺少必要欄位 {cols}：{f}\")\n",
" continue\n",
"\n",
" # 僅統計 useable==1\n",
" df1 = df[df[\"useable\"] == 1]\n",
" if df1.empty:\n",
" # 仍回報 0，讓 log 可見\n",
" print(f\"{f}: 三欄>0=0 (0.0%) | 兩欄>0=0 (0.0%) | 一欄>0=0 (0.0%) | 都不>0或空=0 (0.0%) | 總筆數=0\")\n",
" continue\n",
"\n",
" sub = df1[cols].apply(pd.to_numeric, errors=\"coerce\") # (null)→NaN，自動略過非數值\n",
" cond = (sub > 0).sum(axis=1) # 每列 >0 的欄數\n",
" c3 = int((cond == 3).sum())\n",
" c2 = int((cond == 2).sum())\n",
" c1 = int((cond == 1).sum())\n",
" c0 = int((cond == 0).sum())\n",
" total = int(len(cond))\n",
"\n",
" # 全域彙總\n",
" G3 += c3; G2 += c2; G1 += c1; G0 += c0; GT += total\n",
"\n",
" # 檔案層級輸出（含佔比）\n",
" print(\n",
" f\"{f}: \"\n",
" f\"三欄>0={c3:,} ({pct(c3,total)}%) | \"\n",
" f\"兩欄>0={c2:,} ({pct(c2,total)}%) | \"\n",
" f\"一欄>0={c1:,} ({pct(c1,total)}%) | \"\n",
" f\"都不>0或空={c0:,} ({pct(c0,total)}%) | \"\n",
" f\"總筆數={total:,}\"\n",
" )\n",
"\n",
" except Exception as e:\n",
" print(f\"❌ 讀取失敗: {f} | {e}\")\n",
"\n",
" # 全域統計（含佔比）\n",
" print(\"\\n=== 全域統計 (useable==1) ===\")\n",
" print(f\"三欄>0={G3:,} ({pct(G3,GT)}%)\")\n",
" print(f\"兩欄>0={G2:,} ({pct(G2,GT)}%)\")\n",
" print(f\"一欄>0={G1:,} ({pct(G1,GT)}%)\")\n",
" print(f\"都不>0或空={G0:,} ({pct(G0,GT)}%)\")\n",
" print(f\"總筆數={GT:,}\")\n",
" print(f\"📄 詳細記錄：{LOG_PATH}\")\n",
"\n",
"if __name__ == \"__main__\":\n",
" main()"
]
},
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|