dc-l1-bangkok-attribute-coercion
Map (reference ← swipe → agent)
0:00
Our analytics dashboard computes averages from the vendor's bangkok_aq_stations export and the numbers are coming back wrong. The means show up as NaN and the city director keeps getting figures that do not reconcile. Please investigate the file and fix whatever is keeping the numeric computations from working. Leave the string columns and the geometry alone, and keep Thai script in any string field exactly as it arrives. Write the result to bangkok_aq_typed.geojson.
0:00
System info
{
"adapter": "openrouter",
"model": "deepseek/deepseek-v4-flash",
"base_url": "https://openrouter.ai/api/v1"
}
0:06
Let me start by examining the file to understand its structure and identify what's wrong with the numeric computations.
0:06
Bash
ls /work/
bangkok_aq_stations.geojson
0:10
Let me look at the file to understand its structure.
0:10
Bash
head -100 /work/bangkok_aq_stations.geojson
{
"type": "FeatureCollection",
"name": "bangkok_aq_stations",
"crs": {
"type": "name",
"properties": {
"name": "urn:ogc:def:crs:OGC:1.3:CRS84"
}
},
"features": [
{
"type": "Feature",
"geometry": {
"type": "Point",
"coordinates": [
100.5294,
13.7464
]
},
"properties": {
"station_id": "1",
"name_th": "สนามกีฬาแห่งชาติ",
"name_en": "National Stadium",
"sensor_value": "84.55",
"pm25_ug_m3": "63.6",
"elevation_m": "11.0"
}
},
{
"type": "Feature",
"geometry": {
"type": "Point",
"coordinates": [
100.5343,
13.7456
]
},
"properties": {
"station_id": "2",
"name_th": "สยาม",
"name_en": "Siam",
"sensor_value": "87.00",
"pm25_ug_m3": "60.5",
"elevation_m": "12.5"
}
},
{
"type": "Feature",
"geometry": {
"type": "Point",
"coordinates": [
100.5436,
13.7441
]
},
"properties": {
"station_id": "3",
"name_th": "ชิดลม",
"name_en": "Chit Lom",
"sensor_value": "80.95",
"pm25_ug_m3": "54.8",
"elevation_m": "14.0"
}
},
{
"type": "Feature",
"geometry": {
"type": "Point",
"coordinates": [
100.5485,
13.7434
]
},
"properties": {
"station_id": "4",
"name_th": "เพลินจิต",
"name_en": "Phloen Chit",
"sensor_value": "73.94",
"pm25_ug_m3": "49.0",
"elevation_m": "15.4"
}
},
{
"type": "Feature",
"geometry": {
"type": "Point",
"coordinates": [
100.555,
13.7407
]
},
"properties": {
"station_id": "5",
"name_th": "นานา",
"name_en": "Nana",
"sensor_value": "72.10",
"pm25_ug_m3": "45.6",
"elevation_m": "16.7"
}
},
0:14
I can see the issue right away. The numeric fields like `sensor_value`, `pm25_ug_m3`, and `elevation_m` are stored as strings (e.g., `"84.55"`, `"63.6"`, `"11.0"`) in the GeoJSON. When the analytics dashboard tries to compute averages (mean), NaN results appear because the numeric computation is failing on string values. I need to convert these numeric fields from strings to numbers (float) in the GeoJSON, while leaving string columns (station_id, name_th, name_en) and the geometry alone. Let me first see the full file to understand all fields and features.
0:14
Read
/work/bangkok_aq_stations.geojson
1 {
2 "type": "FeatureCollection",
3 "name": "bangkok_aq_stations",
4 "crs": {
5 "type": "name",
6 "properties": {
7 "name": "urn:ogc:def:crs:OGC:1.3:CRS84"
8 }
9 },
10 "features": [
11 {
12 "type": "Feature",
13 "geometry": {
14 "type": "Point",
15 "coordinates": [
16 100.5294,
17 13.7464
18 ]
19 },
20 "properties": {
21 "station_id": "1",
22 "name_th": "สนามกีฬาแห่งชาติ",
23 "name_en": "National Stadium",
24 "sensor_value": "84.55",
25 "pm25_ug_m3": "63.6",
26 "elevation_m": "11.0"
27 }
28 },
29 {
30 "type": "Feature",
31 "geometry": {
32 "type": "Point",
33 "coordinates": [
34 100.5343,
35 13.7456
36 ]
37 },
38 "properties": {
39 "station_id": "2",
40 "name_th": "สยาม",
41 "name_en": "Siam",
42 "sensor_value": "87.00",
43 "pm25_ug_m3": "60.5",
44 "elevation_m": "12.5"
45 }
46 },
47 {
48 "type": "Feature",
49 "geometry": {
50 "type": "Point",
51 "coordinates": [
52 100.5436,
53 13.7441
54 ]
55 },
56 "properties": {
57 "station_id": "3",
58 "name_th": "ชิดลม",
59 "name_en": "Chit Lom",
60 "sensor_value": "80.95",
61 "pm25_ug_m3": "54.8",
62 "elevation_m": "14.0"
63 }
64 },
65 {
66 "type": "Feature",
67 "geometry": {
68 "type": "Point",
69 "coordinates": [
70 100.5485,
71 13.7434
72 ]
73 },
74 "properties": {
75 "station_id": "4",
76 "name_th": "เพลินจิต",
77 "name_en": "Phloen Chit",
78 "sensor_value": "73.94",
79 "pm25_ug_m3": "49.0",
80 "elevation_m": "15.4"
81 }
82 },
83 {
84 "type": "Feature",
85 "geometry": {
86 "type": "Point",
87 "coordinates": [
88 100.555,
89 13.7407
90 ]
91 },
92 "properties": {
93 "station_id": "5",
94 "name_th": "นานา",
95 "name_en": "Nana",
96 "sensor_value": "72.10",
97 "pm25_ug_m3": "45.6",
98 "elevation_m": "16.7"
99 }
100 },
101 {
102 "type": "Feature",
103 "geometry": {
104 "type": "Point",
105 "coordinates": [
106 100.5604,
107 13.7373
108 ]
109 },
110 "properties": {
111 "station_id": "6",
112 "name_th": "อโศก",
113 "name_en": "Asok",
114 "sensor_value": "75.29",
115 "pm25_ug_m3": "45.1",
116 "elevation_m": "17.8"
117 }
118 },
119 {
120 "type": "Feature",
121 "geometry": {
122 "type": "Point",
123 "coordinates": [
124 100.5694,
125 13.7305
126 ]
127 },
128 "properties": {
129 "station_id": "7",
130 "name_th": "พร้อมพงษ์",
131 "name_en": "Phrom Phong",
132 "sensor_value": "77.39",
133 "pm25_ug_m3": "46.7",
134 "elevation_m": "18.7"
135 }
136 },
137 {
138 "type": "Feature",
139 "geometry": {
140 "type": "Point",
141 "coordinates": [
142 100.578,
143 13.724
144 ]
145 },
146 "properties": {
147 "station_id": "8",
148 "name_th": "ทองหล่อ",
149 "name_en": "Thong Lo",
150 "sensor_value": "71.34",
151 "pm25_ug_m3": "47.9",
152 "elevation_m": "19.4"
153 }
154 },
155 {
156 "type": "Feature",
157 "geometry": {
158 "type": "Point",
159 "coordinates": [
160 100.5852,
161 13.7197
162 ]
163 },
164 "properties": {
165 "station_id": "9",
166 "name_th": "เอกมัย",
167 "name_en": "Ekkamai",
168 "sensor_value": "55.17",
169 "pm25_ug_m3": "46.4",
170 "elevation_m": "19.8"
171 }
172 },
173 {
174 "type": "Feature",
175 "geometry": {
176 "type": "Point",
177 "coordinates": [
178 100.5916,
179 13.7152
180 ]
181 },
182 "properties": {
183 "station_id": "10",
184 "name_th": "พระโขนง",
185 "name_en": "Phra Khanong",
186 "sensor_value": "34.09",
187 "pm25_ug_m3": "40.9",
188 "elevation_m": "20.0"
189 }
190 },
191 {
192 "type": "Feature",
193 "geometry": {
194 "type": "Point",
195 "coordinates": [
196 100.6014,
197 13.7058
198 ]
199 },
200 "properties": {
201 "station_id": "11",
202 "name_th": "อ่อนนุช",
203 "name_en": "On Nut",
204 "sensor_value": "17.21",
205 "pm25_ug_m3": "32.2",
206 "elevation_m": "19.9"
207 }
208 },
209 {
210 "type": "Feature",
211 "geometry": {
212 "type": "Point",
213 "coordinates": [
214 100.6053,
215 13.6963
216 ]
217 },
218 "properties": {
219 "station_id": "12",
220 "name_th": "บางจาก",
221 "name_en": "Bang Chak",
222 "sensor_value": "11.16",
223 "pm25_ug_m3": "22.3",
224 "elevation_m": "19.6"
225 }
226 },
227 {
228 "type": "Feature",
229 "geometry": {
230 "type": "Point",
231 "coordinates": [
232 100.6106,
233 13.689
234 ]
235 },
236 "properties": {
237 "station_id": "13",
238 "name_th": "ปุณณวิถี",
239 "name_en": "Punnawithi",
240 "sensor_value": "15.58",
241 "pm25_ug_m3": "14.2",
242 "elevation_m": "19.0"
243 }
244 },
245 {
246 "type": "Feature",
247 "geometry": {
248 "type": "Point",
249 "coordinates": [
250 100.6166,
251 13.6794
252 ]
253 },
254 "properties": {
255 "station_id": "14",
256 "name_th": "อุดมสุข",
257 "name_en": "Udom Suk",
258 "sensor_value": "23.90",
259 "pm25_ug_m3": "10.1",
260 "elevation_m": "18.2"
261 }
262 },
263 {
264 "type": "Feature",
265 "geometry": {
266 "type": "Point",
267 "coordinates": [
268 100.6256,
269 13.668
270 ]
271 },
272 "properties": {
273 "station_id": "15",
274 "name_th": "บางนา",
275 "name_en": "Bang Na",
276 "sensor_value": "28.68",
277 "pm25_ug_m3": "10.5",
278 "elevation_m": "17.2"
279 }
280 },
281 {
282 "type": "Feature",
283 "geometry": {
284 "type": "Point",
285 "coordinates": [
286 100.6354,
287 13.661
288 ]
289 },
290 "properties": {
291 "station_id": "16",
292 "name_th": "แบริ่ง",
293 "name_en": "Bearing",
294 "sensor_value": "27.49",
295 "pm25_ug_m3": "14.2",
296 "elevation_m": "16.0"
297 }
298 },
299 {
300 "type": "Feature",
301 "geometry": {
302 "type": "Point",
303 "coordinates": [
304 100.5403,
305 13.7398
306 ]
307 },
308 "properties": {
309 "station_id": "17",
310 "name_th": "ราชดำริ",
311 "name_en": "Ratchadamri",
312 "sensor_value": "24.65",
313 "pm25_ug_m3": "18.6",
314 "elevation_m": "14.7"
315 }
316 },
317 {
318 "type": "Feature",
319 "geometry": {
320 "type": "Point",
321 "coordinates": [
322 100.5345,
323 13.7286
324 ]
325 },
326 "properties": {
327 "station_id": "18",
328 "name_th": "ศาลาแดง",
329 "name_en": "Sala Daeng",
330 "sensor_value": "27.55",
331 "pm25_ug_m3": "21.2",
332 "elevation_m": "13.2"
333 }
334 },
335 {
336 "type": "Feature",
337 "geometry": {
338 "type": "Point",
339 "coordinates": [
340 100.5293,
341 13.7235
342 ]
343 },
344 "properties": {
345 "station_id": "19",
346 "name_th": "ช่องนนทรี",
347 "name_en": "Chong Nonsi",
348 "sensor_value": "40.50",
349 "pm25_ug_m3": "21.0",
350 "elevation_m": "11.7"
351 }
352 },
353 {
354 "type": "Feature",
355 "geometry": {
356 "type": "Point",
357 "coordinates": [
358 100.5223,
359 13.7197
360 ]
361 },
362 "properties": {
363 "station_id": "20",
364 "name_th": "สุรศักดิ์",
365 "name_en": "Surasak",
366 "sensor_value": "60.71",
367 "pm25_ug_m3": "18.5",
368 "elevation_m": "10.2"
369 }
370 },
371 {
372 "type": "Feature",
373 "geometry": {
374 "type": "Point",
375 "coordinates": [
376 100.5147,
377 13.719
378 ]
379 },
380 "properties": {
381 "station_id": "21",
382 "name_th": "สะพานตากสิน",
383 "name_en": "Saphan Taksin",
384 "sensor_value": "79.80",
385 "pm25_ug_m3": "15.9",
386 "elevation_m": "8.7"
387 }
388 },
389 {
390 "type": "Feature",
391 "geometry": {
392 "type": "Point",
393 "coordinates": [
394 100.517,
395 13.7378
396 ]
397 },
398 "properties": {
399 "station_id": "22",
400 "name_th": "หัวลำโพง",
401 "name_en": "Hua Lamphong",
402 "sensor_value": "89.59",
403 "pm25_ug_m3": "15.7",
404 "elevation_m": "7.3"
405 }
406 },
407 {
408 "type": "Feature",
409 "geometry": {
410 "type": "Point",
411 "coordinates": [
412 100.529,
413 13.7325
414 ]
415 },
416 "properties": {
417 "station_id": "23",
418 "name_th": "สามย่าน",
419 "name_en": "Sam Yan",
420 "sensor_value": "87.74",
421 "pm25_ug_m3": "19.6",
422 "elevation_m": "5.9"
423 }
424 },
425 {
426 "type": "Feature",
427 "geometry": {
428 "type": "Point",
429 "coordinates": [
430 100.5346,
431 13.729
432 ]
433 },
434 "properties": {
435 "station_id": "24",
436 "name_th": "สีลม",
437 "name_en": "Si Lom",
438 "sensor_value": "79.14",
439 "pm25_ug_m3": "27.5",
440 "elevation_m": "4.7"
441 }
442 },
443 {
444 "type": "Feature",
445 "geometry": {
446 "type": "Point",
447 "coordinates": [
448 100.5443,
449 13.7253
450 ]
451 },
452 "properties": {
453 "station_id": "25",
454 "name_th": "ลุมพินี",
455 "name_en": "Lumphini",
456 "sensor_value": "71.71",
457 "pm25_ug_m3": "37.5",
458 "elevation_m": "3.7"
459 }
460 },
461 {
462 "type": "Feature",
463 "geometry": {
464 "type": "Point",
465 "coordinates": [
466 100.5545,
467 13.7223
468 ]
469 },
470 "properties": {
471 "station_id": "26",
472 "name_th": "คลองเตย",
473 "name_en": "Khlong Toei",
474 "sensor_value": "70.26",
475 "pm25_ug_m3": "46.9",
476 "elevation_m": "2.9"
477 }
478 },
479 {
480 "type": "Feature",
481 "geometry": {
482 "type": "Point",
483 "coordinates": [
484 100.5579,
485 13.7233
486 ]
487 },
488 "properties": {
489 "station_id": "27",
490 "name_th": "ศูนย์การประชุมแห่งชาติสิริกิติ์",
491 "name_en": "Queen Sirikit Centre",
492 "sensor_value": "72.77",
493 "pm25_ug_m3": "53.1",
494 "elevation_m": "2.4"
495 }
496 },
497 {
498 "type": "Feature",
499 "geometry": {
500 "type": "Point",
501 "coordinates": [
502 100.5604,
503 13.7378
504 ]
505 },
506 "properties": {
507 "station_id": "28",
508 "name_th": "สุขุมวิท",
509 "name_en": "Sukhumvit",
510 "sensor_value": "72.31",
511 "pm25_ug_m3": "55.0",
512 "elevation_m": "2.1"
513 }
514 },
515 {
516 "type": "Feature",
517 "geometry": {
518 "type": "Point",
519 "coordinates": [
520 100.5635,
521 13.7479
522 ]
523 },
524 "properties": {
525 "station_id": "29",
526 "name_th": "เพชรบุรี",
527 "name_en": "Phetchaburi",
528 "sensor_value": "62.85",
529 "pm25_ug_m3": "53.3",
530 "elevation_m": "2.0"
531 }
532 },
533 {
534 "type": "Feature",
535 "geometry": {
536 "type": "Point",
537 "coordinates": [
538 100.5654,
539 13.757
540 ]
541 },
542 "properties": {
543 "station_id": "30",
544 "name_th": "พระราม 9",
545 "name_en": "Phra Ram 9",
546 "sensor_value": "44.53",
547 "pm25_ug_m3": "50.4",
548 "elevation_m": "2.2"
549 }
550 },
551 {
552 "type": "Feature",
553 "geometry": {
554 "type": "Point",
555 "coordinates": [
556 100.5701,
557 13.7665
558 ]
559 },
560 "properties": {
561 "station_id": "31",
562 "name_th": "ศูนย์วัฒนธรรมแห่งประเทศไทย",
563 "name_en": "Thailand Cultural Centre",
564 "sensor_value": "24.22",
565 "pm25_ug_m3": "48.6",
566 "elevation_m": "2.7"
567 }
568 },
569 {
570 "type": "Feature",
571 "geometry": {
572 "type": "Point",
573 "coordinates": [
574 100.5736,
575 13.777
576 ]
577 },
578 "properties": {
579 "station_id": "32",
580 "name_th": "ห้วยขวาง",
581 "name_en": "Huai Khwang",
582 "sensor_value": "10.93",
583 "pm25_ug_m3": "49.7",
584 "elevation_m": "3.4"
585 }
586 },
587 {
588 "type": "Feature",
589 "geometry": {
590 "type": "Point",
591 "coordinates": [
592 100.5747,
593 13.7886
594 ]
595 },
596 "properties": {
597 "station_id": "33",
598 "name_th": "สุทธิสาร",
599 "name_en": "Sutthisan",
600 "sensor_value": "9.48",
601 "pm25_ug_m3": "53.3",
602 "elevation_m": "4.3"
603 }
604 },
605 {
606 "type": "Feature",
607 "geometry": {
608 "type": "Point",
609 "coordinates": [
610 100.574,
611 13.7995
612 ]
613 },
614 "properties": {
615 "station_id": "34",
616 "name_th": "รัชดาภิเษก",
617 "name_en": "Ratchadaphisek",
618 "sensor_value": "17.28",
619 "pm25_ug_m3": "57.6",
620 "elevation_m": "5.4"
621 }
622 },
623 {
624 "type": "Feature",
625 "geometry": {
626 "type": "Point",
627 "coordinates": [
628 100.574,
629 13.8062
630 ]
631 },
632 "properties": {
633 "station_id": "35",
634 "name_th": "ลาดพร้าว",
635 "name_en": "Lat Phrao",
636 "sensor_value": "26.71",
637 "pm25_ug_m3": "60.0",
638 "elevation_m": "6.7"
639 }
640 },
641 {
642 "type": "Feature",
643 "geometry": {
644 "type": "Point",
645 "coordinates": [
646 100.5618,
647 13.8141
648 ]
649 },
650 "properties": {
651 "station_id": "36",
652 "name_th": "พหลโยธิน",
653 "name_en": "Phahon Yothin",
654 "sensor_value": "31.13",
655 "pm25_ug_m3": "58.3",
656 "elevation_m": "8.1"
657 }
658 },
659 {
660 "type": "Feature",
661 "geometry": {
662 "type": "Point",
663 "coordinates": [
664 100.5535,
665 13.8138
666 ]
667 },
668 "properties": {
669 "station_id": "37",
670 "name_th": "สวนจตุจักร",
671 "name_en": "Chatuchak Park",
672 "sensor_value": "29.98",
673 "pm25_ug_m3": "52.2",
674 "elevation_m": "9.5"
675 }
676 },
677 {
678 "type": "Feature",
679 "geometry": {
680 "type": "Point",
681 "coordinates": [
682 100.5495,
683 13.8027
684 ]
685 },
686 "properties": {
687 "station_id": "38",
688 "name_th": "กำแพงเพชร",
689 "name_en": "Kamphaeng Phet",
690 "sensor_value": "28.91",
691 "pm25_ug_m3": "42.9",
692 "elevation_m": "11.1"
693 }
694 },
695 {
696 "type": "Feature",
697 "geometry": {
698 "type": "Point",
699 "coordinates": [
700 100.5365,
701 13.8027
702 ]
703 },
704 "properties": {
705 "station_id": "39",
706 "name_th": "บางซื่อ",
707 "name_en": "Bang Sue",
708 "sensor_value": "34.98",
709 "pm25_ug_m3": "33.2",
710 "elevation_m": "12.6"
711 }
712 },
713 {
714 "type": "Feature",
715 "geometry": {
716 "type": "Point",
717 "coordinates": [
718 100.5289,
719 13.8055
720 ]
721 },
722 "properties": {
723 "station_id": "40",
724 "name_th": "เตาปูน",
725 "name_en": "Tao Poon",
726 "sensor_value": "50.61",
727 "pm25_ug_m3": "25.7",
728 "elevation_m": "14.1"
729 }
730 },
731 {
732 "type": "Feature",
733 "geometry": {
734 "type": "Point",
735 "coordinates": [
736 100.524,
737 13.8113
738 ]
739 },
740 "properties": {
741 "station_id": "41",
742 "name_th": "บางซ่อน",
743 "name_en": "Bang Son",
744 "sensor_value": "71.02",
745 "pm25_ug_m3": "22.1",
746 "elevation_m": "15.4"
747 }
748 },
749 {
750 "type": "Feature",
751 "geometry": {
752 "type": "Point",
753 "coordinates": [
754 100.5197,
755 13.8195
756 ]
757 },
758 "properties": {
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1534 "name_th": "รัชดาภิเษก เซนเซอร์ 2",
1535 "name_en": "Ratchadaphisek Sensor 2",
1536 "sensor_value": "91.03",
1537 "pm25_ug_m3": "29.5",
1538 "elevation_m": "19.9"
1539 }
1540 },
1541 {
1542 "type": "Feature",
1543 "geometry": {
1544 "type": "Point",
1545 "coordinates": [
1546 100.574818,
1547 13.806725
1548 ]
1549 },
1550 "properties": {
1551 "station_id": "86",
1552 "name_th": "ลาดพร้าว เซนเซอร์ 2",
1553 "name_en": "Lat Phrao Sensor 2",
1554 "sensor_value": "78.46",
1555 "pm25_ug_m3": "37.6",
1556 "elevation_m": "19.6"
1557 }
1558 },
1559 {
1560 "type": "Feature",
1561 "geometry": {
1562 "type": "Point",
1563 "coordinates": [
1564 100.561808,
1565 13.814997
1566 ]
1567 },
1568 "properties": {
1569 "station_id": "87",
1570 "name_th": "พหลโยธิน เซนเซอร์ 2",
1571 "name_en": "Phahon Yothin Sensor 2",
1572 "sensor_value": "66.19",
1573 "pm25_ug_m3": "47.3",
1574 "elevation_m": "19.0"
1575 }
1576 },
1577 {
1578 "type": "Feature",
1579 "geometry": {
1580 "type": "Point",
1581 "coordinates": [
1582 100.55269,
1583 13.814432
1584 ]
1585 },
1586 "properties": {
1587 "station_id": "88",
1588 "name_th": "สวนจตุจักร เซนเซอร์ 2",
1589 "name_en": "Chatuchak Park Sensor 2",
1590 "sensor_value": "60.19",
1591 "pm25_ug_m3": "55.8",
1592 "elevation_m": "18.1"
1593 }
1594 },
1595 {
1596 "type": "Feature",
1597 "geometry": {
1598 "type": "Point",
1599 "coordinates": [
1600 100.5488,
1601 13.802618
1602 ]
1603 },
1604 "properties": {
1605 "station_id": "89",
1606 "name_th": "กำแพงเพชร เซนเซอร์ 2",
1607 "name_en": "Kamphaeng Phet Sensor 2",
1608 "sensor_value": "59.79",
1609 "pm25_ug_m3": "60.6",
1610 "elevation_m": "17.1"
1611 }
1612 },
1613 {
1614 "type": "Feature",
1615 "geometry": {
1616 "type": "Point",
1617 "coordinates": [
1618 100.536713,
1619 13.801962
1620 ]
1621 },
1622 "properties": {
1623 "station_id": "90",
1624 "name_th": "บางซื่อ เซนเซอร์ 2",
1625 "name_en": "Bang Sue Sensor 2",
1626 "sensor_value": "58.70",
1627 "pm25_ug_m3": "60.8",
1628 "elevation_m": "15.9"
1629 }
1630 },
1631 {
1632 "type": "Feature",
1633 "geometry": {
1634 "type": "Point",
1635 "coordinates": [
1636 100.529782,
1637 13.80463
1638 ]
1639 },
1640 "properties": {
1641 "station_id": "91",
1642 "name_th": "เตาปูน เซนเซอร์ 2",
1643 "name_en": "Tao Poon Sensor 2",
1644 "sensor_value": "50.52",
1645 "pm25_ug_m3": "57.3",
1646 "elevation_m": "14.6"
1647 }
1648 },
1649 {
1650 "type": "Feature",
1651 "geometry": {
1652 "type": "Point",
1653 "coordinates": [
1654 100.524539,
1655 13.810916
1656 ]
1657 },
1658 "properties": {
1659 "station_id": "92",
1660 "name_th": "บางซ่อน เซนเซอร์ 2",
1661 "name_en": "Bang Son Sensor 2",
1662 "sensor_value": "34.36",
1663 "pm25_ug_m3": "52.4",
1664 "elevation_m": "13.1"
1665 }
1666 },
1667 {
1668 "type": "Feature",
1669 "geometry": {
1670 "type": "Point",
1671 "coordinates": [
1672 100.519278,
1673 13.819875
1674 ]
1675 },
1676 "properties": {
1677 "station_id": "93",
1678 "name_th": "วงศ์สว่าง เซนเซอร์ 2",
1679 "name_en": "Wong Sawang Sensor 2",
1680 "sensor_value": "16.21",
1681 "pm25_ug_m3": "48.8",
1682 "elevation_m": "11.6"
1683 }
1684 },
1685 {
1686 "type": "Feature",
1687 "geometry": {
1688 "type": "Point",
1689 "coordinates": [
1690 100.504101,
1691 13.794367
1692 ]
1693 },
1694 "properties": {
1695 "station_id": "94",
1696 "name_th": "บางพลัด เซนเซอร์ 2",
1697 "name_en": "Bang Phlat Sensor 2",
1698 "sensor_value": "4.95",
1699 "pm25_ug_m3": "48.0",
1700 "elevation_m": "10.1"
1701 }
1702 },
1703 {
1704 "type": "Feature",
1705 "geometry": {
1706 "type": "Point",
1707 "coordinates": [
1708 100.533754,
1709 13.757544
1710 ]
1711 },
1712 "properties": {
1713 "station_id": "95",
1714 "name_th": "พญาไท เซนเซอร์ 2",
1715 "name_en": "Phaya Thai Sensor 2",
1716 "sensor_value": "5.96",
1717 "pm25_ug_m3": "49.8",
1718 "elevation_m": "8.6"
1719 }
1720 },
1721 {
1722 "type": "Feature",
1723 "geometry": {
1724 "type": "Point",
1725 "coordinates": [
1726 100.541904,
1727 13.756692
1728 ]
1729 },
1730 "properties": {
1731 "station_id": "96",
1732 "name_th": "ราชปรารภ เซนเซอร์ 2",
1733 "name_en": "Ratchaprarop Sensor 2",
1734 "sensor_value": "17.29",
1735 "pm25_ug_m3": "52.3",
1736 "elevation_m": "7.1"
1737 }
1738 },
1739 {
1740 "type": "Feature",
1741 "geometry": {
1742 "type": "Point",
1743 "coordinates": [
1744 100.561861,
1745 13.750175
1746 ]
1747 },
1748 "properties": {
1749 "station_id": "97",
1750 "name_th": "มักกะสัน เซนเซอร์ 2",
1751 "name_en": "Makkasan Sensor 2",
1752 "sensor_value": "31.28",
1753 "pm25_ug_m3": "52.9",
1754 "elevation_m": "5.8"
1755 }
1756 },
1757 {
1758 "type": "Feature",
1759 "geometry": {
1760 "type": "Point",
1761 "coordinates": [
1762 100.603431,
1763 13.746602
1764 ]
1765 },
1766 "properties": {
1767 "station_id": "98",
1768 "name_th": "รามคำแหง เซนเซอร์ 2",
1769 "name_en": "Ramkhamhaeng Sensor 2",
1770 "sensor_value": "40.38",
1771 "pm25_ug_m3": "49.8",
1772 "elevation_m": "4.7"
1773 }
1774 },
1775 {
1776 "type": "Feature",
1777 "geometry": {
1778 "type": "Point",
1779 "coordinates": [
1780 100.64105,
1781 13.746467
1782 ]
1783 },
1784 "properties": {
1785 "station_id": "99",
1786 "name_th": "หัวหมาก เซนเซอร์ 2",
1787 "name_en": "Hua Mak Sensor 2",
1788 "sensor_value": "42.64",
1789 "pm25_ug_m3": "42.6",
1790 "elevation_m": "3.7"
1791 }
1792 },
1793 {
1794 "type": "Feature",
1795 "geometry": {
1796 "type": "Point",
1797 "coordinates": [
1798 100.66493,
1799 13.746511
1800 ]
1801 },
1802 "properties": {
1803 "station_id": "100",
1804 "name_th": "บ้านทับช้าง เซนเซอร์ 2",
1805 "name_en": "Ban Thap Chang Sensor 2",
1806 "sensor_value": "42.77",
1807 "pm25_ug_m3": "32.8",
1808 "elevation_m": "2.9"
1809 }
1810 }
1811 ]
1812 }
0:24
The issue is clear. The numeric fields like `sensor_value`, `pm25_ug_m3`, and `elevation_m` are stored as strings (e.g., `"84.55"` instead of `84.55`). When the analytics dashboard computes averages, it's likely using a library that expects numeric types (e.g., pandas reading them as object/string dtype), resulting in NaN when trying to compute means. I need to convert these numeric string fields to actual numbers while leaving string columns (station_id, name_th, name_en) and geometry alone. Let me write a Python script using geopandas to read the GeoJSON, convert the numeric columns to float, and write the result.
0:24
0:24
Write
/work/solve.py
content · 16 lines · py
import geopandas as gpd
# Read the source file
gdf = gpd.read_file("/work/bangkok_aq_stations.geojson")
# Identify numeric columns to convert
numeric_cols = ["sensor_value", "pm25_ug_m3", "elevation_m"]
for col in numeric_cols:
if col in gdf.columns:
# Convert to float, coercing any bad values to NaN
gdf[col] = pd.to_numeric(gdf[col], errors="coerce")
# Write to output GeoJSON
gdf.to_file("/work/bangkok_aq_typed.geojson", driver="GeoJSON")
Wrote /work/solve.py (468 chars).
0:28
I forgot to import pandas. Let me fix that.
0:28
Edit
/work/solve.py
Edited /work/solve.py.
0:52
Bash
cd /work && python solve.py
(no output)
1:08
Let me verify the output file was created and check that the numeric fields are indeed floats now.
1:08
Bash
cd /work && python -c "
cd /work && python -c "
import geopandas as gpd
gdf = gpd.read_file('/work/bangkok_aq_typed.geojson')
print('Columns:', gdf.columns.tolist())
print(gdf.dtypes)
print()
print('First 3 rows:')
print(gdf.head(3))
print()
# Verify string columns are still strings
print('station_id type:', gdf['station_id'].dtype)
print('name_th type:', gdf['name_th'].dtype)
print('name_en type:', gdf['name_en'].dtype)
print()
# Check means
print('Mean sensor_value:', gdf['sensor_value'].mean())
print('Mean pm25_ug_m3:', gdf['pm25_ug_m3'].mean())
print('Mean elevation_m:', gdf['elevation_m'].mean())
"
Columns: ['station_id', 'name_th', 'name_en', 'sensor_value', 'pm25_ug_m3', 'elevation_m', 'geometry'] station_id str name_th str name_en str sensor_value float64 pm25_ug_m3 float64 elevation_m float64 geometry geometry dtype: object First 3 rows: station_id name_th ... elevation_m geometry 0 1 สนามกีฬาแห่งชาติ ... 11.0 POINT (100.5294 13.7464) 1 2 สยาม ... 12.5 POINT (100.5343 13.7456) 2 3 ชิดลม ... 14.0 POINT (100.5436 13.7441) [3 rows x 7 columns] station_id type: str name_th type: str name_en type: str Mean sensor_value: 49.97830000000001 Mean pm25_ug_m3: 36.516000000000005 Mean elevation_m: 11.716000000000001
1:14
The output looks correct. The numeric columns are now float64, the string columns remain as strings (with Thai script preserved), the geometry is untouched, and the means compute properly (no NaN).
1:14