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Direct MessagesDate/Time: Mon, 20 May 2024 20:38:51 +0000
Post From: Python for Sierra Chart
| [2024-05-01 00:24:46] |
| User656492 - Posts: 137 |
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This is fun stuff. Thank you all for sharing! I just tried the code above for NQM4 and got this result. I think something's amiss with the time format, which causes Open to be a strange value: print(resample_scdf("NQM4.CME.scid", tz="EST")) Open High Low Close Trades \
Time 2024-02-25 19:01:00-05:00 0.000000e+00 18223.00 18221.25 18221.25 1 2024-02-25 19:02:00-05:00 -1.999001e+35 18207.75 18202.75 18207.75 2 2024-02-25 19:03:00-05:00 0.000000e+00 18208.50 18202.50 18208.75 4 2024-02-25 19:04:00-05:00 0.000000e+00 18209.00 18200.25 18206.25 10 2024-02-25 19:05:00-05:00 0.000000e+00 18207.00 18199.00 18206.00 6 also, because maybe it helps: df.describe() Open High Low Close Trades Volume BidVolume AskVolume
count 5.584600e+04 55846.000000 55846.000000 55846.000000 93144.000000 93144.000000 93144.000000 93144.000000 mean -inf 18176.611328 18170.449219 18173.523438 235.347591 256.042236 128.308200 127.734035 std inf 360.248291 361.233368 360.750702 571.431255 625.932788 316.699976 313.838125 min -1.999001e+35 17130.500000 17113.750000 17121.250000 0.000000 0.000000 0.000000 0.000000 25% 0.000000e+00 17912.500000 17908.750000 17910.750000 0.000000 0.000000 0.000000 0.000000 50% 0.000000e+00 18278.250000 18271.750000 18275.000000 21.000000 22.000000 10.000000 10.000000 75% 0.000000e+00 18463.500000 18458.750000 18461.250000 141.000000 154.000000 77.000000 77.000000 max 0.000000e+00 18708.500000 18702.750000 18706.000000 9990.000000 11664.000000 6341.000000 5972.000000 Date Time Of Last Edit: 2024-05-01 01:28:22
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