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reading tab file
#1
please help with correct pandas syntax sep to read below pasted tab txt file into columns.It has a lot of header columns>>>

Output:
Timestamp Longitude Latitude Speed Operatorname Operator CGI Cellname Node CellID LAC NetworkTech NetworkMode Level Qual SNR CQI LTERSSI ARFCN DL_bitrate UL_bitrate PSC Altitude Height Accuracy Location State PINGAVG PINGMIN PINGMAX PINGSTDEV PINGLOSS TESTDOWNLINK TESTUPLINK TESTDOWNLINKMAX TESTUPLINKMAX Test_Status DataConnection_Type DataConnection_Info Layer Filemark IMEI Distance Bearing IP TA EVENT EVENTDETAILS IMSI MSISDN SERVINGTIME CELLHEX NODEHEX LACHEX RAWCELLID VERSION_NAME VERSION_CODE DEVICE BAND R8 R9 R10 NTech1 NCellName1 NCellid1 NLAC1 NCell1 NARFCN1 NRxLev1 NQual1 NDistance1 NBearing1 NTech2 NCellName2 NCellid2 NLAC2 NCell2 NARFCN2 NRxLev2 NQual2 NDistance2 NBearing2 NTech3 NCellName3 NCellid3 NLAC3 NCell3 NARFCN3 NRxLev3 NQual3 NDistance3 NBearing3 NTech4 NCellName4 NCellid4 NLAC4 NCell4 NARFCN4 NRxLev4 NQual4 NDistance4 NBearing4 NTech5 NCellName5 NCellid5 NLAC5 NCell5 NARFCN5 NRxLev5 NQual5 NDistance5 NBearing5 NTech6 NCellName6 NCellid6 NLAC6 NCell6 NARFCN6 NRxLev6 NQual6 NDistance6 NBearing6 NTech7 NCellName7 NCellid7 NLAC7 NCell7 NARFCN7 NRxLev7 NQual7 NDistance7 NBearing7 NTech8 NCellName8 NCellid8 NLAC8 NCell8 NARFCN8 NRxLev8 NQual8 NDistance8 NBearing8 NTech9 NCellName9 NCellid9 NLAC9 NCell9 NARFCN9 NRxLev9 NQual9 NDistance9 NBearing9 NTech10 NCellName10 NCellid10 NLAC10 NCell10 NARFCN10 NRxLev10 NQual10 NDistance10 NBearing10 NTech11 NCellName11 NCellid11 NLAC11 NCell11 NARFCN11 NRxLev11 NQual11 NDistance11 NBearing11 NTech12 NCellName12 NCellid12 NLAC12 NCell12 NARFCN12 NRxLev12 NQual12 NDistance12 NBearing12 NTech13 NCellName13 NCellid13 NLAC13 NCell13 NARFCN13 NRxLev13 NQual13 NDistance13 NBearing13 NTech14 NCellName14 NCellid14 NLAC14 NCell14 NARFCN14 NRxLev14 NQual14 NDistance14 NBearing14 NTech15 NCellName15 NCellid15 NLAC15 NCell15 NARFCN15 NRxLev15 NQual15 NDistance15 NBearing15 NTech16 NCellName16 NCellid16 NLAC16 NCell16 NARFCN16 NRxLev16 NQual16 NDistance16 NBearing16 NTech17 NCellName17 NCellid17 NLAC17 NCell17 NARFCN17 NRxLev17 NQual17 NDistance17 NBearing17 NTech18 NCellName18 NCellid18 NLAC18 NCell18 NARFCN18 NRxLev18 NQual18 NDistance18 NBearing18 2019.07.31_10.30.49 18.612976 -33.87478 20 Vodacom-SA 65501 655012111200010 LTE_Welgemoed_CT_WES_10 924040 10 21112 4G LTE -97 -9 8.0 8 -80 1771 0 0 66 256 256 2 G I M 13 1 150 177 41.7.127.187 3 LOG START 20 A E1988 5278 236554250 17.4 304 samsung:SM-G955F:R16NW L3 4G 0 0 107 1771 -97 -10 2019.07.31_10.30.50 18.613126 -33.87477 23 Vodacom-SA 65501 655012111200010 LTE_Welgemoed_CT_WES_10 924040 10 21112 4G LTE -97 -9 8.0 8 -80 1771 0 0 66 256 256 6 G I M 13 1 163 176 41.7.127.187 3 20 A E1988 5278 236554250 17.4 304 samsung:SM-G955F:R16NW L3 4G 0 0 107 1771 -97 -10 2019.07.31_10.30.52
Reply
#2
Assuming that your csv file is named test.csv
import pandas as pd
df = pd.read_csv('test.csv', delimiter='\t')
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