使用CSV.file和Dataframes读取完整的值表文件时出现问题
我是Julia的新手（今天才开始！），我正在尝试将带有值表的使用CSV.file和Dataframes读取完整的值表文件时出现问题,dataframe,julia,Dataframe,Julia,我是Julia的新手（今天才开始！），我正在尝试将带有值表的.data作为数据帧读入Julia，以便最终提取第42列和第43列下的两个值。这是输入文件的外观： 1 2 3 4 5
.data 1 2 3 4 5 6 7
version_number compiler build MESA_SDK_version date burn_min1 burn_min2
11701 "gfortran" "9.2.0" "x86_64-linux-20.3.2" "20200718" 5.0000000000000000E+001 1.0000000000000000E+003
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62
model_number star_age star_age_day rsp_phase rsp_GREKM rsp_GREKM_avg_abs rsp_DeltaR rsp_DeltaMag rsp_period_in_days rsp_num_periods log_dt_sec radius log_R v_surf_km_s v_surf_div_escape_v v_div_csound_surf v_div_csound_max max_abs_v_div_cs dt_div_min_dr_div_cs luminosity log_L effective_T log_g log_Teff photosphere_L photosphere_r photosphere_T photosphere_v_km_s photosphere_v_div_cs num_retries bc_V bc_I bc_U bc_B bc_R bc_J bc_H bc_K bc_L bc_Lprime bc_M abs_mag_V abs_mag_I abs_mag_U abs_mag_B abs_mag_R abs_mag_J abs_mag_H abs_mag_K abs_mag_L abs_mag_Lprime abs_mag_M bc_bb_U bc_bb_B bc_bb_V bc_bb_R bc_bb_I abs_mag_bb_U abs_mag_bb_B abs_mag_bb_V abs_mag_bb_R abs_mag_bb_I
1 6.7389636078418866E-007 2.4614493550114818E-004 1.9999999999999998E-005 0.0000000000000000E+000 0.0000000000000000E+000 0.0000000000000000E+000 0.0000000000000000E+000 1.2307246775057409E+001 0 1.3277046469527609E+000 1.0355852690247899E+002 2.0151858640622273E+000 9.9999999081613875E-002 6.3180115760696077E-004 1.5454144687980833E-002 1.5454144687984667E-002 1.5454144687984667E-002 1.6320949498828532E-002 3.9999980998388105E+003 3.6020597850205331E+000 4.5100140752805628E+003 1.2400265636241821E+000 3.6541778972675703E+000 4.0000005694630740E+003 1.0276598054436276E+002 4.5100139503744604E+003 9.5722781222727801E-002 1.3625500625299287E-002 0 -5.0444989520674666E-001 5.9105931711038406E-001 -3.0557187404691080E+000 -1.7462239207128374E+000 8.3956903708770375E-002 1.4560380234244312E+000 2.0946680279357213E+000 1.9906767067550131E+000 2.2200875064387224E+000 2.2276156474047601E+000 2.6456661780258299E+000 8.0200636642834709E+001 7.9105127430517584E+001 8.2751905488097066E+001 8.1442410668340798E+001 7.9612229843919195E+001 7.8240148724203536E+001 7.7601518719692237E+001 7.7705510040872952E+001 7.7476099241189246E+001 7.7468571100223201E+001 7.7050520569602128E+001 -1.5853854762609063E+000 -1.3814794330855515E+000 -4.1347249807174019E-001 2.1272797873251398E-001 7.9829238167607985E-001 8.1281572223888872E+001 8.1077666180713507E+001 8.0109659245699703E+001 7.9483458768895446E+001 7.8897894365951885E+001
using DataFrames
using CSV
cwd = pwd()
ParentDir = joinpath(cwd,"LOGS_A")
dirs = readdir(ParentDir, join=true)
CurrentFile = joinpath(dirs[66],"history.data")
println(CurrentFile)
df = DataFrame(CSV.File(CurrentFile, skipto=5,header=1))
println(df)
println(df[:, :42])
println(df[:, :43])
CSV.write("julia_test_file", df)
Column1,Column2,Column3,Column4,Column5,Column6,Column7,Column8,Column9,Column10,Column11,Column12,Column13,Column14,Column15,Column16,Column17,Column18,Column19,Column20,Column21,Column22,Column23,Column24,Column25,Column26,Column27,1,Column29,Column30,Column31,Column32,Column33,Column34,Column35,Column36,Column37,Column38,Column39,Column40,Column41,Column42,Column43,Column44,Column45,Column46,Column47,Column48,Column49,Column50,Column51,Column52,Column53,Column54,Column55,2,Column57,Column58,Column59,Column60,Column61,Column62,Column63,Column64,Column65,Column66,Column67,Column68,Column69,Column70,Column71,Column72,Column73,Column74,Column75,Column76,Column77,Column78,Column79,Column80,Column81,Column82,Column83,3,Column85,Column86,Column87,Column88,Column89,Column90,Column91,Column92,Column93,Column94,Column95,Column96,Column97,Column98,Column99,Column100,Column101,Column102,Column103,Column104,Column105,Column106,Column107,Column108,Column109,Column110,Column111,4,Column113,Column114,Column115,Column116,Column117,Column118,Column119,Column120,Column121,Column122,Column123,Column124,Column125,Column126,Column127,Column128,Column129,Column130,Column131,Column132,Column133,Column134,Column135,Column136,Column137,Column138,Column139,5,Column141,Column142,Column143,Column144,Column145,Column146,Column147,Column148,Column149,Column150,Column151,Column152,Column153,Column154,Column155,Column156,Column157,Column158,Column159,Column160,Column161,Column162,Column163,Column164,Column165,Column166,Column167,6,Column169,Column170,Column171,Column172,Column173,Column174,Column175,Column176,Column177,Column178,Column179,Column180,Column181,Column182,Column183,Column184,Column185,Column186,Column187,Column188,Column189,Column190,Column191,Column192,Column193,Column194,Column195,7,Column197
,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,2,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,3,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,4,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
,,,,,,,,,,,,,,,,,,,,,,,,,,,,model_number,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,star_age,,,,,,,,,,,,,,,,,,,,,,,,,,,,,star_age_day,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,rsp_phase,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,rsp_GREKM,,,,,,,,,,,,,,,,,,,,,,,,rsp_GREKM_avg_abs,,,,,,,,,,,,,,,,,,
,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,1,,,,,,,,,,,,,,,,,,6.738963607841887e-7,,,,,,,,,,,,,,,,,,0.0002461449355011482,,,,,,,,,,,,,,,,,,1.9999999999999998e-5,,,,,,,,,,,,,,,,,,0.0,,,,,,,,,,,,,,,,,,0.0,,,,,,,,,,,,,,,,,,0.0,,,,,,,,,,,,,,,,,,0.0,,,,,,,,,,,,,,,,,,12.30724677505741,,,,,,,,,,,,,
如何改进代码以成功完成任务？似乎未正确选择
CSV.Filejulia> df = DataFrame(CSV.File("tmp.csv", skipto = 7, header = 6, delim=' ', ignorerepeated=true))
1×62 DataFrame. Omitted printing of 53 columns
│ Row │ model_number │ star_age │ star_age_day │ rsp_phase │ rsp_GREKM │ rsp_GREKM_avg_abs │ rsp_DeltaR │ rsp_DeltaMag │ rsp_period_in_days │
│ │ Int64 │ Float64 │ Float64 │ Float64 │ Float64 │ Float64 │ Float64 │ Float64 │ Float64 │
├─────┼──────────────┼────────────┼──────────────┼───────────┼───────────┼───────────────────┼────────────┼──────────────┼────────────────────┤
│ 1 │ 1 │ 6.73896e-7 │ 0.000246145 │ 2.0e-5 │ 0.0 │ 0.0 │ 0.0 │ 0.0 │ 12.3072 │
julia> df[:,43]
1-element Array{Float64,1}:
79.10512743051758
julia> names(df)[43]
"abs_mag_I"
julia> df.abs_mag_I
1-element Array{Float64,1}:
79.10512743051758
为了更好地回答您的问题，最好能够访问您正在使用的确切CSV。您的逗号分隔值文件似乎格式不正确。我猜CSV.File看不到逗号，而分隔字符是一个空格。结果，会得到一堆空列。