In [2]:
using DataFrames # load DataFrames package

airblankA = readtable("airblankA.CSV", separator = ',',
                    skipstart = 3, header = false,
                    names = [Symbol("time"), Symbol("counts")]
);
first(airblankA,5)
Out[2]:

5 rows × 2 columns

timecounts
Float64⍰Float64⍰
13.09117072.0
23.09617585.0
33.117275.0
43.10416739.0
53.10918590.0
In [3]:
airblankA[:relative_abundance] = airblankA[:counts] ./ maximum(airblankA[:counts]) .*100
Out[3]:
3162-element Array{Float64,1}:
 43.33654871300198
 44.638777478803874
 43.851855612529825
 42.491242321165664
 47.18992740011169
 45.84962176981266
 44.935777021881506
 39.72432350104077
 45.22769964969285
 42.63339594862162
 43.18170279738031
 43.48377925572422
 42.61308828755649
  ⋮
 90.69655277453418
 88.25455653145148
 94.2605472914657
 92.55724221962735
 91.82870487891557
 91.48347464080825
 90.65086053713763
 93.67924049347617
 96.4131593643702
 93.39493323856425
 91.6129359800985
 91.56724374270193
In [5]:
using PyPlot
scatter(airblankA[:time], airblankA[:counts])
xlabel("time (sec)")
ylabel("counts")
Out[5]:
PyObject Text(24,0.5,'counts')
In [6]:
using DataFrames # load DataFrames package

airB= readtable("airblankB.CSV", separator = ',',
                    skipstart = 3, header = false,
                    names = [Symbol("time"), Symbol("counts")]
);
first(airB,5)
Out[6]:

5 rows × 2 columns

timecounts
Float64⍰Float64⍰
13.09119617.0
23.09619400.0
33.119432.0
43.10418666.0
53.10919182.0
In [8]:
airB[:relative_abundance] = airB[:counts] ./ maximum(airB[:counts]) .*100
Out[8]:
3162-element Array{Float64,1}:
 14.92661101938017
 14.761495324258311
 14.785844182525128
 14.202993387763177
 14.595618727315616
 14.53474658164857
 13.983092761540977
 15.13433721646896
 14.774430655212559
 13.46948403247529
 14.567465359944606
 14.607032254628185
 14.509636821560914
  ⋮
 33.89056710012707
 35.8544546997101
 35.55313757865823
 35.28530013772323
 35.851411092426744
 34.018398606027866
 34.52135470960182
 35.288343745006586
 35.28453923590239
 34.88734848542492
 34.02068131149038
 33.17684119218097
In [9]:
using PyPlot
scatter(airB[:time], airB[:counts])
xlabel("time (sec)")
ylabel("counts")
Out[9]:
PyObject Text(24,0.5,'counts')
In [ ]: