LED-Acid_Fly_Research/plotter_acid_fly_data.jl at main · Kannampuzha/LED-Acid_Fly_Research · GitHub

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
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
using DataFrames, CSV, PlotlyJS,Statistics

# Load the data
df= CSV.read("Plots\\Hostel_Data.csv",DataFrame)

#print(df[:,5])


#Graph 1 , frequecy plot of acid fly attacks
#Make Histogram of columns 4 vs 6
function plot_histogram(df)
    layout=Layout(title="Histogram of columns 4 vs 6",
        xaxis_title="Column 7",
        yaxis_title="Column 5",
        font=attr(family="Times New Roman"),
        legend=attr(font=attr(size=18, family="Times New Roman")),
        xaxis=attr(titlefont=attr(size=18,family="Times New Roman")),
        tickfont=attr(size=18,family="Times New Roman"),
        yaxis=attr(titlefont=attr(size=18,family="Times New Roman")),
        barmode="overlay"

        )
    cf=df
    #Remove all coumns except 5th and 7th
    cf=cf[:,[5,7]]
    #only CFL


    #println(cf)
    #Rename the columns as A and B
    cf=rename(cf,:1=>"Lights",:2=>"Encounters")
    #println(cf)

    ans=plot(cf,x=:Encounters,kind="histogram",color=:Lights,xbins=attr(start=1,size=5),Layout(barmode="overlay",font=attr(family="Times New Roman"),
    legend=attr(font=attr(size=18, family="Times New Roman")),xaxis_title="Number of Acid Fly Encounters in Summer 2023",yaxis_title="Number of Rooms Affected"),opacity=0.7)
    savefig(ans,"histogram.pdf",scale=0.5)
end

#Plot 2 - number of people unaffected by acid flies and the lights they use
#plot_histogram(df)
#Count the number of entries which have 7th coulmn as 0
function count_zeros(df)
    count=0
    for i in 1:size(df,1)
        if df[i,7]==0
            count+=1
        end
    end
    println("Number of entries with 0 encounters: $count")
end
#Count Non count_zeros
function count_non_zeros(df)
    count=0
    for i in 1:size(df,1)
        if df[i,7]!=0
            count+=1
        end
    end
    println("Number of entries with non-zero encounters: $count")
end

#count_zeros(df)
#count_non_zeros(df)

#Calculate average of 7th colum groupp by 5th column, new syntax
#remove all rows with 0 encounters

function groupby2(df, col)
    #Remove all rows with 0 encounters
    df=df[df[:,7].!=0,:]
    #Group by the column
    gdf=groupby(df, col)
    return gdf
end

gdf = groupby2(df, :"LED Or CFL" )
#println(gdf)
avg_data=combine(gdf, :"How many times have you been bit or seen the insect?" => mean)
#println(avg_data)

#Plot 3 - Bar graph of average number of acid fly encounters for each type of light
function plot_bar_graph(avg_data)


    #Rename
    avg_data=rename(avg_data,:1=>"Light",:2=>"Average")
    println(avg_data)

    ans=plot(avg_data,x=:Light,y=:Average,kind="bar",Layout(font=attr(family="Times New Roman"),legend=attr(font=attr(size=18, family="Times New Roman")),xaxis_title="Type of Light",yaxis_title="Average number of Acid Fly Encounters"))
    #legend=attr(font=attr(size=18, family="Times New Roman")),xaxis_title="Type of Light",yaxis_title="Average number of Acid Fly Attacks"))
    savefig(ans,"bar_graph.pdf",scale=0.5)
end

plot_bar_graph(avg_data)

#Take all non zero data
function non_zero_data(df)
    return df[df[:,7].!=0,:]
end
#Take all zero data
function zero_data(df)
    return df[df[:,7].==0,:]
end

#Data processing for calcualting Probability by bayes theorem
#For the non zero data, calculate how many lights used LEDs, how many used CFLs and how many used both
function count_lights(df)
    #df=non_zero_data(df)
    #println(df)
    count_led=0
    count_cfl=0
    count_both=0
    for i in 1:size(df,1)
        if df[i,5]=="LED"
            count_led+=1
        elseif df[i,5]=="CFL"
            count_cfl+=1
        else
            count_both+=1
        end
    end
    println("Number of people using LED: $count_led")
    println("Number of people using CFL: $count_cfl")
    println("Number of people using both: $count_both")
end


#count_lights(df)