df1 = DataFrame(XLSX.readtable("C:/Users/Brett/Documents/Soc332Assignment3.xlsx","TestData")...)
#change everything to Float64
for name in names(df1)
df1[!, name] = identity.(df1[:, name])
end
#change everything to real
function new_vector_correct_type(x)
T = reduce(promote_type, typeof.(x))
if T == Any
return identity.(x)
else
return T.(x)
end
end
Test_matrix= Matrix(df1)
function make_pivottable(Test_matrix)
cmap = countmap(Test_matrix)
k = string.(collect(keys(cmap)))
v = collect(values(cmap))
ptab = DataFrame([k v], [:key, :counts])
sort!(ptab, :counts, rev=true)
return ptab
end
Test_pivot= make_pivottable(Test_matrix)
When I try to run this, I get an error
UndefKeywordError: keyword argument dims not assigned
(::Base.var"#kw##sort")(::NamedTuple{(:alg,),Tuple{SortingAlgorithms.RadixSortAlg}}, ::typeof(sort), ::Array{Int64,2}) at none:0
addcounts_radixsort!(::Dict{Int64,Int64}, ::Array{Int64,2}) at counts.jl:348
#addcounts!#70 at counts.jl:262 [inlined]
#addcounts! at none:0 [inlined]
#countmap#73 at counts.jl:389 [inlined]
countmap at counts.jl:389 [inlined]
make_pivottable(::Array{Int64,2}) at Soc332Assignment3.jl:58
top-level scope at Soc332Assignment3.jl:67
This is not a great error message. And maybe a bug in countmap.
countmap claims to work with matrices, but it throws an error when it tries to sort it.
My suggestion would be to use
cmap = countmap(vec(test_matrix))
To be clear, you want to get the counts of the unique values across the whole data frame or just across one vector of the data frame?
using DataFrames, Statistics, FreqTables
N = 1000
speed_opt = ["Speed up", "Slowed down"]
gender_opt = ["Male", "Female"]
age_opt = ["Young", "Old"]
time_day_opt = ["Rush hour", "Non-rush houw"]
df = DataFrame(
speed = rand(speed_opt, N),
gender = rand(gender_opt, N),
age = rand(age_opt, N),
time_day = rand(time_day_opt, N)
)
function get_stats(df, var1, var2)
Ns = freqtable(df, var1, var2)
N = sum(Ns)
percents = Ns ./ N
names_Ns = names(Ns)
results = DataFrame()
results[:, var1] = names_Ns[1]
for name in names(Ns)[2]
results[:, Symbol(name, :_N)] = Ns[:, name]
results[:, Symbol(name, :_pct)] = percents[:, name]
end
return results
end
t = freqtable(df, :speed, :gender)
get_stats(df, :speed, :gender)
Why is there a row that says
df = DataFrame()
You can initialize an emtpy dataframe and then add columns to it. Please read the DataFrames documentation .
function get_stats(df1, consume, marijuana)
Ns = freqtable(df1, consume, marijuana)
N = sum(Ns)
percents = Ns ./ N
names_Ns = names(Ns)
df = DataFrame()
df1[consume, marijuana] = names_Ns[1]
for name in names(Ns)[2]
df1[:, Symbol(name, :_N)] = Ns[:, name]
df1[:, Symbol(name, :_pct)] = percents[:, name]
end
return df1
end
t = freqtable(df1, :consume, :marijuana)
get_stats(df, :_N, :pct)
I thought I had it, but I’m not sure what to have in get_stats, that the df line isn’t highlighted as an error.
You need df[:, marijuana].
pdeffebach:
df[:, marijuana] .
Seems to have fixed that issue, now it’s saying the columns aren’t the same length, but not sure why since the original columns were the same length.
I’m not sure what’s going on. The code I posted above seems to work. Without a full MWE (see how I created the DataFrame above), its tough to help you.
Ok, I’ll see what I can put together.
f1 = DataFrame(XLSX.readtable("C:/Users/Brett/Documents/Soc332Assignment3.xlsx","TestData")...)
#change everything to Float64
for name in names(df1)
df1[!, name] = identity.(df1[:, name])
end
#change evrything to real
function new_vector_correct_type(x)
T = reduce(promote_type, typeof.(x))
if T == Any
return identity.(x)
else
return T.(x)
end
end
Test_matrix= Matrix(df1)
Test_contingency= freqtable(df, names(df1)...)
#change this over for my data
N = 608
function get_stats(df1, consume, marijuana)
Ns = freqtable(df1, consume, marijuana)
N = sum(Ns)
percents = Ns ./ N
names_Ns = names(Ns)
df = DataFrame()
df[:, marijuana] = names_Ns[1]
for name in names(Ns)[2]
df[:, Symbol(name, :_N)] = Ns[:, name]
df[:, Symbol(name, :_pct)] = percents[:, name]
end
return df1
end
t = freqtable(df, :consume, :marijuana)
get_stats(df, :consume, :marijuana)
Data Copied from Excel
Year
Crude_Birth_Rate
Female_Employment
Female_Unemployment
Female_Participation
1976
15.6
50
7.4
54
1977
15.5
51.3
8
55.8
1978
15.2
53.6
8.6
58.7
1979
15.4
55.7
7.7
60.4
1980
15.4
58
7
62.4
1981
15.3
60.3
7.5
65.2
1982
15.1
59.7
9.6
66.1
1983
15
60.5
10.5
67.6
1984
15
62.1
10.6
69.4
1985
14.9
63.8
10.2
71
1986
14.5
66.5
9.2
73.2
1987
14.4
67.5
8.7
74
1988
14.5
69.4
7.9
75.3
1989
14.9
70.5
7.9
76.6
1990
15
71.5
7.9
77.7
1991
14.9
70.5
9.3
77.8
1992
14.7
69.4
9.6
76.8
1993
13.6
69.1
10.3
77.1
1994
13.1
69.6
9.5
76.9
1995
12.6
70.4
8.7
77.1
1996
12
70.9
8.9
77.8
1997
11.6
72.1
8.1
78.5
1998
11.4
73.2
7.3
79
1999
11.2
74.3
6.6
79.6
2000
10.7
75.1
6
79.9
2001
10.7
75.2
6.3
80.3
2002
10.5
75.9
6.7
81.3
2003
10.6
76.2
6.8
81.8
2004
10.5
77
6.3
82.2
2005
10.6
76.9
5.9
81.8
2006
10.9
77.1
5.6
81.7
2007
11.2
78.3
5
82.5
2008
11.3
77.9
5
82
2009
11.3
77
6.4
82.3
2010
11.1
76.7
6.9
82.3
2011
11
76.8
6.4
82
2012
11
77.2
6.1
82.3
2013
10.8
78
5.7
82.7
2014
10.8
77.5
5.6
82
2015
10.7
77
5.7
81.6
2016
10.6
77.6
5.6
82.2
2017
10.3
78.6
5.3
83
2018
10.1
78.9
5
83
Note that your function does not include the variables :consume or :marijuana. However if I add them, everything works.
julia> df.consume = rand(["Consume", "Did not consume"], nrow(df));
julia> df.marijuana = rand(["Marijuana", "None"], nrow(df));
julia> get_stats(df, :consume, :marijuana)
# the correct output
PS. It would be really helpful if you could build your skills in generating DataFrames randomly to produce MWEs. I think it would make getting help a lot easier when people have to only copy and paste a single block of code.
That’s because I used the wrong data set.
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Do you see how I’ve been generating random vectors to create my MWEs though? It would be really helpful if you did what I did above when asking for help.
pdeffebach:
julia> df.consume = rand([“Consume”, “Did not consume”], nrow(df)); julia> df.marijuana = rand([“Marijuana”, “None”], nrow(df)); julia> get_stats(df, :consume, :marijuana)
I think you’re right. The problem is that at this stage I’m getting a bounds error. my dataset is [1,2,3,4,5,6],9] , and I think that’s because 9 is not sequential, not sure if it would would work better with 9 as a :string or NAN, since 9 represents a missing value.
brett_knoss:
I think you’re right. The problem is that at this stage I’m getting a bounds error. my dataset is [1,2,3,4,5,6],9] , and I think that’s because 9 is not sequential, not sure if it would would work better with 9 as a :string or NAN, since 9 represents a missing value.
I don’t understand what you mean by this. I don’t understand what a vector being “sequential” has to do with your problem. I would bet that if you isolated the problem to an MWE you would find that the code works.
Ok, I tried it and it works. I guess what I need to do now is make it work with my spreadsheet.
My goal isn’t to sort random numbers, but to analyze data.
I see. I should not have used df as both the name of the input data frame and the name of the output data frame in my function. I can see how that can result in errors. my apologies for writing sloppy code!
You did the correct thing by naming the input data frame df1 in your function.
