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Quick fix to get experiments to run #22

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Quick fix to get experiments to run #22

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4 changes: 2 additions & 2 deletions experiments/flights/load_data.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -2,8 +2,8 @@ using CSV
using DataFrames: DataFrame

dataset = "flights"
dirty_table = CSV.File("datasets/$(dataset)_dirty.csv") |> DataFrame
clean_data = CSV.File("datasets/$(dataset)_clean.csv") |> DataFrame
dirty_table = CSV.File("datasets/$(dataset)_dirty.csv", stringtype=String) |> DataFrame
clean_data = CSV.File("datasets/$(dataset)_clean.csv", stringtype=String) |> DataFrame

times_for_flight = Dict{String, Set{String}}("$fl-$field" => Set() for fl in unique(dirty_table.flight) for field in [:sched_dep_time, :sched_arr_time, :act_dep_time, :act_arr_time])
for row in eachrow(dirty_table)
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6 changes: 3 additions & 3 deletions experiments/hospital/load_data.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -2,8 +2,8 @@ using CSV
using DataFrames: DataFrame

dataset = "hospital"
dirty_table = CSV.File("datasets/$(dataset)_dirty.csv") |> DataFrame
clean_table = CSV.File("datasets/$(dataset)_clean.csv") |> DataFrame
dirty_table = CSV.File("datasets/$(dataset)_dirty.csv", stringtype=String) |> DataFrame
clean_table = CSV.File("datasets/$(dataset)_clean.csv", stringtype=String) |> DataFrame

# In the dirty data, CSV.jl infers that PhoneNumber, ZipCode, and ProviderNumber
# are strings. Our PClean script also models these columns as string-valued.
Expand All @@ -16,4 +16,4 @@ clean_table[!, :ProviderNumber] = map(x -> "$x", clean_table[!, :ProviderNumber]

# Stores sets of unique observed values of each attribute.
possibilities = Dict(col => remove_missing(unique(collect(dirty_table[!, col])))
for col in propertynames(dirty_table))
for col in propertynames(dirty_table))
4 changes: 2 additions & 2 deletions experiments/rents/load_data.jl
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Expand Up @@ -3,8 +3,8 @@ using DataFrames: DataFrame

# Load data
dataset = "rents"
dirty_table = CSV.File("datasets/$(dataset)_dirty.csv") |> DataFrame
clean_table = CSV.File("datasets/$(dataset)_clean.csv") |> DataFrame
dirty_table = CSV.File("datasets/$(dataset)_dirty.csv", stringtype=String) |> DataFrame
clean_table = CSV.File("datasets/$(dataset)_clean.csv", stringtype=String) |> DataFrame

dirty_table[!, :CountyKey] = map(x -> "$(x[1])$(split(x)[1][end])", dirty_table[!, :County])

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