Farm Management Survey- SPSS data set

anuveyatsu

Files Size Format Created Updated License Source
2 105MB csv zip 2 weeks ago
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Data Files

File Description Size Last changed Download Other formats
data [csv] 16MB data [csv] data [json] (26MB)
datapackage_zip [zip] Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 19MB datapackage_zip [zip]

data  

This is a preview version. There might be more data in the original version.

Field information

Field Name Order Type (Format) Description
UniqueRecord 1 integer
FMSFarm 2 integer
Year 3 integer
WeeklyWage 4 number
API 5 number
CPI 6 number
FPI 7 number
RG 8 number
RG_Eq 9 number
CensusSizeCategories 10 integer
AreaFarmed 11 number
GrassArea 12 number
TotalGrassArea 13 number
TotalCropArea 14 number
Crop_pcent 15 number
Y1wheat 16 number
Y2barley 17 number
Y3oats 18 number
Y4sbeet 19 number
Y5pots 20 number
Y9eggs 21 integer
Y10milk 22 integer
MilkYield_acre 23 number
MilkYield_100Conc 24 number
MilkYield_100Conc_MA3 25 number
O2cereal 26 integer
O3othcr 27 integer
O4hortic 28 integer
O5cattle 29 integer
O6sheep 30 integer
O7pigs 31 integer
O8poultry 32 integer
O9dairy 33 integer
Enterprises 34 integer
P5cattle 35 integer
P6sheep 36 integer
P7pigs 37 integer
P8poultry 38 integer
AllPurchases 39 number
WorkHorses 40 integer
TotalOutput 41 integer
GrazingOutput 42 integer
GrazingOutput_acre 43 number
CropOutput 44 integer
CropOutput_acre 45 number
CerealOutput_100_Fert 46 number
OtherCrop_100_TotalOutput 47 number
CropOutput86 48 number
CropOutput86_acre 49 number
AnimalOutput 50 integer
AniOutput_100_Conc 51 number
AniOutput_100_Conc_MA3 52 number
MaxOutput 53 integer
TotalNetOutput 54 integer
Cattle_DairyNetOutput 55 integer
SheepNetOutput 56 integer
GrazingNetOutput 57 number
GrazingNetOutput_acre 58 number
PigsNetOutput 59 integer
PoultryNetOutput 60 integer
NetAnimalOutput 61 number
NetAniOutput_100_Conc 62 number
NetAniOutput_100_Conc_MA3 63 number
MaxNetOutput 64 integer
GrazingOutput86 65 number
GrazingOutput86_acre 66 number
GrazingNetOutput86 67 number
GrazingNetOutput86_acre 68 number
AbsLab 69 integer
I9lab 70 integer
I1ferts 71 integer
I2pests 72 integer
I3miscc 73 integer
I4seed 74 integer
I5Conc 75 integer
I6vet 76 integer
I7lscosts 77 integer
I8rent 78 integer
I10mach_costs 79 integer
I11bldng 80 integer
I12drain 81 integer
I13misc 82 integer
AverageK 83 integer
TotalCosts 84 integer
TotalCosts_incl_lvstkpurch 85 integer
TotalCosts86 86 integer
TotalCosts_incl_lvstkpurch86 87 integer
IFSgross 88 number
IFSnet 89 number
GrossOutput_100_input 90 number
GrossOutput_100_labour 91 number
GrossOutput_100_capital 92 number
NetOutput_100_input 93 number
NetOutput_100_labour 94 number
NetOutput_100_capital 95 number
Fert_Pest_Ratio 96 number
InputLabourRatio 97 number
LabCosts86 98 number
LabCosts_acre86 99 number
WeeksOFLabour 100 number
FTE_est 101 number
FTE_est_acre 102 number
C2bldnginv 103 integer
Investment 104 string
CapitalGrant 105 integer
Capital_Grant_Purpose 106 string
C1m_cbought 107 integer
Machbought 108 string
Machinery_Grant 109 integer
Machinery_Grant_Purpose 110 string
GovtGrants 111 integer
Grant_Ploughing 112 integer
Grant_Calf 113 integer
Grant_Capitation_Bonus 114 integer
Grant_Beefcow 115 integer
Grant_HillCattle 116 integer
Grant_HillCowSubsidy 117 integer
Grant_SCP 118 integer
Grant_BCBIS 119 integer
Grant_EwePrem 120 integer
Grant_HillSheep 121 integer
Grant_Boar 122 integer
Grant_Drainage 123 integer
Grant_Fertiliser 124 integer
Grant_Petrol 125 integer
Grant_Manure 126 integer
Grant_Cottage 127 integer
Grant_Water_Supply 128 integer
Grant_Guidance 129 integer
Grant_othCrops 130 integer
Grant_Other_grant 131 integer
Grant_Other_Text 132 string
FarmersAge 133 integer
Tenure 134 integer
NameChange 135 integer
FarmType 136 number
SoilType 137 string
AltitudeMin 138 integer
AltitudeMax 139 integer
DistrictType 140 number
GridReference 141 string
SignficantComments 142 string
BreedComments 143 string
Dummy_cattle 144 integer
Dummy_sheep 145 integer
Dummy_pigs 146 integer
Dummy_poultry 147 integer
Dummy_dairy 148 integer
Dummy_Cereals 149 integer
Dummy_othercrops 150 integer
Dummy_workhorses 151 integer
Dummy_Electricity 152 integer
Years1950_1969 153 integer
Years1970on 154 integer
YearsBefore1950 155 integer
SampleYearAreaMean 156 number
SampleYearAreaMedian 157 number
FarmSize_vs_SampleMean 158 integer
FarmSize_vs_SampleMedian 159 integer
Dif_Farmarea_SampleMean 160 number
Dif_Farmarea_SampleMedian 161 number
Pc_dif_Farmarea_SampleMean 162 number
Pc_dif_Farmarea_SampleMedian 163 number
AbsChangeOfFarmSize 164 number
CategorizingChangeMean 165 number
CategorizingChangeMedian 166 number
RelPeriodChange 167 number
CatPeriodChange 168 integer
N_Used_units 169 number
N_Used_units_ac 170 number
Nused_units_ac_MA2 171 number
Nused_units_ac_MA3 172 number
N_Used_kg_ha 173 number
Nused_kg_ha_MA2 174 number
Nused_kg_ha_MA3 175 number
Conc_ac 176 number
Conc_lbs 177 number
FertCosts86 178 number
ConcCosts86 179 number
PropO2cereals_TO 180 number
PropO3othcr_TO 181 number
PropO4hortic_TO 182 number
PropO5cattle_TO 183 number
PropO6sheep_TO 184 number
PropO7pigs_TO 185 number
PropO8poultry_TO 186 number
PropO9dairy_TO 187 number
PropO2cereals_MO 188 number
PropO3othcr_MO 189 number
PropO4hortic_MO 190 number
PropO5cattle_MO 191 number
PropO6sheep_MO 192 number
PropO7pigs_MO 193 number
PropO8poultry_MO 194 number
PropO9dairy_MO 195 number
silage_equip 196 integer
silage_value 197 integer
milking_equip 198 integer
milking_equip_value 199 integer
dairy_buildings1 200 integer
dairy_buildings1_value 201 integer
dairy_buildings2 202 integer
dairy_buildings2_value 203 integer
Hay_equip 204 integer
Hay_equip_value 205 integer
Baler 206 integer
Baler_value 207 integer
Tractor 208 integer
Tractor_value 209 integer
Combine_harvester 210 integer
Combine_harvester_value 211 integer
Bulk_tank 212 integer
Bulk_tank_value 213 integer
MDE 214 integer
MDE_value 215 integer

datapackage_zip  

This is a preview version. There might be more data in the original version.

Read me

Import into your tool

If you are using R here's how to get the data you want quickly loaded:

install.packages("jsonlite")
library("jsonlite")

json_file <- "http://datahub.io/anuveyatsu/farm-survey-simple/datapackage.json"
json_data <- fromJSON(paste(readLines(json_file), collapse=""))

# access csv file by the index starting from 1
path_to_file = json_data$resources[[1]]$path
data <- read.csv(url(path_to_file))
print(data)

In order to work with Data Packages in Pandas you need to install the Frictionless Data data package library and the pandas extension:

pip install datapackage
pip install jsontableschema-pandas

To get the data run following code:

import datapackage

data_url = "http://datahub.io/anuveyatsu/farm-survey-simple/datapackage.json"

# to load Data Package into storage
storage = datapackage.push_datapackage(data_url, 'pandas')

# data frames available (corresponding to data files in original dataset)
storage.buckets

# you can access datasets inside storage, e.g. the first one:
storage[storage.buckets[0]]

For Python, first install the `datapackage` library (all the datasets on DataHub are Data Packages):

pip install datapackage

To get Data Package into your Python environment, run following code:

from datapackage import Package

package = Package('http://datahub.io/anuveyatsu/farm-survey-simple/datapackage.json')

# get list of resources:
resources = package.descriptor['resources']
resourceList = [resources[x]['name'] for x in range(0, len(resources))]
print(resourceList)

data = package.resources[0].read()
print(data)

If you are using JavaScript, please, follow instructions below:

Install data.js module using npm:

  $ npm install data.js

Once the package is installed, use the following code snippet:

const {Dataset} = require('data.js')

const path = 'http://datahub.io/anuveyatsu/farm-survey-simple/datapackage.json'

// We're using self-invoking function here as we want to use async-await syntax:
(async () => {
  const dataset = await Dataset.load(path)

  // Get the first data file in this dataset
  const file = dataset.resources[0]
  // Get a raw stream
  const stream = await file.stream()
  // entire file as a buffer (be careful with large files!)
  const buffer = await file.buffer
})()

Install the datapackage library created specially for Ruby language using gem:

gem install datapackage

Now get the dataset and read the data:

require 'datapackage'

path = 'http://datahub.io/anuveyatsu/farm-survey-simple/datapackage.json'

package = DataPackage::Package.new(path)
# So package variable contains metadata. You can see it:
puts package

# Read data itself:
resource = package.resources[0]
data = resource.read
puts data
Datapackage.json