Files | Size | Format | Created | Updated | License | Source |
---|---|---|---|---|---|---|
2 | 0B | csv zip | 6 years ago |
Download files in this dataset
File | Description | Size | Last changed | Download |
---|---|---|---|---|
data | 16MB | csv (16MB) , json (26MB) | ||
datapackage_zip | Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. | 19MB | zip (19MB) |
This is a preview version. There might be more data in the original version.
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 |
Use our data-cli tool designed for data wranglers:
data get https://datahub.io/anuveyatsu/farm-survey-simple
data info anuveyatsu/farm-survey-simple
tree anuveyatsu/farm-survey-simple
# Get a list of dataset's resources
curl -L -s https://datahub.io/anuveyatsu/farm-survey-simple/datapackage.json | grep path
# Get resources
curl -L https://datahub.io/anuveyatsu/farm-survey-simple/r/0.csv
curl -L https://datahub.io/anuveyatsu/farm-survey-simple/r/1.zip
If you are using R here's how to get the data you want quickly loaded:
install.packages("jsonlite", repos="https://cran.rstudio.com/")
library("jsonlite")
json_file <- 'https://datahub.io/anuveyatsu/farm-survey-simple/datapackage.json'
json_data <- fromJSON(paste(readLines(json_file), collapse=""))
# get list of all resources:
print(json_data$resources$name)
# print all tabular data(if exists any)
for(i in 1:length(json_data$resources$datahub$type)){
if(json_data$resources$datahub$type[i]=='derived/csv'){
path_to_file = json_data$resources$path[i]
data <- read.csv(url(path_to_file))
print(data)
}
}
Note: You might need to run the script with root permissions if you are running on Linux machine
Install the Frictionless Data data package library and the pandas itself:
pip install datapackage
pip install pandas
Now you can use the datapackage in the Pandas:
import datapackage
import pandas as pd
data_url = 'https://datahub.io/anuveyatsu/farm-survey-simple/datapackage.json'
# to load Data Package into storage
package = datapackage.Package(data_url)
# to load only tabular data
resources = package.resources
for resource in resources:
if resource.tabular:
data = pd.read_csv(resource.descriptor['path'])
print (data)
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('https://datahub.io/anuveyatsu/farm-survey-simple/datapackage.json')
# print list of all resources:
print(package.resource_names)
# print processed tabular data (if exists any)
for resource in package.resources:
if resource.descriptor['datahub']['type'] == 'derived/csv':
print(resource.read())
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 = 'https://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 list of all resources:
for (const id in dataset.resources) {
console.log(dataset.resources[id]._descriptor.name)
}
// get all tabular data(if exists any)
for (const id in dataset.resources) {
if (dataset.resources[id]._descriptor.format === "csv") {
const file = dataset.resources[id]
// Get a raw stream
const stream = await file.stream()
// entire file as a buffer (be careful with large files!)
const buffer = await file.buffer
// print data
stream.pipe(process.stdout)
}
}
})()