Help for package PSLM2015

Type:

Package

Title:

Pakistan Social and Living Standards Measurement Survey 2014-15

Version:

0.2.0

Maintainer:

Muhammad Yaseen <myaseen208@gmail.com>

Description:

Data and statistics of Pakistan Social and Living Standards Measurement (PSLM) survey 2014-15 from Pakistan Bureau of Statistics (http://www.pbs.gov.pk/).

URL:

https://github.com/MYaseen208/PSLM2015

Imports:

magrittr , dplyr , ggplot2

Depends:

R(≥ 2.10.0)

License:

GPL-2

Encoding:

UTF-8

LazyData:

true

RoxygenNote:

6.0.1

NeedsCompilation:

Packaged:

2017-12-06 15:34:47 UTC; yaseen

Author:

Muhammad Yaseen [aut, cre], Muhammad Arfan Dilber [ctb]

Repository:

CRAN

Date/Publication:

2017-12-06 15:44:55 UTC

Agriculture data from Pakistan Social and Living Standard Measures 2015

Description

Agriculture data from Pakistan Social and Living Standard Measures 2015.

Usage

data(Agriculture)

Format

A data.table and data.frame with 3324 observations of 97 variables.

hhcode: Household 10 digits code.
Province: Province of Pakistan
Region: Region of Pakistan (Rural/Urban)
PSU: primary sampling unit 8 digits code
a101: Own Land Status (Yes/No)
a102: Owned Land (Acres)
a103: Rent Out Land Status (Yes/No)
a104: Rented Out Land (Acres)
a105: Rent Received (Rs)
a106: Rented Land Status(Yes/No)
a107: Rent Paid (Rs)
a108a: Amount Received by Sold Agriculture Land (Rs.)
a108b: Value of land Received by Gift/Inheritence (Rs.)
a108c: Amount Paid for Purchasing Agriculture Land (Rs.)
a108d: Value of land Given-away/Lost (Rs.)
a109a: Owned operational land (Acres)
a109b: Rented operational land (Acres)
a109c: Share crops basis operational land (Acres)
a109d: Any other basis operational land (Acres)
a110: Total operational land (Acres)
a111a: Irrigated operational cultivated land (Acres)
a111b: Non-irrigated operational cultivated land (Acres)
a111c: Uncultivated land (Acres)
a112: Total cultivated land (Acres)
a113: Cost of owned land improvements (Rs.)
a114: Cost of improvements of other than land (Rs.)
a121a: Wheat harvested per kg
a121b: Wheat harvested per 40 kg
a121c: Value of total Wheat production (Rs.)
a121d: Value of wheat given to landlord (Rs.)
a121e: Value of wheat kept by the household (Rs.)
a122a: Cotton harvested per kg
a122b: Cotton harvested per 40 kg
a122c: Value of total Cotton production (Rs.)
a122d: Value of cotton given to landlord (Rs.)
a122e: Value of cotton kept by the household (Rs.)
a123a: Sugarcane harvested per kg
a123b: Sugarcane harvested per 40 kg
a123c: Value of total sugarcane production (Rs.)
a123d: Value of sugarcane given to landlord (Rs.)
a123e: Value of sugarcane kept by the household (Rs.)
a124a: Rice harvested per kg
a124b: Rice harvested per 40 kg
a124c: Value of total rice production (Rs.)
a124d: Value of rice given to landlord (Rs.)
a124e: Value of rice kept by the household (Rs.)
a125a: Maize harvested per kg
a125b: Maize harvested per 40 kg
a125c: Value of total maize production (Rs.)
a125d: Value of maize given to landlord (Rs.)
a125e: Value of maize kept by the household (Rs.)
a126a: Pulses harvested per kg
a126b: Pulses harvested per 40 kg
a126c: Value of total pulses production (Rs.)
a126d: Value of pulses given to landlord (Rs.)
a126e: Value of pulses kept by the household (Rs.)
a127a: Fruit harvested per kg
a127b: Fruit harvested per 40 kg
a127c: Value of total fruit production (Rs.)
a127d: Value of fruit given to landlord (Rs.)
a127e: Value of fruit kept by the household (Rs.)
a128a: Vegetables harvested per kg
a128b: Vegetables harvested per 40 kg
a128c: Value of total vegetables production (Rs.)
a128d: Value of vegetables given to landlord (Rs.)
a128e: Value of vegetables kept by the household (Rs.)
a129a: Fodder harvested per kg
a129b: Fodder harvested per 40 kg
a129c: Value of total fodder production (Rs.)
a129d: Value of fodder given to landlord (Rs.)
a129e: Value of fodder kept by the household (Rs.)
a130a: Other crop harvested per kg
a130b: Other crop harvested per 40 kg
a130c: Value of total other crop production (Rs.)
a130d: Value of other crop given to landlord (Rs.)
a130e: Value of other crop kept by the household (Rs.)
a131a: Bi-products crops harvested per kg
a131b: Bi-products crops harvested per 40 kg
a131c: Value of total bi-product crop production (Rs.)
a131d: Value of bi-product crop given to landlord (Rs.)
a131e: Value of bi-product crop kept by the household (Rs.)
a135c: Total crops harvested per kg
a135d: Total crops harvested per 40 kg
a135e: Value of total crops production (Rs.)
a135f: Value of total crops given to landlord (Rs.)
a135g: Value of total crops kept by the household (Rs.)
a136: Cost on seeds/plants (Rs.)
a137: Cost on fertilizer (Rs.)
a138: Cost on persticides (Rs.)
a139: Cost on water/electricity/fuel (Rs.)
a140: All types of taxes paid (Rs.)
a141: Freight/transportation/commission/insurance/storage charges (Rs.)
a142: Permanent labour charges (Rs.)
a143: Casual labour charges (Rs.)
a144: Rent of equipment/animal charges (Rs.)
a145: Other expenses (Rs.)
a150: Total expenses (Rs.)

Author(s)

Muhammad Yaseen (myaseen208@gmail.com)
Muhammad Arfan Dilber (pbsfsd041@gmail.com)

References

Pakistan Bureau of Statistics, Micro data (http://www.pbs.gov.pk/content/microdata).

Examples

 # library(PSLM2015)
 # data("Agriculture")
 # library(dplyr)
 # Agriculture %>%
 #   group_by(Province, Region) %>%
 #   summarise(TotalOperationalLand = sum(a110, na.rm = TRUE))
 # library(ggplot2)
 # ggplot(data = Agriculture, mapping = aes(x = Province, y = a110)) + 
 #   geom_col() +
 #   labs(y = "Total Operational Land") +
 #   facet_grid(. ~ Region)
 # 
 #   # Merging two data files
 #   data("Employment")
 #   data("Agriculture")
 #    ab <- Employment %>% 
 #    filter(s1bq06 %in% 
 #    c("Own cultivator","Share cropper", "Contract cultivator")
 #    |s1bq14 %in% c("Own cultivator","Share cropper", "Contract cultivator"))
 #   
 #   EmpAgri <- ab %>% left_join(Agriculture, by = c("hhcode", "Province", "Region", "PSU"))
 #   str(EmpAgri)

Education data from Pakistan Social and Living Standards Measurement 2015-16

Description

Education data from Pakistan Social and Living Standards Measurement 2015-16.

Usage

data(Education)

Format

A data.table and data.frame with 141828 observations of 22 variables.

hhcode: Household 10 digits code.
Province: Province of Pakistan
Region: Region of Pakistan (Rural/Urban)
PSU: primary sampling unit 8 digits code
idc: Identity code of household member
s2ac01: Can read with understanding
s2ac02: Can Write with understanding
s2ac03: Can solve arithmatic questions
s2ac04: Attended any educational institution
s2ac05: Highest level of education passed
s2ac06: Currently attending educational institution
s2ac07: Currently studying class
s2ac08: Type of currently attending institution
s2ac9a: Last year expenditure on school Fees/Admission/Registration/Funds/Donations?
s2ac9b: Last year expenditure on school Uniform?
s2ac9c: Last year expenditure on school Books/stationery items?
s2ac9d: Last year expenditure on school Examination Fee?
s2ac9e: Last year expenditure on Private Tuition?
s2ac9f: Last year expenditure on school transportation?
s2ac9g: Last year expenditure on school hostel expenses?
s2ac9h: Last year expenditure on school other expenses?
s2ac9i: Total expenditure on schooling

Author(s)

Muhammad Yaseen (myaseen208@gmail.com)
Muhammad Arfan Dilber (pbsfsd041@gmail.com)

References

Pakistan Bureau of Statistics, Micro data (http://www.pbs.gov.pk/content/microdata).

Examples

 # library(PSLM2015)
 # library(dplyr)
 # data("Education")
 # TotalP <- Education %>% group_by(Province, Region) %>%
 #   summarise(TotalPersons = n())
 #   
 # literacy <- Education %>% filter(s2ac01 == "yes" & s2ac02 == "yes" & s2ac03 == "yes")
 #   literateP <- literacy %>%
 #   group_by(Province, Region) %>%
 #   summarise(literatePersons = n())
 #   literacyR <- TotalP %>% left_join(literateP, by = c("Province", "Region"))
 #   literacyRate <- mutate(literacyR, Rate = literatePersons/TotalPersons*100)
 # library(ggplot2)
 # ggplot(data = literacyRate, mapping = aes(x = Province, y = Rate)) +
 #   geom_col() +
 #   facet_grid(. ~ Region)
 # 
 # # Merging two data files
 # 
 #   data("Employment")
 #   data("Education")
 #   income <- Employment %>% rowwise() %>%
 #     mutate(TotalIncome = sum((s1bq08*s1bq09),s1bq10,s1bq15,s1bq17,s1bq19,s1bq21, na.rm = TRUE))
 #   ab <- income %>% select(hhcode, idc, TotalIncome)
 #   EduEmp <- Education %>% left_join(ab, by = c("hhcode", "idc"))
 #   str(EduEmp)

Employment and income data from Pakistan Social and Living Standards Measurement 2015-16

Description

Employment and income data from Pakistan Social and Living Standards Measurement 2015-16.

Usage

data(Employment)

Format

A data.table and data.frame with 115910 observations of 27 variables.

hhcode: Household 10 digits code.
Province: Province of Pakistan
Region: Region of Pakistan (Rural/Urban)
PSU: primary sampling unit 8 digits code
idc: Identity code of household member
s1bq01: Last month working status
s1bq02: Number of worked days in last month
s1bq03: Employment/business/economic activity status
s1bq04: Occupation
s1bq05: Industry
s1bq06: Type of economic activity
s1bq07: Income reporting (Monthly/Anually)
s1bq08: Last month cash income (Rs.)
s1bq09: Number of months worked in last year
s1bq10: Last year cash income (Rs.)
s1bq11: Part time working status
s1bq12: Part time occupation
s1bq13: Part time working industry
s1bq14: Part time economic activity type
s1bq15: Last year part time cash income (Rs.)
s1bq16: Any other work done for pay/profit in last year (Yes/No)
s1bq17: Last year cash income from other work (Rs.)
s1bq18: Sold status of in kind wages (Yes/No)
s1bq19: Last year income by selling in-kind wages (Rs.)
s1bq20: Pension or other financial benefits in last year (Yes/No)
s1bq21: Last year income from pension/other financial benefits (Rs.)
s1bq22: Income used to pay expences of household (Rs.)

Author(s)

Muhammad Yaseen (myaseen208@gmail.com)
Muhammad Arfan Dilber (pbsfsd041@gmail.com)

References

Pakistan Bureau of Statistics, Micro data (http://www.pbs.gov.pk/content/microdata).

Examples

 # library(PSLM2015)
 # data("Employment")
 # library(dplyr)
 # x2<- distinct(Employment, hhcode, .keep_all = TRUE)
 # TotalHH<- x2 %>% group_by(Province, Region) %>%
 #   summarise(TotalHH = n())
 # income<- Employment %>% rowwise() %>%
 #   mutate(TotalIncome = sum((s1bq08*s1bq09),s1bq10,s1bq15,s1bq17,s1bq19,s1bq21, na.rm = TRUE))
 # IncomeR <- income %>%
 #   group_by(Province, Region) %>%
 #   summarise(TotalIncome = sum(as.numeric(TotalIncome)))
 # IncomeR2 <- TotalHH %>% left_join(IncomeR, by = c("Province", "Region"))
 # IncomeRate <- IncomeR2 %>% mutate(AverageHHIncome = TotalIncome/TotalHH)
 # 
 # library(ggplot2)
 # ggplot(data = IncomeRate, mapping = aes(x = Province, y = AverageHHIncome)) +
 #   geom_col() +
 #   facet_grid(. ~ Region)
 # 
 # # Merging two data files
 # 
 #   data("Employment")
 #   data("Education")
 #   income <- Employment %>% rowwise() %>%
 #     mutate(TotalIncome = sum((s1bq08*s1bq09),s1bq10,s1bq15,s1bq17,s1bq19,s1bq21, na.rm = TRUE))
 # ab <- select(income, hhcode, idc, TotalIncome)
 # EduEmp<-Education %>% left_join(ab, by = c("hhcode", "idc"))
 # str(EduEmp)

Household's total expenditure data from Pakistan Social and Living Standards Measurement 2015-16

Description

Expenditure data from Pakistan Social and Living Standards Measurement 2015-16.

Usage

data(Expenditure)

Format

A data.table and data.frame with 24238 observation of 14 variables.

hhcode: Household 10 digits code.
Food: Food and non-alcoholic beverages
Hotels: Restaurants and hotels
Furnishing: Furnishing, Household equipment and routine maintenance of the house
Misc: Miscellaneous goods and services
Tobacco: Alcoholic beverages and tobacco
Housing: Housing, Water, Electricity, Gas and other fuels
Clothing: Clothing and Foot wear
Health: Health
Transport: Transport
Communication: Communication, Postal services
Recreation: Recreation and Culture
Education: Education
DurableGoods: Durable Goods
NonDurable: Total expenditure on non-durable goods

Author(s)

Muhammad Yaseen (myaseen208@gmail.com)
Muhammad Arfan Dilber (pbsfsd041@gmail.com)

References

Pakistan Bureau of Statistics, Micro data (http://www.pbs.gov.pk/content/microdata).

Examples

 # library(PSLM2015)
 # data("Expenditure")
 # data("Employment")
 # library(dplyr)
 # income<- Employment %>% rowwise() %>%
 #   mutate(TotalIncome = sum((s1bq08*s1bq09), 
 #    s1bq10, s1bq15, s1bq17, s1bq19, s1bq21
 #    , na.rm = TRUE))
 # exp<-Expenditure %>% select(c("hhcode","NonDurable"))
 # HHIncome<-income %>% group_by(hhcode) %>% 
 # summarise(HHAvgIncome = sum(TotalIncome))
 # IncomeExp<-HHIncome %>% left_join(exp, by = "hhcode")

HouseHold roster data from Pakistan Social and Living Standards Measurement 2015-16

Description

HHRoster data from Pakistan Social and Living Standards Measurement 2015-16.

Usage

data(HHRoster)

Format

A data.table and data.frame with 157775 observations of 18 variables.

hhcode: Household 10 digits code.
Province: Province of Pakistan
Region: Region of Pakistan (Rural/Urban)
PSU: primary sampling unit 8 digits code
idc: Identity code of household member
s1aq02: Relationship with the head of household
s1aq03: Reason of considering household head
s1aq04: Gender of a person
s1aq05: Residential status
age: Age in complete years
s1aq61: Day of birth
s1aq62: Month of birth
s1aq63: Year of birth
s1aq07: Marital status of a person
s1aq08: Identity code of his/her spouse
s1aq09: Identity code of person's father
s1aq10: Identity code of person's mother
s1aq11: Member of household (Yes/No)

Author(s)

Muhammad Yaseen (myaseen208@gmail.com)
Muhammad Arfan Dilber (pbsfsd041@gmail.com)

References

Pakistan Bureau of Statistics, Micro data (http://www.pbs.gov.pk/content/microdata).

Examples

 # library(PSLM2015)
 # data("HHRoster")
 # library(dplyr)
 # SumHH <- HHRoster %>%
 #   group_by(Province, Region, s1aq04) %>%
 #   summarise(Count = n())
 # 
 # library(ggplot2)
 # ggplot(data = SumHH , mapping = aes(x = s1aq04, y = Count)) +
 #   geom_col() +
 #   facet_grid(. ~ Region)

Housing data from Pakistan Social and Living Standards Measurement 2015-16

Description

Housing data from Pakistan Social and Living Standards Measurement 2015-16.

Usage

data(Housing)

Format

A data.table and data.frame with 24238 observations of 36 variables.

hhcode: Household 10 digits code.
Province: Province of Pakistan
Region: Region of Pakistan (Rural/Urban)
PSU: primary sampling unit 8 digits code
S3aq01: Dwelling type
S3aq02: Occupancy status
S3aq03: Estimated rent of the house (Rs.)
S3aq04: Number of rooms in household
S3aq05A: Electricity facility
S3aq05B: Gas facility
S3aq06: Source of drinking water
S3aq07: Water availability (hours)
S3aq08: Water system installed by
S3aq09: Water system look-after by
S3aq10: Distance of source of drinking water (Km.)
S3aq11: Time consumption in fetching drinking water (Minutes)
S3aq12: Water payment status (Yes/No)
S3aq13: One month payment for water (Rs.)
S3aq14: Willingness to improve water supply system (Yes/No)
S3aq15: Toilet used by household
S3aq16: Defecation/urination place
S3aq17: Is your house connected with drainage/swerage system?
S3aq18A: Garbage collected by
S3aq18B: Garbage collected in neighbourhod by
S3aq19A: Monthly expenditure on household's garbage collection
S3aq19B: Monthly expenditure on neighbourhood's garbage collection
S3aq20A: Internet facility in household (Yes/No)
S3aq20B: Broad band facility in household (Yes/No)
S3aq20C: Mobile facility in household (Yes/No)
S3aq20D: Landline facility in household (Yes/No)
S3aq20E: Desktop computer facility in household (Yes/No)
S3aq20F: Laptop facility in household (Yes/No)
S3aq20G: Tablet facility in household (Yes/No)
S3aq20H: I-pad facility in household (Yes/No)
S3aq21A: Type of internet services
S3aq21B: Type of internet services for broadband

Author(s)

Muhammad Yaseen (myaseen208@gmail.com)
Muhammad Arfan Dilber (pbsfsd041@gmail.com)

References

Pakistan Bureau of Statistics, Micro data (http://www.pbs.gov.pk/content/microdata).

Examples

 # library(PSLM2015)
 # data("Housing")
 # library(dplyr)
 # AvgRooms <- Housing %>%
 #   group_by(Province, Region) %>%
 #   summarise(AvgRooms = mean(S3aq04, na.rm = TRUE))
 # 
 # library(ggplot2)
 # ggplot(data = AvgRooms , mapping = aes(x = Province, y = AvgRooms)) +
 #   geom_col() +
 #   facet_grid(. ~ Region)
 # 
 # # Merging two data files
 # 
 #   data("Employment")
 #   data("Housing")
 #   HeadHH <- HHRoster %>% filter(s1aq02 == "Head")
 #   EmpHous <- HeadHH %>% left_join(Housing, by = c("hhcode"))
 #   str(EmpHous)

Information and communication technology data from Pakistan Social and Living Standard Measures 2015

Description

ICT data from Pakistan Social and Living Standard Measures 2015.

Usage

data(ICT)

Format

A data.table and data.frame with 115910 observations of 28 variables.

hhcode: Household 10 digits code.
Province: Province of Pakistan
Region: Region of Pakistan (Rural/Urban)
PSU: primary sampling unit 8 digits code
idc: Identification code
sictq01: Computer using in last month (Yes/No)
sictq0201: Computer related 1st activity
sictq0202: Computer related 2nd activity
sictq0203: Computer related 3rd activity
sictq0204: Computer related 4th activity
sictq0205: Computer related 5th activity
sictq0206: Computer related 6th activity
sictq03: Mobile using in last month (Yes/No)
sictq04: Internet Using in last month (Yes/No)
sictq05: Internet used in last three months
sictq06: Internet using in last year (Yes/No)
sictq0701: Internet using of 1st location
sictq0702: Internet using of 2nd location
sictq0703: Internet using of 3rd location
sictq0704: Internet using of 4th location
sictq0705: Internet using of 5th location
sictq0706: Internet using of 6th location
sictq0801: Private purpose internet using activity 1
sictq0802: Private purpose internet using activity 2
sictq0803: Private purpose internet using activity 3
sictq0804: Private purpose internet using activity 4
sictq0805: Private purpose internet using activity 5
sictq0806: Private purpose internet using activity 6

Author(s)

Muhammad Yaseen (myaseen208@gmail.com)
Muhammad Arfan Dilber (pbsfsd041@gmail.com)

References

Pakistan Bureau of Statistics, Micro data (http://www.pbs.gov.pk/content/microdata).

Examples

 # library(PSLM2015)
 # data("ICT")
 # library(dplyr)
 # TechRate<- ICT %>%
 #   group_by(Province, sictq01) %>%
 #   summarise(Count = n())
 # 
 # library(ggplot2)
 # ggplot(data = TechRate, mapping = aes(x = Province, y = Count)) +
 #   geom_col() + labs(colour = "Cylinders") +
 #   facet_grid(. ~ sictq01)

LiveStock data from Pakistan Social and Living Standard Measures 2015

Description

LiveStock data from Pakistan Social and Living Standard Measures 2015.

Usage

data(LiveStock)

Format

A data.table and data.frame with 3771 observations of 116 variables.

hhcode: Household 10 digits code.
Province: Province of Pakistan
Region: Region of Pakistan (Rural/Urban)
PSU: primary sampling unit 8 digits code
S7bc1.151: Cattle's present value (Rs.)
S7bc2.151: Cattle's last year value (Rs.)
S7bc3.151: Cattle's value sold in last year (Rs.)
S7bc4.151: Cattle's value received as gift/inheritance (Rs.)
S7bc5.151: Cattle's paiment, purchased in last year (Rs.)
S7bc6.151: Given away/lost cattle's value (Rs.)
S7bc1.152: Buffalo's present value (Rs.)
S7bc2.152: Buffalo's last year value (Rs.)
S7bc3.152: Buffalo's value sold in last year (Rs.)
S7bc4.152: Buffalo's value received as gift/inheritance (Rs.)
S7bc5.152: Buffalo's paiment, purchased in last year (Rs.)
S7bc6.152: Given away/lost Buffalo's value (Rs.)
S7bc1.153: Camel's present value (Rs.)
S7bc2.153: Camel's last year value (Rs.)
S7bc3.153: Camel's value sold in last year (Rs.)
S7bc4.153: Camel's value received as gift/inheritance (Rs.)
S7bc5.153: Camel's paiment, purchased in last year (Rs.)
S7bc6.153: Given away/lost camel's value (Rs.)
S7bc1.154: Sheep's present value (Rs.)
S7bc2.154: Sheep's last year value (Rs.)
S7bc3.154: Sheep's value sold in last year (Rs.)
S7bc4.154: Sheep's value received as gift/inheritance (Rs.)
S7bc5.154: Sheep's paiment, purchased in last year (Rs.)
S7bc6.154: Given away/lost sheep's value (Rs.)
S7bc1.155: Goat's present value (Rs.)
S7bc2.155: Goat's last year value (Rs.)
S7bc3.155: Goat's value sold in last year (Rs.)
S7bc4.155: Goat's value received as gift/inheritance (Rs.)
S7bc5.155: Goat's paiment, purchased in last year (Rs.)
S7bc6.155: Given away/lost goat's value (Rs.)
S7bc1.156: Horse's present value (Rs.)
S7bc2.156: Horse's last year value (Rs.)
S7bc3.156: Horse's value sold in last year (Rs.)
S7bc4.156: Horse's value received as gift/inheritance (Rs.)
S7bc5.156: Horse's paiment, purchased in last year (Rs.)
S7bc6.156: Given away/lost horse's value (Rs.)
S7bc1.157: Asse's present value (Rs.)
S7bc2.157: Asse's last year value (Rs.)
S7bc3.157: Asse's value sold in last year (Rs.)
S7bc4.157: Asse's value received as gift/inheritance (Rs.)
S7bc5.157: Asse's paiment, purchased in last year (Rs.)
S7bc6.157: Given away/lost asse's value (Rs.)
S7bc1.158: Mule's present value (Rs.)
S7bc2.158: Mule's last year value (Rs.)
S7bc3.158: Mule's value sold in last year (Rs.)
S7bc4.158: Mule's value received as gift/inheritance (Rs.)
S7bc5.158: Mule's paiment, purchased in last year (Rs.)
S7bc6.158: Given away/lost mule's value (Rs.)
S7bc1.159: Poultry's present value (Rs.)
S7bc2.159: Poultry's last year value (Rs.)
S7bc3.159: Poultry's value sold in last year (Rs.)
S7bc4.159: Poultry's value received as gift/inheritance (Rs.)
S7bc5.159: Poultry's paiment, purchased in last year (Rs.)
S7bc6.159: Given away/lost poultry's value (Rs.)
S7bc1.160: Other animal's present value (Rs.)
S7bc2.160: Other animal's last year value (Rs.)
S7bc3.160: Other animal's value sold in last year (Rs.)
S7bc4.160: Other animal's value received as gift/inheritance (Rs.)
S7bc5.160: Other animal's paiment, purchased in last year (Rs.)
S7bc6.160: Given away/lost other animal's value (Rs.)
S7bc1.165: Total animal's present value (Rs.)
S7bc2.165: Total animal's last year value (Rs.)
S7bc3.165: Total animal's value sold in last year (Rs.)
S7bc4.165: Total animal's value received as gift/inheritance (Rs.)
S7bc5.165: Total animal's paiment, purchased in last year (Rs.)
S7bc6.165: Total given out/lost animal's value (Rs.)
S7bc1.166: Monthly value of eggs produced (Rs.)
S7bc2.166: No. of months eggs produced (Rs.)
S7bc3.166: Total value of eggs produced (Rs.)
S7bc1.167: Monthly value of milk produced (Rs.)
S7bc2.167: No. of months milk produced (Rs.)
S7bc3.167: Total value of milk produced (Rs.)
S7bc1.168: Monthly value of milk products produced (Rs.)
S7bc2.168: No. of months milk products produced (Rs.)
S7bc3.168: Total value of milk products produced (Rs.)
S7bc3.169: Total value of honey produced (Rs.)
S7bc3.170: Total value of forset products produced (Rs.)
S7bc3.171: Total value of fish catches (Rs.)
S7bc3.172: Total value of dung cakes produced (Rs.)
S7bc3.173: Total value of wool produced (Rs.)
S7bc3.174: Total value of other items produced (Rs.)
S7bc3.175: Total value of all other items produced (Rs.)
S7bc3.180: Total value of all items produced (Rs.)
S7bc1.181: Fodder green purchased (Rs.)
S7bc2.181: Fodder green own produced and consumed (Rs.)
S7bc1.182: Fodder dry purchased (Rs.)
S7bc2.182: Fodder dry own produced and consumed (Rs.)
S7bc1.183: Grazing purchased (Rs.)
S7bc2.183: Grazing own produced and consumed (Rs.)
S7bc1.184: Oil cakes/seed purchased (Rs.)
S7bc2.184: Oil cakes/seed own produced and consumed (Rs.)
S7bc1.185: Poultry feed purchased (Rs.)
S7bc2.185: Poultry feed own produced and consumed (Rs.)
S7bc1.186: fishing purchased (Rs.)
S7bc2.186: fishing own produced and consumed (Rs.)
S7bc1.187: Medicines purchased (Rs.)
S7bc2.187: Medicines own produced and consumed (Rs.)
S7bc1.188: Veterinary charges (Rs.)
S7bc2.188: Veterinary own services charges (Rs.)
S7bc1.189: Labour charges (Rs.)
S7bc2.189: Own labour services charges (Rs.)
S7bc1.190: All other items purchased (Rs.)
S7bc2.190: All other items own produced and consumed (Rs.)
S7bc1.195: Total items purchased (Rs.)
S7bc2.195: Total items own produced and consumed (Rs.)
S7bc1.196: Rent out agricultural equipment status
S7bc1.197: Rent received in an year (Rs.)
S7bc1.198: Sold agricultural equipment value (Rs.)
S7bc2.198: Value of agricultural equipment received as gift/inheritance (Rs.)
S7bc3.198: Paiment of purchased agricultural equipment (Rs.)
S7bc4.198: Value of agricultural equipment given away/lost (Rs.)

Author(s)

Muhammad Yaseen (myaseen208@gmail.com)
Muhammad Arfan Dilber (pbsfsd041@gmail.com)

References

Pakistan Bureau of Statistics, Micro data (http://www.pbs.gov.pk/content/microdata).

Examples

 # library(PSLM2015)
 # data("LiveStock")
 # library(dplyr)
 # TotalValue <- LiveStock %>%
 #   group_by(Province, Region) %>%
 #   summarise(TotalValue = sum(S7bc3.165, na.rm = TRUE))
 # 
 # library(ggplot2)
 # ggplot(data = TotalValue, mapping = aes(x = Province, y = TotalValue)) +
 #  geom_col() +
 #  labs(y = "Total Value of Owned Animals") +
 #   facet_grid(. ~ Region)

Agriculture data from Pakistan Social and Living Standard Measures 2015

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Education data from Pakistan Social and Living Standards Measurement 2015-16

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Employment and income data from Pakistan Social and Living Standards Measurement 2015-16

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Household's total expenditure data from Pakistan Social and Living Standards Measurement 2015-16

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HouseHold roster data from Pakistan Social and Living Standards Measurement 2015-16

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Housing data from Pakistan Social and Living Standards Measurement 2015-16

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Information and communication technology data from Pakistan Social and Living Standard Measures 2015

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LiveStock data from Pakistan Social and Living Standard Measures 2015

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