\[ İŞSİZLİK -ORANLARI \]
library(WDI)
df = WDI(indicator='SL.UEM.TOTL.ZS', country=c('TR','US'), start=2013, end=2018)
head(df)
## iso2c country SL.UEM.TOTL.ZS year
## 1 TR Turkey 10.89 2018
## 2 TR Turkey 10.82 2017
## 3 TR Turkey 10.84 2016
## 4 TR Turkey 10.24 2015
## 5 TR Turkey 9.88 2014
## 6 TR Turkey 8.73 2013
library(dplyr)
##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
df <- df %>%
rename(ulkekodu = 1,
ulke = 2,
oran = 3,
sene = 4)
library(reshape2)
data_genis <- dcast(df, sene ~ ulke, value.var="oran")
head(data_genis)
## sene Turkey United States
## 1 2013 8.73 7.37
## 2 2014 9.88 6.17
## 3 2015 10.24 5.28
## 4 2016 10.84 4.87
## 5 2017 10.82 4.36
## 6 2018 10.89 3.90
df2 <- WDI(
country = "all",
indicator = "SL.UEM.TOTL.ZS",
start = 2010,
end = 2020,)
WDIsearch("electricity")
## indicator
## [1,] "1.1_ACCESS.ELECTRICITY.TOT"
## [2,] "1.2_ACCESS.ELECTRICITY.RURAL"
## [3,] "1.3_ACCESS.ELECTRICITY.URBAN"
## [4,] "110400"
## [5,] "2.0.cov.Ele"
## [6,] "2.0.hoi.Ele"
## [7,] "4.1.1_TOTAL.ELECTRICITY.OUTPUT"
## [8,] "4.1.2_REN.ELECTRICITY.OUTPUT"
## [9,] "4.1_SHARE.RE.IN.ELECTRICITY"
## [10,] "9060000"
## [11,] "CC.ESG.EUFE"
## [12,] "CC.ESG.EUMA"
## [13,] "CC.GHG.EMSE.EH"
## [14,] "CC.GHG.SDEG.EH"
## [15,] "EG.ELC.ACCS.RU.ZS"
## [16,] "EG.ELC.ACCS.UR.ZS"
## [17,] "EG.ELC.ACCS.ZS"
## [18,] "EG.ELC.COAL.KH"
## [19,] "EG.ELC.COAL.ZS"
## [20,] "EG.ELC.FOSL.ZS"
## [21,] "EG.ELC.HYRO.KH"
## [22,] "EG.ELC.HYRO.ZS"
## [23,] "EG.ELC.NGAS.KH"
## [24,] "EG.ELC.NGAS.ZS"
## [25,] "EG.ELC.NUCL.KH"
## [26,] "EG.ELC.NUCL.ZS"
## [27,] "EG.ELC.PETR.KH"
## [28,] "EG.ELC.PETR.ZS"
## [29,] "EG.ELC.PROD.KH"
## [30,] "EG.ELC.RNEW.KH"
## [31,] "EG.ELC.RNEW.ZS"
## [32,] "EG.ELC.RNWX.KH"
## [33,] "EG.ELC.RNWX.ZS"
## [34,] "EG.TEG.RNEW.ZS"
## [35,] "EG.TEG.VAR.ZS"
## [36,] "EN.CO2.ETOT.MT"
## [37,] "EN.CO2.ETOT.ZS"
## [38,] "EN.PRD.ELEC"
## [39,] "EN.PRD.ELEC.POP.ZS"
## [40,] "HOU.ELC.ACSN.ZS"
## [41,] "IC.CNS.ELEC.ZS"
## [42,] "IC.ELC.ACES.DFRN.DB1015"
## [43,] "IC.ELC.ACES.DFRN.DB1619"
## [44,] "IC.ELC.ACES.RK.DB19"
## [45,] "IC.ELC.ACS.COST"
## [46,] "IC.ELC.ACS.COST.DFRN"
## [47,] "IC.ELC.COMM.TRFF.CG.01.DB1619"
## [48,] "IC.ELC.GEN.ZS"
## [49,] "IC.ELC.LMTG.OUTG.01.DB1619"
## [50,] "IC.ELC.MONT.OUTG.01.DB1619"
## [51,] "IC.ELC.OUTG.FREQ.DURS.03.DB1619"
## [52,] "IC.ELC.OUTG.MN.DB1619"
## [53,] "IC.ELC.PRI.KH.DB1619"
## [54,] "IC.ELC.PROC.NO"
## [55,] "IC.ELC.PROC.NO.DFRN"
## [56,] "IC.ELC.REGU.MONT.01.DB1619"
## [57,] "IC.ELC.RSTOR.01.DB1619"
## [58,] "IC.ELC.RSTT.XD.08.DB1619"
## [59,] "IC.ELC.RSTT.XD.08.DFRN.DB1619"
## [60,] "IC.ELC.SAID.XD.DB1619"
## [61,] "IC.ELC.SAIF.XD.DB1619"
## [62,] "IC.ELC.TIME"
## [63,] "IC.ELC.TIME.DFRN"
## [64,] "IC.ELEC.COST.PC.ZS"
## [65,] "IC.ELEC.PROC"
## [66,] "IC.ELEC.TIME"
## [67,] "IC.ELEC.XQ"
## [68,] "IC.FRM.ELEC.ZS"
## [69,] "IC.FRM.INFRA.IN10_C"
## [70,] "IC.FRM.INFRA.IN12"
## [71,] "IC.FRM.OBS.OBST8"
## [72,] "IN.ENRGY.ELEC.GEN"
## [73,] "NA.GDP.ELEC.GAS.SNA08.CR"
## [74,] "NA.GDP.ELEC.GAS.SNA08.KR"
## [75,] "NV.IND.GELW.CD"
## [76,] "NV.IND.GELW.CN"
## [77,] "NV.IND.GELW.KN"
## [78,] "SE.PRM.INFR.4"
## [79,] "SE.PRM.INFR.4.R"
## [80,] "SE.PRM.INFR.4.U"
## [81,] "SE.PRM.ISTD.7"
## [82,] "SE.PRM.ISTD.8"
## [83,] "SG.COK.ELEC.ZS"
## [84,] "SI.POV.ELEC.MI"
## [85,] "SL.EMP.ELC"
## [86,] "UIS.SCHBSP.1.WELEC"
## [87,] "UIS.SCHBSP.2.WELEC"
## [88,] "UIS.SCHBSP.3.WELEC"
## name
## [1,] "Access to electricity (% of total population)"
## [2,] "Access to electricity (% of rural population)"
## [3,] "Access to electricity (% of urban population)"
## [4,] "110400:HOUSING, WATER, ELECTRICITY, GAS, AND OTHER FUELS"
## [5,] "Coverage: Electricity"
## [6,] "HOI: Electricity"
## [7,] "Total electricity output (GWh)"
## [8,] "Renewable energy electricity output (GWh)"
## [9,] "Renewable electricity (% in total electricity output)"
## [10,] "9060000:ACTUAL HOUSING, WATER, ELECTRICITY, GAS AND OTHER FUELS"
## [11,] "Employment by sector and gender (% of total) - Electricity and utilities - Female"
## [12,] "Employment by sector and gender (% of total) - Electricity and utilities - Male"
## [13,] "Total GHG emissions by sector (Mt CO2 eq) - Electricity/Heat"
## [14,] "Sectoral drivers of GHG emissions growth in the period 2012-2018 - Electricity/Heat (contribution to total growth, %)"
## [15,] "Access to electricity, rural (% of rural population)"
## [16,] "Access to electricity, urban (% of urban population)"
## [17,] "Access to electricity (% of population)"
## [18,] "Electricity production from coal sources (kWh)"
## [19,] "Electricity production from coal sources (% of total)"
## [20,] "Electricity production from oil, gas and coal sources (% of total)"
## [21,] "Electricity production from hydroelectric sources (kWh)"
## [22,] "Electricity production from hydroelectric sources (% of total)"
## [23,] "Electricity production from natural gas sources (kWh)"
## [24,] "Electricity production from natural gas sources (% of total)"
## [25,] "Electricity production from nuclear sources (kWh)"
## [26,] "Electricity production from nuclear sources (% of total)"
## [27,] "Electricity production from oil sources (kWh)"
## [28,] "Electricity production from oil sources (% of total)"
## [29,] "Electricity production (kWh)"
## [30,] "Electricity production from renewable sources (kWh)"
## [31,] "Renewable electricity output (% of total electricity output)"
## [32,] "Electricity production from renewable sources, excluding hydroelectric (kWh)"
## [33,] "Electricity production from renewable sources, excluding hydroelectric (% of total)"
## [34,] "Share of renewables in total electricity generation (%)"
## [35,] "Share of variable renewables in total electricity generation (%)"
## [36,] "CO2 emissions from electricity and heat production, total (million metric tons)"
## [37,] "CO2 emissions from electricity and heat production, total (% of total fuel combustion)"
## [38,] "Electricity production (million kwh)"
## [39,] "Electricity production (kwh per capita)"
## [40,] "Household Access to Electricity: Total (in % of total household)"
## [41,] "Electricity (% of managers surveyed ranking this as a major constraint)"
## [42,] "Getting electricity (DB10-15 methodology) - Score"
## [43,] "Getting electricity (DB16-20 methodology) - Score"
## [44,] "Rank: Getting electricity (1=most business-friendly regulations)"
## [45,] "Getting electricity: Cost to get electricity (% of income per capita)"
## [46,] "Getting electricity: Cost to get electricity (% of income per capita) - Score"
## [47,] "Getting electricity: Communication of tariffs and tariff changes (0-1) (DB16-20 methodology)"
## [48,] "Electricity from Generator (%)"
## [49,] "Getting electricity: Financial deterrents aimed at limiting outages (0-1) (DB16-20 methodology)"
## [50,] "Getting electricity: Mechanisms for monitoring outages (0-1) (DB16-20 methodology)"
## [51,] "Getting electricity: Total duration and frequency of outages per customer a year (0-3) (DB16-20 methodology)"
## [52,] "Getting electricity: Minimum outage time (in minutes) (DB16-20 methodology)"
## [53,] "Getting electricity: Price of electricity (US cents per kWh) (DB16-20 methodology)"
## [54,] "Getting electricity: Procedures (number)"
## [55,] "Getting electricity: Procedures (number) - Score"
## [56,] "Getting electricity: Regulatory monitoring (0-1) (DB16-20 methodology)"
## [57,] "Getting electricity: Mechanisms for restoring service (0-1) (DB16-20 methodology)"
## [58,] "Getting electricity: Reliability of supply and transparency of tariff index (0-8) (DB16-20 methodology)"
## [59,] "Getting electricity: Reliability of supply and transparency of tariff index (0-8) (DB16-20 methodology) - Score"
## [60,] "Getting electricity: System average interruption duration index (SAIDI) (DB16-20 methodology)"
## [61,] "Getting electricity: System average interruption frequency index (SAIFI) (DB16-20 methodology)"
## [62,] "Time required to get electricity (days)"
## [63,] "Getting electricity: Time (days) - Score"
## [64,] "Cost to get electricity connection (% of income per capita)"
## [65,] "Procedures required to get electricity (number)"
## [66,] "Time required to get electricity (days)"
## [67,] "Getting electricity (rank)"
## [68,] "Electricity (% of firms identifying this as a major constraint)"
## [69,] "If a generator is used, average proportion of electricity from a generator (%)"
## [70,] "Percent of firms identifying electricity as a major constraint"
## [71,] "Percent of firms choosing electricity as their biggest obstacle"
## [72,] "Total-Electricity Generated Gross (GWh)"
## [73,] "GDP on Electricity & Gas Supply Sector (in IDR Million), SNA 2008, Current Price"
## [74,] "GDP on Electricity & Gas Supply Sector (in IDR Million), SNA 2008, Constant Price"
## [75,] "Electricity, gas and water supply, value added (current US$)"
## [76,] "Electricity, gas and water supply, value added (current LCU)"
## [77,] "Electricity, gas and water supply, value added (constant LCU)"
## [78,] "(De Facto) Percent of schools with access to electricity"
## [79,] "(De Facto) Percent of schools with access to electricity - Rural"
## [80,] "(De Facto) Percent of schools with access to electricity - Urban"
## [81,] "(De Jure) Is there a policy in place to require that schools have access to electricity?"
## [82,] "(De Facto) Do you know if there is a policy in place to require that schools have access to electricity?"
## [83,] "Main cooking fuel: electricity (% of households)"
## [84,] "Multidimensional poverty, Electricity (% of population deprived)"
## [85,] "Number of people employed in electricity and utilities sector"
## [86,] "Proportion of primary schools with access to electricity (%)"
## [87,] "Proportion of lower secondary schools with access to electricity (%)"
## [88,] "Proportion of upper secondary schools with access to electricity (%)"
tsveri <- ts(data_genis, start=1960, frequency=1)
head(tsveri)
## sene Turkey United States
## [1,] 2013 8.73 7.37
## [2,] 2014 9.88 6.17
## [3,] 2015 10.24 5.28
## [4,] 2016 10.84 4.87
## [5,] 2017 10.82 4.36
## [6,] 2018 10.89 3.90
library(ggplot2)
library(ggfortify)
autoplot(tsveri[,"Turkey"]) +
ggtitle("TÜRKİYEDE İŞSİZLİK ORANLARI") +
xlab("Sene") +
ylab("")
autoplot(tsveri[,"Turkey"], ts.colour = 'blue', ts.linetype = 'dashed')
plot(tsveri[,"Turkey"])
plot(tsveri[,1:2])
plot(tsveri[,1:2], plot.type = "single")
plot(tsveri[,2],
type = "l",
col = 2,
ylim = c(0, 25),
xlab = "Sene",
ylab = "Oran")
lines(tsveri[,3],
type = "l",
col = 3)
legend("topright",
c("Türkiye", "US"),
lty = 1,
col = 2:4)
data_uzun <- melt(data_genis, id.vars = "sene")
ggplot(data_uzun,
aes(x = sene,
y = value,
col = variable)) +
geom_line()
\[ NUFUS \]
df = WDI(indicator='SP.POP.TOTL', country=c('MX','TR'), start=1960, end=2018)
head(df)
## iso2c country SP.POP.TOTL year
## 1 MX Mexico 126190782 2018
## 2 MX Mexico 124777326 2017
## 3 MX Mexico 123333379 2016
## 4 MX Mexico 121858251 2015
## 5 MX Mexico 120355137 2014
## 6 MX Mexico 118827158 2013
library(dplyr)
df <- df %>%
rename(ulkekodu = 1,
ulke = 2,
nüfus = 3,
sene = 4)
library(reshape2)
data_genis <- dcast(df, sene ~ ulke, value.var="nüfus")
head(data_genis)
## sene Mexico Turkey
## 1 1960 37771861 27472339
## 2 1961 38966049 28146909
## 3 1962 40195318 28832831
## 4 1963 41462373 29531362
## 5 1964 42771077 30244258
## 6 1965 44123863 30972996
df2 <- WDI(
country = "all",
indicator = "SP.POP.TOTL",
start = 2010,
end = 2020,
extra = TRUE,
cache = NULL,
latest = NULL,
)
WDIsearch("electricity")
## indicator
## [1,] "1.1_ACCESS.ELECTRICITY.TOT"
## [2,] "1.2_ACCESS.ELECTRICITY.RURAL"
## [3,] "1.3_ACCESS.ELECTRICITY.URBAN"
## [4,] "110400"
## [5,] "2.0.cov.Ele"
## [6,] "2.0.hoi.Ele"
## [7,] "4.1.1_TOTAL.ELECTRICITY.OUTPUT"
## [8,] "4.1.2_REN.ELECTRICITY.OUTPUT"
## [9,] "4.1_SHARE.RE.IN.ELECTRICITY"
## [10,] "9060000"
## [11,] "CC.ESG.EUFE"
## [12,] "CC.ESG.EUMA"
## [13,] "CC.GHG.EMSE.EH"
## [14,] "CC.GHG.SDEG.EH"
## [15,] "EG.ELC.ACCS.RU.ZS"
## [16,] "EG.ELC.ACCS.UR.ZS"
## [17,] "EG.ELC.ACCS.ZS"
## [18,] "EG.ELC.COAL.KH"
## [19,] "EG.ELC.COAL.ZS"
## [20,] "EG.ELC.FOSL.ZS"
## [21,] "EG.ELC.HYRO.KH"
## [22,] "EG.ELC.HYRO.ZS"
## [23,] "EG.ELC.NGAS.KH"
## [24,] "EG.ELC.NGAS.ZS"
## [25,] "EG.ELC.NUCL.KH"
## [26,] "EG.ELC.NUCL.ZS"
## [27,] "EG.ELC.PETR.KH"
## [28,] "EG.ELC.PETR.ZS"
## [29,] "EG.ELC.PROD.KH"
## [30,] "EG.ELC.RNEW.KH"
## [31,] "EG.ELC.RNEW.ZS"
## [32,] "EG.ELC.RNWX.KH"
## [33,] "EG.ELC.RNWX.ZS"
## [34,] "EG.TEG.RNEW.ZS"
## [35,] "EG.TEG.VAR.ZS"
## [36,] "EN.CO2.ETOT.MT"
## [37,] "EN.CO2.ETOT.ZS"
## [38,] "EN.PRD.ELEC"
## [39,] "EN.PRD.ELEC.POP.ZS"
## [40,] "HOU.ELC.ACSN.ZS"
## [41,] "IC.CNS.ELEC.ZS"
## [42,] "IC.ELC.ACES.DFRN.DB1015"
## [43,] "IC.ELC.ACES.DFRN.DB1619"
## [44,] "IC.ELC.ACES.RK.DB19"
## [45,] "IC.ELC.ACS.COST"
## [46,] "IC.ELC.ACS.COST.DFRN"
## [47,] "IC.ELC.COMM.TRFF.CG.01.DB1619"
## [48,] "IC.ELC.GEN.ZS"
## [49,] "IC.ELC.LMTG.OUTG.01.DB1619"
## [50,] "IC.ELC.MONT.OUTG.01.DB1619"
## [51,] "IC.ELC.OUTG.FREQ.DURS.03.DB1619"
## [52,] "IC.ELC.OUTG.MN.DB1619"
## [53,] "IC.ELC.PRI.KH.DB1619"
## [54,] "IC.ELC.PROC.NO"
## [55,] "IC.ELC.PROC.NO.DFRN"
## [56,] "IC.ELC.REGU.MONT.01.DB1619"
## [57,] "IC.ELC.RSTOR.01.DB1619"
## [58,] "IC.ELC.RSTT.XD.08.DB1619"
## [59,] "IC.ELC.RSTT.XD.08.DFRN.DB1619"
## [60,] "IC.ELC.SAID.XD.DB1619"
## [61,] "IC.ELC.SAIF.XD.DB1619"
## [62,] "IC.ELC.TIME"
## [63,] "IC.ELC.TIME.DFRN"
## [64,] "IC.ELEC.COST.PC.ZS"
## [65,] "IC.ELEC.PROC"
## [66,] "IC.ELEC.TIME"
## [67,] "IC.ELEC.XQ"
## [68,] "IC.FRM.ELEC.ZS"
## [69,] "IC.FRM.INFRA.IN10_C"
## [70,] "IC.FRM.INFRA.IN12"
## [71,] "IC.FRM.OBS.OBST8"
## [72,] "IN.ENRGY.ELEC.GEN"
## [73,] "NA.GDP.ELEC.GAS.SNA08.CR"
## [74,] "NA.GDP.ELEC.GAS.SNA08.KR"
## [75,] "NV.IND.GELW.CD"
## [76,] "NV.IND.GELW.CN"
## [77,] "NV.IND.GELW.KN"
## [78,] "SE.PRM.INFR.4"
## [79,] "SE.PRM.INFR.4.R"
## [80,] "SE.PRM.INFR.4.U"
## [81,] "SE.PRM.ISTD.7"
## [82,] "SE.PRM.ISTD.8"
## [83,] "SG.COK.ELEC.ZS"
## [84,] "SI.POV.ELEC.MI"
## [85,] "SL.EMP.ELC"
## [86,] "UIS.SCHBSP.1.WELEC"
## [87,] "UIS.SCHBSP.2.WELEC"
## [88,] "UIS.SCHBSP.3.WELEC"
## name
## [1,] "Access to electricity (% of total population)"
## [2,] "Access to electricity (% of rural population)"
## [3,] "Access to electricity (% of urban population)"
## [4,] "110400:HOUSING, WATER, ELECTRICITY, GAS, AND OTHER FUELS"
## [5,] "Coverage: Electricity"
## [6,] "HOI: Electricity"
## [7,] "Total electricity output (GWh)"
## [8,] "Renewable energy electricity output (GWh)"
## [9,] "Renewable electricity (% in total electricity output)"
## [10,] "9060000:ACTUAL HOUSING, WATER, ELECTRICITY, GAS AND OTHER FUELS"
## [11,] "Employment by sector and gender (% of total) - Electricity and utilities - Female"
## [12,] "Employment by sector and gender (% of total) - Electricity and utilities - Male"
## [13,] "Total GHG emissions by sector (Mt CO2 eq) - Electricity/Heat"
## [14,] "Sectoral drivers of GHG emissions growth in the period 2012-2018 - Electricity/Heat (contribution to total growth, %)"
## [15,] "Access to electricity, rural (% of rural population)"
## [16,] "Access to electricity, urban (% of urban population)"
## [17,] "Access to electricity (% of population)"
## [18,] "Electricity production from coal sources (kWh)"
## [19,] "Electricity production from coal sources (% of total)"
## [20,] "Electricity production from oil, gas and coal sources (% of total)"
## [21,] "Electricity production from hydroelectric sources (kWh)"
## [22,] "Electricity production from hydroelectric sources (% of total)"
## [23,] "Electricity production from natural gas sources (kWh)"
## [24,] "Electricity production from natural gas sources (% of total)"
## [25,] "Electricity production from nuclear sources (kWh)"
## [26,] "Electricity production from nuclear sources (% of total)"
## [27,] "Electricity production from oil sources (kWh)"
## [28,] "Electricity production from oil sources (% of total)"
## [29,] "Electricity production (kWh)"
## [30,] "Electricity production from renewable sources (kWh)"
## [31,] "Renewable electricity output (% of total electricity output)"
## [32,] "Electricity production from renewable sources, excluding hydroelectric (kWh)"
## [33,] "Electricity production from renewable sources, excluding hydroelectric (% of total)"
## [34,] "Share of renewables in total electricity generation (%)"
## [35,] "Share of variable renewables in total electricity generation (%)"
## [36,] "CO2 emissions from electricity and heat production, total (million metric tons)"
## [37,] "CO2 emissions from electricity and heat production, total (% of total fuel combustion)"
## [38,] "Electricity production (million kwh)"
## [39,] "Electricity production (kwh per capita)"
## [40,] "Household Access to Electricity: Total (in % of total household)"
## [41,] "Electricity (% of managers surveyed ranking this as a major constraint)"
## [42,] "Getting electricity (DB10-15 methodology) - Score"
## [43,] "Getting electricity (DB16-20 methodology) - Score"
## [44,] "Rank: Getting electricity (1=most business-friendly regulations)"
## [45,] "Getting electricity: Cost to get electricity (% of income per capita)"
## [46,] "Getting electricity: Cost to get electricity (% of income per capita) - Score"
## [47,] "Getting electricity: Communication of tariffs and tariff changes (0-1) (DB16-20 methodology)"
## [48,] "Electricity from Generator (%)"
## [49,] "Getting electricity: Financial deterrents aimed at limiting outages (0-1) (DB16-20 methodology)"
## [50,] "Getting electricity: Mechanisms for monitoring outages (0-1) (DB16-20 methodology)"
## [51,] "Getting electricity: Total duration and frequency of outages per customer a year (0-3) (DB16-20 methodology)"
## [52,] "Getting electricity: Minimum outage time (in minutes) (DB16-20 methodology)"
## [53,] "Getting electricity: Price of electricity (US cents per kWh) (DB16-20 methodology)"
## [54,] "Getting electricity: Procedures (number)"
## [55,] "Getting electricity: Procedures (number) - Score"
## [56,] "Getting electricity: Regulatory monitoring (0-1) (DB16-20 methodology)"
## [57,] "Getting electricity: Mechanisms for restoring service (0-1) (DB16-20 methodology)"
## [58,] "Getting electricity: Reliability of supply and transparency of tariff index (0-8) (DB16-20 methodology)"
## [59,] "Getting electricity: Reliability of supply and transparency of tariff index (0-8) (DB16-20 methodology) - Score"
## [60,] "Getting electricity: System average interruption duration index (SAIDI) (DB16-20 methodology)"
## [61,] "Getting electricity: System average interruption frequency index (SAIFI) (DB16-20 methodology)"
## [62,] "Time required to get electricity (days)"
## [63,] "Getting electricity: Time (days) - Score"
## [64,] "Cost to get electricity connection (% of income per capita)"
## [65,] "Procedures required to get electricity (number)"
## [66,] "Time required to get electricity (days)"
## [67,] "Getting electricity (rank)"
## [68,] "Electricity (% of firms identifying this as a major constraint)"
## [69,] "If a generator is used, average proportion of electricity from a generator (%)"
## [70,] "Percent of firms identifying electricity as a major constraint"
## [71,] "Percent of firms choosing electricity as their biggest obstacle"
## [72,] "Total-Electricity Generated Gross (GWh)"
## [73,] "GDP on Electricity & Gas Supply Sector (in IDR Million), SNA 2008, Current Price"
## [74,] "GDP on Electricity & Gas Supply Sector (in IDR Million), SNA 2008, Constant Price"
## [75,] "Electricity, gas and water supply, value added (current US$)"
## [76,] "Electricity, gas and water supply, value added (current LCU)"
## [77,] "Electricity, gas and water supply, value added (constant LCU)"
## [78,] "(De Facto) Percent of schools with access to electricity"
## [79,] "(De Facto) Percent of schools with access to electricity - Rural"
## [80,] "(De Facto) Percent of schools with access to electricity - Urban"
## [81,] "(De Jure) Is there a policy in place to require that schools have access to electricity?"
## [82,] "(De Facto) Do you know if there is a policy in place to require that schools have access to electricity?"
## [83,] "Main cooking fuel: electricity (% of households)"
## [84,] "Multidimensional poverty, Electricity (% of population deprived)"
## [85,] "Number of people employed in electricity and utilities sector"
## [86,] "Proportion of primary schools with access to electricity (%)"
## [87,] "Proportion of lower secondary schools with access to electricity (%)"
## [88,] "Proportion of upper secondary schools with access to electricity (%)"
tsveri <- ts(data_genis, start=1960, frequency=1)
head(tsveri)
## sene Mexico Turkey
## [1,] 1960 37771861 27472339
## [2,] 1961 38966049 28146909
## [3,] 1962 40195318 28832831
## [4,] 1963 41462373 29531362
## [5,] 1964 42771077 30244258
## [6,] 1965 44123863 30972996
library(ggplot2)
library(ggfortify)
autoplot(tsveri[,"Turkey"]) +
ggtitle("Türkiye'nin Nüfusu") +
xlab("Sene") +
ylab("")
autoplot(tsveri[,"Turkey"], ts.colour = 'red', ts.linetype = 'dashed')
plot(tsveri[,"Turkey"])
plot(tsveri[,1:2])
plot(tsveri[,1:3], plot.type = "single")
plot(tsveri[,2],
type = "l",
col = 2,
ylim = c(0, 25),
xlab = "Sene",
ylab = "Nüfus")
lines(tsveri[,3],
type = "l",
col = 3)
legend("topright",
c("Meksika", "Türkiye"),
lty = 1,
col = 2:4)
data_uzun <- melt(data_genis, id.vars = "sene")
ggplot(data_uzun,
aes(x = sene,
y = value,
col = variable)) +
geom_line()
\[
Fred
\]
library(quantmod)
## Zorunlu paket yükleniyor: xts
## Zorunlu paket yükleniyor: zoo
##
## Attaching package: 'zoo'
## The following objects are masked from 'package:base':
##
## as.Date, as.Date.numeric
##
## Attaching package: 'xts'
## The following objects are masked from 'package:dplyr':
##
## first, last
## Zorunlu paket yükleniyor: TTR
## Registered S3 method overwritten by 'quantmod':
## method from
## as.zoo.data.frame zoo
getSymbols("AAPL")
## 'getSymbols' currently uses auto.assign=TRUE by default, but will
## use auto.assign=FALSE in 0.5-0. You will still be able to use
## 'loadSymbols' to automatically load data. getOption("getSymbols.env")
## and getOption("getSymbols.auto.assign") will still be checked for
## alternate defaults.
##
## This message is shown once per session and may be disabled by setting
## options("getSymbols.warning4.0"=FALSE). See ?getSymbols for details.
## [1] "AAPL"
dim(AAPL)
## [1] 3816 6
head(AAPL)
## AAPL.Open AAPL.High AAPL.Low AAPL.Close AAPL.Volume AAPL.Adjusted
## 2007-01-03 3.081786 3.092143 2.925000 2.992857 1238319600 2.562706
## 2007-01-04 3.001786 3.069643 2.993571 3.059286 847260400 2.619587
## 2007-01-05 3.063214 3.078571 3.014286 3.037500 834741600 2.600934
## 2007-01-08 3.070000 3.090357 3.045714 3.052500 797106800 2.613776
## 2007-01-09 3.087500 3.320714 3.041071 3.306071 3349298400 2.830903
## 2007-01-10 3.383929 3.492857 3.337500 3.464286 2952880000 2.966379
tail(AAPL)
## AAPL.Open AAPL.High AAPL.Low AAPL.Close AAPL.Volume AAPL.Adjusted
## 2022-02-18 169.82 170.54 166.19 167.30 82614200 167.30
## 2022-02-22 164.98 166.69 162.15 164.32 91162800 164.32
## 2022-02-23 165.54 166.15 159.75 160.07 90009200 160.07
## 2022-02-24 152.58 162.85 152.00 162.74 141147500 162.74
## 2022-02-25 163.84 165.12 160.87 164.85 91881700 164.85
## 2022-02-28 163.06 165.42 162.43 165.12 94869100 165.12
chartSeries(AAPL, theme="white")
getSymbols("LRHU24TTTRM156S",src="FRED")
## [1] "LRHU24TTTRM156S"
chartSeries(LRHU24TTTRM156S,theme="white")
getFX("USD/TRY",from="2020-01-01")
## Warning in doTryCatch(return(expr), name, parentenv, handler): Oanda only
## provides historical data for the past 180 days. Symbol: USD/TRY
## [1] "USD/TRY"
chartSeries(USDTRY,theme="white")
\[
NETFLİX
\]
getSymbols("NFLX")
## [1] "NFLX"
dim(NFLX)
## [1] 3816 6
head(NFLX)
## NFLX.Open NFLX.High NFLX.Low NFLX.Close NFLX.Volume NFLX.Adjusted
## 2007-01-03 3.714286 3.824286 3.677143 3.801429 16440900 3.801429
## 2007-01-04 3.772857 3.828571 3.585714 3.621429 15959300 3.621429
## 2007-01-05 3.620000 3.620000 3.492857 3.544286 15190700 3.544286
## 2007-01-08 3.545714 3.555714 3.367143 3.404286 18344900 3.404286
## 2007-01-09 3.427143 3.440000 3.360000 3.427143 10611300 3.427143
## 2007-01-10 3.424286 3.464286 3.411429 3.438571 11448500 3.438571
tail(NFLX)
## NFLX.Open NFLX.High NFLX.Low NFLX.Close NFLX.Volume NFLX.Adjusted
## 2022-02-18 392.53 402.87 389.05 391.29 6796300 391.29
## 2022-02-22 388.95 392.42 373.02 377.38 6697500 377.38
## 2022-02-23 382.72 386.00 366.66 367.46 4614300 367.46
## 2022-02-24 355.09 390.73 354.72 390.03 7068700 390.03
## 2022-02-25 386.61 391.29 375.58 390.80 4836100 390.80
## 2022-02-28 387.33 397.75 382.13 394.52 5030600 394.52
chartSeries(NFLX, theme="white")
getSymbols("LRHU24TTTRM156S",src="FRED")
## [1] "LRHU24TTTRM156S"
chartSeries(LRHU24TTTRM156S,theme="white")
\[
FRED
\]