NOTE THAT ((This should be done by R studio !)) Q: Upload your data as a...

NOTE THAT

((This should be done by R studio !))

Q: Upload your data as a CSV in R studio, then do any
cleaning or convert needed for example convert the date in your table
from character to date and NA identifiers . After do all these, run a summary statistics

Year	REX	OilP	Food exports (% of merchandise exports)	Ores and metals exports (% of merchandise exports)
1980	239.5433424	35.52	0.09638294	0.060083757
1981	240.3102173	34	0.094079554	0.024360528
1982	245.3895131	32.38	0.128489839	0.025668368
1983	242.8677506	29.04	..	..
1984	238.0284197	28.2	..	..
1985	221.878717	27.01	0.259787311	0.116943755
1986	169.6457184	13.53	..	..
1987	144.1934823	17.73	..	..
1988	134.5212315	14.24	1.371078529	0.732151804
1989	136.0536024	17.31	1.374888969	0.834330299
1990	125.5311345	22.26	0.713126234	0.491007478
1991	125.8812467	18.62	0.526384845	0.242750346
1992	118.7733668	18.44	1.074388363	0.548851562
1993	122.2521688	16.33	0.982275388	0.429968062
1994	117.8952881	15.53	0.673955645	0.346686956
1995	114.1213899	16.86	0.810242733	0.567217625
1996	116.3114665	20.29	0.632336949	0.304958406
1997	121.4661302	18.86	..	..
1998	127.1948915	12.28	1.114818605	0.507089276
1999	121.9490893	17.44	0.930990348	0.262574488
2000	123.200674	27.6	0.538501429	0.147164016
2001	125.2424379	23.12	0.558465111	0.201693533
2002	121.5455166	24.36	0.628539417	0.223275991
2003	111.1523893	28.1	0.835851768	0.182707717
2004	103.4682918	36.05	0.7405123	0.172800798
2005	100.5070052	50.59	0.620831971	0.137293785
2006	98.93290899	61	0.64203501	0.219532433
2007	95.96813741	69.04	0.838923226	0.283587719
2008	93.62494305	94.1	0.744029125	0.221986187
2009	100.1652448	60.86	1.407633083	0.232499732
2010	100	77.38	1.155876888	0.154654215
2011	96.57013945	107.46	0.898301922	0.122271232
2012	99.61967144	109.45	0.860627792	0.138455596
2013	102.3680362	105.87	0.878931429	0.403127249
2014	105.3894897	96.29	1.006265279	0.769034983
2015	118.5851177	49.49	1.798068624	1.307540253

R ONLY !!

Expert Solution

Below is the R script:-

data=read.delim("clipboard")#import data from excel to R
attach(data)
data#display data frame
mydata=na.omit(data)#omit NA data
mydata
is.na(mydata)#checks if NA data present

summary(mydata)#gives summary of data

Thank you.

venereology answered 7 months ago

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