R eigenvalue matrix diagonal matrix output to csv file - r

I have get the covariance matrix of my data set Usedata. And I also get the diagonal matrix of the eigenvalues and output from R and save it as csv .
I cannot see each variables name at the top of csv file, instead, it just shows me "X1","X2", etc. . I want to see the variable name at the top of each column so I can see which variable has the biggest eigenvalue.
My code:
Usedata <- structure(list(X1 = c(1, 0, 0, 0.244012404, 0, 0, 6, 0, 0, 0,
0, 0), X2 = c(52.72564729, 2, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0),
X3 = c(0, 0, 3, 0, 0.142522511, 0, 0, 0, 8, 0, 0, 0), X4 = c(0,
0.341103073, 0, 4, 0, 0, 0, 0, 0, 9, 0, 0), X5 = c(0, 0,
0, 0, 5, 0.091644475, 0, 0, 0, 0, 10, 0)), .Names = c("X1",
"X2", "X3", "X4", "X5"), class = "data.frame",
row.names = c(NA, -12L))
smallcov <- cov(Usedata)
lam <- eigen(smallcov)$values
LamM <-diag(lam)
diagresult <- data.frame(LamM)
write.csv(diagresult, file = "myoutput.csv")

Related

How to assign first column as rownames in R? [duplicate]

This question already has answers here:
Convert the values in a column into row names in an existing data frame
(5 answers)
Closed 27 days ago.
I want to assign the first column as rownames of kirp.mut.
rownames(kirp.mut) <- kirp.mut[,1]
kirp.mut[,1] <- NULL
Traceback:
> rownames(kirp.mut) <- kirp.mut[,1]
Error in `.rowNamesDF<-`(x, value = value) : invalid 'row.names' length
In addition: Warning message:
Setting row names on a tibble is deprecated.
Dimensions:
> dim(kirp.mut)
[1] 283 8654
Class:
> class(kirp.mut)
[1] "tbl_df" "tbl" "data.frame"
typeof(kirp.mut)
[1] "list"
Data:
> dput(kirp.mut[1:10,1:10])
structure(list(sample_id = c("TCGA-2Z-A9J1-01A-11D-A382-10",
"TCGA-B9-A5W9-01A-11D-A28G-10", "TCGA-GL-A59R-01A-11D-A26P-10",
"TCGA-2Z-A9JM-01A-12D-A42J-10", "TCGA-A4-A57E-01A-11D-A26P-10",
"TCGA-BQ-7044-01A-11D-1961-08", "TCGA-HE-7130-01A-11D-1961-08",
"TCGA-UZ-A9Q0-01A-12D-A42J-10", "TCGA-HE-A5NI-01A-11D-A26P-10",
"TCGA-WN-A9G9-01A-12D-A36X-10"), NBPF1 = c(1, 0, 0, 0, 0, 0,
0, 0, 0, 0), CROCC = c(1, 0, 0, 0, 0, 0, 0, 0, 0, 0), SF3A3 = c(1,
0, 0, 0, 0, 0, 0, 0, 0, 0), GUCA2A = c(1, 0, 0, 0, 0, 0, 0, 0,
0, 0), RAVER2 = c(1, 0, 0, 0, 0, 0, 0, 0, 0, 0), ACADM = c(1,
0, 0, 0, 0, 0, 0, 0, 0, 0), PDE4DIP = c(1, 0, 0, 0, 0, 0, 0,
0, 0, 0), NUP210L = c(1, 0, 0, 0, 0, 0, 0, 0, 0, 0), NCF2 = c(1,
0, 0, 0, 0, 0, 0, 0, 0, 0)), row.names = c(NA, -10L), class = c("tbl_df",
"tbl", "data.frame"))

A tibble cannot have row names assigned. You could convert it to another format, such as a data frame, then assign row names. You can also do this tidyverse solution using column_to_rownames on your tibble without explicitly converting to another form, but it will do so internally and return a data.frame:
library(tidyverse)
library(dplyr)
kirp.mut <- kirp.mut %>%
column_to_rownames(var = "sample_id")
See the technical documentation here on row names and tibbles

Convert to matrix, excluding 1st column, then assign rownames:
m <- as.matrix(kirp.mut[, -1])
rownames(m) <- kirp.mut$sample_id
Or to a dataframe
#convert tibble to data.frame, then add rownames
df <- as.data.frame(kirp.mut[, -1])
rownames(df) <- kirp.mut$sample_id

Aggregate similar constructs/ FA with binary variables

I would like to aggregate, in order to reduce the number of constructs, its following data frame containing only binary variables that correspond to "yes/no", its following data frame (first 10 row). The original data frame contains 169 rows.
outcome <-
structure(list(Q9_Automazione.processi = c(0, 0, 0, 0, 0, 0,
1, 1, 1, 0), Q9_Velocita.Prod = c(1, 0, 0, 1, 0, 0, 1, 1, 1,
0), Q9_Flessibilita.Prod = c(0, 0, 0, 1, 0, 0, 1, 1, 0, 1), Q9_Controllo.processi = c(0,
0, 0, 1, 0, 0, 1, 1, 0, 0), Q9_Effic.Magazzino = c(0, 0, 0, 1,
0, 0, 0, 0, 0, 0), Q9_Riduz.Costi = c(0, 1, 0, 0, 0, 0, 0, 0,
0, 1), Q9_Miglior.Sicurezza = c(0, 0, 0, 0, 0, 0, 1, 0, 1, 1),
Q9_Connett.Interna = c(0, 0, 0, 0, 0, 0, 0, 1, 1, 0), Q9_Connett.Esterna = c(0,
0, 0, 0, 0, 0, 0, 0, 0, 0), Q9_Virtualizzazione = c(0, 0,
0, 0, 0, 0, 0, 0, 0, 0), Q9_Innov.Prod = c(0, 0, 0, 0, 0,
1, 0, 0, 0, 1), Q9_Person.Prod = c(0, 1, 0, 1, 0, 1, 0, 0,
0, 1), Q9_Nuovi.Mercati = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0),
Q9_Nuovi.BM = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0), Q9_Perform.Energ = c(0,
0, 0, 0, 0, 0, 0, 0, 0, 0), Q9_Perform.SostAmb = c(0, 0,
0, 0, 0, 0, 0, 0, 0, 0)), row.names = c(NA, 10L), class = "data.frame")
I have tried performing factor analysis via the tethracoric method on the obtained correlation matrix ( the obtained value from the KMO function turns out to be inadequate) both directly on the dataframe and then using tethracoric correletions in fafunction (using cor = "tet" I get a negative Tucker Lewis Index).
I have been reading up on this but cannot find a methodology that is adequate and of which I am certain of the correctness of the analysis.
So basically what I would like to achieve is to aggregate similar constructs, e.g., assess whether column 5 has value 1 (i.e., "yes") almost always when column 11 has value 1 and then aggregate.
Here the code that I try to used
library(psych)
tet <- tetrachoric(outcome)
corrplot(tet$rho, "ellipse", tl.cex = 0.75, tl.col = "black")
par(mfrow = c(1,2))
corr_matrix %>%
ggcorrplot(show.diag = F,
type="lower",
lab=TRUE,
lab_size=2)
KMO(corr_matrix)
cortest.bartlett(corr_matrix)
fa.parallel(corr_matrix, fm = "ml")
factor <- fa(corr_matrix, nfactors = 3, rotate = "oblimin", fm = "ml")
print(factor, cut = 0.3, digits = 3)
# -------- Pearson --------
cor(outcome, method = 'pearson', use = "pairwise.complete.obs") %>%
ggcorrplot(show.diag = F,
type="lower",
lab=TRUE,
lab_size=2)
KMO(outcome)
cortest.bartlett(outcome)
fa.parallel(outcome)
factor1 <- fa(outcome, nfactors = 3, rotate = "oblimin", cor = "tet", fm = "ml")
print(factor1, cut = 0.3, digits = 3)

Removing characters/words in a column of a large dataframe in R

I am currently strugling to remove words from a large dataframe in R.
This is the df:
The first column (GeneID) contains a so called "ensembl gene ID". First one i.e. ENSG00000223972.5 followed by a "|". Afterwards, the real Gene name is listed. So i now want to remove the "ensembl gene ID" including the "|" to keep only the real gene name in this column. Is there a smart way to do this ? For example with the stringR package?
Cheers!
Edit:
> dput(head(data3))
structure(list(GeneID = c("ENSG00000223972.5|DDX11L1", "ENSG00000227232.5|WASH7P",
"ENSG00000278267.1|MIR6859-1", "ENSG00000243485.5|MIR1302-2HG",
"ENSG00000284332.1|MIR1302-2", "ENSG00000237613.2|FAM138A"),
`DC2-CD5pos-d1` = c(2, 47, 0, 0, 0, 0), `DC2-CD5pos-d2` = c(0,
41, 0, 0, 0, 0), `DC2-CD5pos-d3` = c(2, 31, 0, 0, 0, 0),
`DC2-CD5pos-d4` = c(0, 29, 0, 0, 0, 0), `DC3-d1` = c(1, 36,
0, 0, 0, 0), `DC3-d2` = c(0, 33, 0, 0, 0, 0), `DC3-d3` = c(0,
49, 0, 0, 0, 3), `DC3-d4` = c(0, 27, 0, 0, 0, 0), `DC2-BTLA-S-d1` = c(2,
4, 0, 1, 0, 0), `DC2-BTLA-S-d3` = c(6, 6, 1, 0, 0, 0), `DC2-BTLA-S-d4` = c(2,
1, 0, 0, 0, 0), `DC3-CD163-S-d1` = c(2, 8, 2, 0, 0, 0), `DC3-CD163-S-d3` = c(5,
9, 0, 0, 0, 0), `DC3-CD163-S-d4` = c(0, 5, 0, 0, 0, 0)), row.names = c(NA,
-6L), class = c("tbl_df", "tbl", "data.frame"))

Create bar plot for every level of a factor in a wide format data frame

I'm trying to create a bar plot using ggplot2 and my data is in this format:
dput here:
structure(list(clade = structure(c(1L, 3L, 2L, 3L, 2L, 2L), .Label = c("19A",
"20A", "20B", "20E (EU1)", "20I (Alpha, V1)", "20J (Gamma, V3)",
"21J (Delta)"), class = "factor"), C.T = c(0, 4, 4, 4, 4, 4),
A.G = c(0, 1, 1, 1, 1, 1), G.A = c(0, 2, 0, 2, 0, 0), G.C = c(0,
1, 0, 1, 0, 0), T.C = c(0, 0, 0, 0, 0, 0), C.A = c(0, 0,
0, 0, 0, 0), G.T = c(0, 0, 0, 0, 0, 0), A.T = c(0, 0, 0,
0, 0, 0), T.A = c(0, 0, 0, 0, 0, 0), T.G = c(0, 0, 0, 0,
0, 0), A.C = c(0, 0, 0, 0, 0, 0), C.G = c(0, 0, 0, 0, 0,
0), A.del = c(0, 0, 0, 0, 0, 0), TAT.del = c(0, 0, 0, 0,
0, 0), TCTGGTTTT.del = c(0, 0, 0, 0, 0, 0), TACATG.del = c(0,
0, 0, 0, 0, 0), AGTTCA.del = c(0, 0, 0, 0, 0, 0), GATTTC.del = c(0,
0, 0, 0, 0, 0)), row.names = c(NA, -6L), class = c("data.table",
"data.frame"), .internal.selfref = <pointer: 0x0000014b25a51ef0>)
I'd like to create 7 bar plots (one for each "clade") where the X axis would have the columns of the data frame (C.T would be 1 bar, A.G would be another bar, etc) and the Y axis would be the count. Essentially, for each clade, print a barplot with the counts of column.
For example, for the bar plot of the clade "20B" and the bar name "C.T" the count would be the sum of the values from the data frame. Can I do that in this wide format? Do I need to transform the data to a long format instead?
I was trying to apply this SO answer: Plotting error bar on bar chart for a data frame in wide format using ggplot but I keep getting choose another strategy with names_repair
Thank you in advance, any help is very welcome!

R apply funciton on each cell in data frame

I have a data frame that look something like this
> dput(tes)
structure(list(path = structure(1:6, .Label = c("1893-chicago-fair",
"1960s-afghanistan", "1970s-iran", "1980s-new-york", "20-bizarre-vintage-ads",
"20-bizarre-vintage-ads?utm_campaign=6678&utm_medium=rpages&utm_source=Facebook&utm_term=1e8e704f7b587515c72e6cf7895d55fd110b652c480d98c1440f0a7acba5fb0e",
"20-photos-segregation-america-show-far-weve-come-much-farther-go",
"7-bizarre-cultural-practices", "7-creepy-abandoned-cities?utm_campaign=6928&utm_medium=rpages&utm_source=Facebook&utm_term=4015a7368b588ff09694c96ba720c58f4e7f41a05b4181908b582bae682bef5e",
"a-brief-history-of-hippies", "abandoned-photographs", "albert-kahn",
"amazing-facts", "american-bison-extinction-1800s", "american-english-vs-british-english",
"andre-the-giant-photos", "andre-the-giant-photos??utm_source=facebook&sr_source=lift_facebook&utm_campaign=simplereach_andre-the-giant-photos&utm_medium=social",
"andre-the-giant-photos?grvVariant=d27feef0bfad84d60f335d3a8d241d9e",
"andre-the-giant-photos?grvVariant=d27feef0bfad84d60f335d3a8d241d9e&utm_campaign=gravityus2_142deb68f67fb1a99e7b80250fecc932&utm_medium=referral&utm_source=gravity",
"andre-the-giant-photos?grvVariant=d27feef0bfad84d60f335d3a8d241d9e&utm_campaign=gravityus2_16d63cf07ecf656f602b2d6b209344f7&utm_medium=referral&utm_source=gravity",
"andre-the-giant-photos?grvVariant=d27feef0bfad84d60f335d3a8d241d9e&utm_campaign=gravityus2_713050ecffc51540af02b2246ddf57dd&utm_medium=referral&utm_source=gravity",
"andre-the-giant-photos?grvVariant=d27feef0bfad84d60f335d3a8d241d9e&utm_campaign=gravityus2_c5bb3bc5e9408e0ad52ec9e787bd8654&utm_medium=referral&utm_source=gravity",
"andre-the-giant-photos?sr_source=lift_facebook&utm_campaign=simplereach_andre-the-giant-photos&utm_medium=social&utm_source=facebook",
"astounding-aerial-photography", "astounding-aerial-photography?utm_campaign=7002&utm_medium=rpages&utm_source=Facebook&utm_term=38e9e903d9ba59106d8b4d19be593f3de7ff8b91b12eafa03f2e382228f7b0d1",
"august-landmesser", "ben-franklin", "best-all-that-is-interesting-articles",
"bigfoot-facts", "celebrity-school-photos?grvVariant=82c0ce57a33dfd0209bdefc878665de0&utm_campaign=gravityus2_bc8646aefd6d0a16af03d7caf248f226&utm_medium=referral&utm_source=gravity",
"coolest-mushrooms?utm_campaign=taboolaINTL&utm_medium=referral&utm_source=taboola",
"craziest-ways-drugs-smuggled", "creepy-halloween-costumes",
"danakil-depression", "dark-john-lennon-quotes", "david-bowie-quotes",
"days-in-groundhog-day", "death-photos", "death-photos?utm_campaign=taboolaINTL&utm_medium=referral&utm_source=taboola",
"dr-seuss-quotes", "dream-chaser-spacecraft", "dust-bowl", "earth-two-planets",
"eixample-barcelona", "email-to-space", "evil-science-experiments",
"famous-incest", "famous-spies", "fun-facts-trivia", "golden-age-air-travel?utm_campaign=taboolaINTL&utm_medium=referral&utm_source=taboola",
"gross-foods", "gross-foods?utm_campaign=6928&utm_medium=rpages&utm_source=Facebook&utm_term=106965c54919c24bf37356500ec50f0709b1de621d6950bb4c5d48759ea3677e",
"gross-foods?utm_campaign=6928&utm_medium=rpages&utm_source=Facebook&utm_term=184e0ee39e66af82f9b124b904f6e07964b211e902cb0dc00c28771ff46163a2",
"gross-foods?utm_campaign=6928&utm_medium=rpages&utm_source=Facebook&utm_term=1a0ddea7bed770d5473c45e9f8d81dfd0c4fdd232f207c6b88b53c41ff220c59",
"gross-foods?utm_campaign=6928&utm_medium=rpages&utm_source=Facebook&utm_term=538659f1fc53f28d2c87b93ac73973681c1a46a04954964ab6c52ed1ab09b33a",
"gross-foods?utm_campaign=6928&utm_medium=rpages&utm_source=Facebook&utm_term=87caf0acb91ae2b202f1b00ad9eaad3fef20bbfb23405b9047fb2b5a5462ab9c",
"gross-foods?utm_campaign=6928&utm_medium=rpages&utm_source=Facebook&utm_term=91eae42c8fc9568103d46e0b6b6ec08fc34fd68b2e1918ffe2333ec73035c95a",
"gross-foods?utm_campaign=6928&utm_medium=rpages&utm_source=Facebook&utm_term=a72946874b2003a8e40635c6cf10c851d4e1c0ed45e645d69663214239550602",
"gross-foods?utm_campaign=6928&utm_medium=rpages&utm_source=Facebook&utm_term=ab594f0a1be002c8c3db297e8d33b04678af40e6a6469ac815884ae0a014b3a3",
"gross-foods?utm_campaign=6928&utm_medium=rpages&utm_source=Facebook&utm_term=fb1e333dd58cb7bb9251ec52290aae21771149f73e083440047068a69aaeae09",
"hilarious-insults", "hippie-communes", "hippie-communes?grvVariant=fda07538efb1c25617f7cc3d09c37c79",
"hippie-communes?grvVariant=fda07538efb1c25617f7cc3d09c37c79&utm_campaign=gravityus2_e3cd42d4745768460dab4694a972fd82&utm_medium=referral&utm_source=gravity",
"hippie-communes?pp=0", "history-of-the-vibrator", "history-of-the-vibrator?utm_campaign=whfbpd&utm_medium=social&utm_source=facebook",
"homosexuality-norm", "hunger-games-facts?utm_campaign=6905&utm_medium=rpages&utm_source=Facebook&utm_term=1a9e42ac8abb6ffa90bf0542206505e74d3df12114a2c4445527fb2b88ef8880",
"influential-photographs", "ingeniously-creative-ads", "insane-cults",
"insane-rulers", "inspirational-quotes", "inspirational-quotes?utm_medium=referral&utm_source=taboolainternal",
"interesting-facts-about-the-world", "interesting-quotes", "krokodil",
"making-a-murderer-theories", "maya-angelou-greatest-quotes",
"medieval-torture-devices", "milky-way-colorado", "montreal-metro",
"most-popular-female-names-in-america", "neil-degrasse-tyson-tweets",
"new-york-city-cinemagraphs", "new-york-subways-1980s", "north-korea-photographs",
"north-korea-photographs?utm_campaign=taboolaINTL&utm_medium=referral&utm_source=taboola",
"north-korea-photographs?utm_medium=referral&utm_source=taboolainternal",
"obama-aging", "pablo-escobar", "pablo-escobar??utm_source=facebook",
"pablo-escobar??utm_source=facebook&sr_source=lift_facebook&utm_campaign=simplereach_pablo-escobar&utm_medium=social",
"pablo-escobar?utm_campaign=whfbpd&utm_medium=social&utm_source=facebook",
"panda-facts", "photo-of-the-day-nasa-releases-crystal-clear-image-of-pluto",
"pollution-in-china-photographs", "pollution-in-china-photographs?utm_campaign=3434&utm_medium=rpages&utm_source=Facebook&utm_term=1a0ddea7bed770d5473c45e9f8d81dfd0c4fdd232f207c6b88b53c41ff220c59",
"pollution-in-china-photographs?utm_campaign=3434&utm_medium=rpages&utm_source=Facebook&utm_term=e28a76c1572c36c3a13965e52b4b2ea10518eb9f9c79c4bc84cfb85db16be81e",
"pollution-in-china-photographs?utm_campaign=6806&utm_medium=rpages&utm_source=Facebook&utm_term=1a0ddea7bed770d5473c45e9f8d81dfd0c4fdd232f207c6b88b53c41ff220c59",
"pollution-in-china-photographs?utm_campaign=7048&utm_medium=rpages&utm_source=Facebook&utm_term=2ef4bd7b6cd587601d6eeb35925282a1ed095ebbd4e9e4c0337ef868c7de7a0b",
"pollution-in-china-photographs?utm_campaign=7458&utm_medium=rpages&utm_source=Facebook&utm_term=b9e79a51cd4daf4c3ec02accce75b3e1fc9a22cb3133460c9c32a4f2f9cdb68c",
"powerful-photos-of-2014", "real-x-files", "romanovs-last-days",
"science-of-human-decay", "scientific-discoveries-2015", "scully-effect",
"serial-killer-quotes", "shah-iran", "six-of-the-craziest-gods-in-mythology",
"space-facts", "sun-facts", "sunken-cities", "sunken-ships",
"super-bowl-i-facts", "superhero-movies", "surreal-places", "syrian-civil-war-photographs",
"the-five-greatest-mysteries-of-human-history", "the-four-most-important-battles-of-ancient-greece",
"the-most-colorful-cities-in-the-world", "titanic-facts", "titanic-facts?utm_campaign=6385&utm_medium=rpages&utm_source=Facebook&utm_term=f5905e878216d14e20457ee3265caf6c10022d9545609edfb9a3cb0642c1a310",
"titanic-facts?utm_campaign=6899&utm_medium=rpages&utm_source=Facebook&utm_term=b9e79a51cd4daf4c3ec02accce75b3e1fc9a22cb3133460c9c32a4f2f9cdb68c",
"titanic-facts?utm_campaign=6928&utm_medium=rpages&utm_source=Facebook&utm_term=106965c54919c24bf37356500ec50f0709b1de621d6950bb4c5d48759ea3677e",
"titanic-facts?utm_campaign=6928&utm_medium=rpages&utm_source=Facebook&utm_term=538659f1fc53f28d2c87b93ac73973681c1a46a04954964ab6c52ed1ab09b33a",
"titanic-facts?utm_campaign=6928&utm_medium=rpages&utm_source=Facebook&utm_term=91eae42c8fc9568103d46e0b6b6ec08fc34fd68b2e1918ffe2333ec73035c95a",
"titanic-facts?utm_campaign=6928&utm_medium=rpages&utm_source=Facebook&utm_term=ab594f0a1be002c8c3db297e8d33b04678af40e6a6469ac815884ae0a014b3a3",
"titanic-facts?utm_campaign=6928&utm_medium=rpages&utm_source=Facebook&utm_term=d1864657a05e5b716bb5cb16a29f068a55652eb39fb669ea9c22a6486198f227",
"titanic-facts?utm_campaign=7292&utm_medium=rpages&utm_source=Facebook&utm_term=f5905e878216d14e20457ee3265caf6c10022d9545609edfb9a3cb0642c1a310",
"us-veterans-portraits", "vintage-disneyland", "wall-street-early-20th-century",
"what-we-love-this-week-the-incredible-last-words-of-famous-historical-figures",
"woodstock-photos", "zombie-proof-house"), class = "factor"),
`0089` = c(0, 0, 0, 0, 0, 1), `0096` = c(0, 0, 0, 0, 0, 0
), `02` = c(0, 0, 0, 0, 0, 0), `0215` = c(0, 0, 0, 0, 0,
0), `0225` = c(0, 0, 0, 0, 0, 0), `0252` = c(0, 0, 0, 0,
0, 0), `0271` = c(0, 0, 0, 0, 0, 0), `0272` = c(0, 0, 0,
0, 0, 0), `03` = c(0, 0, 0, 0, 1, 1)), .Names = c("path",
"0089", "0096", "02", "0215", "0225", "0252", "0271", "0272",
"03"), row.names = c(NA, 6L), class = "data.frame")
and I need to apply the min(x,1) function such that this function scan each value in the dataframe (except first column which is not numeric) and return the min(x,1). that way I have only zero's and one's.
I have tried:
f <- function(x) min(1,x)
res1<-do.call(f,tes[,2:ncol(tes)])
but that does not output the right result.
Any help aapreciated

We can use pmin
tes[,-1] <- pmin(1, as.matrix(tes[,-1]))
Or if we need only binary values
tes[,-1] <- +(!!tes[,-1])

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