Bar chart with ID indicator - r

My data:
structure(list(Id = c(8378563200, 5577150313, 4702921684, 4388161847,
7086361926, 6962181067, 4445114986, 5553957443, 4319703577, 1503960366,
2026352035, 3977333714, 6117666160, 8792009665, 4020332650, 2347167796
), total_steps = c(8377719, 6477458, 7174818, 7710336, 6972600,
9412809, 4163404, 8276690, 5858684, 9390475, 4832044, 9227036,
3551544, 806370, 562272, 2570310), total_sleeps = c(427769, 336960,
349432, 285324, 337125, 430528, 334335, 445408, 384183, 279217,
439363, 246660, 241304, 189515, 86645, 120636), total_calories = c(3302554,
2620514, 2482164, 2205930, 1909368, 1904733, 1897616, 1802526,
1642368, 1407725, 1337280, 1271480, 1139616, 853605, 591680,
551730)), row.names = c(NA, -16L), class = c("tbl_df", "tbl",
"data.frame"))
I am looking for a way to build a bar chart in R Languages with the Id indicator on top of each bar chart showing the calories burned, total steps and sleeps. Or I can try to facet them with 24 respondents indicating the calories burned, total steps and sleep. Please tell me which way is better or consult me on a better way to visualize it.


Maybe something like this:
Bring you data in lang format with pivot_longer
transform Id and name to factor type
use ggplot
library(tidyverse)
df %>%
pivot_longer(
-Id
) %>%
mutate(Id = factor(Id),
name=factor(name, levels = c("total_steps", "total_sleeps", "total_calories"))) %>%
ggplot(aes(x=Id, y=value, fill=name, label=value))+
geom_col(position=position_stack()) +
geom_text(aes(label = value,family = "serif"), position = position_stack(vjust = 0.5))+
theme_bw()
data:
df <- structure(list(Id = c(8378563200, 5577150313, 4702921684, 4388161847,
7086361926, 6962181067, 4445114986, 5553957443, 4319703577, 1503960366,
2026352035, 3977333714, 6117666160, 8792009665, 4020332650, 2347167796
), total_steps = c(8377719, 6477458, 7174818, 7710336, 6972600,
9412809, 4163404, 8276690, 5858684, 9390475, 4832044, 9227036,
3551544, 806370, 562272, 2570310), total_sleeps = c(427769, 336960,
349432, 285324, 337125, 430528, 334335, 445408, 384183, 279217,
439363, 246660, 241304, 189515, 86645, 120636), total_calories = c(3302554,
2620514, 2482164, 2205930, 1909368, 1904733, 1897616, 1802526,
1642368, 1407725, 1337280, 1271480, 1139616, 853605, 591680,
551730)), row.names = c(NA, -16L), class = c("tbl_df", "tbl",
"data.frame"))

Related

how to put a plot and a table together using grid.arrange

I have a plot and a table, and I would like to combine them into a plot. how should I do that.
Here is my codes:
df<-structure(list(AEDECOD = c("Hypoxia", "Malignant pleural effusion",
"Decubitus ulcer", "Nausea"), ADY = c(13, 13, 13, 14)), row.names = c(NA,
-4L), class = "data.frame")
tbl <-structure(list(`Analysis Relative Day` = 13, `AE Type` = "SER",
`Adverse Event` = "Hypoxia/Malignant pleural effusion"), row.names = c(NA,
-1L), class = c("tbl_df", "tbl", "data.frame"))
p1<- ggplot(data =df, aes(x = ADY, y = AEDECOD))+ geom_point()
p2 <-grid.arrange(p1, tbl,
nrow = 2,as.table = TRUE)
print(p2)
I got the error codes:
Error: Input must be a vector, not a <viewport> object.
If you know any other way to do the same thing, I would like to learn that as well.

We may use ggarrange after converting the tibble to ggtexttable
library(ggpubr)
ggarrange(p1, ggtexttable(tbl), nrow = 2)
Or using the OP's code
library(gridExtra)
grid.arrange(p1, ggtexttable(tbl),
nrow = 2,as.table = TRUE)
-output

Plot multiple geom_line and geom_smooth objects in one plot

I have somewhat messy looking dataframes, like this one:
df0
# A tibble: 3 x 9
# Groups: Sequ [1]
Sequ Speaker Utterance A_intpl A_dur B_intpl B_dur C_intpl C_dur
<int> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
1 2 ID16.A cool >wha… 31.44786152… 10.5,17,1… 32.86993284… 9.5,16,17… 58.3368399… 14,17,17…
2 2 NA (0.228) 32.75735987… 15.5,17,1… 30.83469006… 14.5,16.9… 26.0386462… 3,17,16,…
3 2 ID16.B u:m Tenne… 32.05752604… 4.5,17,16… 29.95825107… 3.5,16,17… 55.9298614… 8,17,17,…
I want to plot the *_intpl values for each speaker (A, B, or C) for each of the three Utterances in a single chart both as line charts and as trend lines.
I'm just half successful doing this:
library(tidyr)
library(ggplot2)
library(dplyr)
df0 %>%
pivot_longer(cols = contains("_"),
names_to = c("Event_by", ".value"),
names_pattern = "^(.*)_([^_]+$)") %>%
separate_rows(c(intpl, dur), sep = ",", convert = TRUE) %>%
mutate(Time = cumsum(dur)) %>%
mutate(Utterance = paste0(sub(".*(.)$", "\\1",Speaker), ": ", Utterance),
Utterance = factor(Utterance, levels = unique(Utterance))) %>%
ggplot(aes(x = Time, y = log2(intpl),
group = Event_by,
colour = Event_by)) +
geom_line()+
geom_smooth(method = 'lm', color = "red", formula = y~x)+
facet_wrap(~ Utterance, ncol = 1, scales= "free_x")
Half successful because the line plots and trend lines are side-by-side, as if in three columns, whereas they should be in rows, one below the other - how can that be achieved?
Reproducible data:
structure(list(Sequ = c(2L, 2L, 2L), Speaker = c("ID16.A", NA,
"ID16.B"), Utterance = c("cool >what part?<", "(0.228)", "u:m Tennessee="
), A_intpl = c("31.4478615210995,31.5797510648522,31.7143985369445,31.651083739602,31.5806035086034,36.8956763912703,36.2882129597292,35.2124499461012,34.1366869324732,34.1366869324732,32.1927035724058,30.2487202123383,28.3047368522709,26.3607534922035,30.5278334848495,30.5919390424853,30.8898529369568,31.578968913188,31.9011198738002,32.1543265113196,31.9708002079533,31.966536408565,31.8762658607759,31.8994741472105,31.4215913971938,32.1510578328563,31.7863350712876,32.4685052625667,31.7422271490296,32.3286054977263,31.9998974949481,32.5177992323864,32.4727499785435,32.9310888953766,32.7592010033585,33.2231711877427,33.1593949301066,33.2432973964816,33.2569729073414,33.492144800249,33.317650964723,33.4835787832119,33.2377190454279,32.9200836384356,32.9684568771567,32.6400987016883,27.5447101464944,29.3948945479171,35.3449171857603,33.5932932239592,31.8416692621581,30.0900453003569,32.7850431084597,32.7589003618266,32.8365550655013,32.386716057622,32.8420792704881,32.6909995562489,32.6269434402016,32.7370944106334,32.7529759209752,32.6528826975113,32.3663573764448,32.7326853004792,32.6930038462418,32.8975978772676,33.1752899475416,33.2034433355001,33.0667431432803,32.6322933080614,33.2503168843178,32.7573598713719",
"32.7573598713719,32.7531704791313,32.7366130631104,32.918942216354,32.8309939530596,32.3856893430525,32.5368873543441,32.5628510484821,32.5628510484821,32.5628510484821,32.5506564332008,32.7477119716583,32.3458470743288,32.0575260428013",
"32.0575260428013,32.1628824338111,32.0093334061923,32.1461460586991,31.9080762250966,31.9469105074833,31.7431187667232,31.7194255656503,31.7394296413187,31.8594986292975,31.7498243274746,31.9069142374258,32.0835520942767,31.6257067057109,31.757232379438,31.9036689124911,32.1319749301918,31.7203280774998,31.7877137245706,32.3030946636177,32.2800139298454,32.164646135728,32.3636504940227,32.5657818936495,32.3859453482697,32.4797898358193,32.5319835105237,32.92233491509,32.8240561109448,32.664496027779,33.1835064752029,33.0366413969703,33.0406288190821,33.3232964677672,33.2206260057731,33.1537134269402,33.2783471506207,33.2933281566788,33.5322350394609,33.3815736723684,33.7905544185063,33.6143820666896,33.7490659591585,33.7260102344634,34.0721931066557,34.0455026427054,34.3735788774521,34.2888420421073,34.3913721165542,34.5982135545306,34.4417202731001,34.6586347152449,31.1590521215434,31.3276405983897,28.2379253186548,31.133030931336,34.0715906921349,35.8967950760285,35.9334551147377,35.8565504335515,35.7446081905229,35.6300325834155,35.8390086948751,35.9711743270411,36.0029493274176,35.8891056768339"
), A_dur = c("10.5,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,0.5",
"15.5,17,17,16,17,17,16,17,17,16,17,17,16,12.5", "4.5,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,5.5"
), B_intpl = c("32.8699328424689,32.8154348109057,32.5454364786882,32.408257038977,32.5304564519672,32.3270203236281,31.9233218634346,32.0166346064182,31.7360745988363,31.7546527359571,31.8603220354065,31.6520061326962,31.5603191463274,31.3357561466519,31.0976090032219,31.1405090978825,31.1697180784961,31.0863999545386,31.3126984044729,30.580776446803,30.7137016246273,31.0801914571091,31.2343922096768,31.2749857511594,31.3488604642844,30.9327390960718,31.0750482778561,31.1849119826023,31.4180114886183,31.5284273181104,31.147361398529,31.1128597713973,31.5551385744611,31.7479939892741,31.5890352680344,31.5470790538009,31.5427330200078,31.3901913024084,31.5423214446953,31.4814325586741,31.4937336232021,31.3483738841556,31.2516462059018,31.2233881922543,31.2572951780583,31.0087226975291,31.1197589042273,31.053748381687,30.8202174718598,30.845143129195,30.8727194789634,30.4231467151428,30.7254093759809,30.2757746547116,30.6047530953025,29.6835591414008,28.257421076205,29.4634886416064,29.183064807185,28.6935506287734,29.3989017421637,30.8936090542518,30.6884831327852,30.805770713392,30.6938909098627,30.8317757801268,30.8509115577427,30.6836198471168,30.7979978629801,31.0260101704105,30.6248844591805,30.8346900656087",
"30.8346900656087,30.9826158466835,29.814086001996,29.7839590794955,30.7928804535206,31.1589874726521,31.0547403039501,31.2268131145794,31.155503802286,31.3036925274762,31.4782621660348,31.0928322383151,31.589958621025,29.9582510795225",
"29.9582510795225,29.9796434055214,29.9405638729798,30.2602098442174,30.5011865525849,30.6753859842987,28.9331380886365,30.7736467776919,30.8457967803438,30.843630408183,30.8767570425033,30.9178344980247,30.734598946287,30.8877440413271,30.9225051837881,30.9534076039184,31.0172861192043,30.9371712793451,30.9806052132295,31.0593603717961,31.1156928565737,30.4713263393479,26.028518302418,28.1426546887905,29.4308434671559,30.7190322455213,31.2289674937063,31.7389027418913,32.2488379900763,32.7587732382613,33.2687084864463,33.7786437346312,34.2885789828162,34.7985142310012,35.3084494791862,35.8183847273712,36.3283199755562,36.8382552237412,37.3481904719262,37.8581257201112,38.3680609682962,25.5986933949893,29.7968031963901,30.5336819967028,30.1876589408847,30.4260367500101,30.2997107671214,30.3429716412578,30.3537316791924,30.4111899964144,30.7293520851914,30.7778983966343,30.9712137067708,30.9072589183658,31.0696990205164,30.5713926084448,31.3458855877875,31.4169903025083,31.5148974986093,31.5972499257413,31.2293401943969,31.2033325602348,31.1657434266985,30.6784877073261,30.6991365599664,30.6763195188897"
), B_dur = c("9.5,16,17,17,16,17,17,16,17.0000000000146,16.9999999999854,16,17,16.9999999999854,16.0000000000146,17,17,16,17,17,16,17,17,16,17.0000000000146,16.9999999999854,16,17,16.9999999999854,16.0000000000146,17,17,16,17,17,16,17,17,16,17.0000000000146,16.9999999999854,16,17,16.9999999999854,16.0000000000146,17,17,16,17,17,16,17,17,16,17.0000000000146,16.9999999999854,16,17,16.9999999999854,16.0000000000146,17,17,16,17,17,16,17,17,16,17.0000000000146,16.9999999999854,16,2.5",
"14.5,16.9999999999854,16.0000000000146,17,17,16,17,17,16,17,17,16,17.0000000000146,13.4999999999854",
"3.5,16,17,16.9999999999854,16.0000000000146,17,17,16,17,17,16,17,17,16,17.0000000000146,16.9999999999854,16,17,16.9999999999854,16.0000000000146,17,17,16,17,17,16,17,17,16,17.0000000000146,16.9999999999854,16,17,16.9999999999854,16.0000000000146,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,7.5"
), C_intpl = c("58.3368399069697,58.249224089011,59.5198368051218,58.8722012497097,58.4418996252205,58.5849059154389,59.2752163985494,52.8407480422202,51.6276603912397,48.0255346632529,44.753541512539,41.4815483618252,38.2095552111114,34.9375620603975,31.6655689096837,28.3935757589698,25.121582608256,19.4712933827274,22.0108873782783,24.5504813738291,24.8441573376901,24.6902151101703,24.4029572181118,24.9753161974674,24.8664406826514,24.8486668451201,25.1137001504163,25.1142578332509,25.4902077628339,25.4075561268027,25.6622548410237,61.2421678149908,25.1600975771354,25.6667198263373,25.442560744158,25.8736383423437,25.5859074180431,24.7860400673889,24.4337707697216,24.3214953242744,23.915753514736,23.7363185577661,23.7186569801299,23.4313514771952,23.5730151254578,62.5124513171595,23.3260531660862,23.4498217326665,23.2145314844252,57.5586745434594,63.4646233226955,23.0706406704345,23.3318690599491,62.044649715831,62.2720656330432,22.2532276715887,62.7059140614625,22.9511208849958,22.5603175709988,23.3456453893988,63.2523901625561,60.6655429980934,60.2358824325868,59.957910796633,57.3999702562457,54.8277282980263,43.0269305132552,31.2261327284841,19.425334943713,22.7319906068577,26.0386462700023",
"26.0386462700023,29.345301933147,32.6519575962917,35.9586132594364,48.3773995023798,60.7961857453232,49.4980424442242,55.9907960862667,57.2956837917999,58.1409925994177,59.025022056064,60.0098263540792,60.4028460580062,61.2629030450653,55.9298614021542",
"55.9298614021542,55.3877180252389,61.3547152702855,61.7847919095391,56.2457623439544,62.5477315546977,62.3078007189967,62.4272469013149,57.6479672147315,62.9844338801191,58.0081708266629,63.3872796098875,59.0138830718112,58.0612924481098,58.38680047729,58.687179350318,63.8724230039733,63.4126777597892,63.6865154626743,63.5670658627636,63.4496590540706,63.7595297692908,58.9069708176601,63.4547681163061,64.3198376700797,63.415319961042,64.0985879957056,64.1201809531605,63.677902665454,64.1934303628317,64.4682003346273,64.2868853545462,24.8444135816353,64.1579626357752,63.8897139146875,58.5472675827292,64.5784992977498,64.0848591719068,63.8841268679761,64.2901359712354,64.395692486112,64.5425896391638,64.8060565909917,64.3618830026368,64.7088481705444,64.5005944199885,64.5540289192148,64.7408010459365,63.378880767685,63.3415589069662,63.5362700331647,63.5924807719723,63.575801461932,63.6799360982113,64.0041021410894,64.3144923757986,63.8692943755376,63.8594574363473,64.2731841085802,63.3314657812309,64.2758880216293,64.1011768977101,64.0261661917799,64.2865302330478,63.724697791255,64.1202175712152"
), C_dur = c("14,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,14",
"3,17,16,17,17,16,17,17,16,17,17,16,17,17,8", "8,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,17,16,17,2"
)), row.names = c(NA, -3L), groups = structure(list(Sequ = 2L,
.rows = structure(list(1:3), ptype = integer(0), class = c("vctrs_list_of",
"vctrs_vctr", "list"))), row.names = c(NA, -1L), class = c("tbl_df",
"tbl", "data.frame"), .drop = TRUE), class = c("grouped_df",
"tbl_df", "tbl", "data.frame"))

There's a possible solution with use of grid.arrange() func from library(gridExtra) library(grid) packages.
I've wrapped your data into unique charts and combined them together into arranged chart.
df1 = df0 %>%
pivot_longer(cols = contains("_"),
names_to = c("Event_by", ".value"),
names_pattern = "^(.*)_([^_]+$)") %>%
separate_rows(c(intpl, dur), sep = ",", convert = TRUE) %>%
mutate(Time = cumsum(dur)) %>%
mutate(Utterance = paste0(sub(".*(.)$", "\\1",Speaker), ": ", Utterance),
Utterance = factor(Utterance, levels = unique(Utterance)))
Set chart objects into enviroment:
for (i in unique(df1$Event_by)){
for (j in levels(df1$Utterance)){
assign(x = paste0(i,j), value = ggplot(data = df1[df1$Event_by == i & df1$Utterance == j,], aes(x = Time, y = log2(intpl))) +
geom_line()+
geom_smooth(method = 'lm', color = "red", formula = y~x))
}
}
Create grided chart:
library(gridExtra) library(grid)
grid.arrange(
`AA: cool >what part?<`,
`AB: u:m Tennessee=` ,
`ANA: (0.228)` ,
`BA: cool >what part?<` ,
`BB: u:m Tennessee=` ,
`BNA: (0.228)` ,
`CA: cool >what part?<` ,
`CB: u:m Tennessee=` ,
`CNA: (0.228)` ,
nrow = 3)
Although i think there should be better solution for that.
You can also try to explore below articlesfor arranging plots:
http://www.sthda.com/english/articles/24-ggpubr-publication-ready-plots/81-ggplot2-easy-way-to-mix-multiple-graphs-on-the-same-page/
https://ggplot2-book.org/facet.html
Moreover, there's is no themming added to my solution

How to reorder a graph with multiple variable based on one value?

I am trying to reorder the following graph based on the rank of the lowest confidence interval (conf.low). This means that Austria (AU) should be the first country, Bulgaria (BG) the second and Belgium (BE) the third. I know there is a way to do it manually by choosing the order of the country variable but i prefer to find a way to do it automatically since i have 30 countries. Could someone help?
Here is the data and the code:
df= structure(list(cntry = structure(1:3, .Label = c("AU", "BE",
"BG"), class = "factor"), estimate = c(0.0053, 0.01740,
0.0036), conf.low = c(-0.0257, 0.0005,
-0.0006), conf.high = c(0.0365, 0.0343,
0.0079)), row.names = c(NA, -3L), class = "data.frame")
df %>%
arrange(estimate) %>%
mutate(label = replace(round(estimate, 3),cntry==1, '')) %>%
ggplot(aes(estimate, cntry,label=label)) +
geom_point()+
geom_text(vjust= -1) +
geom_linerange(mapping=aes(xmin=conf.low , xmax=conf.high, y=cntry)) +
geom_point(mapping=aes(x=estimate, y=cntry))

Using forcats::fct_reorder() you could do this:
library(dplyr)
library(ggplot2)
library(forcats)
df %>%
arrange(estimate) %>%
mutate(label = replace(round(estimate, 3), cntry==1, '')) %>%
ggplot(aes(estimate, fct_reorder(cntry, conf.low, .desc = TRUE),label=label)) +
geom_point()+
geom_text(vjust= -1) +
geom_linerange(mapping=aes(xmin=conf.low , xmax=conf.high, y=cntry)) +
geom_point(mapping=aes(x=estimate, y=cntry))+
ylab("Country")
Created on 2021-04-22 by the reprex package (v2.0.0)
data
df= structure(list(cntry = structure(1:3, .Label = c("AU", "BE",
"BG"), class = "factor"), estimate = c(0.0053, 0.01740,
0.0036), conf.low = c(-0.0257, 0.0005,
-0.0006), conf.high = c(0.0365, 0.0343,
0.0079)), row.names = c(NA, -3L), class = "data.frame")

Merging data frames to plot multiple time series using plyr

I want to plot multiple time series on one plot. Currently I can plot them all individually but not together. How can I join the data because the years are split by decimals.
What I basically want to end up with is this Plotting multiple time-series in ggplot (See plot in the first answer)
library(tidyverse)
library(plyr)
theme_set(theme_bw(10))
Sydney1<-read.csv("Sydney1.csv",header=TRUE)
Sydney2<-read.csv("Sydney2.csv",header=TRUE)
Eden<-read.csv("Eden.csv",header=TRUE)
StonyBay<-read.csv("Stonybay.csv",header=TRUE)
LowHead<-read.csv("Lowhead.csv",header=TRUE)
Hobart<-read.csv("Hobart.csv",header=TRUE)
Devonport<-read.csv("Devonport.csv",header=TRUE)
Freemantle<-read.csv("Freemantle.csv",header=TRUE)
ggplot(Sydney1,aes(x=Year,y=SLR))+geom_line(aes(color="Sydney1"))
ggplot(Sydney2,aes(x=Year,y=SLR))+geom_line(aes(color="Sydney2"))
ggplot(Eden,aes(x=Year,y=SLR))+geom_line(aes(color="Eden"))
ggplot(StonyBay,aes(x=Year,y=SLR))+geom_line(aes(color="StonyBay"))
ggplot(LowHead,aes(x=Year,y=SLR))+geom_line(aes(color="Lowhead"))
ggplot(Hobart,aes(x=Year,y=SLR))+geom_line(aes(color="Hobart"))
ggplot(Devonport,aes(x=Year,y=SLR))+geom_line(aes(color="Devonport"))
ggplot(Freemantle,aes(x=Year,y=SLR))+geom_line(aes(color="Freemantle"))
#Sydney 1
structure(list(Year = c(1886.0417, 1886.125, 1886.2083, 1886.2917,
1886.375, 1886.4583), SLR = c(6819L, 6942L, 6980L, 6958L, 7015L,
6892L)), row.names = c(NA, 6L), class = "data.frame")
#Sydney 2
structure(list(Year = c(1914.4583, 1914.5417, 1914.625, 1914.7083,
1914.7917, 1914.875), SLR = c(7022L, 6963L, 6915L, 6924L, 6866L,
6956L)), row.names = c(NA, 6L), class = "data.frame")
#Eden
structure(list(Year = c(1986.7917, 1986.875, 1986.9583, 1987.0417,
1987.125, 1987.2083), SLR = c(7003L, 6942L, 6969L, 7067L, NA,
7015L)), row.names = c(NA, 6L), class = "data.frame")
#Stony Bay
structure(list(Year = c(1993.0417, 1993.125, 1993.2083, 1993.2917,
1993.375, 1993.4583), SLR = c(6826L, 6868L, 6796L, 6862L, 6893L,
6951L)), row.names = c(NA, 6L), class = "data.frame")
#Low head
structure(list(Year = c(2010.125, 2010.2083, 2010.2917, 2010.375,
2010.4583, 2010.5417), SLR = c(6971L, 6968L, 7030L, 7088L, 7063L,
7035L)), row.names = c(NA, 6L), class = "data.frame")
#Hobart
structure(list(Year = c(1987.875, 1987.9583, 1988.0417, 1988.125,
1988.2083, 1988.2917), SLR = c(6916L, 6870L, 6930L, 6870L, 6820L,
6817L)), row.names = c(NA, 6L), class = "data.frame")
#Devonport
structure(list(Year = c(1989.875, 1989.9583, 1990.0417, 1990.125,
1990.2083, 1990.2917), SLR = c(6976L, 7025L, 7030L, 7046L, 6999L,
7055L)), row.names = c(NA, 6L), class = "data.frame")
#Freemantle
structure(list(Year = c(1897.0417, 1897.125, 1897.2083, 1897.2917,
1897.375, 1897.4583), SLR = c(6542L, 6524L, 6557L, 6655L, 6648L,
6729L)), row.names = c(NA, 6L), class = "data.frame")

Using the data in the Note at the end first accumulate the series in a list L -- we assume any data frame having column names Year and SLR is to be added -- and then convert that to a single zoo object and plot it using autoplot.zoo which uses ggplot2. Remove the facet = NULL argument if you want them plotted in separate facets.
library(ggplot2)
library(zoo)
is_city_df <- function(x) is.data.frame(x) && identical(names(x), c("Year", "SLR"))
L <- Filter(is_city_df, mget(ls()))
z <- do.call("merge", lapply(L, read.zoo))
autoplot(z, facet = NULL)
Note
We assume the following inputs:
Sydney1 <-
structure(list(Year = c(1886.0417, 1886.125, 1886.2083, 1886.2917,
1886.375, 1886.4583), SLR = c(6819L, 6942L, 6980L, 6958L, 7015L,
6892L)), row.names = c(NA, 6L), class = "data.frame")
Sydney2 <-
structure(list(Year = c(1914.4583, 1914.5417, 1914.625, 1914.7083,
1914.7917, 1914.875), SLR = c(7022L, 6963L, 6915L, 6924L, 6866L,
6956L)), row.names = c(NA, 6L), class = "data.frame")
Eden <-
structure(list(Year = c(1986.7917, 1986.875, 1986.9583, 1987.0417,
1987.125, 1987.2083), SLR = c(7003L, 6942L, 6969L, 7067L, NA,
7015L)), row.names = c(NA, 6L), class = "data.frame")
Freemantle <-
structure(list(Year = c(1897.0417, 1897.125, 1897.2083, 1897.2917,
1897.375, 1897.4583), SLR = c(6542L, 6524L, 6557L, 6655L, 6648L,
6729L)), row.names = c(NA, 6L), class = "data.frame")

Assuming that your global environment only contains the dataframes you want to plot:
bind_rows(mget(ls()), .id = "City") %>%
ggplot(aes(x = Year, y = SLR, color = City)) +
geom_line()

Instead of creating multiple objects in the global env, it can be read all at once in a loop
library(dplyr)
library(purrr)
library(ggplot2)
library(readr)
files <- c("Sydney1.csv", "Sydney2.csv", "Eden.csv", "Stonybay.csv",
"Lowhead.csv", "Hobart.csv", "Devonport.csv", "Freemantle.csv")
map_dfr(files, ~ read_csv(.x) %>%
mutate(City = .x)) %>%
ggplot(aes(x = Year, y = SLR, color = City)) +
geom_line())

Try this:
Sydney1 %>% mutate(city = 'sydney1') %>%
bind_rows(Sydney2 %>% mutate(city = 'sydney2')) %>%
bind_rows(Eden %>% mutate(city = 'eden')) %>%
bind_rows(Freemantle %>% mutate(city = 'freemantle')) %>%
ggplot(aes(x=Year, y=SLR, color=city)) + geom_line() + facet_wrap(~city, scale='free')

How to plot layers of tupples on same plot in R?

I am trying to plot the time and NDVI for each region on the same plot. I think to do this I have to convert the date column from characters to time and then plot each layer. However I cannot figure out how to do this. Any thoughts?
list(structure(list(observation = 1L, HRpcode = NA_character_,
timeseries = NA_character_), row.names = c(NA, -1L), class = c("tbl_df",
"tbl", "data.frame")), structure(list(observation = 1:6, time = c("2014-01-01",
"2014-02-01", "2014-03-01", "2014-04-01", "2014-05-01", "2014-06-01"
), ` NDVI` = c("0.3793765496776215", "0.21686891782421552", "0.3785652933528299",
"0.41027240624704164", "0.4035578030242673", "0.341299793064468"
)), row.names = c(NA, -6L), class = c("tbl_df", "tbl", "data.frame"
)), structure(list(observation = 1:6, time = c("2014-01-01",
"2014-02-01", "2014-03-01", "2014-04-01", "2014-05-01", "2014-06-01"
), ` NDVI` = c("0.4071076986818826", "0.09090719657570319", "0.35214166081795284",
"0.4444311032927228", "0.5220702877666005", "0.5732370503295022"
)), row.names = c(NA, -6L), class = c("tbl_df", "tbl", "data.frame"
)), structure(list(observation = 1:6, time = c("2014-01-01",
"2014-02-01", "2014-03-01", "2014-04-01", "2014-05-01", "2014-06-01"
), ` NDVI` = c("0.3412131556625801", "0.18815996897460135", "0.5218904976415136",
"0.6970128777711452", "0.7229657162729096", "0.535967435470161"
)), row.names = c(NA, -6L), class = c("tbl_df", "tbl", "data.frame"
)))
111

First we need to clean your data. The first element in this list is empty
df = df[-1]
Now we need to make a data.frame
df = do.call(rbind, df)
I am going to add a region variable, change the name of NDVI to remove the space,
change ndvi into a numeric vector, and change time into a Date object
library(dplyr)
df = df %>%
mutate(region = factor(rep(1:3, rep(6, 3)))) %>%
rename(ndvi = ' NDVI') %>%
mutate(ndvi = as.numeric(ndvi)) %>%
mutate(time = as.Date(time))
Now we can use ggplot2 to plot the data by region
library(ggplot2)
g = df %>%
ggplot(aes(x = time, y = ndvi, col = region)) +
geom_line()
g
Which gives this plot:

Here's an approach with lubridate to handle dates and dplyr to make the binding of the data.frames easier to understand.
Note that the group names are taken from the names of the list, and since those don't exist in the data you provided, we have to set them in advance.
library(lubridate)
library(ggplot2)
library(dplyr)
names(data) <- 1:3
data <- bind_rows(data, .id = "group")
data$time <- ymd(data$time)
setnames(data," NDVI","NDVI")
data$NDVI <- as.numeric(data$NDVI)
ggplot(data, aes(x=time,y=NDVI,color=Group)) + geom_line()

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