I am trying to plot date wise multi-variate data along with a independent variable on the top axes. To do so - I merged my multi-variate (response variables) dataframe with the single input (independent variable) into a single data frame. The resulting dataframe now has several NA values in rows and columns (for both data sets).
My question:
- Why am I loosing the width / dodge with my current code?
- Does this have to do with NA values in the factored variable in my data?
- How do you work with NA values in a factored variable ? Half my dataset is a completely different variable and needs only 1 column. The only reason I merged them was because I wanted to bring all the data on the same plot (plan was to use grob after this, but I got stuck here)
Before this, I was using this code to plot the geom_bar with the dataframe just with the response variables and it worked.
The dataframe name is final, Factor variable is TYPE which has Open, Shrub and Lowland as categories and NA for the dates which only has the independent variable (in this case Rain)
final$TYPE<-factor(final$TYPE, levels = c("Open", "Shrub","Lowland"))
limits <- aes(ymax = final$Max, ymin = final$Min, ysd= final$SD)
rhg_cols <- c("brown","forestgreen", "cyan4")
p <- ggplot(final, aes(Date, MeanTWC, fill=TYPE), na.rm=F )+
geom_bar(stat="identity", position = "dodge")+
scale_fill_manual(values = rhg_cols)+
scale_x_date(breaks = seq(as.Date("2016-08-15"), as.Date("2017-10-15"), by="30 days"),labels=date_format("%b-%Y"))
p<-p + labs(x="DATE", y ="Total Water in mm")
p<-p + geom_bar(stat = "Identity",
position = "dodge")+
geom_errorbar(limits, position = "dodge", size =0.2)+
ggtitle("Total Water Storage-60cm")+
scale_y_continuous(limits = c(0,100))
p<-p+theme_bw() +theme(axis.text.x = element_text(angle = 270, vjust = 1,
size =15),axis.text.y = element_text(vjust = 1, hjust = 1, size =20),
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_line(linetype="longdash"),
panel.grid.major.y = element_line(linetype = "longdash"))
print(p)
Sample Data:
Date TYPE MeanTWC Max Min Rain
1 2016-08-13 <NA> NA NA NA 27.686
2 2016-08-14 <NA> NA NA NA 79.248
3 2016-08-15 <NA> NA NA NA 9.398
4 2016-08-16 <NA> NA NA NA 9.906
5 2016-08-17 <NA> NA NA NA 26.670
6 2016-08-21 <NA> NA NA NA 52.324
7 2016-08-27 <NA> NA NA NA 13.200
8 2016-08-28 <NA> NA NA NA 0.200
9 2016-08-29 <NA> NA NA NA 3.000
10 2016-08-30 <NA> NA NA NA 0.400
11 2016-09-02 <NA> NA NA NA 5.400
12 2016-09-04 <NA> NA NA NA 22.200
13 2016-09-05 <NA> NA NA NA 0.400
14 2016-09-06 <NA> NA NA NA 0.400
15 2016-09-11 <NA> NA NA NA 0.200
16 2016-09-19 Open 82.40583 94.13074 71.95022 NA
17 2016-09-19 Shrub 75.25720 81.09062 66.31633 NA
18 2016-09-19 Lowland 79.78265 91.46637 71.42791 NA
19 2016-09-24 <NA> NA NA NA 1.200
20 2016-09-28 Open 107.00762 128.82301 87.78908 NA
21 2016-09-28 Shrub 102.29717 114.59530 93.02085 NA
22 2016-09-28 Lowland 100.62097 108.65464 93.06479 NA
23 2016-10-04 Open 94.35146 119.11809 80.80844 NA
24 2016-10-04 Shrub 89.78960 106.59891 77.91514 NA
25 2016-10-04 Lowland 87.66499 98.93036 77.44905 NA
26 2016-10-07 <NA> NA NA NA 15.200
27 2016-10-24 Open 77.75282 90.99799 60.89542 NA
28 2016-10-24 Shrub 73.13549 84.68082 64.38086 NA
29 2016-10-24 Lowland 77.54505 89.20983 68.77503 NA
30 2016-11-04 Open 75.79262 84.63392 61.17391 NA
structure(list(Date = structure(c(17026, 17027, 17028, 17029,
17030, 17034, 17040, 17041, 17042, 17043, 17046, 17048, 17049,
17050, 17055, 17063, 17063, 17063, 17068, 17072, 17072, 17072,
17078, 17078, 17078, 17081, 17098, 17098, 17098, 17109), class = "Date"),
TYPE = structure(c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, 1L, 2L, 3L, NA, 1L, 2L, 3L, 1L, 2L, 3L,
NA, 1L, 2L, 3L, 1L), .Label = c("Open", "Shrub", "Lowland"
), class = "factor"), MeanTWC = c(NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, 82.4058263935714, 75.2571964744444,
79.782649985, NA, 107.0076241875, 102.297170442857, 100.620970785,
94.3514631776471, 89.7895999577778, 87.664985085, NA, 77.75281636125,
73.135492118, 77.54505326, 75.792624628125), Max = c(NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 94.13073642,
81.09062269, 91.46637475, NA, 128.8230145, 114.5952995, 108.6546353,
119.1180866, 106.5989092, 98.93036216, NA, 90.99798892, 84.68081807,
89.20983383, 84.63391564), Min = c(NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, 71.95021894, 66.31632641,
71.42791015, NA, 87.78907749, 93.02084587, 93.06478569, 80.8084363,
77.91514274, 77.44904985, NA, 60.89542395, 64.38086067, 68.77503196,
61.17390712), SD = c(NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, 6.52668534466645, 5.31370742998586,
8.40565594980702, NA, 10.3287869191442, 8.45785409063748,
6.49446280465913, 9.73718805734734, 10.5575933779477, 9.35169762923353,
NA, 8.27219492616507, 6.75450870627616, 8.51146778459709,
6.75447037137946), N = c(NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, 14, 9, 4, NA, 12, 7, 4, 17, 9,
4, NA, 16, 10, 4, 16), SE = c(NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, 1.74433003078718, 1.77123580999529,
4.20282797490351, NA, 2.9816639540851, 3.19676836415673,
3.24723140232956, 2.36161499158505, 3.51919779264923, 4.67584881461676,
NA, 2.06804873154127, 2.13596319872699, 4.25573389229854,
1.68861759284486), Rain = c(27.686, 79.248, 9.398, 9.906,
26.67, 52.324, 13.2, 0.2, 3, 0.4, 5.4, 22.2, 0.4, 0.4, 0.2,
NA, NA, NA, 1.2, NA, NA, NA, NA, NA, NA, 15.2, NA, NA, NA,
NA)), .Names = c("Date", "TYPE", "MeanTWC", "Max", "Min",
"SD", "N", "SE", "Rain"), row.names = c(NA, 30L), class = "data.frame")
