how to create a date variable from a long string [duplicate] - r

This question already has answers here:
How to convert a String to Date in R
(3 answers)
Closed 2 years ago.
I have a data.frame that looks like this:
samples data can be build using codes:
df<-structure(list(LSAF..Date.acted.On. = structure(c(33L, 18L, 7L,
32L, 51L, 47L, 2L, 45L, 38L, 15L), .Label = c("Aug 13, 2019, 10:44:07 AM GMT-04:00",
"Aug 13, 2019, 10:45:47 AM GMT-04:00", "Aug 13, 2019, 10:47:20 AM GMT-04:00",
"Aug 13, 2019, 10:53:29 AM GMT-04:00", "Aug 13, 2019, 10:54:54 AM GMT-04:00",
"Aug 13, 2019, 10:57:11 AM GMT-04:00", "Aug 13, 2019, 10:58:13 AM GMT-04:00",
"Feb 13, 2020, 1:13:07 PM GMT-05:00", "Feb 13, 2020, 1:17:07 PM GMT-05:00",
"Feb 22, 2019, 11:13:51 AM GMT-05:00", "Jan 28, 2020, 11:19:19 AM GMT-05:00",
"Jan 28, 2020, 11:21:28 AM GMT-05:00", "Jan 7, 2020, 9:59:28 AM GMT-05:00",
"Jul 13, 2020, 9:17:01 PM GMT-04:00", "Jul 15, 2020, 9:08:54 PM GMT-04:00",
"Jul 18, 2019, 11:15:26 AM GMT-04:00", "Jul 23, 2020, 10:50:32 AM GMT-04:00",
"Mar 5, 2020, 10:00:07 AM GMT-05:00", "Mar 5, 2020, 10:01:22 AM GMT-05:00",
"Mar 5, 2020, 9:56:36 AM GMT-05:00", "Mar 5, 2020, 9:58:31 AM GMT-05:00",
"Mar 6, 2020, 1:17:17 PM GMT-05:00", "May 13, 2019, 11:07:52 AM GMT-04:00",
"May 14, 2019, 2:32:40 PM GMT-04:00", "May 16, 2019, 3:46:08 PM GMT-04:00",
"May 16, 2019, 4:23:27 PM GMT-04:00", "May 16, 2019, 4:25:40 PM GMT-04:00",
"May 16, 2019, 4:29:12 PM GMT-04:00", "May 16, 2019, 4:40:58 PM GMT-04:00",
"May 21, 2019, 2:22:07 PM GMT-04:00", "Nov 13, 2020, 4:14:55 PM GMT-05:00",
"Nov 13, 2020, 4:21:06 PM GMT-05:00", "Nov 13, 2020, 4:24:07 PM GMT-05:00",
"Nov 13, 2020, 9:10:19 AM GMT-05:00", "Nov 24, 2020, 10:51:52 AM GMT-05:00",
"Oct 15, 2020, 3:46:52 PM GMT-04:00", "Oct 15, 2020, 3:48:35 PM GMT-04:00",
"Oct 17, 2019, 9:09:20 PM GMT-04:00", "Oct 18, 2019, 11:15:51 AM GMT-04:00",
"Oct 20, 2020, 1:28:57 PM GMT-04:00", "Oct 26, 2020, 1:52:26 PM GMT-04:00",
"Oct 26, 2020, 2:15:11 PM GMT-04:00", "Oct 29, 2019, 1:55:53 PM GMT-04:00",
"Oct 9, 2019, 10:39:10 AM GMT-04:00", "Oct 9, 2019, 10:45:14 AM GMT-04:00",
"Sep 11, 2020, 2:40:34 PM GMT-04:00", "Sep 19, 2019, 2:45:46 PM GMT-04:00",
"Sep 23, 2019, 2:24:01 PM GMT-04:00", "Sep 9, 2019, 10:16:01 AM GMT-04:00",
"Sep 9, 2019, 10:22:23 AM GMT-04:00", "Sep 9, 2019, 10:25:03 AM GMT-04:00",
"Sep 9, 2019, 10:32:44 AM GMT-04:00"), class = "factor")), row.names = c(NA,
10L), class = "data.frame")
How can I modify the data so it can be used as a date variable?
Thanks.


You can use lubridate's mdy_hms
df$date_time <- lubridate::mdy_hms(df$LSAF..Date.acted.On.)
df$date <- as.Date(df$date_time)
head(df)
#. LSAF..Date.acted.On. date_time date
#1 Nov 13, 2020, 4:24:07 PM GMT-05:00 2020-11-13 21:24:07 2020-11-13
#2 Mar 5, 2020, 10:00:07 AM GMT-05:00 2020-03-05 15:00:07 2020-03-05
#3 Aug 13, 2019, 10:58:13 AM GMT-04:00 2019-08-13 14:58:13 2019-08-13
#4 Nov 13, 2020, 4:21:06 PM GMT-05:00 2020-11-13 21:21:06 2020-11-13
#5 Sep 9, 2019, 10:25:03 AM GMT-04:00 2019-09-09 14:25:03 2019-09-09
#6 Sep 19, 2019, 2:45:46 PM GMT-04:00 2019-09-19 18:45:46 2019-09-19


You could try
as.Date(df$LSAF..Date.acted.On.,
format = "%b %d, %Y, %I:%M:%S %p")

Related

How can I reshape date column in a dataframe?

I want to reshape my Date column in the same months-wise. For example, the first 12 rows in the Date column of the dataframe contains a character of all the months in the year 2001 and the respective year itself. The next rows are the same, until the year 2017.
Therefore. I want to reshape my data like the following. For example, I want all Januaries of the all years to be in the first rows of Date column, then all februaries in the next rows, Marches of the all years and so on, until December of all years (2001-2017)
I need like this format:
1 2001 1
2 2002 1
3 2003 1
4 2004 1
5 2005 1
6 2006 1
7 2007 1
8 2008 1
9 2009 1
10 2010 1
11 2011 1
12 2012 1
13 2013 1
14 2014 1
15 2015 1
16 2016 1
17 2017 1
18 2001 2
19 2002 2
20 2003 2
21 2004 2
22 2005 2
23 2006 2
24 2007 2
This is my dataframe I generated using dput()
#load packages that might be required
> library(tidyverse)
> library(xts)
> # Read NDVI
> NDVI <- read.csv("processed//NDVI.csv")
> dput(NDVI)
structure(list(Date = c("Jan 1, 2001", "Feb 1, 2001", "Mar 1, 2001",
"Apr 1, 2001", "May 1, 2001", "Jun 1, 2001", "Jul 1, 2001", "Aug 1, 2001",
"Sep 1, 2001", "Oct 1, 2001", "Nov 1, 2001", "Dec 1, 2001", "Jan 1, 2002",
"Feb 1, 2002", "Mar 1, 2002", "Apr 1, 2002", "May 1, 2002", "Jun 1, 2002",
"Jul 1, 2002", "Aug 1, 2002", "Sep 1, 2002", "Oct 1, 2002", "Nov 1, 2002",
"Dec 1, 2002", "Jan 1, 2003", "Feb 1, 2003", "Mar 1, 2003", "Apr 1, 2003",
"May 1, 2003", "Jun 1, 2003", "Jul 1, 2003", "Aug 1, 2003", "Sep 1, 2003",
"Oct 1, 2003", "Nov 1, 2003", "Dec 1, 2003", "Jan 1, 2004", "Feb 1, 2004",
"Mar 1, 2004", "Apr 1, 2004", "May 1, 2004", "Jun 1, 2004", "Jul 1, 2004",
"Aug 1, 2004", "Sep 1, 2004", "Oct 1, 2004", "Nov 1, 2004", "Dec 1, 2004",
"Jan 1, 2005", "Feb 1, 2005", "Mar 1, 2005", "Apr 1, 2005", "May 1, 2005",
"Jun 1, 2005", "Jul 1, 2005", "Aug 1, 2005", "Sep 1, 2005", "Oct 1, 2005",
"Nov 1, 2005", "Dec 1, 2005", "Jan 1, 2006", "Feb 1, 2006", "Mar 1, 2006",
"Apr 1, 2006", "May 1, 2006", "Jun 1, 2006", "Jul 1, 2006", "Aug 1, 2006",
"Sep 1, 2006", "Oct 1, 2006", "Nov 1, 2006", "Dec 1, 2006", "Jan 1, 2007",
"Feb 1, 2007", "Mar 1, 2007", "Apr 1, 2007", "May 1, 2007", "Jun 1, 2007",
"Jul 1, 2007", "Aug 1, 2007", "Sep 1, 2007", "Oct 1, 2007", "Nov 1, 2007",
"Dec 1, 2007", "Jan 1, 2008", "Feb 1, 2008", "Mar 1, 2008", "Apr 1, 2008",
"May 1, 2008", "Jun 1, 2008", "Jul 1, 2008", "Aug 1, 2008", "Sep 1, 2008",
"Oct 1, 2008", "Nov 1, 2008", "Dec 1, 2008", "Jan 1, 2009", "Feb 1, 2009",
"Mar 1, 2009", "Apr 1, 2009", "May 1, 2009", "Jun 1, 2009", "Jul 1, 2009",
"Aug 1, 2009", "Sep 1, 2009", "Oct 1, 2009", "Nov 1, 2009", "Dec 1, 2009",
"Jan 1, 2010", "Feb 1, 2010", "Mar 1, 2010", "Apr 1, 2010", "May 1, 2010",
"Jun 1, 2010", "Jul 1, 2010", "Aug 1, 2010", "Sep 1, 2010", "Oct 1, 2010",
"Nov 1, 2010", "Dec 1, 2010", "Jan 1, 2011", "Feb 1, 2011", "Mar 1, 2011",
"Apr 1, 2011", "May 1, 2011", "Jun 1, 2011", "Jul 1, 2011", "Aug 1, 2011",
"Sep 1, 2011", "Oct 1, 2011", "Nov 1, 2011", "Dec 1, 2011", "Jan 1, 2012",
"Feb 1, 2012", "Mar 1, 2012", "Apr 1, 2012", "May 1, 2012", "Jun 1, 2012",
"Jul 1, 2012", "Aug 1, 2012", "Sep 1, 2012", "Oct 1, 2012", "Nov 1, 2012",
"Dec 1, 2012", "Jan 1, 2013", "Feb 1, 2013", "Mar 1, 2013", "Apr 1, 2013",
"May 1, 2013", "Jun 1, 2013", "Jul 1, 2013", "Aug 1, 2013", "Sep 1, 2013",
"Oct 1, 2013", "Nov 1, 2013", "Dec 1, 2013", "Jan 1, 2014", "Feb 1, 2014",
"Mar 1, 2014", "Apr 1, 2014", "May 1, 2014", "Jun 1, 2014", "Jul 1, 2014",
"Aug 1, 2014", "Sep 1, 2014", "Oct 1, 2014", "Nov 1, 2014", "Dec 1, 2014",
"Jan 1, 2015", "Feb 1, 2015", "Mar 1, 2015", "Apr 1, 2015", "May 1, 2015",
"Jun 1, 2015", "Jul 1, 2015", "Aug 1, 2015", "Sep 1, 2015", "Oct 1, 2015",
"Nov 1, 2015", "Dec 1, 2015", "Jan 1, 2016", "Feb 1, 2016", "Mar 1, 2016",
"Apr 1, 2016", "May 1, 2016", "Jun 1, 2016", "Jul 1, 2016", "Aug 1, 2016",
"Sep 1, 2016", "Oct 1, 2016", "Nov 1, 2016", "Dec 1, 2016", "Jan 1, 2017",
"Feb 1, 2017", "Mar 1, 2017", "Apr 1, 2017", "May 1, 2017", "Jun 1, 2017",
"Jul 1, 2017", "Aug 1, 2017", "Sep 1, 2017", "Oct 1, 2017", "Nov 1, 2017",
"Dec 1, 2017"), NDVI = c(0.722, 0.418, 0.435, 0.568, 0.616, 0.75,
0.62, 0.516, 0.389, 0.484, 0.65, 0.7, 0.533, 0.327, 0.279, 0.43,
0.701, 0.797, 0.748, 0.569, 0.597, 0.662, 0.794, 0.706, 0.537,
0.338, 0.404, 0.461, 0.759, 0.76, 0.578, 0.408, 0.56, 0.62, 0.684,
0.785, 0.539, 0.442, 0.307, 0.461, 0.593, 0.739, 0.674, 0.495,
0.603, 0.712, 0.776, 0.665, 0.522, 0.333, 0.398, 0.28, 0.713,
0.746, 0.757, 0.549, 0.711, 0.685, 0.693, 0.716, 0.617, 0.476,
0.407, 0.325, 0.555, 0.757, 0.622, 0.544, 0.452, 0.586, 0.761,
0.649, 0.635, 0.472, 0.351, 0.402, 0.662, 0.757, 0.712, 0.69,
0.618, 0.632, 0.797, 0.778, 0.543, 0.401, 0.393, 0.556, 0.68,
0.784, 0.659, 0.654, 0.412, 0.653, 0.694, 0.727, 0.715, 0.55,
0.641, 0.443, 0.709, 0.818, 0.646, 0.59, 0.39, 0.562, 0.67, 0.56,
0.476, 0.312, 0.349, 0.405, 0.705, 0.766, 0.665, 0.577, 0.614,
0.518, 0.718, 0.779, 0.792, 0.547, 0.585, 0.373, 0.605, 0.715,
0.779, 0.758, 0.751, 0.77, 0.752, 0.805, 0.521, 0.471, 0.561,
0.595, 0.688, 0.74, 0.77, 0.69, 0.704, 0.613, 0.653, 0.803, 0.63,
0.472, 0.589, 0.512, 0.562, 0.699, 0.814, 0.637, 0.395, 0.462,
0.419, 0.742, 0.498, 0.35, 0.308, 0.321, 0.597, 0.677, 0.729,
0.526, 0.394, 0.567, 0.806, 0.752, 0.703, 0.495, 0.453, 0.48,
0.593, 0.731, 0.799, 0.619, 0.403, 0.396, 0.556, 0.743, 0.717,
0.504, 0.408, 0.356, 0.215, 0.68, 0.487, 0.594, 0.392, 0.566,
0.547, 0.632, 0.604, 0.528, 0.424, 0.627, 0.448, 0.788, 0.764,
0.592, 0.517, 0.274, 0.577, 0.754)), class = "data.frame", row.names = c(NA,
-204L))

library(dplyr)
library(tidyr)
library(lubridate)
df %>%
mutate(Date = mdy(Date)) %>%
separate(Date, into = c("year", "month", "day"), remove = FALSE) %>%
arrange(month, day, year)
# Date year month day NDVI
# 1 2001-01-01 2001 01 01 0.722
# 2 2002-01-01 2002 01 01 0.533
# 3 2003-01-01 2003 01 01 0.537
# 4 2004-01-01 2004 01 01 0.539
# 5 2005-01-01 2005 01 01 0.522
# 6 2006-01-01 2006 01 01 0.617
# ...
This is not generally called a "reshaping" operation - this is sorting/ordering/arranging rows. Reshaping/pivoting is when something that is a column becomes a row, or vice versa.

Merging of two datasets of different lenghts

I'm trying to merge two datasets I have.
df1:
day
month
year
lon
lat
month-year
3
5
2009
5.7
53.9
May 2009
8
9
2004
6.9
52.6
Sep 2004
15
9
2004
3.8
50.4
Sep 2004
5
5
2009
2.7
51.2
May 2009
28
7
2005
14.8
62.4
Jul 2005
18
9
2004
5.1
52.5
Sep 2004
df2:
nao-value
sign
month-year
- 2.1
Negative
Sep 2004
1.3
Positive
Jul 2005
- 1.1
Negative
May 2009
I want to merge this to add the NAO value for each month and year in the occurrence data, meaning i want the NAO value for each specific month repeated for all registrations of that month in the occurrence data.
Problem is I cannot get the NAO values to line up where it should by the occurrence data, its either placed just repetitive and not aligned with the date it should, given as month-year.x and month-year.y ,or it is given back as NA value.
I have tried a few different approaches:
df3 <- merge(df1, df2, by="month-year")
df3 <- merge(cbind(df1, X=rownames(df1)), cbind(df2, variable=rownames(df2)))
df3 <- merge(df1,df2, by ="month-year", all.x = TRUE,all.y=TRUE, sort = FALSE)
df3 <- merge(df1, df2, by=intersect(df1$month-year(df1), df2$month-year(df2)))
But not of those give the result I desire.
Edit to include dput:
dput(head(df1, 10)) :
structure(list(Day = c(29, 2, 14, 31, 16, 7, 25, 12, 21, 22),
Month = c(7, 7, 7, 8, 8, 7, 8, 6, 6, 9), Year = c(2010, 2015,
2010, 2018, 2016, 2018, 2019, 2004, 2015, 2019), Lon = c(-6.155014,
-5.820868, -5.509842, -5.495277, -5.469389, -5.469389, -5.469389,
-5.466995, -5.461942, -5.457127), Lat = c(59.09478, 59.125228,
57.959196, 57.96022, 57.986825, 57.986825, 57.986825, 57.874527,
57.95972, 58.07697), Date = c("Jul 2010", "Jul 2015", "Jul 2010",
"Aug 2018", "Aug 2016", "Jul 2018", "Aug 2019", "Jun 2004",
"Jun 2015", "Sep 2019")), row.names = c(NA, -10L), class =
c("tbl_df",
"tbl", "data.frame"))
dput(head(df2, 10)) :
structure(list(NAO = c(1.04, 1.41, 1.46, 2, -1.53, -0.02, 0.53,
0.97, 1.06, 0.23), Sign = c("Positive", "Positive", "Positive",
"Positive", "Negative", "Negative", "Positive", "Positive",
"Positive",
"Positive"), Date = c("jan 1990", "feb 1990", "mar 1990", "apr 1990",
"mai 1990", "jun 1990", "jul 1990", "aug 1990", "sep 1990", "okt
1990"
)), row.names = c(NA, -10L), class = c("tbl_df", "tbl", "data.frame"
))

merge function is case sensitive. You have different cases in two dataframes that you are merging. Make the case in both the dataframe same and then perform the merge. Try -
result <- merge(transform(df1, Date = tolower(Date)), df2, by = 'Date')

Using tidyverse
library(dplyr)
df1 %>%
mutate(Date = tolower(Date)) %>%
inner_join(df2, by = 'Date')

How to show year only where necessary on date axis

I'm writing code in R that uses ggplot2 to generate several bar graphs based on test data from several trainings, spanning (at present) about a year, like the following:
Currently all the dates are formatted "mon DD YYYY" ("%b %d %Y" as a Date format):
c("Oct 05 2020", "Nov 02 2020", "Nov 30 2020", "Jan 11 2021", "Feb 22 2021",
"Mar 08 2021", "Mar 29 2021", "Apr 12 2021", "May 03 2021", "May 17 2021")
But I'd like to only display the year on the first date, and any subsequent dates that are the first date in a year:
c("Oct 05 2020", "Nov 02", "Nov 30", "Jan 11 2021", "Feb 22", "Mar 08", "Mar 29",
"Apr 12", "May 03", "May 17")
Is there a way to do this, either via some kind of filtering of the Date column or something in ggplot?

We could convert the vector of date into Date class ('v1'), extract the 'Year' component, create a logical vector with duplicated, use that index ('i1') to replace the values in the original vector with formatted Dates from 'v2'
v2 <- as.Date(v1, '%b %d %Y')
i1 <- duplicated(format(v2, '%Y'))
v1[i1] <- format(v2[i1], '%b %d')
-ouptut
v1
[1] "Oct 05 2020" "Nov 02" "Nov 30"
[4] "Jan 11 2021" "Feb 22" "Mar 08" "Mar 29"
[8] "Apr 12" "May 03" "May 17"
data
v1 <- c("Oct 05 2020", "Nov 02 2020", "Nov 30 2020", "Jan 11 2021", "Feb 22 2021",
"Mar 08 2021", "Mar 29 2021", "Apr 12 2021", "May 03 2021", "May 17 2021")

Converting date formats from one class to another

I have the following dates.
c("Aug 08, 2017", "Aug 09, 2017", "Aug 11, 2017", "Aug 11, 2017",
"Aug 10, 2017", "Sep 22, 2017", "Aug 11, 2017", "Aug 11, 2017",
"Aug 11, 2017", "Aug 14, 2017", "Aug 16, 2017", "Aug 16, 2017",
"Aug 18, 2017", "Aug 18, 2017", "Aug 18, 2017", "Sep 20, 2017",
"Aug 22, 2017", "Sep 20, 2017", "Sep 14, 2017", "Sep 25, 2017"
)
I am trying to convert them into the following format:
structure(c(17386, 17387, 17388, 17389, 17392, 17393, 17394,
17395, 17396, 17399, 17400, 17401, 17402, 17403, 17406, 17407,
17408, 17409, 17410, 17414), class = "Date")
Which looks like;
[1] "2017-08-08" "2017-08-09" "2017-08-10" "2017-08-11" "2017-08-14" "2017-08-15" "2017-08-16" "2017-08-17"
[9] "2017-08-18" "2017-08-21" "2017-08-22" "2017-08-23" "2017-08-24" "2017-08-25" "2017-08-28" "2017-08-29"
[17] "2017-08-30" "2017-08-31" "2017-09-01" "2017-09-05"
How can I convert characters to date format?
EDIT:
I run the following;
> C=c("Aug 08, 2017", "Aug 09, 2017", "Aug 11, 2017", "Aug 11, 2017",
+ "Aug 10, 2017", "Sep 22, 2017", "Aug 11, 2017", "Aug 11, 2017",
+ "Aug 11, 2017", "Aug 14, 2017", "Aug 16, 2017", "Aug 16, 2017",
+ "Aug 18, 2017", "Aug 18, 2017", "Aug 18, 2017", "Sep 20, 2017",
+ "Aug 22, 2017", "Sep 20, 2017", "Sep 14, 2017", "Sep 25, 2017"
+ )
> as.numeric(as.Date(C,format='%B %d, %Y'))
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> as.Date(C,format='%B %d, %Y')
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
EDIT:
The following also does not work;
date <- gsub(",", "", date)
date <- gsub(" ", "-", date)
date
as.numeric(as.Date(date, format='%b %d, %Y'))
EDIT:
The following seems to work;
mdy(C)
Giving;
[1] "2017-08-08" "2017-08-09" "2017-08-11" "2017-08-11" "2017-08-10" "2017-09-22" "2017-08-11" "2017-08-11"
[9] "2017-08-11" "2017-08-14" "2017-08-16" "2017-08-16" "2017-08-18" "2017-08-18" "2017-08-18" "2017-09-20"
[17] "2017-08-22" "2017-09-20" "2017-09-14" "2017-09-25"

You need using the format in as.Date
as.numeric(as.Date(C,format='%B %d, %Y'))
[1] 17386 17387 17389 17389 17388 17431 17389 17389 17389 17392 17394 17394 17396 17396 17396 17429 17400 17429 17423 17434
as.Date(C,format='%B %d, %Y')
[1] "2017-08-08" "2017-08-09" "2017-08-11" "2017-08-11" "2017-08-10" "2017-09-22" "2017-08-11" "2017-08-11" "2017-08-11" "2017-08-14" "2017-08-16"
[12] "2017-08-16" "2017-08-18" "2017-08-18" "2017-08-18" "2017-09-20" "2017-08-22" "2017-09-20" "2017-09-14" "2017-09-25"
Dinput:
C=c("Aug 08, 2017", "Aug 09, 2017", "Aug 11, 2017", "Aug 11, 2017",
"Aug 10, 2017", "Sep 22, 2017", "Aug 11, 2017", "Aug 11, 2017",
"Aug 11, 2017", "Aug 14, 2017", "Aug 16, 2017", "Aug 16, 2017",
"Aug 18, 2017", "Aug 18, 2017", "Aug 18, 2017", "Sep 20, 2017",
"Aug 22, 2017", "Sep 20, 2017", "Sep 14, 2017", "Sep 25, 2017"
)

Change factor to Datetime in R

I have a factor variable which I would to transform in Date. When I try using as.Date() It shows me the error:
Error in charToDate(x) :
character string is not in a standard unambiguous format
My data are these:
[1] Aug 31, 2018 Aug 30, 2018 Aug 29, 2018 Aug 28, 2018 Aug 27, 2018 Aug 26, 2018
[7] Aug 25, 2018 Aug 24, 2018 Aug 23, 2018 Aug 22, 2018 Aug 21, 2018 Aug 20, 2018
[13] Aug 19, 2018 Aug 18, 2018 Aug 17, 2018 Aug 16, 2018 Aug 15, 2018 Aug 14, 2018
[19] Aug 13, 2018 Aug 12, 2018 Aug 11, 2018 Aug 10, 2018 Aug 09, 2018 Aug 08, 2018
[25] Aug 07, 2018 Aug 06, 2018 Aug 05, 2018 Aug 04, 2018 Aug 03, 2018 Aug 02, 2018
How could I transform in Date in the format %d-%m-%Y?

Try with format = "%b %d, %Y":
ss <- c("Aug 31, 2018", "Aug 30, 2018", "Aug 29, 2018", "Aug 28, 2018", "Aug 27, 2018", "Aug 26, 2018")
as.Date(ss, format = "%b %d, %Y")
#[1] "2018-08-31" "2018-08-30" "2018-08-29" "2018-08-28" "2018-08-27"
#[6] "2018-08-26"
For details what the different conversion specifications (e.g. "%b", "%Y" etc.) mean, take a look at ?strptime.
By the way, there is no need to manually convert from factor to character, because as.Date has a method for factors which converts factors to character vectors, see as.Date.factor.

specify the format within the function as.Date
as.Date(MyData, format="%b %d, %Y")

I've solved the problem getting this code Sys.setlocale("LC_TIME", "English") into the console!

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