I want to update the year only to 2025 without changing the month day and time
what I have
2027-01-01 09:30:00
2012-03-06 12:00:00
2014-01-01 17:24:00
2020-07-03 04:30:00
2020-01-01 05:50:00
2021-09-03 06:30:00
2013-01-01 23:30:00
2026-01-01 08:30:00
2028-01-01 09:30:00
what i required is below:
2025-01-01 09:30:00
2025-03-06 12:30:00
2025-01-01 17:24:00
2025-07-03 04:30:00
2025-01-01 05:50:00
2025-09-03 06:30:00
2025-01-01 23:30:00
2025-01-01 08:30:00
2025-01-01 09:30:00
I am using dB Browser for SQLite
what i have tried but it didn't worked
update t set
d = datetime(strftime('%Y', datetime(2059)) || strftime('-%m-%d', d));
You may update via a substring operation:
UPDATE yourTable
SET ts = '2025-' || SUBSTR(ts, 6, 14);
Note that SQLite does not actually have a timestamp/datetime type. Instead, these values would be stored as text, and hence we can do a substring operation on them.
Related
I would like a help ... the clinic has several doctors and each one has a specific time of care. Example: 07:00 to 12:00, 12:00 to 17:00, 09:00 to 15:00 ... What is the SQL statement to display only records within the specified time range in the start_time and end_time ?
fields:
start_time | end_time
07:00:00 | 12:30:00
09:00:00 | 15:00:00
12:30:00 | 17:00:00
07:00:00 | 17:00:00
That is, in the morning, display only the records that are part of 07:00:00 to 12:30:00 from the current time. If it's afternoon show only record that are part of 12:30:00 until 17:00:00.
Thankful.
I need help with this issue:
I have a dataset of water level values distributed every 30 minutes, but I need only the hourly values. I tried with the aggregate() function but due to function FUN is one requisite it determines my analysis to be mean, or median and I don't want to use any stat function.
This one example of my data frame
06/16/2015 02:00:00 0.036068
06/16/2015 02:30:00 0.008916
06/16/2015 03:00:00 -0.008622
06/16/2015 03:30:00 -0.014057
06/16/2015 04:00:00 -0.011172
06/16/2015 04:30:00 0.002401
06/16/2015 05:00:00 0.029632
06/16/2015 05:30:00 0.061902002
06/16/2015 06:00:00 0.087366998
06/16/2015 06:30:00 0.105176002
06/16/2015 07:00:00 0.1153
06/16/2015 07:30:00 0.126197994
06/16/2015 08:00:00 0.144154996
We convert the 'RefDateTimeRef' column to POSIXct, extract the 'minute', 'second' with format and compare it with 00:00 to return a logical vector which we use to subset the rows.
df1[format(as.POSIXct(df1[,1], format = "%m/%d/%Y %H:%M"), "%M:%S")=="00:00",]
# RefDateTimeRef Data
#10 04/14/2016 09:00 0.153
#22 04/14/2016 08:00 0.148
Or with lubridate
library(lubridate)
df1[ minute(mdy_hm(df1[,1]))==0,]
# RefDateTimeRef Data
#10 04/14/2016 09:00 0.153
#22 04/14/2016 08:00 0.148
Or with sub to remove the substring until the hour part and then use == to get the logical vector and subset the rows.
df1[ sub(".*\\s+\\S{2}:", "", df1[,1])=="00",]
NOTE: I would advice against using sub or substr as it can sometimes lead to incorrect answers.
df <- read.table(text = '06/16/2015 02:00:00 0.036068
06/16/2015 02:30:00 0.008916
06/16/2015 03:00:00 -0.008622
06/16/2015 03:30:00 -0.014057
06/16/2015 04:00:00 -0.011172
06/16/2015 04:30:00 0.002401
06/16/2015 05:00:00 0.029632
06/16/2015 05:30:00 0.061902002
06/16/2015 06:00:00 0.087366998
06/16/2015 06:30:00 0.105176002
06/16/2015 07:00:00 0.1153
06/16/2015 07:30:00 0.126197994
06/16/2015 08:00:00 0.144154996')
colnames(df) <- c('Date','Time','Value')
index <- ifelse(substring(df$Time,4) == "00:00",T,F)
final_df <- df[index,]
I was working with a time series dataset having hourly data. The data contained a few missing values so I tried to create a dataframe (time_seq) with the correct time value and do a merge with the original data so the missing values become 'NA'.
> data
date value
7980 2015-03-30 20:00:00 78389
7981 2015-03-30 21:00:00 72622
7982 2015-03-30 22:00:00 65240
7983 2015-03-30 23:00:00 47795
7984 2015-03-31 08:00:00 37455
7985 2015-03-31 09:00:00 70695
7986 2015-03-31 10:00:00 68444
//converting the date in the data to POSIXct format.
> data$date <- format.POSIXct(data$date,'%Y-%m-%d %H:%M:%S')
// creating a dataframe with the correct sequence of dates.
> time_seq <- seq(from = as.POSIXct("2014-05-01 00:00:00"),
to = as.POSIXct("2015-04-30 23:00:00"), by = "hour")
> df <- data.frame(date=time_seq)
> df
date
8013 2015-03-30 20:00:00
8014 2015-03-30 21:00:00
8015 2015-03-30 22:00:00
8016 2015-03-30 23:00:00
8017 2015-03-31 00:00:00
8018 2015-03-31 01:00:00
8019 2015-03-31 02:00:00
8020 2015-03-31 03:00:00
8021 2015-03-31 04:00:00
8022 2015-03-31 05:00:00
8023 2015-03-31 06:00:00
8024 2015-03-31 07:00:00
// merging with the original data
> a <- merge(data,df, x.by = data$date, y.by = df$date ,all=TRUE)
> a
date value
4005 2014-07-23 07:00:00 37003
4006 2014-07-23 07:30:00 NA
4007 2014-07-23 08:00:00 37216
4008 2014-07-23 08:30:00 NA
The values I get after merging are incorrect and they contain half-hourly values. What would be the correct approach for solving this?
Why are is the merge result in 30 minute intervals when both my dataframes are hourly?
PS:I looked into this question : Fastest way for filling-in missing dates for data.table and followed the steps but it didn't help.
You can use the padr package to solve this problem.
library(padr)
library(dplyr) #for the pipe operator
data %>%
pad() %>%
fill_by_value()
Hi I am trying to get dates after datetime('now)
My query is not checking against the time value.
I have the following dates :
2015-09-03 18:00:00
2015-09-03 18:00:00
2015-09-10 16:30:00
2015-09-13 09:00:00
2015-09-13 09:00:00
2015-09-13 09:00:00
2015-09-13 09:00:00
2015-09-13 09:00:00
2015-09-13 09:00:00
2015-09-13 09:00:00
2015-09-13 12:05:00
2015-09-13 12:05:00
2015-09-13 12:25:00
2015-09-13 12:25:00
2015-09-13 12:25:00
2015-09-13 16:30:00
2015-09-14 15:10:00
2015-09-14 18:20:00
It seems to ignore the time completely
I can get it to return anything after the 14th, i would expect it to return anything where the time is greater than my startdate (2015-09-14 12:40:39)
public function getRemainingKeysForTimeframe($timeframeID){
$startDate = new \DateTime('now');
$queryBuilder = $this->createQueryBuilder('q')
->select('q')
->andWhere('q.timeframeID = :timeframeID')
->andWhere('q.date >= :start')
->setParameter('timeframeID', $timeframeID)
->setParameter('start', $startDate->format('Y-m-d h:i:s'));
return $queryBuilder;
}
Inject the actual \DateTime object as a parameter in your query builder:
->setParameter('start', $startDate);
not
->setParameter('start', $startDate->format('Y-m-d h:i:s'));
I am trying to subset an xts object of OHLC hourly data with a vector.
If i create the vector myself with the following command
lookup = c("2012-01-12", "2012-01-31", "2012-03-05", "2012-03-19")
testdfx[lookup]
testdfx[lookup]
I get the correct data displayed which shows all the hours that match the dates in the vector (00:00 to 23:00.
> head(testdfx[lookup])
open high low close
2012-01-12 00:00:00 1.27081 1.27217 1.27063 1.27211
2012-01-12 01:00:00 1.27212 1.27216 1.27089 1.27119
2012-01-12 02:00:00 1.27118 1.27166 1.27017 1.27133
2012-01-12 03:00:00 1.27134 1.27272 1.27133 1.27261
2012-01-12 04:00:00 1.27260 1.27262 1.27141 1.27183
2012-01-12 05:00:00 1.27183 1.27230 1.27145 1.27165
> tail(testdfx[lookup])
open high low close
2012-03-19 18:00:00 1.32451 1.32554 1.32386 1.32414
2012-03-19 19:00:00 1.32417 1.32465 1.32331 1.32372
2012-03-19 20:00:00 1.32373 1.32415 1.32340 1.32372
2012-03-19 21:00:00 1.32373 1.32461 1.32366 1.32376
2012-03-19 22:00:00 1.32377 1.32424 1.32359 1.32366
2012-03-19 23:00:00 1.32364 1.32406 1.32333 1.32336
However when I extract a dates from an object and create a vector to use for subsetting I only get the hours of 00:00-19:00 displayed in my subset.
> head(testdfx[dates])
open high low close
2007-01-05 00:00:00 1.3092 1.3093 1.3085 1.3088
2007-01-05 01:00:00 1.3087 1.3092 1.3075 1.3078
2007-01-05 02:00:00 1.3079 1.3091 1.3078 1.3084
2007-01-05 03:00:00 1.3083 1.3084 1.3073 1.3074
2007-01-05 04:00:00 1.3073 1.3080 1.3061 1.3071
2007-01-05 05:00:00 1.3070 1.3072 1.3064 1.3069
> tail(euro[nfp.releases])
open high low close
2014-01-10 14:00:00 1.35892 1.36625 1.35728 1.36366
2014-01-10 15:00:00 1.36365 1.36784 1.36241 1.36743
2014-01-10 16:00:00 1.36742 1.36866 1.36693 1.36719
2014-01-10 17:00:00 1.36720 1.36752 1.36579 1.36617
2014-01-10 18:00:00 1.36617 1.36663 1.36559 1.36624
2014-01-10 19:00:00 1.36630 1.36717 1.36585 1.36702
I have compared both objects containing the require dates and they appear to be the same.
> class(lookup)
[1] "character"
> class(nfp.releases)
[1] "character"
> str(lookup)
chr [1:4] "2012-01-12" "2012-01-31" "2012-03-05" "2012-03-19"
> str(nfp.releases)
chr [1:86] "2014-02-07" "2014-01-10" "2013-12-06" "2013-11-08" ..
I am new to R but have tried everything over the past 3 days to get this to work. If I can't to it this way I will end up having to create a variable by hand but as its got 86 dates this may take some time.
Thanks in advance.
I cannot reproduce your problem
lookup = c("2012-01-12", "2012-01-31", "2012-03-05", "2012-03-19")
time_index <- seq(from = as.POSIXct("2012-01-01 07:00"), to = as.POSIXct("2012-05-17 18:00"), by = "hour")
set.seed(1)
value <- matrix(rnorm(n = 4*length(time_index)),length(time_index),4)
testdfx <- xts(value, order.by = time_index)
testdfx[lookup[1]]
testdfx["2012-01-12"]
Thanks for the response guys I actually thought i had deleted this thread but obviously not.
The problem in the case above was to be found around 3' from the computer. When looking through the data I was only interested in Fridays which also means that the FX market is closing down for the week end.
Sorry to have wasted your time and Admin please remove.