Dear All,
I usually work with time series data. The data may come in AM/PM date
format or on 24 hour time basis. R can not recognize the two differences
automatically - at least for me. I have to specifically tell R in which
time format the data is. It seems that Pandas knows how to handle date
without being told the format. The problem arises when I try to shift time
by a certain time. Say adding 3600 to shift it forward, that case I have to
use something like:
Measured_data$Date <- as.POSIXct(as.character(Measured_data$Date),
tz="",format = "%m/%d/%Y %I:%M %p")+3600
or Measured_data$Date <- as.POSIXct(as.character(Measured_data$Date),
tz="",format = "%m/%d/%Y %H:%M")+3600 depending on the format. The date
also attaches MDT or MST and so on. When merging two data frames with
dates of different format that may create a problem (I think). When I get
data from excel it could be in any/random format and I needed to customize
the date to use in R in one of the above formats. Any TIPS - for automatic
processing with no need to specifically tell the data format ?
Another problem I saw was that when using r bind to bind data frames, if
one column of one of the data frames is a character data (say for example
none - coming from mysql) format R doesn't know how to concatenate numeric
column from the other data frame to it. I needed to change the numeric to
character and later after binding takes place I had to re-convert it to
numeric. But, this causes problem in an automated environment. Any
suggestion ?
Thanks
Mihretu
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