[R] Problem with converting grib file to excel

Thu Sep 26 01:02:50 CEST 2024

At least for me the dataset file did not come through.  I will look at it if it can be made available.  It does look like the finial step of reading the data into raster failed,  so then did the rest of th commands.

-Roy

> On Sep 25, 2024, at 3:24 PM, CALUM POLWART <polc1410 using gmail.com> wrote:
> 
> Noticeable lack of silence in the group on this one.
> 
> I've not got time to test currently. But my experience of geo location
> files - they often had more than 2 dimensional data. In other words you
> might have a boundary of a region as an object with long and lat for maybe
> 100 data points making up the region. So 200 pieces of data. All held as a
> list or something similar in a single "cell" as excel would refer to it.
> 
> My gut feeling is that's likely to make export to excel difficult without
> data carpentry first?
> 
> On Tue, 24 Sep 2024, 21:26 Bert Gunter, <bgunter.4567 using gmail.com> wrote:
> 
>> You might try posting on r-sig-geo if you don't get a satisfactory
>> response here. I assume there's a lot of expertise there on handling
>> raster-type data.
>> 
>> Cheers,
>> Bert
>> 
>> On Mon, Sep 23, 2024 at 11:31 PM javad bayat <j.bayat194 using gmail.com> wrote:
>>> 
>>> Dear R users;
>>> I have downloaded a grib file format (Met.grib) and I want to export its
>>> data to excel file. Also I want to do some mathematic on some columns.
>> But
>>> I got error. I would be more than happy if anyone can help me to do
>> this. I
>>> have provided the codes and the Met.grib file in this email.
>>> Sincerely yours
>>> 
>>> # Load the necessary libraries
>>>> library(raster)      # For reading GRIB files
>>>> library(dplyr)       # For data manipulation
>>>> library(lubridate)   # For date manipulation
>>>> library(openxlsx)    # For writing Excel files
>>> 
>>> # Specify the file paths
>>>> grib_file_path <- "C:/Users/Omrab_Lab/Downloads/Met.grib"
>>>> excel_file_path <- "C:/Users/Omrab_Lab/Downloads/Met_updated.xlsx"
>>> 
>>> # Open the GRIB file
>>>> raster_data <- stack(grib_file_path)
>>> 
>>> # Check the names of the layers to identify which ones to extract
>>>> layer_names <- names(raster_data)
>>>> print(layer_names)  # Prints
>>> 
>>> 
>>>> # Extract layers based on layer names - adjust as necessary
>>>> t2m <- raster_data[[grep("t2m", layer_names)]]
>>>> d2m <- raster_data[[grep("d2m", layer_names)]]
>>>> tcc <- raster_data[[grep("tcc", layer_names)]]
>>>> valid_time <- raster_data[[grep("valid_time", layer_names)]]
>>>> t2m
>>> class      : RasterStack
>>> nlayers    : 0
>>> 
>>>> # Check if the raster layers are loaded correctly
>>>> if (is.null(t2m) || is.null(d2m) || is.null(tcc) ||
>> is.null(valid_time))
>>> {
>>> +     stop("One or more raster layers could not be loaded. Please check
>> the
>>> layer names.")
>>> + }
>>> 
>>>> # Convert raster values to vectors
>>>> t2m_values <- values(t2m)
>>> Error in dimnames(x) <- dn :
>>>  length of 'dimnames' [2] not equal to array extent
>>>> d2m_values <- values(d2m)
>>> Error in dimnames(x) <- dn :
>>>  length of 'dimnames' [2] not equal to array extent
>>>> tcc_values <- values(tcc)
>>> Error in dimnames(x) <- dn :
>>>  length of 'dimnames' [2] not equal to array extent
>>>> valid_time_values <- values(valid_time)
>>> Error in dimnames(x) <- dn :
>>>  length of 'dimnames' [2] not equal to array extent
>>> 
>>> # Check for NA values and dimensions
>>> if (any(is.na(t2m_values)) || any(is.na(d2m_values)) || any(is.na
>> (tcc_values))
>>> || any(is.na(valid_time_values))) {
>>>  warning("One or more layers contain NA values. These will be removed.")
>>> }
>>> 
>>> # Create the data frame, ensuring no NA values are included
>>> df <- data.frame(
>>>  t2m = t2m_values,
>>>  d2m = d2m_values,
>>>  tcc = tcc_values,
>>>  valid_time = valid_time_values,
>>>  stringsAsFactors = FALSE
>>> )
>>> 
>>> # Remove rows with NA values
>>> df <- na.omit(df)
>>> 
>>> # Convert temperatures from Kelvin to Celsius
>>> df$t2m <- df$t2m - 273.15
>>> df$d2m <- df$d2m - 273.15
>>> 
>>> # Calculate relative humidity
>>> calculate_relative_humidity <- function(t2m, d2m) {
>>>  es <- 6.112 * exp((17.67 * t2m) / (t2m + 243.5))
>>>  e <- 6.112 * exp((17.67 * d2m) / (d2m + 243.5))
>>>  rh <- (e / es) * 100
>>>  return(rh)
>>> }
>>> df$RH <- calculate_relative_humidity(df$t2m, df$d2m)
>>> 
>>> # Convert valid_time from numeric to POSIXct assuming it's in seconds
>> since
>>> the epoch
>>> df$valid_time <- as.POSIXct(df$valid_time, origin = "1970-01-01")
>>> 
>>> # Extract year, month, day, and hour from valid_time
>>> df$Year <- year(df$valid_time)
>>> df$Month <- month(df$valid_time)
>>> df$Day <- day(df$valid_time)
>>> df$Hour <- hour(df$valid_time)
>>> 
>>> # Select only the desired columns
>>> df_selected <- df %>% select(Year, Month, Day, Hour, tcc, t2m, RH)
>>> 
>>> # Save the updated DataFrame to an Excel file
>>> write.xlsx(df_selected, excel_file_path, row.names = FALSE)
>>> 
>>> 
>>> 
>>> 
>>> 
>>> 
>>> --
>>> Best Regards
>>> Javad Bayat
>>> M.Sc. Environment Engineering
>>> Alternative Mail: bayat194 using yahoo.com
>>> 
>>>        [[alternative HTML version deleted]]
>>> 
>>> ______________________________________________
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>> 
>> ______________________________________________
>> R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide
>> https://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>> 
> 
> 	[[alternative HTML version deleted]]
> 
> ______________________________________________
> R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide https://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.

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