Re: [R] Problem with converting grib file to excel

[Roy Mendelssohn - NOAA Federal via R-help]

I have corresponded with Javad off-line,  posting this as a follow-up, to close 
the issue.  There are two separate questions here.  The first is why did the 
posted code below fail.  The second is there an easy way to read in the values, 
given the oddities of his file  (more on that), and yes it turns out "terra" 
performs much better than "raster".

First a little about GRIB files in general,  and this file in particular.  GRIB 
files were design to store grids in files with very small footprints,  usually 
from model output.  GRIB files have the characteristic that if I "cat" a bunch 
of  GRIB files,  I still have a valid GRIB file.  So a given GRIB file often 
contains multiple parameters,  and each of those through time.  To translate 
into terms used by R spatial packages,  each variable grid,  at each time 
period will be seen as a  "band" or a "layer" in the dataset.  Thus if I have 3 
parameters,  say temperature,  dew point and cloud cover at  8670 time periods, 
 R spatial packages will see 3*8670 layers or bands.

However this GRIB file is clearly not a raw GRIB file made by a data provider,  
but rather an extract made with some tool.  In this file there are 3 underlying 
time series. temperature,  dew point and cloud cover,  each of dimension (1, 1, 
8670),  that is because it is defined at one spatial point only.

So why did the code below fail?  raster::stack()  read the file just fine,  and 
the layer_names are correct,  all 3*8670 of them.  The next steps:

>> # 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

which are aimed at subsetting the raster stack based on the variable name all 
fail because ""t2m" , "d2m" and "tcc" are not in the layer_names. So then of 
course everything else fails.

So the next question is how to read the file and get a data frame.  A first 
pass would be:

raster_stack <- raster::stack("Met.grib")
raster_data <- raster::getValues(raster_stack).

but you do not want to do that.  For whatever reason,  the raster_stack created 
above is enormous,  and the raster::getValues() takes forever,  I aborted after 
about an hour.  However,  if you use 'terra" instead:

raster_stack <-terra::rast("Met.grib")
raster_data <-terra::values(raster_stack).

it finishes in a flash.  raster_data is now one long array that needs to be 
reshaped:

raster_data <- array(raster_data, dim = c(3, 8670)

now raster_data[1, ] contains the temperature series,  raster_data[2, ] 
contains the dew point data,  and raster_data[3, ] contains the cloud cover 
data.

HTH,

-Roy

PS - GRIB files can be a bear.  The best GRIB readers in R are just front ends 
for either eccodes or wgrib2,and  while they work very well,  installation 
for eccodes and wgrib2 can be non-trivial,  so I didn't want to use them as a 
solution.  Also for quick viewing of GRIB files there is NASA's Panoply 
(https://www.giss.nasa.gov/tools/panoply/) but that requires a Java 
installation.

> On Sep 23, 2024, at 11:31 PM, javad bayat  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 <-

Re: [R] Problem with converting grib file to excel

[Roy Mendelssohn - NOAA Federal via R-help]

The easiest would be to send the link to the site from which you downloaded the 
file.

Thanks,

-Roy

> On Sep 26, 2024, at 1:26 PM, CALUM POLWART  wrote:
> 
> Attachments CAN NOT be sent to group
> 
> 
> On Thu, 26 Sep 2024, 21:22 javad bayat,  wrote:
> Dear Roy,
> Sorry for my mistake, I thought I have uploaded the grib file.
> I really apologise for that. I will send it   on Saturday.
> Thank you very much.
> 
> On Thu, 26 Sept 2024, 17:40 Roy Mendelssohn - NOAA Federal, <
> roy.mendelss...@noaa.gov> wrote:
> 
> > Hi Javad:
> >
> > I know a lot about reading GRIB files,  I work with them all the time.
> > But if you don’t make the file available,  or point me to where I can
> > download it,  there is not much I can do.
> >
> > Thanks,
> >
> > -Roy
> >
> > On Sep 25, 2024, at 9:41 PM, javad bayat  wrote:
> >
> > Dear all;
> > Many thanks for your responses. Actually it is not completely a GIS file,
> > it is a data file which stores meteorological data of a specific region.
> > But the site allows downloading with grib format and as I searched to read
> > this type of file in R, I found the Raster Package.
> > In python it is possible to do this using cdsapi and xarray library, but I
> > am not familiar with python.
> > Sincerely
> >
> > On Thu, Sep 26, 2024 at 2:33 AM Roy Mendelssohn - NOAA Federal via R-help <
> > r-help@r-project.org> wrote:
> >
> >> 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  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,  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 
> >> 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

Re: [R] Problem with converting grib file to excel

[CALUM POLWART]

Attachments CAN NOT be sent to group

On Thu, 26 Sep 2024, 21:22 javad bayat,  wrote:

> Dear Roy,
> Sorry for my mistake, I thought I have uploaded the grib file.
> I really apologise for that. I will send it   on Saturday.
> Thank you very much.
>
> On Thu, 26 Sept 2024, 17:40 Roy Mendelssohn - NOAA Federal, <
> roy.mendelss...@noaa.gov> wrote:
>
> > Hi Javad:
> >
> > I know a lot about reading GRIB files,  I work with them all the time.
> > But if you don’t make the file available,  or point me to where I can
> > download it,  there is not much I can do.
> >
> > Thanks,
> >
> > -Roy
> >
> > On Sep 25, 2024, at 9:41 PM, javad bayat  wrote:
> >
> > Dear all;
> > Many thanks for your responses. Actually it is not completely a GIS file,
> > it is a data file which stores meteorological data of a specific region.
> > But the site allows downloading with grib format and as I searched to
> read
> > this type of file in R, I found the Raster Package.
> > In python it is possible to do this using cdsapi and xarray library, but
> I
> > am not familiar with python.
> > Sincerely
> >
> > On Thu, Sep 26, 2024 at 2:33 AM Roy Mendelssohn - NOAA Federal via
> R-help <
> > r-help@r-project.org> wrote:
> >
> >> 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 
> 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, 
> 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 
> >> 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 

Re: [R] Problem with converting grib file to excel

[javad bayat]

Dear Roy,
Sorry for my mistake, I thought I have uploaded the grib file.
I really apologise for that. I will send it   on Saturday.
Thank you very much.

On Thu, 26 Sept 2024, 17:40 Roy Mendelssohn - NOAA Federal, <
roy.mendelss...@noaa.gov> wrote:

> Hi Javad:
>
> I know a lot about reading GRIB files,  I work with them all the time.
> But if you don’t make the file available,  or point me to where I can
> download it,  there is not much I can do.
>
> Thanks,
>
> -Roy
>
> On Sep 25, 2024, at 9:41 PM, javad bayat  wrote:
>
> Dear all;
> Many thanks for your responses. Actually it is not completely a GIS file,
> it is a data file which stores meteorological data of a specific region.
> But the site allows downloading with grib format and as I searched to read
> this type of file in R, I found the Raster Package.
> In python it is possible to do this using cdsapi and xarray library, but I
> am not familiar with python.
> Sincerely
>
> On Thu, Sep 26, 2024 at 2:33 AM Roy Mendelssohn - NOAA Federal via R-help <
> r-help@r-project.org> wrote:
>
>> 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  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,  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 
>> 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_valu

Re: [R] Problem with converting grib file to excel

[Roy Mendelssohn - NOAA Federal via R-help]

Hi Javad:

I know a lot about reading GRIB files,  I work with them all the time.  But if 
you don’t make the file available,  or point me to where I can download it,  
there is not much I can do.

Thanks,

-Roy

> On Sep 25, 2024, at 9:41 PM, javad bayat  wrote:
> 
> Dear all;
> Many thanks for your responses. Actually it is not completely a GIS file, it 
> is a data file which stores meteorological data of a specific region. But the 
> site allows downloading with grib format and as I searched to read this type 
> of file in R, I found the Raster Package.
> In python it is possible to do this using cdsapi and xarray library, but I am 
> not familiar with python.
> Sincerely
> 
> On Thu, Sep 26, 2024 at 2:33 AM Roy Mendelssohn - NOAA Federal via R-help 
> mailto:r-help@r-project.org>> wrote:
>> 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 > > > 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, > > > 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 > >> > 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,
>> >>

Re: [R] Problem with converting grib file to excel

[javad bayat]

Dear all;
Many thanks for your responses. Actually it is not completely a GIS file,
it is a data file which stores meteorological data of a specific region.
But the site allows downloading with grib format and as I searched to read
this type of file in R, I found the Raster Package.
In python it is possible to do this using cdsapi and xarray library, but I
am not familiar with python.
Sincerely

On Thu, Sep 26, 2024 at 2:33 AM Roy Mendelssohn - NOAA Federal via R-help <
r-help@r-project.org> wrote:

> 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  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,  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 
> 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 numeri

Re: [R] Problem with converting grib file to excel

[Roy Mendelssohn - NOAA Federal via R-help]

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  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,  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  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: bayat...@yahoo.com
>>> 
>>>[[alter

Re: [R] Problem with converting grib file to excel

[CALUM POLWART]

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,  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  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: bayat...@yahoo.com
> >
> > [[alternative HTML version deleted]]
> >
> > __
> > R-help@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 

Re: [R] Problem with converting grib file to excel

[Bert Gunter]

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  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: bayat...@yahoo.com
>
> [[alternative HTML version deleted]]
>
> __
> R-help@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.

__
R-help@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.