R download nc file

In the previous example, we have downloaded a csv file. Furthermore, it is possible to download files from a sharepoint or a web application such as shiny. Do you need further guidance for the downloading of files from the web?

The video does not only show another example for the application of the download. It also explains how to import this data to R or RStudio. Please accept YouTube cookies to play this video. By accepting you will be accessing content from YouTube, a service provided by an external third party. YouTube privacy policy. Accept YouTube Content. In addition, you might also want to have a look at the other R tutorials on this website. This article explained how to download data from the internet with the download.

I case you have any further questions, let me know in the comments. Then reshape that vector into a by 12 matrix using the matrix function, and verify its dimensions, which should be by Get the annual mean, mtwa and mtco mean temperatures of the warmest and coldest montth values and add them to the second data frame.

Create a third data frame, with only non-missing values. In this set of example code, an R data frame is reshaped into an array that can be written out as a netCDF file. This could be a trivial transformation, if all rows and columns of the target array are contained in the data frame.

In many real-world cases, however, the data frame contains, for example, only land data points, and so transforming or reshaping the data frame to an array is not straighforward, because the data frame contains only a subset of points in the full array. There are several approaches for doing the reshaping, ranging from explict and slow, to rather cryptic, but fast.

The individual approaches below can be timed using the proc. The example also illustrates the conversion of a nlon x nlat rows by 1-column variable in a data frame into a 2-D nlon by nlat array. Another approach is to generate or specify the dimension variables explicitly. However, this may be problematical if the source file longitudes and latitudes were not generated in exactly the same way, or were saved at lower single precision.

The size and shapes of the various arrays are confirmed by repeated applications of the dim function recalling that dim will list the number of columns first, number of rows second and if approriate, the number of times third. The conversion is done in two steps: 1 converting that part of the the data frame containing the 12 monthly values into into a 2-d matrix, and then 2 reshaping the 2-d matrix into a 3-d array.

The columns containing mtwa , mtco and mat are each transformed into 2-D arrays. This can be done explicity, by looping over the individual rows of the data frame, and copying the values from each row into the appropriate locations of the array. This can be very slow, but it has the advantage of being explict. Next, an nlon by nlat by nt array is created, and filled with the original fill value or an alternative. The generated lontitudes and latitudes are used here as opposed to copies from the original netCDF file—this is more general.

In the first, most explict, approach, we loop over the rows in the data frame, find the j -th and k -th column and row that each observation falls in using the which. This takes a relatively long time for data sets with hundreds of rows and columns. In the second approach, the sapply function is used to repeatedly apply a function to create two vectors of indices j2 and k2 that describe which column and row of the array each row of the data frame is assigned to.

For example, the function function x which. Then, the values are copied one time at a time by first reshaping the appropriate column in the data frame using the as. Note how the square-bracket selection on the left side of the assignment [cbind j2,k2 ] puts each row of the data frame into the proper location in the array. Loops can be totally avoided as follows, extending the [ In this example, the arrays created above are written out using the ncdf4 package.

Most methods do not percent-encode special characters such as spaces in URLs see URLencode , but it seems the "wininet" method does. The remaining details apply to the "internal" , "wininet" and "libcurl" methods only. The timeout for many parts of the transfer can be set by the option timeout which defaults to 60 seconds. The level of detail provided during transfer can be set by the quiet argument and the internet. For the "internal" method setting option internet. Using 2 the default gives only serious messages, and 3 or more suppresses all messages.

For the "libcurl" method values of the option less than 2 give verbose output. If the file length is known, the full width of the bar is the known length. Otherwise the initial width represents Kbytes and is doubled whenever the current width is exceeded. In non-interactive use this uses a text version. On Windows, if mode is not supplied missing and url ends in one of. Usage download. If TRUE , suppress status messages if any , and the progress bar.

Is a server-side cached value acceptable? The next two paragraphs apply to the internal code only.