pygmt.grd2xyz(grid, output_type='pandas', outfile=None, *, cstyle=None, region=None, verbose=None, weight=None, convention=None, binary=None, nodata=None, coltypes=None, header=None, outcols=None, skiprows=None, **kwargs)[source]

Convert grid to data table.

Read a grid and output xyz-triplets as a numpy.ndarray, pandas.DataFrame, or ASCII file.

Full option list at


  • C = cstyle

  • R = region

  • V = verbose

  • W = weight

  • Z = convention

  • b = binary

  • d = nodata

  • f = coltypes

  • h = header

  • o = outcols

  • s = skiprows

  • grid (str or xarray.DataArray) – The file name of the input grid or the grid loaded as a xarray.DataArray. This is the only required parameter.

  • output_type (str) –

    Determine the format the xyz data will be returned in [Default is pandas]:

  • outfile (str) – The file name for the output ASCII file.

  • cstyle (str) – [f|i]. Replace the x- and y-coordinates on output with the corresponding column and row numbers. These start at 0 (C-style counting); append f to start at 1 (Fortran-style counting). Alternatively, append i to write just the two columns index and z, where index is the 1-D indexing that GMT uses when referring to grid nodes.

  • region (str or list) – xmin/xmax/ymin/ymax[+r][+uunit]. Specify the region of interest. Adding region will select a subsection of the grid. If this subsection exceeds the boundaries of the grid, only the common region will be output.

  • weight (str) – [a[+uunit]|weight]. Write out x,y,z,w, where w is the supplied weight (or 1 if not supplied) [Default writes x,y,z only]. Choose a to compute weights equal to the area each node represents. For Cartesian grids this is simply the product of the x and y increments (except for gridline-registered grids at all sides [half] and corners [quarter]). For geographic grids we default to a length unit of k. Change this by appending +uunit. For such grids, the area varies with latitude and also sees special cases for gridline-registered layouts at sides, corners, and poles.

  • verbose (bool or str) –

    Select verbosity level [Default is w], which modulates the messages written to stderr. Choose among 7 levels of verbosity:

    • q - Quiet, not even fatal error messages are produced

    • e - Error messages only

    • w - Warnings [Default]

    • t - Timings (report runtimes for time-intensive algorithms);

    • i - Informational messages (same as verbose=True)

    • c - Compatibility warnings

    • d - Debugging messages

  • convention (str) –

    [flags]. Write a 1-column ASCII [or binary] table. Output will be organized according to the specified ordering convention contained in flags. If data should be written by rows, make flags start with T (op) if first row is y = ymax or B (ottom) if first row is y = ymin. Then, append L or R to indicate that first element should start at left or right end of row. Likewise for column formats: start with L or R to position first column, and then append T or B to position first element in a row. For gridline registered grids: If grid is periodic in x but the written data should not contain the (redundant) column at x = xmax, append x. For grid periodic in y, skip writing the redundant row at y = ymax by appending y. If the byte-order needs to be swapped, append w. Select one of several data types (all binary except a):

    • a ASCII representation of a single item per record

    • c int8_t, signed 1-byte character

    • u uint8_t, unsigned 1-byte character

    • h int16_t, short 2-byte integer

    • H uint16_t, unsigned short 2-byte integer

    • i int32_t, 4-byte integer

    • I uint32_t, unsigned 4-byte integer

    • l int64_t, long (8-byte) integer

    • L uint64_t, unsigned long (8-byte) integer

    • f 4-byte floating point single precision

    • d 8-byte floating point double precision

    Default format is scanline orientation of ASCII numbers: TLa.

  • binary (bool or str) –

    i|o[ncols][type][w][+l|b]. Select native binary input (using binary="i") or output (using binary="o"), where ncols is the number of data columns of type, which must be one of:

    • c - int8_t (1-byte signed char)

    • u - uint8_t (1-byte unsigned char)

    • h - int16_t (2-byte signed int)

    • H - uint16_t (2-byte unsigned int)

    • i - int32_t (4-byte signed int)

    • I - uint32_t (4-byte unsigned int)

    • l - int64_t (8-byte signed int)

    • L - uint64_t (8-byte unsigned int)

    • f - 4-byte single-precision float

    • d - 8-byte double-precision float

    • x - use to skip ncols anywhere in the record

    For records with mixed types, append additional comma-separated combinations of ncols type (no space). The following modifiers are supported:

    • w after any item to force byte-swapping.

    • +l|b to indicate that the entire data file should be read as little- or big-endian, respectively.

    Full documentation is at

  • nodata (str) – i|onodata. Substitute specific values with NaN (for tabular data). For example, d="-9999" will replace all values equal to -9999 with NaN during input and all NaN values with -9999 during output. Prepend i to the nodata value for input columns only. Prepend o to the nodata value for output columns only.

  • coltypes (str) – [i|o]colinfo. Specify data types of input and/or output columns (time or geographical data). Full documentation is at

  • header (str) –

    [i|o][n][+c][+d][+msegheader][+rremark][+ttitle]. Specify that input and/or output file(s) have n header records [Default is 0]. Prepend i if only the primary input should have header records. Prepend o to control the writing of header records, with the following modifiers supported:

    • +d to remove existing header records.

    • +c to add a header comment with column names to the output [Default is no column names].

    • +m to add a segment header segheader to the output after the header block [Default is no segment header].

    • +r to add a remark comment to the output [Default is no comment]. The remark string may contain \n to indicate line-breaks.

    • +t to add a title comment to the output [Default is no title]. The title string may contain \n to indicate line-breaks.

    Blank lines and lines starting with # are always skipped.

  • outcols (str or 1d array) –

    cols[,…][,t[word]]. Specify data columns for primary output in arbitrary order. Columns can be repeated and columns not listed will be skipped [Default writes all columns in order, starting with the first (i.e., column 0)].

    • For 1d array: specify individual columns in output order (e.g., outcols=[1,0] for the 2nd column followed by the 1st column).

    • For str: specify individual columns or column ranges in the format start[:inc]:stop, where inc defaults to 1 if not specified, with columns and/or column ranges separated by commas (e.g., outcols="0:2,4" to output the first three columns followed by the 5th column). To write from a given column until the end of the record, leave off stop when specifying the column range. To write trailing text, add the column t. Append the word number to t to write only a single word from the trailing text. Instead of specifying columns, use outcols="n" to simply read numerical input and skip trailing text. Note: if incols is also used then the columns given to outcols correspond to the order after the incols selection has taken place.

  • skiprows (bool or str) –

    [cols][+a][+r]. Suppress output for records whose z-value equals NaN [Default outputs all records]. Optionally, supply a comma-separated list of all columns or column ranges to consider for this NaN test [Default only considers the third data column (i.e., cols = 2)]. Column ranges must be given in the format start[:inc]:stop, where inc defaults to 1 if not specified. The following modifiers are supported:

    • +r to reverse the suppression, i.e., only output the records whose z-value equals NaN.

    • +a to suppress the output of the record if just one or more of the columns equal NaN [Default skips record only if values in all specified cols equal NaN].


ret (pandas.DataFrame or numpy.ndarray or None) – Return type depends on outfile and output_type:

  • None if outfile is set (output will be stored in file set by outfile)

  • pandas.DataFrame or numpy.ndarray if outfile is not set (depends on output_type)