Add docs for the supported numeric dtypes

Author: seisman

doc/techref/array_dtypes.md

@@ -0,0 +1,35 @@
+# Supported Array Dtypes
+
+PyGMT uses NumPy arrays to store data and passes them to the GMT C library. In this way,
+PyGMT can support a wide range of dtypes. This page documents array dtypes supported by
+PyGMT.
+
+## Numeric Dtypes
+
+For 1-D and 2-D arrays, PyGMT supports most numeric dtypes provided by NumPy, pandas, and
+PyArrow.
+
+**Signed Integers:**
+
+- {class}`numpy.int8`, {class}`numpy.int16`, {class}`numpy.int32`, {class}`numpy.int64`
+- {class}`pandas.Int8`, {class}`pandas.Int16`, {class}`pandas.Int32`, {class}`pandas.Int64`
+- {class}`pyarrow.int8`, {class}`pyarrow.int16`, {class}`pyarrow.int32`, {class}`pyarrow.int64`
+
+**Unsigned Integers:**
+
+- {class}`numpy.uint8`, {class}`numpy.uint16`, {class}`numpy.uint32`, {class}`numpy.uint64`
+- {class}`pandas.UInt8`, {class}`pandas.UInt16`, {class}`pandas.UInt32`, {class}`pandas.UInt64`
+- {class}`pyarrow.uint8`, {class}`pyarrow.uint16`, {class}`pyarrow.uint32`, {class}`pyarrow.uint64`
+
+**Floating-point numbers:**
+
+- {class}`numpy.float32`, {class}`numpy.float64`
+- {class}`pandas.Float32`, {class}`pandas.Float64`
+- {class}`pyarrow.float32`, {class}`pyarrow.float64`
+
+For 3-D {class}`xarray.DataArray` objects representing raster images, only 8-bit unsigned
+intergers (i.e., {class}`numpy.uint8`) are supported.
+
+## String Dtypes
+
+## Datetime Dtypes

doc/techref/index.md

@@ -8,6 +8,7 @@ visit the {gmt-docs}`GMT Technical Reference <reference.html>`.
 ```{toctree}
 :maxdepth: 1
 
+array_dtypes.md
 projections.md
 fonts.md
 patterns.md