Rewrite datatype table in docs

Unidata · Nov 22, 2024 · bacab64 · bacab64
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diff --git a/docs/index.html b/docs/index.html
@@ -297,27 +297,83 @@ <h2 id="variables-in-a-netcdf-file">Variables in a netCDF file</h2>
 unlike numpy arrays, netCDF4 variables can be appended to along one or
 more 'unlimited' dimensions. To create a netCDF variable, use the
 <code><a title="netCDF4.Dataset.createVariable" href="#netCDF4.Dataset.createVariable">Dataset.createVariable()</a></code> method of a <code><a title="netCDF4.Dataset" href="#netCDF4.Dataset">Dataset</a></code> or
-<code><a title="netCDF4.Group" href="#netCDF4.Group">Group</a></code> instance. The <code><a title="netCDF4.Dataset.createVariable" href="#netCDF4.Dataset.createVariable">Dataset.createVariable()</a></code>j method
+<code><a title="netCDF4.Group" href="#netCDF4.Group">Group</a></code> instance. The <code><a title="netCDF4.Dataset.createVariable" href="#netCDF4.Dataset.createVariable">Dataset.createVariable()</a></code> method
 has two mandatory arguments, the variable name (a Python string), and
 the variable datatype. The variable's dimensions are given by a tuple
 containing the dimension names (defined previously with
 <code><a title="netCDF4.Dataset.createDimension" href="#netCDF4.Dataset.createDimension">Dataset.createDimension()</a></code>). To create a scalar
 variable, simply leave out the dimensions keyword. The variable
 primitive datatypes correspond to the dtype attribute of a numpy array.
 You can specify the datatype as a numpy dtype object, or anything that
-can be converted to a numpy dtype object.
-Valid datatype specifiers
-include: <code>'f4'</code> (32-bit floating point), <code>'f8'</code> (64-bit floating
-point), <code>'i4'</code> (32-bit signed integer), <code>'i2'</code> (16-bit signed
-integer), <code>'i8'</code> (64-bit signed integer), <code>'i1'</code> (8-bit signed
-integer), <code>'u1'</code> (8-bit unsigned integer), <code>'u2'</code> (16-bit unsigned
-integer), <code>'u4'</code> (32-bit unsigned integer), <code>'u8'</code> (64-bit unsigned
-integer), or <code>'S1'</code> (single-character string).
-The old Numeric
-single-character typecodes (<code>'f'</code>,<code>'d'</code>,<code>'h'</code>,
-<code>'s'</code>,<code>'b'</code>,<code>'B'</code>,<code>'c'</code>,<code>'i'</code>,<code>'l'</code>), corresponding to
-(<code>'f4'</code>,<code>'f8'</code>,<code>'i2'</code>,<code>'i2'</code>,<code>'i1'</code>,<code>'i1'</code>,<code>'S1'</code>,<code>'i4'</code>,<code>'i4'</code>),
-will also work. The unsigned integer types and the 64-bit integer type
+can be converted to a numpy dtype object. Valid datatype specifiers
+include:</p>
+<table>
+<thead>
+<tr>
+<th>Specifier</th>
+<th>Datatype</th>
+<th>Old typecodes</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td><code>'f4'</code></td>
+<td>32-bit floating point</td>
+<td><code>'f'</code></td>
+</tr>
+<tr>
+<td><code>'f8'</code></td>
+<td>64-bit floating point</td>
+<td><code>'d'</code></td>
+</tr>
+<tr>
+<td><code>'i4'</code></td>
+<td>32-bit signed integer</td>
+<td><code>'i'</code> <code>'l'</code></td>
+</tr>
+<tr>
+<td><code>'i2'</code></td>
+<td>16-bit signed integer</td>
+<td><code>'h'</code> <code>'s'</code></td>
+</tr>
+<tr>
+<td><code>'i8'</code></td>
+<td>64-bit signed integer</td>
+<td></td>
+</tr>
+<tr>
+<td><code>'i1'</code></td>
+<td>8-bit signed integer</td>
+<td><code>'b'</code> <code>'B'</code></td>
+</tr>
+<tr>
+<td><code>'u1'</code></td>
+<td>8-bit unsigned integer</td>
+<td></td>
+</tr>
+<tr>
+<td><code>'u2'</code></td>
+<td>16-bit unsigned integer</td>
+<td></td>
+</tr>
+<tr>
+<td><code>'u4'</code></td>
+<td>32-bit unsigned integer</td>
+<td></td>
+</tr>
+<tr>
+<td><code>'u8'</code></td>
+<td>64-bit unsigned integer</td>
+<td></td>
+</tr>
+<tr>
+<td><code>'S1'</code></td>
+<td>single-character string</td>
+<td><code>'c'</code></td>
+</tr>
+</tbody>
+</table>
+<p>The unsigned integer types and the 64-bit integer type
 can only be used if the file format is <code>NETCDF4</code>.</p>
 <p>The dimensions themselves are usually also defined as variables, called
 coordinate variables. The <code><a title="netCDF4.Dataset.createVariable" href="#netCDF4.Dataset.createVariable">Dataset.createVariable()</a></code>

diff --git a/src/netCDF4/_netCDF4.pyx b/src/netCDF4/_netCDF4.pyx
@@ -295,25 +295,32 @@ supplied by the [numpy module](http://numpy.scipy.org). However,
 unlike numpy arrays, netCDF4 variables can be appended to along one or
 more 'unlimited' dimensions. To create a netCDF variable, use the
 `Dataset.createVariable` method of a `Dataset` or
-`Group` instance. The `Dataset.createVariable`j method
+`Group` instance. The `Dataset.createVariable` method
 has two mandatory arguments, the variable name (a Python string), and
 the variable datatype. The variable's dimensions are given by a tuple
 containing the dimension names (defined previously with
 `Dataset.createDimension`). To create a scalar
 variable, simply leave out the dimensions keyword. The variable
 primitive datatypes correspond to the dtype attribute of a numpy array.
 You can specify the datatype as a numpy dtype object, or anything that
-can be converted to a numpy dtype object.  Valid datatype specifiers
-include: `'f4'` (32-bit floating point), `'f8'` (64-bit floating
-point), `'i4'` (32-bit signed integer), `'i2'` (16-bit signed
-integer), `'i8'` (64-bit signed integer), `'i1'` (8-bit signed
-integer), `'u1'` (8-bit unsigned integer), `'u2'` (16-bit unsigned
-integer), `'u4'` (32-bit unsigned integer), `'u8'` (64-bit unsigned
-integer), or `'S1'` (single-character string).  The old Numeric
-single-character typecodes (`'f'`,`'d'`,`'h'`,
-`'s'`,`'b'`,`'B'`,`'c'`,`'i'`,`'l'`), corresponding to
-(`'f4'`,`'f8'`,`'i2'`,`'i2'`,`'i1'`,`'i1'`,`'S1'`,`'i4'`,`'i4'`),
-will also work. The unsigned integer types and the 64-bit integer type
+can be converted to a numpy dtype object. Valid datatype specifiers
+include:
+
+| Specifier | Datatype                | Old typecodes |
+|-----------|-------------------------|---------------|
+| `'f4'`    | 32-bit floating point   | `'f'`         |
+| `'f8'`    | 64-bit floating point   | `'d'`         |
+| `'i4'`    | 32-bit signed integer   | `'i'` `'l'`   |
+| `'i2'`    | 16-bit signed integer   | `'h'` `'s'`   |
+| `'i8'`    | 64-bit signed integer   |               |
+| `'i1'`    | 8-bit signed integer    | `'b'` `'B'`   |
+| `'u1'`    | 8-bit unsigned integer  |               |
+| `'u2'`    | 16-bit unsigned integer |               |
+| `'u4'`    | 32-bit unsigned integer |               |
+| `'u8'`    | 64-bit unsigned integer |               |
+| `'S1'`    | single-character string | `'c'`         |
+
+The unsigned integer types and the 64-bit integer type
 can only be used if the file format is `NETCDF4`.
 
 The dimensions themselves are usually also defined as variables, called