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Rewrite datatype list as table in docs #1390

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Nov 23, 2024
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Rewrite datatype list as table in docs #1390

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84 changes: 70 additions & 14 deletions docs/index.html
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Expand Up @@ -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>
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31 changes: 19 additions & 12 deletions src/netCDF4/_netCDF4.pyx
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Expand Up @@ -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
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