Numpy

README.md

@@ -1731,32 +1731,27 @@ indexes = <array>.argmin(<axis>)
 * **Axis is an index of dimension, that gets collapsed.**
 
 ### Indexing
-#### Basic indexing:
-```bash
-<el>       = <2d_array>[0, 0]
-```
-
-#### Basic slicing:
+#### Basic:
 ```bash
+<el>       = <2d_array>[0, 0]        # First element.
 <1d_view>  = <2d_array>[0]           # First row.
 <1d_view>  = <2d_array>[:, 0]        # First column. Also [..., 0].
 <3d_view>  = <2d_array>[None, :, :]  # Expanded by dimension of size 1.
 ```
 
-#### Integer array indexing:
+#### Advanced:
 ```bash
 <1d_array> = <2d_array>[<1d_row_indexes>, <1d_column_indexes>]
 <2d_array> = <2d_array>[<2d_row_indexes>, <2d_column_indexes>]
 ```
 
-* **If row and column indexes differ in shape, they are combined with broadcasting.**
-
-#### Boolean array indexing:
 ```bash
 <2d_bools> = <2d_array> > 0
 <1d_array> = <2d_array>[<2d_bools>]
 ```
 
+* **If row and column indexes differ in shape, they are combined with broadcasting.**
+
 ### Broadcasting
 **Broadcasting is a set of rules by which NumPy functions operate on arrays of different sizes and/or dimensions.**