Apply suggestions from code review minor

Co-authored-by: Martijn Govers <[email protected]>
Signed-off-by: Nitish Bharambe <[email protected]>

Author: nitbharambe

docs/examples/arrow_example.ipynb

@@ -10,7 +10,7 @@
     "\n",
     "It is by no means intended to provide complete documentation on the topic, but only to show how such conversions could be done.\n",
     "\n",
-    "This example uses `pyarrow.RecordBatch` to demonstrate zero copy operations. The user can choose a `pyarrow.Table` or other structures based on the requirement.\n",
+    "This example uses `pyarrow.RecordBatch` to demonstrate zero-copy operations. The user can choose a `pyarrow.Table` or other structures based on the requirement.\n",
     "\n",
     "**NOTE:** To run this example, the optional `examples` dependencies are required:\n",
     "\n",
@@ -78,7 +78,7 @@
     "\n",
     "Construct the input data for the model and construct the actual model.\n",
     "\n",
-    "Arrow uses a columnar data format while the power-grid-model offers both: row based or columnar data format.\n",
+    "Arrow uses a columnar data format while the power-grid-model offers support for both row based and columnar data format.\n",
     "Because of this, the columnar data format of power-grid-model provides a zero-copy interface for Arrow data. This differs from the row-based data format, for which conversions always require a copy."
    ]
   },
@@ -123,11 +123,11 @@
    "metadata": {},
    "source": [
     "The primitive types of each attribute in the arrow tables need to match to make the operation efficient.\n",
-    "A zero copy is not guaranteed if the data types from power_grid_meta_data / initialize_array are not used.\n",
+    "Zero-copy conversion is not guaranteed if the data types provided via the PGM via `power_grid_meta_data` are not used.\n",
     "Note that the asymmetric type of attribute in power-grid-model has a shape of `(3,)` along with a specific type. These represent the 3 phases of electrical system.\n",
-    "Hence asymmetric attributes need to be handled specially. \n",
+    "Hence, special care is required when handling asymmetric attributes. \n",
     "\n",
-    "In this tutorial we use the respective primitive types for the symmetrical attributes and a `FixedSizeListArray` of the primitive types with length 3 for asymmetrical attributes. This results in them being stored as contigious memory which would enable zero copy conversion. There might be other ways to approach this problem too."
+    "In this example, we use the respective primitive types for the symmetrical attributes and a `FixedSizeListArray` of the primitive types with length 3 for asymmetrical attributes. This results in them being stored as contiguous memory which would enable zero-copy conversion. Other possible solutions to this problem are beyond the scope of this example."
    ]
   },
   {
@@ -179,9 +179,9 @@
     "    return pa.schema(schemas)\n",
     "\n",
     "\n",
-    "print(\"-------node combined asym scehma-------\")\n",
+    "print(\"-------node combined asym schema-------\")\n",
     "print(pgm_schema(DatasetType.input, ComponentType.node))\n",
-    "print(\"-------asym load combined asym scehma-------\")\n",
+    "print(\"-------asym load combined asym schema-------\")\n",
     "print(pgm_schema(DatasetType.input, ComponentType.asym_load))"
    ]
   },
@@ -269,7 +269,7 @@
     "Converting Arrow data to columnar NumPy arrays is recommended to leverage the columnar nature of Arrow data. \n",
     "This conversion can be done with zero-copy operations.\n",
     "\n",
-    "Similar approach be adopted by the user to convert to row based data.\n",
+    "A similar approach be adopted by the user to convert to row based data.\n",
     "\n",
     "```{note}\n",
     "The option of `zero_copy_only` in the function below is added in this demo to verify no copies are made. Its usage is not mandatory to do zero copy conversion.\n",