Update Lecture4.ipynb

Replace O by Li for faster first search. Thanks to Patrick for the tip.

Lecture4.ipynb

@@ -298,7 +298,7 @@
     "\n",
     "* a band gap between 0.5 and 1.5 eV: `band_gap=(0.5,1.5)`\n",
     "* two elements: `num_elements=(2,3)`\n",
-    "* contains oxygen: `elements=[\"O\"]`\n",
+    "* contains lithium: `elements=[\"Li\"]`\n",
     "\n",
     "We want to return the following properties: `material_id`,`formula_pretty` ,`band_gap`, `theoretical`, `is_stable`."
    ]
@@ -333,16 +333,16 @@
    },
    "outputs": [],
    "source": [
-    "# Query for binary and ternary oxides\n",
+    "# Query for binary and ternary Li compounds with compact output\n",
     "with MPRester(FBI_KEY, use_document_model=False) as mpr:\n",
     "    docs = mpr.materials.summary.search(\n",
-    "        elements=[\"O\"],\n",
+    "        elements=[\"Li\"],\n",
     "        band_gap=(0.5,1.5),\n",
     "        num_elements=(2,3),\n",
     "        fields=['material_id', 'formula_pretty','band_gap','is_stable', 'theoretical']\n",
     "       )\n",
     "\n",
-    "print(\"Number of binary and ternary oxides with band gap between 0.5 and 1.5 eV: \", len(docs))"
+    "print(\"Number of binary and ternary Li containing compounds with a band gap between 0.5 and 1.5 eV: \", len(docs))"
    ]
   },
   {
@@ -513,7 +513,7 @@
    "source": [
     "We now have a DataFrame with the properties that we requested. However, the symmetry is still in dictionary form. This type of issue arises many times in data pre-processing for machine learning models.\n",
     "\n",
-    "The `symmetry` property contains key value pairs  of the symmetry data: `number`, `symbol`, `crystal_system`, `point_group`, `source`, `version`. With the exception of `number`, these are all currently `None` as we only requested the property `symmetry.number`. We can convert the `symmetry` into a column of the DataFrame using `.apply()`. This method applies a function to each row of the DataFrame. In this case, we will apply a function that returns the value of the `number` key of the `symmetry` dictionary. "
+    "The `symmetry` property contains key value pairs  of the symmetry data. We can convert the `symmetry` into a column of the DataFrame using `.apply()`. This method applies a function to each row of the DataFrame. In this case, we will apply a function that returns the value of the `number` key of the `symmetry` dictionary. "
    ]
   },
   {
@@ -540,13 +540,13 @@
     "    \"\"\"\n",
     "    return symmetry[\"number\"]\n",
     "\n",
-    "# Apply the function to each row of the dataframe\n",
+    "# Apply the function to each row of the DataFrame\n",
     "oxide_df[\"symmetry.number\"] = oxide_df[\"symmetry\"].apply(get_spacegroup_number)\n",
     "\n",
-    "# Drop the \"symmetry\" column from the dataframe\n",
+    "# Drop the \"symmetry\" column from the DataFrame\n",
     "oxide_df.drop(columns=[\"symmetry\"], inplace=True)\n",
     "\n",
-    "# Display the first few rows of the dataframe\n",
+    "# Display the first few rows of the DataFrame\n",
     "oxide_df.head()"
    ]
   },