docs: fix typo for "population" in the GeminiTextGenerator.predict(..., output_schema={...}) sample notebook (#1748)

* docs: fix type in output_schema sample notebook * Update bq_dataframes_llm_output_schema.ipynb

Author: tswast

notebooks/generative_ai/bq_dataframes_llm_output_schema.ipynb

@@ -361,7 +361,7 @@
  "cell_type": "markdown",
  "metadata": {},
  "source": [
- "You can also get float or int values, for example, to get polulations in millions:"
+ "You can also get float or int values, for example, to get populations in millions:"
  ]
  },
  {
@@ -400,7 +400,7 @@
  " <tr style=\"text-align: right;\">\n",
  " <th></th>\n",
  " <th>city</th>\n",
- " <th>polulation_million</th>\n",
+ " <th>population_in_millions</th>\n",
  " </tr>\n",
  " </thead>\n",
  " <tbody>\n",
@@ -425,7 +425,7 @@
  "</div>[3 rows x 2 columns in total]"
  ],
  "text/plain": [
- " city polulation_million\n",
+ " city population_in_millions\n",
  "0 Seattle 0.75\n",
  "1 New York 19.68\n",
  "2 Shanghai 26.32\n",
@@ -439,8 +439,8 @@
  }
  ],
  "source": [
- "result = gemini.predict(df, prompt=[\"what is the population in millions of\", df[\"city\"]], output_schema={\"polulation_million\": \"float64\"})\n",
- "result[[\"city\", \"polulation_million\"]]"
+ "result = gemini.predict(df, prompt=[\"what is the population in millions of\", df[\"city\"]], output_schema={\"population_in_millions\": \"float64\"})\n",
+ "result[[\"city\", \"population_in_millions\"]]"
  ]
  },
  {
@@ -576,7 +576,7 @@
  " <th></th>\n",
  " <th>city</th>\n",
  " <th>is_US_city</th>\n",
- " <th>polulation_in_millions</th>\n",
+ " <th>population_in_millions</th>\n",
  " <th>rainy_days_per_year</th>\n",
  " </tr>\n",
  " </thead>\n",
@@ -608,7 +608,7 @@
  "</div>[3 rows x 4 columns in total]"
  ],
  "text/plain": [
- " city is_US_city polulation_in_millions rainy_days_per_year\n",
+ " city is_US_city population_in_millions rainy_days_per_year\n",
  "0 Seattle True 0.75 152\n",
  "1 New York True 8.8 121\n",
  "2 Shanghai False 26.32 115\n",
@@ -622,8 +622,8 @@
  }
  ],
  "source": [
- "result = gemini.predict(df, prompt=[df[\"city\"]], output_schema={\"is_US_city\": \"bool\", \"polulation_in_millions\": \"float64\", \"rainy_days_per_year\": \"int64\"})\n",
- "result[[\"city\", \"is_US_city\", \"polulation_in_millions\", \"rainy_days_per_year\"]]"
+ "result = gemini.predict(df, prompt=[df[\"city\"]], output_schema={\"is_US_city\": \"bool\", \"population_in_millions\": \"float64\", \"rainy_days_per_year\": \"int64\"})\n",
+ "result[[\"city\", \"is_US_city\", \"population_in_millions\", \"rainy_days_per_year\"]]"
  ]
  },
  {
@@ -677,7 +677,7 @@
  " <th></th>\n",
  " <th>city</th>\n",
  " <th>is_US_city</th>\n",
- " <th>polulation_in_millions</th>\n",
+ " <th>population_in_millions</th>\n",
  " <th>rainy_days_per_year</th>\n",
  " <th>places_to_visit</th>\n",
  " <th>gps_coordinates</th>\n",
@@ -717,7 +717,7 @@
  "</div>[3 rows x 6 columns in total]"
  ],
  "text/plain": [
- " city is_US_city polulation_in_millions rainy_days_per_year \\\n",
+ " city is_US_city population_in_millions rainy_days_per_year \\\n",
  "0 Seattle True 0.74 150 \n",
  "1 New York True 8.4 121 \n",
  "2 Shanghai False 26.32 115 \n",
@@ -741,8 +741,8 @@
  }
  ],
  "source": [
- "result = gemini.predict(df, prompt=[df[\"city\"]], output_schema={\"is_US_city\": \"bool\", \"polulation_in_millions\": \"float64\", \"rainy_days_per_year\": \"int64\", \"places_to_visit\": \"array<string>\", \"gps_coordinates\": \"struct<latitude float64, longitude float64>\"})\n",
- "result[[\"city\", \"is_US_city\", \"polulation_in_millions\", \"rainy_days_per_year\", \"places_to_visit\", \"gps_coordinates\"]]"
+ "result = gemini.predict(df, prompt=[df[\"city\"]], output_schema={\"is_US_city\": \"bool\", \"population_in_millions\": \"float64\", \"rainy_days_per_year\": \"int64\", \"places_to_visit\": \"array<string>\", \"gps_coordinates\": \"struct<latitude float64, longitude float64>\"})\n",
+ "result[[\"city\", \"is_US_city\", \"population_in_millions\", \"rainy_days_per_year\", \"places_to_visit\", \"gps_coordinates\"]]"
  ]
  }
  ],