Reshape Data: Concatenate
<pre>
DataFrame <code>df1</code>
+-------------+--------+
| Column Name | Type   |
+-------------+--------+
| student_id  | int    |
| name        | object |
| age         | int    |
+-------------+--------+

DataFrame <code>df2</code>
+-------------+--------+
| Column Name | Type   |
+-------------+--------+
| student_id  | int    |
| name        | object |
| age         | int    |
+-------------+--------+

</pre>

<p>Write a solution to concatenate these two DataFrames <strong>vertically</strong> into one DataFrame.</p>

<p>The result format is in the following example.</p>

<p>&nbsp;</p>
<p><strong class="example">Example 1:</strong></p>

<pre>
<strong>Input:
df1</strong>
+------------+---------+-----+
| student_id | name    | age |
+------------+---------+-----+
| 1          | Mason   | 8   |
| 2          | Ava     | 6   |
| 3          | Taylor  | 15  |
| 4          | Georgia | 17  |
+------------+---------+-----+
<strong>df2
</strong>+------------+------+-----+
| student_id | name | age |
+------------+------+-----+
| 5          | Leo  | 7   |
| 6          | Alex | 7   |
+------------+------+-----+
<strong>Output:</strong>
+------------+---------+-----+
| student_id | name    | age |
+------------+---------+-----+
| 1          | Mason   | 8   |
| 2          | Ava     | 6   |
| 3          | Taylor  | 15  |
| 4          | Georgia | 17  |
| 5          | Leo     | 7   |
| 6          | Alex    | 7   |
+------------+---------+-----+
<strong>Explanation:
</strong>The two DataFramess are stacked vertically, and their rows are combined.</pre>

[]
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{
  "pythondata": [
    "df1 = pd.DataFrame([], columns=['student_id', 'name', 'age']).astype({'student_id':'Int64', 'name':'object', 'age':'Int64'})",
    "df2 = pd.DataFrame([], columns=['student_id', 'name', 'age']).astype({'student_id':'Int64', 'name':'object', 'age':'Int64'})"
  ],
  "database": true,
  "name": "concatenateTables",
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    "pythondata"
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{"pythondata": ["Pandas", "<p>Python 3.10 with Pandas 2.2.2 and NumPy 1.26.4</p>"]}
[]