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Intuition\nThe problem seems to ask for a solution to concatenate two given Pandas DataFrames, \'df1\' and \'df2\', into a single DataFrame.\n\n# Approach\nTo s
# Intuition\nThe problem seems to ask for a solution to concatenate two given Pandas DataFrames, \'df1\' and \'df2\', into a single DataFrame.\n\n# Approach\nTo solve this problem, we can utilize the Pandas library in Python. We use the `pd.concat()` function to concatenate \'df1\' and \'df2\' along the rows (vertically) and return the resulting DataFrame.\n\n# Complexity\n- Time complexity:\n  - The time complexity depends on the sizes of \'df1\' and \'df2\' but can be considered as O(n), where n is the combined number of rows in both DataFrames.\n\n- Space complexity:\n  - The space complexity is O(n) because we create a new DataFrame containing the concatenated data.\n\n# Code\n```python\nimport pandas as pd\n\ndef concatenateTables(df1: pd.DataFrame, df2: pd.DataFrame) -> pd.DataFrame:\n    return pd.concat([df1, df2])\n
['Database', 'Python', 'Python3', 'Pandas']