One-liner code using concat()
Intuition\n Describe your first thoughts on how to solve this problem. \nThe intuition for this problem is to combine two DataFrames by stacking them vertically
# Intuition\n<!-- Describe your first thoughts on how to solve this problem. -->\nThe intuition for this problem is to combine two DataFrames by stacking them vertically, one on top of the other. This operation is commonly known as concatenation or vertical stacking in data manipulation.\n# Approach\n<!-- Describe your approach to solving the problem. -->\nWe can use pandas\' concat() function to vertically concatenate the two DataFrames. Here\'s the step-by-step approach:\n\nUse pd.concat() function.\nPass both DataFrames as a list to the concat() function.\nSet axis=0 to indicate vertical concatenation (this is the default, so we can omit it).\nUse ignore_index=True if we want to reset the index of the resulting DataFrame.\n# Complexity\nTime complexity: O(n)\n\n<!-- Add your time complexity here, e.g. $$O(n)$$ -->\nThe time complexity is O(n), where n is the total number of rows in both DataFrames combined. The concat() operation is generally considered to be O(n) for simple vertical concatenation.\n\nSpace complexity: O(n)\n\n<!-- Add your space complexity here, e.g. $$O(n)$$ -->\nThe space complexity is O(n), where n is the total number of rows in both DataFrames combined. We\'re creating a new DataFrame that contains all the rows from both input DataFrames.\n\n# Code\n```pythondata []\nimport pandas as pd\n\ndef concatenateTables(df1: pd.DataFrame, df2: pd.DataFrame) -> pd.DataFrame:\n    return pd.concat([df1,df2])\n```
['Pandas']