Easy Solution with simple explanation
Intuition\nWe need to determine the dimensions of the given DataFrame, which in pandas are easily accessible through built-in attributes.\n\n# Approach\nUse the
# Intuition\nWe need to determine the dimensions of the given DataFrame, which in pandas are easily accessible through built-in attributes.\n\n# Approach\nUse the shape attribute of the DataFrame, which returns a tuple containing the number of rows and columns.\nConvert the tuple to a list to match the required output format.\n\n# Complexity\nTime complexity: O(1)\n\n<!-- Add your time complexity here, e.g. $$O(n)$$ -->\nThe time complexity is constant O(1) because accessing the shape attribute of a pandas DataFrame is an instantaneous operation that doesn\'t depend on the size of the DataFrame.\n\nSpace complexity: O(1)\n\n<!-- Add your space complexity here, e.g. $$O(n)$$ -->\nThe space complexity is also constant O(1) because we\'re only creating a small list with two integer values, regardless of the size of the input DataFrame.\nThis solution efficiently calculates the number of rows and columns in the DataFrame without iterating through the data, making it both fast and memory-efficient.\n\n# Code\n```pythondata []\nimport pandas as pd\n\ndef getDataframeSize(players: pd.DataFrame) -> List[int]:\n    #shape attribute of DataFrame player is accessed to get its dimensions\n    [r,c] = players.shape #returns a tuple\n    return[r,c]\n```
['Pandas']