Which will NOT evaluate to 20.6? Select all that apply.1 pointdf.iloc[4,5]df.iloc[6,5]df.loc[4,’Music Recording Sales’]df.iloc[6, ‘Music Recording Sales (millions)’]
Question
Which will NOT evaluate to 20.6? Select all that apply.1 pointdf.iloc[4,5]df.iloc[6,5]df.loc[4,’Music Recording Sales’]df.iloc[6, ‘Music Recording Sales (millions)’]
Solution
The question is asking which of the given pandas DataFrame indexing methods will not return a value of 20.6. However, without knowing the actual content of the DataFrame 'df', it's impossible to definitively answer this question.
Here's what each indexing method does:
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df.iloc[4,5]: This will return the value at the 5th row and 6th column of the DataFrame, using zero-based indexing.
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df.iloc[6,5]: This will return the value at the 7th row and 6th column of the DataFrame, using zero-based indexing.
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df.loc[4,’Music Recording Sales’]: This will return the value in the 'Music Recording Sales' column for the row with index label 4.
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df.iloc[6, ‘Music Recording Sales (millions)’]: This is actually an invalid command because .iloc[] does not accept column names, it only accepts integer-based indexing.
So, without knowing the DataFrame, we can say that df.iloc[6, ‘Music Recording Sales (millions)’] will not evaluate to 20.6 because it's an invalid command. For the others, it depends on the DataFrame's content.
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