Which of the following code blocks returns a collection of summary statistics for all columns in
DataFrame storesDF?
Which of the following code blocks returns a collection of summary statistics for all columns in
DataFrame storesDF?
The describe() method in DataFrame returns a DataFrame with summary statistics for all numeric columns in the input DataFrame. These statistics include count, mean, standard deviation, minimum, and maximum values. By calling storesDF.describe(), it provides a comprehensive summary without needing additional parameters.
E is correct, it's giving the output.
The answer is B. Explanation: The describe() method in DataFrame returns a DataFrame with summary statistics for all numeric columns in the input DataFrame. By default, only the count, mean, standard deviation, minimum, and maximum values are returned, but additional statistics can be specified with the percentiles parameter. Setting the all parameter to True will include non-numeric columns in the output as well. Therefore, option B is the correct answer. Option A is not correct, as the summary() method only returns summary statistics for the specified column(s) and is not a valid option for returning summary statistics for all columns in the DataFrame. Option C is not correct, as the describe() method does not have an "all" option. Option D is also not correct, as the summary() method only returns summary statistics for the specified column(s) and does not have an "all" option. Option E is not incorrect, but it does not specify whether to include non-numeric columns in the output. Therefore, option B is a better answer.
Did you really try this in pyspark, or look up the document? TypeError: describe() got an unexpected keyword argument 'all'
describe() is correct
Is you answer from Chat GPT ?
even chat gpt says E is the correct one :)
TypeError Traceback (most recent call last) <ipython-input-34-5077330dead7> in <cell line: 1>() ----> 1 storesDF.describe(all = True) TypeError: DataFrame.describe() got an unexpected keyword argument 'all'
B is correct. On running the last option it gives error. TypeError: describe() got an unexpected keyword argument 'all'
checked it, it gave me the right result, so E is the one
check the documentation, mates. both methods receive names of columns as arguments, so E is correct!
E is the correct answer
tested e is the right answer
E would be correct here
E is the correct one