{"id":52460,"date":"2024-04-15T23:39:40","date_gmt":"2024-04-15T23:39:40","guid":{"rendered":"https:\/\/exam.pscnotes.com\/mcq\/?p=52460"},"modified":"2024-04-15T23:39:40","modified_gmt":"2024-04-15T23:39:40","slug":"in-pandas-what-method-is-used-to-apply-a-function-to-each-element-of-a-series","status":"publish","type":"post","link":"https:\/\/exam.pscnotes.com\/mcq\/in-pandas-what-method-is-used-to-apply-a-function-to-each-element-of-a-series\/","title":{"rendered":"In Pandas, what method is used to apply a function to each element of a Series?"},"content":{"rendered":"

[amp_mcq option1=”pivot()” option2=”melt()” option3=”sort_values()” option4=”apply()” correct=”option4″]<\/p>\n

The correct answer is D. apply().<\/p>\n

The apply() method is used to apply a function to each element of a Series. The function can be any Python function, and it can take any number of arguments. The apply() method returns a new Series with the results of the function applied to each element of the original Series.<\/p>\n

The pivot() method is used to pivot a DataFrame. This means that it changes the DataFrame’s columns into rows and the rows into columns. The melt() method is used to melt a DataFrame. This means that it changes the DataFrame’s columns into a single column with multiple values. The sort_values() method is used to sort a DataFrame by one or more columns.<\/p>\n

Here is an example of how to use the apply() method:<\/p>\n

“`
\nimport pandas as pd<\/p>\n

df = pd.DataFrame({‘A’: [1, 2, 3], ‘B’: [4, 5, 6]})<\/p>\n

result = df.apply(lambda x: x * 2)<\/p>\n

print(result)<\/p>\n

\n
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