[amp_mcq option1=”melt()” option2=”df[‘new_column’] = np.where(…)” option3=”sort_values()” option4=”melt()” correct=”option2″]<\/p>\n
The correct answer is B. df[‘new_column’] = np.where(…).<\/p>\n
The The The Here is an example of how to use the “` df = pd.DataFrame({‘A’: [1, 2, 3], ‘B’: [4, 5, 6]})<\/p>\n df[‘new_column’] = np.where(df[‘A’] > 2, ‘greater than 2’, ‘less than or equal to 2’)<\/p>\n print(df)<\/p>\n A B new_column In this example, the [amp_mcq option1=”melt()” option2=”df[‘new_column’] = np.where(…)” option3=”sort_values()” option4=”melt()” correct=”option2″]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[737],"tags":[],"class_list":["post-51944","post","type-post","status-publish","format-standard","hentry","category-data-analysis-with-python","no-featured-image-padding"],"yoast_head":"\nnp.where()<\/code> function takes three arguments: a condition, a value to return if the condition is true, and a value to return if the condition is false. In this case, the condition is a boolean expression that compares the values in two columns. If the condition is true, the value in the new_column<\/code> will be the value in the first column. If the condition is false, the value in the new_column<\/code> will be the value in the second column.<\/p>\nmelt()<\/code> function converts a DataFrame from a long format to a wide format. In a long format DataFrame, each row represents a single observation, and each column represents a variable. In a wide format DataFrame, each row represents a single variable, and each column represents a single observation.<\/p>\nsort_values()<\/code> function sorts a DataFrame by the values in a specified column.<\/p>\nnp.where()<\/code> function to create a new column based on conditional logic applied to existing columns:<\/p>\n
\nimport pandas as pd<\/p>\n
\n0 1 4 greater than 2
\n1 2 5 less than or equal to 2
\n2 3 6 less than or equal to 2
\n“`<\/p>\nnew_column<\/code> is created by comparing the values in the A<\/code> column to the value 2. If the value in the A<\/code> column is greater than 2, the value in the new_column<\/code> is greater than 2<\/code>. If the value in the A<\/code> column is less than or equal to 2, the value in the new_column<\/code> is less than or equal to 2<\/code>.<\/p>\n","protected":false},"excerpt":{"rendered":"