dp-100-data-scientist-assoc video for scenario: The Unlimited Class Wrestling Federation (UCWF) was founded by promoter Edward Garner, who strives to enhance
Scenario: The Unlimited Class Wrestling Federation (UCWF) was founded by promoter Edward Garner, who strives to enhance his business through technology. He has enlisted your expertise to assist with the company's Microsoft Azure service. Currently, the team is working on a project to analyze demographic data for wrestling fans across different cities. The dataset is stored in a CSV file with the following structure: age , city , income , wrestling_fans 21 , Chicago , 50000 , 1200 35 , Seattle , 120000 , 1300 23 , Seattle , 65000 , 2300 45 , Seattle , 130000 , 1100 18 , Chicago , 48000 , 3500 The lead data scientist is conducting an experiment in the Azure Machine Learning workspace and must log key insights, including: The number of observations in the dataset. A box plot showing income by wrestling fans. A dictionary mapping city names to average income. The following code snippet contains placeholders [A], [B], and [C], where the appropriate logging methods need to be inserted: python # Log the number of observations row_count = ( len ( data )) run .[ A ]( "observations" , row_count ) # Log box plot for income by wrestling_fan fig = fig . gca () data . boxplot ( column = 'income' , by = "wrestling_fan" , ax = ax ) ax . set_title ( 'income by wresting_fan' ) ax . set_ylable ( 'income' ) run .[ B ]( name = 'income_by_wrestling_fan' , plot = fig ) # Createa dataframe of mean income per city mean_inc_df = data . groupby ( 'city' )[ 'income' ]. agg ( np . mean ). to_frame (). reset_index () # Convert to a dictionary mean_inc_dict = mean_inc_df . to_dict ( 'dict' ) # Log city names and average income dictionary run .[ C ]( name = "mean_income_by_city" , value = mean_inc_dict ) # Complete tracking and get link to details run . complete () Which of the following methods should be used to replace placeholders [A] , [B] , and [C] in the code?