WGU D206 - Data Cleaning - Lesson 3 Python Labs/ (Top 2024/2025 EXAM REVIEW PAPERS / GRADED A+/ 100% Accurate)

WGU D206 - Data Cleaning - Lesson 3 Python Labs Import the dataset Boston_housing_ with the locationid column being an integer. Use print() to see the dataset as output. - df = _csv('/home/ucertify/Boston_housing_',dtype={'locationid':64}) data = (5) print(data) Displays the number of rows and columns in the dataframe stored as df. - df = _csv('/home/ucertify/Boston_housing_',dtype={'locationid':64}) print() Display the column names in the dataframe stored as df. - df = _csv('/home/ucertify/Boston_housing_',dtype={'locationid':64}) print(list(s)) Display the mean, count, min, and max of all the numeric data using a single line of code in the dataframe stored as df. - df = _csv('/home/ucertify/Boston_housing_',dtype={'locationid':64}) data = ibe() print(data) Display the variable type of each column in the dataframe stored as df. - df = _csv('/home/ucertify/Boston_housing_',dtype={'locationid':64}) print (s) Display unique values in the locationzone column in dataframe stored as df. - df = _csv('/home/ucertify/Boston_housing_',dtype={'locationid':64}) uniqueValues = df['locationzone'].unique() print('Unique elements in column "locationzone" ') print(uniqueValues) Display the unique values in the locationzone column and the number of times each value appears in the dataframe stored as df. -df = _csv('/home/ucertify/Boston_housing_',dtype={'locationid':64}) data = df['locationzone'].value_counts() print(data) Import the data set Boston_housing_data_ with the locationid column being an integer. Use print() to see the data set as output. -df = _csv('/home/ucertify/Boston_housing_data_',dtype={'locationid':64}) print(df) Display any duplicate rows in the dataframe stored as df. -df = _csv('/home/ucertify/Boston_housing_',dtype={'locationid':64}) duplicatedRows = [cated()] print('Duplicated rows in "Boston_housing_data_clean" ') print(duplicatedRows) Ensure there are no missing observations in the dataframe stored as df. -df = _csv('/home/ucertify/Boston_housing_data_cle