Given the following Python code: import pandas as pd p = pd. read_csv ("patients.csv") a = pd. read_csv ("appointments.c

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Given The Following Python Code Import Pandas As Pd P Pd Read Csv Patients Csv A Pd Read Csv Appointments C 1 (43.22 KiB) Viewed 25 times

Given the following Python code: import pandas as pd p = pd. read_csv ("patients.csv") a = pd. read_csv ("appointments.csv") c = pd.merge(a, p, how='inner', on='pid') pf = c[ c['payment']>50.00 ] pf.sort_values (by=['date'], ascending=False) Assume the input CSV data would have been stored in relational tables of the same schema. What would be an equivalent SQL query producing the same output than the given Python/Pandas code? O SELECT * FROM Patients INNER JOIN Appointments USING (pid) WHERE payment > 50.00 ORDER BY ASC-False SELECT * FROM Appointments JOIN Patients WHERE payment > 50.00 ORDER BY date ASC SELECT * FROM Patients MERGE Appointments WHERE payment > 50.00 ORDER BY date ASC SELECT * FROM Appointments NATURAL JOIN Patients WHERE payment > 50.00 ORDER BY date DESC SELECT * FROM Patients INNER JOIN Appointments USING (pid) ORDER BY date DESC O