Write down the algorithm of this code: count = 0 delivery_df_1st_innings = pd.DataFrame() for index, row in final_df.iterrows(): if count in [75,108,150,180,268,360,443,458,584,748,982,1052,1111,1226,1345]: count+=1 continue count+=1 ball_of_match = [] runs = [] player_of_dismissed = [] teams = [] batting_team = [] winner = [] win_by_runs = 0 win_by_wickets = [] match_id= [] city = [] venue = [] for ball in row['innings'][0]['1st innings']['deliveries']: for key in ball.keys(): match_id.append(count) batting_team.append(row['innings'][0]['1st innings']['team']) teams.append(row['info.teams']) winner.append(row['info.outcome.winner']) ball_of_match.append(key) runs.append(ball[key]['runs']['total']) city.append(row['info.city']) venue.append(row['info.venue']) try: player_of_dismissed.append(ball[key]['wicket']['player_out']) except: player_of_dismissed.append('0') loop_df = pd.DataFrame({ 'match_id':match_id, 'teams':teams, 'batting_team':batting_team, 'winner':winner, 'ball':ball_of_match, 'runs':runs, 'player_dismissed':player_of_dismissed, 'city':city, 'venue':venue }) delivery_df_1st_innings = delivery_df_1st_innings.append(loop_df)

Write down the algorithm of this code: count = 0 delivery_df_1st_innings = pd.DataFrame() for index, row in final_df.iterrows(): if count in [75,108,150,180,268,360,443,458,584,748,982,1052,1111,1226,1345]: count+=1 continue count+=1 ball_of_match = [] runs = [] player_of_dismissed = [] teams = [] batting_team = [] winner = [] win_by_runs = 0 win_by_wickets = [] match_id= [] city = [] venue = [] for ball in row['innings'][0]['1st innings']['deliveries']: for key in ball.keys(): match_id.append(count) batting_team.append(row['innings'][0]['1st innings']['team']) teams.append(row['info.teams']) winner.append(row['info.outcome.winner']) ball_of_match.append(key) runs.append(ball[key]['runs']['total']) city.append(row['info.city']) venue.append(row['info.venue']) try: player_of_dismissed.append(ball[key]['wicket']['player_out']) except: player_of_dismissed.append('0') loop_df = pd.DataFrame({ 'match_id':match_id, 'teams':teams, 'batting_team':batting_team, 'winner':winner, 'ball':ball_of_match, 'runs':runs, 'player_dismissed':player_of_dismissed, 'city':city, 'venue':venue }) delivery_df_1st_innings = delivery_df_1st_innings.append(loop_df)

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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Recamán's sequencedef recaman(n):Compute and return the first n terms of the Recamán's sequence, starting from the term a1 = 1. n Expected result 10 [1, 3, 6, 2, 7, 13, 20, 12, 21, 11] 1000000 (a list of million elements whose last five elements are [2057162,1057165, 2057163, 1057164, 2057164] )
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Case study: An event company asks you to design the data structure and program prototype for their running event system. The participant for the running event is expected to reach more than 1000 in various categories. You decided to use hashing function method to store the information for each participant's BIB number in the hash table. To begin the problem solving, suppose that 10 registered runners need to be stored in a hash table, HT, with a size of 13. The sample BIB number of the runners are: 101, 102, 103, 104, 107, 111, 121, 217, 157, and 185. Furthermore, you set the hash function to determine the index of the participant in the HT as: hash (BIB) = BIB % table size (or 13) However, if the hash index given by hash(BIB) is already occupied (collision), the linear probing hash function will be used as: hash (BIB) = (Hash (BIB)+1) % 17 and, further collision with hash function: hash (BIB) = (Hash(BIB)+2) % 17 or, hash(BIB) = (Hash (BIB) + n) % 17, where n is probe increment. Refer…
Given code that reads user IDs (until -1), complete the quicksort() and partition() functions to sort the IDs in ascending order using the Quicksort algorithm. Increment the global variable num_calls in quicksort() to keep track of how many times quicksort() is called. The given code outputs num_calls followed by the sorted IDs. Ex: If the input is: kaylasimms julia myron1994 kaylajones -1 the output is: 7 julia kaylajones kaylasimms myron1994 I am having issues getting the count correct. What should I be looking at to adjust the count?
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