3.) Find the goalkeepers of teams that played more than four games. List the surname of the goalkeeper, the team, and the number of minutes the goalkeeper played. 4) How many players who play on a team with ranking<10played more than 350 minutes? Return one number in a column named 'superstar'. 5) What is the average number of passes made by forwards? By midfielders? Write one query that gives both values with the corresponding position.

Np Ms Office 365/Excel 2016 I Ntermed
1st Edition
ISBN:9781337508841
Author:Carey
Publisher:Carey
Chapter8: Working With Advanced Functions
Section: Chapter Questions
Problem 2.7CP
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3.) Find the goalkeepers of teams that played more than four games. List the surname of the goalkeeper, the team, and the number of minutes the goalkeeper played.
4) How many players who play on a team with ranking<10played more than 350 minutes? Return one number in a column named 'superstar'.
5) What is the average number of passes made by forwards? By midfielders? Write one query that gives both values with the corresponding position.
6) Which team has the highest average number of passes per minute played? Return the team and average passes per minute. Hints:
(1) You can compute a team's average number of passes per minute played by dividing the total number of passes by the total number of minutes. To force floating point division, multiply one operand by 1.0.
(2) Consider using Limit.
 
a
KOO
[ ]: %%sql
YOUR QUERY HERE
Markdown
Your Turn - Basic SQL on World Cup Data (Graded)
[ ]: # Upload world cup data files
# Choose files Players.csv and Teams.csv
from google.colab import files
uploaded files.upload()
# Then Load tables from CSV files
with open('Players.csv') as f: Players
Xsql drop table if exists Players;
[ ]: XXsql
%sql persist Players
with open('Teams.csv') as f: Teams pd.read_csv(f, index_col-0)
Xsql drop table if exists Teams;
Xsql persist Teams
must be on Local computer
-
select from Players limit 5
pd.read_csv(f, index_col-0)
Look at sample of Players and Teams tables
Transcribed Image Text:a KOO [ ]: %%sql YOUR QUERY HERE Markdown Your Turn - Basic SQL on World Cup Data (Graded) [ ]: # Upload world cup data files # Choose files Players.csv and Teams.csv from google.colab import files uploaded files.upload() # Then Load tables from CSV files with open('Players.csv') as f: Players Xsql drop table if exists Players; [ ]: XXsql %sql persist Players with open('Teams.csv') as f: Teams pd.read_csv(f, index_col-0) Xsql drop table if exists Teams; Xsql persist Teams must be on Local computer - select from Players limit 5 pd.read_csv(f, index_col-0) Look at sample of Players and Teams tables
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