Question
Based on the given dataset answer the questions given below:

From_To FlightNumber RecentDelays Airline
0 NewDelhi_Chennai 10045.0 [23, 47] Spicejet
1 Mumbai_NewDelhi NaN [] Indigo
2 Jaipur_Jammu 10065.0 [24, 43, 87] Spicejet
3 Chennai_Lucknow NaN [13] Indian Airlines
4 Mumnbai_Chennai 10085.0 [67, 32] Spicejet

(i) #To display the maximum flight number

(ii) #To print the number of flights airline wise

(iii) #to drop the nan values from the dataframe

(iv) To fill nan with blank values

(v) To print the maximum values of recent delays

(vi) To print the median of all the numeric values.

(vii) To print the sum of the recentdelays

(viii) To count the flight numbers.

(ix) To print the airline wise the sum of the recentdelays along with From_to as column

(x) To print the airline wise the sum of the recentdelays along with From_to as column. Also fill NaN values as blank.

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Relation: Club

Coach-ID CoachName Age Sports date_of_app Pay Sex
1 Kukreja 35 Karate 27/03/1996 1000 M
2 Ravina 34 Karate 20/01/1998 1200 F
3 Karan 34 Squash 19/02/1998 2000 M
4 Tarun 33 Basketball 01/01/1998 1500 M
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8 Zareen 37 Karate 22/02/1998 1100 F
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10 Shailya 37 Basketball 19/02/1998 1700 M

(a) To show all information about the swimming coaches in the club.

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(c) To display a report showing coach name, pay, age, and bonus (15% of pay) for all coaches.

(d) To insert a new row in the Club table with ANY relevant data:

(e) Give the output of the following SQL statements:

(i) Select COUNT(Distinct Sports) from Club;

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Write the SQL query questions from (i) to (iv) and write the output of SQL command for questions from (v) to (vii) given below:

EMPID FIRST NAME LAST NAME ADDRESS CITY
010 George Smith 83 First Street Howard
105 Mary Jones 842 Vine Ave. Losantiville
152 Sam Tones 33 Elm St. Paris
215 Sarah Ackerman 440 U.S. 110 Upton
244 Manila Sengupta 24 Friends Street New Delhi
300 Robert Samuel 9 Fifth Cross Washington
335 Henry Williams 12 Moore Street Boston
400 Rachel Lee 121 Harrison St. New York
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Table: EMPSalary

EMPID SALARY BENEFITS DESIGNATION
010 75000 15000 Manager
105 65000 15000 Manager
152 80000 25000 Director
215 75000 12500 Manager
244 50000 12000 Clerk
300 45000 10000 Clerk
355 40000 10000 Clerk
4000 32000 7500 Salesman
441 28000 7500 Salesman

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empid=Empsalary.empid;

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