HALL OF FAME

INDUCTIONSTALIA STRNAD

Agenda

Story

Problems

Solutions

Questions

Queries

References

Story

I am the dba at the baseball hall of fame.

My job duties include supervising the different customer service reps that

utilize the database on a daily basis.

At the museum, we use projections to display different information about

hall of fame inductions.

Also, we regularly get calls from organizations requesting statistics from the

hall of fame database.

Since my representatives don’t need access to the entire database, I

created different views for them to search through.

Problems

Did not have download problems with data

Online source converted to csv

However, had to copy/paste data into notepad, vs simply downloading data.

CSV format issues

%

Code names instead of real names

DECIMAL vs INT datatype

Try inserting/selecting value as integer

If column datatype is decimal need decimal value vs integer value

Problems with Common Table Expressions for certain math functions

Solutions

Changed data type from decimal to varchar in my table to accept %

Found new data to list names instead of codes

Changed selection to decimal value vs int value

For example: typed 437 instead of 437.0

Researched & found an example query of what I wanted: Common Table

Expression (CTE)

Helpful when you need to reference/join the same data set multiple times.

Questions Attempted

Are there more players than other positions inducted into the hall of fame

since 1936?

Are there more null or not null entries in the votes column?

How many managers have been inducted between 2009 & 2013? Since

2000?

Queries

Created a database

Created tables

Imported data into database/table

Inserted data into table

Created a view

Deleted entries in a table

Created an index

Retrieved data from more than one table

Combined rows from the player_info table based on the common

‘name’ field.

Queries Pt 2

Combined rows from the player_info & player_votestables based on the common ‘votes’ field.

Found the difference between 2 different counts of data

Counted all the votes in the table

Null valuesVacant (NOT EMPTY)

Not null values Not_Vacant

View all the results from the view

The year inducted between 2009-2013.

Query Pt 3

Described the table’s structure to test what

allowed nulls vs not nulls

VOTES & PERCENT_OF_BALLOTS = NULL

Concepts

Ch 1– Database (P1)

Structure that contains different categories of information and the relationships between these categories.

Use of: Created new database.

Ch 1- Sample Data (Entire chapter)

Set of data collected.

Use of: Retrieved sample data from website.

A sample of data: the view I created of managers inducted

after the year 2000.

Ch 2- Primary Key (P30)

Unique Identifier for the table.

All columns in the table functionally dependent on PK

No subcollection of the columns in the PK (if it’s a collection) also has attribute 1

Data didn’t come with one, so SQL created one (for each table & view).

Ch 2- First (1NF) & Second (2NF) normal forms (P40&44)

Does not contain a repeating group—1NF

1 NF & the primary key only contains a single column.—2NF

Concepts pt 2

Ch 3- INSERT command (P72)

Adds rows to a table.

Used when importing the data.

Ch 3- Data types (P70)

For each column in the table, specify the type of data to be stored.

For PERCENT_OF_BALLOTS, wanted to use DECIMAL. Needed VARCHAR instead. [%]

Ch 4- Aggregate functions (P112)

Special functions used by SQL

Used count to identify number of null values vs not nulls

Ch 4- Operators to retrieve certain sections/subsections of data (P105&108)

BETWEEN OPERATOR in view determine managers inducted BETWEEN 2009 & 2013

LIKE OPERATOR in create view query to only include those positions in view where the name is LIKE ‘MAN’.

Concepts pt 3

Ch 5- Self-join (P143)

Using an alias to join a table to itself

JOINED player_info table to itself with alias

NAME=NAME & INDUCTED_AS LIKE ‘%MAN%’

Ch 5- Correlated subquery (P139)

The subquery involves a table listed in the outer query

Ch 6- Creating new table from an existing (P167-169)

CREATE TABLE command

INSERT INTO command

Ch 6- DELETE COMMAND (P175)

To delete data from the database, use the DELETE COMMAND

DELETE COMMAND query

SELECT YEAR_INDUCTED, NAME, INDUCTED_ASFROM PLAYER_INFOWHERE EXISTS(SELECT *FROM AFTER2000WHERE INDUCTED BETWEEN 2010 AND 2014AND PLAYER_INFO.NAME = AFTER2000.NAMEAND NAME LIKE '%BOB%‘)GO

Concepts pt 4

Ch 7- CREATE VIEW COMMAND/defining query (P192)

A program’s/individual user’s picture of the database

Create view AFTER2000 to view the managers inducted after the year 2000

Ch 7-CREATE INDEX COMMAND (P 207)

The main way to increase the efficiency which data is retrieved from the

database.

Use of: Created index to search more easily through the names &

corresponding votes in descending order.

Takeaways

While working with my data, I began

to realize there were more

players than any other positions.

I couldn’t decide how to use basic math

in this assignment.

I realized, I could use math to describe this trend.

I figured out how to subtract 2 count queries and display the results as

‘difference.’

Sum up

I learned that even with a small data set (312 rows), you can still use the

data to help learn more about databases.

I enjoyed learning about & using baseball hall of fame statistics.

I enjoyed relearning all the database concepts.

References

http://stackoverflow.com/questions/2934192/beginner-sql-question-

arithmetic-with-multiple-count-results

http://stackoverflow.com/questions/4740748/when-to-use-common-table-

expression-cte

http://www.baseball-reference.com/awards/hof.shtml

Once at this site, select the CSV option as shown below. The data will be

converted to CSV on the browser. The downside is the CSV format is not directly

downloaded and you must copy/paste into a text editor.

Code--Appendix

CREATE DATABASE BASEBALL_STATS;

CREATE TABLE PLAYER_INFO

(

YEAR_INDUCTED VARCHAR(5) NOT NULL,

NAME VARCHAR(40) NOT NULL,

LIFE_SPAN VARCHAR(15) NOT NULL,

VOTED_BY VARCHAR(30) NOT NULL,

INDUCTED_AS VARCHAR(30) NOT NULL,

VOTES VARCHAR(15) NULL,

PERCENT_OF_BALLOTS VARCHAR(10) NULL

)

GO

Code—Pt 2

BULK

INSERT PLAYER_INFO

FROM '\\cpsc231-sqla\SHARED\TS28576\playerInfo.csv'

WITH

(

FIELDTERMINATOR = ',',

ROWTERMINATOR = '\n'

)

GO

--Check the content of the table.

Code—Pt 3

CREATE VIEW AFTER2000 (INDUCTED, NAME, JOB_TITLE) AS

SELECT YEAR_INDUCTED, NAME, INDUCTED_AS

FROM PLAYER_INFO

WHERE YEAR_INDUCTED > 2000

AND INDUCTED_AS LIKE '%MAN%';

CREATE TABLE PLAYER_VOTES

(NAME VARCHAR (50) NOT NULL,

VOTED_BY VARCHAR(15) NOT NULL,

VOTES DECIMAL(4, 1) NULL,

BALLOT_PERCENTAGE VARCHAR(25) NULL

)

GO

Code—Pt 4

INSERT INTO PLAYER_VOTES

SELECT NAME, VOTED_BY, VOTES, PERCENT_OF_BALLOTS

FROM PLAYER_INFO

WHERE VOTES < 300.0

GO

SELECT P1.NAME, P2.NAME, P1.INDUCTED_AS

FROM PLAYER_INFO P1, PLAYER_INFO P2

WHERE P1.NAME = P2.NAME

AND P1.INDUCTED_AS LIKE '%MAN%'

GO

Code—Pt 5

SELECT PLAY.NAME, VOTE.NAME, PLAY.INDUCTED_AS, VOTE.VOTES

FROM PLAYER_INFO PLAY, PLAYER_VOTES VOTE

WHERE PLAY.VOTES = VOTE.VOTES

AND PLAY.INDUCTED_AS LIKE '%PLAY%'

GO

SELECT * FROM AFTER2000 WHERE INDUCTED BETWEEN 2009 AND 2013

GO

SELECT COUNT(*) AS VACANT FROM PLAYER_INFO WHERE VOTES IS NULL;

SELECT COUNT(*) AS NOT_VACANT FROM PLAYER_INFO WHERE VOTES IS NOT NULL;

Code—Pt 6

CREATE INDEX VOTES ON PLAYER_VOTES(NAME, VOTES DESC);

SELECT YEAR_INDUCTED, NAME, INDUCTED_AS

FROM PLAYER_INFO

WHERE EXISTS

(SELECT *

FROM AFTER2000

WHERE INDUCTED BETWEEN 2010 AND 2014

AND PLAYER_INFO.NAME = AFTER2000.NAME

AND NAME LIKE '%BOB%'

)

GO

Code—Pt 7

WITH c1 AS(select count(*) as position from PLAYER_INFO WHERE INDUCTED_AS IS NOT NULL),

c2 AS

(SELECT COUNT(*) AS PLAYER FROM PLAYER_INFO WHERE INDUCTED_AS LIKE '%PLAY%')

SELECT c1.position, c2.PLAYER, c1.position -c2.PLAYER AS DIFFERENCE

FROM c1, c2

GO

sp_help PLAYER_INFO

GO

DELETE FROM PLAYER_VOTES WHERE VOTED_BY LIKE '%RU%';

Schema Diagram

Data Flow Diagram