Where's the real money in Texas $$$

[Graybeard]

Well it's not in Dallas

data source: US IRS `individual personal` Tax Returns 2016 *based on public data
Multiplier is my own algorithm. USA median is about 220 :: Rank or 1.000

Where da F*K is Fullshear?

What you don't know can't help you!

 

[Graybeard]

Is gets worse!
The Fat Cats in Washington DC representing "the people"
look what they are making!

 

[Graybeard]

Would visual charts be better -- something like this?

 

[Graybeard]

______________________________________________________________
K.I.S.S

 

[tom804]

Am i'm the only one that thinks Graybeard is robot? lol

 

[Paularo]

Am i'm the only one that thinks Graybeard is robot? lol

He is Mr Robot's robot

 

[Graybeard]

I am one of the Puppet Masters -- I make the robots dance

mysql> select AVG(borrowerInc), AVG(AreaMedianHsldInc),
AVG(AgeB1) from fha_loans_2017 WHERE postal2d='6'
and MSA ='40900' AND county_code = '113' ;
+------------------+------------------------+------------+
| AVG(borrowerInc) | AVG(AreaMedianHsldInc) | AVG(AgeB1) |
+------------------+------------------------+------------+
| 124942.5527 | 75200.0000 | 47.7468 |
+------------------+------------------------+------------+
1 row in set (1.00 sec)

mysql> select * from zip_tract_crosswalk WHERE tract REGEXP '10310$'; +--------+-------+-------------+
| id | zip | tract |
+--------+-------+-------------+
| 4246 | 23666 | 51650010310 |
| 46303 | 46254 | 18097310310 |
| 58806 | 87035 | 35049010310 |
| 75379 | 95691 | 06113010310 |
| 102903 | 87047 | 35049010310 |
| 120218 | 87056 | 35049010310 |
| 145511 | 87015 | 35049010310 |
+--------+-------+-------------+
7 rows in set (0.09 sec)

mysql> select * from zip_tract_crosswalk WHERE zip REGEXP '95691';
+--------+-------+-------------+
| id | zip | tract |
+--------+-------+-------------+
| 11210 | 95691 | 06113010402 |
| 32745 | 95691 | 06113010201 |
| 32747 | 95691 | 06113010204 |
| 37769 | 95691 | 06113010102 |
| 75379 | 95691 | 06113010310 |
| 96790 | 95691 | 06113010302 |
| 118221 | 95691 | 06113010312 |
| 139894 | 95691 | 06113010203 |
+--------+-------+-------------+
8 rows in set (0.09 sec)

Google Maps

 

[marketingbro]

Nice SQL skills. I also appreciate your ability to use open source libraries to create user interfaces to display data.

 

[marketingbro]

There seems to be a miscommunication between the display of purpose portrayed.

 

[Graybeard]

the chart is just a test mock-up -- the JavaScript injection of the watermarked background was the purpose of that test.

my database is getting big
| DATABASE_NAME | SUM(TABLE_ROWS) |
+----------------------+-----------------------+
| entries | 17,791,908 |
+----------------------+-----------------------+
| medical | 20,037,242 |
+----------------------+-----------------------+



In the end there will be small specific databases related to categories and chart data will be injected into the HTML from JSON code

 

[Graybeard]

this is the complex stuff; and it really isn't once composed as a query
***need to SET the variable FIRST
oops
mysql> SET @INCaffinity:=(SELECT
-> affinity
-> FROM change_pct_cx WHERE series_id = 'CXU270102LB0201M' AND year=2017);
Query OK, 0 rows affected (0.33 sec)
mysql> SELECT
-> "All USA Consumers" AS "Cellular phone by Income Range:",
-> year,
-> (affinity/@INCaffinity) AS "Affinity Index"
-> FROM change_pct_cx WHERE series_id = 'CXU270102LB0201M' AND year=2017
-> UNION ALL
-> SELECT
-> "Less than $15,000" AS "Cellular phone by Income Range:",
-> year,
-> (affinity/@INCaffinity) AS "Affinity Index"
-> FROM change_pct_cx WHERE series_id = 'CXU270102LB0218M' AND year=2017
-> UNION ALL
-> SELECT
-> "$15,000 to $29,999" AS "Cellular phone by Income Range:",
-> year,
-> (affinity/@INCaffinity) AS "Affinity Index"
-> FROM change_pct_cx WHERE series_id = 'CXU270102LB0219M' AND year=2017
-> UNION ALL
-> SELECT
-> "$30,000 to $39,999" AS "Cellular phone by Income Range:",
-> year,
-> (affinity/@INCaffinity) AS "Affinity Index"
-> FROM change_pct_cx WHERE series_id = 'CXU270102LB0207M' AND year=2017
-> UNION ALL
-> SELECT
-> "$40,000 to $49,999" AS "Cellular phone by Income Range:",
-> year,
-> (affinity/@INCaffinity) AS "Affinity Index"
-> FROM change_pct_cx WHERE series_id = 'CXU270102LB0208M' AND year=2017
-> UNION ALL
-> SELECT
-> "$50,000 to $69,999" AS "Cellular phone by Income Range:",
-> year,
-> (affinity/@INCaffinity) AS "Affinity Index"
-> FROM change_pct_cx WHERE series_id = 'CXU270102LB0209M' AND year=2017
-> UNION ALL
-> SELECT
-> "$70,000 to $99,999" AS "Cellular phone by Income Range:",
-> year,
-> (affinity/@INCaffinity) AS "Affinity Index"
-> FROM change_pct_cx WHERE series_id = 'CXU270102LB0220M' AND year=2017
-> UNION ALL
-> SELECT
-> "$100,000 to $149,999" AS "Cellular phone by Income Range:",
-> year,
-> (affinity/@INCaffinity) AS "Affinity Index"
-> FROM change_pct_cx WHERE series_id = 'CXU270102LB0221M' AND year=2017
-> UNION ALL
-> SELECT
-> "$150,000 to $199,999" AS "Cellular phone by Income Range:",
-> year,
-> (affinity/@INCaffinity) AS "Affinity Index"
-> FROM change_pct_cx WHERE series_id = 'CXU270102LB0222M' AND year=2017
-> UNION ALL
-> SELECT
-> "$200,000 and more" AS "Cellular phone by Income Range:",
-> year,
-> (affinity/@INCaffinity) AS "Affinity Index"
-> FROM change_pct_cx WHERE series_id = 'CXU270102LB0223M' AND year=2017
-> ORDER BY `Affinity Index`DESC
-> ;
+---------------------------------+------+----------------+
| Cellular phone by Income Range: | year | Affinity Index |
+---------------------------------+------+----------------+
| $200,000 and more | 2017 | 1.7182 |
| $150,000 to $199,999 | 2017 | 1.6055 |
| $100,000 to $149,999 | 2017 | 1.4410 |
| $70,000 to $99,999 | 2017 | 1.2460 |
| $50,000 to $69,999 | 2017 | 1.0599 |
| All USA Consumers | 2017 | 1.0000 |
| $40,000 to $49,999 | 2017 | 0.8980 |
| $30,000 to $39,999 | 2017 | 0.8426 |
| $15,000 to $29,999 | 2017 | 0.5760 |
| Less than $15,000 | 2017 | 0.4195 |
+---------------------------------+------+----------------+
10 rows in set (1.47 sec)
this indicates people that pay for service and probably pay for most mobile phone userd. This is NOT mobile phone USAGE by income group.