Numeric Data Types and Summary Functions

Exploratory Data Analysis in SQL

Christina Maimone

Data Scientist

Numeric types: integer

Name	Storage Size	Description	Range
`integer` or `int` or `int4`	4 bytes	typical choice	-2147483648 to +2147483647

Numeric types: integer

Name	Storage Size	Description	Range
`integer` or `int` or `int4`	4 bytes	typical choice	-2147483648 to +2147483647
`smallint` or `int2`	2 bytes	small-range	-32768 to +32767
`bigint` or `int8`	8 bytes	large-range	-9223372036854775808 to +9223372036854775807

Numeric types: integer

Name	Storage Size	Description	Range
`integer` or `int` or `int4`	4 bytes	typical choice	-2147483648 to +2147483647
`smallint` or `int2`	2 bytes	small-range	-32768 to +32767
`bigint` or `int8`	8 bytes	large-range	-9223372036854775808 to +9223372036854775807
`serial`	4 bytes	auto-increment	1 to 2147483647
`smallserial`	2 bytes	small auto-increment	1 to 32767
`bigserial`	8 bytes	large auto-increment	1 to 9223372036854775807

Numeric types: decimal

Name	Storage Size	Description	Range
`decimal` or `numeric`	variable	user-specified precision, exact	up to 131072 digits before the decimal point; up to 16383 digits after the decimal point

Numeric types: decimal

Name	Storage Size	Description	Range
`decimal` or `numeric`	variable	user-specified precision, exact	up to 131072 digits before the decimal point; up to 16383 digits after the decimal point
`real`	4 bytes	variable-precision, inexact	6 decimal digits precision
`double precision`	8 bytes	variable-precision, inexact	15 decimal digits precision

Division

-- integer division
SELECT 10/4;

-- numeric division
SELECT 10/4.0;

2.500000000

Range: min and max

SELECT min(question_pct)
  FROM stackoverflow;

 min 
-----
   0
(1 row)

SELECT max(question_pct)
  FROM stackoverflow;

     max     
-------------
 0.071957428
(1 row)

Average or mean

SELECT avg(question_pct)
  FROM stackoverflow;

         avg         
---------------------
 0.00379494620059319
(1 row)

Variance

Population Variance

SELECT var_pop(question_pct)
  FROM stackoverflow;

       var_pop        
----------------------
 0.000140268640974167
(1 row)

Sample Variance

SELECT var_samp(question_pct)
  FROM stackoverflow;

       var_samp       
----------------------
 0.000140271571051059
(1 row)

SELECT variance(question_pct)
  FROM stackoverflow;

       variance       
----------------------
 0.000140271571051059
(1 row)

Standard deviation

Sample Standard Deviation

SELECT stddev_samp(question_pct)
  FROM stackoverflow;

     stddev_samp     
--------------------
 0.0118436299778007
(1 row)

SELECT stddev(question_pct)
  FROM stackoverflow;

       stddev       
--------------------
 0.0118436299778007
(1 row)

Population Standard Deviation

SELECT stddev_pop(question_pct)
  FROM stackoverflow;

      stddev_pop     
--------------------
 0.0118435062787237
(1 row)

Round

SELECT round(42.1256, 2);

42.13

Summarize by group

-- Summarize by group with GROUP BY
SELECT tag,
       min(question_pct), 
       avg(question_pct), 
       max(question_pct) 
  FROM stackoverflow
 GROUP BY tag;

           tag            |     min     |         avg          |     max     
--------------------------+-------------+----------------------+-------------
 amazon-sqs               |    6.91e-05 | 8.08328877005347e-05 |     9.6e-05
 amazon-kinesis           |     2.1e-05 |  3.3924064171123e-05 |    4.64e-05
 android-pay              |    2.97e-05 | 3.16712477396022e-05 |    3.29e-05
 amazon-cloudformation    |     4.8e-05 | 9.34518997326204e-05 |  0.00015246
 citrix                   |     3.6e-05 | 3.95804407713499e-05 |    4.39e-05
 amazon-ec2               | 0.001058039 |  0.00122817236730946 | 0.001378872
 actionscript             | 0.000551486 |  0.00067589990909091 | 0.000856132
 amazon-ecs               |    1.17e-05 | 3.40544117647059e-05 |    6.51e-05
 mongodb                  |   0.0049625 |  0.00577465885069125 |  0.00631164
 amazon-redshift          | 0.000117294 | 0.000160832181818182 | 0.000212208
...

Let's work with numbers!

Exploratory Data Analysis in SQL