Goal Find base table columns that have FLOAT, REAL, or DOUBLE PRECISION type. "The data types real and double precision are inexact, variable-precision numeric types. On all currently supported platforms, these types are implementations of IEEE Standard 754 for Binary Floating-Point Arithmetic (single and double precision, respectively), to the extent that the underlying processor, operating system, and compiler support it." (PostgreSQL documentation) Do not use the approximate numeric types FLOAT, REAL, and DOUBLE PRECISION in order to present fractional numeric data. Due to the use of the IEEE 754 standard the results of calculations with the values, which have one of these types, can be inexact because out of necessity some numbers must be rounded to a value, which is very close. "Comparing two floating-point values for equality might not always work as expected." (PostgreSQL documentation)
Type Problem detection (Each row in the result could represent a flaw in the design)
Reliability High (Few or no false-positive results)
License MIT (opens in new tab)
Fixing Suggestion If you require exact storage and calculations (such as for monetary amounts), use the numeric type instead.
Data Source INFORMATION_SCHEMA only
SQL Query 
SELECT table_schema, table_name, column_name, data_type
FROM INFORMATION_SCHEMA.columns
WHERE data_type IN ('real','float', 'double precision') AND 
(table_schema, table_name) IN (SELECT table_schema, table_name
FROM INFORMATION_SCHEMA.tables WHERE table_type='BASE TABLE') AND 
table_schema NOT IN (SELECT schema_name
FROM INFORMATION_SCHEMA.schemata
WHERE schema_name<>'public' AND
schema_owner='postgres' AND schema_name IS NOT NULL)
ORDER BY table_schema, table_name, ordinal_position;

Collections

This query belongs to the following collections:

Find problems about base tables

A selection of queries that return information about the data types, field sizes, default values as well as general structure of base tables. Contains all the types of queries - problem detection, software measure, and general overview

Find problems automatically

Queries, that results point to problems in the database. Each query in the collection produces an initial assessment. However, a human reviewer has the final say as to whether there is a problem or not .

NameDescription
Find problems about base tablesA selection of queries that return information about the data types, field sizes, default values as well as general structure of base tables. Contains all the types of queries - problem detection, software measure, and general overview
Find problems automaticallyQueries, that results point to problems in the database. Each query in the collection produces an initial assessment. However, a human reviewer has the final say as to whether there is a problem or not .

Categories

This query is classified under the following categories:

Comfortability of data management

Queries of this category provide information about the means that have been used to make the use or management of database more comfortable and thus, more efficient.

Database design antipatterns

Queries of this category provide information about possible occurrences of SQL database design antipatterns.

Data types

Queries of this category provide information about the data types and their usage.

NameDescription
Comfortability of data managementQueries of this category provide information about the means that have been used to make the use or management of database more comfortable and thus, more efficient.
Database design antipatternsQueries of this category provide information about possible occurrences of SQL database design antipatterns.
Data typesQueries of this category provide information about the data types and their usage.

Further reading and related materials:

This is one of the antipatterns from the Bill Karwin's book of SQL antipatterns. See Chapter 10: Rounding errors.
https://www.postgresql.org/docs/current/datatype-numeric.html
http://weitz.de/ieee/
https://stackoverflow.com/questions/15726535/postgresql-which-datatype-should-be-used-for-currency
Factor, P.: SQL Code Smells. Redgate, http://assets.red-gate.com/community/books/sql-code-smells.pdf, last accessed 2019/12/29 (Using FLOAT or REAL data types)
Dintyala, P., Narechania, A., Arulraj, J.: SQLCheck: automated detection and diagnosis of SQL anti-patterns. In: 2020 ACM SIGMOD International Conference on Management of Data, pp. 2331–2345. (2020). https://doi.org/10.1145/3318464.3389754 (Rounding Errors)
Reference
This is one of the antipatterns from the Bill Karwin's book of SQL antipatterns. See Chapter 10: Rounding errors.
https://www.postgresql.org/docs/current/datatype-numeric.html
http://weitz.de/ieee/
https://stackoverflow.com/questions/15726535/postgresql-which-datatype-should-be-used-for-currency
Factor, P.: SQL Code Smells. Redgate, http://assets.red-gate.com/community/books/sql-code-smells.pdf, last accessed 2019/12/29 (Using FLOAT or REAL data types)
Dintyala, P., Narechania, A., Arulraj, J.: SQLCheck: automated detection and diagnosis of SQL anti-patterns. In: 2020 ACM SIGMOD International Conference on Management of Data, pp. 2331–2345. (2020). https://doi.org/10.1145/3318464.3389754 (Rounding Errors)