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Pandas is built around data structures called Series and DataFrames. Data for these collections can be imported from various file formats such as comma-separated values, JSON, Parquet, SQL database tables or queries, and Microsoft Excel. [8] A Series is a 1-dimensional data structure built on top of NumPy's array.
Programs calling a database that accords to the SQL standard receive an indication of the success or failure of the call. This return code - which is called SQLSTATE - consists of 5 bytes.
A relation is in first normal form if and only if no attribute domain has relations as elements. [1] Or more informally, that no table column can have tables as values. Database normalization is the process of representing a database in terms of relations in standard normal forms, where first normal is a minimal requirement.
This is an important element of SQL. Statements, which may have a persistent effect on schemata and data, or may control transactions, program flow, connections, sessions, or diagnostics. SQL statements also include the semicolon (";") statement terminator. Though not required on every platform, it is defined as a standard part of the SQL grammar.
Data cleansing or data cleaning is the process of identifying and correcting (or removing) corrupt, inaccurate, or irrelevant records from a dataset, table, or database.It involves detecting incomplete, incorrect, or inaccurate parts of the data and then replacing, modifying, or deleting the affected data. [1]
SQL statements are used to perform tasks such as insert data to a database, delete or update data in a database, or retrieve data from a database. Though database systems use SQL, they also have their own additional proprietary extensions that are usually only used on their system.
Databases and other data stores which treat the integrity of data as paramount often include the ability to handle transactions to maintain the integrity of data. A single transaction consists of one or more independent units of work, each reading and/or writing information to a database or other data store.
The CAP theorem is based on three trade-offs, one of which is "atomic consistency" (shortened to "consistency" for the acronym), about which the authors note, "Discussing atomic consistency is somewhat different than talking about an ACID database, as database consistency refers to transactions, while atomic consistency refers only to a property of a single request/response operation sequence.