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Pandas (styled as pandas) is a software library written for the Python programming language for data manipulation and analysis. In particular, it offers data structures and operations for manipulating numerical tables and time series. It is free software released under the three-clause BSD license. [2]
SQLAlchemy offers tools for database schema generation, querying, and object-relational mapping. Key features include: A comprehensive embedded domain-specific language for SQL in Python called "SQLAlchemy Core" that provides means to construct and execute SQL queries. A powerful ORM that allows the mapping of Python classes to database tables.
In a database, a table is a collection of related data organized in table format; consisting of columns and rows.. In relational databases, and flat file databases, a table is a set of data elements (values) using a model of vertical columns (identifiable by name) and horizontal rows, the cell being the unit where a row and column intersect. [1]
Below are some of the areas where Python is used: [16] Web Development: Frameworks like Django and Flask have allowed web developers to create robust web servers that can also take advantage of the wider Python ecosystem. Science and Academia: Scientific and data libraries, like SciPy and Pandas, have enabled Python's use in scientific research ...
An alternative to implementing ORM is use of the native procedural languages provided with every major database. These can be called from the client using SQL statements. The Data Access Object (DAO) design pattern is used to abstract these statements and offer a lightweight object-oriented interface to the rest of the application. [5]
The web server or database management system also varies. LEMP is a version where Apache has been replaced with the more lightweight web server Nginx. [6] A version where MySQL has been replaced by PostgreSQL is called LAPP, or sometimes by keeping the original acronym, LAMP (Linux / Apache / Middleware (Perl, PHP, Python, Ruby) / PostgreSQL). [7]
Depending on the amount and format of the incoming data, data wrangling has traditionally been performed manually (e.g. via spreadsheets such as Excel), tools like KNIME or via scripts in languages such as Python or SQL. R, a language often used in data mining and statistical data analysis, is now also sometimes used for data wrangling. [6]
It is an open-source cross-platform integrated development environment (IDE) for scientific programming in the Python language.Spyder integrates with a number of prominent packages in the scientific Python stack, including NumPy, SciPy, Matplotlib, pandas, IPython, SymPy and Cython, as well as other open-source software.