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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 .
The name "CSV" indicates the use of the comma to separate data fields. Nevertheless, the term "CSV" is widely used to refer to a large family of formats that differ in many ways. Some implementations allow or require single or double quotation marks around some or all fields; and some reserve the first record as a header containing a list of ...
The two most common representations are column-oriented (columnar format) and row-oriented (row format). [ 1 ] [ 2 ] The choice of data orientation is a trade-off and an architectural decision in databases , query engines, and numerical simulations. [ 1 ]
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]
In analogy with relational databases, a column family is as a "table", each key-value pair being a "row". Each column is a tuple consisting of a column name, a value, and a timestamp. In a relational database table, this data would be grouped together within a table with other non-related data. Two types of column families exist:
A column may contain text values, numbers, or even pointers to files in the operating system. [2] Columns typically contain simple types, though some relational database systems allow columns to contain more complex data types, such as whole documents, images, or even video clips. [3] [better source needed] A column can also be called an attribute.
NumPy (pronounced / ˈ n ʌ m p aɪ / NUM-py) is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays. [3]
"Data frames," as implemented in R, Python's Pandas package, and Julia's DataFrames.jl package, are interfaces to access SoA like AoS. The Julia package StructArrays.jl allows for accessing SoA as AoS to combine the performance of SoA with the intuitiveness of AoS. Code generators for the C language, including Datadraw and the X Macro technique.