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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.
It centers on the entity-oriented integration of statistical observations from a variety of public datasets. Although it supports a subset of the W3C SPARQL query language, [15] its APIs [16] also include tools — such as a Pandas dataframe interface — oriented towards data science, statistics and data visualization.
Views also function as relational tables, but their data are calculated at query time. External tables (in Informix [3] or Oracle, [4] [5] for example) can also be thought of as views. In many systems for computational statistics, such as R and Python's pandas, a data frame or data table is a data type supporting the table
Wes McKinney is an American software developer and businessman. He is the creator and "Benevolent Dictator for Life" (BDFL) of the open-source pandas package for data analysis in the Python programming language, and has also authored three versions of the reference book Python for Data Analysis.
Comma-separated values (CSV) is a text file format that uses commas to separate values, and newlines to separate records. A CSV file stores tabular data (numbers and text) in plain text, where each line of the file typically represents one data record.
Star schema used by example query. Consider a database of sales, perhaps from a store chain, classified by date, store and product. The image of the schema to the right is a star schema version of the sample schema provided in the snowflake schema article.
A query language, also known as data query language or database query language (DQL), is a computer language used to make queries in databases and information systems. In database systems, query languages rely on strict theory to retrieve information. [1] A well known example is the Structured Query Language (SQL).
In SQL, the data manipulation language comprises the SQL-data change statements, [3] which modify stored data but not the schema or database objects. Manipulation of persistent database objects, e.g., tables or stored procedures, via the SQL schema statements, [3] rather than the data stored within them, is considered to be part of a separate data definition language (DDL).