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A DataReader parses a Tabular Data Stream from Microsoft SQL Server, and other methods of retrieving data from other sources. A DataReader is usually accompanied by a Command object that contains the query, optionally any parameters, and the connection object to run the query on.
However, if data is a DataFrame, then data['a'] returns all values in the column(s) named a. To avoid this ambiguity, Pandas supports the syntax data.loc['a'] as an alternative way to filter using the index. Pandas also supports the syntax data.iloc[n], which always takes an integer n and returns the nth value, counting from 0. This allows a ...
The import and export of data is the automated or semi-automated input and output of data sets between different software applications.It involves "translating" from the format used in one application into that used by another, where such translation is accomplished automatically via machine processes, such as transcoding, data transformation, and others.
Tabular Data Stream (TDS) is an application layer protocol used to transfer data between a database server and a client. It was initially designed and developed by Sybase Inc. for their Sybase SQL Server relational database engine in 1984, and later by Microsoft in Microsoft SQL Server .
Attributes – each attribute [3] of the data stream represents a certain type of data, e.g. segment / data point ID, timestamp, geodata. Timestamp attribute helps to identify when an event occurred. Subject ID is an encoded-by-algorithm ID, that has been extracted out of a cookie .
Data loading, or simply loading, is a part of data processing where data is moved between two systems so that it ends up in a staging area on the target system. With the traditional extract, transform and load (ETL) method, the load job is the last step, and the data that is loaded has already been transformed.
The data segment is read/write, since the values of variables can be altered at run time. This is in contrast to the read-only data segment ( rodata segment or .rodata ), which contains static constants rather than variables; it also contrasts to the code segment , also known as the text segment, which is read-only on many architectures.
Semantic data mining is a subset of data mining that specifically seeks to incorporate domain knowledge, such as formal semantics, into the data mining process.Domain knowledge is the knowledge of the environment the data was processed in. Domain knowledge can have a positive influence on many aspects of data mining, such as filtering out redundant or inconsistent data during the preprocessing ...