Data Sets
In Data Science, a data set is a collection of data that is organized in a specific way. It can be a structured or unstructured collection of data that is used for analysis, modeling, and machine learning. A data set can be a table, a spreadsheet, a database, or any other format that can be used to store and organize data. Data sets can be used to train machine learning models, to test hypotheses, to validate algorithms, and to make predictions. They can be collected from various sources such as surveys, experiments, sensors, social media, and web scraping. Data sets can be preprocessed, cleaned, and transformed to make them suitable for analysis. They can also be combined with other data sets to create more complex and comprehensive data sets.
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- Aggregating: Aggregating refers to the process of combining multiple data points into a single summary statistic or visualization. This is often done to simplify the analysis of large datasets or to provide a high-level overview of the data. Aggregating ... Read More >>
- Outer Joins: In data science, outer join is a type of join operation that combines data from two or more tables based on a common attribute and includes all the rows from one or both tables, even if there is no match in the other table. Outer joins are ... Read More >>
- Visualization Techniques: Visualization techniques refer to the methods and tools used to represent data in a visual format, such as charts, graphs, and maps. These techniques are used to help people understand complex data sets by presenting them in a way that is e ... Read More >>
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