Glossary

Anaconda

What is Anaconda?

Anaconda is a widely used distribution of the Python and R programming languages for data analysis and machine learning, published by Anaconda Inc. It bundles the conda package manager with pre-installed libraries such as NumPy, pandas and Jupyter and makes it easy to keep separate environments per project. Organisations with more than 200 staff need a paid licence for the Anaconda Distribution and its default package channel; conda itself and the community channel conda-forge remain free to use (as of October 2026).

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Python
Data science
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Related terms

NumPy

NumPy is the fundamental open-source Python library for numerical computing. It provides multidimensional arrays and fast functions for linear algebra, statistics and random numbers, with its core running in compiled code. Many data analysis and machine learning tools, such as pandas, scikit-learn and numerous visualisation libraries, are built on NumPy. Anyone working with data in Python therefore almost always uses it, directly or indirectly.

Python
data analysis
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pandas

pandas is an open-source Python library for analysing and manipulating tabular data, developed from 2008 onwards by Wes McKinney. Its central object, the DataFrame, resembles a table with named columns. It can be used to load data from CSV files, Excel or databases and to clean, filter, group and merge it. pandas is built on NumPy and is a standard tool in data analysis, reporting and training data preparation.

Python
data analysis
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Jupyter Notebook

Jupyter Notebook is an open-source, browser-based application from Project Jupyter that combines executable code, results, charts and explanatory text in a single document. Notebooks are widely used in data analysis, machine learning, research and teaching because each step can be documented and shared in a traceable way. Python is the most common language. Example: an analyst loads sales data, cleans it and shows the results as a chart directly below.

Data analysis
Python
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Scikit-learn

Scikit-learn is an open-source Python library for classical machine learning. It provides consistent tools for classification, regression, clustering, dimensionality reduction, data preprocessing and model evaluation, such as cross-validation. Built on NumPy and SciPy, it is widely used in education, research and practice thanks to its simple, uniform interface. For deep neural networks, frameworks such as PyTorch or TensorFlow are usually chosen instead.

Python
library
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