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Pandas (software): History & Art

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. It is free software released under the three-clause BSD license. The name is derived from the term "panel data", an…

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Pandas (software) topic overview

The analysis highlights History and Art as prominent areas in the source structure around Pandas (software).

Related topics
54
Source areas
5
Connected nodes
59
Extracted relationships
29
Concept neighborhoods
22
Bridge connections
59

What this topic covers Research coverage

Source areas are shown by the number of related topics found in each part of the analysis. Use smaller areas too: they can reveal specialized angles and content gaps.

Data model · 25 topics
Overview · 14 topics
Functionality · 6 topics
Criticisms · 5 topics
History · 4 topics

Smaller areas are not necessarily less important. They contain fewer connections in this analysis and can be useful for finding specialized angles or coverage gaps.

Key facts & relationships

High-confidence facts extracted from structured source data. Use them as anchors for further research.

Developer
Community
License
New BSD License
Operating system
Cross-platform
Original author
Wes McKinney
Preview release
2.0rc1 / 15 March 2023; 3 years ago (2023-03-15)
Release
11 January 2008; 18 years ago (2008-01-11)[citation needed]

Explore all related topics Closing gaps

Browse the complete topic structure, not only the most central items. Less prominent entities and concepts can reveal missing angles, specialized context and useful research gaps. Each item opens a new analysis centered on that subject.

Overview

History

Data model

Functionality

Criticisms

Advanced semantic analysis

Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.

How Pandas (software) connects Entity context

The extracted context around Pandas (software) shows recurring relationship patterns in the source. For example, Pandas (software) → Community Another extracted example is Pandas (software) → New BSD License. Use these groups to spot repeated connection types before inspecting the individual relationships.

Pandas (software)

Top relations

Developer · 1
Pandas (software) → Community
License · 1
Pandas (software) → New BSD License
Operating system · 1
Pandas (software) → Cross-platform
Original author · 1
Pandas (software) → Wes McKinney
Preview release · 1
Pandas (software) → 2.0rc1 / 15 March 2023; 3 years ago (2023-03-15)
Release · 1
Pandas (software) → 11 January 2008; 18 years ago (2008-01-11)[citation needed]
Repository · 1
Pandas (software) → github.com/pandas-dev/pandas
Stable release · 1
Pandas (software) → 3.0.5 / 22 July 2026; 33 days ago (22 July 2026)
Type · 1
Pandas (software) → Technical computing
Website · 1
Pandas (software) → pandas.pydata.org

Important terminology

Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.

Important terminology

data pandas index values series python library also column dataframes dataframe numpy analysis value df operations labels indices missing multiple

Pandas (software) relationships Subject–Predicate–Object triples

TTTA extracted 29 structured relationships around Pandas (software). Examples in this analysis include Pandas (software) → Developer → Community and Pandas (software) → License → New BSD License. The table shows each extracted connection, where it came from and its confidence.

SubjectPredicateObjectConfidenceSrc
Pandas (software)DeveloperCommunity1.00infobox
Pandas (software)LicenseNew BSD License1.00infobox
Pandas (software)Operating systemCross-platform1.00infobox
Pandas (software)Original authorWes McKinney1.00infobox
Pandas (software)Preview release2.0rc1 / 15 March 2023; 3 years ago (2023-03-15)1.00infobox
Pandas (software)Release11 January 2008; 18 years ago (2008-01-11)[citation needed]1.00infobox
Pandas (software)Repositorygithub.com/pandas-dev/pandas1.00infobox
Pandas (software)Stable release3.0.5 / 22 July 2026; 33 days ago (22 July 2026)1.00infobox
Pandas (software)TypeTechnical computing1.00infobox
Pandas (software)Websitepandas.pydata.org1.00infobox
Pandas (software)Written inPython, Cython, C1.00infobox
comma-separated valuesinstance ofData for these collections can be imported from various file formats0.80text

Related concept clusters Concept neighborhoods

The concept neighborhoods around Pandas (software) bring nearby vocabulary together. In this analysis, examples include Python, Data and Analysis. Use the clusters to find adjacent concepts and terminology that may deserve separate research.

  • Pandas (software)
    • Python
    • Data
    • Analysis
    • Time
    • Index
    • Dataframes
    • Series
    • Also
    • Mckinney
    • Wes
    • Using
    • Indices
  • pandas (software)
    • Python
    • Data
    • Analysis
    • Time
    • Wes
    • Index
    • Dataframes
    • Series
    • Also
    • Mckinney
    • Using
    • Indices
  • data structures
    • Values
    • Index
    • Series
    • Also
    • Pandas
    • Python
    • Analysis
    • Labels
    • Type
    • Missing
    • Dataframe
    • Example
  • time series
    • Index
    • Example
    • Values
    • Labels
    • Wes
    • Arrays
    • Built
    • 'a'
    • Type
    • Numpy
    • Dataframe
    • Dataframes
  • panel data
    • Values
    • Index
    • Series
    • Also
    • Pandas
    • Python
    • Analysis
    • Labels
    • Type
    • Missing
    • Dataframe
    • Example
  • data sets
    • Values
    • Index
    • Series
    • Also
    • Pandas
    • Python
    • Analysis
    • Labels
    • Type
    • Missing
    • Dataframe
    • Example
  • comma-separated values
    • Index
    • Data
    • Also
    • Labels
    • Series
    • Missing
    • Value
    • Column
    • 'a'
    • Columns
    • Rows
    • Multiple
  • data type
    • Values
    • Rows
    • Index
    • Series
    • Also
    • Pandas
    • Python
    • Analysis
    • Labels
    • Column
    • Type
    • Missing

Connections between topic areas Semantic bridges

For Pandas (software), one of the stronger structural bridges in this analysis connects Pandas (software) with Data model. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.

Min side: 3
Pandas (software) — Data model · splits 34 ⟂ 26
Pandas (software) — Overview · splits 45 ⟂ 15
Pandas (software) — Functionality · splits 53 ⟂ 7
Pandas (software) — Criticisms · splits 54 ⟂ 6
Pandas (software) — History · splits 55 ⟂ 5

Map overview Semantic statistics

Pandas (software)

Nodes60
Edges59
Triples29
Avg. degree1.97
Density0.033333
Components1

Source & methodology

TTTA analyzes the structure around Pandas (software) to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as History & Art, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.

Source: Wikipedia — Pandas (software) · EN edition · Analysis: TopicsToTalkAbout

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