Wes McKinney

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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.[1][2] He was the CEO and founder of technology startup Datapad. He was a software engineer at Two Sigma Investments. He founded Ursa Labs,[3] which, in 2021, became part of Voltron Data.[4] In 2022, it was announced that Voltron Data had raised $110 million.[5]

Early life and education[edit]

McKinney graduated from MIT with a B.S. in Mathematics in 2007.[1] In 2010, he began a Ph.D program in Statistics at Duke University, but went on leave in 2011.[6]

Career[edit]

From 2007 to 2010, McKinney researched global macro and credit trading strategies at AQR Capital Management. During his time at AQR Capital, he learned Python and started building what would become pandas.[1] McKinney made the pandas project public in 2009.[6]

McKinney left AQR in 2010 to start a PhD in Statistics at Duke University. He went on leave from Duke in the summer of 2011 to devote more time to developing Pandas,[6] culminating in the writing of Python for Data Analysis in 2012.

In 2012, he co-founded Lambda Foundry Inc.[7]

McKinney co-founded Datapad with Cheng She in January 2013, with McKinney as CEO. Datapad developed a data visualization product also on the Python stack targeting enterprise customers. Datapad was acquired by Cloudera in September 2014.[8][9] McKinney joined the engineering team at Cloudera following the acquisition. He worked on an open-source project called Ibis, incubated within Cloudera Labs, aiming at using Python for big data problems.[10] In 2016, McKinney joined the investment fund Two Sigma Investments to work on Apache Arrow. In 2018, he launched Ursa Labs.[3] In 2023, he joined Posit (formerly RStudio) as a Principal Architect.[11]

Media coverage[edit]

McKinney has been interviewed by VentureBeat and others.[12][13][14] He frequently gives talks to the Python community.[15][16]

References[edit]

  1. ^ a b c McKinney, Wes (2013). Python for Data Analysis (1st ed.). Sebastopol, Calif.: O'Reilly. ISBN 978-1449319793.
  2. ^ McKinney, Wes (2017). Python for Data Analysis (2nd ed.). Sebastopol, Calif.: O'Reilly. ISBN 978-1491957660.
  3. ^ a b "Announcing Ursa Labs: An innovation lab for open source data science". 19 April 2018.
  4. ^ McKinney, Wes (2021-08-05). "Wes McKinney - Joining Forces for an Arrow-Native Future". wesmckinney.com. Retrieved 2024-02-28.
  5. ^ Miller, Ron (2022-02-17). "Voltron Data grabs $110M to build startup based on Apache Arrow project". TechCrunch. Retrieved 2024-02-28.
  6. ^ a b c Kopf, Dan. "Meet the man behind the most important tool in data science", Quartz, 8 December 2017. Retrieved on 24 October 2019.
  7. ^ "wesmckinney.com". Retrieved 26 July 2023.
  8. ^ "Data startup DataPad gets acquired, says it will shut down on Friday". VentureBeat. 29 September 2014. Retrieved 2016-01-10.
  9. ^ "Cloudera Bought Datapad". GigaOm. 30 September 2014. Retrieved 10 January 2016.
  10. ^ "Ibis on Impala: Python at Scale for Data Science - Cloudera Engineering Blog". Cloudera Engineering Blog. Retrieved 2016-01-10. [W]e are excited to announce a new open source project, called Ibis, that will deliver the great Python experience and ecosystem, only at any data and node scale.
  11. ^ "Welcome, Wes!". Posit. 2023-11-06. Retrieved 2024-01-26.
  12. ^ "DataPad emerges to let everyone at your company create and play with charts". VentureBeat. 20 May 2014. Retrieved 2016-01-10.
  13. ^ "Meet Quantopian's Newest Advisor: Wes McKinney". Quantopian Blog. Retrieved 2016-01-10.
  14. ^ "Big data's 4 big Vs: It's our Data Summit highlights - Web Summit Blog". Web Summit Blog. Retrieved 2016-01-10.
  15. ^ "LFPUG: Python in the enterprise + Pandas | Enthought Blog". blog.enthought.com. Retrieved 2016-01-10.
  16. ^ "Big Data Conference - Wes McKinney". O'Reilly Media. Retrieved 10 January 2016.

External links[edit]

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