Data cleaning python

Use methods such as mode, median, mean, and cluster analysis to effectively clean the Bank of Portugal telemarketing data (http://archive.ics.uci.edu/ml/datasets/Bank+Marketing#).

Data field description:

(1) Bank customer information:

  1. age: age (number)
  2. job: job type. admin, blue-collar, entrepreneur, housemaid, 'management', retired, 'self-employed', Services ('services'), students ('student'), technicians ('technician'), unemployed ('unemployed'), unknown ('unknown')
  3. marital: Marital status, divorced ('divorced'), married ('married'), single ('single'), unknown ('unknown'). Note: Divorce also includes widowhood
  4. education: Education status: Basic 4 years ('basic.4y'), Basic 6 years ('basic.6y'), Basic nine years ('basic.9y'), high school &

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Origin blog.csdn.net/m0_72935705/article/details/135013576