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Table Of Contents

  • What’s New
  • Installation
  • Frequently Asked Questions (FAQ)
  • Package overview
  • 10 Minutes to Pandas
  • Cookbook
  • Intro to Data Structures
  • Essential Basic Functionality
  • Indexing and Selecting Data
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  • Group By: split-apply-combine
  • Merge, join, and concatenate
  • Reshaping and Pivot Tables
  • Time Series / Date functionality
  • Plotting with matplotlib
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  • IO Tools (Text, CSV, HDF5, ...)
  • Enhancing Performance
  • Sparse data structures
  • Caveats and Gotchas
  • rpy2 / R interface
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  • Comparison with R / R libraries
  • API Reference
    • Input/Output
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    • Series
      • Attributes and underlying data
      • Conversion / Constructors
      • Indexing, iteration
      • Binary operator functions
      • Function application, GroupBy
      • Computations / Descriptive Stats
      • Reindexing / Selection / Label manipulation
      • Missing data handling
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      • Time series-related
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pandas.Series.map¶

Series.map(arg, na_action=None)¶

Map values of Series using input correspondence (which can be a dict, Series, or function)

Parameters :

arg : function, dict, or Series

na_action : {None, ‘ignore’}

If ‘ignore’, propagate NA values

Returns :

y : Series

same index as caller

Examples

>>> x
one   1
two   2
three 3
>>> y
1  foo
2  bar
3  baz
>>> x.map(y)
one   foo
two   bar
three baz

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