DataFrame.set_index

DataFrame.set_index(keys, drop=True, append=False, inplace=False, verify_integrity=False)
使用现有列设置DataFrame的索引。

Parameters

keys 此参数可以是单个列键、与调用DataFrame长度相同的单个数组或是包含列键和数组任意组合的列表。
drop 删除要用作新索引的列。
append 是否将列附加到现有索引
inplace False：返回一个副本；True：就地执行操作并返回None
verify_integrity 检查新索引是否有重复项

Example

  1. import pandas as pd
  3. df = pd.DataFrame({'site':['google', 'baidu', 'wiki', 'pandas'],
  4.                     'age':[18, 39, 22, 45],
  5.                     'price': [1.0, 2.0, 3.0, 4.0],
  6.                     'color': ['red', 'black', None, 'red']}, index=['first', 'second', 'third', 'forth'])
  7. df.set_index('site')
  8. --------------------------------------------------------------------
  9.         age    price    color
  10. site            
  11. google    18    1.0        red
  12. baidu    39    2.0        black
  13. wiki    22    3.0        None
  14. pandas    45    4.0        red

Example

  1. import pandas as pd
  3. df = pd.DataFrame({'site':['google', 'baidu', 'wiki', 'pandas'],
  4.                     'age':[18, 39, 22, 45],
  5.                     'price': [1.0, 2.0, 3.0, 4.0],
  6.                     'color': ['red', 'black', None, 'red']}, index=['first', 'second', 'third', 'forth'])
  7. df.set_index(['site', 'age'])
  8. --------------------------------------------------------------------
  9.             price    color
  10. site    age        
  11. google    18    1.0        red
  12. baidu    39    2.0        black
  13. wiki    22    3.0        None
  14. pandas    45    4.0        red

Example

  1. import pandas as pd
  3. df = pd.DataFrame({'site':['google', 'baidu', 'wiki', 'pandas'],
  4.                     'age':[18, 39, 22, 45],
  5.                     'price': [1.0, 2.0, 3.0, 4.0],
  6.                     'color': ['red', 'black', None, 'red']}, index=['first', 'second', 'third', 'forth'])
  7. df.set_index([pd.Index(['a', 'b', 'c', 'd'])])
  8. ------------------------------------------------------------
  9.     site    age    price    color
  10. a    google    18    1.0        red
  11. b    baidu    39    2.0        black
  12. c    wiki    22    3.0        None
  13. d    pandas    45    4.0        red