_property _DataFrame.loc

通过标签或布尔数组访问一行和一列。

Allow Inputs

  • 单个标签，例如：“5”或“a”，“5”被解释为索引的标签
  • 标签列表或数组，例如：[‘a’, ‘b’, ‘c’]
  • 带有标签的切片对象，例如：’a’: ‘f’
  • 与被切片的轴长度相同的布尔数组，例如：[True, False, True]
  • 一个可对齐的布尔Series
  • 一个可调用函数，带有一个参数并返回用于索引的有效输出

    Example

    ```python import pandas as pd

df = pd.DataFrame({‘site’:[‘google’, ‘baidu’, ‘wiki’], ‘age’:[18, 39, 22], ‘price’: [1.0, 2.0, 3.0], ‘color’: [‘red’, ‘black’, None]},index=[‘first’,’second’,’third’])

df.loc[‘first’]

site google age 18 price 1 color red Name: first, dtype: object

  1. <a name="U7UX2"></a>
  2. # Example
  3. ```python
  4. import pandas as pd
  6. df = pd.DataFrame({'site':['google', 'baidu', 'wiki'],
  7.                     'age':[18, 39, 22],
  8.                     'price': [1.0, 2.0, 3.0],
  9.                     'color': ['red', 'black', None]},index=['first','second','third'])
  10. df.loc[['first', 'second']]
  11. -----------------------------------------------------------
  12.         site    age    price    color
  13. first    google    18    1.0        red
  14. second    baidu    39    2.0        black

Example

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

Example

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

Example

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

Example

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

Example

  1. import pandas as pd
  3. df = pd.DataFrame({"site":["google", "baidu", "wiki"],
  4.                     "age":[18, 39, 22],
  5.                     "price": [1.0, 2.0, 3.0],
  6.                     "color": ["red", "black", None]},index=["first","second","third"])
  8. df.loc[(df["age"] >= 18) & (df["age"] <= 25)]
  9. ----------------------------------------------------------
  10.         site    age    price    color
  11. first    google    18    1.0        red
  12. third    wiki    22    3.0        None

Example

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

Example

对每一行应用函数，返回符合条件的行。

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

Example

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

Example

  1. import pandas as pd
  3. df = pd.DataFrame({'site':['google', 'baidu', 'wiki'],
  4.                     'age':[18, 39, 22],
  5.                     'price': [1.0, 2.0, 3.0],
  6.                     'color': ['red', 'black', None]},index=['first','second','third'])
  7. df.loc['first'] = 10
  8. df
  9. --------------------------------------------------------
  10.         site    age    price    color
  11. first    10        10    10.0    10
  12. second    baidu    39    2.0        black
  13. third    wiki    22    3.0        None

Example

  1. import pandas as pd
  3. df = pd.DataFrame({'site':['google', 'baidu', 'wiki'],
  4.                     'age':[18, 39, 22],
  5.                     'price': [1.0, 2.0, 3.0],
  6.                     'color': ['red', 'black', None]},index=['first','second','third'])
  7. df.loc[:, 'age'] = 30
  8. df
  9. ---------------------------------------------------
  10.         site    age    price    color
  11. first    google    30    1.0        red
  12. second    baidu    30    2.0        black
  13. third    wiki    30    3.0        None

Example

  1. import pandas as pd
  3. df = pd.DataFrame({'site':['google', 'baidu', 'wiki'],
  4.                     'age':[18, 39, 22],
  5.                     'price': [1.0, 2.0, 3.0],
  6.                     'color': ['red', 'black', None]},index=['first','second','third'])
  7. df.loc[df['age'] > 18] = 0
  8. df
  9. -----------------------------------------------------------
  10.         site    age    price    color
  11. first    google    18    1.0        red
  12. second    0        0    0.0        0
  13. third    0        0    0.0        0

Example

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