_property _DataFrame.iloc

纯粹基于整数位置的索引，用于按位置选择。

Allow Inputs

• 一个整数，例如：5
• 整数列表或数组，例如：[4, 3, 0]
• 带有整数的切片对象，例如：1:7
• 一个布尔数组
• 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]})

df.iloc[0]

site google age 18 price 1 color red Name: 0, dtype: object

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# 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]})
df.iloc[[0, 1]]
-----------------------------------------
    site    age    price    color
0    google    18    1.0        red
1    baidu    39    2.0        black

Example

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]})
df.iloc[:3]
-----------------------------------------------------
    site    age    price    color
0    google    18    1.0        red
1    baidu    39    2.0        black
2    wiki    22    3.0        None

Example

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]})
df.iloc[[True, False, True]]
-------------------------------------------
    site    age    price    color
0    google    18    1.0        red
2    wiki    22    3.0        None

Example

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]})
df.iloc[lambda x: x.index % 2 == 0]
-----------------------------------------------------
    site    age    price    color
0    google    18    1.0        red
2    wiki    22    3.0        None

Example

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]})
df.iloc[0, 1]
---------------------------------------------------------
18

Example

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]})
df.iloc[[0, 2], [1, 3]]
-------------------------------------------------------------
    age    color
0    18    red
2    22    None

Example

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]})
df.iloc[1:3, 0:3]
-----------------------------------------------------------
    site    age    price
1    baidu    39    2.0
2    wiki    22    3.0

Example

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]})
df.iloc[:, [True, False, True, False]]
---------------------------------------------------------
    site    price
0    google    1.0
1    baidu    2.0
2    wiki    3.0

Example

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]})
df.iloc[:, lambda df: [0, 2]]
------------------------------------------------------------
    site    price
0    google    1.0
1    baidu    2.0
2    wiki    3.0