Pandas：如何使用 LocIndexer

使用 Pandas 的 LocIndexer 对象可以方便地进行基于标签的数据选择和操作。LocIndexer 是一个基于标签的选择器，可以通过行标签和列标签来定位和访问数据。它提供了一种简单而直观的方式来处理 Pandas DataFrame 和 Series 对象。

python
import pandas as pd
data = {'Name': ['John', 'Emma', 'Peter', 'Lisa'],
        'Age': [25, 30, 28, 35],
        'Gender': ['Male', 'Female', 'Male', 'Female'],
        'City': ['New York', 'London', 'Paris', 'Tokyo']}
df = pd.DataFrame(data)

python
row = df.loc[1]
print(row)

Name          Emma
Age             30
Gender      Female
City        London
Name: 1, dtype: object

python
rows = df.loc[[0, 2]]
print(rows)

   Name  Age Gender      City
0  John   25   Male  New York
2  Peter   28   Male     Paris

python
rows = df.loc[1:3]
print(rows)

    Name  Age  Gender    City
1   Emma   30  Female  London
2  Peter   28    Male   Paris
3   Lisa   35  Female   Tokyo

python
rows = df.loc[df['Age'] >= 30]
print(rows)

   Name  Age  Gender    City
1  Emma   30  Female  London
3  Lisa   35  Female   Tokyo

python
rows = df.loc[(df['Age'] >= 30) & (df['Gender'] == 'Female')]
print(rows)

   Name  Age  Gender    City
3  Lisa   35  Female   Tokyo

python
column = df.loc[:, 'Age']
print(column)

0    25
1    30
2    28
3    35
Name: Age, dtype: int64

python
columns = df.loc[:, ['Name', 'City']]
print(columns)

   Name      City
0  John  New York
1  Emma    London
2  Peter     Paris
3  Lisa     Tokyo

python
data = df.loc[1, 'Age']
print(data)

30

python
data = df.loc[[0, 2], ['Name', 'City']]
print(data)

   Name      City
0  John  New York
2  Peter     Paris