获取 Pandas 中列的数据类型 - Python

让我们看看如何获取pandas dataframe中列的数据类型。首先，让我们创建一个 pandas 数据框。

例子：

Python3

# importing pandas library
import pandas as pd
  
# List of Tuples
employees = [
            ('Stuti', 28, 'Varanasi', 20000),
            ('Saumya', 32, 'Delhi', 25000),
            ('Aaditya', 25, 'Mumbai', 40000),
            ('Saumya', 32, 'Delhi', 35000),
            ('Saumya', 32, 'Delhi', 30000),
            ('Saumya', 32, 'Mumbai', 20000),
            ('Aaditya', 40, 'Dehradun', 24000),
            ('Seema', 32, 'Delhi', 70000)
            ]
  
   
  
# Create a DataFrame
df = pd.DataFrame(employees,
                  columns = ['Name', 'Age',
                             'City', 'Salary'])
# show the dataframe
df

输出：

数据框

方法一：使用Dataframe.dtypes 属性。

此属性返回具有每列数据类型的 Series。

Syntax: DataFrame.dtypes.

Parameter: None.

Returns: dtype of each column.

示例 1：获取 Dataframe 的所有列的数据类型。

Python3

# importing pandas library
import pandas as pd
  
# List of Tuples
employees = [
            ('Stuti', 28, 'Varanasi', 20000),
            ('Saumya', 32, 'Delhi', 25000),
            ('Aaditya', 25, 'Mumbai', 40000),
            ('Saumya', 32, 'Delhi', 35000),
            ('Saumya', 32, 'Delhi', 30000),
            ('Saumya', 32, 'Mumbai', 20000),
            ('Aaditya', 40, 'Dehradun', 24000),
            ('Seema', 32, 'Delhi', 70000)
            ]
  
   
  
# Create a DataFrame
df = pd.DataFrame(employees,
                  columns = ['Name', 'Age',
                             'City', 'Salary'])
  
   
  
# Use Dataframe.dtypes to
# give the series of 
# data types as result
datatypes = df.dtypes
  
# Print the data types
# of each column
datatypes

输出：

数据框的数据类型

示例 2：获取 Dataframe 中单列的数据类型。

Python3

#importing pandas library
import pandas as pd
  
# List of Tuples
employees = [('Stuti', 28, 'Varanasi', 20000),
            ('Saumya', 32, 'Delhi', 25000),
            ('Aaditya', 25, 'Mumbai', 40000),
            ('Saumya', 32, 'Delhi', 35000),
            ('Saumya', 32, 'Delhi', 30000),
            ('Saumya', 32, 'Mumbai', 20000),
            ('Aaditya', 40, 'Dehradun', 24000),
            ('Seema', 32, 'Delhi', 70000)
            ]
  
# Create a DataFrame
df = pd.DataFrame(employees, 
                  columns = ['Name', 'Age',
                             'City', 'Salary'])
  
# Use Dataframe.dtypes to give 
# data type of 'Salary' as result
datatypes = df.dtypes['Salary']
  
# Print the data types
# of single column
datatypes

输出：

单列的数据类型

方法 2：使用Dataframe.info()方法。

此方法用于获取数据框的简明摘要，例如：

• 列名
• 列的数据类型
• 数据框中的行
• 每列中的非空条目
• 它还将打印列数、名称和数据类型。

Syntax: DataFrame.info(verbose=None, buf=None, max_cols=None, memory_usage=None, null_counts=None)

Return: None and prints a summary of a DataFrame.

示例：获取 Dataframe 的所有列的数据类型。

Python3

# importing pandas library
import pandas as pd
  
 # List of Tuples
employees = [('Stuti', 28, 'Varanasi', 20000),
            ('Saumya', 32, 'Delhi', 25000),
            ('Aaditya', 25, 'Mumbai', 40000),
            ('Saumya', 32, 'Delhi', 35000),
            ('Saumya', 32, 'Delhi', 30000),
            ('Saumya', 32, 'Mumbai', 20000),
            ('Aaditya', 40, 'Dehradun', 24000),
            ('Seema', 32, 'Delhi', 70000)
            ]
  
# Create a DataFrame
df = pd.DataFrame(employees,
                  columns = ['Name', 'Age', 
                             'City', 'Salary'])
  
# Print complete details 
# about the data frame
df.info()

输出：

数据框摘要，包括数据类型