在Python Pandas中获取列的数据类型

让我们看看如何在pandas数据框架中获得列的数据类型。首先，让我们创建一个pandas数据框架。

示例:

# 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:

方法1：使用Dataframe.dtypes 属性。

该属性返回一个带有每列数据类型的系列。

语法： DataFrame.dtypes

参数：无。

返回：每一列的dtype。

示例1：获取数据框架所有列的数据类型。

# 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:

数据框架的数据类型

示例2：获取数据框架中单列的数据类型。

#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:

单一列的数据类型

方法2：使用Dataframe.info()方法。

该方法用于获得数据框架的简明摘要，如。

• 栏目名称
• 列的数据类型
• 数据框架中的行数
• 每一列中的非空条目
• 它还会打印列数、名称和数据类型。

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

返回：无，并打印出一个DataFrame的摘要。

示例：获取数据框架所有列的数据类型。

# 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:

数据框架的摘要，包括数据类型