如何从熊猫数据框中选择行？

原文:https://www.geesforgeks.org/如何从熊猫数据框中选择行/

pandas.DataFrame.loc是根据提供的条件从熊猫数据框中选择行的函数。在本文中，让我们学习根据一些条件从熊猫数据框中选择行。

语法:df.loc[df[' cname ']' condition ']

参数: df: 代表数据框 cname: 代表列名 条件:代表必须选择行的条件

例 1:

# Importing pandas as pd
from pandas import DataFrame

# Creating a data frame
cart = {'Product': ['Mobile', 'AC', 'Laptop', 'TV', 'Football'],
        'Type': ['Electronic', 'HomeAppliances', 'Electronic', 
                 'HomeAppliances', 'Sports'],
        'Price': [10000, 35000, 50000, 30000, 799]
       }

df = DataFrame(cart, columns = ['Product', 'Type', 'Price'])

# Print original data frame
print("Original data frame:\n")
print(df)

# Selecting the product of Electronic Type
select_prod = df.loc[df['Type'] == 'Electronic']

print("\n")

# Print selected rows based on the condition
print("Selecting rows:\n")
print (select_prod)

产量:T2T4例 2:

# Importing pandas as pd
from pandas import DataFrame

# Creating a data frame
cart = {'Product': ['Mobile', 'AC', 'Laptop', 'TV', 'Football'],
        'Type': ['Electronic', 'HomeAppliances', 'Electronic',
                 'HomeAppliances', 'Sports'],
        'Price': [10000, 35000, 50000, 30000, 799]
       }

df = DataFrame(cart, columns = ['Product', 'Type', 'Price'])

# Print original data frame
print("Original data frame:\n")
print(df)

# Selecting the product of HomeAppliances Type
select_prod = df.loc[df['Type'] == 'HomeAppliances']

print("\n")

# Print selected rows based on the condition
print("Selecting rows:\n")
print (select_prod)

输出: 例 3:

# Importing pandas as pd
from pandas import DataFrame

# Creating a data frame
cart = {'Product': ['Mobile', 'AC', 'Laptop', 'TV', 'Football'],
        'Type': ['Electronic', 'HomeAppliances', 'Electronic',
                 'HomeAppliances', 'Sports'],
        'Price': [10000, 35000, 50000, 30000, 799]
       }

df = DataFrame(cart, columns = ['Product', 'Type', 'Price'])

# Print original data frame
print("Original data frame:\n")
print(df)

# Selecting the product of Price greater 
# than or equal to 25000
select_prod = df.loc[df['Price'] >= 25000]

print("\n")

# Print selected rows based on the condition
print("Selecting rows:\n")
print (select_prod)

输出: 例 4:

# Importing pandas as pd
from pandas import DataFrame

# Creating a data frame
cart = {'Product': ['Mobile', 'AC', 'Laptop', 'TV', 'Football'],
        'Type': ['Electronic', 'HomeAppliances', 'Electronic',
                 'HomeAppliances', 'Sports'],
        'Price': [10000, 35000, 30000, 30000, 799]
       }

df = DataFrame(cart, columns = ['Product', 'Type', 'Price'])

# Print original data frame
print("Original data frame:\n")
print(df)

# Selecting the product of Price not 
# equal to 30000
select_prod = df.loc[df['Price'] != 30000]

print("\n")

# Print selected rows based on the condition
print("Selecting rows:\n")
print (select_prod)

输出:

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