在 Pandas 数据框中选择具有最大值和最小值的行

让我们看看如何借助不同的示例在 Pandas 数据框中选择具有最大值和最小值的行。

考虑这个数据集。

# importing pandas and numpy
import pandas as pd
import numpy as np
  
# data of 2018 drivers world championship
dict1 ={'Driver':['Hamilton', 'Vettel', 'Raikkonen',
                  'Verstappen', 'Bottas', 'Ricciardo',
                  'Hulkenberg', 'Perez', 'Magnussen', 
                  'Sainz', 'Alonso', 'Ocon', 'Leclerc',
                  'Grosjean', 'Gasly', 'Vandoorne',
                  'Ericsson', 'Stroll', 'Hartley', 'Sirotkin'],
                    
        'Points':[408, 320, 251, 249, 247, 170, 69, 62, 56,
                   53, 50, 49, 39, 37, 29, 12, 9, 6, 4, 1],
                     
        'Age':[33, 31, 39, 21, 29, 29, 31, 28, 26, 24, 37,
                      22, 21, 32, 22, 26, 28, 20, 29, 23]}
                        
# creating dataframe using DataFrame constructor
df = pd.DataFrame(dict1)
print(df.head(10))

输出：

在 Dataframe 上使用 max –

代码 #1：在 Driver、Points、Age 列上显示最大值。

# importing pandas and numpy
import pandas as pd
import numpy as np
  
# data of 2018 drivers world championship
dict1 ={'Driver':['Hamilton', 'Vettel', 'Raikkonen',
                  'Verstappen', 'Bottas', 'Ricciardo',
                  'Hulkenberg', 'Perez', 'Magnussen', 
                  'Sainz', 'Alonso', 'Ocon', 'Leclerc',
                  'Grosjean', 'Gasly', 'Vandoorne',
                  'Ericsson', 'Stroll', 'Hartley', 'Sirotkin'],
                    
        'Points':[408, 320, 251, 249, 247, 170, 69, 62, 56,
                   53, 50, 49, 39, 37, 29, 12, 9, 6, 4, 1],
                     
        'Age':[33, 31, 39, 21, 29, 29, 31, 28, 26, 24, 37,
                      22, 21, 32, 22, 26, 28, 20, 29, 23]}
                        
# creating dataframe using DataFrame constructor
df = pd.DataFrame(dict1)
  
# the result shows max on
# Driver, Points, Age columns.
print(df.max())

输出：
代码 #2：谁得分最高

# importing pandas and numpy
import pandas as pd
import numpy as np
  
# data of 2018 drivers world championship
dict1 ={'Driver':['Hamilton', 'Vettel', 'Raikkonen',
                  'Verstappen', 'Bottas', 'Ricciardo',
                  'Hulkenberg', 'Perez', 'Magnussen', 
                  'Sainz', 'Alonso', 'Ocon', 'Leclerc',
                  'Grosjean', 'Gasly', 'Vandoorne',
                  'Ericsson', 'Stroll', 'Hartley', 'Sirotkin'],
                    
        'Points':[408, 320, 251, 249, 247, 170, 69, 62, 56,
                   53, 50, 49, 39, 37, 29, 12, 9, 6, 4, 1],
                     
        'Age':[33, 31, 39, 21, 29, 29, 31, 28, 26, 24, 37,
                      22, 21, 32, 22, 26, 28, 20, 29, 23]}
                        
# creating dataframe using DataFrame constructor
df = pd.DataFrame(dict1)
  
# Who scored more points ?
print(df[df.Points == df.Points.max()])

输出：

代码#3：最大年龄是多少

# importing pandas and numpy
import pandas as pd
import numpy as np
  
# data of 2018 drivers world championship
dict1 ={'Driver':['Hamilton', 'Vettel', 'Raikkonen',
                  'Verstappen', 'Bottas', 'Ricciardo',
                  'Hulkenberg', 'Perez', 'Magnussen', 
                  'Sainz', 'Alonso', 'Ocon', 'Leclerc',
                  'Grosjean', 'Gasly', 'Vandoorne',
                  'Ericsson', 'Stroll', 'Hartley', 'Sirotkin'],
                    
        'Points':[408, 320, 251, 249, 247, 170, 69, 62, 56,
                   53, 50, 49, 39, 37, 29, 12, 9, 6, 4, 1],
                     
        'Age':[33, 31, 39, 21, 29, 29, 31, 28, 26, 24, 37,
                      22, 21, 32, 22, 26, 28, 20, 29, 23]}
                        
# creating dataframe using DataFrame constructor
df = pd.DataFrame(dict1)
  
# what is the maximum age ?
print(df.Age.max())

输出：

代码#4：数据框中哪一行的年龄最大|谁是最年长的司机？

# importing pandas and numpy
import pandas as pd
import numpy as np
  
# data of 2018 drivers world championship
dict1 ={'Driver':['Hamilton', 'Vettel', 'Raikkonen',
                  'Verstappen', 'Bottas', 'Ricciardo',
                  'Hulkenberg', 'Perez', 'Magnussen', 
                  'Sainz', 'Alonso', 'Ocon', 'Leclerc',
                  'Grosjean', 'Gasly', 'Vandoorne',
                  'Ericsson', 'Stroll', 'Hartley', 'Sirotkin'],
                    
        'Points':[408, 320, 251, 249, 247, 170, 69, 62, 56,
                   53, 50, 49, 39, 37, 29, 12, 9, 6, 4, 1],
                     
        'Age':[33, 31, 39, 21, 29, 29, 31, 28, 26, 24, 37,
                      22, 21, 32, 22, 26, 28, 20, 29, 23]}
                        
# creating dataframe using DataFrame constructor
df = pd.DataFrame(dict1)
  
# Which row has maximum age |
# who is the oldest driver ?
print(df[df.Age == df.Age.max()])

输出：

在 Dataframe 上使用 min –

代码 #1：在 Driver、Points、Age 列上显示 min。

# importing pandas and numpy
import pandas as pd
import numpy as np
  
# data of 2018 drivers world championship
dict1 ={'Driver':['Hamilton', 'Vettel', 'Raikkonen',
                  'Verstappen', 'Bottas', 'Ricciardo',
                  'Hulkenberg', 'Perez', 'Magnussen', 
                  'Sainz', 'Alonso', 'Ocon', 'Leclerc',
                  'Grosjean', 'Gasly', 'Vandoorne',
                  'Ericsson', 'Stroll', 'Hartley', 'Sirotkin'],
                    
        'Points':[408, 320, 251, 249, 247, 170, 69, 62, 56,
                   53, 50, 49, 39, 37, 29, 12, 9, 6, 4, 1],
                     
        'Age':[33, 31, 39, 21, 29, 29, 31, 28, 26, 24, 37,
                      22, 21, 32, 22, 26, 28, 20, 29, 23]}
                        
# creating dataframe using DataFrame constructor
df = pd.DataFrame(dict1)
  
# the result shows min on 
# Driver, Points, Age columns.
print(df.min())

输出：

代码 #2：谁得分少

# importing pandas and numpy
import pandas as pd
import numpy as np
  
# data of 2018 drivers world championship
dict1 ={'Driver':['Hamilton', 'Vettel', 'Raikkonen',
                  'Verstappen', 'Bottas', 'Ricciardo',
                  'Hulkenberg', 'Perez', 'Magnussen', 
                  'Sainz', 'Alonso', 'Ocon', 'Leclerc',
                  'Grosjean', 'Gasly', 'Vandoorne',
                  'Ericsson', 'Stroll', 'Hartley', 'Sirotkin'],
                    
        'Points':[408, 320, 251, 249, 247, 170, 69, 62, 56,
                   53, 50, 49, 39, 37, 29, 12, 9, 6, 4, 1],
                     
        'Age':[33, 31, 39, 21, 29, 29, 31, 28, 26, 24, 37,
                      22, 21, 32, 22, 26, 28, 20, 29, 23]}
                        
# creating dataframe using DataFrame constructor
df = pd.DataFrame(dict1)
  
# Who scored less points ?
print(df[df.Points == df.Points.min()])

输出：
代码#3：数据框中哪一行的年龄最小 |谁是最年轻的司机

# importing pandas and numpy
import pandas as pd
import numpy as np
  
# data of 2018 drivers world championship
dict1 ={'Driver':['Hamilton', 'Vettel', 'Raikkonen',
                  'Verstappen', 'Bottas', 'Ricciardo',
                  'Hulkenberg', 'Perez', 'Magnussen', 
                  'Sainz', 'Alonso', 'Ocon', 'Leclerc',
                  'Grosjean', 'Gasly', 'Vandoorne',
                  'Ericsson', 'Stroll', 'Hartley', 'Sirotkin'],
                    
        'Points':[408, 320, 251, 249, 247, 170, 69, 62, 56,
                   53, 50, 49, 39, 37, 29, 12, 9, 6, 4, 1],
                     
        'Age':[33, 31, 39, 21, 29, 29, 31, 28, 26, 24, 37,
                      22, 21, 32, 22, 26, 28, 20, 29, 23]}
                        
# creating dataframe using DataFrame constructor
df = pd.DataFrame(dict1)
  
# Which row has maximum age | 
# who is the youngest driver ?
print(df[df.Age == df.Age.min()])

输出：