在Pandas中使用iloc[]和iat[]从数据框架中选择任何行

在Pandas中使用iloc[]和iat[]从数据框架中选择任何行

在这篇文章中,我们将学习如何使用函数ilic[]和iat[]从数据框架中获取列表形式的行。有多种方法可以从给定的数据框架中以列表的形式获取行。让我们在例子的帮助下看看这些方法。

import pandas as pd
   
# Create the dataframe
df = pd.DataFrame({'Date':['10/2/2011', '11/2/2011', '12/2/2011', '13/2/11'],
                    'Event':['Music', 'Poetry', 'Theatre', 'Comedy'],
                    'Cost':[10000, 5000, 15000, 2000]})
 
# Create an empty list
Row_list =[]
   
# Iterate over each row
for i in range((df.shape[0])):
   
    # Using iloc to access the values of 
    # the current row denoted by "i"
    Row_list.append(list(df.iloc[i, :]))
   
# Print the first 3 elements
print(Row_list[:3])
Python

输出:

[[10000, '10/2/2011', 'Music'], [5000, '11/2/2011', 'Poetry'],
      [15000, '12/2/2011', 'Theatre']
Python

使用iat[]方法 –

# importing pandas as pd
import pandas as pd
   
# Create the dataframe
df = pd.DataFrame({'Date':['10/2/2011', '11/2/2011', '12/2/2011', '13/2/11'],
                    'Event':['Music', 'Poetry', 'Theatre', 'Comedy'],
                    'Cost':[10000, 5000, 15000, 2000]})
   
# Create an empty list
Row_list =[]
   
# Iterate over each row
for i in range((df.shape[0])):
    # Create a list to store the data
    # of the current row
    cur_row =[]
       
    # iterate over all the columns
    for j in range(df.shape[1]):
           
        # append the data of each
        # column to the list
        cur_row.append(df.iat[i, j])
           
    # append the current row to the list
    Row_list.append(cur_row)
 
# Print the first 3 elements
print(Row_list[:3])
Python

输出:

[[10000, '10/2/2011', 'Music'], [5000, '11/2/2011', 'Poetry'], 
      [15000, '12/2/2011', 'Theatre']]
Python

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