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在熊猫数据框的特定位置插入给定的列

原文:https://www.geeksforgeeks.org/insert-a-给定栏-特定位置-熊猫-dataframe/

在本文中,我们将使用 Pandas 的data frame.insert()方法在数据帧的特定列索引处插入一个新列。

语法:数据框。插入(loc,列,值,allow_duplicates = False)

返回:

代码:让我们创建一个数据帧。

蟒蛇 3

# Importing pandas library
import pandas as pd

# dictionary
values = {'col2': [6, 7, 8, 
                   9, 10],
          'col3': [11, 12, 13,
                   14, 15]}

# Creating dataframe
df = pd.DataFrame(values)

# show the dataframe
df

输出:

Dataframe

示例 1: 在数据框的开头插入列。

蟒蛇 3

# Importing pandas library
import pandas as pd

# dictionary
values = {'col2': [6, 7, 8, 
                   9, 10], 
          'col3': [11, 12, 13,
                   14, 15]}

# Creating dataframe
df = pd.DataFrame(values)

# New column to be added
new_col = [1, 2, 3, 4, 5] 

# Inserting the column at the
# beginning in the DataFrame
df.insert(loc = 0,
          column = 'col1',
          value = new_col)
# show the dataframe
df

输出:

Insert new column at beginning of the dataframe

示例 2: 在数据框的中间插入列

蟒蛇 3

# Importing pandas library
import pandas as pd

# dictionary
values = {'col2': [6, 7, 8, 
                   9, 10], 
          'col3': [11, 12, 13,
                   14, 15]}

# Creating dataframe
df = pd.DataFrame(values)

# New column to be added
new_col = [1, 2, 3, 4, 5] 

# Inserting the column at the
# middle of the DataFrame
df.insert(loc = 1,
          column = 'col1',
          value = new_col)
# show the dataframe
df

输出:

Insert new column at middle of the dataframe

示例 3: 在数据框的末尾插入列

蟒蛇 3

# Importing pandas library
import pandas as pd

# dictionary
values = {'col2': [6, 7, 8, 
                   9, 10], 
          'col3': [11, 12, 13,
                   14, 15]}

# Creating dataframe
df = pd.DataFrame(values)

# New column to be added
new_col = [1, 2, 3, 4, 5] 

# Inserting the column at the
# end of the DataFrame
# df.columns gives index array 
# of column names
df.insert(loc = len(df.columns),
          column = 'col1',
          value = new_col)
# show the dataframe
df

输出:

Insert new column at end of the dataframe



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