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📜  在 Pandas DataFrame 中将文本列拆分为两列

📅  最后修改于: 2022-05-13 01:55:43.991000             🧑  作者: Mango

在 Pandas DataFrame 中将文本列拆分为两列

让我们看看如何在 Pandas DataFrame 中将文本列拆分为两列。

方法#1:使用Series.str.split()函数。

名称列拆分为两个不同的列。默认情况下,拆分是通过str.split()函数在单个空格的基础上完成的。

# import Pandas as pd
import pandas as pd
   
# create a new data frame
df = pd.DataFrame({'Name': ['John Larter', 'Robert Junior', 'Jonny Depp'],
                   'Age':[32, 34, 36]})
   
print("Given Dataframe is :\n",df)
   
# bydefault splitting is done on the basis of single space.
print("\nSplitting 'Name' column into two different columns :\n",
                                  df.Name.str.split(expand=True))

输出 :
Name列分别拆分为“First”和“Last”列,并将其添加到现有的 Dataframe 中。

# import Pandas as pd
import pandas as pd
   
# create a new data frame
df = pd.DataFrame({'Name': ['John Larter', 'Robert Junior', 'Jonny Depp'],
                    'Age':[32, 34, 36]})
   
print("Given Dataframe is :\n",df)
   
# Adding two new columns to the existing dataframe.
# bydefault splitting is done on the basis of single space.
df[['First','Last']] = df.Name.str.split(expand=True)
   
print("\n After adding two new columns : \n", df)

输出:


使用下划线作为分隔符将列拆分为两列。

# import Pandas as pd
import pandas as pd
   
# create a new data frame
df = pd.DataFrame({'Name': ['John_Larter', 'Robert_Junior', 'Jonny_Depp'],
                    'Age':[32, 34, 36]})
   
print("Given Dataframe is :\n",df)
   
# Adding two new columns to the existing dataframe.
# splitting is done on the basis of underscore.
df[['First','Last']] = df.Name.str.split("_",expand=True)
   
print("\n After adding two new columns : \n",df)

输出 :
一起使用str.split()tolist()函数。

# import Pandas as pd
import pandas as pd
   
# create a new data frame
df = pd.DataFrame({'Name': ['John_Larter', 'Robert_Junior', 'Jonny_Depp'],
                    'Age':[32, 34, 36]})
   
print("Given Dataframe is :\n",df)
  
print("\nSplitting Name column into two different columns :") 
print(pd.DataFrame(df.Name.str.split('_',1).tolist(),
                         columns = ['first','Last']))

输出 :
方法 #2:使用apply()函数。

名称列拆分为两个不同的列。

# import Pandas as pd
import pandas as pd
   
# create a new data frame
df = pd.DataFrame({'Name': ['John_Larter', 'Robert_Junior', 'Jonny_Depp'],
                    'Age':[32, 34, 36]})
   
print("Given Dataframe is :\n",df)
  
print("\nSplitting Name column into two different columns :") 
print(df.Name.apply(lambda x: pd.Series(str(x).split("_"))))

输出 :

Name列拆分为两个不同的列,分别命名为“First”和“Last”,然后将其添加到现有的 Dataframe 中。

# import Pandas as pd
import pandas as pd
   
# create a new data frame
df = pd.DataFrame({'Name': ['John_Larter', 'Robert_Junior', 'Jonny_Depp'],
                    'Age':[32, 34, 36]})
   
print("Given Dataframe is :\n",df)
  
print("\nSplitting Name column into two different columns :") 
  
# splitting 'Name' column into Two columns 
# i.e. 'First' and 'Last'respectively and 
# Adding these columns to the existing dataframe.
df[['First','Last']] = df.Name.apply(
   lambda x: pd.Series(str(x).split("_")))
   
print(df)

输出 :