在 Pandas 中将列转换为行名/索引

Pandas 提供了一种方便的方式来处理数据及其转换。让我们看看如何在 Pandas 中将列转换为行名/索引。

首先使用列表的字典创建一个数据框。

Python3

# importing pandas as pd
import pandas as pd
 
# Creating a dict of lists
data = {'Name':["Akash", "Geeku", "Pankaj", "Sumitra","Ramlal"],
       'Branch':["B.Tech", "MBA", "BCA", "B.Tech", "BCA"],
       'Score':["80","90","60", "30", "50"],
       'Result': ["Pass","Pass","Pass","Fail","Fail"]}
 
# creating a dataframe
df = pd.DataFrame(data)
  
df

输出：

方法 #1：使用 set_index() 方法。

Python3

# importing pandas as pd
import pandas as pd
 
# Creating a dict of lists
data = {'Name':["Akash", "Geeku", "Pankaj", "Sumitra","Ramlal"],
       'Branch':["B.Tech", "MBA", "BCA", "B.Tech", "BCA"],
       'Score':["80","90","60", "30", "50"],
       'Result': ["Pass","Pass","Pass","Fail","Fail"]}
 
# Creating a dataframe
df = pd.DataFrame(data)
 
# Using set_index() method on 'Name' column
df = df.set_index('Name')
 
df

输出：

现在，将索引名称设置为无。

Python3

# set the index to 'None' via its name property
df.index.names = [None]
 
df

输出：

方法 #2：使用 pivot() 方法。
为了将列转换为数据框中的行名/索引，Pandas 有一个内置函数Pivot。
现在，假设我们希望 Result 是行/索引，列是我们数据框中的名称，为了实现这一点，pandas 提供了一个名为 Pivot 的方法。让我们看看它是如何工作的，

Python3

# importing pandas as pd
import pandas as pd
 
# Creating a dict of lists
data = {'name':["Akash", "Geeku", "Pankaj", "Sumitra", "Ramlal"],
       'Branch':["B.Tech", "MBA", "BCA", "B.Tech", "BCA"],
       'Score':["80", "90", "60", "30", "50"],
       'Result': ["Pass", "Pass", "Pass", "Fail", "Fail"]}
 
df = pd.DataFrame(data)
 
# pivoting the dataframe
df.pivot(index ='Result', columns ='name')
 
df

输出：