作者：LINBO-D_915 | 来源：互联网 | 2023-09-15 15:18
在熊猫数据框中分割一列并获得其中的一部分
原文:https://www . geesforgeks . org/split-a-column-in-pandas-data frame-and-get-part-it/
当 Dataframe 中任何列的一部分很重要并且需要将其分离时，我们可以根据需求拆分一个列。
我们可以用熊猫。str 访问器，它对 Series 和 Dataframes 进行快速矢量化字符串操作，并返回一个字符串对象。Pandas str 访问器有许多有用的方法，其中之一是str.split，它可以与 split 一起使用来获取字符串的所需部分。要获取字符串的第 n th 部分，首先通过分隔符分割列，并在返回的对象上再次应用str【n-1】，即Dataframe.columnName.str.split(" ").str[n-1]。
我们通过例子来说明一下。
代码#1: 打印分割列的数据对象。
import pandas as pd
import numpy as np
df = pd.DataFrame({'Geek_ID':['Geek1_id', 'Geek2_id', 'Geek3_id',
'Geek4_id', 'Geek5_id'],
'Geek_A': [1, 1, 3, 2, 4],
'Geek_B': [1, 2, 3, 4, 6],
'Geek_R': np.random.randn(5)})
# Geek_A Geek_B Geek_ID Geek_R
# 0 1 1 Geek1_id random number
# 1 1 2 Geek2_id random number
# 2 3 3 Geek3_id random number
# 3 2 4 Geek4_id random number
# 4 4 6 Geek5_id random number
print(df.Geek_ID.str.split('_').str[0])
Output:
0 Geek1
1 Geek2
2 Geek3
3 Geek4
4 Geek5
dtype: object
代码#2: 打印返回数据对象列表。
import pandas as pd
import numpy as np
df = pd.DataFrame({'Geek_ID':['Geek1_id', 'Geek2_id', 'Geek3_id',
'Geek4_id', 'Geek5_id'],
'Geek_A': [1, 1, 3, 2, 4],
'Geek_B': [1, 2, 3, 4, 6],
'Geek_R': np.random.randn(5)})
# Geek_A Geek_B Geek_ID Geek_R
# 0 1 1 Geek1_id random number
# 1 1 2 Geek2_id random number
# 2 3 3 Geek3_id random number
# 3 2 4 Geek4_id random number
# 4 4 6 Geek5_id random number
print(df.Geek_ID.str.split('_').str[0].tolist())
Output:
['Geek1', 'Geek2', 'Geek3', 'Geek4', 'Geek5']
代码#3: 打印元素列表。
import pandas as pd
import numpy as np
df = pd.DataFrame({'Geek_ID':['Geek1_id', 'Geek2_id', 'Geek3_id',
'Geek4_id', 'Geek5_id'],
'Geek_A': [1, 1, 3, 2, 4],
'Geek_B': [1, 2, 3, 4, 6],
'Geek_R': np.random.randn(5)})
# Geek_A Geek_B Geek_ID Geek_R
# 0 1 1 Geek1_id random number
# 1 1 2 Geek2_id random number
# 2 3 3 Geek3_id random number
# 3 2 4 Geek4_id random number
# 4 4 6 Geek5_id random number
print(df.Geek_ID.str.split('_').str[1].tolist())
Output:
['id', 'id', 'id', 'id', 'id']
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