在 Pandas DataFrame 中替换字符中的字符

在本文中，我们将了解如何使用Python替换 pandas 数据框中字符串中的字符。

我们可以使用 str.replace() 方法替换字符基本上是用新的替换现有字符串或字符中的字符串。我们可以为整个数据框以及特定列替换字符中的字符串。

Syntax: str.replace (old_string, new_string, n=-1, case=None, regex=True)

Parameters:

• old_string: string to be replaced.
• new_string: string or callable to replace instead of pat.
• n: Number of replacement to make in a single string, default is -1 which means All.
• case: Takes boolean value to decide case sensitivity. Make false for case insensitivity.
• regex: Boolean value, if True assume that the passed pattern is a regex.

Return Type: return a copy of the object with all matching occurrences of old_string replaced by new_string.

示例 1：下面的程序是为整个数据帧替换字符串中的一个字符。

Python3

# import pandas
import pandas as pd
 
data = {'Student_Full_Name':  ['Mukul_Jatav', 'Rahul_Shukla',
                               'Robin_Singh', 'Mayank_Sharma',
                               'Akash_Verma'],
        'Father_Full_name': ['Mukesh_Jatav', 'Siddhart_Shukla',
                             'Rohit_Singh', 'Sunil_Sharma',
                             'Rajesh_Verma']
        }
# create an dataframe
df = pd.DataFrame(data, columns=['Student_Full_Name',
                                 'Father_Full_name'])
 
# print dataframe
print(" original dataframe \n", df)
 
# replace '_' with '-'
df = df.replace('_', '+', regex=True)
 
# print dataframe
print(" After replace character \n", df)

输出：

示例 2：下面的程序是为特定列替换字符串中的一个字符。

Python3

# import pandas
import pandas as pd
 
data = {'first':  ['abcp', 'xyzp', 'mpok',
                   'qrps', 'ptuw'],
        'second': ['abcp', 'xyzp', 'mpok',
                   'qrps', 'ptuw']
        }
# create an dataframe
df = pd.DataFrame(data, columns=['first', 'second'])
 
# print dataframe
print("\n original dataframe \n\n", df)
 
# replace '_' with '='
df['first'] = df['first'].str.replace('p', '-')
 
# print dataframe
print("\n\n After replace character \n\n", df)

输出：