[英]How to remove selected special characters from DataFrame column in Python
I am merging different excel files into a csv file.我正在将不同的 excel 文件合并到一个 csv 文件中。 Values in one of the columns(Length) in the source files contain single quote (eg '200, '50 etc.).
源文件中列(长度)之一中的值包含单引号(例如'200、'50 等)。 Some values can also contain a period at the end(eg '200., '50., '10.3 etc.).
某些值还可以在末尾包含句点(例如'200.、'50.、'10.3 等)。 I want to to remove only the single quote from the values.
我只想从值中删除单引号。
Input输入
Length
=======
'2000
'100.
'10.3
Desired output期望输出
Length
=======
2000
100.
10.3
I am using the following code but somehow it also removes period(.) from the values.我正在使用以下代码,但不知何故它也从值中删除了 period(.)。 Please help.
请帮忙。
import pandas as pd
import glob
path= input("Enter the location of files ")
GLB_DM_VER = input("Enter global DM version")
GLB_DM_ENV = input("Enter the global DM version environment")
file_list = glob.glob(path+"\*.xls")
excels = [pd.ExcelFile(name) for name in file_list]
frames = [x.parse(x.sheet_names[2], header=0,index_col=None) for x in excels]
combined = pd.concat(frames)
**combined['LENGTH'].replace(regex=True,inplace=True,to_replace=r'\'',value=r'')**
combined.to_csv("STAND_2.csv", header=['Global_DM_VERSION_ID','Global_DM_VERSION_ENV','TARGET_DOMAIN','SOURCE_DOMAIN','DOMAIN_LABEL','SOURCE_VARIABLE','RAVE_LABEL','TYPE','VARIABLE_LENGTH','CONTROL_TYPE','CODELIST_OID','TARGET_VARIABLE','MANDATORY','RAVE_ORIGIN'], index=False)
You can try with:您可以尝试:
df['length'].str.replace("'","")
This will remove all the single quotes in the column这将删除列中的所有单引号
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