如何删除数据框中的回车 [英] How to remove carriage return in a dataframe
问题描述
我有一个数据框，其中包含名为id，country_name，location和total_deaths的列.在执行数据清理过程时，我在附加了'\r'的行中遇到了一个值.完成清理过程后，将结果数据帧存储在destination.csv文件中.由于上面的特定行已附加\r，因此始终会创建一个新行.
I am having a dataframe that contains columns named id, country_name, location and total_deaths. While doing data cleaning process, I came across a value in a row that has '\r' attached. Once I complete cleaning process, I store the resulting dataframe in destination.csv file. Since the above particular row has \r attached, it always creates a new row.
id 29
location Uttar Pradesh\r
country_name India
total_deaths 20
我要删除\r.我尝试了df.replace({'\r': ''}, regex=True).它对我不起作用.
I want to remove \r. I tried df.replace({'\r': ''}, regex=True). It isn't working for me.
还有其他解决方案吗?有人可以帮忙吗?
Is there any other solution. Can somebody help?
在上面的过程中，我遍历df以查看是否存在\r.如果存在，则需要更换.在这里row.replace()或row.str.strip()似乎没有用，或者我做错了方法.
In the above process, I am iterating over df to see if \r is present. If present, then need to replace. Here row.replace() or row.str.strip() doesn't seem to be working or I could be doing it in a wrong way.
在使用replace()时，我不想指定列名或行号.因为我不能确定只有'location'列会包含\r.请在下面找到代码.
I don't want specify the column name or row number while using replace(). Because I can't be certain that only 'location' column will be having \r. Please find the code below.
count = 0
for row_index, row in df.iterrows():
if re.search(r"\\r", str(row)):
print type(row) #Return type is pandas.Series
row.replace({r'\\r': ''} , regex=True)
print row
count += 1
推荐答案
Another solution is use str.strip:
df['29'] = df['29'].str.strip(r'\\r')
print df
id 29
0 location Uttar Pradesh
1 country_name India
2 total_deaths 20
如果要使用 replace ，添加r和一个\:
print df.replace({r'\\r': ''}, regex=True)
id 29
0 location Uttar Pradesh
1 country_name India
2 total_deaths 20
在replace中，您可以定义要替换的列，例如:
In replace you can define column for replacing like:
print df
id 29
0 location Uttar Pradesh\r
1 country_name India
2 total_deaths\r 20
print df.replace({'29': {r'\\r': ''}}, regex=True)
id 29
0 location Uttar Pradesh
1 country_name India
2 total_deaths\r 20
print df.replace({r'\\r': ''}, regex=True)
id 29
0 location Uttar Pradesh
1 country_name India
2 total_deaths 20
通过评论
import pandas as pd
df = pd.read_csv('data_source_test.csv')
print df
id country_name location total_deaths
0 1 India New Delhi 354
1 2 India Tamil Nadu 48
2 3 India Karnataka 0
3 4 India Andra Pradesh 32
4 5 India Assam 679
5 6 India Kerala 128
6 7 India Punjab 0
7 8 India Mumbai, Thane 1
8 9 India Uttar Pradesh\r\n 20
9 10 India Orissa 69
print df.replace({r'\r\n': ''}, regex=True)
id country_name location total_deaths
0 1 India New Delhi 354
1 2 India Tamil Nadu 48
2 3 India Karnataka 0
3 4 India Andra Pradesh 32
4 5 India Assam 679
5 6 India Kerala 128
6 7 India Punjab 0
7 8 India Mumbai, Thane 1
8 9 India Uttar Pradesh 20
9 10 India Orissa 69
如果仅需要在location列中替换:
If need replace only in column location:
df['location'] = df.location.str.replace(r'\r\n', '')
print df
id country_name location total_deaths
0 1 India New Delhi 354
1 2 India Tamil Nadu 48
2 3 India Karnataka 0
3 4 India Andra Pradesh 32
4 5 India Assam 679
5 6 India Kerala 128
6 7 India Punjab 0
7 8 India Mumbai, Thane 1
8 9 India Uttar Pradesh 20
9 10 India Orissa 69
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