如何删除数据框中的回车

Question

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

I want to remove \\r . I tried df.replace({'\\r': ''}, regex=True) . It isn't working for me.

Is there any other solution. Can somebody help?

Edit:

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.

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

Answer 1

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

If you want use replace , add r and one \\ :

print df.replace({r'\\r': ''}, regex=True)
             id             29
0      location  Uttar Pradesh
1  country_name          India
2  total_deaths             20

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

EDIT by comment:

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

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

Answer 2

use str.replace , you need to escape the sequence so it treats it as a carriage return rather than the literal \\r :

In [15]:
df['29'] = df['29'].str.replace(r'\\r','')
df

Out[15]:
             id             29
0      location  Uttar Pradesh
1  country_name          India
2  total_deaths             20

Answer 3

The below code removes \\n tab spaces, \\n new line and \\r carriage return and is great for condensing datum into one row. The answer was taken from https://gist.github.com/smram/d6ded3c9028272360eb65bcab564a18a

df.replace(to_replace=[r"\\t|\\n|\\r", "\t|\n|\r"], value=["",""], regex=True, inplace=<INPLACE>)

Answer 4

Somehow, the accepted answer did not work for me. Ultimately, I found the solution by doing it like followed

df["29"] = df["29"].replace(r'\r', '', regex=True)

The difference is that I use \\r instead of \\\\r .

Answer 5

Just make df equal to the df.replace code line and then print df.

df=df.replace({'\r': ''}, regex=True) 
print(df)