pandas python replace/deleting a hyphen in read_csv
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Hi I am trying to delete all hyphens from a csv data table. Where all values are XYZ-001, XYZ-002, XYZ-003, etc AND I want them to look like XYZ001, XYZ002, XYZ003. I cannot seem to figure out how to use the .replace() feature. Any other ideas??
import pandas as pd
dfz = pd.read_csv('control.csv', index_col=0, parse_dates=True)
df1 = pd.DataFrame(dfz[0])
print(dfz['Unnamed: 1'])
dfz['Unnamed: 1'].replace('-','')
python pandas
asked Jan 4 at 2:44
Ed_Ed_
195
add a comment |
Hi I am trying to delete all hyphens from a csv data table. Where all values are XYZ-001, XYZ-002, XYZ-003, etc AND I want them to look like XYZ001, XYZ002, XYZ003. I cannot seem to figure out how to use the .replace() feature. Any other ideas??
import pandas as pd
dfz = pd.read_csv('control.csv', index_col=0, parse_dates=True)
df1 = pd.DataFrame(dfz[0])
print(dfz['Unnamed: 1'])
dfz['Unnamed: 1'].replace('-','')
python pandas
asked Jan 4 at 2:44
Ed_Ed_
195
1
dfz['Unnamed: 1'].str.replace('-','')
– najeem
Jan 4 at 2:51
add a comment |
Hi I am trying to delete all hyphens from a csv data table. Where all values are XYZ-001, XYZ-002, XYZ-003, etc AND I want them to look like XYZ001, XYZ002, XYZ003. I cannot seem to figure out how to use the .replace() feature. Any other ideas??
import pandas as pd
dfz = pd.read_csv('control.csv', index_col=0, parse_dates=True)
df1 = pd.DataFrame(dfz[0])
print(dfz['Unnamed: 1'])
dfz['Unnamed: 1'].replace('-','')
python pandas
asked Jan 4 at 2:44
Ed_Ed_
195
Hi I am trying to delete all hyphens from a csv data table. Where all values are XYZ-001, XYZ-002, XYZ-003, etc AND I want them to look like XYZ001, XYZ002, XYZ003. I cannot seem to figure out how to use the .replace() feature. Any other ideas??
import pandas as pd
dfz = pd.read_csv('control.csv', index_col=0, parse_dates=True)
df1 = pd.DataFrame(dfz[0])
print(dfz['Unnamed: 1'])
dfz['Unnamed: 1'].replace('-','')
python pandas
python pandas
asked Jan 4 at 2:44
Ed_Ed_
195
asked Jan 4 at 2:44
Ed_Ed_
195
asked Jan 4 at 2:44
Ed_Ed_
195
asked Jan 4 at 2:44
Ed_Ed_
195
asked Jan 4 at 2:44
Ed_Ed_
195
195
1
dfz['Unnamed: 1'].str.replace('-','')
– najeem
Jan 4 at 2:51
add a comment |
1
dfz['Unnamed: 1'].str.replace('-','')
– najeem
Jan 4 at 2:51
1
1
dfz['Unnamed: 1'].str.replace('-','')– najeem
Jan 4 at 2:51
dfz['Unnamed: 1'].str.replace('-','')– najeem
Jan 4 at 2:51
add a comment |
2 Answers
2
active
oldest
votes
you can also use:
df.replace(r'[W]','',inplace=True,regex=True)
if you dont want to use inplace (you can go through this for pros and cons of inplace) you could assign it back like :
df = df.replace(r'[W]','',regex=True)
W finds any character that is not a letter, numeric digit, or the underscore character.
Use this only if you have unknown special characters in the dataframe.
answered Jan 4 at 3:27
anky_91anky_91
10.6k2922
add a comment |
dfz['Unnamed: 1'] = dfz['Unnamed: 1'].str.replace('-','')
Remember to assign it back.
Documentation here
answered Jan 4 at 3:21
ycxycx
1,711518
add a comment |
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2 Answers
2
active
oldest
votes
2 Answers
2
active
oldest
votes
active
oldest
votes
active
oldest
votes
you can also use:
df.replace(r'[W]','',inplace=True,regex=True)
if you dont want to use inplace (you can go through this for pros and cons of inplace) you could assign it back like :
df = df.replace(r'[W]','',regex=True)
W finds any character that is not a letter, numeric digit, or the underscore character.
Use this only if you have unknown special characters in the dataframe.
answered Jan 4 at 3:27
anky_91anky_91
10.6k2922
add a comment |
you can also use:
df.replace(r'[W]','',inplace=True,regex=True)
if you dont want to use inplace (you can go through this for pros and cons of inplace) you could assign it back like :
df = df.replace(r'[W]','',regex=True)
W finds any character that is not a letter, numeric digit, or the underscore character.
Use this only if you have unknown special characters in the dataframe.
answered Jan 4 at 3:27
anky_91anky_91
10.6k2922
add a comment |
you can also use:
df.replace(r'[W]','',inplace=True,regex=True)
if you dont want to use inplace (you can go through this for pros and cons of inplace) you could assign it back like :
df = df.replace(r'[W]','',regex=True)
W finds any character that is not a letter, numeric digit, or the underscore character.
Use this only if you have unknown special characters in the dataframe.
answered Jan 4 at 3:27
anky_91anky_91
10.6k2922
you can also use:
df.replace(r'[W]','',inplace=True,regex=True)
if you dont want to use inplace (you can go through this for pros and cons of inplace) you could assign it back like :
df = df.replace(r'[W]','',regex=True)
W finds any character that is not a letter, numeric digit, or the underscore character.
Use this only if you have unknown special characters in the dataframe.
answered Jan 4 at 3:27
anky_91anky_91
10.6k2922
edited Jan 4 at 3:53
answered Jan 4 at 3:27
anky_91anky_91
10.6k2922
answered Jan 4 at 3:27
anky_91anky_91
10.6k2922
answered Jan 4 at 3:27
anky_91anky_91
10.6k2922
10.6k2922
add a comment |
add a comment |
dfz['Unnamed: 1'] = dfz['Unnamed: 1'].str.replace('-','')
Remember to assign it back.
Documentation here
answered Jan 4 at 3:21
ycxycx
1,711518
add a comment |
dfz['Unnamed: 1'] = dfz['Unnamed: 1'].str.replace('-','')
Remember to assign it back.
Documentation here
answered Jan 4 at 3:21
ycxycx
1,711518
add a comment |
dfz['Unnamed: 1'] = dfz['Unnamed: 1'].str.replace('-','')
Remember to assign it back.
Documentation here
answered Jan 4 at 3:21
ycxycx
1,711518
dfz['Unnamed: 1'] = dfz['Unnamed: 1'].str.replace('-','')
Remember to assign it back.
Documentation here
answered Jan 4 at 3:21
ycxycx
1,711518
answered Jan 4 at 3:21
ycxycx
1,711518
answered Jan 4 at 3:21
ycxycx
1,711518
answered Jan 4 at 3:21
ycxycx
1,711518
1,711518
add a comment |
add a comment |
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dfz['Unnamed: 1'].str.replace('-','')– najeem
Jan 4 at 2:51