Setting flag column depending on whether column contains a given string
Can anyone see why this isn't working?
Its trying to do; if Column Name Contains the text 'Andy', then make a column called Andy and set that row = to 1
df.loc[df['Name'].str.contains(['Andy']),'Andy']=1
python string pandas series
asked Dec 13 at 9:25
fred.schwartz
2958
add a comment |
Can anyone see why this isn't working?
Its trying to do; if Column Name Contains the text 'Andy', then make a column called Andy and set that row = to 1
df.loc[df['Name'].str.contains(['Andy']),'Andy']=1
python string pandas series
asked Dec 13 at 9:25
fred.schwartz
2958
If you are planning to do this for other names then consider get_dummies method pandas.pydata.org/pandas-docs/stable/generated/…
– shantanuo
Dec 16 at 14:01
add a comment |
Can anyone see why this isn't working?
Its trying to do; if Column Name Contains the text 'Andy', then make a column called Andy and set that row = to 1
df.loc[df['Name'].str.contains(['Andy']),'Andy']=1
python string pandas series
asked Dec 13 at 9:25
fred.schwartz
2958
Can anyone see why this isn't working?
Its trying to do; if Column Name Contains the text 'Andy', then make a column called Andy and set that row = to 1
df.loc[df['Name'].str.contains(['Andy']),'Andy']=1
python string pandas series
python string pandas series
asked Dec 13 at 9:25
fred.schwartz
2958
asked Dec 13 at 9:25
fred.schwartz
2958
edited Dec 14 at 9:32
asked Dec 13 at 9:25
fred.schwartz
2958
asked Dec 13 at 9:25
fred.schwartz
2958
asked Dec 13 at 9:25
fred.schwartz
2958
2958
If you are planning to do this for other names then consider get_dummies method pandas.pydata.org/pandas-docs/stable/generated/…
– shantanuo
Dec 16 at 14:01
add a comment |
If you are planning to do this for other names then consider get_dummies method pandas.pydata.org/pandas-docs/stable/generated/…
– shantanuo
Dec 16 at 14:01
If you are planning to do this for other names then consider get_dummies method pandas.pydata.org/pandas-docs/stable/generated/…
– shantanuo
Dec 16 at 14:01
If you are planning to do this for other names then consider get_dummies method pandas.pydata.org/pandas-docs/stable/generated/…
– shantanuo
Dec 16 at 14:01
add a comment |
2 Answers
2
active
oldest
votes
You have to remove list, need only string:
df.loc[df['Name'].str.contains('Andy'),'Andy'] = 1
For multiple values chain by |:
df.loc[df['Name'].str.contains('Andy|George'),'Andy'] = 1
answered Dec 13 at 9:30
jezrael
319k22258337
add a comment |
pd.Series.str.contains requires for its pat argument a "Character sequence or regular expression", not a list.
Just use Boolean assignment and convert to int. This will set unmatched rows to 0. For example:
# Name includes 'Andy'
df['Andy'] = df['Name'].str.contains('Andy').astype(int)
# Name includes 'Andy' or 'George'
df['Andy'] = df['Name'].str.contains('Andy|George').astype(int)
answered Dec 13 at 9:46
jpp
90.4k2052101
@fred.Schwartz, Yes, that's not valid regex for what you want. That's a separate question.
– jpp
Dec 14 at 9:31
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 have to remove list, need only string:
df.loc[df['Name'].str.contains('Andy'),'Andy'] = 1
For multiple values chain by |:
df.loc[df['Name'].str.contains('Andy|George'),'Andy'] = 1
answered Dec 13 at 9:30
jezrael
319k22258337
add a comment |
You have to remove list, need only string:
df.loc[df['Name'].str.contains('Andy'),'Andy'] = 1
For multiple values chain by |:
df.loc[df['Name'].str.contains('Andy|George'),'Andy'] = 1
answered Dec 13 at 9:30
jezrael
319k22258337
add a comment |
You have to remove list, need only string:
df.loc[df['Name'].str.contains('Andy'),'Andy'] = 1
For multiple values chain by |:
df.loc[df['Name'].str.contains('Andy|George'),'Andy'] = 1
answered Dec 13 at 9:30
jezrael
319k22258337
You have to remove list, need only string:
df.loc[df['Name'].str.contains('Andy'),'Andy'] = 1
For multiple values chain by |:
df.loc[df['Name'].str.contains('Andy|George'),'Andy'] = 1
answered Dec 13 at 9:30
jezrael
319k22258337
answered Dec 13 at 9:30
jezrael
319k22258337
answered Dec 13 at 9:30
jezrael
319k22258337
answered Dec 13 at 9:30
jezrael
319k22258337
319k22258337
add a comment |
add a comment |
pd.Series.str.contains requires for its pat argument a "Character sequence or regular expression", not a list.
Just use Boolean assignment and convert to int. This will set unmatched rows to 0. For example:
# Name includes 'Andy'
df['Andy'] = df['Name'].str.contains('Andy').astype(int)
# Name includes 'Andy' or 'George'
df['Andy'] = df['Name'].str.contains('Andy|George').astype(int)
answered Dec 13 at 9:46
jpp
90.4k2052101
@fred.Schwartz, Yes, that's not valid regex for what you want. That's a separate question.
– jpp
Dec 14 at 9:31
add a comment |
pd.Series.str.contains requires for its pat argument a "Character sequence or regular expression", not a list.
Just use Boolean assignment and convert to int. This will set unmatched rows to 0. For example:
# Name includes 'Andy'
df['Andy'] = df['Name'].str.contains('Andy').astype(int)
# Name includes 'Andy' or 'George'
df['Andy'] = df['Name'].str.contains('Andy|George').astype(int)
answered Dec 13 at 9:46
jpp
90.4k2052101
@fred.Schwartz, Yes, that's not valid regex for what you want. That's a separate question.
– jpp
Dec 14 at 9:31
add a comment |
pd.Series.str.contains requires for its pat argument a "Character sequence or regular expression", not a list.
Just use Boolean assignment and convert to int. This will set unmatched rows to 0. For example:
# Name includes 'Andy'
df['Andy'] = df['Name'].str.contains('Andy').astype(int)
# Name includes 'Andy' or 'George'
df['Andy'] = df['Name'].str.contains('Andy|George').astype(int)
answered Dec 13 at 9:46
jpp
90.4k2052101
pd.Series.str.contains requires for its pat argument a "Character sequence or regular expression", not a list.
Just use Boolean assignment and convert to int. This will set unmatched rows to 0. For example:
# Name includes 'Andy'
df['Andy'] = df['Name'].str.contains('Andy').astype(int)
# Name includes 'Andy' or 'George'
df['Andy'] = df['Name'].str.contains('Andy|George').astype(int)
answered Dec 13 at 9:46
jpp
90.4k2052101
answered Dec 13 at 9:46
jpp
90.4k2052101
answered Dec 13 at 9:46
jpp
90.4k2052101
answered Dec 13 at 9:46
jpp
90.4k2052101
90.4k2052101
@fred.Schwartz, Yes, that's not valid regex for what you want. That's a separate question.
– jpp
Dec 14 at 9:31
add a comment |
@fred.Schwartz, Yes, that's not valid regex for what you want. That's a separate question.
– jpp
Dec 14 at 9:31
@fred.Schwartz, Yes, that's not valid regex for what you want. That's a separate question.
– jpp
Dec 14 at 9:31
@fred.Schwartz, Yes, that's not valid regex for what you want. That's a separate question.
– jpp
Dec 14 at 9:31
add a comment |
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If you are planning to do this for other names then consider get_dummies method pandas.pydata.org/pandas-docs/stable/generated/…
– shantanuo
Dec 16 at 14:01