python replace string function throws asterix wildcard error - regex

Question

When i use * i receive the error
raise error, v # invalid expression
error: nothing to repeat
other wildcard characters such as ^ work fine.
the line of code:
df.columns = df.columns.str.replace('*agriculture', 'agri')
am using pandas and python
edit:
when I try using / to escape, the wildcard does not work as i intend
In[44]df = pd.DataFrame(columns=['agriculture', 'dfad agriculture df'])
In[45]df
Out[45]:
Empty DataFrame
Columns: [agriculture, dfad agriculture df]
Index: []
in[46]df.columns.str.replace('/*agriculture*','agri')
Out[46]: Index([u'agri', u'dfad agri df'], dtype='object')
I thought the wildcard should output Index([u'agri', u'agri'], dtype='object)
edit:
I am currently using hierarchical columns and would like to only replace agri for that specific level (level = 2).
original:
df.columns[0] = ('grand total', '2005', 'agriculture')
df.columns[1] = ('grand total', '2005', 'other')
desired:
df.columns[0] = ('grand total', '2005', 'agri')
df.columns[1] = ('grand total', '2005', 'other')
I'm looking at this link right now: Changing columns names in Pandas with hierarchical columns
and that author says it will get easier at 0.15.0 so I am hoping there are more recent updated solutions

Answer 1

You need to the asterisk * at the end in order to match the string 0 or more times, see the docs:
In [287]:
df = pd.DataFrame(columns=['agriculture'])
df
Out[287]:
Empty DataFrame
Columns: [agriculture]
Index: []
In [289]:
df.columns.str.replace('agriculture*', 'agri')
Out[289]:
Index(['agri'], dtype='object')
EDIT
Based on your new and actual requirements, you can use str.contains to find matches and then use this to build a dict to map the old against new names and then call rename:
In [307]:
matching_cols = df.columns[df.columns.str.contains('agriculture')]
df.rename(columns = dict(zip(matching_cols, ['agri'] * len(matching_cols))))
Out[307]:
Empty DataFrame
Columns: [agri, agri]
Index: []