I have a CSV file with two columns (permno_adj and publn_year) and I want to combine them but don't know how to do it.
The code I am using:
patents = pd.read_csv('E:/Work/file.csv')
patents = patents[['publn_nr', 'permno_adj', 'publn_year', 'IPC1']].dropna().drop_duplicates().reset_index(drop=True)
patents = patents[(patents['publn_year'] >= 1980) & (patents['publn_year'] < 2016)].reset_index(drop=True)
print(patents)
The output I am currently getting i:
publn_nr permno_adj publn_year IPC1
0 1830 US4060B 2005 F16F
1 24429 US4060A 2004 B29C
2 24943 US1794 2006 C08J
3 26115 US133366B 1999 A61B
4 31737 US4060A 2004 C08F
The output I am looking for is something like "US4060B2005"
CodePudding user response:
You could concatenate like string
patents['new_column'] = patents['permno_adj'].astype(str) patents['publn_year'].astype(str)
CodePudding user response:
follow assign
function pandas assign
d = {'col1': ['c11', 'c12'], 'col2': ['c21', 'c22']}
df = pd.DataFrame(d)
df = df.assign(col3=df['col1'] df['col2'])
df
col1 col2 col3
0 c11 c21 c11c21
1 c12 c22 c12c22