根据另一个 dataframe 替换列中的值

Question

I have a table:

Name        Profession         Character
Ben         cinematographer    Nan
Scarlett    actress            Black Widow
Robert      actor              Iron Man
Chris       actor              Thor
Kevin       producer           Nan

I created a new data frame with a column of unique values sorted in ascending order from the table above and an incremental column

ID    Job
1      actor
2      actress
3      cinematographer
4      producer

Now i need to replace the values in the profession column in the original table with their corresponding ID from the new table Desired Output

Name        Profession         Character
Ben         3                  Nan
Scarlett    2                  Black Widow
Robert      1                  Iron Man
Chris       1                  Thor
Kevin       4                  Nan

code so far
df=pdf.read_csv(filename)
column = df['Profession'].unique()
new_df=pd.DataFrame(column, columns=['Job])
new_df=new_df.sort_values(['Job'])
new_df = new_df.reset_index()
new_df.columns.values[0] = 'ID'
new_df['ID'] = new_df.index + 1
df.loc[df['Profession] == new_df['Job'], 'Profession'] = new_df['ID']

The last line yeilds 'ValueError: Can only compare identically-labeled Series objects'

Answer 1

Try with replace then

df1.Profession = df1.Profession.replace(df2.set_index('Job').ID)