I have a dataframe that looks like below:
| Name | String Names |
|---|---|
| First | ['A','A','B','C'] |
| Second | ['AA','BB'] |
I want the output to be like
| Name | String Names |
|---|---|
| First | 'A','B','C' |
| Second | 'AA','BB' |
I need the list to be converted to str . I've done that using the below code
df['String Names'] = df['String Names'].str.join(',')
But I'm unable to get only the unique values.
Any suggestion how I can do it in python?
You might harness pandas.unique function following way:
import pandas as pd
df = pd.DataFrame({'Name':['First','Second'],'String Names':[['A','A','B','C'],['AA','BB']]})
df['String Names'] = df['String Names'].apply(pd.unique).str.join(',')
print(df)
output:
Name String Names
0 First A,B,C
1 Second AA,BB
pandas.unique does preserve order.
If order is not important convert values to sets:
df['String Names'] = df['String Names'].apply(set).str.join(',')
If order and performance is important use dict trick for remove duplicates:
df['String Names'] = df['String Names'].apply(lambda x: ','.join(dict.fromkeys(x).keys()))
df['String Names1'] = df['String Names'].apply(set).str.join(',')
df['String Names2'] = df['String Names'].apply(lambda x: ','.join(dict.fromkeys(x).keys()))
print(df)
Name String Names String Names1 String Names2
0 First [A, A, B, C] B,A,C A,B,C
1 Second [AA, BB] AA,BB AA,BB
