如何根据外部列表的值在 dataframe 中添加新列？

Question

I have a dataframe df with two columns: col1 and col2 .

col1 includes the id of my users. users is a list of names (ie strings). So, id=0 is equal to the name at index 0 in my users list.

I want to add a new column in my dataframe including the corresponding names of the ids .

Answer 1

If the id column only has unique values (meaning there aren't multiple rows with the same id) you can sort the dataframe by the id column then assign the list to a new column.

data = {'id': [2, 1, 0, 3]}    
df = pandas.DataFrame(data=d)

users = ['dave', 'sandy', 'will', 'arthur']

df.sort_values(by=['id'], inplace=True) 

df['user'] = users

Output:

id    user
 0    dave
 1   sandy
 2    will
 3  arthur

If the id column has multiple instances of the same id, you can use a lambda function:

data = {'id': [3, 1, 0, 3]}    
df = pandas.DataFrame(data=d)

users = ['dave', 'sandy', 'will', 'arthur']

df['user'] = df.apply(lambda row: users[row.id], axis=1)

Output:

id    user
 3  arthur
 1   sandy
 0    dave
 3  arthur

The lambda is basically saying for every row in this new column 'user', the value should be from the users list at the index given by the rows 'id' column value.

Answer 2

user_list = ['user_1', 'user_2', 'user_3']
Adding column to dataframe:

df['UserName'] = user_list