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pythonpandasloops
Mauritius
Mauritius

Reputation: 275

Pandas set column value based on other columns value with list item by iteration

I am trying to set the value of a pandas column based on another columns value. The new value should be set by iterating through a list, that has the same length like the unique values of col1

Example:

d = {'col1': [1, 2,2,2,3,3,4], 'col2': [1,1,1,1,1,1,1]}
df = pd.DataFrame(data=d)
items_to_add=[5,2,11,9]
#list has length of unique values in `column1`

Now i want to add for example 5 to column2 if column1is 1 and 2 to all column2 rows where column1 is 2 .... So i should get:

col1    col2
1       5
2       2
2       2
2       2
3       11
3       11
4       9

This code throws me an syntax error but i do not know why

items_to_add=[5,2,11,9]
for i in range(len(items_to_add)):
    df['col2'][df.col1[i]] = items_to_add[i]

What am I doing wrong? How can i fix it?

Upvotes: 0

Views: 770

Answers (3)

Pyd
Pyd

Reputation: 6159

I think you need to remove duplicates then map,

df['col1'].map(dict(zip(df['col1'].drop_duplicates(),items_to_add)))
#out[]
0     5
1     2
2     2
3     2
4    11
5    11
6     9

Upvotes: 0

Bharath M Shetty
Bharath M Shetty

Reputation: 30605

You can simply replace the values in col1 by creating a dictionary i.e 

di =  dict(zip(df['col1'].unique(), items_to_add))
# {1: 5, 2: 2, 3: 11, 4: 9}
df['col3'] = df['col1'].map(di)

   col1  col2  col3
0     1     1     5
1     2     1     2
2     2     1     2
3     2     1     2
4     3     1    11
5     3     1    11
6     4     1     9

Upvotes: 2

Atul Shanbhag
Atul Shanbhag

Reputation: 636

This is what you do

df['col2'] = df['col1'].apply(lambda x: items_to_add[x-1])

By doing this you create a new column col2 where for every x in df[col1], you choose the (x-1)th indexed value of items_to_add.

Upvotes: 0

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