I have a data set like the following:
ID Type
1 a
2 a
3 b
4 b
5 c
And I'm trying to create the column URL as shown by specifying a different URL based on the "Type" and appending the "ID".
ID Type URL
1 a http://example.com/examplea/id=1
2 a http://example.com/examplea/id=2
3 b http://example.com/bbb/id=3
4 b http://example.com/bbb/id=4
5 c http://example.com/testc/id=5
I'm using something like this for the code but it is not pulling in the ID for just that row, instead it is appending all the IDs that have Type = a.
df.loc[df['Type'] == 'a', 'URL']= 'http://example.com/examplea/id='+str(df['ID'])
df.loc[df['Type'] == 'b', 'URL']= 'http://example.com/bbb/id='+str(df['ID'])
You should alter the command a bit:
df.loc[df['Type'] == 'a', 'URL']= 'http://example.com/examplea/id='+df['ID'].astype(str)
df.loc[df['Type'] == 'b', 'URL']= 'http://example.com/bbb/id='+df['ID'].astype(str)
Or you can use map
like this:
url_dict = {
'a':'http://example.com/examplea/id=',
'b':'http://example.com/bbb/id=',
'c':'http://example.com/testc/id='
}
df['URL'] = df['Type'].map(url_dict) + df['ID'].astype(str)
Output:
ID Type URL
0 1 a http://example.com/examplea/id=1
1 2 a http://example.com/examplea/id=2
2 3 b http://example.com/bbb/id=3
3 4 b http://example.com/bbb/id=4
4 5 c http://example.com/testc/id=5