For example I have the following DataFrame:
| A header | header. 1 | header. 2 | header. 3 |
|---|---|---|---|
| First | 111 | 121 | 323 |
| Second | 222 | 212 | 232 |
I want my new column to be based on the following if condition: if (value in df.header1 > than 0, then add 2) and (value in df.header2 is between 2 and 3, then add 5) and (value in df.header3 and < 400, then add 11)
so my new df would look like this:
| A header | header. 1 | header. 2 | header. 3 | condition_head |
|---|---|---|---|---|
| First | 111 | 121 | 323 | 13 |
| Second | 222 | 212 | 232 | 12 |
Based on your logic use:
df['output'] = (df['header.1'].gt(0) * 2 +
df['header.2'].between(2,3) * 5 +
df['header.3'].lt(400) * 11 )
Output:
A header header. 1 header. 2 header. 3 output
0 First 111 121 323 13
1 Second 222 212 232 13
I'm not sure how you get to your expected output.
df['condition_head'] = 0
df['condition_head'] += 2 * (df['header.1'] > 0)
df['condition_head'] += 5 * (df['header.2'] > 2 and df['header.2'] < 3)
df['condition_head'] += 11 * (df['header.3'] > 400)
Try using df.apply() and a self defined helper function:
def helper(x):
ans= 0
if 0< x['header.1']:
ans+=2
if 2< x['header.2']<=3:
ans+=5
if x['header.3']<400:
ans+=11
return ans
df['contition_head'] = df.apply(helper, axis=1)
df['condition_head']?