DataFrame: IF-condition in lambda asks about Series, but single element is needed to be checked-CodePudding

import numpy as np
import pandas as pd

#create DataFrame
df = pd.DataFrame({'str': [700,705,710,715,720,1095,1100,1105,1110,1115,1120,1125,1130,1135,1205,1210,1215,1220,1225,1230,1235,1240,1245,1250,1255],
 'P': [0.075,0.075,0.075,0.075,0.075,17.95,19.75,21.85,24.25,26.55,29.2,31.9,35.05,37.7,98.6,102.15,108.5,113.5,118.4,123.55,127.3,132.7,138.7,142.7,148.35],
 'C': [407.8,403.65,398.3,391.65,387.8,30.05,26.65,23.7,21.35,19.65,16.05,14.3,11.95,9.95,0.475,0,0.525,0,0.2,0.175,0.15,0.375,0.125,0.075,0.175]})

df = df.assign(ot= lambda x: x['P']  if (x['str']<1105) else x['C'])
print(df)

ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

I suppose, x['str'] is being taken as Series, thus perhaps the index of the current row is needed, though it seems strange as so as "lambda x" I think should include only current row index & not the whole x['str'] Series. HOW to make condition "x['str']<1105" to be checked in such a lambda correctly??

CodePudding user response：

I think you're looking for this:

result_list = [(x['P'] if (x['str'] < 1105) else x['C']) for i, x in df.iterrows()]

CodePudding user response：

also Solution from here:

df['ot'] = df[['P','C', 'str']].apply(lambda x: x['P'] if x['str']<1105 else x['C'], axis=1)