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

Question

I am trying to add a new column to a dataframe that uses other columns to create a 'Green Score' for reach row. In the example below, I would like each car 'Model' to have a score that shows how 'green' the car is.

My data (simplified):

cars = {'Model': ['Honda Civic','Toyota Corolla','Smart Car','Tesla'],
        'Green Fuel': [False, False, True, True],
        'Energy Use': ['High','Medium','Low','Low'],
        }

df = pd.DataFrame(cars, columns = ['Model', 'Green Fuel', 'Energy Use'])

df['Green Score'] = 0

A printing the cars dataframe:

    Model   Green Fuel  Energy Use  Green Score
0   Honda Civic     False   High    0
1   Toyota Corolla  False   Medium  0
2   Smart Car   True    Low     0
3   Tesla   True    Low     0

Now, to calculate the Green Scores of each model I am trying this:

for car in df['Model']:
    if df['Green Fuel'] == True:
        df['Green Score'] += 1
    else:
        pass

When I run this, however, I get the error:

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

Can someone point me in the right direction as to how to solve this error?

Thank jezrael, you got it pretty much right in your answer – Toms Code Dec 03 '20 at 13:01 — Toms Code, Dec 03 '20 at 13:01

score 2 · Accepted Answer · answered Dec 03 '20 at 12:41

First the best is forget for loops with for in pandas, if exist some vectorized methods - e.g. here is possible convert boolean to integers and sum with mapping another column (only my idea, I try to be creative ;) ):

d = {'High':1,'Medium':2,'Low':3}
df['Green Score'] = df['Green Fuel'].astype(int) + df['Energy Use'].map(d)
print (df)
            Model  Green Fuel Energy Use  Green Score
0     Honda Civic       False       High            1
1  Toyota Corolla       False     Medium            2
2       Smart Car        True        Low            4
3           Tesla        True        Low            4

score 1 · Answer 2 · answered Dec 03 '20 at 12:57

1

I think that the problem is in your for loop, you are iterating over values of a specific column and then you're trying to verify value of a whole column when writing if df['Green Fuel'] == True.You should iterate over rows and verify the values of each row giving the name of the column ex:

for row in df.iterrows():
  if row['Green Fuel'] == True:
        row['Green Score'] += 1
    else:
        pass```

answered Dec 03 '20 at 12:57

D_action

83
6

1

https://stackoverflow.com/questions/24870953/does-pandas-iterrows-have-performance-issues/24871316#24871316 – jezrael Dec 03 '20 at 12:58

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

2 Answers2