Python Pandas ValueError on simple query

Question

The following line causes a ValueError (Pandas 17.1), and I'm trying to understand why.

x = (matchdf['ANPR Matched_x'] == 1)

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

I'm trying to use it for following conditional assignment:

matchdf.loc[x, 'FullMatch'] = 1

But I can't get past the previous issue.

I'm sure I've done this kind of thing dozens of times before, and I can't see why it should matter what is in the dataframe, but perhaps it does? or more likely, I'm probably making a silly mistake I just can't see!

Thanks for any help.

EDIT: For more context here's some preceding code:

inpairs = []
for m in inmatchedpairs:
    # more code
    p = {'Type In': mtype ,'Best In Time': besttime, 'Best G In Time': bestgtime,
         'Reg In': reg, 'ANPR Matched': anprmatch, 'ANPR Match Key': anprmatchkey}
    inpairs.append(p)

outpairs = []
for m in outmatchedpairs:
    # more code
    p = {'Type Out': mtype ,'Best Out Time': besttime, 'Best G Out Time': bestgtime,
         'Reg Out': reg, 'ANPR Matched': anprmatch, 'ANPR Match Key': anprmatchkey}
    outpairs.append(p)

indf = pd.DataFrame(inpairs)
outdf = pd.DataFrame(outpairs)
matchdf = pd.merge(indf, outdf, how='outer', on='ANPR Match Key')
matchdf['FullMatch'] = 0

x = (matchdf['ANPR Matched_x'] == 0)

I get the error on the last line.

I've added more of the example, but can't seem to replicate it elsewhere. Confused! — Incompetent Perfectionist
– Incompetent Perfectionist, Commented Sep 1, 2016 at 16:55

Alexander · Accepted Answer · 2016-09-01 17:03:59Z

2

Use loc to set the values.

matchdf.loc[matchdf['APNR Matched_x'] == 1, 'FullMatch'] = 1

Example

df = pd.DataFrame({'APNR Matched_x': [0, 1, 1, 0], 'Full Match': [False] * 4})

>>> df
   APNR Matched_x Full Match
0               0      False
1               1      False
2               1      False
3               0      False

df.loc[df['APNR Matched_x'] == 1, 'FullMatch'] = 1

>>> df
   APNR Matched_x Full Match  FullMatch
0               0      False        NaN
1               1      False          1
2               1      False          1
3               0      False        NaN

edited Sep 1, 2016 at 17:03

answered Sep 1, 2016 at 16:45

Alexander

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1 Comment

Incompetent Perfectionist Over a year ago

Thanks. I think my problem must relate to what's in my DataFrame after the merge, or a Pandas bug of some kind then.

Incompetent Perfectionist · Accepted Answer · 2016-09-01 18:14:12Z

1

If you have this kind of error, first check your dataframe contains what you think it does.

I was stupidly ending up with some Series objects being added to one of the columns which should have contained ints!

answered Sep 1, 2016 at 18:14

Incompetent Perfectionist

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