3

Am new to python programming. Can anyone pls check the below syntax for if condition-

if df1[A]<= df2[B]):
       print("")
else:
       print("")

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

derek9988
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1 Answers1

9

You compare arrays, no scalar, so output of camparing is another array. So need any or all. Also need length of both Series is same:

df1 = pd.DataFrame({'A':[1,2,3]})
print (df1)
   A
0  1
1  2
2  3

df2 = pd.DataFrame({'B':[1,2,0]})
print (df2)
   B
0  1
1  2
2  0

print (df1['A']<= df2['B'])
0     True
1     True
2    False
dtype: bool

#check if at least one True
print ((df1['A']<= df2['B']).any())
True

#check if all values are True
print ((df1['A']<= df2['B']).all())
False

if (df1['A']<= df2['B']).any():
       print("at least one value True")
else:
       print("no False values")
at least one value True

if (df1['A']<= df2['B']).all():
       print("all values True")
else:
       print("not all values True")

not all values True

df1 = pd.DataFrame({'A':[1,2,3]})
print (df1)
   A
0  1
1  2
2  3

df2 = pd.DataFrame({'B':[1,2,3]})
print (df2)
   B
0  1
1  2
2  3

print (df1['A']<= df2['B'])
0    True
1    True
2    True
dtype: bool

#check if at least one True
print ((df1['A']<= df2['B']).any())
True

#check if all values are True
print ((df1['A']<= df2['B']).all())
True

if (df1['A']<= df2['B']).any():
       print("at least one value True")
else:
       print("no False values")

at least one value True

if (df1['A']<= df2['B']).all():
       print("all values True")
else:
       print("not all values True")

all values True
jezrael
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  • no more true. I am using v.19.2 and df1 = pandas.DataFrame({'A':[1,2,3]}); df2 = pandas.DataFrame({'B':[2,2,3]}); df1 > df2; gives an error "ValueError: Can only compare identically-labeled DataFrame objects" – lehalle Feb 21 '18 at 14:46
  • @lehalle - You need compare columns `print (df1['A'] > df2['B'])` – jezrael Feb 21 '18 at 14:48