How to count occurrences of specified value in column in Pandas using Python

Question

I have the following dataframe where I need to count how many rows contain 'False' in column IsCleared.

       IsCleared
0       False   
1       False
2       True
3       False

So I do the following in Python 2.7:

sum = df[df.IsCleared == 'False'].count()
print sum

But I get this error:

FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison
  result = getattr(x, name)(y)
invalid type comparison

What am I doing wrong?

Answer 1

You have a boolean mask. So why not work with it?

>>> (~df.IsCleared).sum()
3

Negate False values to True , and then sum them up (since True is equivalent to 1 , and False equivalent to 0 , this works nicely).

Answer 2

Do this:

df['IsCleared'].value_counts()

This should give you the total counts of false and true

Answer 3

You did it wrong because you turned False into a string 'False' at the line

df[df.IsCleared == 'False'].count() .

Thus, it is complaining because you make it compare a boolean value with a string.

invalid type comparison

Change it into

df[df.IsCleared == False].count()

and it shall work.