Need count of negative values in a dataframe

Question

I need total count of negative values in a dataframe. i am able to get for an array but unable to find for DataFrame. for array i am using below code can any one suggest me how to get the count for below DataFrame.

sum(n<0 for n in numbers)

Below is my dataframe and expected result is 4

  a  b  c  d
   -3 -2 -1  1
   -2  2  3  4
    4  5  7  8

Answer 1

You can call .lt to compare the df against a scalar value and then call sum twice (this is because it sums row-wise first)

In [66]:
df.lt(0).sum()

Out[66]:
a    2
b    1
c    1
d    0
dtype: int64

Call sum again to sum the Series:

In [58]:
df.lt(0).sum().sum()

Out[58]:
4

You can also convert the boolean df to a 1-D array and call np.sum:

In [62]:
np.sum((df < 0).values.ravel())

Out[62]:
4

Timings

For a 30K row df:

In [70]:
%timeit sum(n < 0 for n in df.values.flatten())
%timeit df.lt(0).sum().sum()
%timeit np.sum((df < 0).values.ravel())

1 loops, best of 3: 405 ms per loop
100 loops, best of 3: 2.36 ms per loop
1000 loops, best of 3: 770 µs per loop

The np method wins easily here ~525x faster than the loop method and ~4x faster than the pure pandas method