如何计算特定名称出现在 Pandas 数据框列中的次数？

Question

I have a column of names. I need to get a count of how many times a specific name appears in that column.

Column:
Dave
John
John
Thanos
Bob

I need something like:

[in] df['Column'].count_name('John')
[out] 2

Using value_counts() doesn't work because there are thousands of names in the column, and many of them only appear once. I'm sorry if this question has been asked/answered before, but I haven't been able to figure out a way to search for it that doesn't just give me an answer telling me to use value_counts() .

Thanks!

Answer 1

Just for speed up using numpy.count_nonzero

import numpy as np 

np.count_nonzero(df['Column']=='John')
Out[186]: 2

Answer 2

Try using this:

df['Column:'].value_counts()['John']

In [6]: %timeit df[0].value_counts()['John']
1000 loops, best of 3: 548 µs per loop

In [7]: %timeit df[0].eq('John').sum()
The slowest run took 8.19 times longer than the fastest. This could mean that an intermediate result is being cached.
1000 loops, best of 3: 311 µs per loop

In [8]: %timeit np.count_nonzero(df[0]=='John')
10000 loops, best of 3: 162 µs per loop

EDIT: Fastest is using np.count_nonzero...

Apparently, using eq() proves to be faster than using value_counts() which is obvious as value_counts calculates counts for all values whereas .eq() calculates for only given value..