How to get the number of times a piece if word is inside a particular column in pandas?

Question

I\'ll try to use a simple example to describe my problem.

I have a csv file with many columns. One of this columns\' header is \"names\".

In this column \"n

Answer 1

You can use pandas.Series.str.count to count the number of times in each row a pattern is encountered.

df.names.str.count('John').sum()

3

In this example, it matches OP's output. However, this would produce different results if John appeared more than once in one row. Suppose we had this df instead:

df

                 names
0            John John
1        John M John M
2  Mike John Mike John
3        Audrey Audrey
4        Andrew Andrew

Then my answer produces

df.names.str.count('John').sum()

6

While Wen's answer produces

df.names.str.contains('John').sum()

3

Answer 2

Using str.contains

df.Name.str.contains('John').sum()
Out[246]: 3

Or we using list and map with in

sum(list(map(lambda x : 'John' in x,df.Name)))
Out[248]: 3