Count occurances of a value in an entire dataframe

Question

For instance:

df = pd.DataFrame({A: ['Sally', 'Mark', 'John', 'Bridget', 'Anthony'], 'B': ['Tim', 'Sally', 'Sally', 'Bridget', 'Mark'], 'C': ['Matt', 'Jeff', 'Carl', 'Tim', 'Gus']})

How would I find the amount of times "Sally" appears in all of the columns combined? I'm looking for something more efficient than combining the amount of occurrences for each column.

Answer 1

So chain stack with value_counts

df.stack().value_counts()
Out[113]: 
Sally      3
Tim        2
Bridget    2
Mark       2
John       1
Carl       1
Matt       1
Gus        1
Jeff       1
Anthony    1
dtype: int64

Answer 2

Try this.

(df.values == 'Sally').sum()

However, assuming you need to do this for all the unique values, I would suggest using df.stack().value_counts() (as also suggested in @BENY's answer).

Data

import pandas as pd

df = pd.DataFrame({
    'A': ['Sally', 'Mark', 'John', 'Bridget', 'Anthony'], 
    'B': ['Tim', 'Sally', 'Sally', 'Bridget', 'Mark'], 
    'C': ['Matt', 'Jeff', 'Carl', 'Tim', 'Gus'],
})
# print(df)

#          A        B     C
# 0    Sally      Tim  Matt
# 1     Mark    Sally  Jeff
# 2     John    Sally  Carl
# 3  Bridget  Bridget   Tim
# 4  Anthony     Mark   Gus