Вот несколько способов достижения этой задачи:

Метод 1: использование функции value_counts()

import pandas as pd
# Assuming your DataFrame is called 'df'
column_counts = {}
for column in df.columns:
    column_counts[column] = df[column].value_counts()
# Accessing the count of each value in a specific column
print(column_counts['column_name'])

Метод 2: использование groupby()и size()

import pandas as pd
# Assuming your DataFrame is called 'df'
column_counts = df.groupby(df.columns.tolist()).size()
# Accessing the count of each value in a specific column
print(column_counts['column_name'])

Метод 3: использование apply()и value_counts()

import pandas as pd
# Assuming your DataFrame is called 'df'
column_counts = df.apply(pd.value_counts)
# Accessing the count of each value in a specific column
print(column_counts['column_name'])