ใช้เมธอด Series.value_counts() เพื่อนับความถี่ของ itemsets เริ่มต้นด้วยการสร้าง DataFrame:
# Create DataFrame
dataFrame = pd.DataFrame({'Car': ['BMW', 'Mercedes', 'Lamborghini', 'Audi', 'Mercedes', 'Porsche', 'Lamborghini', 'BMW'],
'Place': ['Delhi', 'Hyderabad', 'Chandigarh', 'Bangalore', 'Hyderabad', 'Mumbai', 'Mumbai', 'Pune'],
'UnitsSold': [95, 80, 80, 75, 92, 90, 95, 50 ]})
นับความถี่คอลัมน์ Car ด้วย value_counts():
# counting frequency of column Car
count1 = dataFrame['Car'].value_counts()
print("\nCount in column Car")
print(count1)
นับคอลัมน์อื่นๆ แบบเดียวกัน โค้ดเต็มสำหรับนับความถี่ itemsets:
ตัวอย่าง
import pandas as pd
# Create DataFrame
dataFrame = pd.DataFrame({'Car': ['BMW', 'Mercedes', 'Lamborghini', 'Audi', 'Mercedes', 'Porsche', 'Lamborghini', 'BMW'],
'Place': ['Delhi', 'Hyderabad', 'Chandigarh', 'Bangalore', 'Hyderabad', 'Mumbai', 'Mumbai', 'Pune'],
'UnitsSold': [95, 80, 80, 75, 92, 90, 95, 50 ]})
print("Dataframe...")
print(dataFrame)
# counting frequency of column Car
count1 = dataFrame['Car'].value_counts()
print("\nCount in column Car")
print(count1)
# counting frequency of column Place
count2 = dataFrame['Place'].value_counts()
print("\nCount in column Place")
print(count2)
# counting frequency of column Car
count3 = dataFrame['UnitsSold'].value_counts()
print("\nCount in column UnitsSold")
print(count3)
ผลลัพธ์
Dataframe...
Car Place UnitsSold
0 BMW Delhi 95
1 Mercedes Hyderabad 80
2 Lamborghini Chandigarh 80
3 Audi Bangalore 75
4 Mercedes Hyderabad 92
5 Porsche Mumbai 90
6 Lamborghini Mumbai 95
7 BMW Pune 50
Count in column Car
BMW 2
Lamborghini 2
Mercedes 2
Audi 1
Porsche 1
Name: Car, dtype: int64
Count in column Place
Mumbai 2
Hyderabad 2
Chandigarh 1
Pune 1
Delhi 1
Bangalore 1
Name: Place, dtype: int64
Count in column UnitsSold
95 2
80 2
92 1
75 1
90 1
50 1
Name: UnitsSold, dtype: int64
