如何计算 Pandas DataFrame 中项集的频率
使用该方法计算项集的频率。首先，让我们创建一个DataFrame-Series.value_counts()
# 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 ]})使用value_counts()方法计算列车的频率-
# counting frequency of column Car
count1 = dataFrame['Car'].value_counts()
print("\nCount in column Car")
print(count1)同理，统计其他列出现的频率。以下是计算PandasDataFrame中项集频率的完整代码-
示例
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)输出结果这将产生以下输出-
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