Python - 从 Pandas DataFrame 中删除重复值

若要从 Pandas DataFrame 中删除重复值，请使用 drop_duplicates() 方法。首先，创建一个有 3 列的 DataFrame −

dataFrame = pd.DataFrame({'Car': ['BMW', 'Mercedes', 'Lamborghini', 'BMW', 'Mercedes', 'Porsche'],'Place': ['Delhi', 'Hyderabad', 'Chandigarh', 'Delhi', 'Hyderabad', 'Mumbai'],'UnitsSold': [95, 70, 80, 95, 70, 90]})

删除重复值 −

dataFrame = dataFrame.drop_duplicates()

范例

以下是完整的代码 −

import pandas as pd

# Create DataFrame
dataFrame = pd.DataFrame({'Car': ['BMW', 'Mercedes', 'Lamborghini', 'BMW', 'Mercedes', 'Porsche'],'Place': ['Delhi', 'Hyderabad', 'Chandigarh', 'Delhi', 'Hyderabad', 'Mumbai'], 'UnitsSold': [95, 70, 80, 95, 70, 90]})

print"Dataframe...\n", dataFrame

# counting frequency of column Car
count = dataFrame['Car'].value_counts()
print"\nCount in column Car"
print(count)

# removing duplicates
dataFrame = dataFrame.drop_duplicates()
print"\nUpdated DataFrame after removing duplicates...\n",dataFrame

# counting frequency of column Car after removing duplicates
count = dataFrame['Car'].value_counts()
print"\nCount in column Car"
print(count)

输出

将产生以下输出 −

Dataframe...
           Car        Place   UnitsSold
0          BMW        Delhi         95
1     Mercedes    Hyderabad         70
2  Lamborghini   Chandigarh         80
3          BMW        Delhi         95
4     Mercedes    Hyderabad         70
5      Porsche       Mumbai         90

Count in column Car
BMW            2
Mercedes       2
Porsche        1
Lamborghini    1
Name: Car, dtype: int64

Updated DataFrame after removing duplicates...
           Car         Place   UnitsSold
0          BMW        Delhi         95
1     Mercedes    Hyderabad         70
2  Lamborghini   Chandigarh         80
5      Porsche       Mumbai         90

Count in column Car
BMW           1
Porsche       1
Lamborghini   1
Mercedes      1
Name: Car, dtype: int64

更新于：2021-09-16

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