09 ,df 空值 : 空值处理,每列空值数,单列空值数,删除空值列,行,空值默认值

    技术2025-10-12  23

    1 ,每列有多少空值 : data.isnull().sum()

    代码 : if __name__ == '__main__': # 读文件 csv data = pd.read_csv("titanic_train.csv") # 空值统计 res = data.isnull().sum() print(res) ================================ PassengerId 0 Survived 0 Pclass 0 Name 0 Sex 0 Age 177 SibSp 0 Parch 0 Ticket 0 Fare 0 Cabin 687 Embarked 2

    2 ,Age 列有多少空值 : data[“Age”].isnull().sum()

    代码 : if __name__ == '__main__': # 读文件 csv data = pd.read_csv("titanic_train.csv") # 空值统计 res = data["Age"].isnull().sum() print(res) ========================= 177

    3 ,删除空值,行 : res = data.dropna()

    代码 : if __name__ == '__main__': # 读文件 csv data = pd.read_csv("titanic_train.csv") # 取出两列 print(data.shape) res = data.dropna() print(res.shape) ========================= (891, 12) (183, 12)

    4 ,删除空值,列 : res = data.dropna(axis=1)

    代码 : if __name__ == '__main__': # 读文件 csv data = pd.read_csv("titanic_train.csv") # 取出两列 print(data.shape) res = data.dropna(axis=1) print(res.shape) ================================== (891, 12) (891, 9)

    5 ,空值,全部填默认值 :data.fillna(0)

    代码 : 用 0 填充 if __name__ == '__main__': # 读文件 csv data = pd.read_csv("titanic_train.csv") # 空值统计 res = data.isnull().sum() print(res) # 空值用 0 补全 data02 = data.fillna(0) # 空值统计 res = data02.isnull().sum() print("=======================================") print(res) =========================================================== PassengerId 0 Survived 0 Pclass 0 Name 0 Sex 0 Age 177 SibSp 0 Parch 0 Ticket 0 Fare 0 Cabin 687 Embarked 2 dtype: int64 ======================================= PassengerId 0 Survived 0 Pclass 0 Name 0 Sex 0 Age 0 SibSp 0 Parch 0 Ticket 0 Fare 0 Cabin 0 Embarked 0 dtype: int64

    6 ,空值,指定列填值 :data[“Age”] = data[“Age”].fillna(0)

    代码 : if __name__ == '__main__': # 读文件 csv data = pd.read_csv("titanic_train.csv") # 空值统计 res = data.isnull().sum() print(res) # 空值用 0 补全,指定列 data["Age"] = data["Age"].fillna(0) # 空值统计 res = data.isnull().sum() print("=======================================") print(res) ======================================================= PassengerId 0 Survived 0 Pclass 0 Name 0 Sex 0 Age 177 SibSp 0 Parch 0 Ticket 0 Fare 0 Cabin 687 Embarked 2 dtype: int64 ======================================= PassengerId 0 Survived 0 Pclass 0 Name 0 Sex 0 Age 0 SibSp 0 Parch 0 Ticket 0 Fare 0 Cabin 687 Embarked 2 dtype: int64
    Processed: 0.011, SQL: 9