我想根據熊貓中的其他列填充缺失值。這是我的表：Gender MarriedMale YesMale YesFemale NoFemale NoMale NaNFemale NaN如果性別為男性，我將填充已婚字段的缺失值 -> 已婚為是，否則已婚為否：df['Married'].fillna(df[df['Married'].isnull()].apply(lambda x: 'Yes' if (df[df['Married'].isnull()]['Gender'] is 'Male') else 'No', axis=1), inplace=True)但它失敗了，我嘗試了很多方法，但沒有得到預期的結果。我希望收到你們所有人。
1 回答
慕尼黑8549860
TA貢獻1818條經驗 獲得超11個贊
我相信你需要map有dictionary只在過濾行：
mask = df['Married'].isnull()
df.loc[mask, 'Married'] = df.loc[mask, 'Gender'].map({'Male':'Yes', 'Female':'No'})
print (df)
Gender Married
0 Male Yes
1 Male Yes
2 Female No
3 Female No
4 Male Yes
5 Female No
另一個解決方案numpy.where：
mask = df['Married'].isnull()
df.loc[mask, 'Married'] = np.where(df.loc[mask, 'Gender'] == 'Male', 'Yes','No')
print (df)
Gender Married
0 Male Yes
1 Male Yes
2 Female No
3 Female No
4 Male Yes
5 Female No
fillna映射的另一個解決方案Series：
df['Married'] = df['Married'].fillna(df['Gender'].map({'Male':'Yes', 'Female':'No'}))
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