如何在pandas中将一个值替换为NaN？

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如何在pandas中将一个值替换为NaN？

我是pandas的新手，我正在尝试将csv文件加载到Dataframe中。我的数据中有缺失值，用?表示，我想将其替换为标准的缺失值NaN。请帮助我。我尝试阅读了Pandas文档，但是不太懂。

def readData(filename):
    DataLabels = ["age", "workclass", "fnlwgt", "education", "education-num", "marital-status",
               "occupation", "relationship", "race", "sex", "capital-gain",
               "capital-loss", "hours-per-week", "native-country", "class"] 
    # ==== 试图使用na_values将?替换为NaN
    rawfile = pd.read_csv(filename, header=None, names=DataLabels, na_values=["?"])
    age = rawfile["age"]
    print(age)
    print(rawfile[25:40])
    #========试图替换?
    rawfile.replace("?", "NaN")
    print(rawfile[25:40])
    return rawfile

数据：

[adult.data](http://archive.ics.uci.edu/ml/machine-learning-databases/adult/)

    age   workclass  fnlwgt      education  education-num       marital-status        occupation    relationship                 race    sex  capital-gain  capital-loss  hours-per-week  native-country   class
25   56   Local-gov  216851      Bachelors             13   Married-civ-spouse      Tech-support         Husband                White   Male             0             0              40   United-States    >50K
26   19     Private  168294        HS-grad              9        Never-married      Craft-repair       Own-child                White   Male             0             0              40   United-States   <=50K
27   54           ?  180211   Some-college             10   Married-civ-spouse                 ?         Husband   Asian-Pac-Islander   Male             0             0              60           South    >50K
28   39     Private  367260        HS-grad              9             Divorced   Exec-managerial   Not-in-family                White   Male             0             0              80   United-States   <=50K
29   49     Private  193366        HS-grad              9   Married-civ-spouse      Craft-repair         Husband                White   Male             0             0              40   United-States   <=50K

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