pandas 使用loc赋值后，值的类型从int变成了float，这是为什么？


def NowTime(df: pd.DataFrame, p=''):
    now13 = int(time.time() * 1000)
    now = int(now13 / 1000)
    now_F = time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(now13 / 1000))
    now_F_T = time.strftime('%Y-%m-%dT%H:%M:%S', time.localtime(now13 / 1000))
    now_F_TZ = time.strftime('%Y-%m-%dT%H:%M:%SZ', time.localtime(now13 / 1000))
    resultDF = pd.DataFrame()
    print(type(now13))
    resultDF.loc[0, 'Now'] = now
    resultDF.loc[0, 'Now13'] = now13
    resultDF.loc[0, 'Now_F'] = now_F
    resultDF.loc[0, 'now_F_T'] = now_F_T
    resultDF.loc[0, 'now_F_TZ'] = now_F_TZ

    return resultDF

if __name__ == '__main__':
    df=pd.DataFrame()
    xx=NowTime(df)
    print(xx.dtypes)

运行结果

<class 'int'>
Now         float64
Now13       float64
Now_F        object
now_F_T      object
now_F_TZ     object
dtype: object

因为你原始df是个空值， pandas在处理缺失值上，拥有一个自己的处理及转化逻辑 会将int转float的，可以去看文档

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