双子男和巨蟹女object数据类型
1 object数据类型是dataframe中特殊的数据类型，当某⼀列出现数字、字符串、特殊字符和时间格式两种及以上时，就会出现object类型，即便把不同类型的拆分开，仍然是object类型.
如下replace()函数改变数据类型后,⽤astype()函数再转化⼀次才能将object格式转化，但有的时候不⽤.
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print(train.info())
train['repay_date'] = train['repay_date'].replace("\\N",'2020-01-01')
train['repay_date'] = pd.to_datetime(train['repay_date'])
train['repay_amt'] = train['repay_amt'].replace("\\N",0)
train['repay_amt'] = train['repay_amt'].astype(float)
print(train.info())
# <class 'frame.DataFrame'>
# RangeIndex: 1000000 entries, 0 to 999999
# Data columns (total 7 columns):
鸡树# ur_id 1000000 non-null int64
# listing_id 1000000 non-null int64
# due_date 1000000 non-null datetime64[ns]
# due_amt 1000000 non-null float64
# repay_date 1000000 non-null object
# repay_amt 1000000 non-null object
# order_id 1000000 non-null int64
# dtypes: datetime64[ns](1), float64(1), int64(3), object(2)
# memory usage: 53.4+ MB
# None
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# <class 'frame.DataFrame'>
# RangeIndex: 1000000 entries, 0 to 999999电脑如何升级系统
# Data columns (total 7 columns):
# ur_id 1000000 non-null int64
# listing_id 1000000 non-null int64胆小的我
# due_date 1000000 non-null datetime64[ns]
# due_amt 1000000 non-null float64
# repay_date 1000000 non-null datetime64[ns]
# repay_amt 1000000 non-null float64
# order_id 1000000 non-null int64
# dtypes: datetime64[ns](2), float64(2), int64(3)
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# memory usage: 53.4 MB
# None
