参见英文答案 > Convert Pandas column containing NaNs to dtype `int`11个
我在转换包含字符串格式(类型:str)和NaN(类型:float64)的2位数字的列时遇到问题.我想以这种方式获得一个新列:NaN,其中有NaN和整数,其中有两个数字的字符串格式.
举个例子:我想从列YearBirth1获取列Yearbirth2,如下所示:
YearBirth1 #numbers here are formatted as strings: type(YearBirth1[0])=str
34 # and NaN are floats: type(YearBirth1[2])=float64.
76
Nan
09
Nan
91
YearBirth2 #numbers here are formatted as integers: type(YearBirth2[0])=int
34 #NaN can remain floats as they were.
76
Nan
9
Nan
91
我试过这个:
csv['YearBirth2'] = (csv['YearBirth1']).astype(int)
正如我所料,我得到了这个错误:
ValueError: cannot convert float NaN to integer
所以我尝试了这个:
csv['YearBirth2'] = (csv['YearBirth1']!=NaN).astype(int)
并得到这个错误:
NameError: name 'NaN' is not defined
最后我试过这个:
csv['YearBirth2'] = (csv['YearBirth1']!='NaN').astype(int)
没有错误,但当我检查列YearBirth2时,这是结果:
YearBirth2:
1
1
1
1
1
1
非常糟糕..我认为这个想法是对的,但是有一个问题让Python能够理解我对NaN的意思..或者我尝试的方法可能是错的..
我也使用了pd.to_numeric()方法,但这种方式我获得了浮点数,而不是整数.
有什么帮助?!
谢谢大家!
P.S:csv是我的DataFrame的名称;
对不起,如果我不太清楚,我正在改进英语!
解决方法:
您可以使用to_numeric,但不可能使用NaN值获取int – 它们始终转换为float:see na type promotions.
df['YearBirth2'] = pd.to_numeric(df.YearBirth1, errors='coerce')
print (df)
YearBirth1 YearBirth2
0 34 34.0
1 76 76.0
2 Nan NaN
3 09 9.0
4 Nan NaN
5 91 91.0
标签:python,pandas,nan,type-conversion
来源: https://codeday.me/bug/0828/1755321.html