无法将 nan 转换为 int(但没有 nan) [英] cannot convert nan to int (but there are no nans)

问题描述

我有一个包含一列浮点数的数据框，我想将其转换为 int:

I have a dataframe with a column of floats that I want to convert to int:

> df['VEHICLE_ID'].head()
0    8659366.0
1    8659368.0
2    8652175.0
3    8652174.0
4    8651488.0

理论上我应该可以使用:

In theory I should just be able to use:

> df['VEHICLE_ID'] = df['VEHICLE_ID'].astype(int)

但我明白了:

Output: ValueError: Cannot convert NA to integer

但我很确定这个系列中没有 NaN:

But I am pretty sure that there are no NaNs in this series:

> df['VEHICLE_ID'].fillna(999,inplace=True)
> df[df['VEHICLE_ID'] == 999]
> Output: Empty DataFrame
Columns: [VEHICLE_ID]
Index: []

怎么回事?

推荐答案

基本上错误是告诉你你的 NaN 值，我将说明为什么你的尝试没有揭示这一点:

Basically the error is telling you that you NaN values and I will show why your attempts didn't reveal this:

In [7]:
# setup some data
df = pd.DataFrame({'a':[1.0, np.NaN, 3.0, 4.0]})
df
Out[7]:
     a
0  1.0
1  NaN
2  3.0
3  4.0

现在尝试投射:

df['a'].astype(int)

这引发了:

ValueError: Cannot convert NA to integer

但后来你尝试了这样的事情:

but then you tried something like this:

In [5]:
for index, row in df['a'].iteritems():
    if row == np.NaN:
        print('index:', index, 'isnull')

this 什么也没打印，但是 NaN 不能像这样使用相等来求值，事实上它有一个特殊的属性，当与自身比较时它会返回 False:>

this printed nothing, but NaN cannot be evaluated like this using equality, in fact it has a special property that it will return False when comparing against itself:

In [6]:
for index, row in df['a'].iteritems():
    if row != row:
        print('index:', index, 'isnull')

index: 1 isnull

现在它打印行，您应该使用 isnull 以提高可读性:

now it prints the row, you should use isnull for readability:

In [9]:
for index, row in df['a'].iteritems():
    if pd.isnull(row):
        print('index:', index, 'isnull')

index: 1 isnull

那怎么办?我们可以删除行:df.dropna(subset='a')，或者我们可以使用 fillna 替换:

So what to do? We can drop the rows: df.dropna(subset='a'), or we can replace using fillna:

In [8]:
df['a'].fillna(0).astype(int)

Out[8]:
0    1
1    0
2    3
3    4
Name: a, dtype: int32

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