pandas 无法将 nan 转换为 int（但没有 nan）
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cannot convert nan to int (but there are no nans)
提问by ale19
I have a dataframe with a column of floats that I want to convert to int:
我有一个包含一列浮点数的数据框，我想将其转换为 int：
> df['VEHICLE_ID'].head()
0 8659366.0
1 8659368.0
2 8652175.0
3 8652174.0
4 8651488.0
In theory I should just be able to use:
从理论上讲，我应该能够使用：
> df['VEHICLE_ID'] = df['VEHICLE_ID'].astype(int)
But I get:
但我得到：
Output: ValueError: Cannot convert NA to integer
But I am pretty sure that there are no NaNs in this series:
但我很确定这个系列中没有 NaN：
> df['VEHICLE_ID'].fillna(999,inplace=True)
> df[df['VEHICLE_ID'] == 999]
> Output: Empty DataFrame
Columns: [VEHICLE_ID]
Index: []
What's going on?
这是怎么回事？
回答by EdChum
Basically the error is telling you that you NaNvalues and I will show why your attempts didn't reveal this:
基本上错误是告诉你你NaN重视，我将说明为什么你的尝试没有揭示这一点：
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
now try to cast:
现在尝试投射：
df['a'].astype(int)
this raises:
这提出：
ValueError: Cannot convert NA to integer
but then you tried something like this:
但后来你尝试了这样的事情：
In [5]:
for index, row in df['a'].iteritems():
if row == np.NaN:
print('index:', index, 'isnull')
this printed nothing, but NaNcannot be evaluated like this using equality, in fact it has a special property that it will return Falsewhen comparing against itself:
this 什么都不打印，但NaN不能像这样使用相等进行评估，实际上它有一个特殊的属性，False当与自身比较时它将返回：
In [6]:
for index, row in df['a'].iteritems():
if row != row:
print('index:', index, 'isnull')
index: 1 isnull
now it prints the row, you should use isnullfor readability:
现在它打印行，您应该使用isnull可读性：
In [9]:
for index, row in df['a'].iteritems():
if pd.isnull(row):
print('index:', index, 'isnull')
index: 1 isnull
So what to do? We can drop the rows: df.dropna(subset='a'), or we can replace using fillna:
那么该怎么办？我们可以删除行：df.dropna(subset='a')，或者我们可以使用fillna：
In [8]:
df['a'].fillna(0).astype(int)
Out[8]:
0 1
1 0
2 3
3 4
Name: a, dtype: int32
