用 mode() 填充 NAN 数据不起作用 -Pandas
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Filling NAN data with mode() doesn't work -Pandas
提问by Gabdu Gunnu
I have a data set in which there is a series known as Outlet_Sizewhich contain either of {'Medium', nan, 'High', 'Small'}around 2566 records are missing so I thought to fill it with mode() value so I wrote something like this :
我有一个数据集，其中有一个Outlet_Size包含{'Medium', nan, 'High', 'Small'}大约 2566 条记录的系列缺失，所以我想用 mode() 值填充它，所以我写了这样的东西：
train['Outlet_Size']=train['Outlet_Size'].fillna(train['Outlet_Size'].dropna().mode()]
But when I tried to find number of missing NaN record by command
但是当我试图通过命令查找丢失的 NaN 记录的数量时
sum(train['Outlet_Size'].isnull())
it is still showing 2566 NaN records.Why is it so ?
它仍然显示 2566 条 NaN 记录。为什么会这样？
Thank you for answers
谢谢你的回答
回答by EdChum
The problem here is that modereturns a series and this is causing the fillnato fail, if we look at a simple example:
这里的问题是mode返回一个系列，这导致fillna失败，如果我们看一个简单的例子：
In [194]:
df = pd.DataFrame({'a':['low','low',np.NaN,'medium','medium','medium','medium']})
df
Out[194]:
a
0 low
1 low
2 NaN
3 medium
4 medium
5 medium
6 medium
In [195]:
df['a'].fillna(df['a'].mode())
Out[195]:
0 low
1 low
2 NaN
3 medium
4 medium
5 medium
6 medium
Name: a, dtype: object
So you can see that it fails above, if we look at what modereturns:
所以你可以看到上面的失败，如果我们看一下mode返回的内容：
In [196]:
df['a'].mode()
Out[196]:
0 medium
dtype: object
it's a series albeit with a single row, so when you pass this to fillnait only fills the first row, so what you want is to get the scalar value by indexing into the Series:
它是一个系列，尽管只有一行，因此当您将fillna它传递给它时，它只会填充第一行，因此您想要的是通过索引到以下内容来获取标量值Series：
In [197]:
df['a'].fillna(df['a'].mode()[0])
Out[197]:
0 low
1 low
2 medium
3 medium
4 medium
5 medium
6 medium
Name: a, dtype: object
EDIT
编辑
Regarding whether dropnais required, no it isn't:
关于是否dropna需要，不，不是：
In [204]:
df = pd.DataFrame({'a':['low','low',np.NaN,'medium','medium','medium','medium',np.NaN,np.NaN,np.NaN,np.NaN]})
df['a'].mode()
Out[204]:
0 medium
dtype: object
You can see that NaNis ignored
你可以看到它NaN被忽略了
