pandas Sklearn 将字符串类标签更改为 int
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Sklearn changing string class label to int
提问by Lukasz
I have a pandas dataframe and I'm trying to change the values in a given column which are represented by strings into integers. For instance:
我有一个 Pandas 数据框，我正在尝试将给定列中的值更改为由字符串表示的整数。例如：
df = index fruit quantity price
0 apple 5 0.99
1 apple 2 0.99
2 orange 4 0.89
4 banana 1 1.64
...
10023 kiwi 10 0.92
I would like it to look at:
我想看看：
df = index fruit quantity price
0 1 5 0.99
1 1 2 0.99
2 2 4 0.89
4 3 1 1.64
...
10023 5 10 0.92
I can do this using
我可以使用
df["fruit"] = df["fruit"].map({"apple": 1, "orange": 2,...})
which works if I have a small list to change, but I'm looking at a column with over 500 different labels. Is there any way of changing this from a stringto a an int?
如果我有一个要更改的小列表，这会起作用，但我正在查看具有 500 多个不同标签的列。有什么办法可以将其从 astring更改为 anint吗？
回答by jezrael
Use factorizeand then convert to categoricalif necessary:
使用factorize然后categorical在必要时转换为：
df.fruit = pd.factorize(df.fruit)[0]
print (df)
fruit quantity price
0 0 5 0.99
1 0 2 0.99
2 1 4 0.89
3 2 1 1.64
4 3 10 0.92
df.fruit = pd.Categorical(pd.factorize(df.fruit)[0])
print (df)
fruit quantity price
0 0 5 0.99
1 0 2 0.99
2 1 4 0.89
3 2 1 1.64
4 3 10 0.92
print (df.dtypes)
fruit category
quantity int64
price float64
dtype: object
Also if need count from 1:
此外，如果需要从1：
df.fruit = pd.Categorical(pd.factorize(df.fruit)[0] + 1)
print (df)
fruit quantity price
0 1 5 0.99
1 1 2 0.99
2 2 4 0.89
3 3 1 1.64
4 4 10 0.92
回答by MaxU
you can use factorizemethod:
您可以使用分解方法：
In [13]: df['fruit'] = pd.factorize(df['fruit'])[0].astype(np.uint16)
In [14]: df
Out[14]:
index fruit quantity price
0 0 0 5 0.99
1 1 0 2 0.99
2 2 1 4 0.89
3 4 2 1 1.64
4 10023 3 10 0.92
In [15]: df.dtypes
Out[15]:
index int64
fruit uint16
quantity int64
price float64
dtype: object
alternatively you can do it this way:
或者你可以这样做：
In [21]: df['fruit'] = df.fruit.astype('category').cat.codes
In [22]: df
Out[22]:
index fruit quantity price
0 0 0 5 0.99
1 1 0 2 0.99
2 2 3 4 0.89
3 4 1 1 1.64
4 10023 2 10 0.92
In [23]: df.dtypes
Out[23]:
index int64
fruit int8
quantity int64
price float64
dtype: object
