获取分类变量的类别列表（Python Pandas）
声明：本页面是StackOverFlow热门问题的中英对照翻译，遵循CC BY-SA 4.0协议，如果您需要使用它，必须同样遵循CC BY-SA许可，注明原文地址和作者信息，同时你必须将它归于原作者（不是我）：StackOverFlow
原文地址: http://stackoverflow.com/questions/52404971/
Warning: these are provided under cc-by-sa 4.0 license. You are free to use/share it, But you must attribute it to the original authors (not me):
StackOverFlow
Get a list of categories of categorical variable (Python Pandas)
提问by Mona
I have a pandas DataFrame with a column representing a categorical variable. How can I get a list of the categories? I tried .values on the column but that does not return the unique levels.
我有一个 Pandas DataFrame，其中有一列表示分类变量。如何获取类别列表？我在列上尝试了 .values ，但这不会返回唯一级别。
Thanks!
谢谢！
回答by jezrael
I believe need Series.cat.categoriesor unique:
我相信需要Series.cat.categories或unique：
np.random.seed(1245)
a = ['No', 'Yes', 'Maybe']
df = pd.DataFrame(np.random.choice(a, size=(10, 3)), columns=['Col1','Col2','Col3'])
df['Col1'] = pd.Categorical(df['Col1'])
print (df.dtypes)
Col1 category
Col2 object
Col3 object
dtype: object
print (df['Col1'].cat.categories)
Index(['Maybe', 'No', 'Yes'], dtype='object')
print (df['Col2'].unique())
['Yes' 'Maybe' 'No']
print (df['Col1'].unique())
[Maybe, No, Yes]
Categories (3, object): [Maybe, No, Yes]
回答by Anand Mohan
You can also use value_counts(), but it only works when you use it with a column name, with which you'll get the counts of each category as well. Example:
您也可以使用 value_counts()，但它仅在您将它与列名一起使用时才有效，您还将获得每个类别的计数。例子：
dataframe['Columnn name'].value_counts()
数据框['列名称'].value_counts()
Alternatively, if you want the total count of categories in a variable, you can do this,
或者，如果您想要变量中类别的总数，您可以这样做，
dataframe['Columnn name'].value_counts().count()
数据框['列名称'].value_counts().count()
回答by SABARISH KAVALA
Try executing the below code.
尝试执行以下代码。
List_Of_Categories_In_Column=list(df['Categorical Column Name'].value_counts().index)
List_Of_Categories_In_Column=list(df['Categorical Column Name'].value_counts().index)
