Python:endog 已评估为具有多列的数组 [英] Python: endog has evaluated to an array with multiple columns

问题描述

我正在尝试运行泊松模型，如下所示:

I'm trying to run a Poisson model, like this:

poisson_model_xg = smf.glm(formula="xG ~ home + team + opponent", data=xg_model_data, 
                        family=sm.families.Poisson()).fit()

我收到以下错误:

ValueError:endog 已评估为包含多个列的数组具有形状 (760, 9).当变量转换为 endg 时会发生这种情况是非数字的(例如 bool 或 str).

ValueError: endog has evaluated to an array with multiple columns that has shape (760, 9). This occurs when the variable converted to endog is non-numeric (e.g., bool or str).

但我不知道这是什么意思，因为我所有的数据框都是数字:

But I can't figure out what does it mean, since all my dataframe is numeric:

xg_model_data.apply(lambda s: pd.to_numeric(s, errors='coerce').notnull().all())
Out[10]: 
goals       True
xG          True
team        True
opponent    True
home        True
dtype: bool

推荐答案

已解决.技巧不在于内容类型，而在于列类型:

Solved. The trick was not in content type, but in columns type:

xg_model_data.info()
<class 'pandas.core.frame.DataFrame'>
Int64Index: 760 entries, 0 to 759
Data columns (total 5 columns):
 #   Column    Non-Null Count  Dtype 
---  ------    --------------  ----- 
 0   goals     760 non-null    object
 1   xG        760 non-null    object
 2   team      760 non-null    object
 3   opponent  760 non-null    object
 4   home      760 non-null    object
dtypes: object(5)
memory usage: 55.6+ KB

在所需的列上应用 pd.to_numeric() 后，数据框如下所示，并且泊松能够处理.

After I applied pd.to_numeric() on desired columns, the dataframe looks like the following, and Poisson is able to process.

xg_model_data.info()
<class 'pandas.core.frame.DataFrame'>
Int64Index: 760 entries, 0 to 759
Data columns (total 5 columns):
 #   Column    Non-Null Count  Dtype  
---  ------    --------------  -----  
 0   goals     760 non-null    int64  
 1   xG        760 non-null    float64
 2   team      760 non-null    object 
 3   opponent  760 non-null    object 
 4   home      760 non-null    int64  
dtypes: float64(1), int64(2), object(2)
memory usage: 55.6+ KB

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