Python编程语言学习：利用locals函数判断某个变量参数之前是否已经被定义/存在/出现

左手的ㄟ右手 2022-11-15 03:41 132阅读 0赞

**目录**

利用locals函数判断某个变量参数之前是否已经被定义/存在/出现

输出结果

实现代码

--------------------

# 利用locals函数判断某个变量参数之前是否已经被定义/存在/出现 #

## 输出结果 ##

<class 'pandas.core.frame.DataFrame'>
    RangeIndex: 768 entries, 0 to 767
    Data columns (total 9 columns):
     #   Column                    Non-Null Count  Dtype  
    ---  ------                    --------------  -----  
     0   Pregnancies               768 non-null    int64  
     1   Glucose                   768 non-null    int64  
     2   BloodPressure             768 non-null    int64  
     3   SkinThickness             768 non-null    int64  
     4   Insulin                   768 non-null    int64  
     5   BMI                       768 non-null    float64
     6   DiabetesPedigreeFunction  768 non-null    float64
     7   Age                       768 non-null    int64  
     8   Outcome                   768 non-null    int64  
    dtypes: float64(2), int64(7)
    memory usage: 54.1 KB
    None
    dict_keys(['__name__', '__doc__', '__package__', '__loader__', '__spec__', '__annotations__', '__builtins__', '__file__', '__cached__', 'plt', 'pd', 'data_frame', 'col_label', 'cols_other', 'data_X', 'data_y_label_μ'])
    data_X
    data_y_label_μ
    data_dall02
    data_dall02 not in locals().keys()!

## 实现代码 ##

# Python编程语言学习：利用locals函数判断某个变量参数之前是否已经被定义/存在/出现
    import pandas as pd
    
    data_frame=pd.read_csv('data_csv_xls\diabetes\diabetes.csv')
    
    col_label='Outcome'
    cols_other=['Pregnancies','Glucose','BloodPressure','SkinThickness','BMI']
    data_X=data_frame[cols_other]
    data_y_label_μ=data_frame[col_label]
    
    
    
    # 判断某个参数之前是否已经被定义/存在/出现
    print(locals().keys())
    param_lists=['data_X','data_y_label_μ','data_dall02']
    for param in param_lists:
        print(param)
        if param not in locals().keys():
            print('%s not in locals().keys()!'%param)