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
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
- <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()!
- 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)
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