缺失值填充
概述
“缺失值填充”节点用来将某些列出现的缺失值(如空值、指定的值)替换为均值或者中位数。
输入
参数 |
子参数 |
参数说明 |
---|---|---|
inputs |
dataframe |
inputs为字典类型,dataframe为pyspark中的DataFrame类型对象 |
输出
数据集
参数说明
参数 |
子参数 |
参数说明 |
---|---|---|
input_features_str |
- |
列名组成的字符串,例如: "column_a" "column_a,column_b" |
missing_value |
- |
类型为数值,表示该值为缺失值,将要被填充 |
strategy |
- |
填充策略,支持mean和median |
output_col_postfix |
- |
输出特征列的后缀 |
样例
inputs = { "dataframe": None # @input {"label":"dataframe","type":"DataFrame"} } params = { "inputs": inputs, "b_output_action": True, "outer_pipeline_stages": None, "input_features_str": "", # @param {"label":"input_features_str","type":"string","required":"true","helpTip":""} "missing_value": "", # @param {"label":"missing_value","type":"number","required":"false","range":"(none,none)","helpTip":""} "strategy": "mean", # @param {"label":"strategy","type":"enum","options":"mean,median","required":"true","helpTip":""} "output_col_postfix": "_impute" # @param {"label":"output_col_postfix","type":"string","required":"true","helpTip":""} } missing_value_impute____id___ = MLSMissingValueImpute(**params) missing_value_impute____id___.run() # @output {"label":"dataframe","name":"missing_value_impute____id___.get_outputs()['output_port_1']","type":"DataFrame"}