i wonder how i can transform this block of code, (that use a pandas dataframe in order to calculate new features);
into tensorflow dataset that has the raw data of lst in it but using transformations in order to calculate the new columns
lst = [[1,2,3], [4,5,6],[7,8,9]]
df = pd.DataFrame(lst, columns =['field1', 'field2','field3'])
df
output:
field1 field2 field3
1 2 3
4 5 6
7 8 9
df['max'] = df[['field1', 'field2', 'field3']].max(numeric_only=True, axis=1)
df['mean'] = df[['field1', 'field2', 'field3']].mean(numeric_only=True, axis=1)
question from:
https://stackoverflow.com/questions/65916893/how-to-create-new-columns-like-tensorflow-dataset-as-same-as-pandas-dataframe 与恶龙缠斗过久,自身亦成为恶龙;凝视深渊过久,深渊将回以凝视…