10: Apply TableVectorizer

This step used:

9: CallMethod 'assign'

This step was used by:

11: CallMethod 'groupby'

Where was this step created?

                
  File "/home/circleci/project/doc/conf.py", line 586, in <module>
    create_expression_report()
  File "/home/circleci/project/doc/expression_report.py", line 39, in create_expression_report
    vectorized_products = products.skb.apply(vectorizer, cols=s.all() - "basket_ID")

Estimator fitted in this step:

ApplyToFrame(cols=(all() - cols('basket_ID')),
             transformer=TableVectorizer(high_cardinality=MinHashEncoder(n_components=np.int64(9))))

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ApplyToFrame

iFitted

Parameters

	transformer	TableVectoriz...=np.int64(9)))
	cols	(all() - cols('basket_ID'))
	keep_original	False
	rename_columns	'{}'

transformer: TableVectorizer

TableVectorizer(high_cardinality=MinHashEncoder(n_components=np.int64(9)))

numeric

PassThrough

Parameters

datetime

DatetimeEncoder

Parameters

	resolution	'hour'
	add_weekday	False
	add_total_seconds	True
	add_day_of_year	False
	periodic_encoding	None

low_cardinality

OneHotEncoder

?Documentation for OneHotEncoder

Parameters

	categories	'auto'
	drop	'if_binary'
	sparse_output	False
	dtype	'float32'
	handle_unknown	'ignore'
	min_frequency	None
	max_categories	None
	feature_name_combiner	'concat'

high_cardinality

MinHashEncoder

Parameters

	n_components	np.int64(9)
	ngram_range	(2, ...)
	hashing	'fast'
	minmax_hash	False
	n_jobs	None

Output of this step

Column	Column name	dtype	Is sorted	Unique values	Mean	Std	Min	Median	Max
0	basket_ID	Int64DType	False	61241 (56.0%)	3.59e+04	2.24e+04	0	35,203	76,543
1	item_0	Float32DType	False	70 (< 0.1%)	-2.03e+09	1.54e+08	-2.15e+09	-2.12e+09	-1.04e+09
2	item_1	Float32DType	False	46 (< 0.1%)	-1.92e+09	2.63e+08	-2.14e+09	-2.06e+09	-1.09e+09
3	item_2	Float32DType	False	57 (< 0.1%)	-1.98e+09	1.85e+08	-2.14e+09	-2.09e+09	-3.95e+08
4	item_3	Float32DType	False	52 (< 0.1%)	-2.06e+09	8.25e+07	-2.15e+09	-2.07e+09	-8.27e+08
5	item_4	Float32DType	False	63 (< 0.1%)	-2.02e+09	6.26e+07	-2.15e+09	-2.05e+09	-1.08e+09
6	item_5	Float32DType	False	61 (< 0.1%)	-1.99e+09	2.14e+08	-2.14e+09	-2.06e+09	-8.93e+08
7	item_6	Float32DType	False	67 (< 0.1%)	-1.77e+09	3.82e+08	-2.14e+09	-1.99e+09	-9.01e+07
8	item_7	Float32DType	False	60 (< 0.1%)	-1.97e+09	1.38e+08	-2.14e+09	-2.00e+09	-1.20e+09
9	item_8	Float32DType	False	64 (< 0.1%)	-1.98e+09	1.06e+08	-2.15e+09	-2.02e+09	-9.20e+08
10	cash_price	Float32DType	False	1280 (1.2%)	672.	714.	0.00	499.	1.83e+04
11	make_0	Float32DType	False	337 (0.3%)	-1.48e+09	7.40e+08	-2.15e+09	-1.72e+09	1.30e+09
12	make_1	Float32DType	False	323 (0.3%)	-1.20e+09	8.17e+08	-2.15e+09	-5.10e+08	1.23e+09
13	make_2	Float32DType	False	301 (0.3%)	-1.65e+09	3.86e+08	-2.15e+09	-1.52e+09	1.39e+09
14	make_3	Float32DType	False	301 (0.3%)	-1.79e+09	6.28e+08	-2.15e+09	-1.97e+09	6.60e+08
15	make_4	Float32DType	False	316 (0.3%)	-1.30e+09	6.31e+08	-2.15e+09	-8.56e+08	1.75e+09
16	make_5	Float32DType	False	314 (0.3%)	-1.98e+09	2.89e+08	-2.15e+09	-2.00e+09	7.58e+08
17	make_6	Float32DType	False	264 (0.2%)	-1.30e+09	3.18e+08	-2.14e+09	-1.15e+09	7.29e+08
18	make_7	Float32DType	False	323 (0.3%)	-1.71e+09	6.09e+08	-2.15e+09	-1.87e+09	1.20e+09
19	make_8	Float32DType	False	307 (0.3%)	-1.63e+09	2.74e+08	-2.15e+09	-1.52e+09	1.61e+09
20	model_0	Float32DType	False	429 (0.4%)	-1.92e+09	2.97e+08	-2.15e+09	-2.07e+09	0.00
21	model_1	Float32DType	False	309 (0.3%)	-2.07e+09	2.47e+08	-2.15e+09	-2.14e+09	0.00
22	model_2	Float32DType	False	309 (0.3%)	-2.06e+09	2.32e+08	-2.15e+09	-2.12e+09	4.22e+07
23	model_3	Float32DType	False	311 (0.3%)	-2.03e+09	2.36e+08	-2.15e+09	-2.10e+09	0.00
24	model_4	Float32DType	False	386 (0.4%)	-2.00e+09	2.32e+08	-2.15e+09	-1.99e+09	0.00
25	model_5	Float32DType	False	301 (0.3%)	-2.08e+09	2.29e+08	-2.15e+09	-2.10e+09	8.95e+08
26	model_6	Float32DType	False	296 (0.3%)	-1.85e+09	4.02e+08	-2.15e+09	-2.08e+09	0.00
27	model_7	Float32DType	False	329 (0.3%)	-2.00e+09	2.39e+08	-2.15e+09	-2.09e+09	0.00
28	model_8	Float32DType	False	385 (0.4%)	-1.96e+09	2.66e+08	-2.15e+09	-2.07e+09	0.00
29	goods_code_0	Float32DType	False	247 (0.2%)	-1.94e+09	1.69e+08	-2.15e+09	-1.95e+09	-2.78e+08
30	goods_code_1	Float32DType	False	249 (0.2%)	-1.89e+09	2.08e+08	-2.15e+09	-1.93e+09	-1.39e+08
31	goods_code_2	Float32DType	False	264 (0.2%)	-1.88e+09	2.56e+08	-2.15e+09	-1.92e+09	-2.86e+08
32	goods_code_3	Float32DType	False	199 (0.2%)	-1.99e+09	2.02e+08	-2.15e+09	-2.10e+09	-1.09e+08
33	goods_code_4	Float32DType	False	259 (0.2%)	-1.95e+09	2.30e+08	-2.14e+09	-2.05e+09	-9.31e+08
34	goods_code_5	Float32DType	False	270 (0.2%)	-1.97e+09	2.05e+08	-2.13e+09	-2.05e+09	-3.79e+08
35	goods_code_6	Float32DType	False	282 (0.3%)	-1.91e+09	2.02e+08	-2.15e+09	-1.97e+09	1.05e+09
36	goods_code_7	Float32DType	False	295 (0.3%)	-1.89e+09	1.91e+08	-2.15e+09	-1.88e+09	-3.88e+08
37	goods_code_8	Float32DType	False	228 (0.2%)	-1.90e+09	2.39e+08	-2.14e+09	-1.93e+09	-3.42e+08
38	Nbr_of_prod_purchas	Float32DType	False	19 (< 0.1%)	1.05	0.426	1.00	1.00	40.0
39	total_price	Float32DType	False	1454 (1.3%)	704.	882.	0.00	519.	7.13e+04

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10: Apply TableVectorizer

This step used:

This step was used by:

Where was this step created?

Estimator fitted in this step:

Output of this step

basket_ID

item_0

item_1

item_2

item_3

item_4

item_5

item_6

item_7

item_8

cash_price

make_0

make_1

make_2

make_3

make_4

make_5

make_6

make_7

make_8

model_0

model_1

model_2

model_3

model_4

model_5

model_6

model_7

model_8

goods_code_0

goods_code_1

goods_code_2

goods_code_3

goods_code_4

goods_code_5

goods_code_6

goods_code_7

goods_code_8

Nbr_of_prod_purchas

total_price

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