gimi9 Pandas Profiling

Dataset statistics

Number of variables	13
Number of observations	100
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	10.5 KiB
Average record size in memory	107.3 B

Variable types

Numeric	1
Categorical	6
Boolean	6

Dataset

Description	Sample
Author	컨슈머인사이트
URL	https://www.bigdata-culture.kr/bigdata/user/data_market/detail.do?id=53e6be30-eb98-11ec-a6e8-cdf27550dc0d

Alerts

`examin_ym` has constant value ""	Constant
`marn_sports_supli_prchs_at` has constant value ""	Constant
`answrr_oc_area_nm` is highly overall correlated with `climd_camping_fshng_supli_prchs_at`	High correlation
`climd_camping_fshng_supli_prchs_at` is highly overall correlated with `answrr_oc_area_nm`	High correlation
`bal_supli_prchs_at` is highly imbalanced (75.8%)	Imbalance
`climd_camping_fshng_supli_prchs_at` is highly imbalanced (85.9%)	Imbalance
`bcycl_wrkot_yoga_supli_prchs_at` is highly imbalanced (71.4%)	Imbalance
`golf_supli_prchs_at` is highly imbalanced (91.9%)	Imbalance
`wnt_sports_supli_prchs_at` is highly imbalanced (91.9%)	Imbalance
`respond_id` has unique values	Unique

Reproduction

Analysis started	2023-12-10 10:02:16.288826
Analysis finished	2023-12-10 10:02:18.300408
Duration	2.01 seconds
Software version	ydata-profiling vv4.5.1
Download configuration	config.json

respond_id
Real number (ℝ)

UNIQUE

Distinct	100
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	103660.11

Minimum	199
Maximum	3242878
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.0 KiB

Quantile statistics

Minimum	199
5-th percentile	725.1
Q1	3399.75
median	5873.5
Q3	10576.25
95-th percentile	14898.95
Maximum	3242878
Range	3242679
Interquartile range (IQR)	7176.5

Descriptive statistics

Standard deviation	554781.24
Coefficient of variation (CV)	5.351926
Kurtosis	29.89392
Mean	103660.11
Median Absolute Deviation (MAD)	3239.5
Skewness	5.5941265
Sum	10366011
Variance	3.0778222 × 10¹¹
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
199	1	1.0%
7094	1	1.0%
9592	1	1.0%
9495	1	1.0%
8817	1	1.0%
8717	1	1.0%
8671	1	1.0%
8573	1	1.0%
8370	1	1.0%
7351	1	1.0%
Other values (90)	90	90.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
199	1	1.0%
354	1	1.0%
497	1	1.0%
547	1	1.0%
689	1	1.0%
727	1	1.0%
982	1	1.0%
988	1	1.0%
1267	1	1.0%
1467	1	1.0%

Value	Count	Frequency (%)
3242878	1	1.0%
3242247	1	1.0%
3242000	1	1.0%
15661	1	1.0%
15392	1	1.0%
14873	1	1.0%
14840	1	1.0%
14550	1	1.0%
14227	1	1.0%
14152	1	1.0%

examin_ym
Categorical

CONSTANT

Distinct	1
Distinct (%)	1.0%
Missing	0
Missing (%)	0.0%
Memory size	932.0 B

202204	100

Length

Max length	6
Median length	6
Mean length	6
Min length	6

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	202204
2nd row	202204
3rd row	202204
4th row	202204
5th row	202204

Common Values

Value	Count	Frequency (%)
202204	100	100.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
202204	100	100.0%

sexdstn_flag_cd
Categorical

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	932.0 B

M	60
F	40

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	F
2nd row	F
3rd row	M
4th row	M
5th row	M

Common Values

Value	Count	Frequency (%)
M	60	60.0%
F	40	40.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
m	60	60.0%
f	40	40.0%

agrde_flag_nm
Categorical

Distinct	4
Distinct (%)	4.0%
Missing	0
Missing (%)	0.0%
Memory size	932.0 B

40대	31
50대	29
60대	26
30대	14

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	60대
2nd row	40대
3rd row	60대
4th row	60대
5th row	60대

Common Values

Value	Count	Frequency (%)
40대	31	31.0%
50대	29	29.0%
60대	26	26.0%
30대	14	14.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
40대	31	31.0%
50대	29	29.0%
60대	26	26.0%
30대	14	14.0%

answrr_oc_area_nm
Categorical

HIGH CORRELATION

Distinct	15
Distinct (%)	15.0%
Missing	0
Missing (%)	0.0%
Memory size	932.0 B

서울특별시	32
경기도	23
인천광역시	12
부산광역시	6
광주광역시	5
Other values (10)	22

Length

Max length	12
Median length	5
Mean length	4.56
Min length	3

Unique

Unique	3 ?
Unique (%)	3.0%

Sample

1st row	서울특별시
2nd row	부산광역시
3rd row	서울특별시
4th row	전라남도
5th row	충청북도

Common Values

Value	Count	Frequency (%)
서울특별시	32	32.0%
경기도	23	23.0%
인천광역시	12	12.0%
부산광역시	6	6.0%
광주광역시	5	5.0%
충청북도	4	4.0%
전라남도	3	3.0%
대구광역시	3	3.0%
대전광역시	3	3.0%
충청남도(세종시 포함)	2	2.0%
Other values (5)	7	7.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
서울특별시	32	31.4%
경기도	23	22.5%
인천광역시	12	11.8%
부산광역시	6	5.9%
광주광역시	5	4.9%
충청북도	4	3.9%
전라남도	3	2.9%
대구광역시	3	2.9%
대전광역시	3	2.9%
충청남도(세종시	2	2.0%
Other values (6)	9	8.8%

hshld_income_dgree_nm
Categorical

Distinct	5
Distinct (%)	5.0%
Missing	0
Missing (%)	0.0%
Memory size	932.0 B

300만원 미만	27
300이상500만원 미만	24
700만원 이상	22
500이상700만원 미만	20
무응답	7

Length

Max length	13
Median length	8
Mean length	9.85
Min length	3

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	300이상500만원 미만
2nd row	700만원 이상
3rd row	500이상700만원 미만
4th row	500이상700만원 미만
5th row	300이상500만원 미만

Common Values

Value	Count	Frequency (%)
300만원 미만	27	27.0%
300이상500만원 미만	24	24.0%
700만원 이상	22	22.0%
500이상700만원 미만	20	20.0%
무응답	7	7.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
미만	71	36.8%
300만원	27	14.0%
300이상500만원	24	12.4%
700만원	22	11.4%
이상	22	11.4%
500이상700만원	20	10.4%
무응답	7	3.6%

prchs_mth_nm
Categorical

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	932.0 B

오프라인	53
온라인	47

Length

Max length	4
Median length	4
Mean length	3.53
Min length	3

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	온라인
2nd row	오프라인
3rd row	온라인
4th row	온라인
5th row	온라인

Common Values

Value	Count	Frequency (%)
오프라인	53	53.0%
온라인	47	47.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
오프라인	53	53.0%
온라인	47	47.0%

bal_supli_prchs_at
Boolean

IMBALANCE

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	232.0 B

False	96
True	4

Common Values (Table)
Common Values (Plot)

Value	Count	Frequency (%)
False	96	96.0%
True	4	4.0%

climd_camping_fshng_supli_prchs_at
Boolean

HIGH CORRELATION IMBALANCE

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	232.0 B

False	98
True	2

Common Values (Table)
Common Values (Plot)

Value	Count	Frequency (%)
False	98	98.0%
True	2	2.0%

bcycl_wrkot_yoga_supli_prchs_at
Boolean

IMBALANCE

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	232.0 B

False	95
True	5

Common Values (Table)
Common Values (Plot)

Value	Count	Frequency (%)
False	95	95.0%
True	5	5.0%

golf_supli_prchs_at
Boolean

IMBALANCE

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	232.0 B

False	99
True	1

Common Values (Table)
Common Values (Plot)

Value	Count	Frequency (%)
False	99	99.0%
True	1	1.0%

marn_sports_supli_prchs_at
Boolean

CONSTANT

Distinct	1
Distinct (%)	1.0%
Missing	0
Missing (%)	0.0%
Memory size	232.0 B

False	100

Common Values (Table)
Common Values (Plot)

Value	Count	Frequency (%)
False	100	100.0%

wnt_sports_supli_prchs_at
Boolean

IMBALANCE

Distinct	2
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	232.0 B

False	99
True	1

Common Values (Table)
Common Values (Plot)

Value	Count	Frequency (%)
False	99	99.0%
True	1	1.0%

respond_id

respond_id

Heatmap
Table

	respond_id	sexdstn_flag_cd	agrde_flag_nm	answrr_oc_area_nm	hshld_income_dgree_nm	prchs_mth_nm	bal_supli_prchs_at	climd_camping_fshng_supli_prchs_at	bcycl_wrkot_yoga_supli_prchs_at	golf_supli_prchs_at	wnt_sports_supli_prchs_at
respond_id	1.000	0.000	0.131	0.000	0.000	0.000	0.000	0.241	0.000	0.000	0.000
sexdstn_flag_cd	0.000	1.000	0.000	0.270	0.165	0.000	0.088	0.000	0.000	0.000	0.000
agrde_flag_nm	0.131	0.000	1.000	0.000	0.000	0.000	0.000	0.077	0.043	0.000	0.000
answrr_oc_area_nm	0.000	0.270	0.000	1.000	0.000	0.197	0.063	0.706	0.481	0.000	0.000
hshld_income_dgree_nm	0.000	0.165	0.000	0.000	1.000	0.059	0.080	0.000	0.000	0.000	0.000
prchs_mth_nm	0.000	0.000	0.000	0.197	0.059	1.000	0.207	0.000	0.054	0.000	0.000
bal_supli_prchs_at	0.000	0.088	0.000	0.063	0.080	0.207	1.000	0.000	0.000	0.331	0.000
climd_camping_fshng_supli_prchs_at	0.241	0.000	0.077	0.706	0.000	0.000	0.000	1.000	0.133	0.000	0.000
bcycl_wrkot_yoga_supli_prchs_at	0.000	0.000	0.043	0.481	0.000	0.054	0.000	0.133	1.000	0.000	0.000
golf_supli_prchs_at	0.000	0.000	0.000	0.000	0.000	0.000	0.331	0.000	0.000	1.000	0.000
wnt_sports_supli_prchs_at	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	1.000

Heatmap
Table

	answrr_oc_area_nm	golf_supli_prchs_at	bcycl_wrkot_yoga_supli_prchs_at	agrde_flag_nm	hshld_income_dgree_nm	wnt_sports_supli_prchs_at	climd_camping_fshng_supli_prchs_at	sexdstn_flag_cd	bal_supli_prchs_at	prchs_mth_nm
answrr_oc_area_nm	1.000	0.000	0.409	0.000	0.000	0.000	0.612	0.226	0.037	0.163
golf_supli_prchs_at	0.000	1.000	0.000	0.000	0.000	0.000	0.000	0.000	0.215	0.000
bcycl_wrkot_yoga_supli_prchs_at	0.409	0.000	1.000	0.022	0.000	0.000	0.085	0.000	0.000	0.033
agrde_flag_nm	0.000	0.000	0.022	1.000	0.000	0.000	0.047	0.000	0.000	0.000
hshld_income_dgree_nm	0.000	0.000	0.000	0.000	1.000	0.000	0.000	0.197	0.094	0.068
wnt_sports_supli_prchs_at	0.000	0.000	0.000	0.000	0.000	1.000	0.000	0.000	0.000	0.000
climd_camping_fshng_supli_prchs_at	0.612	0.000	0.085	0.047	0.000	0.000	1.000	0.000	0.000	0.000
sexdstn_flag_cd	0.226	0.000	0.000	0.000	0.197	0.000	0.000	1.000	0.055	0.000
bal_supli_prchs_at	0.037	0.215	0.000	0.000	0.094	0.000	0.000	0.055	1.000	0.132
prchs_mth_nm	0.163	0.000	0.033	0.000	0.068	0.000	0.000	0.000	0.132	1.000

Heatmap
Table

	respond_id	sexdstn_flag_cd	agrde_flag_nm	answrr_oc_area_nm	hshld_income_dgree_nm	prchs_mth_nm	bal_supli_prchs_at	climd_camping_fshng_supli_prchs_at	bcycl_wrkot_yoga_supli_prchs_at	golf_supli_prchs_at	wnt_sports_supli_prchs_at
respond_id	1.000	0.000	0.088	0.000	0.000	0.000	0.000	0.155	0.000	0.000	0.000
sexdstn_flag_cd	0.000	1.000	0.000	0.226	0.197	0.000	0.055	0.000	0.000	0.000	0.000
agrde_flag_nm	0.088	0.000	1.000	0.000	0.000	0.000	0.000	0.047	0.022	0.000	0.000
answrr_oc_area_nm	0.000	0.226	0.000	1.000	0.000	0.163	0.037	0.612	0.409	0.000	0.000
hshld_income_dgree_nm	0.000	0.197	0.000	0.000	1.000	0.068	0.094	0.000	0.000	0.000	0.000
prchs_mth_nm	0.000	0.000	0.000	0.163	0.068	1.000	0.132	0.000	0.033	0.000	0.000
bal_supli_prchs_at	0.000	0.055	0.000	0.037	0.094	0.132	1.000	0.000	0.000	0.215	0.000
climd_camping_fshng_supli_prchs_at	0.155	0.000	0.047	0.612	0.000	0.000	0.000	1.000	0.085	0.000	0.000
bcycl_wrkot_yoga_supli_prchs_at	0.000	0.000	0.022	0.409	0.000	0.033	0.000	0.085	1.000	0.000	0.000
golf_supli_prchs_at	0.000	0.000	0.000	0.000	0.000	0.000	0.215	0.000	0.000	1.000	0.000
wnt_sports_supli_prchs_at	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	1.000

Count
Matrix

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

First rows
Last rows

	respond_id	examin_ym	sexdstn_flag_cd	agrde_flag_nm	answrr_oc_area_nm	hshld_income_dgree_nm	prchs_mth_nm	bal_supli_prchs_at	climd_camping_fshng_supli_prchs_at	bcycl_wrkot_yoga_supli_prchs_at	golf_supli_prchs_at	marn_sports_supli_prchs_at	wnt_sports_supli_prchs_at
0	199	202204	F	60대	서울특별시	300이상500만원 미만	온라인	N	N	N	N	N	N
1	3242000	202204	F	40대	부산광역시	700만원 이상	오프라인	N	N	N	N	N	N
2	354	202204	M	60대	서울특별시	500이상700만원 미만	온라인	N	N	N	N	N	N
3	497	202204	M	60대	전라남도	500이상700만원 미만	온라인	N	N	N	N	N	N
4	547	202204	M	60대	충청북도	300이상500만원 미만	온라인	N	N	N	N	N	N
5	689	202204	M	40대	경기도	500이상700만원 미만	온라인	N	N	N	N	N	N
6	727	202204	M	50대	경기도	300이상500만원 미만	오프라인	N	N	N	N	N	N
7	3242247	202204	M	30대	경기도	300만원 미만	온라인	N	Y	N	N	N	N
8	982	202204	M	50대	서울특별시	300만원 미만	온라인	N	N	N	N	N	N
9	988	202204	F	50대	부산광역시	300만원 미만	오프라인	N	N	N	N	N	N

	respond_id	examin_ym	sexdstn_flag_cd	agrde_flag_nm	answrr_oc_area_nm	hshld_income_dgree_nm	prchs_mth_nm	bal_supli_prchs_at	climd_camping_fshng_supli_prchs_at	bcycl_wrkot_yoga_supli_prchs_at	golf_supli_prchs_at	marn_sports_supli_prchs_at	wnt_sports_supli_prchs_at
90	13801	202204	M	50대	경기도	300만원 미만	오프라인	N	N	N	N	N	N
91	13810	202204	F	30대	경기도	700만원 이상	오프라인	N	N	N	N	N	N
92	14108	202204	M	40대	인천광역시	300만원 미만	오프라인	N	N	N	N	N	N
93	14152	202204	M	40대	경기도	700만원 이상	온라인	N	N	N	N	N	N
94	14227	202204	M	60대	경기도	300이상500만원 미만	온라인	N	N	N	N	N	N
95	14550	202204	F	60대	서울특별시	300만원 미만	오프라인	N	N	N	N	N	N
96	14840	202204	M	50대	인천광역시	700만원 이상	오프라인	N	N	N	N	N	N
97	14873	202204	M	40대	경기도	500이상700만원 미만	오프라인	N	N	N	N	N	N
98	15392	202204	F	40대	광주광역시	300만원 미만	오프라인	N	N	N	N	N	N
99	15661	202204	M	60대	대전광역시	300이상500만원 미만	온라인	N	N	N	N	N	N

Overview

Variables

Common Values

Length

Common Values (Plot)

Common Values

Length

Common Values (Plot)

Common Values

Length

Common Values (Plot)

Common Values

Length

Common Values

Length

Common Values (Plot)

Common Values

Length

Common Values (Plot)

Interactions

Correlations

Missing values

Sample