Overview

Dataset statistics

Number of variables26
Number of observations10000
Missing cells84966
Missing cells (%)32.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.1 MiB
Average record size in memory225.0 B

Variable types

Numeric4
Text7
DateTime7
Categorical5
Unsupported3

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),판매점영업면적
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-16483/S/1/datasetView.do

Alerts

영업상태코드 is highly imbalanced (54.4%)Imbalance
영업상태명 is highly imbalanced (54.4%)Imbalance
상세영업상태코드 is highly imbalanced (54.4%)Imbalance
상세영업상태명 is highly imbalanced (54.4%)Imbalance
인허가취소일자 has 9792 (97.9%) missing valuesMissing
폐업일자 has 4421 (44.2%) missing valuesMissing
휴업시작일자 has 9995 (> 99.9%) missing valuesMissing
휴업종료일자 has 9996 (> 99.9%) missing valuesMissing
재개업일자 has 10000 (100.0%) missing valuesMissing
전화번호 has 5799 (58.0%) missing valuesMissing
소재지면적 has 10000 (100.0%) missing valuesMissing
소재지우편번호 has 6531 (65.3%) missing valuesMissing
지번주소 has 1300 (13.0%) missing valuesMissing
업태구분명 has 10000 (100.0%) missing valuesMissing
좌표정보(X) has 124 (1.2%) missing valuesMissing
좌표정보(Y) has 124 (1.2%) missing valuesMissing
판매점영업면적 has 6853 (68.5%) missing valuesMissing
판매점영업면적 is highly skewed (γ1 = 52.04739572)Skewed
관리번호 has unique valuesUnique
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
판매점영업면적 has 737 (7.4%) zerosZeros

Reproduction

Analysis started2024-04-06 11:11:31.205471
Analysis finished2024-04-06 11:11:34.596002
Duration3.39 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Real number (ℝ)

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3134462
Minimum3000000
Maximum3240000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-06T20:11:34.707329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3010000
Q13070000
median3140000
Q33200000
95-th percentile3230000
Maximum3240000
Range240000
Interquartile range (IQR)130000

Descriptive statistics

Standard deviation72972.207
Coefficient of variation (CV)0.023280616
Kurtosis-1.1983596
Mean3134462
Median Absolute Deviation (MAD)70000
Skewness-0.22988223
Sum3.134462 × 1010
Variance5.3249431 × 109
MonotonicityNot monotonic
2024-04-06T20:11:34.906247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
3220000 983
 
9.8%
3230000 560
 
5.6%
3130000 556
 
5.6%
3150000 555
 
5.5%
3200000 465
 
4.7%
3210000 465
 
4.7%
3180000 454
 
4.5%
3240000 445
 
4.5%
3050000 427
 
4.3%
3040000 404
 
4.0%
Other values (15) 4686
46.9%
ValueCountFrequency (%)
3000000 316
3.2%
3010000 316
3.2%
3020000 253
2.5%
3030000 256
2.6%
3040000 404
4.0%
3050000 427
4.3%
3060000 314
3.1%
3070000 357
3.6%
3080000 306
3.1%
3090000 245
2.5%
ValueCountFrequency (%)
3240000 445
4.5%
3230000 560
5.6%
3220000 983
9.8%
3210000 465
4.7%
3200000 465
4.7%
3190000 306
 
3.1%
3180000 454
4.5%
3170000 251
 
2.5%
3160000 347
 
3.5%
3150000 555
5.5%

관리번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-06T20:11:35.257935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters250000
Distinct characters13
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10000 ?
Unique (%)100.0%

Sample

1st rowPHMH320163180034087500046
2nd rowPHMH320173000034087500026
3rd rowPHMH320153160034087500026
4th rowPHMH320233170035087500002
5th rowPHMH320153180034087500012
ValueCountFrequency (%)
phmh320163180034087500046 1
 
< 0.1%
phmh320143110032087500014 1
 
< 0.1%
phmh320123060034087500021 1
 
< 0.1%
phmh320123080033087500103 1
 
< 0.1%
phmh320123240033087500054 1
 
< 0.1%
phmh320223000034087500014 1
 
< 0.1%
phmh320193200033087500019 1
 
< 0.1%
phmh320233180034087500003 1
 
< 0.1%
phmh320223140033087500011 1
 
< 0.1%
phmh320193210034087500034 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-04-06T20:11:35.840161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 76826
30.7%
3 40278
16.1%
2 22994
 
9.2%
H 20000
 
8.0%
1 17150
 
6.9%
5 13754
 
5.5%
7 13442
 
5.4%
8 12665
 
5.1%
P 10000
 
4.0%
M 10000
 
4.0%
Other values (3) 12891
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 210000
84.0%
Uppercase Letter 40000
 
16.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 76826
36.6%
3 40278
19.2%
2 22994
 
10.9%
1 17150
 
8.2%
5 13754
 
6.5%
7 13442
 
6.4%
8 12665
 
6.0%
4 7521
 
3.6%
6 3039
 
1.4%
9 2331
 
1.1%
Uppercase Letter
ValueCountFrequency (%)
H 20000
50.0%
P 10000
25.0%
M 10000
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 210000
84.0%
Latin 40000
 
16.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 76826
36.6%
3 40278
19.2%
2 22994
 
10.9%
1 17150
 
8.2%
5 13754
 
6.5%
7 13442
 
6.4%
8 12665
 
6.0%
4 7521
 
3.6%
6 3039
 
1.4%
9 2331
 
1.1%
Latin
ValueCountFrequency (%)
H 20000
50.0%
P 10000
25.0%
M 10000
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 250000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 76826
30.7%
3 40278
16.1%
2 22994
 
9.2%
H 20000
 
8.0%
1 17150
 
6.9%
5 13754
 
5.5%
7 13442
 
5.4%
8 12665
 
5.1%
P 10000
 
4.0%
M 10000
 
4.0%
Other values (3) 12891
 
5.2%
Distinct2542
Distinct (%)25.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2011-11-05 00:00:00
Maximum2024-04-04 00:00:00
2024-04-06T20:11:36.082769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:11:36.306360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Date

MISSING 

Distinct168
Distinct (%)80.8%
Missing9792
Missing (%)97.9%
Memory size156.2 KiB
Minimum2013-07-18 00:00:00
Maximum2023-03-28 00:00:00
2024-04-06T20:11:36.769837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:11:36.980341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

영업상태코드
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3
5497 
1
4415 
4
 
82
2
 
5
5
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row3
2nd row3
3rd row3
4th row1
5th row1

Common Values

ValueCountFrequency (%)
3 5497
55.0%
1 4415
44.1%
4 82
 
0.8%
2 5
 
0.1%
5 1
 
< 0.1%

Length

2024-04-06T20:11:37.227927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:11:37.463285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 5497
55.0%
1 4415
44.1%
4 82
 
0.8%
2 5
 
< 0.1%
5 1
 
< 0.1%

영업상태명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
5497 
영업/정상
4415 
취소/말소/만료/정지/중지
 
82
휴업
 
5
제외/삭제/전출
 
1

Length

Max length14
Median length2
Mean length3.4235
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row폐업
2nd row폐업
3rd row폐업
4th row영업/정상
5th row영업/정상

Common Values

ValueCountFrequency (%)
폐업 5497
55.0%
영업/정상 4415
44.1%
취소/말소/만료/정지/중지 82
 
0.8%
휴업 5
 
0.1%
제외/삭제/전출 1
 
< 0.1%

Length

2024-04-06T20:11:37.709145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:11:37.970693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 5497
55.0%
영업/정상 4415
44.1%
취소/말소/만료/정지/중지 82
 
0.8%
휴업 5
 
< 0.1%
제외/삭제/전출 1
 
< 0.1%

상세영업상태코드
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3
5497 
13
4415 
24
 
82
2
 
5
99
 
1

Length

Max length2
Median length1
Mean length1.4498
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row3
2nd row3
3rd row3
4th row13
5th row13

Common Values

ValueCountFrequency (%)
3 5497
55.0%
13 4415
44.1%
24 82
 
0.8%
2 5
 
0.1%
99 1
 
< 0.1%

Length

2024-04-06T20:11:38.148731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:11:38.459378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 5497
55.0%
13 4415
44.1%
24 82
 
0.8%
2 5
 
< 0.1%
99 1
 
< 0.1%

상세영업상태명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
5497 
영업중
4415 
직권폐업
 
82
휴업
 
5
삭제
 
1

Length

Max length4
Median length2
Mean length2.4579
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row폐업
2nd row폐업
3rd row폐업
4th row영업중
5th row영업중

Common Values

ValueCountFrequency (%)
폐업 5497
55.0%
영업중 4415
44.1%
직권폐업 82
 
0.8%
휴업 5
 
0.1%
삭제 1
 
< 0.1%

Length

2024-04-06T20:11:38.654599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:11:38.832561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 5497
55.0%
영업중 4415
44.1%
직권폐업 82
 
0.8%
휴업 5
 
< 0.1%
삭제 1
 
< 0.1%

폐업일자
Date

MISSING 

Distinct2339
Distinct (%)41.9%
Missing4421
Missing (%)44.2%
Memory size156.2 KiB
Minimum2012-11-15 00:00:00
Maximum2024-04-03 00:00:00
2024-04-06T20:11:39.059251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:11:39.401045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Date

MISSING 

Distinct5
Distinct (%)100.0%
Missing9995
Missing (%)> 99.9%
Memory size156.2 KiB
Minimum2012-12-26 00:00:00
Maximum2023-12-02 00:00:00
2024-04-06T20:11:39.665544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:11:39.853334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)

휴업종료일자
Date

MISSING 

Distinct4
Distinct (%)100.0%
Missing9996
Missing (%)> 99.9%
Memory size156.2 KiB
Minimum2020-05-09 00:00:00
Maximum2024-12-02 00:00:00
2024-04-06T20:11:40.036068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:11:40.208290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=4)

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

전화번호
Text

MISSING 

Distinct3811
Distinct (%)90.7%
Missing5799
Missing (%)58.0%
Memory size156.2 KiB
2024-04-06T20:11:40.600215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length10.002618
Min length7

Characters and Unicode

Total characters42021
Distinct characters19
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3504 ?
Unique (%)83.4%

Sample

1st row782-3340
2nd row02-766-0409
3rd row508-8554
4th row3443-4849
5th row2638-7117
ValueCountFrequency (%)
1577-9621 26
 
0.6%
1577-0711 11
 
0.3%
080-855-5525 10
 
0.2%
02-535-6103 9
 
0.2%
535-6103 8
 
0.2%
02-3284-8129 5
 
0.1%
02-6916-1500 4
 
0.1%
02-3284-8112 4
 
0.1%
02-3284-8120 4
 
0.1%
02-2269-7728 4
 
0.1%
Other values (3801) 4116
98.0%
2024-04-06T20:11:41.319342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 6360
15.1%
2 5937
14.1%
0 5081
12.1%
5 3428
8.2%
3 3382
8.0%
4 3229
7.7%
7 3166
7.5%
6 2987
7.1%
9 2905
6.9%
8 2790
6.6%
Other values (9) 2756
6.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 35645
84.8%
Dash Punctuation 6360
 
15.1%
Other Punctuation 8
 
< 0.1%
Other Letter 6
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 5937
16.7%
0 5081
14.3%
5 3428
9.6%
3 3382
9.5%
4 3229
9.1%
7 3166
8.9%
6 2987
8.4%
9 2905
8.1%
8 2790
7.8%
1 2740
7.7%
Other Letter
ValueCountFrequency (%)
2
33.3%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 6360
100.0%
Other Punctuation
ValueCountFrequency (%)
* 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 42015
> 99.9%
Hangul 6
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
- 6360
15.1%
2 5937
14.1%
0 5081
12.1%
5 3428
8.2%
3 3382
8.0%
4 3229
7.7%
7 3166
7.5%
6 2987
7.1%
9 2905
6.9%
8 2790
6.6%
Other values (4) 2750
6.5%
Hangul
ValueCountFrequency (%)
2
33.3%
1
16.7%
1
16.7%
1
16.7%
1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 42015
> 99.9%
Hangul 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 6360
15.1%
2 5937
14.1%
0 5081
12.1%
5 3428
8.2%
3 3382
8.0%
4 3229
7.7%
7 3166
7.5%
6 2987
7.1%
9 2905
6.9%
8 2790
6.6%
Other values (4) 2750
6.5%
Hangul
ValueCountFrequency (%)
2
33.3%
1
16.7%
1
16.7%
1
16.7%
1
16.7%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

소재지우편번호
Text

MISSING 

Distinct1771
Distinct (%)51.1%
Missing6531
Missing (%)65.3%
Memory size156.2 KiB
2024-04-06T20:11:41.915609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0590948
Min length5

Characters and Unicode

Total characters21019
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1011 ?
Unique (%)29.1%

Sample

1st row152101
2nd row150885
3rd row143150
4th row110450
5th row135840
ValueCountFrequency (%)
150010 22
 
0.6%
151050 17
 
0.5%
138842 12
 
0.3%
130872 12
 
0.3%
135897 11
 
0.3%
121854 10
 
0.3%
120833 10
 
0.3%
134830 10
 
0.3%
135840 10
 
0.3%
139804 9
 
0.3%
Other values (1761) 3346
96.5%
2024-04-06T20:11:42.844744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 5082
24.2%
8 2944
14.0%
3 2908
13.8%
0 2339
11.1%
5 1832
 
8.7%
2 1471
 
7.0%
7 1204
 
5.7%
4 1169
 
5.6%
9 1046
 
5.0%
6 765
 
3.6%
Other values (2) 259
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20760
98.8%
Dash Punctuation 220
 
1.0%
Space Separator 39
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 5082
24.5%
8 2944
14.2%
3 2908
14.0%
0 2339
11.3%
5 1832
 
8.8%
2 1471
 
7.1%
7 1204
 
5.8%
4 1169
 
5.6%
9 1046
 
5.0%
6 765
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 220
100.0%
Space Separator
ValueCountFrequency (%)
39
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 21019
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 5082
24.2%
8 2944
14.0%
3 2908
13.8%
0 2339
11.1%
5 1832
 
8.7%
2 1471
 
7.0%
7 1204
 
5.7%
4 1169
 
5.6%
9 1046
 
5.0%
6 765
 
3.6%
Other values (2) 259
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21019
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 5082
24.2%
8 2944
14.0%
3 2908
13.8%
0 2339
11.1%
5 1832
 
8.7%
2 1471
 
7.0%
7 1204
 
5.7%
4 1169
 
5.6%
9 1046
 
5.0%
6 765
 
3.6%
Other values (2) 259
 
1.2%

지번주소
Text

MISSING 

Distinct7861
Distinct (%)90.4%
Missing1300
Missing (%)13.0%
Memory size156.2 KiB
2024-04-06T20:11:43.468206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length47
Mean length24.28954
Min length10

Characters and Unicode

Total characters211319
Distinct characters549
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7147 ?
Unique (%)82.1%

Sample

1st row서울특별시 영등포구 대림동 695번지
2nd row서울특별시 구로구 오류동 156번지 100호
3rd row서울특별시 금천구 시흥동 818-6
4th row서울특별시 영등포구 여의도동 35번지 5호 107호
5th row서울특별시 광진구 군자동 474번지 28호
ValueCountFrequency (%)
서울특별시 8688
 
19.3%
1층 1168
 
2.6%
강남구 982
 
2.2%
1호 768
 
1.7%
송파구 546
 
1.2%
마포구 465
 
1.0%
강서구 463
 
1.0%
관악구 459
 
1.0%
서초구 455
 
1.0%
동대문구 425
 
0.9%
Other values (5874) 30684
68.0%
2024-04-06T20:11:44.446861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36463
 
17.3%
10287
 
4.9%
10281
 
4.9%
1 9947
 
4.7%
9183
 
4.3%
8821
 
4.2%
8734
 
4.1%
8692
 
4.1%
8689
 
4.1%
7055
 
3.3%
Other values (539) 93167
44.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 131645
62.3%
Decimal Number 40936
 
19.4%
Space Separator 36463
 
17.3%
Dash Punctuation 1537
 
0.7%
Uppercase Letter 457
 
0.2%
Other Punctuation 169
 
0.1%
Lowercase Letter 44
 
< 0.1%
Close Punctuation 22
 
< 0.1%
Open Punctuation 21
 
< 0.1%
Math Symbol 20
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10287
 
7.8%
10281
 
7.8%
9183
 
7.0%
8821
 
6.7%
8734
 
6.6%
8692
 
6.6%
8689
 
6.6%
7055
 
5.4%
6721
 
5.1%
6560
 
5.0%
Other values (476) 46622
35.4%
Uppercase Letter
ValueCountFrequency (%)
B 66
14.4%
K 44
 
9.6%
A 40
 
8.8%
C 34
 
7.4%
S 33
 
7.2%
M 31
 
6.8%
E 27
 
5.9%
I 24
 
5.3%
D 23
 
5.0%
L 18
 
3.9%
Other values (15) 117
25.6%
Lowercase Letter
ValueCountFrequency (%)
e 20
45.5%
i 3
 
6.8%
s 3
 
6.8%
r 3
 
6.8%
l 2
 
4.5%
n 2
 
4.5%
b 2
 
4.5%
a 1
 
2.3%
z 1
 
2.3%
t 1
 
2.3%
Other values (6) 6
 
13.6%
Decimal Number
ValueCountFrequency (%)
1 9947
24.3%
2 5006
12.2%
3 4232
10.3%
4 3819
 
9.3%
5 3412
 
8.3%
0 3398
 
8.3%
6 3233
 
7.9%
7 2889
 
7.1%
8 2580
 
6.3%
9 2420
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 162
95.9%
& 3
 
1.8%
. 3
 
1.8%
? 1
 
0.6%
Letter Number
ValueCountFrequency (%)
3
60.0%
1
 
20.0%
1
 
20.0%
Space Separator
ValueCountFrequency (%)
36463
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1537
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Math Symbol
ValueCountFrequency (%)
~ 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 131645
62.3%
Common 79168
37.5%
Latin 506
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10287
 
7.8%
10281
 
7.8%
9183
 
7.0%
8821
 
6.7%
8734
 
6.6%
8692
 
6.6%
8689
 
6.6%
7055
 
5.4%
6721
 
5.1%
6560
 
5.0%
Other values (476) 46622
35.4%
Latin
ValueCountFrequency (%)
B 66
13.0%
K 44
 
8.7%
A 40
 
7.9%
C 34
 
6.7%
S 33
 
6.5%
M 31
 
6.1%
E 27
 
5.3%
I 24
 
4.7%
D 23
 
4.5%
e 20
 
4.0%
Other values (34) 164
32.4%
Common
ValueCountFrequency (%)
36463
46.1%
1 9947
 
12.6%
2 5006
 
6.3%
3 4232
 
5.3%
4 3819
 
4.8%
5 3412
 
4.3%
0 3398
 
4.3%
6 3233
 
4.1%
7 2889
 
3.6%
8 2580
 
3.3%
Other values (9) 4189
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 131645
62.3%
ASCII 79669
37.7%
Number Forms 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36463
45.8%
1 9947
 
12.5%
2 5006
 
6.3%
3 4232
 
5.3%
4 3819
 
4.8%
5 3412
 
4.3%
0 3398
 
4.3%
6 3233
 
4.1%
7 2889
 
3.6%
8 2580
 
3.2%
Other values (50) 4690
 
5.9%
Hangul
ValueCountFrequency (%)
10287
 
7.8%
10281
 
7.8%
9183
 
7.0%
8821
 
6.7%
8734
 
6.6%
8692
 
6.6%
8689
 
6.6%
7055
 
5.4%
6721
 
5.1%
6560
 
5.0%
Other values (476) 46622
35.4%
Number Forms
ValueCountFrequency (%)
3
60.0%
1
 
20.0%
1
 
20.0%
Distinct8962
Distinct (%)89.7%
Missing14
Missing (%)0.1%
Memory size156.2 KiB
2024-04-06T20:11:45.050902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length73
Median length62
Mean length31.345584
Min length20

Characters and Unicode

Total characters313017
Distinct characters624
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8054 ?
Unique (%)80.7%

Sample

1st row서울특별시 영등포구 도림로47길 1 (대림동, 우성아파트)
2nd row서울특별시 종로구 청계천로 331, 제라동 나열1층 6호 (창신동, 동대문상가,일신파워빌딩)
3rd row서울특별시 구로구 오류로8길 6 (오류동)
4th row서울특별시 금천구 독산로24길 15, 1층 (시흥동)
5th row서울특별시 영등포구 여의나루로 42, 107호 (여의도동)
ValueCountFrequency (%)
서울특별시 9986
 
16.2%
1층 4088
 
6.6%
강남구 981
 
1.6%
101호 615
 
1.0%
송파구 560
 
0.9%
마포구 555
 
0.9%
강서구 554
 
0.9%
관악구 465
 
0.8%
서초구 462
 
0.7%
영등포구 449
 
0.7%
Other values (8488) 42886
69.6%
2024-04-06T20:11:46.046216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
51626
 
16.5%
1 16269
 
5.2%
13157
 
4.2%
12232
 
3.9%
10803
 
3.5%
10643
 
3.4%
10355
 
3.3%
10098
 
3.2%
) 10022
 
3.2%
( 10021
 
3.2%
Other values (614) 157791
50.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 181341
57.9%
Space Separator 51626
 
16.5%
Decimal Number 49331
 
15.8%
Close Punctuation 10022
 
3.2%
Open Punctuation 10021
 
3.2%
Other Punctuation 8887
 
2.8%
Dash Punctuation 877
 
0.3%
Uppercase Letter 795
 
0.3%
Lowercase Letter 62
 
< 0.1%
Math Symbol 46
 
< 0.1%
Other values (2) 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
13157
 
7.3%
12232
 
6.7%
10803
 
6.0%
10643
 
5.9%
10355
 
5.7%
10098
 
5.6%
9993
 
5.5%
9987
 
5.5%
5883
 
3.2%
4464
 
2.5%
Other values (548) 83726
46.2%
Uppercase Letter
ValueCountFrequency (%)
B 195
24.5%
A 95
11.9%
C 59
 
7.4%
K 52
 
6.5%
M 50
 
6.3%
S 44
 
5.5%
D 39
 
4.9%
E 36
 
4.5%
I 33
 
4.2%
R 29
 
3.6%
Other values (15) 163
20.5%
Lowercase Letter
ValueCountFrequency (%)
e 25
40.3%
r 5
 
8.1%
s 4
 
6.5%
b 4
 
6.5%
c 4
 
6.5%
o 3
 
4.8%
w 3
 
4.8%
k 3
 
4.8%
l 2
 
3.2%
h 2
 
3.2%
Other values (6) 7
 
11.3%
Decimal Number
ValueCountFrequency (%)
1 16269
33.0%
2 6078
 
12.3%
0 5095
 
10.3%
3 4697
 
9.5%
4 3730
 
7.6%
5 3288
 
6.7%
6 2865
 
5.8%
7 2725
 
5.5%
8 2406
 
4.9%
9 2178
 
4.4%
Other Punctuation
ValueCountFrequency (%)
, 8863
99.7%
. 16
 
0.2%
& 3
 
< 0.1%
? 3
 
< 0.1%
# 1
 
< 0.1%
/ 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
5
62.5%
2
 
25.0%
1
 
12.5%
Space Separator
ValueCountFrequency (%)
51626
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10022
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10021
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 877
100.0%
Math Symbol
ValueCountFrequency (%)
~ 46
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 181339
57.9%
Common 130811
41.8%
Latin 865
 
0.3%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
13157
 
7.3%
12232
 
6.7%
10803
 
6.0%
10643
 
5.9%
10355
 
5.7%
10098
 
5.6%
9993
 
5.5%
9987
 
5.5%
5883
 
3.2%
4464
 
2.5%
Other values (546) 83724
46.2%
Latin
ValueCountFrequency (%)
B 195
22.5%
A 95
11.0%
C 59
 
6.8%
K 52
 
6.0%
M 50
 
5.8%
S 44
 
5.1%
D 39
 
4.5%
E 36
 
4.2%
I 33
 
3.8%
R 29
 
3.4%
Other values (34) 233
26.9%
Common
ValueCountFrequency (%)
51626
39.5%
1 16269
 
12.4%
) 10022
 
7.7%
( 10021
 
7.7%
, 8863
 
6.8%
2 6078
 
4.6%
0 5095
 
3.9%
3 4697
 
3.6%
4 3730
 
2.9%
5 3288
 
2.5%
Other values (12) 11122
 
8.5%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 181339
57.9%
ASCII 131668
42.1%
Number Forms 8
 
< 0.1%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
51626
39.2%
1 16269
 
12.4%
) 10022
 
7.6%
( 10021
 
7.6%
, 8863
 
6.7%
2 6078
 
4.6%
0 5095
 
3.9%
3 4697
 
3.6%
4 3730
 
2.8%
5 3288
 
2.5%
Other values (53) 11979
 
9.1%
Hangul
ValueCountFrequency (%)
13157
 
7.3%
12232
 
6.7%
10803
 
6.0%
10643
 
5.9%
10355
 
5.7%
10098
 
5.6%
9993
 
5.5%
9987
 
5.5%
5883
 
3.2%
4464
 
2.5%
Other values (546) 83724
46.2%
Number Forms
ValueCountFrequency (%)
5
62.5%
2
 
25.0%
1
 
12.5%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%
Distinct4391
Distinct (%)44.0%
Missing17
Missing (%)0.2%
Memory size156.2 KiB
2024-04-06T20:11:46.720724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.0999699
Min length5

Characters and Unicode

Total characters50913
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1854 ?
Unique (%)18.6%

Sample

1st row07410
2nd row03120
3rd row08343
4th row08570
5th row07328
ValueCountFrequency (%)
03766 13
 
0.1%
06017 13
 
0.1%
03190 12
 
0.1%
03938 12
 
0.1%
05354 12
 
0.1%
02624 12
 
0.1%
06197 12
 
0.1%
07788 12
 
0.1%
02708 11
 
0.1%
07803 11
 
0.1%
Other values (4381) 9863
98.8%
2024-04-06T20:11:47.537805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12785
25.1%
1 5004
 
9.8%
3 4775
 
9.4%
7 4541
 
8.9%
5 4498
 
8.8%
6 4292
 
8.4%
2 4265
 
8.4%
8 4155
 
8.2%
4 3973
 
7.8%
9 2624
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 50912
> 99.9%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12785
25.1%
1 5004
 
9.8%
3 4775
 
9.4%
7 4541
 
8.9%
5 4498
 
8.8%
6 4292
 
8.4%
2 4265
 
8.4%
8 4155
 
8.2%
4 3973
 
7.8%
9 2624
 
5.2%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 50913
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12785
25.1%
1 5004
 
9.8%
3 4775
 
9.4%
7 4541
 
8.9%
5 4498
 
8.8%
6 4292
 
8.4%
2 4265
 
8.4%
8 4155
 
8.2%
4 3973
 
7.8%
9 2624
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 50913
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12785
25.1%
1 5004
 
9.8%
3 4775
 
9.4%
7 4541
 
8.9%
5 4498
 
8.8%
6 4292
 
8.4%
2 4265
 
8.4%
8 4155
 
8.2%
4 3973
 
7.8%
9 2624
 
5.2%
Distinct9007
Distinct (%)90.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-06T20:11:48.142481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length19
Mean length10.673
Min length2

Characters and Unicode

Total characters106730
Distinct characters651
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8153 ?
Unique (%)81.5%

Sample

1st row(주)코리아세븐 대림로점
2nd row씨유종로청계점
3rd rowGS25 오류타운점
4th row지에스(GS25)금천독산로점
5th row씨유 여의도역점
ValueCountFrequency (%)
씨유 1856
 
10.6%
gs25 1324
 
7.5%
세븐일레븐 896
 
5.1%
지에스25 864
 
4.9%
주)코리아세븐 663
 
3.8%
미니스톱 310
 
1.8%
cu 293
 
1.7%
지에스(gs)25 242
 
1.4%
이마트24 187
 
1.1%
주)비지에프리테일 92
 
0.5%
Other values (8042) 10814
61.6%
2024-04-06T20:11:48.931241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9113
 
8.5%
7569
 
7.1%
2 4086
 
3.8%
5 3783
 
3.5%
3090
 
2.9%
3085
 
2.9%
2874
 
2.7%
2758
 
2.6%
2379
 
2.2%
S 2290
 
2.1%
Other values (641) 65703
61.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 80612
75.5%
Decimal Number 8814
 
8.3%
Space Separator 7569
 
7.1%
Uppercase Letter 5963
 
5.6%
Open Punctuation 1789
 
1.7%
Close Punctuation 1788
 
1.7%
Other Symbol 86
 
0.1%
Lowercase Letter 86
 
0.1%
Other Punctuation 12
 
< 0.1%
Dash Punctuation 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
9113
 
11.3%
3090
 
3.8%
3085
 
3.8%
2874
 
3.6%
2758
 
3.4%
2379
 
3.0%
2164
 
2.7%
2094
 
2.6%
1671
 
2.1%
1645
 
2.0%
Other values (576) 49739
61.7%
Uppercase Letter
ValueCountFrequency (%)
S 2290
38.4%
G 2225
37.3%
C 550
 
9.2%
U 515
 
8.6%
K 76
 
1.3%
R 32
 
0.5%
I 29
 
0.5%
L 27
 
0.5%
E 26
 
0.4%
M 26
 
0.4%
Other values (14) 167
 
2.8%
Lowercase Letter
ValueCountFrequency (%)
s 17
19.8%
e 14
16.3%
u 10
11.6%
l 6
 
7.0%
p 5
 
5.8%
g 5
 
5.8%
a 4
 
4.7%
r 4
 
4.7%
c 3
 
3.5%
o 3
 
3.5%
Other values (10) 15
17.4%
Decimal Number
ValueCountFrequency (%)
2 4086
46.4%
5 3783
42.9%
4 303
 
3.4%
1 249
 
2.8%
3 161
 
1.8%
6 99
 
1.1%
7 74
 
0.8%
9 23
 
0.3%
0 19
 
0.2%
8 17
 
0.2%
Other Punctuation
ValueCountFrequency (%)
. 5
41.7%
& 4
33.3%
, 1
 
8.3%
# 1
 
8.3%
/ 1
 
8.3%
Space Separator
ValueCountFrequency (%)
7569
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1789
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1788
100.0%
Other Symbol
ValueCountFrequency (%)
86
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 80698
75.6%
Common 19983
 
18.7%
Latin 6049
 
5.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
9113
 
11.3%
3090
 
3.8%
3085
 
3.8%
2874
 
3.6%
2758
 
3.4%
2379
 
2.9%
2164
 
2.7%
2094
 
2.6%
1671
 
2.1%
1645
 
2.0%
Other values (577) 49825
61.7%
Latin
ValueCountFrequency (%)
S 2290
37.9%
G 2225
36.8%
C 550
 
9.1%
U 515
 
8.5%
K 76
 
1.3%
R 32
 
0.5%
I 29
 
0.5%
L 27
 
0.4%
E 26
 
0.4%
M 26
 
0.4%
Other values (34) 253
 
4.2%
Common
ValueCountFrequency (%)
7569
37.9%
2 4086
20.4%
5 3783
18.9%
( 1789
 
9.0%
) 1788
 
8.9%
4 303
 
1.5%
1 249
 
1.2%
3 161
 
0.8%
6 99
 
0.5%
7 74
 
0.4%
Other values (10) 82
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 80612
75.5%
ASCII 26032
 
24.4%
None 86
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
9113
 
11.3%
3090
 
3.8%
3085
 
3.8%
2874
 
3.6%
2758
 
3.4%
2379
 
3.0%
2164
 
2.7%
2094
 
2.6%
1671
 
2.1%
1645
 
2.0%
Other values (576) 49739
61.7%
ASCII
ValueCountFrequency (%)
7569
29.1%
2 4086
15.7%
5 3783
14.5%
S 2290
 
8.8%
G 2225
 
8.5%
( 1789
 
6.9%
) 1788
 
6.9%
C 550
 
2.1%
U 515
 
2.0%
4 303
 
1.2%
Other values (54) 1134
 
4.4%
None
ValueCountFrequency (%)
86
100.0%
Distinct9999
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2013-07-08 17:43:29
Maximum2024-04-04 17:42:26
2024-04-06T20:11:49.140848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:11:49.344655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
I
5803 
U
4197 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowU
2nd rowI
3rd rowI
4th rowI
5th rowI

Common Values

ValueCountFrequency (%)
I 5803
58.0%
U 4197
42.0%

Length

2024-04-06T20:11:49.578346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:11:49.749007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 5803
58.0%
u 4197
42.0%
Distinct1882
Distinct (%)18.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:06:00
2024-04-06T20:11:49.943118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:11:50.188688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct7231
Distinct (%)73.2%
Missing124
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean199314.13
Minimum182293.36
Maximum216029.39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-06T20:11:50.419025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum182293.36
5-th percentile186222.42
Q1192916.02
median200942.58
Q3205022.6
95-th percentile211234.6
Maximum216029.39
Range33736.03
Interquartile range (IQR)12106.579

Descriptive statistics

Standard deviation7564.6339
Coefficient of variation (CV)0.037953324
Kurtosis-0.89994956
Mean199314.13
Median Absolute Deviation (MAD)5975.9279
Skewness-0.16805462
Sum1.9684264 × 109
Variance57223685
MonotonicityNot monotonic
2024-04-06T20:11:50.618769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
194584.959249312 11
 
0.1%
210868.397496689 10
 
0.1%
204108.263654233 9
 
0.1%
205271.704936121 8
 
0.1%
198797.140043517 6
 
0.1%
183400.714787118 6
 
0.1%
202905.275867311 5
 
0.1%
195874.639172861 5
 
0.1%
202176.459585279 5
 
0.1%
212440.285753723 5
 
0.1%
Other values (7221) 9806
98.1%
(Missing) 124
 
1.2%
ValueCountFrequency (%)
182293.357671337 1
< 0.1%
182524.823835629 1
< 0.1%
182794.441839414 1
< 0.1%
182846.62641593 1
< 0.1%
182895.668483962 1
< 0.1%
182914.598086861 1
< 0.1%
182920.603878336 1
< 0.1%
182933.515903576 1
< 0.1%
182941.05762285 1
< 0.1%
182957.325956453 1
< 0.1%
ValueCountFrequency (%)
216029.388021 1
 
< 0.1%
215927.688523964 2
< 0.1%
215898.113091143 1
 
< 0.1%
215888.898816 1
 
< 0.1%
215784.2264 4
< 0.1%
215728.497758 3
< 0.1%
215661.222623 1
 
< 0.1%
215659.154061 1
 
< 0.1%
215527.721278 1
 
< 0.1%
215502.593610945 2
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct7230
Distinct (%)73.2%
Missing124
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean449371.71
Minimum436888.77
Maximum465076.35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-06T20:11:50.802694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum436888.77
5-th percentile441632
Q1444748.5
median449164.55
Q3452794.5
95-th percentile460094.83
Maximum465076.35
Range28187.577
Interquartile range (IQR)8046.0042

Descriptive statistics

Standard deviation5581.0829
Coefficient of variation (CV)0.012419747
Kurtosis-0.41537534
Mean449371.71
Median Absolute Deviation (MAD)4145.2353
Skewness0.45605816
Sum4.437995 × 109
Variance31148486
MonotonicityNot monotonic
2024-04-06T20:11:51.088116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
451381.585492051 11
 
0.1%
442053.227933005 10
 
0.1%
450598.470063263 9
 
0.1%
452706.897879436 8
 
0.1%
451689.782780181 6
 
0.1%
451887.51214766 6
 
0.1%
448775.751543649 5
 
0.1%
451973.905769526 5
 
0.1%
445622.784336132 5
 
0.1%
445841.377603245 5
 
0.1%
Other values (7220) 9806
98.1%
(Missing) 124
 
1.2%
ValueCountFrequency (%)
436888.773525926 2
< 0.1%
436891.0 1
 
< 0.1%
436946.358720615 2
< 0.1%
437602.625094324 1
 
< 0.1%
437653.308606196 1
 
< 0.1%
437759.995574674 1
 
< 0.1%
437811.811502379 1
 
< 0.1%
437818.53216611 3
< 0.1%
437938.827513414 1
 
< 0.1%
437945.283977421 1
 
< 0.1%
ValueCountFrequency (%)
465076.350406458 1
 
< 0.1%
464959.058464501 2
< 0.1%
464949.868090487 2
< 0.1%
464947.538929422 3
< 0.1%
464945.364582841 1
 
< 0.1%
464923.878757013 1
 
< 0.1%
464814.717432497 1
 
< 0.1%
464630.505734089 3
< 0.1%
464591.516973411 1
 
< 0.1%
464509.429001456 1
 
< 0.1%

판매점영업면적
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct637
Distinct (%)20.2%
Missing6853
Missing (%)68.5%
Infinite0
Infinite (%)0.0%
Mean70.912224
Minimum0
Maximum58361
Zeros737
Zeros (%)7.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-06T20:11:51.321677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q116.5
median49.5
Q366
95-th percentile119.7
Maximum58361
Range58361
Interquartile range (IQR)49.5

Descriptive statistics

Standard deviation1070.8717
Coefficient of variation (CV)15.101369
Kurtosis2802.7578
Mean70.912224
Median Absolute Deviation (MAD)19.8
Skewness52.047396
Sum223160.77
Variance1146766.1
MonotonicityNot monotonic
2024-04-06T20:11:51.562366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 737
 
7.4%
66.0 154
 
1.5%
49.5 148
 
1.5%
33.0 125
 
1.2%
50.0 77
 
0.8%
60.0 59
 
0.6%
39.6 42
 
0.4%
59.4 39
 
0.4%
99.0 35
 
0.4%
42.9 32
 
0.3%
Other values (627) 1699
 
17.0%
(Missing) 6853
68.5%
ValueCountFrequency (%)
0.0 737
7.4%
1.65 1
 
< 0.1%
2.0 1
 
< 0.1%
3.0 5
 
0.1%
3.3 16
 
0.2%
5.0 4
 
< 0.1%
6.0 1
 
< 0.1%
6.06 1
 
< 0.1%
6.6 3
 
< 0.1%
7.0 2
 
< 0.1%
ValueCountFrequency (%)
58361.0 1
< 0.1%
14329.0 1
< 0.1%
463.0 1
< 0.1%
424.79 1
< 0.1%
333.0 1
< 0.1%
315.38 1
< 0.1%
270.6 1
< 0.1%
265.0 1
< 0.1%
260.0 1
< 0.1%
233.72 1
< 0.1%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)판매점영업면적
109383180000PHMH32016318003408750004620160701<NA>3폐업3폐업20230117<NA><NA><NA><NA><NA><NA>서울특별시 영등포구 대림동 695번지서울특별시 영등포구 도림로47길 1 (대림동, 우성아파트)07410(주)코리아세븐 대림로점2023-01-17 16:25:04U2022-11-30 23:09:00.0<NA>191088.099791443718.459773<NA>
22293000000PHMH32017300003408750002620170719201802143폐업3폐업20180214<NA><NA><NA><NA><NA><NA><NA>서울특별시 종로구 청계천로 331, 제라동 나열1층 6호 (창신동, 동대문상가,일신파워빌딩)03120씨유종로청계점2018-02-14 15:45:23I2018-08-31 23:59:59.0<NA>201236.543011451980.76162233.0
100923160000PHMH32015316003408750002620150730<NA>3폐업3폐업20170720<NA><NA><NA><NA><NA>152101서울특별시 구로구 오류동 156번지 100호서울특별시 구로구 오류로8길 6 (오류동)08343GS25 오류타운점2017-07-20 13:52:19I2018-08-31 23:59:59.0<NA>185867.982685443187.33699833.0
16023170000PHMH3202331700350875000022023-02-06<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 금천구 시흥동 818-6서울특별시 금천구 독산로24길 15, 1층 (시흥동)08570지에스(GS25)금천독산로점2023-02-06 09:44:20I2022-12-02 00:08:00.0<NA>191681.829135439234.409011<NA>
109023180000PHMH32015318003408750001220150319<NA>1영업/정상13영업중<NA><NA><NA><NA>782-3340<NA>150885서울특별시 영등포구 여의도동 35번지 5호 107호서울특별시 영등포구 여의나루로 42, 107호 (여의도동)07328씨유 여의도역점2017-07-07 15:37:25I2018-08-31 23:59:59.0<NA>193306.330044446582.78231142.9
35523040000PHMH32015304003308750003220150730<NA>3폐업3폐업20221201<NA><NA><NA><NA><NA>143150서울특별시 광진구 군자동 474번지 28호서울특별시 광진구 능동로31길 22, 1층 (군자동)04996세븐일레븐 군자하나점2022-12-01 17:08:11U2021-11-02 00:03:00.0<NA>206768.458793450417.771366<NA>
116433190000PHMH32014319003308750001920141008<NA>3폐업3폐업20191004<NA><NA><NA><NA><NA><NA><NA>서울특별시 동작구 등용로 80 (대방동, 한뜻학원)06933씨유 대방등용점2019-10-04 17:07:10U2019-10-06 02:40:00.0<NA>193951.147644445124.07507256.1
49433060000PHMH32020306003408750002220200720<NA>3폐업3폐업20220718<NA><NA><NA><NA><NA><NA>서울특별시 중랑구 신내동 262-1서울특별시 중랑구 신내역로3길 40-36, 신내데시앙플렉스 지하1층 RB123,RB124호 (신내동)02055씨유 중랑데시앙플렉스점2022-07-18 16:40:34U2021-12-06 22:00:00.0<NA>209085.926142457283.215342<NA>
20403000000PHMH32012300003408750012720121127201405303폐업3폐업20140530<NA><NA><NA>02-766-0409<NA>110450서울특별시 종로구 원남동 282번지서울특별시 종로구 창경궁로 133 (원남동)110450ANY252014-05-30 17:46:21I2018-08-31 23:59:59.0<NA>199689.745659452449.278783<NA>
20793080000PHMH32022308003308750000720220516<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강북구 번동 526-13서울특별시 강북구 덕릉로40길 18, 1층 (번동)01139지에스(GS)25 강북최고점2022-05-16 17:23:16I2021-12-04 23:08:00.0<NA>202614.011916459104.631099<NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)판매점영업면적
20413000000PHMH32015300003408750001820150708201711283폐업3폐업20171128<NA><NA><NA>02-732-7397<NA>110160서울특별시 종로구 공평동 124번지 1호 1층서울특별시 종로구 삼봉로 100, 1층 (공평동)03158씨유 종로 공평점2017-11-28 17:46:36I2018-08-31 23:59:59.0<NA>198405.973333452183.450333<NA>
104443170000PHMH3202131700350875000082021-04-09<NA>3폐업3폐업2024-02-16<NA><NA><NA><NA><NA><NA><NA>서울특별시 금천구 디지털로9길 46, 이앤씨드림타워7차 104호 (가산동)08512씨유 가산ENC72024-02-16 10:05:05U2023-12-01 23:08:00.0<NA>189943.546219441990.817437<NA>
60883090000PHMH32019309003308750001120190402<NA>1영업/정상13영업중<NA><NA><NA><NA>02-903-9902<NA><NA>서울특별시 도봉구 쌍문동 723번지 신원주상복합2차아파트 102호서울특별시 도봉구 해등로 190, 1층 102호 (쌍문동, 신원주상복합2차아파트)01394GS25쌍문신원점2019-04-02 17:33:27I2019-04-04 02:20:12.0<NA>203089.442774461770.48875958.8
22983000000PHMH32019300003408750001020190430<NA>3폐업3폐업20190514<NA><NA><NA>07077656473<NA><NA>서울특별시 종로구 신문로1가 58번지 18호 목영빌딩 1층 101호서울특별시 종로구 경희궁길 4, 목영빌딩 1층 101호 (신문로1가)03175주식회사 비지에프리테일 종로경희궁점2019-05-14 14:30:39U2019-05-16 02:40:00.0<NA>197469.959025452033.989112<NA>
132473240000PHMH32021324003308750000520210210<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강동구 길동 97서울특별시 강동구 명일로19길 12, 1층 (길동)05344세븐일레븐 길동해그린점2021-02-10 14:55:25I2021-02-12 00:23:02.0<NA>212841.775861448597.318159<NA>
83753130000PHMH32016313003308750007320161205<NA>3폐업3폐업20201228<NA><NA><NA><NA><NA><NA>서울특별시 마포구 상수동 337번지 2호 1층서울특별시 마포구 와우산로3길 21, 1호 (상수동)04074씨유 상수팜팜점2020-12-28 12:36:58U2020-12-30 02:40:00.0<NA>193018.255183449296.3709566.0
108373180000PHMH32013318003408750003720130617<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA>150040서울특별시 영등포구 당산동 376번지서울특별시 영등포구 버드나루로 130 (당산동)07225지에스25 당산강변점2013-11-15 11:38:03I2018-08-31 23:59:59.0<NA>191819.261328447513.14293266.0
35033030000PHMH32018303003308750001320180510<NA>3폐업3폐업20200121<NA><NA><NA>4018-0401<NA><NA>서울특별시 성동구 성수동2가 333번지 15호 서울숲 한라시그마밸리Ⅱ 103~4호서울특별시 성동구 성수이로7길 7, 서울숲 한라시그마밸리Ⅱ 103~4호 (성수동2가)04781이마트24 성수한라점2020-01-21 18:18:53U2020-01-23 02:40:00.0<NA>204749.401115448614.910605<NA>
12913150000PHMH3202431500370875000052024-01-16<NA>3폐업3폐업2024-01-18<NA><NA><NA><NA><NA><NA>서울특별시 강서구 마곡동 744 마곡 엠밸리 9단지서울특별시 강서구 공항대로 103, 3동 101호 (마곡동, 마곡 엠밸리 9단지)07600지에스25(GS25) 강서마곡점2024-01-18 18:03:14U2023-11-30 22:00:00.0<NA><NA><NA><NA>
152423230000PHMH32015323003408750002620150423<NA>3폐업3폐업20180307<NA><NA><NA>02-419-5508<NA>138863서울특별시 송파구 잠실동 214번지 7호 1층서울특별시 송파구 올림픽로12길 52 (잠실동)05569GS25잠실잠전2018-03-07 15:38:10I2018-08-31 23:59:59.0<NA>207296.538805444989.836108<NA>