Overview

Dataset statistics

Number of variables29
Number of observations10000
Missing cells65654
Missing cells (%)22.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 MiB
Average record size in memory252.0 B

Variable types

Categorical10
Numeric5
DateTime7
Text6
Unsupported1

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),자산규모,부채총액,자본금,판매방식명
Author서대문구
URLhttps://data.seoul.go.kr/dataList/OA-18814/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 is highly imbalanced (98.7%)Imbalance
자산규모 is highly imbalanced (54.0%)Imbalance
부채총액 is highly imbalanced (54.0%)Imbalance
자본금 is highly imbalanced (54.0%)Imbalance
판매방식명 is highly imbalanced (72.8%)Imbalance
폐업일자 has 6744 (67.4%) missing valuesMissing
휴업시작일자 has 9956 (99.6%) missing valuesMissing
휴업종료일자 has 9956 (99.6%) missing valuesMissing
재개업일자 has 9992 (99.9%) missing valuesMissing
전화번호 has 6601 (66.0%) missing valuesMissing
소재지면적 has 10000 (100.0%) missing valuesMissing
소재지우편번호 has 8343 (83.4%) missing valuesMissing
도로명주소 has 816 (8.2%) missing valuesMissing
도로명우편번호 has 1892 (18.9%) missing valuesMissing
좌표정보(X) has 659 (6.6%) missing valuesMissing
좌표정보(Y) has 659 (6.6%) missing valuesMissing
소재지우편번호 is highly skewed (γ1 = 27.70791261)Skewed
관리번호 has unique valuesUnique
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-11 02:08:30.694139
Analysis finished2024-05-11 02:08:37.247828
Duration6.55 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3120000
10000 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3120000
2nd row3120000
3rd row3120000
4th row3120000
5th row3120000

Common Values

ValueCountFrequency (%)
3120000 10000
100.0%

Length

2024-05-11T02:08:37.441491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:08:37.826406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3120000 10000
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0176098 × 1018
Minimum2.002312 × 1018
Maximum2.024312 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T02:08:38.179163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.002312 × 1018
5-th percentile2.006312 × 1018
Q12.014312 × 1018
median2.019312 × 1018
Q32.022312 × 1018
95-th percentile2.023312 × 1018
Maximum2.024312 × 1018
Range2.2000011 × 1016
Interquartile range (IQR)8.0000047 × 1015

Descriptive statistics

Standard deviation5.5218838 × 1015
Coefficient of variation (CV)0.0027368442
Kurtosis-0.4603713
Mean2.0176098 × 1018
Median Absolute Deviation (MAD)3 × 1015
Skewness-0.85975985
Sum-4.6398399 × 1018
Variance3.04912 × 1031
MonotonicityNot monotonic
2024-05-11T02:08:38.585485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2009312011930200323 1
 
< 0.1%
2020312019230201102 1
 
< 0.1%
2016312018330200651 1
 
< 0.1%
2010312011930200395 1
 
< 0.1%
2016312018330200677 1
 
< 0.1%
2014312014530200267 1
 
< 0.1%
2015312018330200309 1
 
< 0.1%
2018312019230200291 1
 
< 0.1%
2011312014530200549 1
 
< 0.1%
2016312018330200713 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
2002312010723200028 1
< 0.1%
2002312010723200033 1
< 0.1%
2002312010723200042 1
< 0.1%
2002312010723200062 1
< 0.1%
2002312010723200085 1
< 0.1%
2002312010723200091 1
< 0.1%
2002312010723200096 1
< 0.1%
2002312010723200099 1
< 0.1%
2002312010723200111 1
< 0.1%
2002312010723200119 1
< 0.1%
ValueCountFrequency (%)
2024312021930200666 1
< 0.1%
2024312021930200664 1
< 0.1%
2024312021930200662 1
< 0.1%
2024312021930200660 1
< 0.1%
2024312021930200658 1
< 0.1%
2024312021930200656 1
< 0.1%
2024312021930200655 1
< 0.1%
2024312021930200653 1
< 0.1%
2024312021930200652 1
< 0.1%
2024312021930200651 1
< 0.1%

인허가일자
Date

Distinct3466
Distinct (%)34.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2000-04-14 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T02:08:38.897273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:08:39.270843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9980 
20080918
 
19
20181227
 
1

Length

Max length8
Median length4
Mean length4.008
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 9980
99.8%
20080918 19
 
0.2%
20181227 1
 
< 0.1%

Length

2024-05-11T02:08:39.712312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:08:40.066170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9980
99.8%
20080918 19
 
0.2%
20181227 1
 
< 0.1%

영업상태코드
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
4671 
3
2604 
4
2005 
5
691 
2
 
29

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row1
4th row3
5th row4

Common Values

ValueCountFrequency (%)
1 4671
46.7%
3 2604
26.0%
4 2005
20.1%
5 691
 
6.9%
2 29
 
0.3%

Length

2024-05-11T02:08:40.420788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:08:40.756621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 4671
46.7%
3 2604
26.0%
4 2005
20.1%
5 691
 
6.9%
2 29
 
0.3%

영업상태명
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
영업/정상
4671 
폐업
2604 
취소/말소/만료/정지/중지
2005 
제외/삭제/전출
691 
휴업
 
29

Length

Max length14
Median length8
Mean length6.2219
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row폐업
2nd row폐업
3rd row영업/정상
4th row폐업
5th row취소/말소/만료/정지/중지

Common Values

ValueCountFrequency (%)
영업/정상 4671
46.7%
폐업 2604
26.0%
취소/말소/만료/정지/중지 2005
20.1%
제외/삭제/전출 691
 
6.9%
휴업 29
 
0.3%

Length

2024-05-11T02:08:41.109353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:08:41.537435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 4671
46.7%
폐업 2604
26.0%
취소/말소/만료/정지/중지 2005
20.1%
제외/삭제/전출 691
 
6.9%
휴업 29
 
0.3%

상세영업상태코드
Real number (ℝ)

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.9986
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T02:08:41.773548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q35
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.3081878
Coefficient of variation (CV)0.76975514
Kurtosis-0.90418463
Mean2.9986
Median Absolute Deviation (MAD)2
Skewness0.77698034
Sum29986
Variance5.3277308
MonotonicityNot monotonic
2024-05-11T02:08:42.107937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 4668
46.7%
3 2604
26.0%
7 1985
19.9%
5 691
 
6.9%
2 29
 
0.3%
4 20
 
0.2%
6 3
 
< 0.1%
ValueCountFrequency (%)
1 4668
46.7%
2 29
 
0.3%
3 2604
26.0%
4 20
 
0.2%
5 691
 
6.9%
6 3
 
< 0.1%
7 1985
19.9%
ValueCountFrequency (%)
7 1985
19.9%
6 3
 
< 0.1%
5 691
 
6.9%
4 20
 
0.2%
3 2604
26.0%
2 29
 
0.3%
1 4668
46.7%

상세영업상태명
Categorical

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
정상영업
4668 
폐업처리
2604 
직권말소
1985 
타시군구이관
691 
휴업처리
 
29
Other values (2)
 
23

Length

Max length6
Median length4
Mean length4.1388
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row폐업처리
2nd row폐업처리
3rd row정상영업
4th row폐업처리
5th row직권말소

Common Values

ValueCountFrequency (%)
정상영업 4668
46.7%
폐업처리 2604
26.0%
직권말소 1985
19.9%
타시군구이관 691
 
6.9%
휴업처리 29
 
0.3%
직권취소 20
 
0.2%
타시군구전입 3
 
< 0.1%

Length

2024-05-11T02:08:42.543346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:08:43.000989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상영업 4668
46.7%
폐업처리 2604
26.0%
직권말소 1985
19.9%
타시군구이관 691
 
6.9%
휴업처리 29
 
0.3%
직권취소 20
 
0.2%
타시군구전입 3
 
< 0.1%

폐업일자
Date

MISSING 

Distinct1849
Distinct (%)56.8%
Missing6744
Missing (%)67.4%
Memory size156.2 KiB
Minimum2007-05-31 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T02:08:43.364679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:08:43.787242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Date

MISSING 

Distinct44
Distinct (%)100.0%
Missing9956
Missing (%)99.6%
Memory size156.2 KiB
Minimum2008-05-21 00:00:00
Maximum2024-04-22 00:00:00
2024-05-11T02:08:44.194963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:08:44.645900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)

휴업종료일자
Date

MISSING 

Distinct43
Distinct (%)97.7%
Missing9956
Missing (%)99.6%
Memory size156.2 KiB
Minimum2008-09-26 00:00:00
Maximum2033-12-31 00:00:00
2024-05-11T02:08:45.056417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:08:45.483370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)

재개업일자
Date

MISSING 

Distinct8
Distinct (%)100.0%
Missing9992
Missing (%)99.9%
Memory size156.2 KiB
Minimum2010-01-21 00:00:00
Maximum2023-09-18 00:00:00
2024-05-11T02:08:45.806068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:08:46.171140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)

전화번호
Text

MISSING 

Distinct3134
Distinct (%)92.2%
Missing6601
Missing (%)66.0%
Memory size156.2 KiB
2024-05-11T02:08:46.872547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length10.884378
Min length1

Characters and Unicode

Total characters36996
Distinct characters16
Distinct categories6 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3060 ?
Unique (%)90.0%

Sample

1st row070-7590-5067
2nd row02-
3rd row070-8863-7321
4th row070-4531-1035
5th row312-7857
ValueCountFrequency (%)
02 752
 
16.4%
28
 
0.6%
363 27
 
0.6%
394 24
 
0.5%
393 22
 
0.5%
364 19
 
0.4%
312 19
 
0.4%
365 18
 
0.4%
3216 17
 
0.4%
313 16
 
0.3%
Other values (3246) 3643
79.5%
2024-05-11T02:08:48.165985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5935
16.0%
- 4840
13.1%
2 4705
12.7%
3 4074
11.0%
7 3041
8.2%
1 2295
 
6.2%
6 2271
 
6.1%
5 2023
 
5.5%
4 1997
 
5.4%
8 1997
 
5.4%
Other values (6) 3818
10.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 30270
81.8%
Dash Punctuation 4840
 
13.1%
Space Separator 1866
 
5.0%
Other Punctuation 12
 
< 0.1%
Math Symbol 5
 
< 0.1%
Close Punctuation 3
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5935
19.6%
2 4705
15.5%
3 4074
13.5%
7 3041
10.0%
1 2295
 
7.6%
6 2271
 
7.5%
5 2023
 
6.7%
4 1997
 
6.6%
8 1997
 
6.6%
9 1932
 
6.4%
Other Punctuation
ValueCountFrequency (%)
. 10
83.3%
, 2
 
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 4840
100.0%
Space Separator
ValueCountFrequency (%)
1866
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 36996
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5935
16.0%
- 4840
13.1%
2 4705
12.7%
3 4074
11.0%
7 3041
8.2%
1 2295
 
6.2%
6 2271
 
6.1%
5 2023
 
5.5%
4 1997
 
5.4%
8 1997
 
5.4%
Other values (6) 3818
10.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 36996
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5935
16.0%
- 4840
13.1%
2 4705
12.7%
3 4074
11.0%
7 3041
8.2%
1 2295
 
6.2%
6 2271
 
6.1%
5 2023
 
5.5%
4 1997
 
5.4%
8 1997
 
5.4%
Other values (6) 3818
10.3%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

소재지우편번호
Real number (ℝ)

MISSING  SKEWED 

Distinct147
Distinct (%)8.9%
Missing8343
Missing (%)83.4%
Infinite0
Infinite (%)0.0%
Mean120846.2
Minimum100080
Maximum463010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T02:08:48.787849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100080
5-th percentile120030
Q1120101
median120140
Q3120781
95-th percentile120855
Maximum463010
Range362930
Interquartile range (IQR)680

Descriptive statistics

Standard deviation11502.734
Coefficient of variation (CV)0.095184907
Kurtosis788.04811
Mean120846.2
Median Absolute Deviation (MAD)50
Skewness27.707913
Sum2.0024216 × 108
Variance1.323129 × 108
MonotonicityNot monotonic
2024-05-11T02:08:49.665478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
120110 184
 
1.8%
120170 121
 
1.2%
120180 107
 
1.1%
120090 99
 
1.0%
120100 96
 
1.0%
120190 74
 
0.7%
120120 69
 
0.7%
120130 64
 
0.6%
120030 58
 
0.6%
120091 43
 
0.4%
Other values (137) 742
 
7.4%
(Missing) 8343
83.4%
ValueCountFrequency (%)
100080 1
 
< 0.1%
120012 38
0.4%
120013 34
0.3%
120020 4
 
< 0.1%
120030 58
0.6%
120040 20
 
0.2%
120050 4
 
< 0.1%
120060 3
 
< 0.1%
120070 5
 
0.1%
120080 3
 
< 0.1%
ValueCountFrequency (%)
463010 1
< 0.1%
430040 1
< 0.1%
158050 1
< 0.1%
150093 1
< 0.1%
150050 1
< 0.1%
140080 2
< 0.1%
140012 1
< 0.1%
138170 1
< 0.1%
136100 1
< 0.1%
136090 1
< 0.1%

지번주소
Text

Distinct3509
Distinct (%)35.2%
Missing36
Missing (%)0.4%
Memory size156.2 KiB
2024-05-11T02:08:50.420480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length50
Mean length25.442393
Min length5

Characters and Unicode

Total characters253508
Distinct characters497
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2634 ?
Unique (%)26.4%

Sample

1st row서울특별시 서대문구 홍제동 **번지 **통 *반 홍제한양아파트 ***동 ***호
2nd row서울특별시 서대문구 충정로*가 ***번지 *호
3rd row서울특별시 서대문구 남가좌동 *** DMC에코자이
4th row서울특별시 서대문구 충정로*가 ** 정성빌라
5th row서울특별시 서대문구 연희동 ***번지 **통 *반 오성빌라 나동 ***호
ValueCountFrequency (%)
서울특별시 9349
18.6%
서대문구 9327
18.5%
4910
9.8%
호 4688
9.3%
번지 4647
9.2%
창천동 1589
 
3.2%
연희동 1456
 
2.9%
홍은동 1283
 
2.6%
홍제동 1102
 
2.2%
북가좌동 1017
 
2.0%
Other values (2101) 10914
21.7%
2024-05-11T02:08:52.135659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 47403
18.7%
40544
16.0%
서 18751
 
7.4%
대 10520
 
4.1%
동 10360
 
4.1%
문 9496
 
3.7%
시 9464
 
3.7%
구 9412
 
3.7%
울 9377
 
3.7%
별 9350
 
3.7%
Other values (487) 78831
31.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 158111
62.4%
Other Punctuation 47561
 
18.8%
Space Separator 40544
 
16.0%
Dash Punctuation 4106
 
1.6%
Uppercase Letter 1499
 
0.6%
Decimal Number 1433
 
0.6%
Lowercase Letter 179
 
0.1%
Close Punctuation 31
 
< 0.1%
Open Punctuation 31
 
< 0.1%
Math Symbol 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 18751
 
11.9%
대 10520
 
6.7%
동 10360
 
6.6%
문 9496
 
6.0%
시 9464
 
6.0%
구 9412
 
6.0%
울 9377
 
5.9%
별 9350
 
5.9%
특 9349
 
5.9%
지 5204
 
3.3%
Other values (419) 56828
35.9%
Uppercase Letter
ValueCountFrequency (%)
C 337
22.5%
M 331
22.1%
D 329
21.9%
B 96
 
6.4%
A 82
 
5.5%
K 63
 
4.2%
S 48
 
3.2%
I 33
 
2.2%
P 27
 
1.8%
R 25
 
1.7%
Other values (15) 128
 
8.5%
Lowercase Letter
ValueCountFrequency (%)
e 109
60.9%
s 12
 
6.7%
k 8
 
4.5%
o 7
 
3.9%
i 6
 
3.4%
h 4
 
2.2%
a 4
 
2.2%
l 4
 
2.2%
w 3
 
1.7%
p 3
 
1.7%
Other values (10) 19
 
10.6%
Decimal Number
ValueCountFrequency (%)
1 268
18.7%
3 223
15.6%
2 185
12.9%
0 167
11.7%
4 137
9.6%
5 134
9.4%
7 93
 
6.5%
8 91
 
6.4%
6 70
 
4.9%
9 65
 
4.5%
Other Punctuation
ValueCountFrequency (%)
* 47403
99.7%
, 102
 
0.2%
@ 46
 
0.1%
. 5
 
< 0.1%
& 4
 
< 0.1%
# 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
Ⅱ 5
83.3%
Ⅲ 1
 
16.7%
Space Separator
ValueCountFrequency (%)
40544
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4106
100.0%
Close Punctuation
ValueCountFrequency (%)
) 31
100.0%
Open Punctuation
ValueCountFrequency (%)
( 31
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 158109
62.4%
Common 93713
37.0%
Latin 1684
 
0.7%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 18751
 
11.9%
대 10520
 
6.7%
동 10360
 
6.6%
문 9496
 
6.0%
시 9464
 
6.0%
구 9412
 
6.0%
울 9377
 
5.9%
별 9350
 
5.9%
특 9349
 
5.9%
지 5204
 
3.3%
Other values (418) 56826
35.9%
Latin
ValueCountFrequency (%)
C 337
20.0%
M 331
19.7%
D 329
19.5%
e 109
 
6.5%
B 96
 
5.7%
A 82
 
4.9%
K 63
 
3.7%
S 48
 
2.9%
I 33
 
2.0%
P 27
 
1.6%
Other values (37) 229
13.6%
Common
ValueCountFrequency (%)
* 47403
50.6%
40544
43.3%
- 4106
 
4.4%
1 268
 
0.3%
3 223
 
0.2%
2 185
 
0.2%
0 167
 
0.2%
4 137
 
0.1%
5 134
 
0.1%
, 102
 
0.1%
Other values (11) 444
 
0.5%
Han
ValueCountFrequency (%)
休 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 158109
62.4%
ASCII 95391
37.6%
Number Forms 6
 
< 0.1%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 47403
49.7%
40544
42.5%
- 4106
 
4.3%
C 337
 
0.4%
M 331
 
0.3%
D 329
 
0.3%
1 268
 
0.3%
3 223
 
0.2%
2 185
 
0.2%
0 167
 
0.2%
Other values (56) 1498
 
1.6%
Hangul
ValueCountFrequency (%)
서 18751
 
11.9%
대 10520
 
6.7%
동 10360
 
6.6%
문 9496
 
6.0%
시 9464
 
6.0%
구 9412
 
6.0%
울 9377
 
5.9%
별 9350
 
5.9%
특 9349
 
5.9%
지 5204
 
3.3%
Other values (418) 56826
35.9%
Number Forms
ValueCountFrequency (%)
Ⅱ 5
83.3%
Ⅲ 1
 
16.7%
CJK
ValueCountFrequency (%)
休 2
100.0%

도로명주소
Text

MISSING 

Distinct5261
Distinct (%)57.3%
Missing816
Missing (%)8.2%
Memory size156.2 KiB
2024-05-11T02:08:53.016445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length52
Mean length36.375327
Min length22

Characters and Unicode

Total characters334071
Distinct characters531
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

Unique4109 ?
Unique (%)44.7%

Sample

1st row서울특별시 서대문구 충정로 ** (충정로*가)
2nd row서울특별시 서대문구 거북골로 **, ***동 ***호 (남가좌동, DMC에코자이)
3rd row서울특별시 서대문구 충정로**길 **, *층 (충정로*가)
4th row서울특별시 서대문구 연희로**길 **-*, 나동 ***호 (연희동,오성빌라)
5th row서울특별시 서대문구 홍은중앙로 **, ***동 ****호 (홍은동,동일아파트)
ValueCountFrequency (%)
서울특별시 9181
14.8%
서대문구 9157
14.7%
8794
14.2%
호 5355
 
8.6%
층 2943
 
4.7%
동 1650
 
2.7%
창천동 1558
 
2.5%
연희동 1328
 
2.1%
홍은동 1160
 
1.9%
신촌로 1063
 
1.7%
Other values (2721) 19913
32.1%
2024-05-11T02:08:54.351556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 55448
16.6%
53108
 
15.9%
서 18720
 
5.6%
동 11274
 
3.4%
, 11254
 
3.4%
대 11101
 
3.3%
문 9832
 
2.9%
울 9495
 
2.8%
시 9308
 
2.8%
구 9240
 
2.8%
Other values (521) 135291
40.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 189640
56.8%
Other Punctuation 66714
 
20.0%
Space Separator 53108
 
15.9%
Close Punctuation 9205
 
2.8%
Open Punctuation 9204
 
2.8%
Dash Punctuation 2230
 
0.7%
Uppercase Letter 1991
 
0.6%
Decimal Number 1743
 
0.5%
Lowercase Letter 217
 
0.1%
Math Symbol 12
 
< 0.1%
Other values (2) 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 18720
 
9.9%
동 11274
 
5.9%
대 11101
 
5.9%
문 9832
 
5.2%
울 9495
 
5.0%
시 9308
 
4.9%
구 9240
 
4.9%
별 9184
 
4.8%
특 9181
 
4.8%
로 8223
 
4.3%
Other values (449) 84082
44.3%
Uppercase Letter
ValueCountFrequency (%)
C 397
19.9%
D 370
18.6%
M 357
17.9%
B 304
15.3%
A 153
 
7.7%
K 60
 
3.0%
S 48
 
2.4%
E 44
 
2.2%
G 41
 
2.1%
I 32
 
1.6%
Other values (15) 185
9.3%
Lowercase Letter
ValueCountFrequency (%)
e 123
56.7%
o 15
 
6.9%
b 12
 
5.5%
a 10
 
4.6%
i 10
 
4.6%
h 6
 
2.8%
l 6
 
2.8%
n 5
 
2.3%
u 4
 
1.8%
s 4
 
1.8%
Other values (13) 22
 
10.1%
Decimal Number
ValueCountFrequency (%)
1 397
22.8%
2 321
18.4%
0 243
13.9%
3 204
11.7%
5 141
 
8.1%
4 133
 
7.6%
7 95
 
5.5%
6 85
 
4.9%
9 72
 
4.1%
8 52
 
3.0%
Other Punctuation
ValueCountFrequency (%)
* 55448
83.1%
, 11254
 
16.9%
. 6
 
< 0.1%
& 4
 
< 0.1%
/ 1
 
< 0.1%
# 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
Ⅱ 5
83.3%
Ⅲ 1
 
16.7%
Space Separator
ValueCountFrequency (%)
53108
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9205
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9204
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2230
100.0%
Math Symbol
ValueCountFrequency (%)
~ 12
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 189638
56.8%
Common 142217
42.6%
Latin 2214
 
0.7%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 18720
 
9.9%
동 11274
 
5.9%
대 11101
 
5.9%
문 9832
 
5.2%
울 9495
 
5.0%
시 9308
 
4.9%
구 9240
 
4.9%
별 9184
 
4.8%
특 9181
 
4.8%
로 8223
 
4.3%
Other values (448) 84080
44.3%
Latin
ValueCountFrequency (%)
C 397
17.9%
D 370
16.7%
M 357
16.1%
B 304
13.7%
A 153
 
6.9%
e 123
 
5.6%
K 60
 
2.7%
S 48
 
2.2%
E 44
 
2.0%
G 41
 
1.9%
Other values (40) 317
14.3%
Common
ValueCountFrequency (%)
* 55448
39.0%
53108
37.3%
, 11254
 
7.9%
) 9205
 
6.5%
( 9204
 
6.5%
- 2230
 
1.6%
1 397
 
0.3%
2 321
 
0.2%
0 243
 
0.2%
3 204
 
0.1%
Other values (12) 603
 
0.4%
Han
ValueCountFrequency (%)
休 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 189638
56.8%
ASCII 144425
43.2%
Number Forms 6
 
< 0.1%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 55448
38.4%
53108
36.8%
, 11254
 
7.8%
) 9205
 
6.4%
( 9204
 
6.4%
- 2230
 
1.5%
1 397
 
0.3%
C 397
 
0.3%
D 370
 
0.3%
M 357
 
0.2%
Other values (60) 2455
 
1.7%
Hangul
ValueCountFrequency (%)
서 18720
 
9.9%
동 11274
 
5.9%
대 11101
 
5.9%
문 9832
 
5.2%
울 9495
 
5.0%
시 9308
 
4.9%
구 9240
 
4.9%
별 9184
 
4.8%
특 9181
 
4.8%
로 8223
 
4.3%
Other values (448) 84080
44.3%
Number Forms
ValueCountFrequency (%)
Ⅱ 5
83.3%
Ⅲ 1
 
16.7%
CJK
ValueCountFrequency (%)
休 2
100.0%

도로명우편번호
Text

MISSING 

Distinct344
Distinct (%)4.2%
Missing1892
Missing (%)18.9%
Memory size156.2 KiB
2024-05-11T02:08:55.476257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.125925
Min length5

Characters and Unicode

Total characters41561
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

Unique58 ?
Unique (%)0.7%

Sample

1st row03742
2nd row03687
3rd row03736
4th row03779
5th row03734
ValueCountFrequency (%)
03785 779
 
9.6%
03766 187
 
2.3%
03650 172
 
2.1%
03786 157
 
1.9%
03709 153
 
1.9%
03787 151
 
1.9%
03730 93
 
1.1%
120110 91
 
1.1%
03707 91
 
1.1%
03741 87
 
1.1%
Other values (334) 6147
75.8%
2024-05-11T02:08:56.893427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10314
24.8%
3 8454
20.3%
7 5789
13.9%
6 4640
11.2%
1 3132
 
7.5%
8 2591
 
6.2%
2 2227
 
5.4%
5 2061
 
5.0%
9 1160
 
2.8%
4 1152
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 41520
99.9%
Dash Punctuation 41
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10314
24.8%
3 8454
20.4%
7 5789
13.9%
6 4640
11.2%
1 3132
 
7.5%
8 2591
 
6.2%
2 2227
 
5.4%
5 2061
 
5.0%
9 1160
 
2.8%
4 1152
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
- 41
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 41561
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10314
24.8%
3 8454
20.3%
7 5789
13.9%
6 4640
11.2%
1 3132
 
7.5%
8 2591
 
6.2%
2 2227
 
5.4%
5 2061
 
5.0%
9 1160
 
2.8%
4 1152
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 41561
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10314
24.8%
3 8454
20.3%
7 5789
13.9%
6 4640
11.2%
1 3132
 
7.5%
8 2591
 
6.2%
2 2227
 
5.4%
5 2061
 
5.0%
9 1160
 
2.8%
4 1152
 
2.8%

사업장명
Text

Distinct9836
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:08:58.120410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length39
Mean length7.1464
Min length1

Characters and Unicode

Total characters71464
Distinct characters1144
Distinct categories12 ?
Distinct scripts5 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9682 ?
Unique (%)96.8%

Sample

1st row쇼핑고스톱
2nd row꽃길
3rd row가가샵
4th row엔알필라테스 1호점
5th row봄날
ValueCountFrequency (%)
주식회사 632
 
4.8%
주 61
 
0.5%
스튜디오 31
 
0.2%
더 28
 
0.2%
컴퍼니 25
 
0.2%
inc 23
 
0.2%
company 23
 
0.2%
코리아 19
 
0.1%
co.,ltd 19
 
0.1%
studio 18
 
0.1%
Other values (11169) 12208
93.3%
2024-05-11T02:08:59.539060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3090
 
4.3%
이 2488
 
3.5%
( 2080
 
2.9%
) 2077
 
2.9%
스 2018
 
2.8%
리 1202
 
1.7%
주 1102
 
1.5%
사 1043
 
1.5%
e 953
 
1.3%
아 944
 
1.3%
Other values (1134) 54467
76.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 47999
67.2%
Lowercase Letter 8767
 
12.3%
Uppercase Letter 6369
 
8.9%
Space Separator 3090
 
4.3%
Open Punctuation 2080
 
2.9%
Close Punctuation 2077
 
2.9%
Decimal Number 528
 
0.7%
Other Punctuation 404
 
0.6%
Other Symbol 88
 
0.1%
Dash Punctuation 43
 
0.1%
Other values (2) 19
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 2488
 
5.2%
스 2018
 
4.2%
리 1202
 
2.5%
주 1102
 
2.3%
사 1043
 
2.2%
아 944
 
2.0%
회 741
 
1.5%
에 738
 
1.5%
트 715
 
1.5%
식 701
 
1.5%
Other values (1051) 36307
75.6%
Lowercase Letter
ValueCountFrequency (%)
e 953
 
10.9%
o 917
 
10.5%
a 767
 
8.7%
i 657
 
7.5%
n 644
 
7.3%
r 573
 
6.5%
l 521
 
5.9%
t 469
 
5.3%
s 419
 
4.8%
m 359
 
4.1%
Other values (16) 2488
28.4%
Uppercase Letter
ValueCountFrequency (%)
A 526
 
8.3%
O 507
 
8.0%
E 453
 
7.1%
S 433
 
6.8%
N 348
 
5.5%
T 347
 
5.4%
I 347
 
5.4%
L 330
 
5.2%
C 328
 
5.1%
M 304
 
4.8%
Other values (16) 2446
38.4%
Other Punctuation
ValueCountFrequency (%)
. 213
52.7%
& 71
 
17.6%
, 47
 
11.6%
' 38
 
9.4%
: 12
 
3.0%
? 10
 
2.5%
/ 4
 
1.0%
# 3
 
0.7%
! 2
 
0.5%
@ 2
 
0.5%
Other values (2) 2
 
0.5%
Decimal Number
ValueCountFrequency (%)
1 101
19.1%
2 95
18.0%
3 69
13.1%
0 65
12.3%
5 41
7.8%
9 39
 
7.4%
8 33
 
6.2%
4 30
 
5.7%
7 29
 
5.5%
6 26
 
4.9%
Math Symbol
ValueCountFrequency (%)
+ 3
60.0%
< 1
 
20.0%
> 1
 
20.0%
Space Separator
ValueCountFrequency (%)
3090
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2080
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2077
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 88
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 43
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 48069
67.3%
Latin 15136
 
21.2%
Common 8241
 
11.5%
Han 15
 
< 0.1%
Hiragana 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 2488
 
5.2%
스 2018
 
4.2%
리 1202
 
2.5%
주 1102
 
2.3%
사 1043
 
2.2%
아 944
 
2.0%
회 741
 
1.5%
에 738
 
1.5%
트 715
 
1.5%
식 701
 
1.5%
Other values (1035) 36377
75.7%
Latin
ValueCountFrequency (%)
e 953
 
6.3%
o 917
 
6.1%
a 767
 
5.1%
i 657
 
4.3%
n 644
 
4.3%
r 573
 
3.8%
A 526
 
3.5%
l 521
 
3.4%
O 507
 
3.3%
t 469
 
3.1%
Other values (42) 8602
56.8%
Common
ValueCountFrequency (%)
3090
37.5%
( 2080
25.2%
) 2077
25.2%
. 213
 
2.6%
1 101
 
1.2%
2 95
 
1.2%
& 71
 
0.9%
3 69
 
0.8%
0 65
 
0.8%
, 47
 
0.6%
Other values (20) 333
 
4.0%
Han
ValueCountFrequency (%)
美 2
13.3%
巨 1
 
6.7%
錄 1
 
6.7%
成 1
 
6.7%
萬 1
 
6.7%
女 1
 
6.7%
龍 1
 
6.7%
吊 1
 
6.7%
進 1
 
6.7%
興 1
 
6.7%
Other values (4) 4
26.7%
Hiragana
ValueCountFrequency (%)
せ 1
33.3%
つ 1
33.3%
な 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 47978
67.1%
ASCII 23377
32.7%
None 88
 
0.1%
CJK 14
 
< 0.1%
Compat Jamo 3
 
< 0.1%
Hiragana 3
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3090
 
13.2%
( 2080
 
8.9%
) 2077
 
8.9%
e 953
 
4.1%
o 917
 
3.9%
a 767
 
3.3%
i 657
 
2.8%
n 644
 
2.8%
r 573
 
2.5%
A 526
 
2.3%
Other values (72) 11093
47.5%
Hangul
ValueCountFrequency (%)
이 2488
 
5.2%
스 2018
 
4.2%
리 1202
 
2.5%
주 1102
 
2.3%
사 1043
 
2.2%
아 944
 
2.0%
회 741
 
1.5%
에 738
 
1.5%
트 715
 
1.5%
식 701
 
1.5%
Other values (1031) 36286
75.6%
None
ValueCountFrequency (%)
㈜ 88
100.0%
CJK
ValueCountFrequency (%)
美 2
14.3%
巨 1
 
7.1%
錄 1
 
7.1%
成 1
 
7.1%
萬 1
 
7.1%
龍 1
 
7.1%
吊 1
 
7.1%
進 1
 
7.1%
興 1
 
7.1%
淸 1
 
7.1%
Other values (3) 3
21.4%
Compat Jamo
ValueCountFrequency (%)
ㄷ 1
33.3%
ㅅ 1
33.3%
ㅠ 1
33.3%
CJK Compat Ideographs
ValueCountFrequency (%)
女 1
100.0%
Hiragana
ValueCountFrequency (%)
せ 1
33.3%
つ 1
33.3%
な 1
33.3%

최종수정일자
Date

Distinct9991
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2007-06-15 16:38:16
Maximum2024-05-09 10:56:11
2024-05-11T02:08:59.981065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:09:00.587183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
I
6688 
U
3312 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 6688
66.9%
U 3312
33.1%

Length

2024-05-11T02:09:01.063519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:09:01.388239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 6688
66.9%
u 3312
33.1%

데이터갱신일자
Date

Distinct1499
Distinct (%)15.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T02:09:02.105294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:09:02.729255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Text

Distinct491
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:09:03.274441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length87
Median length84
Mean length9.3496
Min length1

Characters and Unicode

Total characters93496
Distinct characters51
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique296 ?
Unique (%)3.0%

Sample

1st row의류/패션/잡화/뷰티
2nd row기타
3rd row종합몰 교육/도서/완구/오락 컴퓨터/사무용품 가구/수납용품 의류/패션/잡화/뷰티 자동차/자동차용품
4th row의류/패션/잡화/뷰티
5th row의류/패션/잡화/뷰티
ValueCountFrequency (%)
의류/패션/잡화/뷰티 3969
28.1%
종합몰 3261
23.1%
기타 1750
12.4%
건강/식품 1062
 
7.5%
교육/도서/완구/오락 900
 
6.4%
638
 
4.5%
가구/수납용품 595
 
4.2%
컴퓨터/사무용품 581
 
4.1%
가전 450
 
3.2%
레져/여행/공연 433
 
3.1%
Other values (3) 469
 
3.3%
2024-05-11T02:09:04.449039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 18072
19.3%
4108
 
4.4%
의 3969
 
4.2%
화 3969
 
4.2%
티 3969
 
4.2%
뷰 3969
 
4.2%
류 3969
 
4.2%
잡 3969
 
4.2%
션 3969
 
4.2%
패 3969
 
4.2%
Other values (41) 39564
42.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 70678
75.6%
Other Punctuation 18072
 
19.3%
Space Separator 4108
 
4.4%
Dash Punctuation 638
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 3969
 
5.6%
화 3969
 
5.6%
티 3969
 
5.6%
뷰 3969
 
5.6%
류 3969
 
5.6%
잡 3969
 
5.6%
션 3969
 
5.6%
패 3969
 
5.6%
종 3261
 
4.6%
합 3261
 
4.6%
Other values (38) 32404
45.8%
Other Punctuation
ValueCountFrequency (%)
/ 18072
100.0%
Space Separator
ValueCountFrequency (%)
4108
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 638
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 70678
75.6%
Common 22818
 
24.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 3969
 
5.6%
화 3969
 
5.6%
티 3969
 
5.6%
뷰 3969
 
5.6%
류 3969
 
5.6%
잡 3969
 
5.6%
션 3969
 
5.6%
패 3969
 
5.6%
종 3261
 
4.6%
합 3261
 
4.6%
Other values (38) 32404
45.8%
Common
ValueCountFrequency (%)
/ 18072
79.2%
4108
 
18.0%
- 638
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 70678
75.6%
ASCII 22818
 
24.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 18072
79.2%
4108
 
18.0%
- 638
 
2.8%
Hangul
ValueCountFrequency (%)
의 3969
 
5.6%
화 3969
 
5.6%
티 3969
 
5.6%
뷰 3969
 
5.6%
류 3969
 
5.6%
잡 3969
 
5.6%
션 3969
 
5.6%
패 3969
 
5.6%
종 3261
 
4.6%
합 3261
 
4.6%
Other values (38) 32404
45.8%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct4321
Distinct (%)46.3%
Missing659
Missing (%)6.6%
Infinite0
Infinite (%)0.0%
Mean194257.66
Minimum190684.22
Maximum210198.74
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T02:09:04.981626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum190684.22
5-th percentile192115.92
Q1193501.88
median194033.04
Q3195204.51
95-th percentile196564.3
Maximum210198.74
Range19514.522
Interquartile range (IQR)1702.6378

Descriptive statistics

Standard deviation1324.6751
Coefficient of variation (CV)0.0068191652
Kurtosis4.7629073
Mean194257.66
Median Absolute Deviation (MAD)941.90723
Skewness0.6650337
Sum1.8145608 × 109
Variance1754764
MonotonicityNot monotonic
2024-05-11T02:09:05.873776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
193712.476983727 720
 
7.2%
193946.395220305 137
 
1.4%
194191.552230532 134
 
1.3%
194033.03782295 120
 
1.2%
192672.067512964 110
 
1.1%
193998.104669318 80
 
0.8%
192028.41586192 67
 
0.7%
195057.033841623 65
 
0.7%
196259.480927405 60
 
0.6%
196892.09236853 60
 
0.6%
Other values (4311) 7788
77.9%
(Missing) 659
 
6.6%
ValueCountFrequency (%)
190684.216398175 1
 
< 0.1%
191098.385823469 1
 
< 0.1%
191380.878019415 5
0.1%
191434.887463719 3
< 0.1%
191453.512519269 1
 
< 0.1%
191462.573966707 1
 
< 0.1%
191465.484776927 1
 
< 0.1%
191476.603416955 1
 
< 0.1%
191482.50302055 1
 
< 0.1%
191484.483531908 1
 
< 0.1%
ValueCountFrequency (%)
210198.737995073 1
< 0.1%
209536.653318159 1
< 0.1%
204683.056501747 1
< 0.1%
204201.673896874 1
< 0.1%
203806.897017765 1
< 0.1%
202896.91284225 1
< 0.1%
202769.875844183 1
< 0.1%
200426.003382604 1
< 0.1%
197987.671414294 1
< 0.1%
197374.613688051 1
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct4321
Distinct (%)46.3%
Missing659
Missing (%)6.6%
Infinite0
Infinite (%)0.0%
Mean452274.76
Minimum425564.66
Maximum457797.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T02:09:06.721353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum425564.66
5-th percentile450534.93
Q1450884
median452221.96
Q3453296.21
95-th percentile454786.02
Maximum457797.7
Range32233.044
Interquartile range (IQR)2412.2077

Descriptive statistics

Standard deviation1483.8903
Coefficient of variation (CV)0.0032809488
Kurtosis19.203878
Mean452274.76
Median Absolute Deviation (MAD)1208.8509
Skewness-0.99052748
Sum4.2246986 × 109
Variance2201930.5
MonotonicityNot monotonic
2024-05-11T02:09:07.582058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
450637.010875398 720
 
7.2%
450525.834024158 137
 
1.4%
454194.693044027 134
 
1.3%
450514.653917441 120
 
1.2%
452221.960661496 110
 
1.1%
453150.85412164 80
 
0.8%
452265.952165442 67
 
0.7%
454786.019433577 65
 
0.7%
451698.351672354 60
 
0.6%
450948.915518467 60
 
0.6%
Other values (4311) 7788
77.9%
(Missing) 659
 
6.6%
ValueCountFrequency (%)
425564.655078798 1
< 0.1%
429201.742934126 1
< 0.1%
434904.362535703 1
< 0.1%
440827.53556948 1
< 0.1%
442892.914010425 1
< 0.1%
444114.402903965 1
< 0.1%
444714.322672044 1
< 0.1%
444786.125869275 1
< 0.1%
445021.619966947 1
< 0.1%
445883.474973877 1
< 0.1%
ValueCountFrequency (%)
457797.698904806 1
 
< 0.1%
456287.693876267 1
 
< 0.1%
455973.403559421 1
 
< 0.1%
455922.891075209 2
< 0.1%
455892.807363022 1
 
< 0.1%
455818.263119181 1
 
< 0.1%
455755.483684061 1
 
< 0.1%
455736.252642508 3
< 0.1%
455735.363417848 1
 
< 0.1%
455732.792526116 4
< 0.1%

자산규모
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9029 
0
971 

Length

Max length4
Median length4
Mean length3.7087
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 9029
90.3%
0 971
 
9.7%

Length

2024-05-11T02:09:08.618399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:09:09.188582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9029
90.3%
0 971
 
9.7%

부채총액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9029 
0
971 

Length

Max length4
Median length4
Mean length3.7087
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 9029
90.3%
0 971
 
9.7%

Length

2024-05-11T02:09:09.769116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:09:10.221772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9029
90.3%
0 971
 
9.7%

자본금
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9029 
0
971 

Length

Max length4
Median length4
Mean length3.7087
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 9029
90.3%
0 971
 
9.7%

Length

2024-05-11T02:09:10.600222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:09:10.962267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9029
90.3%
0 971
 
9.7%

판매방식명
Categorical

IMBALANCE 

Distinct23
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5425 
인터넷
4307 
인터넷, 기타
 
84
기타
 
52
TV홈쇼핑, 인터넷
 
32
Other values (18)
 
100

Length

Max length26
Median length4
Mean length3.7121
Min length2

Unique

Unique7 ?
Unique (%)0.1%

Sample

1st row인터넷
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row인터넷

Common Values

ValueCountFrequency (%)
<NA> 5425
54.2%
인터넷 4307
43.1%
인터넷, 기타 84
 
0.8%
기타 52
 
0.5%
TV홈쇼핑, 인터넷 32
 
0.3%
TV홈쇼핑, 인터넷, 카다로그, 신문잡지, 기타 18
 
0.2%
인터넷, 카다로그 14
 
0.1%
인터넷, 카다로그, 기타 12
 
0.1%
TV홈쇼핑 11
 
0.1%
TV홈쇼핑, 인터넷, 카다로그, 신문잡지 7
 
0.1%
Other values (13) 38
 
0.4%

Length

2024-05-11T02:09:11.413980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 5425
52.6%
인터넷 4507
43.7%
기타 183
 
1.8%
tv홈쇼핑 80
 
0.8%
카다로그 73
 
0.7%
신문잡지 51
 
0.5%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)자산규모부채총액자본금판매방식명
22273120000200931201193020032320090701<NA>3폐업3폐업처리20091228<NA><NA><NA>070-7590-5067<NA>120782서울특별시 서대문구 홍제동 **번지 **통 *반 홍제한양아파트 ***동 ***호<NA><NA>쇼핑고스톱2009-12-28 10:09:58I2018-08-31 23:59:59.0의류/패션/잡화/뷰티195259.429273453430.811542<NA><NA><NA>인터넷
88203120000202031201923020006720200116<NA>3폐업3폐업처리20221012<NA><NA><NA><NA><NA><NA>서울특별시 서대문구 충정로*가 ***번지 *호서울특별시 서대문구 충정로 ** (충정로*가)03742꽃길2022-10-13 17:06:56U2021-10-30 23:05:00.0기타196724.281032450979.413366<NA><NA><NA><NA>
120013120000202131201923020138520210721<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 서대문구 남가좌동 *** DMC에코자이서울특별시 서대문구 거북골로 **, ***동 ***호 (남가좌동, DMC에코자이)03687가가샵2021-07-21 14:10:58I2021-12-03 22:02:00.0종합몰 교육/도서/완구/오락 컴퓨터/사무용품 가구/수납용품 의류/패션/잡화/뷰티 자동차/자동차용품192834.889904452702.52553<NA><NA><NA><NA>
13608312000020223120192302009272022-06-17<NA>3폐업3폐업처리2023-02-03<NA><NA><NA><NA><NA><NA>서울특별시 서대문구 충정로*가 ** 정성빌라서울특별시 서대문구 충정로**길 **, *층 (충정로*가)03736엔알필라테스 1호점2023-02-02 15:26:26U2022-12-02 00:04:00.0의류/패션/잡화/뷰티196817.932346451453.499963<NA><NA><NA><NA>
27033120000201031201193020032020100707<NA>4취소/말소/만료/정지/중지7직권말소<NA><NA><NA><NA>02-<NA>120110서울특별시 서대문구 연희동 ***번지 **통 *반 오성빌라 나동 ***호서울특별시 서대문구 연희로**길 **-*, 나동 ***호 (연희동,오성빌라)<NA>봄날2015-06-03 15:44:07I2018-08-31 23:59:59.0의류/패션/잡화/뷰티194421.31522452569.256432<NA><NA><NA>인터넷
24543120000200931201193020058720091230<NA>3폐업3폐업처리20101228<NA><NA><NA>070-8863-7321<NA>120100서울특별시 서대문구 홍은동 ***번지 **통 *반 동일아파트 ***동 ****호서울특별시 서대문구 홍은중앙로 **, ***동 ****호 (홍은동,동일아파트)<NA>에스테틱 센스2010-12-28 18:21:28I2018-08-31 23:59:59.0기타195219.8026455134.654298<NA><NA><NA>인터넷
14797312000020233120192302000332023-01-03<NA>3폐업3폐업처리2024-01-16<NA><NA><NA><NA><NA><NA>서울특별시 서대문구 창천동 **-** 신촌르메이에르타운*서울특별시 서대문구 신촌로 ***, 신촌르메이에르타운* 지하*층 ***-*호 (창천동)03779바이수 브로우바 (Bysoo Brow Bar)2024-01-16 17:36:53U2023-11-30 23:08:00.0의류/패션/잡화/뷰티194474.819384450422.374151<NA><NA><NA><NA>
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15386312000020233120219302005262023-04-04<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 서대문구 충정로*가 ***-**서울특별시 서대문구 충정로*길 ** (충정로*가)03741데이바이데이 (DAYBYDAY)2023-04-04 16:42:38I2022-12-04 00:06:00.0의류/패션/잡화/뷰티196768.244681450933.641946<NA><NA><NA><NA>
15978312000020233120219302011182023-07-28<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 서대문구 북가좌동 *** 북가좌삼호아파트서울특별시 서대문구 거북골로 ***, ***동 ***호 (북가좌동, 북가좌삼호아파트)03690볼매마켓2023-07-28 16:12:12I2022-12-06 21:00:00.0종합몰 가전 컴퓨터/사무용품 가구/수납용품 의류/패션/잡화/뷰티192260.299912452692.508807<NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)자산규모부채총액자본금판매방식명
68703120000201831201833020014920140625<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 서대문구 홍은동 ***번지 *호서울특별시 서대문구 통일로 ***, ***동 ****호 (홍은동)03615아이디어셀 (IDEACELL)2018-02-23 16:28:12I2018-08-31 23:59:59.0컴퓨터/사무용품194755.789839454458.773194<NA><NA><NA>인터넷
14309312000020223120192302016302022-09-05<NA>3폐업3폐업처리2023-08-15<NA><NA><NA><NA><NA><NA>서울특별시 서대문구 연희동 ***-**서울특별시 서대문구 성산로 ***-**, *층 ***호 (연희동)03706연희스토어2023-08-16 10:04:00U2022-12-07 23:08:00.0종합몰193279.477963451636.567661<NA><NA><NA><NA>
15144312000020233120219302002842023-02-21<NA>3폐업3폐업처리2023-03-15<NA><NA><NA><NA><NA><NA>서울특별시 서대문구 홍은동 *** 극동아파트서울특별시 서대문구 포방터**길 **, ***동 ****호 (홍은동, 극동아파트)03601노마드792023-03-15 15:38:17U2022-12-02 23:07:00.0종합몰195591.551749455588.317097<NA><NA><NA><NA>
119793120000202131201923020136220210715<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 서대문구 남가좌동 *-**서울특별시 서대문구 명지대*길 **-*, *층 (남가좌동)03672몰로토브2021-07-15 14:00:06I2021-07-17 00:22:52.0의류/패션/잡화/뷰티193037.859109453427.948832000인터넷
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23343120000200931201193020045120090914<NA>3폐업3폐업처리20100601<NA><NA><NA>02-379-2093<NA>120841서울특별시 서대문구 홍은동 *번지 ***호 **통 *반 *층서울특별시 서대문구 포방터*길 **-** (홍은동,*층)<NA>자연에2010-06-01 20:25:19I2018-08-31 23:59:59.0종합몰195685.078701454899.832456<NA><NA><NA>인터넷
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