Overview

Dataset statistics

Number of variables29
Number of observations470
Missing cells4379
Missing cells (%)32.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory114.9 KiB
Average record size in memory250.3 B

Variable types

Categorical7
Numeric10
DateTime4
Unsupported4
Text4

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
Author강북구
URLhttps://data.seoul.go.kr/dataList/OA-18760/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
휴업시작일자 is highly imbalanced (96.2%)Imbalance
휴업종료일자 is highly imbalanced (96.2%)Imbalance
인허가취소일자 has 414 (88.1%) missing valuesMissing
폐업일자 has 240 (51.1%) missing valuesMissing
재개업일자 has 470 (100.0%) missing valuesMissing
전화번호 has 148 (31.5%) missing valuesMissing
소재지면적 has 470 (100.0%) missing valuesMissing
소재지우편번호 has 244 (51.9%) missing valuesMissing
지번주소 has 42 (8.9%) missing valuesMissing
도로명주소 has 26 (5.5%) missing valuesMissing
도로명우편번호 has 172 (36.6%) missing valuesMissing
업태구분명 has 470 (100.0%) missing valuesMissing
좌표정보(X) has 11 (2.3%) missing valuesMissing
좌표정보(Y) has 11 (2.3%) missing valuesMissing
자산규모 has 397 (84.5%) missing valuesMissing
부채총액 has 397 (84.5%) missing valuesMissing
자본금 has 397 (84.5%) missing valuesMissing
판매방식명 has 470 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
최종수정일자 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
판매방식명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
자산규모 has 34 (7.2%) zerosZeros
부채총액 has 53 (11.3%) zerosZeros
자본금 has 31 (6.6%) zerosZeros

Reproduction

Analysis started2024-05-11 01:51:09.686003
Analysis finished2024-05-11 01:51:11.218479
Duration1.53 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
3080000
470 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3080000
2nd row3080000
3rd row3080000
4th row3080000
5th row3080000

Common Values

ValueCountFrequency (%)
3080000 470
100.0%

Length

2024-05-11T01:51:11.415307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:51:11.758938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3080000 470
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct470
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0122697 × 1018
Minimum1.996308 × 1018
Maximum2.024308 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2024-05-11T01:51:12.259870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.996308 × 1018
5-th percentile2.004308 × 1018
Q12.008308 × 1018
median2.011308 × 1018
Q32.016308 × 1018
95-th percentile2.021308 × 1018
Maximum2.024308 × 1018
Range2.800001 × 1016
Interquartile range (IQR)8.0000047 × 1015

Descriptive statistics

Standard deviation5.465403 × 1015
Coefficient of variation (CV)0.002716039
Kurtosis-0.41266803
Mean2.0122697 × 1018
Median Absolute Deviation (MAD)4 × 1015
Skewness0.13648395
Sum4.9828181 × 1018
Variance2.987063 × 1031
MonotonicityStrictly increasing
2024-05-11T01:51:12.899812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1996308009223200011 1
 
0.2%
2014308013923200016 1
 
0.2%
2015308013923200010 1
 
0.2%
2015308013923200009 1
 
0.2%
2015308013923200008 1
 
0.2%
2015308013923200007 1
 
0.2%
2015308013923200006 1
 
0.2%
2015308013923200005 1
 
0.2%
2015308013923200004 1
 
0.2%
2015308013923200003 1
 
0.2%
Other values (460) 460
97.9%
ValueCountFrequency (%)
1996308009223200011 1
0.2%
1996308009223200021 1
0.2%
1998308009223200033 1
0.2%
1998308009223200036 1
0.2%
1999308009223200042 1
0.2%
1999308009223200048 1
0.2%
2000308009223200001 1
0.2%
2000308009223200012 1
0.2%
2001308009223200055 1
0.2%
2002308009223200066 1
0.2%
ValueCountFrequency (%)
2024308019023200001 1
0.2%
2023308019023200012 1
0.2%
2023308019023200011 1
0.2%
2023308019023200010 1
0.2%
2023308019023200009 1
0.2%
2023308019023200008 1
0.2%
2023308019023200007 1
0.2%
2023308019023200006 1
0.2%
2023308019023200005 1
0.2%
2023308019023200004 1
0.2%

인허가일자
Date

Distinct438
Distinct (%)93.2%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
Minimum1996-09-02 00:00:00
Maximum2024-01-02 00:00:00
2024-05-11T01:51:13.675359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:51:14.194715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)10.7%
Missing414
Missing (%)88.1%
Infinite0
Infinite (%)0.0%
Mean20142458
Minimum20071119
Maximum20170728
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2024-05-11T01:51:14.720558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20071119
5-th percentile20080429
Q120080529
median20170728
Q320170728
95-th percentile20170728
Maximum20170728
Range99609
Interquartile range (IQR)90199

Descriptive statistics

Standard deviation42237.015
Coefficient of variation (CV)0.0020969146
Kurtosis-1.2784984
Mean20142458
Median Absolute Deviation (MAD)0
Skewness-0.85926149
Sum1.1279777 × 109
Variance1.7839654 × 109
MonotonicityNot monotonic
2024-05-11T01:51:15.164202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
20170728 38
 
8.1%
20080429 7
 
1.5%
20080529 6
 
1.3%
20080731 2
 
0.4%
20071119 2
 
0.4%
20140127 1
 
0.2%
(Missing) 414
88.1%
ValueCountFrequency (%)
20071119 2
 
0.4%
20080429 7
 
1.5%
20080529 6
 
1.3%
20080731 2
 
0.4%
20140127 1
 
0.2%
20170728 38
8.1%
ValueCountFrequency (%)
20170728 38
8.1%
20140127 1
 
0.2%
20080731 2
 
0.4%
20080529 6
 
1.3%
20080429 7
 
1.5%
20071119 2
 
0.4%

영업상태코드
Categorical

Distinct5
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
3
227 
4
159 
1
80 
5
 
3
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
3 227
48.3%
4 159
33.8%
1 80
 
17.0%
5 3
 
0.6%
2 1
 
0.2%

Length

2024-05-11T01:51:15.698793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:51:16.165685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 227
48.3%
4 159
33.8%
1 80
 
17.0%
5 3
 
0.6%
2 1
 
0.2%

영업상태명
Categorical

Distinct5
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
폐업
227 
취소/말소/만료/정지/중지
159 
영업/정상
80 
제외/삭제/전출
 
3
휴업
 
1

Length

Max length14
Median length8
Mean length6.6085106
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 227
48.3%
취소/말소/만료/정지/중지 159
33.8%
영업/정상 80
 
17.0%
제외/삭제/전출 3
 
0.6%
휴업 1
 
0.2%

Length

2024-05-11T01:51:16.716937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:51:17.184798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 227
48.3%
취소/말소/만료/정지/중지 159
33.8%
영업/정상 80
 
17.0%
제외/삭제/전출 3
 
0.6%
휴업 1
 
0.2%

상세영업상태코드
Real number (ℝ)

Distinct7
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.6702128
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2024-05-11T01:51:17.498567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median3
Q34
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.9676938
Coefficient of variation (CV)0.53612526
Kurtosis-0.62087069
Mean3.6702128
Median Absolute Deviation (MAD)1
Skewness0.62127231
Sum1725
Variance3.8718187
MonotonicityNot monotonic
2024-05-11T01:51:17.810095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
3 227
48.3%
7 102
21.7%
1 79
 
16.8%
4 57
 
12.1%
5 3
 
0.6%
6 1
 
0.2%
2 1
 
0.2%
ValueCountFrequency (%)
1 79
 
16.8%
2 1
 
0.2%
3 227
48.3%
4 57
 
12.1%
5 3
 
0.6%
6 1
 
0.2%
7 102
21.7%
ValueCountFrequency (%)
7 102
21.7%
6 1
 
0.2%
5 3
 
0.6%
4 57
 
12.1%
3 227
48.3%
2 1
 
0.2%
1 79
 
16.8%

상세영업상태명
Categorical

Distinct7
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
폐업처리
227 
직권말소
102 
정상영업
79 
직권취소
57 
타시군구이관
 
3
Other values (2)
 
2

Length

Max length6
Median length4
Mean length4.0170213
Min length4

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
폐업처리 227
48.3%
직권말소 102
21.7%
정상영업 79
 
16.8%
직권취소 57
 
12.1%
타시군구이관 3
 
0.6%
타시군구전입 1
 
0.2%
휴업처리 1
 
0.2%

Length

2024-05-11T01:51:18.504235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:51:19.008645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업처리 227
48.3%
직권말소 102
21.7%
정상영업 79
 
16.8%
직권취소 57
 
12.1%
타시군구이관 3
 
0.6%
타시군구전입 1
 
0.2%
휴업처리 1
 
0.2%

폐업일자
Date

MISSING 

Distinct211
Distinct (%)91.7%
Missing240
Missing (%)51.1%
Memory size3.8 KiB
Minimum2006-11-01 00:00:00
Maximum2024-04-04 00:00:00
2024-05-11T01:51:19.512290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:51:19.945747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
466 
20181026
 
1
20151015
 
1
20210602
 
1
20200904
 
1

Length

Max length8
Median length4
Mean length4.0340426
Min length4

Unique

Unique4 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 466
99.1%
20181026 1
 
0.2%
20151015 1
 
0.2%
20210602 1
 
0.2%
20200904 1
 
0.2%

Length

2024-05-11T01:51:20.425349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:51:20.773974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 466
99.1%
20181026 1
 
0.2%
20151015 1
 
0.2%
20210602 1
 
0.2%
20200904 1
 
0.2%

휴업종료일자
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
466 
20201025
 
1
20151120
 
1
20211231
 
1
20221231
 
1

Length

Max length8
Median length4
Mean length4.0340426
Min length4

Unique

Unique4 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 466
99.1%
20201025 1
 
0.2%
20151120 1
 
0.2%
20211231 1
 
0.2%
20221231 1
 
0.2%

Length

2024-05-11T01:51:21.207939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:51:21.616713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 466
99.1%
20201025 1
 
0.2%
20151120 1
 
0.2%
20211231 1
 
0.2%
20221231 1
 
0.2%

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing470
Missing (%)100.0%
Memory size4.3 KiB

전화번호
Text

MISSING 

Distinct308
Distinct (%)95.7%
Missing148
Missing (%)31.5%
Memory size3.8 KiB
2024-05-11T01:51:22.160443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length10.083851
Min length2

Characters and Unicode

Total characters3247
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique298 ?
Unique (%)92.5%

Sample

1st row02 905 0729
2nd row02 982 0579
3rd row02 999 2491
4th row02 989 3330
5th row02 984 8880
ValueCountFrequency (%)
02 64
 
14.2%
02-985-2033 5
 
1.1%
999 5
 
1.1%
989 4
 
0.9%
987 4
 
0.9%
993 3
 
0.7%
982 3
 
0.7%
905 3
 
0.7%
985 3
 
0.7%
903 3
 
0.7%
Other values (329) 353
78.4%
2024-05-11T01:51:23.210263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 549
16.9%
9 435
13.4%
2 396
12.2%
8 322
9.9%
- 275
8.5%
5 198
 
6.1%
1 196
 
6.0%
193
 
5.9%
7 186
 
5.7%
4 170
 
5.2%
Other values (3) 327
10.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2777
85.5%
Dash Punctuation 275
 
8.5%
Space Separator 193
 
5.9%
Math Symbol 2
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 549
19.8%
9 435
15.7%
2 396
14.3%
8 322
11.6%
5 198
 
7.1%
1 196
 
7.1%
7 186
 
6.7%
4 170
 
6.1%
3 166
 
6.0%
6 159
 
5.7%
Dash Punctuation
ValueCountFrequency (%)
- 275
100.0%
Space Separator
ValueCountFrequency (%)
193
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3247
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 549
16.9%
9 435
13.4%
2 396
12.2%
8 322
9.9%
- 275
8.5%
5 198
 
6.1%
1 196
 
6.0%
193
 
5.9%
7 186
 
5.7%
4 170
 
5.2%
Other values (3) 327
10.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3247
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 549
16.9%
9 435
13.4%
2 396
12.2%
8 322
9.9%
- 275
8.5%
5 198
 
6.1%
1 196
 
6.0%
193
 
5.9%
7 186
 
5.7%
4 170
 
5.2%
Other values (3) 327
10.1%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing470
Missing (%)100.0%
Memory size4.3 KiB

소재지우편번호
Real number (ℝ)

MISSING 

Distinct57
Distinct (%)25.2%
Missing244
Missing (%)51.9%
Infinite0
Infinite (%)0.0%
Mean142265.78
Minimum136827
Maximum142892
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2024-05-11T01:51:23.734504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum136827
5-th percentile142060
Q1142070
median142100
Q3142713.5
95-th percentile142878
Maximum142892
Range6065
Interquartile range (IQR)643.5

Descriptive statistics

Standard deviation494.86639
Coefficient of variation (CV)0.0034784639
Kurtosis64.074016
Mean142265.78
Median Absolute Deviation (MAD)30
Skewness-5.5684359
Sum32152067
Variance244892.75
MonotonicityNot monotonic
2024-05-11T01:51:24.202600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
142100 57
 
12.1%
142060 26
 
5.5%
142070 23
 
4.9%
142071 18
 
3.8%
142061 15
 
3.2%
142703 6
 
1.3%
142877 5
 
1.1%
142878 4
 
0.9%
142717 4
 
0.9%
142072 4
 
0.9%
Other values (47) 64
 
13.6%
(Missing) 244
51.9%
ValueCountFrequency (%)
136827 1
 
0.2%
142060 26
5.5%
142061 15
3.2%
142062 1
 
0.2%
142070 23
4.9%
142071 18
3.8%
142072 4
 
0.9%
142073 3
 
0.6%
142074 1
 
0.2%
142075 2
 
0.4%
ValueCountFrequency (%)
142892 1
 
0.2%
142887 1
 
0.2%
142886 3
0.6%
142882 2
 
0.4%
142881 1
 
0.2%
142879 1
 
0.2%
142878 4
0.9%
142877 5
1.1%
142876 1
 
0.2%
142874 3
0.6%

지번주소
Text

MISSING 

Distinct253
Distinct (%)59.1%
Missing42
Missing (%)8.9%
Memory size3.8 KiB
2024-05-11T01:51:24.953954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length41
Mean length26.247664
Min length12

Characters and Unicode

Total characters11234
Distinct characters178
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique205 ?
Unique (%)47.9%

Sample

1st row서울특별시 강북구 수유동 *-**
2nd row서울특별시 강북구 수유동 **-*
3rd row서울특별시 강북구 수유동 ***-*
4th row서울특별시 강북구 미아동 ***-** 여은빌딩
5th row미아동 미아*동 ***-**
ValueCountFrequency (%)
서울특별시 421
17.5%
강북구 420
17.4%
호 349
14.5%
번지 292
12.1%
미아동 162
 
6.7%
수유동 137
 
5.7%
125
 
5.2%
번동 93
 
3.9%
층 69
 
2.9%
통 32
 
1.3%
Other values (167) 312
12.9%
2024-05-11T01:51:26.350447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 2424
21.6%
2012
17.9%
동 468
 
4.2%
북 429
 
3.8%
강 426
 
3.8%
시 425
 
3.8%
서 424
 
3.8%
울 424
 
3.8%
구 421
 
3.7%
별 421
 
3.7%
Other values (168) 3360
29.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6634
59.1%
Other Punctuation 2436
 
21.7%
Space Separator 2012
 
17.9%
Dash Punctuation 120
 
1.1%
Uppercase Letter 19
 
0.2%
Open Punctuation 4
 
< 0.1%
Close Punctuation 4
 
< 0.1%
Decimal Number 4
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 468
 
7.1%
북 429
 
6.5%
강 426
 
6.4%
시 425
 
6.4%
서 424
 
6.4%
울 424
 
6.4%
구 421
 
6.3%
별 421
 
6.3%
특 421
 
6.3%
번 402
 
6.1%
Other values (150) 2373
35.8%
Uppercase Letter
ValueCountFrequency (%)
B 8
42.1%
S 3
 
15.8%
A 2
 
10.5%
K 2
 
10.5%
D 2
 
10.5%
E 1
 
5.3%
F 1
 
5.3%
Other Punctuation
ValueCountFrequency (%)
* 2424
99.5%
, 11
 
0.5%
/ 1
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
1 2
50.0%
3 1
25.0%
6 1
25.0%
Space Separator
ValueCountFrequency (%)
2012
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 120
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6634
59.1%
Common 4581
40.8%
Latin 19
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 468
 
7.1%
북 429
 
6.5%
강 426
 
6.4%
시 425
 
6.4%
서 424
 
6.4%
울 424
 
6.4%
구 421
 
6.3%
별 421
 
6.3%
특 421
 
6.3%
번 402
 
6.1%
Other values (150) 2373
35.8%
Common
ValueCountFrequency (%)
* 2424
52.9%
2012
43.9%
- 120
 
2.6%
, 11
 
0.2%
( 4
 
0.1%
) 4
 
0.1%
1 2
 
< 0.1%
3 1
 
< 0.1%
6 1
 
< 0.1%
~ 1
 
< 0.1%
Latin
ValueCountFrequency (%)
B 8
42.1%
S 3
 
15.8%
A 2
 
10.5%
K 2
 
10.5%
D 2
 
10.5%
E 1
 
5.3%
F 1
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6634
59.1%
ASCII 4600
40.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 2424
52.7%
2012
43.7%
- 120
 
2.6%
, 11
 
0.2%
B 8
 
0.2%
( 4
 
0.1%
) 4
 
0.1%
S 3
 
0.1%
1 2
 
< 0.1%
A 2
 
< 0.1%
Other values (8) 10
 
0.2%
Hangul
ValueCountFrequency (%)
동 468
 
7.1%
북 429
 
6.5%
강 426
 
6.4%
시 425
 
6.4%
서 424
 
6.4%
울 424
 
6.4%
구 421
 
6.3%
별 421
 
6.3%
특 421
 
6.3%
번 402
 
6.1%
Other values (150) 2373
35.8%

도로명주소
Text

MISSING 

Distinct343
Distinct (%)77.3%
Missing26
Missing (%)5.5%
Memory size3.8 KiB
2024-05-11T01:51:27.049193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length42
Mean length31.243243
Min length18

Characters and Unicode

Total characters13872
Distinct characters186
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique292 ?
Unique (%)65.8%

Sample

1st row서울특별시 강북구 수유로 **, *층 (수유동)
2nd row서울특별시 강북구 도봉로**길 * (수유동)
3rd row서울특별시 강북구 한천로 **** (수유동)
4th row서울특별시 강북구 도봉로 ***, 여은빌딩 *층 (미아동)
5th row서울특별시 강북구 솔샘로**길 **, ***,***호 (미아동, 코리아나빌딩)
ValueCountFrequency (%)
447
16.4%
서울특별시 444
16.3%
강북구 443
16.2%
층 158
 
5.8%
호 144
 
5.3%
미아동 135
 
4.9%
수유동 132
 
4.8%
도봉로 103
 
3.8%
번동 77
 
2.8%
도봉로**길 43
 
1.6%
Other values (233) 604
22.1%
2024-05-11T01:51:28.082018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 2329
16.8%
2289
16.5%
동 480
 
3.5%
, 478
 
3.4%
북 451
 
3.3%
강 450
 
3.2%
시 447
 
3.2%
서 445
 
3.2%
울 445
 
3.2%
특 444
 
3.2%
Other values (176) 5614
40.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7798
56.2%
Other Punctuation 2812
 
20.3%
Space Separator 2289
 
16.5%
Open Punctuation 444
 
3.2%
Close Punctuation 444
 
3.2%
Dash Punctuation 55
 
0.4%
Uppercase Letter 22
 
0.2%
Decimal Number 6
 
< 0.1%
Lowercase Letter 1
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 480
 
6.2%
북 451
 
5.8%
강 450
 
5.8%
시 447
 
5.7%
서 445
 
5.7%
울 445
 
5.7%
특 444
 
5.7%
로 444
 
5.7%
별 444
 
5.7%
구 443
 
5.7%
Other values (156) 3305
42.4%
Uppercase Letter
ValueCountFrequency (%)
B 12
54.5%
S 3
 
13.6%
K 2
 
9.1%
H 1
 
4.5%
A 1
 
4.5%
D 1
 
4.5%
F 1
 
4.5%
E 1
 
4.5%
Other Punctuation
ValueCountFrequency (%)
* 2329
82.8%
, 478
 
17.0%
. 5
 
0.2%
Decimal Number
ValueCountFrequency (%)
4 4
66.7%
6 1
 
16.7%
1 1
 
16.7%
Space Separator
ValueCountFrequency (%)
2289
100.0%
Open Punctuation
ValueCountFrequency (%)
( 444
100.0%
Close Punctuation
ValueCountFrequency (%)
) 444
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 55
100.0%
Lowercase Letter
ValueCountFrequency (%)
c 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7798
56.2%
Common 6051
43.6%
Latin 23
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 480
 
6.2%
북 451
 
5.8%
강 450
 
5.8%
시 447
 
5.7%
서 445
 
5.7%
울 445
 
5.7%
특 444
 
5.7%
로 444
 
5.7%
별 444
 
5.7%
구 443
 
5.7%
Other values (156) 3305
42.4%
Common
ValueCountFrequency (%)
* 2329
38.5%
2289
37.8%
, 478
 
7.9%
( 444
 
7.3%
) 444
 
7.3%
- 55
 
0.9%
. 5
 
0.1%
4 4
 
0.1%
6 1
 
< 0.1%
~ 1
 
< 0.1%
Latin
ValueCountFrequency (%)
B 12
52.2%
S 3
 
13.0%
K 2
 
8.7%
H 1
 
4.3%
A 1
 
4.3%
D 1
 
4.3%
c 1
 
4.3%
F 1
 
4.3%
E 1
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7798
56.2%
ASCII 6074
43.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 2329
38.3%
2289
37.7%
, 478
 
7.9%
( 444
 
7.3%
) 444
 
7.3%
- 55
 
0.9%
B 12
 
0.2%
. 5
 
0.1%
4 4
 
0.1%
S 3
 
< 0.1%
Other values (10) 11
 
0.2%
Hangul
ValueCountFrequency (%)
동 480
 
6.2%
북 451
 
5.8%
강 450
 
5.8%
시 447
 
5.7%
서 445
 
5.7%
울 445
 
5.7%
특 444
 
5.7%
로 444
 
5.7%
별 444
 
5.7%
구 443
 
5.7%
Other values (156) 3305
42.4%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct125
Distinct (%)41.9%
Missing172
Missing (%)36.6%
Infinite0
Infinite (%)0.0%
Mean49442.745
Minimum1006
Maximum142878
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2024-05-11T01:51:28.482221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1006
5-th percentile1041
Q11072.25
median1172
Q3142071
95-th percentile142866.15
Maximum142878
Range141872
Interquartile range (IQR)140998.75

Descriptive statistics

Standard deviation67108.814
Coefficient of variation (CV)1.3573036
Kurtosis-1.5639949
Mean49442.745
Median Absolute Deviation (MAD)116
Skewness0.66820898
Sum14733938
Variance4.503593 × 109
MonotonicityNot monotonic
2024-05-11T01:51:28.901303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
142100 25
 
5.3%
142071 19
 
4.0%
142061 17
 
3.6%
1062 10
 
2.1%
142703 6
 
1.3%
1125 6
 
1.3%
142867 6
 
1.3%
1179 5
 
1.1%
142070 5
 
1.1%
1056 5
 
1.1%
Other values (115) 194
41.3%
(Missing) 172
36.6%
ValueCountFrequency (%)
1006 1
 
0.2%
1011 1
 
0.2%
1014 1
 
0.2%
1016 1
 
0.2%
1028 1
 
0.2%
1029 2
0.4%
1033 1
 
0.2%
1034 3
0.6%
1037 1
 
0.2%
1038 1
 
0.2%
ValueCountFrequency (%)
142878 4
0.9%
142876 1
 
0.2%
142874 1
 
0.2%
142873 2
 
0.4%
142872 1
 
0.2%
142867 6
1.3%
142866 1
 
0.2%
142864 1
 
0.2%
142861 2
 
0.4%
142815 1
 
0.2%

사업장명
Text

Distinct443
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
2024-05-11T01:51:29.572294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length20
Mean length6.9042553
Min length2

Characters and Unicode

Total characters3245
Distinct characters416
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique421 ?
Unique (%)89.6%

Sample

1st row백옥자연한방화장품세종지사
2nd row시사영어교실도봉남부지사
3rd row한국에너지
4th row유니베라강북대리점
5th row마임
ValueCountFrequency (%)
주식회사 28
 
4.6%
마임 11
 
1.8%
강북지사 4
 
0.7%
신신의료기 3
 
0.5%
종근당건강 3
 
0.5%
헬스벨스토리 3
 
0.5%
아이앤 3
 
0.5%
cnn 3
 
0.5%
에치와이 3
 
0.5%
해피월드 3
 
0.5%
Other values (517) 548
89.5%
2024-05-11T01:51:30.954111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
142
 
4.4%
이 95
 
2.9%
스 80
 
2.5%
사 77
 
2.4%
아 74
 
2.3%
리 71
 
2.2%
주 64
 
2.0%
( 51
 
1.6%
) 51
 
1.6%
점 47
 
1.4%
Other values (406) 2493
76.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2832
87.3%
Space Separator 142
 
4.4%
Uppercase Letter 86
 
2.7%
Lowercase Letter 59
 
1.8%
Open Punctuation 51
 
1.6%
Close Punctuation 51
 
1.6%
Other Punctuation 17
 
0.5%
Other Symbol 3
 
0.1%
Dash Punctuation 2
 
0.1%
Decimal Number 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 95
 
3.4%
스 80
 
2.8%
사 77
 
2.7%
아 74
 
2.6%
리 71
 
2.5%
주 64
 
2.3%
점 47
 
1.7%
강 45
 
1.6%
지 42
 
1.5%
대 42
 
1.5%
Other values (355) 2195
77.5%
Uppercase Letter
ValueCountFrequency (%)
N 15
17.4%
C 9
10.5%
E 8
 
9.3%
T 6
 
7.0%
L 6
 
7.0%
R 5
 
5.8%
M 5
 
5.8%
A 4
 
4.7%
S 4
 
4.7%
U 3
 
3.5%
Other values (10) 21
24.4%
Lowercase Letter
ValueCountFrequency (%)
s 7
11.9%
a 6
 
10.2%
o 5
 
8.5%
e 5
 
8.5%
t 4
 
6.8%
i 4
 
6.8%
u 4
 
6.8%
r 3
 
5.1%
h 3
 
5.1%
n 3
 
5.1%
Other values (10) 15
25.4%
Other Punctuation
ValueCountFrequency (%)
. 12
70.6%
, 3
 
17.6%
& 1
 
5.9%
? 1
 
5.9%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%
Space Separator
ValueCountFrequency (%)
142
100.0%
Open Punctuation
ValueCountFrequency (%)
( 51
100.0%
Close Punctuation
ValueCountFrequency (%)
) 51
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2835
87.4%
Common 265
 
8.2%
Latin 145
 
4.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 95
 
3.4%
스 80
 
2.8%
사 77
 
2.7%
아 74
 
2.6%
리 71
 
2.5%
주 64
 
2.3%
점 47
 
1.7%
강 45
 
1.6%
지 42
 
1.5%
대 42
 
1.5%
Other values (356) 2198
77.5%
Latin
ValueCountFrequency (%)
N 15
 
10.3%
C 9
 
6.2%
E 8
 
5.5%
s 7
 
4.8%
a 6
 
4.1%
T 6
 
4.1%
L 6
 
4.1%
o 5
 
3.4%
R 5
 
3.4%
M 5
 
3.4%
Other values (30) 73
50.3%
Common
ValueCountFrequency (%)
142
53.6%
( 51
 
19.2%
) 51
 
19.2%
. 12
 
4.5%
, 3
 
1.1%
- 2
 
0.8%
& 1
 
0.4%
? 1
 
0.4%
2 1
 
0.4%
1 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2832
87.3%
ASCII 410
 
12.6%
None 3
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
142
34.6%
( 51
 
12.4%
) 51
 
12.4%
N 15
 
3.7%
. 12
 
2.9%
C 9
 
2.2%
E 8
 
2.0%
s 7
 
1.7%
a 6
 
1.5%
T 6
 
1.5%
Other values (40) 103
25.1%
Hangul
ValueCountFrequency (%)
이 95
 
3.4%
스 80
 
2.8%
사 77
 
2.7%
아 74
 
2.6%
리 71
 
2.5%
주 64
 
2.3%
점 47
 
1.7%
강 45
 
1.6%
지 42
 
1.5%
대 42
 
1.5%
Other values (355) 2195
77.5%
None
ValueCountFrequency (%)
㈜ 3
100.0%

최종수정일자
Date

UNIQUE 

Distinct470
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
Minimum2007-07-25 16:03:22
Maximum2024-04-08 09:45:15
2024-05-11T01:51:31.429380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:51:31.913468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
I
316 
U
154 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 316
67.2%
U 154
32.8%

Length

2024-05-11T01:51:32.297528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:51:32.578703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 316
67.2%
u 154
32.8%

데이터갱신일자
Date

Distinct121
Distinct (%)25.7%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 23:00:00
2024-05-11T01:51:32.937683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:51:33.671838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing470
Missing (%)100.0%
Memory size4.3 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct314
Distinct (%)68.4%
Missing11
Missing (%)2.3%
Infinite0
Infinite (%)0.0%
Mean202089
Minimum200466.45
Maximum204531.65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2024-05-11T01:51:34.224168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum200466.45
5-th percentile201059.87
Q1201715.77
median202129.43
Q3202461.53
95-th percentile203232.42
Maximum204531.65
Range4065.2031
Interquartile range (IQR)745.76444

Descriptive statistics

Standard deviation640.93504
Coefficient of variation (CV)0.0031715485
Kurtosis1.0014195
Mean202089
Median Absolute Deviation (MAD)336.38621
Skewness0.46956147
Sum92758849
Variance410797.73
MonotonicityNot monotonic
2024-05-11T01:51:34.904722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
202155.401317068 23
 
4.9%
202465.042504763 17
 
3.6%
201760.840899656 7
 
1.5%
202511.102551438 7
 
1.5%
202032.757631932 6
 
1.3%
202052.37985575 4
 
0.9%
202099.830367084 4
 
0.9%
201367.434505028 4
 
0.9%
203874.192185321 4
 
0.9%
200921.855251696 4
 
0.9%
Other values (304) 379
80.6%
(Missing) 11
 
2.3%
ValueCountFrequency (%)
200466.445878305 1
0.2%
200587.037712252 1
0.2%
200706.59176064 1
0.2%
200737.464286084 1
0.2%
200738.594475356 1
0.2%
200802.615294385 1
0.2%
200813.155990823 1
0.2%
200886.333781015 1
0.2%
200894.60830383 1
0.2%
200909.42602306 1
0.2%
ValueCountFrequency (%)
204531.649027488 1
 
0.2%
204089.673173372 1
 
0.2%
203999.650902849 2
0.4%
203874.192185321 4
0.9%
203821.073410934 1
 
0.2%
203784.358132827 3
0.6%
203760.618259685 1
 
0.2%
203742.886285674 1
 
0.2%
203681.897120967 1
 
0.2%
203627.347902029 1
 
0.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct314
Distinct (%)68.4%
Missing11
Missing (%)2.3%
Infinite0
Infinite (%)0.0%
Mean458825.89
Minimum456377.65
Maximum462160.31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2024-05-11T01:51:35.507968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum456377.65
5-th percentile456987.84
Q1457858.51
median459059.08
Q3459617.41
95-th percentile460426
Maximum462160.31
Range5782.6604
Interquartile range (IQR)1758.9024

Descriptive statistics

Standard deviation1079.3828
Coefficient of variation (CV)0.0023524889
Kurtosis-0.62283936
Mean458825.89
Median Absolute Deviation (MAD)809.75707
Skewness-0.085911419
Sum2.1060108 × 108
Variance1165067.2
MonotonicityNot monotonic
2024-05-11T01:51:36.013506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
459411.940883021 23
 
4.9%
457640.23984676 17
 
3.6%
459314.389044069 7
 
1.5%
459156.609544031 7
 
1.5%
459259.443978524 6
 
1.3%
459491.573913047 4
 
0.9%
458756.889791888 4
 
0.9%
459977.826459484 4
 
0.9%
458045.425631086 4
 
0.9%
457533.770785984 4
 
0.9%
Other values (304) 379
80.6%
(Missing) 11
 
2.3%
ValueCountFrequency (%)
456377.651999255 1
0.2%
456473.886142136 1
0.2%
456507.284374071 1
0.2%
456622.678015493 1
0.2%
456655.934466674 1
0.2%
456663.090756306 1
0.2%
456676.934581735 1
0.2%
456705.489879639 2
0.4%
456706.94870624 1
0.2%
456720.763700646 1
0.2%
ValueCountFrequency (%)
462160.312358665 1
0.2%
461950.330011532 1
0.2%
461704.439581595 1
0.2%
461497.076608921 1
0.2%
460847.85580713 1
0.2%
460738.590438978 2
0.4%
460686.989222997 1
0.2%
460673.965765146 1
0.2%
460651.772909553 1
0.2%
460634.337221595 1
0.2%

자산규모
Real number (ℝ)

MISSING  ZEROS 

Distinct32
Distinct (%)43.8%
Missing397
Missing (%)84.5%
Infinite0
Infinite (%)0.0%
Mean2.5697142 × 109
Minimum0
Maximum1.3381489 × 1011
Zeros34
Zeros (%)7.2%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2024-05-11T01:51:36.586466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median10000000
Q31.1477888 × 108
95-th percentile4.7675923 × 108
Maximum1.3381489 × 1011
Range1.3381489 × 1011
Interquartile range (IQR)1.1477888 × 108

Descriptive statistics

Standard deviation1.6540206 × 1010
Coefficient of variation (CV)6.4365936
Kurtosis57.551087
Mean2.5697142 × 109
Median Absolute Deviation (MAD)10000000
Skewness7.4202515
Sum1.8758914 × 1011
Variance2.7357842 × 1020
MonotonicityNot monotonic
2024-05-11T01:51:37.234653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
0 34
 
7.2%
10000000 4
 
0.9%
50000000 4
 
0.9%
30000000 2
 
0.4%
200000000 2
 
0.4%
505408752 1
 
0.2%
100000000 1
 
0.2%
144525588 1
 
0.2%
15990890 1
 
0.2%
266348895 1
 
0.2%
Other values (22) 22
 
4.7%
(Missing) 397
84.5%
ValueCountFrequency (%)
0 34
7.2%
1000000 1
 
0.2%
10000000 4
 
0.9%
15990890 1
 
0.2%
23023256 1
 
0.2%
30000000 2
 
0.4%
40000000 1
 
0.2%
50000000 4
 
0.9%
78000000 1
 
0.2%
91415868 1
 
0.2%
ValueCountFrequency (%)
133814894098 1
0.2%
47658841166 1
0.2%
521508503 1
0.2%
505408752 1
0.2%
457659548 1
0.2%
412013464 1
0.2%
400000000 1
0.2%
377430043 1
0.2%
372540872 1
0.2%
350000000 1
0.2%

부채총액
Real number (ℝ)

MISSING  ZEROS 

Distinct21
Distinct (%)28.8%
Missing397
Missing (%)84.5%
Infinite0
Infinite (%)0.0%
Mean7.9897797 × 108
Minimum0
Maximum5.1910769 × 1010
Zeros53
Zeros (%)11.3%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2024-05-11T01:51:37.890728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q341934015
95-th percentile6.9168025 × 108
Maximum5.1910769 × 1010
Range5.1910769 × 1010
Interquartile range (IQR)41934015

Descriptive statistics

Standard deviation6.0723714 × 109
Coefficient of variation (CV)7.6001738
Kurtosis72.644543
Mean7.9897797 × 108
Median Absolute Deviation (MAD)0
Skewness8.5138466
Sum5.8325392 × 1010
Variance3.6873694 × 1019
MonotonicityNot monotonic
2024-05-11T01:51:38.324705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 53
 
11.3%
146423994 1
 
0.2%
202000000 1
 
0.2%
77495460 1
 
0.2%
205697336 1
 
0.2%
77137026 1
 
0.2%
235641237 1
 
0.2%
642365940 1
 
0.2%
360126759 1
 
0.2%
15628610 1
 
0.2%
Other values (11) 11
 
2.3%
(Missing) 397
84.5%
ValueCountFrequency (%)
0 53
11.3%
15628610 1
 
0.2%
41934015 1
 
0.2%
48274935 1
 
0.2%
67000000 1
 
0.2%
69787298 1
 
0.2%
77137026 1
 
0.2%
77495460 1
 
0.2%
80803961 1
 
0.2%
146423994 1
 
0.2%
ValueCountFrequency (%)
51910769016 1
0.2%
2176122904 1
0.2%
800384992 1
0.2%
765651703 1
0.2%
642365940 1
0.2%
360126759 1
0.2%
235641237 1
0.2%
223012036 1
0.2%
205697336 1
0.2%
202000000 1
0.2%

자본금
Real number (ℝ)

MISSING  ZEROS 

Distinct27
Distinct (%)37.0%
Missing397
Missing (%)84.5%
Infinite0
Infinite (%)0.0%
Mean8.2053298 × 108
Minimum-2.5603672 × 108
Maximum4.5482718 × 1010
Zeros31
Zeros (%)6.6%
Negative1
Negative (%)0.2%
Memory size4.3 KiB
2024-05-11T01:51:38.899283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-2.5603672 × 108
5-th percentile0
Q10
median10000000
Q350000000
95-th percentile3.7 × 108
Maximum4.5482718 × 1010
Range4.5738755 × 1010
Interquartile range (IQR)50000000

Descriptive statistics

Standard deviation5.445366 × 109
Coefficient of variation (CV)6.6363767
Kurtosis65.349473
Mean8.2053298 × 108
Median Absolute Deviation (MAD)10000000
Skewness7.9610322
Sum5.9898907 × 1010
Variance2.965201 × 1019
MonotonicityNot monotonic
2024-05-11T01:51:39.518265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 31
 
6.6%
10000000 8
 
1.7%
50000000 7
 
1.5%
100000000 3
 
0.6%
30000000 2
 
0.4%
300000000 1
 
0.2%
15990890 1
 
0.2%
13920408 1
 
0.2%
200000000 1
 
0.2%
139075479 1
 
0.2%
Other values (17) 17
 
3.6%
(Missing) 397
84.5%
ValueCountFrequency (%)
-256036725 1
 
0.2%
0 31
6.6%
1000000 1
 
0.2%
8000000 1
 
0.2%
10000000 8
 
1.7%
13920408 1
 
0.2%
15990890 1
 
0.2%
20000000 1
 
0.2%
30000000 2
 
0.4%
30707658 1
 
0.2%
ValueCountFrequency (%)
45482718262 1
0.2%
10691250000 1
0.2%
500000000 1
0.2%
400000000 1
0.2%
350000000 1
0.2%
330606857 1
0.2%
311235554 1
0.2%
300000000 1
0.2%
278876489 1
0.2%
200000000 1
0.2%

판매방식명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing470
Missing (%)100.0%
Memory size4.3 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)자산규모부채총액자본금판매방식명
03080000199630800922320001120000620<NA>3폐업3폐업처리20081231<NA><NA><NA>02 905 0729<NA><NA>서울특별시 강북구 수유동 *-**서울특별시 강북구 수유로 **, *층 (수유동)1080백옥자연한방화장품세종지사2020-11-27 14:10:47U2020-11-29 02:40:00.0<NA>201831.986165459336.278135<NA><NA><NA><NA>
13080000199630800922320002119961128<NA>4취소/말소/만료/정지/중지7직권말소<NA><NA><NA><NA>02 982 0579<NA><NA>서울특별시 강북구 수유동 **-*서울특별시 강북구 도봉로**길 * (수유동)1114시사영어교실도봉남부지사2020-11-27 14:32:27U2020-11-29 02:40:00.0<NA>201938.133236459013.568717<NA><NA><NA><NA>
23080000199830800922320003319980220200807314취소/말소/만료/정지/중지4직권취소<NA><NA><NA><NA>02 999 2491<NA><NA>서울특별시 강북구 수유동 ***-*서울특별시 강북구 한천로 **** (수유동)1039한국에너지2020-11-27 14:13:32U2020-11-29 02:40:00.0<NA>201523.019576460404.096223<NA><NA><NA><NA>
33080000199830800922320003619980709<NA>3폐업3폐업처리20130924<NA><NA><NA>02 989 3330<NA><NA>서울특별시 강북구 미아동 ***-** 여은빌딩서울특별시 강북구 도봉로 ***, 여은빌딩 *층 (미아동)1158유니베라강북대리점2020-11-27 14:24:40U2020-11-29 02:40:00.0<NA>202352.004852457965.209082<NA><NA><NA><NA>
43080000199930800922320004219990413<NA>3폐업3폐업처리20181119<NA><NA><NA>02 984 8880<NA><NA>미아동 미아*동 ***-**서울특별시 강북구 솔샘로**길 **, ***,***호 (미아동, 코리아나빌딩)142100마임2018-11-19 17:00:43U2018-11-21 02:37:57.0<NA>202399.141092457515.66769<NA><NA><NA><NA>
53080000199930800922320004819991101<NA>3폐업3폐업처리20130830<NA><NA><NA>02 984 4258<NA>142100서울특별시 강북구 미아동 ***번지 **호 청암빌딩 ***호서울특별시 강북구 도봉로 ***, ***호 (미아동,청암빌딩)<NA>마임2018-08-10 13:58:34I2018-08-31 23:59:59.0<NA>202099.830367458756.889792<NA><NA><NA><NA>
63080000200030800922320000120000131<NA>3폐업3폐업처리20180119<NA><NA><NA>02 575 3929<NA><NA>서울특별시 강북구 번동 ***-**서울특별시 강북구 도봉로 ***, *층 (번동)1056한생화장품2020-11-27 13:06:37U2020-11-29 02:40:00.0<NA>202405.481985459721.500101<NA><NA><NA><NA>
73080000200030800922320001220000425<NA>3폐업3폐업처리20071004<NA><NA><NA>02 955 0958<NA><NA>서울특별시 강북구 수유동 ***-* SD빌딩서울특별시 강북구 도봉로 ***, SD빌딩 *층 (수유동)1054생그린화장품강북점2020-11-27 10:49:28U2020-11-29 02:40:00.0<NA>202426.032099459837.927511<NA><NA><NA><NA>
83080000200130800922320005520010919<NA>3폐업3폐업처리20090918<NA><NA><NA>02 999 8575<NA><NA>서울특별시 강북구 수유동 *-**서울특별시 강북구 수유로 **, *층 (수유동)1080황토테크놀러지2020-11-27 14:09:07U2020-11-29 02:40:00.0<NA>201831.986165459336.278135<NA><NA><NA><NA>
93080000200230800922320006620020322<NA>3폐업3폐업처리20140519<NA><NA><NA>02 991 3161<NA><NA>수유동 수유*동 ***-*<NA><NA>이롬라이프수유북부점2014-05-19 14:01:17I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)자산규모부채총액자본금판매방식명
460308000020233080190232000042023-03-23<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 강북구 수유동 ***-*서울특별시 강북구 도봉로 ***, *층 (수유동)1054탑셀바이오뱅크 수유지사2023-03-23 14:04:41I2022-12-02 22:05:00.0<NA>202441.260546459852.150637<NA><NA><NA><NA>
461308000020233080190232000052023-04-03<NA>3폐업3폐업처리2023-11-22<NA><NA><NA><NA><NA><NA>서울특별시 강북구 수유동 **-*서울특별시 강북구 도봉로**가길 **-*, *층 (수유동)1114종근당건강 헬스벨스토리 서울수유점2023-11-23 10:07:51U2022-10-31 22:05:00.0<NA>201904.230117458869.002324<NA><NA><NA><NA>
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