Overview

Dataset statistics

Number of variables29
Number of observations615
Missing cells6416
Missing cells (%)36.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory147.3 KiB
Average record size in memory245.2 B

Variable types

Categorical6
Numeric7
DateTime7
Text6
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),자산규모,부채총액,자본금,판매방식명
Author동대문구
URLhttps://data.seoul.go.kr/dataList/OA-18757/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 is highly imbalanced (97.0%)Imbalance
폐업일자 has 264 (42.9%) missing valuesMissing
휴업시작일자 has 612 (99.5%) missing valuesMissing
휴업종료일자 has 612 (99.5%) missing valuesMissing
재개업일자 has 578 (94.0%) missing valuesMissing
전화번호 has 265 (43.1%) missing valuesMissing
소재지면적 has 615 (100.0%) missing valuesMissing
소재지우편번호 has 274 (44.6%) missing valuesMissing
지번주소 has 90 (14.6%) missing valuesMissing
도로명주소 has 102 (16.6%) missing valuesMissing
도로명우편번호 has 319 (51.9%) missing valuesMissing
업태구분명 has 615 (100.0%) missing valuesMissing
좌표정보(X) has 8 (1.3%) missing valuesMissing
좌표정보(Y) has 8 (1.3%) missing valuesMissing
자산규모 has 480 (78.0%) missing valuesMissing
부채총액 has 480 (78.0%) missing valuesMissing
자본금 has 479 (77.9%) missing valuesMissing
판매방식명 has 615 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
최종수정일자 has unique valuesUnique
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 30 (4.9%) zerosZeros
부채총액 has 78 (12.7%) zerosZeros
자본금 has 18 (2.9%) zerosZeros

Reproduction

Analysis started2024-04-17 20:11:14.807179
Analysis finished2024-04-17 20:11:15.392929
Duration0.59 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
3050000
615 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3050000
2nd row3050000
3rd row3050000
4th row3050000
5th row3050000

Common Values

ValueCountFrequency (%)
3050000 615
100.0%

Length

2024-04-18T05:11:15.451647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:11:15.525425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3050000 615
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct615
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0124644 × 1018
Minimum1.996305 × 1018
Maximum2.024305 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2024-04-18T05:11:15.602597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.996305 × 1018
5-th percentile2.005305 × 1018
Q12.010305 × 1018
median2.010305 × 1018
Q32.016305 × 1018
95-th percentile2.021305 × 1018
Maximum2.024305 × 1018
Range2.8000011 × 1016
Interquartile range (IQR)6.000004 × 1015

Descriptive statistics

Standard deviation5.0875712 × 1015
Coefficient of variation (CV)0.0025280305
Kurtosis0.21851421
Mean2.0124644 × 1018
Median Absolute Deviation (MAD)3 × 1015
Skewness0.16719324
Sum1.7337295 × 1018
Variance2.5883381 × 1031
MonotonicityStrictly increasing
2024-04-18T05:11:15.733118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1996305010023200052 1
 
0.2%
2014305014023200003 1
 
0.2%
2013305014023200029 1
 
0.2%
2013305014023200030 1
 
0.2%
2013305014023200031 1
 
0.2%
2013305014023200032 1
 
0.2%
2013305014023200033 1
 
0.2%
2014305014023200001 1
 
0.2%
2014305014023200002 1
 
0.2%
2014305014023200004 1
 
0.2%
Other values (605) 605
98.4%
ValueCountFrequency (%)
1996305010023200052 1
0.2%
1996305010023200094 1
0.2%
1996305010023200095 1
0.2%
1997305010023200111 1
0.2%
1998305010023200177 1
0.2%
1998305010023200204 1
0.2%
1999305010023200251 1
0.2%
1999305010023200260 1
0.2%
1999305010023200287 1
0.2%
2001305010023200453 1
0.2%
ValueCountFrequency (%)
2024305021023200006 1
0.2%
2024305021023200005 1
0.2%
2024305021023200004 1
0.2%
2024305021023200003 1
0.2%
2024305021023200002 1
0.2%
2024305021023200001 1
0.2%
2023305021023200010 1
0.2%
2023305021023200009 1
0.2%
2023305021023200008 1
0.2%
2023305021023200007 1
0.2%

인허가일자
Date

Distinct487
Distinct (%)79.2%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
Minimum1996-11-04 00:00:00
Maximum2024-04-09 00:00:00
2024-04-18T05:11:15.861913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T05:11:16.253907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
611 
20080911
 
1
20080501
 
1
20120803
 
1
20120906
 
1

Length

Max length8
Median length4
Mean length4.0260163
Min length4

Unique

Unique4 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 611
99.3%
20080911 1
 
0.2%
20080501 1
 
0.2%
20120803 1
 
0.2%
20120906 1
 
0.2%

Length

2024-04-18T05:11:16.355982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:11:16.441540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 611
99.3%
20080911 1
 
0.2%
20080501 1
 
0.2%
20120803 1
 
0.2%
20120906 1
 
0.2%

영업상태코드
Categorical

Distinct5
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
3
348 
4
165 
1
96 
5
 
3
2
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 348
56.6%
4 165
26.8%
1 96
 
15.6%
5 3
 
0.5%
2 3
 
0.5%

Length

2024-04-18T05:11:16.525734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:11:16.609553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 348
56.6%
4 165
26.8%
1 96
 
15.6%
5 3
 
0.5%
2 3
 
0.5%

영업상태명
Categorical

Distinct5
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
폐업
348 
취소/말소/만료/정지/중지
165 
영업/정상
96 
제외/삭제/전출
 
3
휴업
 
3

Length

Max length14
Median length2
Mean length5.7170732
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 348
56.6%
취소/말소/만료/정지/중지 165
26.8%
영업/정상 96
 
15.6%
제외/삭제/전출 3
 
0.5%
휴업 3
 
0.5%

Length

2024-04-18T05:11:16.705616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:11:16.792085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 348
56.6%
취소/말소/만료/정지/중지 165
26.8%
영업/정상 96
 
15.6%
제외/삭제/전출 3
 
0.5%
휴업 3
 
0.5%

상세영업상태코드
Real number (ℝ)

Distinct6
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.7463415
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2024-04-18T05:11:16.871701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median3
Q37
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.0721628
Coefficient of variation (CV)0.55311638
Kurtosis-0.90526251
Mean3.7463415
Median Absolute Deviation (MAD)0
Skewness0.62480819
Sum2304
Variance4.2938587
MonotonicityNot monotonic
2024-04-18T05:11:16.947783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3 348
56.6%
7 161
26.2%
1 96
 
15.6%
4 4
 
0.7%
5 3
 
0.5%
2 3
 
0.5%
ValueCountFrequency (%)
1 96
 
15.6%
2 3
 
0.5%
3 348
56.6%
4 4
 
0.7%
5 3
 
0.5%
7 161
26.2%
ValueCountFrequency (%)
7 161
26.2%
5 3
 
0.5%
4 4
 
0.7%
3 348
56.6%
2 3
 
0.5%
1 96
 
15.6%

상세영업상태명
Categorical

Distinct6
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
폐업처리
348 
직권말소
161 
정상영업
96 
직권취소
 
4
타시군구이관
 
3

Length

Max length6
Median length4
Mean length4.0097561
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업처리 348
56.6%
직권말소 161
26.2%
정상영업 96
 
15.6%
직권취소 4
 
0.7%
타시군구이관 3
 
0.5%
휴업처리 3
 
0.5%

Length

2024-04-18T05:11:17.050917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:11:17.142413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업처리 348
56.6%
직권말소 161
26.2%
정상영업 96
 
15.6%
직권취소 4
 
0.7%
타시군구이관 3
 
0.5%
휴업처리 3
 
0.5%

폐업일자
Date

MISSING 

Distinct270
Distinct (%)76.9%
Missing264
Missing (%)42.9%
Memory size4.9 KiB
Minimum2007-12-04 00:00:00
Maximum2024-03-25 00:00:00
2024-04-18T05:11:17.241111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T05:11:17.346408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Date

MISSING 

Distinct3
Distinct (%)100.0%
Missing612
Missing (%)99.5%
Memory size4.9 KiB
Minimum2020-11-20 00:00:00
Maximum2023-01-19 00:00:00
2024-04-18T05:11:17.422601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T05:11:17.495936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=3)

휴업종료일자
Date

MISSING 

Distinct3
Distinct (%)100.0%
Missing612
Missing (%)99.5%
Memory size4.9 KiB
Minimum2021-11-19 00:00:00
Maximum2024-01-19 00:00:00
2024-04-18T05:11:17.570530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T05:11:17.643555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=3)

재개업일자
Date

MISSING 

Distinct37
Distinct (%)100.0%
Missing578
Missing (%)94.0%
Memory size4.9 KiB
Minimum1996-11-04 00:00:00
Maximum2020-07-09 00:00:00
2024-04-18T05:11:17.754671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T05:11:17.869922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)

전화번호
Text

MISSING 

Distinct336
Distinct (%)96.0%
Missing265
Missing (%)43.1%
Memory size4.9 KiB
2024-04-18T05:11:18.096746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length16
Mean length9.6285714
Min length1

Characters and Unicode

Total characters3370
Distinct characters16
Distinct categories7 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique323 ?
Unique (%)92.3%

Sample

1st row960-5955
2nd row2217-7770
3rd row2213-6964
4th row923-8472
5th row927-4260
ValueCountFrequency (%)
2057-3608 3
 
0.9%
02 3
 
0.9%
921-2366 2
 
0.6%
2
 
0.6%
564-9140 2
 
0.6%
957-7575 2
 
0.6%
969-1114 2
 
0.6%
0 2
 
0.6%
2215-5771 2
 
0.6%
02-2217-7770 2
 
0.6%
Other values (326) 330
93.8%
2024-04-18T05:11:18.441305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 538
16.0%
- 470
13.9%
0 400
11.9%
9 298
8.8%
5 263
7.8%
1 260
7.7%
4 254
7.5%
3 238
7.1%
7 236
7.0%
6 228
6.8%
Other values (6) 185
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2892
85.8%
Dash Punctuation 470
 
13.9%
Space Separator 3
 
0.1%
Math Symbol 2
 
0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 538
18.6%
0 400
13.8%
9 298
10.3%
5 263
9.1%
1 260
9.0%
4 254
8.8%
3 238
8.2%
7 236
8.2%
6 228
7.9%
8 177
 
6.1%
Dash Punctuation
ValueCountFrequency (%)
- 470
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3370
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 538
16.0%
- 470
13.9%
0 400
11.9%
9 298
8.8%
5 263
7.8%
1 260
7.7%
4 254
7.5%
3 238
7.1%
7 236
7.0%
6 228
6.8%
Other values (6) 185
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3370
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 538
16.0%
- 470
13.9%
0 400
11.9%
9 298
8.8%
5 263
7.8%
1 260
7.7%
4 254
7.5%
3 238
7.1%
7 236
7.0%
6 228
6.8%
Other values (6) 185
 
5.5%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing615
Missing (%)100.0%
Memory size5.5 KiB

소재지우편번호
Text

MISSING 

Distinct75
Distinct (%)22.0%
Missing274
Missing (%)44.6%
Memory size4.9 KiB
2024-04-18T05:11:18.641048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0058651
Min length6

Characters and Unicode

Total characters2048
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

Unique32 ?
Unique (%)9.4%

Sample

1st row130849
2nd row130-805
3rd row130876
4th row130864
5th row130840
ValueCountFrequency (%)
130100 87
25.5%
130845 22
 
6.5%
130101 21
 
6.2%
130070 12
 
3.5%
130864 12
 
3.5%
130110 10
 
2.9%
130823 10
 
2.9%
130060 9
 
2.6%
130867 9
 
2.6%
130842 9
 
2.6%
Other values (65) 140
41.1%
2024-04-18T05:11:18.958672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 673
32.9%
1 536
26.2%
3 382
18.7%
8 161
 
7.9%
4 86
 
4.2%
6 57
 
2.8%
7 45
 
2.2%
2 43
 
2.1%
5 41
 
2.0%
9 22
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2046
99.9%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 673
32.9%
1 536
26.2%
3 382
18.7%
8 161
 
7.9%
4 86
 
4.2%
6 57
 
2.8%
7 45
 
2.2%
2 43
 
2.1%
5 41
 
2.0%
9 22
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2048
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 673
32.9%
1 536
26.2%
3 382
18.7%
8 161
 
7.9%
4 86
 
4.2%
6 57
 
2.8%
7 45
 
2.2%
2 43
 
2.1%
5 41
 
2.0%
9 22
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2048
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 673
32.9%
1 536
26.2%
3 382
18.7%
8 161
 
7.9%
4 86
 
4.2%
6 57
 
2.8%
7 45
 
2.2%
2 43
 
2.1%
5 41
 
2.0%
9 22
 
1.1%

지번주소
Text

MISSING 

Distinct331
Distinct (%)63.0%
Missing90
Missing (%)14.6%
Memory size4.9 KiB
2024-04-18T05:11:19.116195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length38
Mean length28.895238
Min length9

Characters and Unicode

Total characters15170
Distinct characters229
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique273 ?
Unique (%)52.0%

Sample

1st row서울특별시 동대문구 제기동 ****번지
2nd row서울특별시 동대문구 전농*동 **번지
3rd row서울특별시 동대문구 답십리동 ***번지 **호
4th row서울특별시 동대문구 용두동 ***번지 *호
5th row서울특별시 동대문구 용두동 ***번지 **호 지하
ValueCountFrequency (%)
서울특별시 524
16.8%
동대문구 524
16.8%
호 500
16.1%
번지 459
14.7%
장안동 204
 
6.6%
층 132
 
4.2%
79
 
2.5%
동원빌딩 51
 
1.6%
용두동 48
 
1.5%
청량리동 44
 
1.4%
Other values (227) 548
17.6%
2024-04-18T05:11:19.375037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 2956
19.5%
2601
17.1%
동 1186
 
7.8%
대 547
 
3.6%
문 542
 
3.6%
서 530
 
3.5%
울 528
 
3.5%
구 526
 
3.5%
시 526
 
3.5%
별 524
 
3.5%
Other values (219) 4704
31.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9479
62.5%
Other Punctuation 2963
 
19.5%
Space Separator 2601
 
17.1%
Dash Punctuation 59
 
0.4%
Decimal Number 26
 
0.2%
Uppercase Letter 24
 
0.2%
Lowercase Letter 14
 
0.1%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1186
 
12.5%
대 547
 
5.8%
문 542
 
5.7%
서 530
 
5.6%
울 528
 
5.6%
구 526
 
5.5%
시 526
 
5.5%
별 524
 
5.5%
특 524
 
5.5%
호 520
 
5.5%
Other values (182) 3526
37.2%
Uppercase Letter
ValueCountFrequency (%)
A 7
29.2%
J 3
12.5%
C 2
 
8.3%
X 2
 
8.3%
B 1
 
4.2%
G 1
 
4.2%
S 1
 
4.2%
K 1
 
4.2%
Y 1
 
4.2%
T 1
 
4.2%
Other values (4) 4
16.7%
Decimal Number
ValueCountFrequency (%)
2 5
19.2%
7 4
15.4%
9 3
11.5%
1 3
11.5%
4 2
 
7.7%
5 2
 
7.7%
0 2
 
7.7%
6 2
 
7.7%
3 2
 
7.7%
8 1
 
3.8%
Lowercase Letter
ValueCountFrequency (%)
e 3
21.4%
a 2
14.3%
t 2
14.3%
s 2
14.3%
l 2
14.3%
w 1
 
7.1%
x 1
 
7.1%
j 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
* 2956
99.8%
, 7
 
0.2%
Space Separator
ValueCountFrequency (%)
2601
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 59
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9479
62.5%
Common 5653
37.3%
Latin 38
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1186
 
12.5%
대 547
 
5.8%
문 542
 
5.7%
서 530
 
5.6%
울 528
 
5.6%
구 526
 
5.5%
시 526
 
5.5%
별 524
 
5.5%
특 524
 
5.5%
호 520
 
5.5%
Other values (182) 3526
37.2%
Latin
ValueCountFrequency (%)
A 7
18.4%
e 3
 
7.9%
J 3
 
7.9%
a 2
 
5.3%
t 2
 
5.3%
s 2
 
5.3%
l 2
 
5.3%
C 2
 
5.3%
X 2
 
5.3%
B 1
 
2.6%
Other values (12) 12
31.6%
Common
ValueCountFrequency (%)
* 2956
52.3%
2601
46.0%
- 59
 
1.0%
, 7
 
0.1%
2 5
 
0.1%
~ 4
 
0.1%
7 4
 
0.1%
9 3
 
0.1%
1 3
 
0.1%
4 2
 
< 0.1%
Other values (5) 9
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9479
62.5%
ASCII 5691
37.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 2956
51.9%
2601
45.7%
- 59
 
1.0%
A 7
 
0.1%
, 7
 
0.1%
2 5
 
0.1%
~ 4
 
0.1%
7 4
 
0.1%
e 3
 
0.1%
9 3
 
0.1%
Other values (27) 42
 
0.7%
Hangul
ValueCountFrequency (%)
동 1186
 
12.5%
대 547
 
5.8%
문 542
 
5.7%
서 530
 
5.6%
울 528
 
5.6%
구 526
 
5.5%
시 526
 
5.5%
별 524
 
5.5%
특 524
 
5.5%
호 520
 
5.5%
Other values (182) 3526
37.2%

도로명주소
Text

MISSING 

Distinct450
Distinct (%)87.7%
Missing102
Missing (%)16.6%
Memory size4.9 KiB
2024-04-18T05:11:19.588292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length72
Median length47
Mean length33.576998
Min length22

Characters and Unicode

Total characters17225
Distinct characters260
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

Unique405 ?
Unique (%)78.9%

Sample

1st row서울특별시 동대문구 정릉천동로 *** (제기동)
2nd row서울특별시 동대문구 사가정로 *** (전농동)
3rd row서울특별시 동대문구 답십리로**길 *-** (답십리동)
4th row서울특별시 동대문구 무학로 ***-* (용두동)
5th row서울특별시 동대문구 무학로**길 **-* (용두동,지하)
ValueCountFrequency (%)
524
16.6%
서울특별시 513
16.3%
동대문구 511
16.2%
호 188
 
6.0%
층 156
 
4.9%
장안동 107
 
3.4%
왕산로 49
 
1.6%
천호대로**길 46
 
1.5%
천호대로 43
 
1.4%
용두동 43
 
1.4%
Other values (373) 973
30.9%
2024-04-18T05:11:19.908427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2658
 
15.4%
* 2609
 
15.1%
동 1118
 
6.5%
대 653
 
3.8%
, 575
 
3.3%
문 556
 
3.2%
시 541
 
3.1%
서 540
 
3.1%
울 535
 
3.1%
구 514
 
3.0%
Other values (250) 6926
40.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10204
59.2%
Other Punctuation 3184
 
18.5%
Space Separator 2658
 
15.4%
Close Punctuation 513
 
3.0%
Open Punctuation 513
 
3.0%
Dash Punctuation 59
 
0.3%
Decimal Number 43
 
0.2%
Uppercase Letter 30
 
0.2%
Lowercase Letter 17
 
0.1%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1118
 
11.0%
대 653
 
6.4%
문 556
 
5.4%
시 541
 
5.3%
서 540
 
5.3%
울 535
 
5.2%
구 514
 
5.0%
별 513
 
5.0%
특 513
 
5.0%
로 511
 
5.0%
Other values (214) 4210
41.3%
Uppercase Letter
ValueCountFrequency (%)
B 8
26.7%
A 8
26.7%
J 3
 
10.0%
X 2
 
6.7%
C 2
 
6.7%
G 1
 
3.3%
E 1
 
3.3%
N 1
 
3.3%
I 1
 
3.3%
W 1
 
3.3%
Other values (2) 2
 
6.7%
Lowercase Letter
ValueCountFrequency (%)
e 4
23.5%
s 3
17.6%
t 2
11.8%
l 2
11.8%
a 2
11.8%
w 1
 
5.9%
k 1
 
5.9%
j 1
 
5.9%
x 1
 
5.9%
Decimal Number
ValueCountFrequency (%)
1 10
23.3%
0 8
18.6%
4 6
14.0%
9 6
14.0%
2 5
11.6%
3 4
 
9.3%
6 3
 
7.0%
5 1
 
2.3%
Other Punctuation
ValueCountFrequency (%)
* 2609
81.9%
, 575
 
18.1%
Space Separator
ValueCountFrequency (%)
2658
100.0%
Close Punctuation
ValueCountFrequency (%)
) 513
100.0%
Open Punctuation
ValueCountFrequency (%)
( 513
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 59
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10204
59.2%
Common 6974
40.5%
Latin 47
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1118
 
11.0%
대 653
 
6.4%
문 556
 
5.4%
시 541
 
5.3%
서 540
 
5.3%
울 535
 
5.2%
구 514
 
5.0%
별 513
 
5.0%
특 513
 
5.0%
로 511
 
5.0%
Other values (214) 4210
41.3%
Latin
ValueCountFrequency (%)
B 8
17.0%
A 8
17.0%
e 4
 
8.5%
s 3
 
6.4%
J 3
 
6.4%
X 2
 
4.3%
t 2
 
4.3%
C 2
 
4.3%
l 2
 
4.3%
a 2
 
4.3%
Other values (11) 11
23.4%
Common
ValueCountFrequency (%)
2658
38.1%
* 2609
37.4%
, 575
 
8.2%
) 513
 
7.4%
( 513
 
7.4%
- 59
 
0.8%
1 10
 
0.1%
0 8
 
0.1%
4 6
 
0.1%
9 6
 
0.1%
Other values (5) 17
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10204
59.2%
ASCII 7021
40.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2658
37.9%
* 2609
37.2%
, 575
 
8.2%
) 513
 
7.3%
( 513
 
7.3%
- 59
 
0.8%
1 10
 
0.1%
B 8
 
0.1%
0 8
 
0.1%
A 8
 
0.1%
Other values (26) 60
 
0.9%
Hangul
ValueCountFrequency (%)
동 1118
 
11.0%
대 653
 
6.4%
문 556
 
5.4%
시 541
 
5.3%
서 540
 
5.3%
울 535
 
5.2%
구 514
 
5.0%
별 513
 
5.0%
특 513
 
5.0%
로 511
 
5.0%
Other values (214) 4210
41.3%

도로명우편번호
Text

MISSING 

Distinct156
Distinct (%)52.7%
Missing319
Missing (%)51.9%
Memory size4.9 KiB
2024-04-18T05:11:20.203248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.4087838
Min length5

Characters and Unicode

Total characters1601
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

Unique97 ?
Unique (%)32.8%

Sample

1st row130850
2nd row130876
3rd row130810
4th row130823
5th row02634
ValueCountFrequency (%)
02622 12
 
4.1%
130823 9
 
3.0%
130864 8
 
2.7%
130844 6
 
2.0%
02624 6
 
2.0%
130070 6
 
2.0%
02633 6
 
2.0%
02594 5
 
1.7%
130842 5
 
1.7%
130812 5
 
1.7%
Other values (146) 228
77.0%
2024-04-18T05:11:20.604321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 367
22.9%
2 265
16.6%
3 190
11.9%
1 170
10.6%
8 137
 
8.6%
4 125
 
7.8%
6 122
 
7.6%
5 117
 
7.3%
7 61
 
3.8%
9 46
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1600
99.9%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 367
22.9%
2 265
16.6%
3 190
11.9%
1 170
10.6%
8 137
 
8.6%
4 125
 
7.8%
6 122
 
7.6%
5 117
 
7.3%
7 61
 
3.8%
9 46
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1601
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 367
22.9%
2 265
16.6%
3 190
11.9%
1 170
10.6%
8 137
 
8.6%
4 125
 
7.8%
6 122
 
7.6%
5 117
 
7.3%
7 61
 
3.8%
9 46
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1601
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 367
22.9%
2 265
16.6%
3 190
11.9%
1 170
10.6%
8 137
 
8.6%
4 125
 
7.8%
6 122
 
7.6%
5 117
 
7.3%
7 61
 
3.8%
9 46
 
2.9%

사업장명
Text

Distinct604
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2024-04-18T05:11:20.822811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length24
Mean length7.1333333
Min length1

Characters and Unicode

Total characters4387
Distinct characters458
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

Unique593 ?
Unique (%)96.4%

Sample

1st row신영상사
2nd row윤선생영어숲동대문
3rd row남양알로에신답대리점
4th row영진문화사
5th row원진상사
ValueCountFrequency (%)
주식회사 50
 
5.8%
주 22
 
2.6%
대리점 11
 
1.3%
인셀덤 10
 
1.2%
코웨이 4
 
0.5%
유니베라 4
 
0.5%
윤선생영어교실 4
 
0.5%
동대문 4
 
0.5%
동대문지사 3
 
0.4%
go 3
 
0.4%
Other values (699) 741
86.6%
2024-04-18T05:11:21.139018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
242
 
5.5%
주 143
 
3.3%
리 117
 
2.7%
스 108
 
2.5%
사 108
 
2.5%
) 103
 
2.3%
( 103
 
2.3%
이 98
 
2.2%
대 95
 
2.2%
점 70
 
1.6%
Other values (448) 3200
72.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3640
83.0%
Space Separator 242
 
5.5%
Uppercase Letter 135
 
3.1%
Lowercase Letter 118
 
2.7%
Close Punctuation 103
 
2.3%
Open Punctuation 103
 
2.3%
Other Punctuation 24
 
0.5%
Decimal Number 19
 
0.4%
Dash Punctuation 2
 
< 0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 143
 
3.9%
리 117
 
3.2%
스 108
 
3.0%
사 108
 
3.0%
이 98
 
2.7%
대 95
 
2.6%
점 70
 
1.9%
회 59
 
1.6%
식 57
 
1.6%
에 54
 
1.5%
Other values (395) 2731
75.0%
Uppercase Letter
ValueCountFrequency (%)
S 13
 
9.6%
O 13
 
9.6%
H 12
 
8.9%
G 12
 
8.9%
C 11
 
8.1%
L 10
 
7.4%
M 9
 
6.7%
E 8
 
5.9%
I 6
 
4.4%
B 6
 
4.4%
Other values (10) 35
25.9%
Lowercase Letter
ValueCountFrequency (%)
e 22
18.6%
a 14
11.9%
n 10
8.5%
t 10
8.5%
l 9
 
7.6%
i 8
 
6.8%
m 7
 
5.9%
c 5
 
4.2%
o 5
 
4.2%
r 4
 
3.4%
Other values (8) 24
20.3%
Decimal Number
ValueCountFrequency (%)
1 14
73.7%
2 1
 
5.3%
9 1
 
5.3%
5 1
 
5.3%
0 1
 
5.3%
4 1
 
5.3%
Other Punctuation
ValueCountFrequency (%)
. 14
58.3%
& 6
25.0%
, 3
 
12.5%
/ 1
 
4.2%
Space Separator
ValueCountFrequency (%)
242
100.0%
Close Punctuation
ValueCountFrequency (%)
) 103
100.0%
Open Punctuation
ValueCountFrequency (%)
( 103
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3641
83.0%
Common 493
 
11.2%
Latin 253
 
5.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 143
 
3.9%
리 117
 
3.2%
스 108
 
3.0%
사 108
 
3.0%
이 98
 
2.7%
대 95
 
2.6%
점 70
 
1.9%
회 59
 
1.6%
식 57
 
1.6%
에 54
 
1.5%
Other values (396) 2732
75.0%
Latin
ValueCountFrequency (%)
e 22
 
8.7%
a 14
 
5.5%
S 13
 
5.1%
O 13
 
5.1%
H 12
 
4.7%
G 12
 
4.7%
C 11
 
4.3%
L 10
 
4.0%
n 10
 
4.0%
t 10
 
4.0%
Other values (28) 126
49.8%
Common
ValueCountFrequency (%)
242
49.1%
) 103
20.9%
( 103
20.9%
1 14
 
2.8%
. 14
 
2.8%
& 6
 
1.2%
, 3
 
0.6%
- 2
 
0.4%
/ 1
 
0.2%
2 1
 
0.2%
Other values (4) 4
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3640
83.0%
ASCII 746
 
17.0%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
242
32.4%
) 103
13.8%
( 103
13.8%
e 22
 
2.9%
1 14
 
1.9%
a 14
 
1.9%
. 14
 
1.9%
S 13
 
1.7%
O 13
 
1.7%
H 12
 
1.6%
Other values (42) 196
26.3%
Hangul
ValueCountFrequency (%)
주 143
 
3.9%
리 117
 
3.2%
스 108
 
3.0%
사 108
 
3.0%
이 98
 
2.7%
대 95
 
2.6%
점 70
 
1.9%
회 59
 
1.6%
식 57
 
1.6%
에 54
 
1.5%
Other values (395) 2731
75.0%
None
ValueCountFrequency (%)
㈜ 1
100.0%

최종수정일자
Date

UNIQUE 

Distinct615
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
Minimum2007-12-05 10:26:05
Maximum2024-04-09 13:08:57
2024-04-18T05:11:21.247251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T05:11:21.352543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
I
494 
U
121 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 494
80.3%
U 121
 
19.7%

Length

2024-04-18T05:11:21.446598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:11:21.522389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 494
80.3%
u 121
 
19.7%

데이터갱신일자
Date

Distinct131
Distinct (%)21.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 23:01:00
2024-04-18T05:11:21.628413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T05:11:21.734515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing615
Missing (%)100.0%
Memory size5.5 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct388
Distinct (%)63.9%
Missing8
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean204685.89
Minimum202023.92
Maximum206687.93
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2024-04-18T05:11:21.836500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum202023.92
5-th percentile202251.56
Q1203499.33
median205060.27
Q3205787.11
95-th percentile206116.05
Maximum206687.93
Range4664.0091
Interquartile range (IQR)2287.7802

Descriptive statistics

Standard deviation1316.354
Coefficient of variation (CV)0.0064310928
Kurtosis-1.0346741
Mean204685.89
Median Absolute Deviation (MAD)840.74915
Skewness-0.60273257
Sum1.2424434 × 108
Variance1732787.8
MonotonicityNot monotonic
2024-04-18T05:11:21.941876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
205787.106208763 89
 
14.5%
204933.43346021 8
 
1.3%
204082.111844228 6
 
1.0%
202582.019563324 6
 
1.0%
205142.103666569 5
 
0.8%
203075.098504907 5
 
0.8%
203369.281852618 5
 
0.8%
203188.427527295 4
 
0.7%
204190.10878253 4
 
0.7%
203851.375424856 4
 
0.7%
Other values (378) 471
76.6%
(Missing) 8
 
1.3%
ValueCountFrequency (%)
202023.921749857 1
 
0.2%
202033.22548938 1
 
0.2%
202045.581261433 3
0.5%
202046.336404167 1
 
0.2%
202056.394367168 1
 
0.2%
202067.971954012 1
 
0.2%
202091.896824059 1
 
0.2%
202093.908184725 2
0.3%
202104.76690462 2
0.3%
202114.75984426 1
 
0.2%
ValueCountFrequency (%)
206687.930864017 1
0.2%
206536.015099006 1
0.2%
206522.763968502 1
0.2%
206521.405320134 1
0.2%
206502.751884821 1
0.2%
206483.555525111 1
0.2%
206473.617790663 1
0.2%
206455.561310775 2
0.3%
206419.497908653 1
0.2%
206405.429725609 1
0.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct389
Distinct (%)64.1%
Missing8
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean452438.67
Minimum450994.91
Maximum455801.64
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2024-04-18T05:11:22.043158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum450994.91
5-th percentile451167.62
Q1451349.11
median452466.87
Q3453041.01
95-th percentile454315.17
Maximum455801.64
Range4806.7248
Interquartile range (IQR)1691.8987

Descriptive statistics

Standard deviation1065.2534
Coefficient of variation (CV)0.0023544703
Kurtosis-0.10169879
Mean452438.67
Median Absolute Deviation (MAD)851.88287
Skewness0.59711275
Sum2.7463027 × 108
Variance1134764.8
MonotonicityNot monotonic
2024-04-18T05:11:22.149348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
451191.34653897 89
 
14.5%
451349.111701538 8
 
1.3%
452860.046752763 6
 
1.0%
452472.990548179 6
 
1.0%
453316.133764732 5
 
0.8%
452918.836458244 5
 
0.8%
451167.624821007 5
 
0.8%
453238.594217594 4
 
0.7%
452835.044818809 4
 
0.7%
453415.795068163 4
 
0.7%
Other values (379) 471
76.6%
(Missing) 8
 
1.3%
ValueCountFrequency (%)
450994.913744005 1
 
0.2%
451017.540622804 1
 
0.2%
451059.346901649 1
 
0.2%
451065.321633611 2
0.3%
451080.986788942 3
0.5%
451103.146980087 2
0.3%
451107.156556872 1
 
0.2%
451108.047802152 1
 
0.2%
451120.5353714 1
 
0.2%
451122.88876405 1
 
0.2%
ValueCountFrequency (%)
455801.638525525 1
0.2%
455710.688794955 1
0.2%
455659.587050802 1
0.2%
455648.553079576 2
0.3%
455643.381169191 1
0.2%
455558.950900891 1
0.2%
455449.903263934 2
0.3%
455220.257356121 1
0.2%
455106.352468219 1
0.2%
454976.715315362 1
0.2%

자산규모
Real number (ℝ)

MISSING  ZEROS 

Distinct65
Distinct (%)48.1%
Missing480
Missing (%)78.0%
Infinite0
Infinite (%)0.0%
Mean3.072251 × 1010
Minimum0
Maximum3.8252004 × 1012
Zeros30
Zeros (%)4.9%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2024-04-18T05:11:22.254179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16250000
median50000000
Q32.391108 × 108
95-th percentile9.3426945 × 109
Maximum3.8252004 × 1012
Range3.8252004 × 1012
Interquartile range (IQR)2.328608 × 108

Descriptive statistics

Standard deviation3.2945374 × 1011
Coefficient of variation (CV)10.723529
Kurtosis134.2645
Mean3.072251 × 1010
Median Absolute Deviation (MAD)50000000
Skewness11.573283
Sum4.1475389 × 1012
Variance1.0853976 × 1023
MonotonicityNot monotonic
2024-04-18T05:11:22.370829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 30
 
4.9%
50000000 14
 
2.3%
100000000 12
 
2.0%
10000000 11
 
1.8%
20000000 4
 
0.7%
60000000 2
 
0.3%
80000000 2
 
0.3%
300000000 2
 
0.3%
5000000 2
 
0.3%
115860060 1
 
0.2%
Other values (55) 55
 
8.9%
(Missing) 480
78.0%
ValueCountFrequency (%)
0 30
4.9%
2593418 1
 
0.2%
3000000 1
 
0.2%
5000000 2
 
0.3%
7500000 1
 
0.2%
10000000 11
 
1.8%
10700000 1
 
0.2%
20000000 4
 
0.7%
21070000 1
 
0.2%
27753720 1
 
0.2%
ValueCountFrequency (%)
3825200434847 1
0.2%
194927684422 1
0.2%
27753832640 1
0.2%
14708751395 1
0.2%
12016227923 1
0.2%
11495710125 1
0.2%
10966805822 1
0.2%
8646646764 1
0.2%
6986000000 1
0.2%
5719153118 1
0.2%

부채총액
Real number (ℝ)

MISSING  ZEROS 

Distinct55
Distinct (%)40.7%
Missing480
Missing (%)78.0%
Infinite0
Infinite (%)0.0%
Mean1.0285604 × 109
Minimum0
Maximum5.6601747 × 1010
Zeros78
Zeros (%)12.7%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2024-04-18T05:11:22.480620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31.3597605 × 108
95-th percentile5.1814957 × 109
Maximum5.6601747 × 1010
Range5.6601747 × 1010
Interquartile range (IQR)1.3597605 × 108

Descriptive statistics

Standard deviation5.2647657 × 109
Coefficient of variation (CV)5.1185773
Kurtosis94.855853
Mean1.0285604 × 109
Median Absolute Deviation (MAD)0
Skewness9.2486212
Sum1.3885565 × 1011
Variance2.7717758 × 1019
MonotonicityNot monotonic
2024-04-18T05:11:22.580943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 78
 
12.7%
50000000 2
 
0.3%
10000000 2
 
0.3%
20000000 2
 
0.3%
90000000 1
 
0.2%
188218170 1
 
0.2%
2393916259 1
 
0.2%
15520623 1
 
0.2%
135174755 1
 
0.2%
1262570000 1
 
0.2%
Other values (45) 45
 
7.3%
(Missing) 480
78.0%
ValueCountFrequency (%)
0 78
12.7%
297000 1
 
0.2%
700000 1
 
0.2%
2000000 1
 
0.2%
5000000 1
 
0.2%
5495000 1
 
0.2%
10000000 2
 
0.3%
11000000 1
 
0.2%
15520623 1
 
0.2%
17426348 1
 
0.2%
ValueCountFrequency (%)
56601747254 1
0.2%
18359722598 1
0.2%
10658291131 1
0.2%
6796571743 1
0.2%
6075914091 1
0.2%
5234000000 1
0.2%
5184290315 1
0.2%
5180298061 1
0.2%
2993287899 1
0.2%
2574001828 1
0.2%

자본금
Real number (ℝ)

MISSING  ZEROS 

Distinct42
Distinct (%)30.9%
Missing479
Missing (%)77.9%
Infinite0
Infinite (%)0.0%
Mean5.2519322 × 108
Minimum-50199722
Maximum2.6022381 × 1010
Zeros18
Zeros (%)2.9%
Negative1
Negative (%)0.2%
Memory size5.5 KiB
2024-04-18T05:11:22.680780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-50199722
5-th percentile0
Q110000000
median50000000
Q31 × 108
95-th percentile1.6163838 × 109
Maximum2.6022381 × 1010
Range2.6072581 × 1010
Interquartile range (IQR)90000000

Descriptive statistics

Standard deviation2.4868589 × 109
Coefficient of variation (CV)4.7351314
Kurtosis83.773889
Mean5.2519322 × 108
Median Absolute Deviation (MAD)47000000
Skewness8.5610939
Sum7.1426278 × 1010
Variance6.1844672 × 1018
MonotonicityNot monotonic
2024-04-18T05:11:22.783939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
50000000 33
 
5.4%
0 18
 
2.9%
10000000 17
 
2.8%
100000000 13
 
2.1%
3000000 6
 
1.0%
20000000 5
 
0.8%
300000000 3
 
0.5%
950000000 2
 
0.3%
1000000 2
 
0.3%
60000000 2
 
0.3%
Other values (32) 35
 
5.7%
(Missing) 479
77.9%
ValueCountFrequency (%)
-50199722 1
 
0.2%
0 18
2.9%
1000000 2
 
0.3%
2000000 1
 
0.2%
3000000 6
 
1.0%
5000000 1
 
0.2%
6043418 1
 
0.2%
10000000 17
2.8%
10250577 1
 
0.2%
10327372 1
 
0.2%
ValueCountFrequency (%)
26022381009 1
0.2%
8349168948 1
0.2%
6835929862 1
0.2%
5419796034 1
0.2%
4200000000 1
0.2%
4020000000 1
0.2%
2715535319 1
0.2%
1250000000 1
0.2%
1200000000 1
0.2%
1000000000 2
0.3%

판매방식명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing615
Missing (%)100.0%
Memory size5.5 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)자산규모부채총액자본금판매방식명
03050000199630501002320005219961104<NA>1영업/정상1정상영업<NA><NA><NA>19961104960-5955<NA><NA>서울특별시 동대문구 제기동 ****번지서울특별시 동대문구 정릉천동로 *** (제기동)<NA>신영상사2012-11-26 15:44:58I2018-08-31 23:59:59.0<NA>203095.67321453423.742663<NA><NA><NA><NA>
13050000199630501002320009419961212<NA>3폐업3폐업처리20131227<NA><NA><NA>2217-7770<NA>130849서울특별시 동대문구 전농*동 **번지서울특별시 동대문구 사가정로 *** (전농동)130850윤선생영어숲동대문2013-12-27 09:14:16I2018-08-31 23:59:59.0<NA>205220.658039452809.966304<NA><NA><NA><NA>
23050000199630501002320009519961214<NA>3폐업3폐업처리20130410<NA><NA><NA>2213-6964<NA><NA>서울특별시 동대문구 답십리동 ***번지 **호서울특별시 동대문구 답십리로**길 *-** (답십리동)<NA>남양알로에신답대리점2013-04-10 09:13:27I2018-08-31 23:59:59.0<NA>204496.528839452349.108893<NA><NA><NA><NA>
33050000199730501002320011119970310<NA>3폐업3폐업처리20091125<NA><NA><NA>923-8472<NA><NA>서울특별시 동대문구 용두동 ***번지 *호서울특별시 동대문구 무학로 ***-* (용두동)<NA>영진문화사2009-11-25 15:34:41I2018-08-31 23:59:59.0<NA>202597.14554452556.999957<NA><NA><NA><NA>
43050000199830501002320017719980327<NA>3폐업3폐업처리20071210<NA><NA><NA>927-4260<NA><NA>서울특별시 동대문구 용두동 ***번지 **호 지하서울특별시 동대문구 무학로**길 **-* (용두동,지하)<NA>원진상사2007-12-12 10:29:23I2018-08-31 23:59:59.0<NA>202721.094378452508.069006<NA><NA><NA><NA>
53050000199830501002320020419980905<NA>3폐업3폐업처리20130903<NA><NA><NA>2217-2905<NA><NA>서울특별시 동대문구 휘경동 ***번지 *호 효자워너빌 *층 *호서울특별시 동대문구 망우로 **, *호 (휘경동,효자워너빌 *층)<NA>경희건강생활2013-09-03 09:16:10I2018-08-31 23:59:59.0<NA>205310.579776454183.350224<NA><NA><NA><NA>
6305000019993050100232002511999-05-31<NA>5제외/삭제/전출5타시군구이관2024-03-25<NA><NA>1999-05-312244-7125<NA>130-805서울특별시 동대문구 답십리*동 ***번지 **호 삼용빌딩 ***서울특별시 동대문구 황물로 *** (답십리동,삼용빌딩 ***)<NA>고시포코2024-03-25 10:14:33U2023-12-02 22:07:00.0<NA>204486.997989451928.858919<NA><NA><NA><NA>
73050000199930501002320026019990710<NA>3폐업3폐업처리20120320<NA><NA><NA>2202-8254<NA><NA>서울특별시 동대문구 용두동 ***번지 **호서울특별시 동대문구 왕산로 ** (용두동)<NA>북구대우자동차판매(주)2012-03-20 15:20:19I2018-08-31 23:59:59.0<NA>202582.019563452860.0467530080000000<NA>
83050000199930501002320028719991026200809114취소/말소/만료/정지/중지4직권취소<NA><NA><NA>19991026927-8661<NA><NA>서울특별시 동대문구 용두동 ***번지 *호서울특별시 동대문구 왕산로**나길 ** (용두동)<NA>내가보산업2008-09-18 15:51:35I2018-08-31 23:59:59.0<NA>202869.074187452745.387862<NA><NA><NA><NA>
9305000020013050100232004532001-08-02<NA>1영업/정상1정상영업<NA><NA><NA>2001-08-022242-1557<NA><NA>서울특별시 동대문구 답십리동 ***번지<NA><NA>쉐보레신답선봉대리점2023-08-01 09:09:59U2022-12-08 00:03:00.0<NA><NA><NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)자산규모부채총액자본금판매방식명
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