Overview

Dataset statistics

Number of variables29
Number of observations1301
Missing cells13386
Missing cells (%)35.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory315.2 KiB
Average record size in memory248.1 B

Variable types

Categorical8
Numeric7
DateTime4
Unsupported4
Text6

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
Author마포구
URLhttps://data.seoul.go.kr/dataList/OA-18765/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
휴업시작일자 is highly imbalanced (98.9%)Imbalance
휴업종료일자 is highly imbalanced (98.9%)Imbalance
재개업일자 is highly imbalanced (98.9%)Imbalance
인허가취소일자 has 1301 (100.0%) missing valuesMissing
폐업일자 has 845 (65.0%) missing valuesMissing
전화번호 has 187 (14.4%) missing valuesMissing
소재지면적 has 1301 (100.0%) missing valuesMissing
소재지우편번호 has 998 (76.7%) missing valuesMissing
지번주소 has 164 (12.6%) missing valuesMissing
도로명주소 has 701 (53.9%) missing valuesMissing
도로명우편번호 has 923 (70.9%) missing valuesMissing
업태구분명 has 1301 (100.0%) missing valuesMissing
좌표정보(X) has 684 (52.6%) missing valuesMissing
좌표정보(Y) has 684 (52.6%) missing valuesMissing
자산규모 has 998 (76.7%) missing valuesMissing
부채총액 has 1000 (76.9%) missing valuesMissing
자본금 has 998 (76.7%) missing valuesMissing
판매방식명 has 1301 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 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 57 (4.4%) zerosZeros
부채총액 has 169 (13.0%) zerosZeros
자본금 has 48 (3.7%) zerosZeros

Reproduction

Analysis started2024-05-11 04:33:09.312072
Analysis finished2024-05-11 04:33:11.507105
Duration2.2 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size10.3 KiB
3130000
1301 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3130000
2nd row3130000
3rd row3130000
4th row3130000
5th row3130000

Common Values

ValueCountFrequency (%)
3130000 1301
100.0%

Length

2024-05-11T04:33:11.708087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:33:12.058332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3130000 1301
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct1301
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0080801 × 1018
Minimum1.996313 × 1018
Maximum2.024313 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.6 KiB
2024-05-11T04:33:12.400594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.996313 × 1018
5-th percentile1.999313 × 1018
Q12.003313 × 1018
median2.006313 × 1018
Q32.012313 × 1018
95-th percentile2.020313 × 1018
Maximum2.024313 × 1018
Range2.8000014 × 1016
Interquartile range (IQR)9 × 1015

Descriptive statistics

Standard deviation6.3764278 × 1015
Coefficient of variation (CV)0.0031753851
Kurtosis-0.27147078
Mean2.0080801 × 1018
Median Absolute Deviation (MAD)4 × 1015
Skewness0.63094655
Sum-6.925428 × 1018
Variance4.0658831 × 1031
MonotonicityStrictly increasing
2024-05-11T04:33:12.851010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1996313011823200002 1
 
0.1%
2009313011823200059 1
 
0.1%
2010313011823200009 1
 
0.1%
2010313011823200008 1
 
0.1%
2010313011823200007 1
 
0.1%
2010313011823200006 1
 
0.1%
2010313011823200005 1
 
0.1%
2010313011823200004 1
 
0.1%
2010313011823200003 1
 
0.1%
2010313011823200002 1
 
0.1%
Other values (1291) 1291
99.2%
ValueCountFrequency (%)
1996313011823200002 1
0.1%
1996313011823200003 1
0.1%
1996313011823200006 1
0.1%
1996313011823200007 1
0.1%
1996313011823200008 1
0.1%
1996313011823200009 1
0.1%
1996313011823200011 1
0.1%
1996313011823200014 1
0.1%
1996313011823200018 1
0.1%
1996313011823200019 1
0.1%
ValueCountFrequency (%)
2024313025523200009 1
0.1%
2024313025523200008 1
0.1%
2024313025523200007 1
0.1%
2024313025523200006 1
0.1%
2024313025523200005 1
0.1%
2024313025523200004 1
0.1%
2024313025523200003 1
0.1%
2024313025523200002 1
0.1%
2024313025523200001 1
0.1%
2023313025523200014 1
0.1%

인허가일자
Date

Distinct1057
Distinct (%)81.2%
Missing0
Missing (%)0.0%
Memory size10.3 KiB
Minimum1996-08-17 00:00:00
Maximum2024-04-24 00:00:00
2024-05-11T04:33:13.394449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:33:13.741818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1301
Missing (%)100.0%
Memory size11.6 KiB

영업상태코드
Categorical

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size10.3 KiB
3
863 
4
297 
1
129 
5
 
10
2
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 863
66.3%
4 297
 
22.8%
1 129
 
9.9%
5 10
 
0.8%
2 2
 
0.2%

Length

2024-05-11T04:33:14.126638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:33:14.494224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 863
66.3%
4 297
 
22.8%
1 129
 
9.9%
5 10
 
0.8%
2 2
 
0.2%

영업상태명
Categorical

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size10.3 KiB
폐업
863 
취소/말소/만료/정지/중지
297 
영업/정상
129 
제외/삭제/전출
 
10
휴업
 
2

Length

Max length14
Median length2
Mean length5.0830131
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 863
66.3%
취소/말소/만료/정지/중지 297
 
22.8%
영업/정상 129
 
9.9%
제외/삭제/전출 10
 
0.8%
휴업 2
 
0.2%

Length

2024-05-11T04:33:14.932501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:33:15.236301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 863
66.3%
취소/말소/만료/정지/중지 297
 
22.8%
영업/정상 129
 
9.9%
제외/삭제/전출 10
 
0.8%
휴업 2
 
0.2%

상세영업상태코드
Real number (ℝ)

Distinct6
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.7194466
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.6 KiB
2024-05-11T04:33:15.574999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median3
Q33
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.8762889
Coefficient of variation (CV)0.50445378
Kurtosis-0.43381709
Mean3.7194466
Median Absolute Deviation (MAD)0
Skewness0.86771946
Sum4839
Variance3.52046
MonotonicityNot monotonic
2024-05-11T04:33:15.923248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3 863
66.3%
7 293
 
22.5%
1 129
 
9.9%
5 10
 
0.8%
4 4
 
0.3%
2 2
 
0.2%
ValueCountFrequency (%)
1 129
 
9.9%
2 2
 
0.2%
3 863
66.3%
4 4
 
0.3%
5 10
 
0.8%
7 293
 
22.5%
ValueCountFrequency (%)
7 293
 
22.5%
5 10
 
0.8%
4 4
 
0.3%
3 863
66.3%
2 2
 
0.2%
1 129
 
9.9%

상세영업상태명
Categorical

Distinct6
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size10.3 KiB
폐업처리
863 
직권말소
293 
정상영업
129 
타시군구이관
 
10
직권취소
 
4

Length

Max length6
Median length4
Mean length4.0153728
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업처리 863
66.3%
직권말소 293
 
22.5%
정상영업 129
 
9.9%
타시군구이관 10
 
0.8%
직권취소 4
 
0.3%
휴업처리 2
 
0.2%

Length

2024-05-11T04:33:16.377655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:33:16.756596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업처리 863
66.3%
직권말소 293
 
22.5%
정상영업 129
 
9.9%
타시군구이관 10
 
0.8%
직권취소 4
 
0.3%
휴업처리 2
 
0.2%

폐업일자
Date

MISSING 

Distinct398
Distinct (%)87.3%
Missing845
Missing (%)65.0%
Memory size10.3 KiB
Minimum2003-11-25 00:00:00
Maximum2024-04-29 00:00:00
2024-05-11T04:33:17.372972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:33:17.994031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.3 KiB
<NA>
1299 
20210401
 
1
20200901
 
1

Length

Max length8
Median length4
Mean length4.0061491
Min length4

Unique

Unique2 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1299
99.8%
20210401 1
 
0.1%
20200901 1
 
0.1%

Length

2024-05-11T04:33:18.628799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:33:19.087707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1299
99.8%
20210401 1
 
0.1%
20200901 1
 
0.1%

휴업종료일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.3 KiB
<NA>
1299 
20260401
 
1
20210331
 
1

Length

Max length8
Median length4
Mean length4.0061491
Min length4

Unique

Unique2 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1299
99.8%
20260401 1
 
0.1%
20210331 1
 
0.1%

Length

2024-05-11T04:33:19.573665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:33:19.953095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1299
99.8%
20260401 1
 
0.1%
20210331 1
 
0.1%

재개업일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.3 KiB
<NA>
1299 
20091209
 
1
20070522
 
1

Length

Max length8
Median length4
Mean length4.0061491
Min length4

Unique

Unique2 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1299
99.8%
20091209 1
 
0.1%
20070522 1
 
0.1%

Length

2024-05-11T04:33:20.438857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:33:20.919222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1299
99.8%
20091209 1
 
0.1%
20070522 1
 
0.1%

전화번호
Text

MISSING 

Distinct1042
Distinct (%)93.5%
Missing187
Missing (%)14.4%
Memory size10.3 KiB
2024-05-11T04:33:21.610844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length16
Mean length11.032316
Min length2

Characters and Unicode

Total characters12290
Distinct characters15
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique997 ?
Unique (%)89.5%

Sample

1st row02 716 1114
2nd row20778024
3rd row02 702 2583
4th row02 393 2262
5th row02 710 7780
ValueCountFrequency (%)
02 610
26.3%
322 36
 
1.5%
333 26
 
1.1%
334 25
 
1.1%
338 24
 
1.0%
3141 23
 
1.0%
3142 23
 
1.0%
325 22
 
0.9%
3143 21
 
0.9%
337 20
 
0.9%
Other values (1132) 1493
64.3%
2024-05-11T04:33:23.003134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1929
15.7%
0 1699
13.8%
2 1673
13.6%
3 1526
12.4%
1 956
7.8%
7 928
7.6%
4 681
 
5.5%
5 654
 
5.3%
6 649
 
5.3%
- 596
 
4.8%
Other values (5) 999
8.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9749
79.3%
Space Separator 1929
 
15.7%
Dash Punctuation 596
 
4.8%
Other Punctuation 9
 
0.1%
Math Symbol 7
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1699
17.4%
2 1673
17.2%
3 1526
15.7%
1 956
9.8%
7 928
9.5%
4 681
7.0%
5 654
 
6.7%
6 649
 
6.7%
8 569
 
5.8%
9 414
 
4.2%
Other Punctuation
ValueCountFrequency (%)
/ 6
66.7%
. 3
33.3%
Space Separator
ValueCountFrequency (%)
1929
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 596
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12290
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1929
15.7%
0 1699
13.8%
2 1673
13.6%
3 1526
12.4%
1 956
7.8%
7 928
7.6%
4 681
 
5.5%
5 654
 
5.3%
6 649
 
5.3%
- 596
 
4.8%
Other values (5) 999
8.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12290
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1929
15.7%
0 1699
13.8%
2 1673
13.6%
3 1526
12.4%
1 956
7.8%
7 928
7.6%
4 681
 
5.5%
5 654
 
5.3%
6 649
 
5.3%
- 596
 
4.8%
Other values (5) 999
8.1%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1301
Missing (%)100.0%
Memory size11.6 KiB

소재지우편번호
Text

MISSING 

Distinct74
Distinct (%)24.4%
Missing998
Missing (%)76.7%
Memory size10.3 KiB
2024-05-11T04:33:24.120311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0033003
Min length6

Characters and Unicode

Total characters1819
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

Unique42 ?
Unique (%)13.9%

Sample

1st row121020
2nd row121200
3rd row121250
4th row121080
5th row121-270
ValueCountFrequency (%)
121210 47
15.5%
121200 23
 
7.6%
121220 20
 
6.6%
121250 19
 
6.3%
121020 16
 
5.3%
121230 16
 
5.3%
121040 14
 
4.6%
121050 12
 
4.0%
121110 11
 
3.6%
121010 8
 
2.6%
Other values (64) 117
38.6%
2024-05-11T04:33:25.126594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 720
39.6%
2 493
27.1%
0 358
19.7%
8 65
 
3.6%
5 42
 
2.3%
3 39
 
2.1%
4 36
 
2.0%
7 31
 
1.7%
9 20
 
1.1%
6 14
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1818
99.9%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 720
39.6%
2 493
27.1%
0 358
19.7%
8 65
 
3.6%
5 42
 
2.3%
3 39
 
2.1%
4 36
 
2.0%
7 31
 
1.7%
9 20
 
1.1%
6 14
 
0.8%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1819
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 720
39.6%
2 493
27.1%
0 358
19.7%
8 65
 
3.6%
5 42
 
2.3%
3 39
 
2.1%
4 36
 
2.0%
7 31
 
1.7%
9 20
 
1.1%
6 14
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1819
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 720
39.6%
2 493
27.1%
0 358
19.7%
8 65
 
3.6%
5 42
 
2.3%
3 39
 
2.1%
4 36
 
2.0%
7 31
 
1.7%
9 20
 
1.1%
6 14
 
0.8%

지번주소
Text

MISSING 

Distinct874
Distinct (%)76.9%
Missing164
Missing (%)12.6%
Memory size10.3 KiB
2024-05-11T04:33:25.931684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length102
Median length95
Mean length53.945471
Min length17

Characters and Unicode

Total characters61336
Distinct characters322
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique767 ?
Unique (%)67.5%

Sample

1st row서울특별시 마포구 공덕동 ***-*
2nd row서울특별시 마포구 공덕동 ***번지 **호
3rd row서울특별시 마포구 염리동 ***-**
4th row서울특별시 마포구 현석동 ***-**
5th row서울특별시 마포구 공덕동 ***-*
ValueCountFrequency (%)
마포구 1138
18.8%
서울특별시 1137
18.7%
772
12.7%
호 515
 
8.5%
번지 367
 
6.0%
서교동 279
 
4.6%
층 237
 
3.9%
합정동 111
 
1.8%
공덕동 108
 
1.8%
도화동 106
 
1.7%
Other values (506) 1299
21.4%
2024-05-11T04:33:27.178171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36830
60.0%
* 6305
 
10.3%
서 1432
 
2.3%
마 1225
 
2.0%
포 1212
 
2.0%
동 1212
 
2.0%
구 1151
 
1.9%
시 1149
 
1.9%
별 1139
 
1.9%
특 1138
 
1.9%
Other values (312) 8543
 
13.9%

Most occurring categories

ValueCountFrequency (%)
Space Separator 36830
60.0%
Other Letter 17338
28.3%
Other Punctuation 6340
 
10.3%
Dash Punctuation 679
 
1.1%
Uppercase Letter 103
 
0.2%
Decimal Number 11
 
< 0.1%
Close Punctuation 10
 
< 0.1%
Open Punctuation 10
 
< 0.1%
Lowercase Letter 8
 
< 0.1%
Other Symbol 5
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 1432
 
8.3%
마 1225
 
7.1%
포 1212
 
7.0%
동 1212
 
7.0%
구 1151
 
6.6%
시 1149
 
6.6%
별 1139
 
6.6%
특 1138
 
6.6%
울 1138
 
6.6%
호 584
 
3.4%
Other values (267) 5958
34.4%
Uppercase Letter
ValueCountFrequency (%)
B 28
27.2%
D 16
15.5%
L 7
 
6.8%
G 7
 
6.8%
S 7
 
6.8%
I 6
 
5.8%
K 5
 
4.9%
A 4
 
3.9%
M 4
 
3.9%
F 3
 
2.9%
Other values (8) 16
15.5%
Lowercase Letter
ValueCountFrequency (%)
e 1
12.5%
l 1
12.5%
g 1
12.5%
p 1
12.5%
i 1
12.5%
v 1
12.5%
t 1
12.5%
k 1
12.5%
Decimal Number
ValueCountFrequency (%)
5 2
18.2%
1 2
18.2%
2 2
18.2%
3 2
18.2%
8 1
9.1%
6 1
9.1%
4 1
9.1%
Other Punctuation
ValueCountFrequency (%)
* 6305
99.4%
, 19
 
0.3%
/ 14
 
0.2%
. 1
 
< 0.1%
? 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
36830
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 679
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Other Symbol
ValueCountFrequency (%)
㉵ 5
100.0%
Math Symbol
ValueCountFrequency (%)
∥ 1
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 43881
71.5%
Hangul 17341
 
28.3%
Latin 112
 
0.2%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 1432
 
8.3%
마 1225
 
7.1%
포 1212
 
7.0%
동 1212
 
7.0%
구 1151
 
6.6%
시 1149
 
6.6%
별 1139
 
6.6%
특 1138
 
6.6%
울 1138
 
6.6%
호 584
 
3.4%
Other values (266) 5961
34.4%
Latin
ValueCountFrequency (%)
B 28
25.0%
D 16
14.3%
L 7
 
6.2%
G 7
 
6.2%
S 7
 
6.2%
I 6
 
5.4%
K 5
 
4.5%
A 4
 
3.6%
M 4
 
3.6%
F 3
 
2.7%
Other values (17) 25
22.3%
Common
ValueCountFrequency (%)
36830
83.9%
* 6305
 
14.4%
- 679
 
1.5%
, 19
 
< 0.1%
/ 14
 
< 0.1%
) 10
 
< 0.1%
( 10
 
< 0.1%
5 2
 
< 0.1%
1 2
 
< 0.1%
2 2
 
< 0.1%
Other values (7) 8
 
< 0.1%
Han
ValueCountFrequency (%)
家 1
50.0%
休 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 43991
71.7%
Hangul 17336
 
28.3%
None 5
 
< 0.1%
CJK 2
 
< 0.1%
Math Operators 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36830
83.7%
* 6305
 
14.3%
- 679
 
1.5%
B 28
 
0.1%
, 19
 
< 0.1%
D 16
 
< 0.1%
/ 14
 
< 0.1%
) 10
 
< 0.1%
( 10
 
< 0.1%
L 7
 
< 0.1%
Other values (32) 73
 
0.2%
Hangul
ValueCountFrequency (%)
서 1432
 
8.3%
마 1225
 
7.1%
포 1212
 
7.0%
동 1212
 
7.0%
구 1151
 
6.6%
시 1149
 
6.6%
별 1139
 
6.6%
특 1138
 
6.6%
울 1138
 
6.6%
호 584
 
3.4%
Other values (265) 5956
34.4%
None
ValueCountFrequency (%)
㉵ 5
100.0%
Math Operators
ValueCountFrequency (%)
∥ 1
100.0%
CJK
ValueCountFrequency (%)
家 1
50.0%
休 1
50.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

도로명주소
Text

MISSING 

Distinct537
Distinct (%)89.5%
Missing701
Missing (%)53.9%
Memory size10.3 KiB
2024-05-11T04:33:27.906830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length48
Mean length34.005
Min length21

Characters and Unicode

Total characters20403
Distinct characters304
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique489 ?
Unique (%)81.5%

Sample

1st row서울특별시 마포구 만리재옛길 ** (공덕동)
2nd row서울특별시 마포구 새창로 **, *층 (도화동)
3rd row서울특별시 마포구 연희로 ** (동교동)
4th row서울특별시 마포구 월드컵북로 ***, ***호 (성산동)
5th row서울특별시 마포구 대흥로 **, ***호 (대흥동,별관*층)
ValueCountFrequency (%)
608
15.7%
서울특별시 600
15.5%
마포구 600
15.5%
호 269
 
7.0%
층 206
 
5.3%
마포대로 61
 
1.6%
서교동 55
 
1.4%
동교동 51
 
1.3%
도화동 40
 
1.0%
월드컵북로*길 36
 
0.9%
Other values (496) 1337
34.6%
2024-05-11T04:33:29.293572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3264
 
16.0%
* 3204
 
15.7%
, 783
 
3.8%
동 765
 
3.7%
마 730
 
3.6%
포 729
 
3.6%
서 710
 
3.5%
구 614
 
3.0%
울 611
 
3.0%
시 606
 
3.0%
Other values (294) 8387
41.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11787
57.8%
Other Punctuation 3992
 
19.6%
Space Separator 3264
 
16.0%
Close Punctuation 603
 
3.0%
Open Punctuation 603
 
3.0%
Dash Punctuation 79
 
0.4%
Uppercase Letter 54
 
0.3%
Decimal Number 14
 
0.1%
Lowercase Letter 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 765
 
6.5%
마 730
 
6.2%
포 729
 
6.2%
서 710
 
6.0%
구 614
 
5.2%
울 611
 
5.2%
시 606
 
5.1%
별 602
 
5.1%
특 601
 
5.1%
로 576
 
4.9%
Other values (261) 5243
44.5%
Uppercase Letter
ValueCountFrequency (%)
B 12
22.2%
A 7
13.0%
T 6
11.1%
S 5
9.3%
D 5
9.3%
K 4
 
7.4%
G 3
 
5.6%
L 3
 
5.6%
R 3
 
5.6%
I 2
 
3.7%
Other values (4) 4
 
7.4%
Decimal Number
ValueCountFrequency (%)
1 4
28.6%
7 2
14.3%
6 2
14.3%
2 2
14.3%
0 2
14.3%
9 1
 
7.1%
5 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
* 3204
80.3%
, 783
 
19.6%
/ 4
 
0.1%
. 1
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
b 4
57.1%
k 1
 
14.3%
t 1
 
14.3%
e 1
 
14.3%
Space Separator
ValueCountFrequency (%)
3264
100.0%
Close Punctuation
ValueCountFrequency (%)
) 603
100.0%
Open Punctuation
ValueCountFrequency (%)
( 603
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 79
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11785
57.8%
Common 8555
41.9%
Latin 61
 
0.3%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 765
 
6.5%
마 730
 
6.2%
포 729
 
6.2%
서 710
 
6.0%
구 614
 
5.2%
울 611
 
5.2%
시 606
 
5.1%
별 602
 
5.1%
특 601
 
5.1%
로 576
 
4.9%
Other values (259) 5241
44.5%
Latin
ValueCountFrequency (%)
B 12
19.7%
A 7
11.5%
T 6
9.8%
S 5
8.2%
D 5
8.2%
K 4
 
6.6%
b 4
 
6.6%
G 3
 
4.9%
L 3
 
4.9%
R 3
 
4.9%
Other values (8) 9
14.8%
Common
ValueCountFrequency (%)
3264
38.2%
* 3204
37.5%
, 783
 
9.2%
) 603
 
7.0%
( 603
 
7.0%
- 79
 
0.9%
1 4
 
< 0.1%
/ 4
 
< 0.1%
7 2
 
< 0.1%
6 2
 
< 0.1%
Other values (5) 7
 
0.1%
Han
ValueCountFrequency (%)
家 1
50.0%
休 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11785
57.8%
ASCII 8616
42.2%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3264
37.9%
* 3204
37.2%
, 783
 
9.1%
) 603
 
7.0%
( 603
 
7.0%
- 79
 
0.9%
B 12
 
0.1%
A 7
 
0.1%
T 6
 
0.1%
S 5
 
0.1%
Other values (23) 50
 
0.6%
Hangul
ValueCountFrequency (%)
동 765
 
6.5%
마 730
 
6.2%
포 729
 
6.2%
서 710
 
6.0%
구 614
 
5.2%
울 611
 
5.2%
시 606
 
5.1%
별 602
 
5.1%
특 601
 
5.1%
로 576
 
4.9%
Other values (259) 5241
44.5%
CJK
ValueCountFrequency (%)
家 1
50.0%
休 1
50.0%

도로명우편번호
Text

MISSING 

Distinct193
Distinct (%)51.1%
Missing923
Missing (%)70.9%
Memory size10.3 KiB
2024-05-11T04:33:30.191147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.4126984
Min length5

Characters and Unicode

Total characters2046
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

Unique100 ?
Unique (%)26.5%

Sample

1st row121803
2nd row04169
3rd row121-914
4th row121866
5th row121883
ValueCountFrequency (%)
121898 11
 
2.9%
121210 9
 
2.4%
121819 8
 
2.1%
04089 7
 
1.9%
04043 6
 
1.6%
04195 6
 
1.6%
121816 5
 
1.3%
04072 5
 
1.3%
04168 5
 
1.3%
04214 5
 
1.3%
Other values (183) 311
82.3%
2024-05-11T04:33:31.540419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 477
23.3%
0 390
19.1%
2 257
12.6%
4 218
10.7%
8 189
 
9.2%
9 153
 
7.5%
3 124
 
6.1%
5 83
 
4.1%
7 78
 
3.8%
6 76
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2045
> 99.9%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 477
23.3%
0 390
19.1%
2 257
12.6%
4 218
10.7%
8 189
 
9.2%
9 153
 
7.5%
3 124
 
6.1%
5 83
 
4.1%
7 78
 
3.8%
6 76
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2046
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 477
23.3%
0 390
19.1%
2 257
12.6%
4 218
10.7%
8 189
 
9.2%
9 153
 
7.5%
3 124
 
6.1%
5 83
 
4.1%
7 78
 
3.8%
6 76
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2046
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 477
23.3%
0 390
19.1%
2 257
12.6%
4 218
10.7%
8 189
 
9.2%
9 153
 
7.5%
3 124
 
6.1%
5 83
 
4.1%
7 78
 
3.8%
6 76
 
3.7%

사업장명
Text

Distinct1266
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size10.3 KiB
2024-05-11T04:33:32.753056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length27
Mean length7.292083
Min length2

Characters and Unicode

Total characters9487
Distinct characters582
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1236 ?
Unique (%)95.0%

Sample

1st row신진출판사
2nd row(주)금성출판사
3rd row(주)래더교육
4th row한국섬머힐
5th row국민서관(주)
ValueCountFrequency (%)
주식회사 125
 
7.3%
주 23
 
1.3%
마포지사 12
 
0.7%
인셀덤 7
 
0.4%
코리아 5
 
0.3%
앤 5
 
0.3%
윤선생 4
 
0.2%
영어교실 4
 
0.2%
유니베라 4
 
0.2%
윤선생영어교실 4
 
0.2%
Other values (1414) 1519
88.7%
2024-05-11T04:33:34.170444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
412
 
4.3%
주 346
 
3.6%
이 323
 
3.4%
사 250
 
2.6%
스 239
 
2.5%
) 239
 
2.5%
( 236
 
2.5%
리 194
 
2.0%
아 161
 
1.7%
회 151
 
1.6%
Other values (572) 6936
73.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7847
82.7%
Space Separator 412
 
4.3%
Uppercase Letter 302
 
3.2%
Close Punctuation 239
 
2.5%
Open Punctuation 236
 
2.5%
Lowercase Letter 206
 
2.2%
Other Symbol 142
 
1.5%
Other Punctuation 68
 
0.7%
Decimal Number 24
 
0.3%
Dash Punctuation 9
 
0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 346
 
4.4%
이 323
 
4.1%
사 250
 
3.2%
스 239
 
3.0%
리 194
 
2.5%
아 161
 
2.1%
회 151
 
1.9%
식 148
 
1.9%
에 135
 
1.7%
마 115
 
1.5%
Other values (505) 5785
73.7%
Uppercase Letter
ValueCountFrequency (%)
C 34
 
11.3%
S 27
 
8.9%
L 19
 
6.3%
H 19
 
6.3%
I 18
 
6.0%
T 18
 
6.0%
E 17
 
5.6%
K 16
 
5.3%
M 16
 
5.3%
N 16
 
5.3%
Other values (13) 102
33.8%
Lowercase Letter
ValueCountFrequency (%)
o 26
12.6%
n 23
11.2%
i 23
11.2%
e 21
10.2%
a 17
8.3%
t 16
7.8%
d 12
 
5.8%
m 12
 
5.8%
c 10
 
4.9%
l 9
 
4.4%
Other values (13) 37
18.0%
Decimal Number
ValueCountFrequency (%)
0 10
41.7%
2 4
 
16.7%
1 3
 
12.5%
8 2
 
8.3%
4 2
 
8.3%
5 1
 
4.2%
6 1
 
4.2%
3 1
 
4.2%
Other Punctuation
ValueCountFrequency (%)
. 42
61.8%
& 16
 
23.5%
, 5
 
7.4%
? 2
 
2.9%
/ 2
 
2.9%
' 1
 
1.5%
Space Separator
ValueCountFrequency (%)
412
100.0%
Close Punctuation
ValueCountFrequency (%)
) 239
100.0%
Open Punctuation
ValueCountFrequency (%)
( 236
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 142
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7985
84.2%
Common 989
 
10.4%
Latin 509
 
5.4%
Han 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 346
 
4.3%
이 323
 
4.0%
사 250
 
3.1%
스 239
 
3.0%
리 194
 
2.4%
아 161
 
2.0%
회 151
 
1.9%
식 148
 
1.9%
㈜ 142
 
1.8%
에 135
 
1.7%
Other values (502) 5896
73.8%
Latin
ValueCountFrequency (%)
C 34
 
6.7%
S 27
 
5.3%
o 26
 
5.1%
n 23
 
4.5%
i 23
 
4.5%
e 21
 
4.1%
L 19
 
3.7%
H 19
 
3.7%
I 18
 
3.5%
T 18
 
3.5%
Other values (37) 281
55.2%
Common
ValueCountFrequency (%)
412
41.7%
) 239
24.2%
( 236
23.9%
. 42
 
4.2%
& 16
 
1.6%
0 10
 
1.0%
- 9
 
0.9%
, 5
 
0.5%
2 4
 
0.4%
1 3
 
0.3%
Other values (9) 13
 
1.3%
Han
ValueCountFrequency (%)
右 1
25.0%
女 1
25.0%
知 1
25.0%
美 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7843
82.7%
ASCII 1497
 
15.8%
None 142
 
1.5%
CJK 3
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
412
27.5%
) 239
16.0%
( 236
15.8%
. 42
 
2.8%
C 34
 
2.3%
S 27
 
1.8%
o 26
 
1.7%
n 23
 
1.5%
i 23
 
1.5%
e 21
 
1.4%
Other values (55) 414
27.7%
Hangul
ValueCountFrequency (%)
주 346
 
4.4%
이 323
 
4.1%
사 250
 
3.2%
스 239
 
3.0%
리 194
 
2.5%
아 161
 
2.1%
회 151
 
1.9%
식 148
 
1.9%
에 135
 
1.7%
마 115
 
1.5%
Other values (501) 5781
73.7%
None
ValueCountFrequency (%)
㈜ 142
100.0%
CJK
ValueCountFrequency (%)
右 1
33.3%
知 1
33.3%
美 1
33.3%
CJK Compat Ideographs
ValueCountFrequency (%)
女 1
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

최종수정일자
Date

Distinct879
Distinct (%)67.6%
Missing0
Missing (%)0.0%
Memory size10.3 KiB
Minimum2007-07-27 14:42:41
Maximum2024-04-29 11:00:44
2024-05-11T04:33:35.113759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:33:35.725548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.3 KiB
I
1093 
U
208 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 1093
84.0%
U 208
 
16.0%

Length

2024-05-11T04:33:36.349821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:33:36.756214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 1093
84.0%
u 208
 
16.0%

데이터갱신일자
Date

Distinct174
Distinct (%)13.4%
Missing0
Missing (%)0.0%
Memory size10.3 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:01:00
2024-05-11T04:33:37.152266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:33:37.579157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1301
Missing (%)100.0%
Memory size11.6 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct444
Distinct (%)72.0%
Missing684
Missing (%)52.6%
Infinite0
Infinite (%)0.0%
Mean193452.69
Minimum189212.74
Maximum196657.68
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.6 KiB
2024-05-11T04:33:38.217976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189212.74
5-th percentile191177.32
Q1192225.47
median193104.77
Q3195019.4
95-th percentile195998.98
Maximum196657.68
Range7444.9444
Interquartile range (IQR)2793.927

Descriptive statistics

Standard deviation1651.3046
Coefficient of variation (CV)0.0085359611
Kurtosis-0.8961162
Mean193452.69
Median Absolute Deviation (MAD)1306.5989
Skewness-0.010564056
Sum1.1936031 × 108
Variance2726807
MonotonicityNot monotonic
2024-05-11T04:33:38.856276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
193088.824663271 12
 
0.9%
195766.588069694 8
 
0.6%
195748.06444032 7
 
0.5%
194974.587674037 6
 
0.5%
194301.304865904 6
 
0.5%
195324.793653981 6
 
0.5%
193166.430144679 5
 
0.4%
195266.07314617 4
 
0.3%
192031.046712611 4
 
0.3%
195019.399817378 4
 
0.3%
Other values (434) 555
42.7%
(Missing) 684
52.6%
ValueCountFrequency (%)
189212.737535822 1
0.1%
189333.273693129 1
0.1%
189392.864151 1
0.1%
189586.493821292 1
0.1%
189683.413598 1
0.1%
189731.350651 1
0.1%
189855.433985731 1
0.1%
189954.316212248 1
0.1%
190020.777440717 2
0.2%
190027.704804 1
0.1%
ValueCountFrequency (%)
196657.681931264 1
0.1%
196541.251852568 1
0.1%
196468.456780034 1
0.1%
196466.254395531 1
0.1%
196465.125796143 1
0.1%
196447.2324759 1
0.1%
196378.162500119 1
0.1%
196336.521513202 1
0.1%
196327.4512852 1
0.1%
196325.537558722 1
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct444
Distinct (%)72.0%
Missing684
Missing (%)52.6%
Infinite0
Infinite (%)0.0%
Mean450094.81
Minimum448116.64
Maximum453879.76
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.6 KiB
2024-05-11T04:33:39.512158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum448116.64
5-th percentile448540.43
Q1449288.42
median450015.88
Q3450669.06
95-th percentile452120.44
Maximum453879.76
Range5763.1201
Interquartile range (IQR)1380.635

Descriptive statistics

Standard deviation1074.012
Coefficient of variation (CV)0.0023861906
Kurtosis1.0396398
Mean450094.81
Median Absolute Deviation (MAD)671.65237
Skewness0.84073057
Sum2.777085 × 108
Variance1153501.7
MonotonicityNot monotonic
2024-05-11T04:33:40.131075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
450798.385203407 12
 
0.9%
449083.306922623 8
 
0.6%
449145.578789461 7
 
0.5%
448229.063825491 6
 
0.5%
449388.053900946 6
 
0.5%
448885.430093289 6
 
0.5%
450425.852790862 5
 
0.4%
448799.641804029 4
 
0.3%
450319.298880089 4
 
0.3%
448407.752664604 4
 
0.3%
Other values (434) 555
42.7%
(Missing) 684
52.6%
ValueCountFrequency (%)
448116.639953919 1
 
0.1%
448229.063825491 6
0.5%
448236.655548283 2
 
0.2%
448276.965250949 1
 
0.1%
448345.713688045 1
 
0.1%
448372.301911412 1
 
0.1%
448393.658663222 4
0.3%
448407.752664604 4
0.3%
448460.50414883 1
 
0.1%
448476.859046692 1
 
0.1%
ValueCountFrequency (%)
453879.760075 1
0.1%
453797.100407641 1
0.1%
453614.583448105 1
0.1%
453494.813761 1
0.1%
453468.379147545 1
0.1%
453438.907954 1
0.1%
453407.67377 1
0.1%
453323.0 1
0.1%
453263.335891345 1
0.1%
453225.465779 1
0.1%

자산규모
Real number (ℝ)

MISSING  ZEROS 

Distinct158
Distinct (%)52.1%
Missing998
Missing (%)76.7%
Infinite0
Infinite (%)0.0%
Mean1.0183023 × 1010
Minimum0
Maximum1.9868336 × 1012
Zeros57
Zeros (%)4.4%
Negative0
Negative (%)0.0%
Memory size11.6 KiB
2024-05-11T04:33:40.632118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q110000000
median50700336
Q32.5 × 108
95-th percentile3.0786413 × 109
Maximum1.9868336 × 1012
Range1.9868336 × 1012
Interquartile range (IQR)2.4 × 108

Descriptive statistics

Standard deviation1.181875 × 1011
Coefficient of variation (CV)11.606327
Kurtosis261.93167
Mean1.0183023 × 1010
Median Absolute Deviation (MAD)50700336
Skewness15.79941
Sum3.085456 × 1012
Variance1.3968285 × 1022
MonotonicityNot monotonic
2024-05-11T04:33:41.258473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 57
 
4.4%
50000000 34
 
2.6%
100000000 16
 
1.2%
10000000 15
 
1.2%
30000000 7
 
0.5%
300000000 6
 
0.5%
20000000 5
 
0.4%
150000000 4
 
0.3%
200000000 4
 
0.3%
5000000 3
 
0.2%
Other values (148) 152
 
11.7%
(Missing) 998
76.7%
ValueCountFrequency (%)
0 57
4.4%
181724 1
 
0.1%
500000 1
 
0.1%
1000000 1
 
0.1%
5000000 3
 
0.2%
6030000 1
 
0.1%
9558858 1
 
0.1%
10000000 15
 
1.2%
10680188 1
 
0.1%
10751141 1
 
0.1%
ValueCountFrequency (%)
1986833637298 1
0.1%
439946955096 1
0.1%
274223448000 1
0.1%
174373945000 1
0.1%
44967000000 1
0.1%
18956205944 1
0.1%
15779606165 1
0.1%
11701675877 1
0.1%
10337474596 1
0.1%
10100000000 1
0.1%

부채총액
Real number (ℝ)

MISSING  ZEROS 

Distinct130
Distinct (%)43.2%
Missing1000
Missing (%)76.9%
Infinite0
Infinite (%)0.0%
Mean5.7114435 × 109
Minimum0
Maximum1.06025 × 1012
Zeros169
Zeros (%)13.0%
Negative0
Negative (%)0.0%
Memory size11.6 KiB
2024-05-11T04:33:41.903160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31.2298105 × 108
95-th percentile2.2178939 × 109
Maximum1.06025 × 1012
Range1.06025 × 1012
Interquartile range (IQR)1.2298105 × 108

Descriptive statistics

Standard deviation6.3509904 × 1010
Coefficient of variation (CV)11.119764
Kurtosis256.22235
Mean5.7114435 × 109
Median Absolute Deviation (MAD)0
Skewness15.592022
Sum1.7191445 × 1012
Variance4.033508 × 1021
MonotonicityNot monotonic
2024-05-11T04:33:42.534544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 169
 
13.0%
467367053 2
 
0.2%
15000000 2
 
0.2%
5000000 2
 
0.2%
841296877 1
 
0.1%
354165243 1
 
0.1%
4692137 1
 
0.1%
50101470 1
 
0.1%
34542017 1
 
0.1%
145953485 1
 
0.1%
Other values (120) 120
 
9.2%
(Missing) 1000
76.9%
ValueCountFrequency (%)
0 169
13.0%
11000 1
 
0.1%
128161 1
 
0.1%
778800 1
 
0.1%
1210360 1
 
0.1%
1497024 1
 
0.1%
4039102 1
 
0.1%
4500000 1
 
0.1%
4692137 1
 
0.1%
5000000 2
 
0.2%
ValueCountFrequency (%)
1060250012236 1
0.1%
225941552089 1
0.1%
194460140000 1
0.1%
63369826000 1
0.1%
35760000000 1
0.1%
27215524919 1
0.1%
19550984432 1
0.1%
15900000000 1
0.1%
7462452234 1
0.1%
6779406500 1
0.1%

자본금
Real number (ℝ)

MISSING  ZEROS 

Distinct75
Distinct (%)24.8%
Missing998
Missing (%)76.7%
Infinite0
Infinite (%)0.0%
Mean4.270973 × 109
Minimum-3.6802122 × 108
Maximum9.2658363 × 1011
Zeros48
Zeros (%)3.7%
Negative4
Negative (%)0.3%
Memory size11.6 KiB
2024-05-11T04:33:43.469967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-3.6802122 × 108
5-th percentile0
Q110000000
median50000000
Q31 × 108
95-th percentile1 × 109
Maximum9.2658363 × 1011
Range9.2695165 × 1011
Interquartile range (IQR)90000000

Descriptive statistics

Standard deviation5.4762829 × 1010
Coefficient of variation (CV)12.822097
Kurtosis269.47214
Mean4.270973 × 109
Median Absolute Deviation (MAD)50000000
Skewness16.119405
Sum1.2941048 × 1012
Variance2.9989675 × 1021
MonotonicityNot monotonic
2024-05-11T04:33:44.076455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50000000 68
 
5.2%
0 48
 
3.7%
100000000 27
 
2.1%
10000000 23
 
1.8%
30000000 12
 
0.9%
300000000 11
 
0.8%
150000000 9
 
0.7%
20000000 9
 
0.7%
200000000 8
 
0.6%
5000000 7
 
0.5%
Other values (65) 81
 
6.2%
(Missing) 998
76.7%
ValueCountFrequency (%)
-368021219 1
 
0.1%
-147961149 1
 
0.1%
-27991528 1
 
0.1%
-24464972 1
 
0.1%
0 48
3.7%
8000 1
 
0.1%
50000 1
 
0.1%
100000 1
 
0.1%
1000000 3
 
0.2%
5000000 7
 
0.5%
ValueCountFrequency (%)
926583625062 1
0.1%
214005403007 1
0.1%
79763317000 1
0.1%
20000000000 1
0.1%
5000000000 1
0.1%
4846199800 1
0.1%
4075304878 1
0.1%
2204641440 1
0.1%
2000000000 2
0.2%
1612166280 1
0.1%

판매방식명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1301
Missing (%)100.0%
Memory size11.6 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)자산규모부채총액자본금판매방식명
03130000199631301182320000219960817<NA>3폐업3폐업처리<NA><NA><NA><NA>02 716 1114<NA><NA>서울특별시 마포구 공덕동 ***-*<NA><NA>신진출판사2008-02-21 00:00:00I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
13130000199631301182320000319960828<NA>1영업/정상1정상영업<NA><NA><NA><NA>20778024<NA>121020서울특별시 마포구 공덕동 ***번지 **호서울특별시 마포구 만리재옛길 ** (공덕동)121803(주)금성출판사2021-09-29 10:17:53U2021-10-01 02:40:00.0<NA>195986.29321449335.253493174373945000633698260004846199800<NA>
23130000199631301182320000619960828<NA>3폐업3폐업처리<NA><NA><NA><NA>02 702 2583<NA><NA>서울특별시 마포구 염리동 ***-**<NA><NA>(주)래더교육2008-02-21 00:00:00I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
33130000199631301182320000719960830<NA>4취소/말소/만료/정지/중지7직권말소<NA><NA><NA><NA>02 393 2262<NA><NA>서울특별시 마포구 현석동 ***-**<NA><NA>한국섬머힐2009-10-23 11:33:36I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
43130000199631301182320000819960830<NA>3폐업3폐업처리<NA><NA><NA><NA>02 710 7780<NA><NA>서울특별시 마포구 공덕동 ***-*<NA><NA>국민서관(주)2008-02-21 00:00:00I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
53130000199631301182320000919960830<NA>3폐업3폐업처리<NA><NA><NA><NA>02 325 6528<NA><NA>서울특별시 마포구 서교동 ***-** 씨티빌딩***<NA><NA>(주)한우리홈파티스2008-02-21 00:00:00I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
63130000199631301182320001119960903<NA>3폐업3폐업처리<NA><NA><NA><NA>02 712 7902<NA><NA>서울특별시 마포구 염리동 ***-*<NA><NA>(주)햄텍코리아2008-02-21 00:00:00I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
73130000199631301182320001419960923<NA>3폐업3폐업처리<NA><NA><NA><NA>02 701 5050<NA><NA>서울특별시 마포구 도화동 ***-*<NA><NA>(주)동서2008-02-21 00:00:00I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
83130000199631301182320001819961024<NA>3폐업3폐업처리<NA><NA><NA><NA>02 336 8327<NA><NA>서울특별시 마포구 서교동 ***-**<NA><NA>평산기획2008-02-21 00:00:00I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
93130000199631301182320001919961025<NA>4취소/말소/만료/정지/중지7직권말소<NA><NA><NA><NA>02 714 3002<NA><NA>서울특별시 마포구 신수동 **-*<NA><NA>A+과학나라2022-08-02 08:56:56U2021-12-08 00:04:00.0<NA><NA><NA><NA><NA><NA><NA>
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