Overview

Dataset statistics

Number of variables29
Number of observations214
Missing cells1430
Missing cells (%)23.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory52.4 KiB
Average record size in memory250.6 B

Variable types

Categorical10
Numeric9
DateTime3
Text4
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
Author강북구
URLhttps://data.seoul.go.kr/dataList/OA-18785/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 is highly imbalanced (84.3%)Imbalance
휴업시작일자 is highly imbalanced (94.6%)Imbalance
휴업종료일자 is highly imbalanced (94.6%)Imbalance
재개업일자 is highly imbalanced (94.6%)Imbalance
데이터갱신일자 is highly imbalanced (61.6%)Imbalance
폐업일자 has 83 (38.8%) missing valuesMissing
전화번호 has 69 (32.2%) missing valuesMissing
소재지면적 has 214 (100.0%) missing valuesMissing
소재지우편번호 has 80 (37.4%) missing valuesMissing
지번주소 has 10 (4.7%) missing valuesMissing
도로명주소 has 10 (4.7%) missing valuesMissing
도로명우편번호 has 106 (49.5%) missing valuesMissing
업태구분명 has 214 (100.0%) missing valuesMissing
좌표정보(X) has 5 (2.3%) missing valuesMissing
좌표정보(Y) has 5 (2.3%) missing valuesMissing
자산규모 has 140 (65.4%) missing valuesMissing
부채총액 has 140 (65.4%) missing valuesMissing
자본금 has 140 (65.4%) missing valuesMissing
판매방식명 has 214 (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 19 (8.9%) zerosZeros
부채총액 has 49 (22.9%) zerosZeros
자본금 has 15 (7.0%) zerosZeros

Reproduction

Analysis started2024-05-11 02:17:47.814187
Analysis finished2024-05-11 02:17:49.129054
Duration1.31 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
3080000
214 

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 214
100.0%

Length

2024-05-11T02:17:49.452068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:17:50.134143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3080000 214
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct214
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0126772 × 1018
Minimum2.007308 × 1018
Maximum2.024308 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-05-11T02:17:50.563488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.007308 × 1018
5-th percentile2.007308 × 1018
Q12.007308 × 1018
median2.011308 × 1018
Q32.016308 × 1018
95-th percentile2.022308 × 1018
Maximum2.024308 × 1018
Range1.700001 × 1016
Interquartile range (IQR)9.0000047 × 1015

Descriptive statistics

Standard deviation5.233444 × 1015
Coefficient of variation (CV)0.0026002402
Kurtosis-1.0797744
Mean2.0126772 × 1018
Median Absolute Deviation (MAD)4.0000047 × 1015
Skewness0.55556298
Sum6.437801 × 1018
Variance2.7388936 × 1031
MonotonicityStrictly increasing
2024-05-11T02:17:51.173133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2007308009224200001 1
 
0.5%
2015308013924200003 1
 
0.5%
2015308013924200005 1
 
0.5%
2015308013924200006 1
 
0.5%
2015308013924200007 1
 
0.5%
2015308013924200010 1
 
0.5%
2015308013924200011 1
 
0.5%
2015308013924200012 1
 
0.5%
2015308013924200013 1
 
0.5%
2015308013924200014 1
 
0.5%
Other values (204) 204
95.3%
ValueCountFrequency (%)
2007308009224200001 1
0.5%
2007308009224200002 1
0.5%
2007308009224200003 1
0.5%
2007308009224200004 1
0.5%
2007308009224200005 1
0.5%
2007308009224200006 1
0.5%
2007308009224200007 1
0.5%
2007308009224200008 1
0.5%
2007308009224200009 1
0.5%
2007308009224200010 1
0.5%
ValueCountFrequency (%)
2024308019024200001 1
0.5%
2023308019024200003 1
0.5%
2023308019024200002 1
0.5%
2023308019024200001 1
0.5%
2022308016924200008 1
0.5%
2022308016924200007 1
0.5%
2022308016924200006 1
0.5%
2022308016924200005 1
0.5%
2022308016924200004 1
0.5%
2022308016924200003 1
0.5%

인허가일자
Date

Distinct190
Distinct (%)88.8%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
Minimum2002-08-14 00:00:00
Maximum2024-01-11 00:00:00
2024-05-11T02:17:51.631795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:17:52.234730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Categorical

IMBALANCE 

Distinct5
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
204 
20080731
 
3
20080529
 
3
20040706
 
2
20080429
 
2

Length

Max length8
Median length4
Mean length4.1869159
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 204
95.3%
20080731 3
 
1.4%
20080529 3
 
1.4%
20040706 2
 
0.9%
20080429 2
 
0.9%

Length

2024-05-11T02:17:52.782967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:17:53.309869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 204
95.3%
20080731 3
 
1.4%
20080529 3
 
1.4%
20040706 2
 
0.9%
20080429 2
 
0.9%

영업상태코드
Categorical

Distinct5
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
3
103 
4
76 
1
30 
5
 
3
2
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 103
48.1%
4 76
35.5%
1 30
 
14.0%
5 3
 
1.4%
2 2
 
0.9%

Length

2024-05-11T02:17:53.701863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:17:54.113979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 103
48.1%
4 76
35.5%
1 30
 
14.0%
5 3
 
1.4%
2 2
 
0.9%

영업상태명
Categorical

Distinct5
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
폐업
103 
취소/말소/만료/정지/중지
76 
영업/정상
30 
제외/삭제/전출
 
3
휴업
 
2

Length

Max length14
Median length8
Mean length6.7663551
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 103
48.1%
취소/말소/만료/정지/중지 76
35.5%
영업/정상 30
 
14.0%
제외/삭제/전출 3
 
1.4%
휴업 2
 
0.9%

Length

2024-05-11T02:17:54.579074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:17:54.969017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 103
48.1%
취소/말소/만료/정지/중지 76
35.5%
영업/정상 30
 
14.0%
제외/삭제/전출 3
 
1.4%
휴업 2
 
0.9%

상세영업상태코드
Real number (ℝ)

Distinct6
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.0186916
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-05-11T02:17:55.382017image/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 deviation2.1427082
Coefficient of variation (CV)0.53318552
Kurtosis-1.2439112
Mean4.0186916
Median Absolute Deviation (MAD)1
Skewness0.38594854
Sum860
Variance4.5911983
MonotonicityNot monotonic
2024-05-11T02:17:55.734465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3 103
48.1%
7 66
30.8%
1 30
 
14.0%
4 10
 
4.7%
5 3
 
1.4%
2 2
 
0.9%
ValueCountFrequency (%)
1 30
 
14.0%
2 2
 
0.9%
3 103
48.1%
4 10
 
4.7%
5 3
 
1.4%
7 66
30.8%
ValueCountFrequency (%)
7 66
30.8%
5 3
 
1.4%
4 10
 
4.7%
3 103
48.1%
2 2
 
0.9%
1 30
 
14.0%

상세영업상태명
Categorical

Distinct6
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
폐업처리
103 
직권말소
66 
정상영업
30 
직권취소
 
10
타시군구이관
 
3

Length

Max length6
Median length4
Mean length4.0280374
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업처리 103
48.1%
직권말소 66
30.8%
정상영업 30
 
14.0%
직권취소 10
 
4.7%
타시군구이관 3
 
1.4%
휴업처리 2
 
0.9%

Length

2024-05-11T02:17:56.202351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:17:56.573657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업처리 103
48.1%
직권말소 66
30.8%
정상영업 30
 
14.0%
직권취소 10
 
4.7%
타시군구이관 3
 
1.4%
휴업처리 2
 
0.9%

폐업일자
Date

MISSING 

Distinct106
Distinct (%)80.9%
Missing83
Missing (%)38.8%
Memory size1.8 KiB
Minimum2002-12-03 00:00:00
Maximum2024-03-04 00:00:00
2024-05-11T02:17:56.866403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:17:57.173532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
212 
20161130
 
1
20220729
 
1

Length

Max length8
Median length4
Mean length4.0373832
Min length4

Unique

Unique2 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 212
99.1%
20161130 1
 
0.5%
20220729 1
 
0.5%

Length

2024-05-11T02:17:57.527050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:17:57.852067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 212
99.1%
20161130 1
 
0.5%
20220729 1
 
0.5%

휴업종료일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
212 
20191231
 
1
20230729
 
1

Length

Max length8
Median length4
Mean length4.0373832
Min length4

Unique

Unique2 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 212
99.1%
20191231 1
 
0.5%
20230729 1
 
0.5%

Length

2024-05-11T02:17:58.107354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:17:58.339232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 212
99.1%
20191231 1
 
0.5%
20230729 1
 
0.5%

재개업일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
212 
20200428
 
1
20200706
 
1

Length

Max length8
Median length4
Mean length4.0373832
Min length4

Unique

Unique2 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 212
99.1%
20200428 1
 
0.5%
20200706 1
 
0.5%

Length

2024-05-11T02:17:58.684432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:17:58.984778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 212
99.1%
20200428 1
 
0.5%
20200706 1
 
0.5%

전화번호
Text

MISSING 

Distinct131
Distinct (%)90.3%
Missing69
Missing (%)32.2%
Memory size1.8 KiB
2024-05-11T02:17:59.670927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length9.0896552
Min length7

Characters and Unicode

Total characters1318
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique118 ?
Unique (%)81.4%

Sample

1st row9993051
2nd row9456491
3rd row0807008549
4th row0809983000
5th row9020569
ValueCountFrequency (%)
02-999-6001 3
 
2.1%
070-8915-6777 2
 
1.4%
62240012 2
 
1.4%
20880533 2
 
1.4%
9830390 2
 
1.4%
64035602 2
 
1.4%
07081727502 2
 
1.4%
070-8188-0174 2
 
1.4%
070-4689-8000 2
 
1.4%
62273991 2
 
1.4%
Other values (121) 124
85.5%
2024-05-11T02:18:01.179764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 225
17.1%
9 177
13.4%
2 141
10.7%
8 120
9.1%
1 118
9.0%
- 104
7.9%
4 93
7.1%
5 90
 
6.8%
6 86
 
6.5%
7 86
 
6.5%
Other values (2) 78
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1213
92.0%
Dash Punctuation 104
 
7.9%
Math Symbol 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 225
18.5%
9 177
14.6%
2 141
11.6%
8 120
9.9%
1 118
9.7%
4 93
7.7%
5 90
 
7.4%
6 86
 
7.1%
7 86
 
7.1%
3 77
 
6.3%
Dash Punctuation
ValueCountFrequency (%)
- 104
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1318
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 225
17.1%
9 177
13.4%
2 141
10.7%
8 120
9.1%
1 118
9.0%
- 104
7.9%
4 93
7.1%
5 90
 
6.8%
6 86
 
6.5%
7 86
 
6.5%
Other values (2) 78
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1318
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 225
17.1%
9 177
13.4%
2 141
10.7%
8 120
9.1%
1 118
9.0%
- 104
7.9%
4 93
7.1%
5 90
 
6.8%
6 86
 
6.5%
7 86
 
6.5%
Other values (2) 78
 
5.9%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing214
Missing (%)100.0%
Memory size2.0 KiB

소재지우편번호
Real number (ℝ)

MISSING 

Distinct22
Distinct (%)16.4%
Missing80
Missing (%)37.4%
Infinite0
Infinite (%)0.0%
Mean142130.45
Minimum136090
Maximum142878
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-05-11T02:18:01.901812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum136090
5-th percentile142060
Q1142061
median142070
Q3142100
95-th percentile142873.4
Maximum142878
Range6788
Interquartile range (IQR)39

Descriptive statistics

Standard deviation584.04883
Coefficient of variation (CV)0.004109245
Kurtosis87.210472
Mean142130.45
Median Absolute Deviation (MAD)10
Skewness-8.2169455
Sum19045480
Variance341113.03
MonotonicityNot monotonic
2024-05-11T02:18:02.516284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
142100 33
15.4%
142060 30
 
14.0%
142070 25
 
11.7%
142061 14
 
6.5%
142071 5
 
2.3%
142717 4
 
1.9%
142878 4
 
1.9%
142703 2
 
0.9%
142073 2
 
0.9%
142104 2
 
0.9%
Other values (12) 13
 
6.1%
(Missing) 80
37.4%
ValueCountFrequency (%)
136090 1
 
0.5%
142060 30
14.0%
142061 14
6.5%
142070 25
11.7%
142071 5
 
2.3%
142072 1
 
0.5%
142073 2
 
0.9%
142075 1
 
0.5%
142077 1
 
0.5%
142100 33
15.4%
ValueCountFrequency (%)
142878 4
1.9%
142877 1
 
0.5%
142876 2
0.9%
142872 1
 
0.5%
142868 1
 
0.5%
142865 1
 
0.5%
142820 1
 
0.5%
142810 1
 
0.5%
142717 4
1.9%
142703 2
0.9%

지번주소
Text

MISSING 

Distinct136
Distinct (%)66.7%
Missing10
Missing (%)4.7%
Memory size1.8 KiB
2024-05-11T02:18:03.488688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length38
Mean length27.397059
Min length13

Characters and Unicode

Total characters5589
Distinct characters141
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique105 ?
Unique (%)51.5%

Sample

1st row서울특별시 강북구 번동 ***번지 *호 *층
2nd row서울특별시 강북구 번동 ***번지 **호 창강b/d ***호
3rd row서울특별시 강북구 수유동 ***번지 **호 *층 *호
4th row서울특별시 강북구 수유동 ***번지 *호
5th row서울특별시 강북구 번동 ***번지 **호 가든타워 ****호
ValueCountFrequency (%)
호 210
17.5%
서울특별시 204
17.0%
강북구 203
16.9%
번지 163
13.6%
번동 79
 
6.6%
수유동 66
 
5.5%
미아동 54
 
4.5%
층 50
 
4.2%
37
 
3.1%
창강빌딩 8
 
0.7%
Other values (81) 128
10.6%
2024-05-11T02:18:04.904174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 1223
21.9%
1013
18.1%
번 248
 
4.4%
동 217
 
3.9%
강 216
 
3.9%
호 215
 
3.8%
북 209
 
3.7%
시 207
 
3.7%
울 204
 
3.7%
서 204
 
3.7%
Other values (131) 1633
29.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3278
58.7%
Other Punctuation 1228
 
22.0%
Space Separator 1013
 
18.1%
Dash Punctuation 40
 
0.7%
Decimal Number 13
 
0.2%
Lowercase Letter 9
 
0.2%
Uppercase Letter 8
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
번 248
 
7.6%
동 217
 
6.6%
강 216
 
6.6%
호 215
 
6.6%
북 209
 
6.4%
시 207
 
6.3%
울 204
 
6.2%
서 204
 
6.2%
구 204
 
6.2%
별 204
 
6.2%
Other values (105) 1150
35.1%
Decimal Number
ValueCountFrequency (%)
0 3
23.1%
5 2
15.4%
7 2
15.4%
3 2
15.4%
4 1
 
7.7%
9 1
 
7.7%
1 1
 
7.7%
2 1
 
7.7%
Lowercase Letter
ValueCountFrequency (%)
k 2
22.2%
t 2
22.2%
e 1
11.1%
n 1
11.1%
u 1
11.1%
b 1
11.1%
d 1
11.1%
Uppercase Letter
ValueCountFrequency (%)
S 2
25.0%
K 2
25.0%
E 1
12.5%
J 1
12.5%
D 1
12.5%
B 1
12.5%
Other Punctuation
ValueCountFrequency (%)
* 1223
99.6%
, 4
 
0.3%
/ 1
 
0.1%
Space Separator
ValueCountFrequency (%)
1013
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 40
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3278
58.7%
Common 2294
41.0%
Latin 17
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
번 248
 
7.6%
동 217
 
6.6%
강 216
 
6.6%
호 215
 
6.6%
북 209
 
6.4%
시 207
 
6.3%
울 204
 
6.2%
서 204
 
6.2%
구 204
 
6.2%
별 204
 
6.2%
Other values (105) 1150
35.1%
Common
ValueCountFrequency (%)
* 1223
53.3%
1013
44.2%
- 40
 
1.7%
, 4
 
0.2%
0 3
 
0.1%
5 2
 
0.1%
7 2
 
0.1%
3 2
 
0.1%
4 1
 
< 0.1%
9 1
 
< 0.1%
Other values (3) 3
 
0.1%
Latin
ValueCountFrequency (%)
S 2
11.8%
K 2
11.8%
k 2
11.8%
t 2
11.8%
E 1
 
5.9%
e 1
 
5.9%
n 1
 
5.9%
u 1
 
5.9%
J 1
 
5.9%
D 1
 
5.9%
Other values (3) 3
17.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3278
58.7%
ASCII 2311
41.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 1223
52.9%
1013
43.8%
- 40
 
1.7%
, 4
 
0.2%
0 3
 
0.1%
5 2
 
0.1%
7 2
 
0.1%
3 2
 
0.1%
S 2
 
0.1%
K 2
 
0.1%
Other values (16) 18
 
0.8%
Hangul
ValueCountFrequency (%)
번 248
 
7.6%
동 217
 
6.6%
강 216
 
6.6%
호 215
 
6.6%
북 209
 
6.4%
시 207
 
6.3%
울 204
 
6.2%
서 204
 
6.2%
구 204
 
6.2%
별 204
 
6.2%
Other values (105) 1150
35.1%

도로명주소
Text

MISSING 

Distinct162
Distinct (%)79.4%
Missing10
Missing (%)4.7%
Memory size1.8 KiB
2024-05-11T02:18:05.781116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length40
Mean length31.563725
Min length22

Characters and Unicode

Total characters6439
Distinct characters162
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

Unique134 ?
Unique (%)65.7%

Sample

1st row서울특별시 강북구 도봉로 ***-* (번동,*층)
2nd row서울특별시 강북구 덕릉로 ***, ***호 (번동,창강b/d)
3rd row서울특별시 강북구 인수봉로 ***, *호 (수유동,*층)
4th row서울특별시 강북구 인수봉로 *** (수유동)
5th row서울특별시 강북구 도봉로 ***, ****호 (번동,가든타워)
ValueCountFrequency (%)
서울특별시 204
16.3%
203
16.2%
강북구 203
16.2%
호 80
 
6.4%
층 79
 
6.3%
수유동 52
 
4.2%
번동 45
 
3.6%
도봉로 45
 
3.6%
덕릉로 38
 
3.0%
미아동 30
 
2.4%
Other values (125) 272
21.7%
2024-05-11T02:18:06.730526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 1094
17.0%
1048
16.3%
, 237
 
3.7%
강 216
 
3.4%
동 211
 
3.3%
북 209
 
3.2%
시 206
 
3.2%
서 204
 
3.2%
로 204
 
3.2%
울 204
 
3.2%
Other values (152) 2606
40.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3599
55.9%
Other Punctuation 1333
 
20.7%
Space Separator 1048
 
16.3%
Open Punctuation 204
 
3.2%
Close Punctuation 204
 
3.2%
Dash Punctuation 19
 
0.3%
Decimal Number 16
 
0.2%
Lowercase Letter 9
 
0.1%
Uppercase Letter 7
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
강 216
 
6.0%
동 211
 
5.9%
북 209
 
5.8%
시 206
 
5.7%
서 204
 
5.7%
로 204
 
5.7%
울 204
 
5.7%
구 204
 
5.7%
별 204
 
5.7%
특 204
 
5.7%
Other values (124) 1533
42.6%
Decimal Number
ValueCountFrequency (%)
1 5
31.2%
3 4
25.0%
9 2
 
12.5%
2 2
 
12.5%
7 1
 
6.2%
5 1
 
6.2%
0 1
 
6.2%
Lowercase Letter
ValueCountFrequency (%)
k 2
22.2%
t 2
22.2%
e 1
11.1%
n 1
11.1%
u 1
11.1%
b 1
11.1%
d 1
11.1%
Uppercase Letter
ValueCountFrequency (%)
B 2
28.6%
J 1
14.3%
D 1
14.3%
K 1
14.3%
S 1
14.3%
E 1
14.3%
Other Punctuation
ValueCountFrequency (%)
* 1094
82.1%
, 237
 
17.8%
. 1
 
0.1%
/ 1
 
0.1%
Space Separator
ValueCountFrequency (%)
1048
100.0%
Open Punctuation
ValueCountFrequency (%)
( 204
100.0%
Close Punctuation
ValueCountFrequency (%)
) 204
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3599
55.9%
Common 2824
43.9%
Latin 16
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
강 216
 
6.0%
동 211
 
5.9%
북 209
 
5.8%
시 206
 
5.7%
서 204
 
5.7%
로 204
 
5.7%
울 204
 
5.7%
구 204
 
5.7%
별 204
 
5.7%
특 204
 
5.7%
Other values (124) 1533
42.6%
Common
ValueCountFrequency (%)
* 1094
38.7%
1048
37.1%
, 237
 
8.4%
( 204
 
7.2%
) 204
 
7.2%
- 19
 
0.7%
1 5
 
0.2%
3 4
 
0.1%
9 2
 
0.1%
2 2
 
0.1%
Other values (5) 5
 
0.2%
Latin
ValueCountFrequency (%)
k 2
12.5%
t 2
12.5%
B 2
12.5%
e 1
 
6.2%
J 1
 
6.2%
n 1
 
6.2%
u 1
 
6.2%
D 1
 
6.2%
K 1
 
6.2%
S 1
 
6.2%
Other values (3) 3
18.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3599
55.9%
ASCII 2840
44.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 1094
38.5%
1048
36.9%
, 237
 
8.3%
( 204
 
7.2%
) 204
 
7.2%
- 19
 
0.7%
1 5
 
0.2%
3 4
 
0.1%
9 2
 
0.1%
2 2
 
0.1%
Other values (18) 21
 
0.7%
Hangul
ValueCountFrequency (%)
강 216
 
6.0%
동 211
 
5.9%
북 209
 
5.8%
시 206
 
5.7%
서 204
 
5.7%
로 204
 
5.7%
울 204
 
5.7%
구 204
 
5.7%
별 204
 
5.7%
특 204
 
5.7%
Other values (124) 1533
42.6%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct49
Distinct (%)45.4%
Missing106
Missing (%)49.5%
Infinite0
Infinite (%)0.0%
Mean50778.574
Minimum1014
Maximum142891
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-05-11T02:18:07.132635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1014
5-th percentile1055
Q11068
median1131.5
Q3142071
95-th percentile142870.6
Maximum142891
Range141877
Interquartile range (IQR)141003

Descriptive statistics

Standard deviation67745.07
Coefficient of variation (CV)1.3341271
Kurtosis-1.6346146
Mean50778.574
Median Absolute Deviation (MAD)69.5
Skewness0.62925578
Sum5484086
Variance4.5893944 × 109
MonotonicityNot monotonic
2024-05-11T02:18:07.587692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
1062 15
 
7.0%
142071 11
 
5.1%
142061 8
 
3.7%
142100 7
 
3.3%
1069 5
 
2.3%
1081 4
 
1.9%
1073 4
 
1.9%
1064 3
 
1.4%
1055 3
 
1.4%
142878 3
 
1.4%
Other values (39) 45
21.0%
(Missing) 106
49.5%
ValueCountFrequency (%)
1014 1
 
0.5%
1041 1
 
0.5%
1054 2
 
0.9%
1055 3
 
1.4%
1059 1
 
0.5%
1062 15
7.0%
1064 3
 
1.4%
1065 1
 
0.5%
1069 5
 
2.3%
1070 1
 
0.5%
ValueCountFrequency (%)
142891 1
 
0.5%
142878 3
1.4%
142876 1
 
0.5%
142872 1
 
0.5%
142868 1
 
0.5%
142867 1
 
0.5%
142865 1
 
0.5%
142703 2
 
0.9%
142100 7
3.3%
142072 1
 
0.5%

사업장명
Text

Distinct206
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-05-11T02:18:08.313272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length13
Mean length7.6261682
Min length2

Characters and Unicode

Total characters1632
Distinct characters282
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

Unique198 ?
Unique (%)92.5%

Sample

1st row한국저소득장애인협회
2nd row한국아카데미
3rd row장수넷
4th row스마일쇼핑
5th row푸른
ValueCountFrequency (%)
주식회사 40
 
14.2%
대부중개 4
 
1.4%
주 3
 
1.1%
스마트폰코리아 2
 
0.7%
net 2
 
0.7%
lnc파이낸셜대부중개 2
 
0.7%
경남텔레콤 2
 
0.7%
온누리넷 2
 
0.7%
포스넷 2
 
0.7%
웰로스 2
 
0.7%
Other values (217) 220
78.3%
2024-05-11T02:18:09.921970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 79
 
4.8%
67
 
4.1%
이 63
 
3.9%
스 56
 
3.4%
) 46
 
2.8%
( 46
 
2.8%
회 45
 
2.8%
사 44
 
2.7%
식 43
 
2.6%
트 33
 
2.0%
Other values (272) 1110
68.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1388
85.0%
Space Separator 67
 
4.1%
Uppercase Letter 62
 
3.8%
Close Punctuation 46
 
2.8%
Open Punctuation 46
 
2.8%
Lowercase Letter 17
 
1.0%
Dash Punctuation 2
 
0.1%
Other Punctuation 2
 
0.1%
Decimal Number 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 79
 
5.7%
이 63
 
4.5%
스 56
 
4.0%
회 45
 
3.2%
사 44
 
3.2%
식 43
 
3.1%
트 33
 
2.4%
에 24
 
1.7%
아 22
 
1.6%
리 21
 
1.5%
Other values (235) 958
69.0%
Uppercase Letter
ValueCountFrequency (%)
M 7
11.3%
S 7
11.3%
C 7
11.3%
T 6
9.7%
N 5
 
8.1%
Y 4
 
6.5%
U 4
 
6.5%
E 3
 
4.8%
R 3
 
4.8%
L 3
 
4.8%
Other values (8) 13
21.0%
Lowercase Letter
ValueCountFrequency (%)
s 4
23.5%
h 3
17.6%
e 2
11.8%
t 1
 
5.9%
n 1
 
5.9%
a 1
 
5.9%
g 1
 
5.9%
m 1
 
5.9%
p 1
 
5.9%
o 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
. 1
50.0%
& 1
50.0%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%
Space Separator
ValueCountFrequency (%)
67
100.0%
Close Punctuation
ValueCountFrequency (%)
) 46
100.0%
Open Punctuation
ValueCountFrequency (%)
( 46
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1388
85.0%
Common 165
 
10.1%
Latin 79
 
4.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 79
 
5.7%
이 63
 
4.5%
스 56
 
4.0%
회 45
 
3.2%
사 44
 
3.2%
식 43
 
3.1%
트 33
 
2.4%
에 24
 
1.7%
아 22
 
1.6%
리 21
 
1.5%
Other values (235) 958
69.0%
Latin
ValueCountFrequency (%)
M 7
 
8.9%
S 7
 
8.9%
C 7
 
8.9%
T 6
 
7.6%
N 5
 
6.3%
s 4
 
5.1%
Y 4
 
5.1%
U 4
 
5.1%
E 3
 
3.8%
R 3
 
3.8%
Other values (19) 29
36.7%
Common
ValueCountFrequency (%)
67
40.6%
) 46
27.9%
( 46
27.9%
- 2
 
1.2%
. 1
 
0.6%
2 1
 
0.6%
& 1
 
0.6%
1 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1388
85.0%
ASCII 244
 
15.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 79
 
5.7%
이 63
 
4.5%
스 56
 
4.0%
회 45
 
3.2%
사 44
 
3.2%
식 43
 
3.1%
트 33
 
2.4%
에 24
 
1.7%
아 22
 
1.6%
리 21
 
1.5%
Other values (235) 958
69.0%
ASCII
ValueCountFrequency (%)
67
27.5%
) 46
18.9%
( 46
18.9%
M 7
 
2.9%
S 7
 
2.9%
C 7
 
2.9%
T 6
 
2.5%
N 5
 
2.0%
s 4
 
1.6%
Y 4
 
1.6%
Other values (27) 45
18.4%

최종수정일자
Date

UNIQUE 

Distinct214
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
Minimum2007-07-24 11:16:37
Maximum2024-03-04 13:22:48
2024-05-11T02:18:10.499106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:18:11.149327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
I
181 
U
33 

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 181
84.6%
U 33
 
15.4%

Length

2024-05-11T02:18:11.719724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:18:12.096351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 181
84.6%
u 33
 
15.4%

데이터갱신일자
Categorical

IMBALANCE 

Distinct45
Distinct (%)21.0%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2018-08-31 23:59:59.0
161 
2022-02-23 02:40:00.0
 
7
2021-08-07 00:22:51.0
 
2
2021-11-01 22:02:00.0
 
2
2021-01-21 00:23:03.0
 
2
Other values (40)
40 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique40 ?
Unique (%)18.7%

Sample

1st row2018-08-31 23:59:59.0
2nd row2018-08-31 23:59:59.0
3rd row2018-08-31 23:59:59.0
4th row2018-08-31 23:59:59.0
5th row2018-08-31 23:59:59.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 161
75.2%
2022-02-23 02:40:00.0 7
 
3.3%
2021-08-07 00:22:51.0 2
 
0.9%
2021-11-01 22:02:00.0 2
 
0.9%
2021-01-21 00:23:03.0 2
 
0.9%
2019-12-18 02:40:00.0 1
 
0.5%
2021-10-30 22:03:00.0 1
 
0.5%
2020-03-22 02:40:00.0 1
 
0.5%
2020-02-08 02:40:00.0 1
 
0.5%
2018-09-18 23:59:59.0 1
 
0.5%
Other values (35) 35
 
16.4%

Length

2024-05-11T02:18:12.704460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
23:59:59.0 162
37.9%
2018-08-31 161
37.6%
02:40:00.0 19
 
4.4%
2022-02-23 7
 
1.6%
2021-11-01 4
 
0.9%
22:02:00.0 4
 
0.9%
23:06:00.0 3
 
0.7%
00:09:00.0 2
 
0.5%
2021-12-08 2
 
0.5%
2021-06-09 2
 
0.5%
Other values (53) 62
 
14.5%

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing214
Missing (%)100.0%
Memory size2.0 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct126
Distinct (%)60.3%
Missing5
Missing (%)2.3%
Infinite0
Infinite (%)0.0%
Mean202214.93
Minimum200802.62
Maximum203874.19
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-05-11T02:18:13.292252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum200802.62
5-th percentile201492.17
Q1202052.38
median202165.85
Q3202443.07
95-th percentile202833.61
Maximum203874.19
Range3071.5769
Interquartile range (IQR)390.69007

Descriptive statistics

Standard deviation449.29116
Coefficient of variation (CV)0.0022218496
Kurtosis3.7625332
Mean202214.93
Median Absolute Deviation (MAD)196.65366
Skewness0.6629247
Sum42262921
Variance201862.55
MonotonicityNot monotonic
2024-05-11T02:18:14.588962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
202155.401317068 17
 
7.9%
202511.102551438 11
 
5.1%
202157.200384579 7
 
3.3%
202052.37985575 5
 
2.3%
202584.95535682 4
 
1.9%
203874.192185321 4
 
1.9%
202253.015161523 4
 
1.9%
202257.319917341 4
 
1.9%
202445.004649696 3
 
1.4%
201852.357635512 3
 
1.4%
Other values (116) 147
68.7%
(Missing) 5
 
2.3%
ValueCountFrequency (%)
200802.615294385 1
0.5%
201045.611312321 2
0.9%
201072.909901738 1
0.5%
201098.913236898 1
0.5%
201278.240759186 1
0.5%
201317.737524527 1
0.5%
201322.286465964 1
0.5%
201411.465015449 1
0.5%
201445.583642301 1
0.5%
201483.350029986 1
0.5%
ValueCountFrequency (%)
203874.192185321 4
1.9%
203589.199617419 1
 
0.5%
203452.54250506 1
 
0.5%
203395.513845154 1
 
0.5%
203033.025955793 1
 
0.5%
202992.215295927 1
 
0.5%
202973.127176547 1
 
0.5%
202886.021376141 1
 
0.5%
202754.986733832 1
 
0.5%
202741.313701115 1
 
0.5%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct126
Distinct (%)60.3%
Missing5
Missing (%)2.3%
Infinite0
Infinite (%)0.0%
Mean459000.64
Minimum454922.3
Maximum460603.28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-05-11T02:18:15.894059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum454922.3
5-th percentile457380.74
Q1458345.67
median459216.62
Q3459421.35
95-th percentile460009.12
Maximum460603.28
Range5680.9746
Interquartile range (IQR)1075.6812

Descriptive statistics

Standard deviation825.47398
Coefficient of variation (CV)0.0017984158
Kurtosis2.7565482
Mean459000.64
Median Absolute Deviation (MAD)274.95815
Skewness-1.339496
Sum95931133
Variance681407.29
MonotonicityNot monotonic
2024-05-11T02:18:16.627804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
459411.940883021 17
 
7.9%
459156.609544031 11
 
5.1%
458298.50542541 7
 
3.3%
459491.573913047 5
 
2.3%
460019.814255249 4
 
1.9%
458045.425631086 4
 
1.9%
459146.903188746 4
 
1.9%
459203.633789762 4
 
1.9%
458021.25327625 3
 
1.4%
459181.42721284 3
 
1.4%
Other values (116) 147
68.7%
(Missing) 5
 
2.3%
ValueCountFrequency (%)
454922.301194827 1
0.5%
456580.920380914 1
0.5%
456654.557071446 1
0.5%
456770.630403897 1
0.5%
456924.170790826 1
0.5%
456931.518518136 1
0.5%
457074.811678173 1
0.5%
457088.119453254 1
0.5%
457292.551352479 1
0.5%
457292.961457264 2
0.9%
ValueCountFrequency (%)
460603.275808031 1
 
0.5%
460584.002572911 1
 
0.5%
460431.789046655 1
 
0.5%
460404.096223242 1
 
0.5%
460166.629217976 1
 
0.5%
460138.547624302 1
 
0.5%
460027.695602706 1
 
0.5%
460019.814255249 4
1.9%
459993.074907442 1
 
0.5%
459975.940915805 1
 
0.5%

자산규모
Real number (ℝ)

MISSING  ZEROS 

Distinct39
Distinct (%)52.7%
Missing140
Missing (%)65.4%
Infinite0
Infinite (%)0.0%
Mean2.8752848 × 109
Minimum0
Maximum1.5431256 × 1011
Zeros19
Zeros (%)8.9%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-05-11T02:18:17.279215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1250
median25000000
Q31.9663294 × 108
95-th percentile1.0241815 × 109
Maximum1.5431256 × 1011
Range1.5431256 × 1011
Interquartile range (IQR)1.9663269 × 108

Descriptive statistics

Standard deviation1.8682043 × 1010
Coefficient of variation (CV)6.4974583
Kurtosis61.575775
Mean2.8752848 × 109
Median Absolute Deviation (MAD)25000000
Skewness7.6896816
Sum2.1277107 × 1011
Variance3.4901873 × 1020
MonotonicityNot monotonic
2024-05-11T02:18:17.788443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
0 19
 
8.9%
10000000 8
 
3.7%
50000000 5
 
2.3%
20000000 3
 
1.4%
100000000 3
 
1.4%
30000000 2
 
0.9%
15000000 2
 
0.9%
40000000 1
 
0.5%
37743043 1
 
0.5%
266348895 1
 
0.5%
Other values (29) 29
 
13.6%
(Missing) 140
65.4%
ValueCountFrequency (%)
0 19
8.9%
1000 1
 
0.5%
1000000 1
 
0.5%
5000000 1
 
0.5%
6553524 1
 
0.5%
10000000 8
3.7%
10050000 1
 
0.5%
15000000 2
 
0.9%
20000000 3
 
1.4%
30000000 2
 
0.9%
ValueCountFrequency (%)
154312564609 1
0.5%
47658841166 1
0.5%
1105882851 1
0.5%
1063207586 1
0.5%
1003167438 1
0.5%
720980412 1
0.5%
622156695 1
0.5%
564794418 1
0.5%
552542466 1
0.5%
505408752 1
0.5%

부채총액
Real number (ℝ)

MISSING  ZEROS 

Distinct26
Distinct (%)35.1%
Missing140
Missing (%)65.4%
Infinite0
Infinite (%)0.0%
Mean7.2761867 × 108
Minimum0
Maximum4.5287977 × 1010
Zeros49
Zeros (%)22.9%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-05-11T02:18:18.223160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q353327685
95-th percentile8.2551414 × 108
Maximum4.5287977 × 1010
Range4.5287977 × 1010
Interquartile range (IQR)53327685

Descriptive statistics

Standard deviation5.2609229 × 109
Coefficient of variation (CV)7.2303297
Kurtosis73.419714
Mean7.2761867 × 108
Median Absolute Deviation (MAD)0
Skewness8.5533866
Sum5.3843782 × 1010
Variance2.767731 × 1019
MonotonicityNot monotonic
2024-05-11T02:18:18.623451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 49
 
22.9%
2176122904 1
 
0.5%
77495460 1
 
0.5%
47994452 1
 
0.5%
104550151 1
 
0.5%
32266000 1
 
0.5%
54436913 1
 
0.5%
235641237 1
 
0.5%
15628610 1
 
0.5%
223012036 1
 
0.5%
Other values (16) 16
 
7.5%
(Missing) 140
65.4%
ValueCountFrequency (%)
0 49
22.9%
6077200 1
 
0.5%
10000000 1
 
0.5%
15628610 1
 
0.5%
32266000 1
 
0.5%
47994452 1
 
0.5%
50000000 1
 
0.5%
54436913 1
 
0.5%
59343708 1
 
0.5%
77495460 1
 
0.5%
ValueCountFrequency (%)
45287976888 1
0.5%
2176122904 1
0.5%
970700686 1
0.5%
936687244 1
0.5%
765651703 1
0.5%
744310235 1
0.5%
597575460 1
0.5%
441138274 1
0.5%
302566837 1
0.5%
289016048 1
0.5%

자본금
Real number (ℝ)

MISSING  ZEROS 

Distinct36
Distinct (%)48.6%
Missing140
Missing (%)65.4%
Infinite0
Infinite (%)0.0%
Mean8.2943692 × 108
Minimum-97996627
Maximum4.5482718 × 1010
Zeros15
Zeros (%)7.0%
Negative1
Negative (%)0.5%
Memory size2.0 KiB
2024-05-11T02:18:19.042196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-97996627
5-th percentile0
Q15000000
median18457804
Q373155030
95-th percentile4.2297124 × 108
Maximum4.5482718 × 1010
Range4.5580715 × 1010
Interquartile range (IQR)68155030

Descriptive statistics

Standard deviation5.4062682 × 109
Coefficient of variation (CV)6.517998
Kurtosis66.253145
Mean8.2943692 × 108
Median Absolute Deviation (MAD)18457804
Skewness8.0155824
Sum6.1378332 × 1010
Variance2.9227736 × 1019
MonotonicityNot monotonic
2024-05-11T02:18:19.468046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
0 15
 
7.0%
10000000 10
 
4.7%
50000000 8
 
3.7%
20000000 3
 
1.4%
5000000 3
 
1.4%
15000000 2
 
0.9%
300000000 2
 
0.9%
100000000 2
 
0.9%
40000000 2
 
0.9%
8000000 1
 
0.5%
Other values (26) 26
 
12.1%
(Missing) 140
65.4%
ValueCountFrequency (%)
-97996627 1
 
0.5%
0 15
7.0%
1000 1
 
0.5%
1000000 1
 
0.5%
5000000 3
 
1.4%
8000000 1
 
0.5%
10000000 10
4.7%
10050000 1
 
0.5%
13920408 1
 
0.5%
15000000 2
 
0.9%
ValueCountFrequency (%)
45482718262 1
0.5%
10691250000 1
0.5%
666543499 1
0.5%
465632126 1
0.5%
400000000 1
0.5%
311235554 1
0.5%
304838015 1
0.5%
300000000 2
0.9%
262227581 1
0.5%
260242951 1
0.5%

판매방식명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing214
Missing (%)100.0%
Memory size2.0 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)자산규모부채총액자본금판매방식명
03080000200730800922420000120020814<NA>3폐업3폐업처리20070801<NA><NA><NA>9993051<NA>142060서울특별시 강북구 번동 ***번지 *호 *층서울특별시 강북구 도봉로 ***-* (번동,*층)<NA>한국저소득장애인협회2009-03-23 17:12:27I2018-08-31 23:59:59.0<NA>202524.354061459851.24159<NA><NA><NA><NA>
13080000200730800922420000220020814<NA>3폐업3폐업처리20041109<NA><NA><NA>9456491<NA>142060서울특별시 강북구 번동 ***번지 **호 창강b/d ***호서울특별시 강북구 덕릉로 ***, ***호 (번동,창강b/d)<NA>한국아카데미2007-07-24 11:16:37I2018-08-31 23:59:59.0<NA>202511.102551459156.609544<NA><NA><NA><NA>
23080000200730800922420000320020826<NA>3폐업3폐업처리20021203<NA><NA><NA>0807008549<NA>142070서울특별시 강북구 수유동 ***번지 **호 *층 *호서울특별시 강북구 인수봉로 ***, *호 (수유동,*층)<NA>장수넷2007-07-24 11:17:08I2018-08-31 23:59:59.0<NA>201072.909902459260.651108<NA><NA><NA><NA>
33080000200730800922420000420020902<NA>4취소/말소/만료/정지/중지7직권말소<NA><NA><NA><NA>0809983000<NA>142070서울특별시 강북구 수유동 ***번지 *호서울특별시 강북구 인수봉로 *** (수유동)<NA>스마일쇼핑2016-08-18 10:24:29I2018-08-31 23:59:59.0<NA>201098.913237459437.396211<NA><NA><NA><NA>
43080000200730800922420000520030117<NA>3폐업3폐업처리20030916<NA><NA><NA>9020569<NA>142060서울특별시 강북구 번동 ***번지 **호 가든타워 ****호서울특별시 강북구 도봉로 ***, ****호 (번동,가든타워)<NA>푸른2007-07-24 11:25:33I2018-08-31 23:59:59.0<NA>202155.401317459411.940883<NA><NA><NA><NA>
53080000200730800922420000620030117<NA>3폐업3폐업처리20100519<NA><NA><NA>64350330<NA>142060서울특별시 강북구 번동 ***번지 **호 창강빌딩 ***호서울특별시 강북구 덕릉로 ***, ***호 (번동,창강빌딩)<NA>(주)디지탈우민2010-05-19 10:50:33I2018-08-31 23:59:59.0<NA>202511.102551459156.609544457659548146423994311235554<NA>
63080000200730800922420000720030320<NA>3폐업3폐업처리20040706<NA><NA><NA>9893138<NA>142100서울특별시 강북구 미아동 ***번지 **호 ***호서울특별시 강북구 솔매로**길 *, ***호 (미아동)<NA>인컴퍼니2007-07-24 14:22:18I2018-08-31 23:59:59.0<NA>202277.745063458284.971515<NA><NA><NA><NA>
73080000200730800922420000820030320<NA>3폐업3폐업처리20030625<NA><NA><NA>4982222<NA>142060서울특별시 강북구 번동 ***번지 **호 *층서울특별시 강북구 오현로**길 *** (번동,*층)<NA>솔표조선건강2007-07-24 14:27:39I2018-08-31 23:59:59.0<NA>202973.127177458955.176049<NA><NA><NA><NA>
83080000200730800922420000920030526<NA>3폐업3폐업처리20040706<NA><NA><NA>9970358<NA>142070서울특별시 강북구 수유동 ***번지 **호 수유하이츠빌라 다동 **호서울특별시 강북구 삼양로***길 **-**, **호 (수유동,수유하이츠빌라 다동)<NA>텔레베이스2007-07-24 14:32:31I2018-08-31 23:59:59.0<NA>201317.737525460027.695603<NA><NA><NA><NA>
93080000200730800922420001020030802200407064취소/말소/만료/정지/중지4직권취소20040706<NA><NA><NA>9889467<NA>142060서울특별시 강북구 번동 ***번지 **호 쌍용빌딩 *층서울특별시 강북구 한천로 **** (번동,쌍용빌딩 *층)<NA>코리아텔레콤2007-07-24 14:37:08I2018-08-31 23:59:59.0<NA>202503.384425459591.35306<NA><NA><NA><NA>
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