Overview

Dataset statistics

Number of variables60
Number of observations245
Missing cells4429
Missing cells (%)30.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory124.3 KiB
Average record size in memory519.5 B

Variable types

Categorical24
Text7
DateTime4
Numeric11
Unsupported14

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),문화체육업종명,문화사업자구분명,지역구분명,총층수,주변환경명,제작취급품목내용,보험기관명,건물용도명,지상층수,지하층수,객실수,건축연면적,영문상호명,영문상호주소,선박총톤수,선박척수,선박제원,무대면적,좌석수,기념품종류,회의실별동시수용인원,시설면적,놀이기구수내역,놀이시설수,방송시설유무,발전시설유무,의무실유무,안내소유무,기획여행보험시작일자,기획여행보험종료일자,자본금,보험시작일자,보험종료일자,부대시설내역,시설규모
Author영등포구
URLhttps://data.seoul.go.kr/dataList/OA-17570/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 is highly imbalanced (85.8%)Imbalance
휴업시작일자 is highly imbalanced (93.4%)Imbalance
휴업종료일자 is highly imbalanced (93.4%)Imbalance
지역구분명 is highly imbalanced (85.2%)Imbalance
주변환경명 is highly imbalanced (79.8%)Imbalance
건물용도명 is highly imbalanced (78.4%)Imbalance
지하층수 is highly imbalanced (63.4%)Imbalance
영문상호주소 is highly imbalanced (84.5%)Imbalance
폐업일자 has 90 (36.7%) missing valuesMissing
재개업일자 has 245 (100.0%) missing valuesMissing
전화번호 has 59 (24.1%) missing valuesMissing
소재지면적 has 245 (100.0%) missing valuesMissing
소재지우편번호 has 105 (42.9%) missing valuesMissing
도로명주소 has 8 (3.3%) missing valuesMissing
도로명우편번호 has 101 (41.2%) missing valuesMissing
업태구분명 has 245 (100.0%) missing valuesMissing
총층수 has 36 (14.7%) missing valuesMissing
제작취급품목내용 has 245 (100.0%) missing valuesMissing
지상층수 has 36 (14.7%) missing valuesMissing
영문상호명 has 236 (96.3%) missing valuesMissing
선박제원 has 245 (100.0%) missing valuesMissing
기념품종류 has 245 (100.0%) missing valuesMissing
시설면적 has 36 (14.7%) missing valuesMissing
놀이기구수내역 has 245 (100.0%) missing valuesMissing
방송시설유무 has 245 (100.0%) missing valuesMissing
발전시설유무 has 245 (100.0%) missing valuesMissing
의무실유무 has 245 (100.0%) missing valuesMissing
안내소유무 has 245 (100.0%) missing valuesMissing
기획여행보험시작일자 has 245 (100.0%) missing valuesMissing
기획여행보험종료일자 has 245 (100.0%) missing valuesMissing
자본금 has 36 (14.7%) missing valuesMissing
보험시작일자 has 108 (44.1%) missing valuesMissing
보험종료일자 has 108 (44.1%) missing valuesMissing
부대시설내역 has 245 (100.0%) missing valuesMissing
시설규모 has 36 (14.7%) missing valuesMissing
관리번호 has unique valuesUnique
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
제작취급품목내용 is an unsupported type, check if it needs cleaning or further analysisUnsupported
선박제원 is an unsupported type, check if it needs cleaning or further analysisUnsupported
기념품종류 is an unsupported type, check if it needs cleaning or further analysisUnsupported
놀이기구수내역 is an unsupported type, check if it needs cleaning or further analysisUnsupported
방송시설유무 is an unsupported type, check if it needs cleaning or further analysisUnsupported
발전시설유무 is an unsupported type, check if it needs cleaning or further analysisUnsupported
의무실유무 is an unsupported type, check if it needs cleaning or further analysisUnsupported
안내소유무 is an unsupported type, check if it needs cleaning or further analysisUnsupported
기획여행보험시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
기획여행보험종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
부대시설내역 is an unsupported type, check if it needs cleaning or further analysisUnsupported
총층수 has 195 (79.6%) zerosZeros
지상층수 has 192 (78.4%) zerosZeros
시설면적 has 191 (78.0%) zerosZeros
자본금 has 74 (30.2%) zerosZeros
시설규모 has 191 (78.0%) zerosZeros

Reproduction

Analysis started2024-05-11 06:10:21.093716
Analysis finished2024-05-11 06:10:22.380497
Duration1.29 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
3180000
245 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3180000
2nd row3180000
3rd row3180000
4th row3180000
5th row3180000

Common Values

ValueCountFrequency (%)
3180000 245
100.0%

Length

2024-05-11T15:10:22.461436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:10:22.853165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3180000 245
100.0%

관리번호
Text

UNIQUE 

Distinct245
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2024-05-11T15:10:23.095222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters4900
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique245 ?
Unique (%)100.0%

Sample

1st rowCDFI2260011983000001
2nd rowCDFI2260011987000001
3rd rowCDFI2260011989000001
4th rowCDFI2260011989000002
5th rowCDFI2260011989000003
ValueCountFrequency (%)
cdfi2260011983000001 1
 
0.4%
cdfi2260012010000018 1
 
0.4%
cdfi2260012013000010 1
 
0.4%
cdfi2260012013000011 1
 
0.4%
cdfi2260012013000012 1
 
0.4%
cdfi2260012013000013 1
 
0.4%
cdfi2260012013000014 1
 
0.4%
cdfi2260012013000015 1
 
0.4%
cdfi2260012013000017 1
 
0.4%
cdfi2260012014000001 1
 
0.4%
Other values (235) 235
95.9%
2024-05-11T15:10:23.649947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1942
39.6%
2 777
15.9%
1 534
 
10.9%
6 282
 
5.8%
C 245
 
5.0%
D 245
 
5.0%
F 245
 
5.0%
I 245
 
5.0%
9 133
 
2.7%
4 64
 
1.3%
Other values (4) 188
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3920
80.0%
Uppercase Letter 980
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1942
49.5%
2 777
19.8%
1 534
 
13.6%
6 282
 
7.2%
9 133
 
3.4%
4 64
 
1.6%
7 56
 
1.4%
5 46
 
1.2%
8 43
 
1.1%
3 43
 
1.1%
Uppercase Letter
ValueCountFrequency (%)
C 245
25.0%
D 245
25.0%
F 245
25.0%
I 245
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3920
80.0%
Latin 980
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1942
49.5%
2 777
19.8%
1 534
 
13.6%
6 282
 
7.2%
9 133
 
3.4%
4 64
 
1.6%
7 56
 
1.4%
5 46
 
1.2%
8 43
 
1.1%
3 43
 
1.1%
Latin
ValueCountFrequency (%)
C 245
25.0%
D 245
25.0%
F 245
25.0%
I 245
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4900
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1942
39.6%
2 777
15.9%
1 534
 
10.9%
6 282
 
5.8%
C 245
 
5.0%
D 245
 
5.0%
F 245
 
5.0%
I 245
 
5.0%
9 133
 
2.7%
4 64
 
1.3%
Other values (4) 188
 
3.8%
Distinct236
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
Minimum1983-10-06 00:00:00
Maximum2023-05-22 00:00:00
2024-05-11T15:10:23.854268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:10:24.057820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
235 
20121210
 
8
20190710
 
1
20151020
 
1

Length

Max length8
Median length4
Mean length4.1632653
Min length4

Unique

Unique2 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 235
95.9%
20121210 8
 
3.3%
20190710 1
 
0.4%
20151020 1
 
0.4%

Length

2024-05-11T15:10:24.248518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:10:24.380423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 235
95.9%
20121210 8
 
3.3%
20190710 1
 
0.4%
20151020 1
 
0.4%
Distinct5
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
3
153 
1
61 
4
25 
2
 
4
5
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 153
62.4%
1 61
 
24.9%
4 25
 
10.2%
2 4
 
1.6%
5 2
 
0.8%

Length

2024-05-11T15:10:24.541028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:10:24.675532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 153
62.4%
1 61
 
24.9%
4 25
 
10.2%
2 4
 
1.6%
5 2
 
0.8%

영업상태명
Categorical

Distinct5
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
폐업
153 
영업/정상
61 
취소/말소/만료/정지/중지
25 
휴업
 
4
제외/삭제/전출
 
2

Length

Max length14
Median length2
Mean length4.0204082
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 153
62.4%
영업/정상 61
 
24.9%
취소/말소/만료/정지/중지 25
 
10.2%
휴업 4
 
1.6%
제외/삭제/전출 2
 
0.8%

Length

2024-05-11T15:10:24.842397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:10:24.999253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 153
62.4%
영업/정상 61
 
24.9%
취소/말소/만료/정지/중지 25
 
10.2%
휴업 4
 
1.6%
제외/삭제/전출 2
 
0.8%

상세영업상태코드
Real number (ℝ)

Distinct6
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.3673469
Minimum2
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-05-11T15:10:25.174875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3
Q13
median3
Q313
95-th percentile30
Maximum31
Range29
Interquartile range (IQR)10

Descriptive statistics

Standard deviation8.6149267
Coefficient of variation (CV)1.0295888
Kurtosis1.594915
Mean8.3673469
Median Absolute Deviation (MAD)0
Skewness1.6140191
Sum2050
Variance74.216962
MonotonicityNot monotonic
2024-05-11T15:10:25.342187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3 153
62.4%
13 61
 
24.9%
30 15
 
6.1%
31 10
 
4.1%
2 4
 
1.6%
15 2
 
0.8%
ValueCountFrequency (%)
2 4
 
1.6%
3 153
62.4%
13 61
 
24.9%
15 2
 
0.8%
30 15
 
6.1%
31 10
 
4.1%
ValueCountFrequency (%)
31 10
 
4.1%
30 15
 
6.1%
15 2
 
0.8%
13 61
 
24.9%
3 153
62.4%
2 4
 
1.6%
Distinct6
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
폐업
153 
영업중
61 
허가취소
 
15
등록취소
 
10
휴업
 
4

Length

Max length4
Median length2
Mean length2.4530612
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row폐업
2nd row허가취소
3rd row폐업
4th row허가취소
5th row폐업

Common Values

ValueCountFrequency (%)
폐업 153
62.4%
영업중 61
 
24.9%
허가취소 15
 
6.1%
등록취소 10
 
4.1%
휴업 4
 
1.6%
전출 2
 
0.8%

Length

2024-05-11T15:10:25.580403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:10:25.794898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 153
62.4%
영업중 61
 
24.9%
허가취소 15
 
6.1%
등록취소 10
 
4.1%
휴업 4
 
1.6%
전출 2
 
0.8%

폐업일자
Date

MISSING 

Distinct145
Distinct (%)93.5%
Missing90
Missing (%)36.7%
Memory size2.0 KiB
Minimum1996-10-07 00:00:00
Maximum2024-04-24 00:00:00
2024-05-11T15:10:25.950132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:10:26.122219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Categorical

IMBALANCE 

Distinct5
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
241 
20060816
 
1
20100928
 
1
20081111
 
1
20100608
 
1

Length

Max length8
Median length4
Mean length4.0653061
Min length4

Unique

Unique4 ?
Unique (%)1.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 241
98.4%
20060816 1
 
0.4%
20100928 1
 
0.4%
20081111 1
 
0.4%
20100608 1
 
0.4%

Length

2024-05-11T15:10:26.282981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:10:26.428095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 241
98.4%
20060816 1
 
0.4%
20100928 1
 
0.4%
20081111 1
 
0.4%
20100608 1
 
0.4%

휴업종료일자
Categorical

IMBALANCE 

Distinct5
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
241 
20070815
 
1
20111231
 
1
20090131
 
1
20110108
 
1

Length

Max length8
Median length4
Mean length4.0653061
Min length4

Unique

Unique4 ?
Unique (%)1.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 241
98.4%
20070815 1
 
0.4%
20111231 1
 
0.4%
20090131 1
 
0.4%
20110108 1
 
0.4%

Length

2024-05-11T15:10:26.588863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:10:26.749449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 241
98.4%
20070815 1
 
0.4%
20111231 1
 
0.4%
20090131 1
 
0.4%
20110108 1
 
0.4%

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing245
Missing (%)100.0%
Memory size2.3 KiB

전화번호
Text

MISSING 

Distinct179
Distinct (%)96.2%
Missing59
Missing (%)24.1%
Memory size2.0 KiB
2024-05-11T15:10:27.044274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length13
Mean length9.9247312
Min length8

Characters and Unicode

Total characters1846
Distinct characters14
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique173 ?
Unique (%)93.0%

Sample

1st row823-6774
2nd row785-0111
3rd row831-1235
4th row783-7772
5th row02-848-0674
ValueCountFrequency (%)
785-0111 3
 
1.6%
2165-8080 2
 
1.1%
070-8827-3660 2
 
1.1%
02-737-5121 2
 
1.1%
853-0110 2
 
1.1%
783-6601 2
 
1.1%
02-2675-6280 1
 
0.5%
585-5656 1
 
0.5%
2085-7531 1
 
0.5%
1544-1782 1
 
0.5%
Other values (170) 170
90.9%
2024-05-11T15:10:27.528636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 260
14.1%
0 260
14.1%
2 232
12.6%
7 202
10.9%
6 170
9.2%
8 169
9.2%
3 151
8.2%
1 136
7.4%
5 110
6.0%
4 91
 
4.9%
Other values (4) 65
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1583
85.8%
Dash Punctuation 260
 
14.1%
Other Punctuation 2
 
0.1%
Space Separator 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 260
16.4%
2 232
14.7%
7 202
12.8%
6 170
10.7%
8 169
10.7%
3 151
9.5%
1 136
8.6%
5 110
6.9%
4 91
 
5.7%
9 62
 
3.9%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
* 1
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 260
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1846
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 260
14.1%
0 260
14.1%
2 232
12.6%
7 202
10.9%
6 170
9.2%
8 169
9.2%
3 151
8.2%
1 136
7.4%
5 110
6.0%
4 91
 
4.9%
Other values (4) 65
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1846
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 260
14.1%
0 260
14.1%
2 232
12.6%
7 202
10.9%
6 170
9.2%
8 169
9.2%
3 151
8.2%
1 136
7.4%
5 110
6.0%
4 91
 
4.9%
Other values (4) 65
 
3.5%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing245
Missing (%)100.0%
Memory size2.3 KiB

소재지우편번호
Text

MISSING 

Distinct75
Distinct (%)53.6%
Missing105
Missing (%)42.9%
Memory size2.0 KiB
2024-05-11T15:10:27.850118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0285714
Min length6

Characters and Unicode

Total characters844
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

Unique41 ?
Unique (%)29.3%

Sample

1st row150045
2nd row150890
3rd row150814
4th row150741
5th row150850
ValueCountFrequency (%)
150033 8
 
5.7%
150010 6
 
4.3%
150035 5
 
3.6%
150874 5
 
3.6%
150890 5
 
3.6%
150886 4
 
2.9%
150036 4
 
2.9%
150037 4
 
2.9%
150877 3
 
2.1%
150891 3
 
2.1%
Other values (65) 93
66.4%
2024-05-11T15:10:28.442802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 232
27.5%
1 180
21.3%
5 160
19.0%
8 77
 
9.1%
3 50
 
5.9%
7 46
 
5.5%
9 32
 
3.8%
4 25
 
3.0%
6 23
 
2.7%
2 15
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 840
99.5%
Dash Punctuation 4
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 232
27.6%
1 180
21.4%
5 160
19.0%
8 77
 
9.2%
3 50
 
6.0%
7 46
 
5.5%
9 32
 
3.8%
4 25
 
3.0%
6 23
 
2.7%
2 15
 
1.8%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 844
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 232
27.5%
1 180
21.3%
5 160
19.0%
8 77
 
9.1%
3 50
 
5.9%
7 46
 
5.5%
9 32
 
3.8%
4 25
 
3.0%
6 23
 
2.7%
2 15
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 844
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 232
27.5%
1 180
21.3%
5 160
19.0%
8 77
 
9.1%
3 50
 
5.9%
7 46
 
5.5%
9 32
 
3.8%
4 25
 
3.0%
6 23
 
2.7%
2 15
 
1.8%
Distinct241
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2024-05-11T15:10:28.862791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length36
Mean length29.114286
Min length18

Characters and Unicode

Total characters7133
Distinct characters205
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique238 ?
Unique (%)97.1%

Sample

1st row서울특별시 영등포구 당산동5가 11-33번지
2nd row서울특별시 영등포구 여의도동 44-26번지
3rd row서울특별시 영등포구 대림동 700-1번지
4th row서울특별시 영등포구 여의도동 44-26번지 중앙빌딩 101동
5th row서울특별시 영등포구 신길동 425-7번지
ValueCountFrequency (%)
서울특별시 245
19.4%
영등포구 245
19.4%
여의도동 83
 
6.6%
대림동 21
 
1.7%
당산동6가 13
 
1.0%
당산동3가 12
 
0.9%
양평동4가 10
 
0.8%
2층 10
 
0.8%
영등포동5가 10
 
0.8%
영등포동3가 9
 
0.7%
Other values (428) 607
48.0%
2024-05-11T15:10:29.444797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1194
 
16.7%
1 301
 
4.2%
299
 
4.2%
297
 
4.2%
295
 
4.1%
261
 
3.7%
250
 
3.5%
249
 
3.5%
246
 
3.4%
246
 
3.4%
Other values (195) 3495
49.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4359
61.1%
Decimal Number 1339
 
18.8%
Space Separator 1194
 
16.7%
Dash Punctuation 200
 
2.8%
Uppercase Letter 19
 
0.3%
Open Punctuation 8
 
0.1%
Close Punctuation 8
 
0.1%
Other Punctuation 4
 
0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
299
 
6.9%
297
 
6.8%
295
 
6.8%
261
 
6.0%
250
 
5.7%
249
 
5.7%
246
 
5.6%
246
 
5.6%
245
 
5.6%
245
 
5.6%
Other values (163) 1726
39.6%
Uppercase Letter
ValueCountFrequency (%)
B 4
21.1%
C 2
10.5%
M 2
10.5%
E 2
10.5%
T 2
10.5%
G 1
 
5.3%
A 1
 
5.3%
K 1
 
5.3%
S 1
 
5.3%
R 1
 
5.3%
Other values (2) 2
10.5%
Decimal Number
ValueCountFrequency (%)
1 301
22.5%
3 171
12.8%
2 167
12.5%
4 165
12.3%
0 129
9.6%
5 114
 
8.5%
6 113
 
8.4%
7 76
 
5.7%
9 52
 
3.9%
8 51
 
3.8%
Other Punctuation
ValueCountFrequency (%)
, 2
50.0%
& 1
25.0%
: 1
25.0%
Open Punctuation
ValueCountFrequency (%)
( 7
87.5%
1
 
12.5%
Close Punctuation
ValueCountFrequency (%)
) 7
87.5%
1
 
12.5%
Space Separator
ValueCountFrequency (%)
1194
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 200
100.0%
Lowercase Letter
ValueCountFrequency (%)
c 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4359
61.1%
Common 2753
38.6%
Latin 21
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
299
 
6.9%
297
 
6.8%
295
 
6.8%
261
 
6.0%
250
 
5.7%
249
 
5.7%
246
 
5.6%
246
 
5.6%
245
 
5.6%
245
 
5.6%
Other values (163) 1726
39.6%
Common
ValueCountFrequency (%)
1194
43.4%
1 301
 
10.9%
- 200
 
7.3%
3 171
 
6.2%
2 167
 
6.1%
4 165
 
6.0%
0 129
 
4.7%
5 114
 
4.1%
6 113
 
4.1%
7 76
 
2.8%
Other values (9) 123
 
4.5%
Latin
ValueCountFrequency (%)
B 4
19.0%
C 2
9.5%
M 2
9.5%
E 2
9.5%
c 2
9.5%
T 2
9.5%
G 1
 
4.8%
A 1
 
4.8%
K 1
 
4.8%
S 1
 
4.8%
Other values (3) 3
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4359
61.1%
ASCII 2772
38.9%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1194
43.1%
1 301
 
10.9%
- 200
 
7.2%
3 171
 
6.2%
2 167
 
6.0%
4 165
 
6.0%
0 129
 
4.7%
5 114
 
4.1%
6 113
 
4.1%
7 76
 
2.7%
Other values (20) 142
 
5.1%
Hangul
ValueCountFrequency (%)
299
 
6.9%
297
 
6.8%
295
 
6.8%
261
 
6.0%
250
 
5.7%
249
 
5.7%
246
 
5.6%
246
 
5.6%
245
 
5.6%
245
 
5.6%
Other values (163) 1726
39.6%
None
ValueCountFrequency (%)
1
50.0%
1
50.0%

도로명주소
Text

MISSING 

Distinct234
Distinct (%)98.7%
Missing8
Missing (%)3.3%
Memory size2.0 KiB
2024-05-11T15:10:29.817504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length44
Mean length36.270042
Min length24

Characters and Unicode

Total characters8596
Distinct characters232
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique231 ?
Unique (%)97.5%

Sample

1st row서울특별시 영등포구 당산로 222 (당산동5가)
2nd row서울특별시 영등포구 국제금융로8길 19 (여의도동)
3rd row서울특별시 영등포구 대림로 154 (대림동)
4th row서울특별시 영등포구 국제금융로8길 19, 101동 (여의도동,중앙빌딩)
5th row서울특별시 영등포구 신길로 79-2 (신길동)
ValueCountFrequency (%)
서울특별시 237
 
15.9%
영등포구 237
 
15.9%
여의도동 42
 
2.8%
대림동 16
 
1.1%
영중로 14
 
0.9%
당산로 14
 
0.9%
양평로 13
 
0.9%
19 11
 
0.7%
영등포로 10
 
0.7%
당산동6가 10
 
0.7%
Other values (506) 883
59.4%
2024-05-11T15:10:30.450046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1317
 
15.3%
331
 
3.9%
304
 
3.5%
301
 
3.5%
1 266
 
3.1%
260
 
3.0%
, 254
 
3.0%
245
 
2.9%
245
 
2.9%
) 244
 
2.8%
Other values (222) 4829
56.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5129
59.7%
Decimal Number 1351
 
15.7%
Space Separator 1317
 
15.3%
Other Punctuation 256
 
3.0%
Close Punctuation 245
 
2.9%
Open Punctuation 245
 
2.9%
Uppercase Letter 28
 
0.3%
Dash Punctuation 23
 
0.3%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
331
 
6.5%
304
 
5.9%
301
 
5.9%
260
 
5.1%
245
 
4.8%
245
 
4.8%
239
 
4.7%
239
 
4.7%
237
 
4.6%
237
 
4.6%
Other values (189) 2491
48.6%
Uppercase Letter
ValueCountFrequency (%)
B 7
25.0%
E 3
10.7%
C 3
10.7%
K 2
 
7.1%
S 2
 
7.1%
A 2
 
7.1%
T 2
 
7.1%
M 2
 
7.1%
V 1
 
3.6%
U 1
 
3.6%
Other values (3) 3
10.7%
Decimal Number
ValueCountFrequency (%)
1 266
19.7%
2 183
13.5%
3 171
12.7%
0 156
11.5%
6 118
8.7%
4 114
8.4%
7 101
 
7.5%
5 96
 
7.1%
8 86
 
6.4%
9 60
 
4.4%
Other Punctuation
ValueCountFrequency (%)
, 254
99.2%
: 1
 
0.4%
& 1
 
0.4%
Close Punctuation
ValueCountFrequency (%)
) 244
99.6%
1
 
0.4%
Open Punctuation
ValueCountFrequency (%)
( 244
99.6%
1
 
0.4%
Space Separator
ValueCountFrequency (%)
1317
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%
Lowercase Letter
ValueCountFrequency (%)
c 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5129
59.7%
Common 3437
40.0%
Latin 30
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
331
 
6.5%
304
 
5.9%
301
 
5.9%
260
 
5.1%
245
 
4.8%
245
 
4.8%
239
 
4.7%
239
 
4.7%
237
 
4.6%
237
 
4.6%
Other values (189) 2491
48.6%
Common
ValueCountFrequency (%)
1317
38.3%
1 266
 
7.7%
, 254
 
7.4%
) 244
 
7.1%
( 244
 
7.1%
2 183
 
5.3%
3 171
 
5.0%
0 156
 
4.5%
6 118
 
3.4%
4 114
 
3.3%
Other values (9) 370
 
10.8%
Latin
ValueCountFrequency (%)
B 7
23.3%
E 3
10.0%
C 3
10.0%
c 2
 
6.7%
K 2
 
6.7%
S 2
 
6.7%
A 2
 
6.7%
T 2
 
6.7%
M 2
 
6.7%
V 1
 
3.3%
Other values (4) 4
13.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5129
59.7%
ASCII 3465
40.3%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1317
38.0%
1 266
 
7.7%
, 254
 
7.3%
) 244
 
7.0%
( 244
 
7.0%
2 183
 
5.3%
3 171
 
4.9%
0 156
 
4.5%
6 118
 
3.4%
4 114
 
3.3%
Other values (21) 398
 
11.5%
Hangul
ValueCountFrequency (%)
331
 
6.5%
304
 
5.9%
301
 
5.9%
260
 
5.1%
245
 
4.8%
245
 
4.8%
239
 
4.7%
239
 
4.7%
237
 
4.6%
237
 
4.6%
Other values (189) 2491
48.6%
None
ValueCountFrequency (%)
1
50.0%
1
50.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct78
Distinct (%)54.2%
Missing101
Missing (%)41.2%
Infinite0
Infinite (%)0.0%
Mean21206.653
Minimum7203
Maximum150979
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-05-11T15:10:30.654371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7203
5-th percentile7208.75
Q17237
median7272.5
Q37334.25
95-th percentile150623.2
Maximum150979
Range143776
Interquartile range (IQR)97.25

Descriptive statistics

Standard deviation42584.077
Coefficient of variation (CV)2.0080527
Kurtosis5.6286619
Mean21206.653
Median Absolute Deviation (MAD)50.5
Skewness2.7478255
Sum3053758
Variance1.8134036 × 109
MonotonicityNot monotonic
2024-05-11T15:10:30.891826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7222 7
 
2.9%
7237 7
 
2.9%
7250 6
 
2.4%
7333 6
 
2.4%
7345 5
 
2.0%
7238 5
 
2.0%
7299 5
 
2.0%
7251 4
 
1.6%
7223 3
 
1.2%
7366 3
 
1.2%
Other values (68) 93
38.0%
(Missing) 101
41.2%
ValueCountFrequency (%)
7203 1
 
0.4%
7205 1
 
0.4%
7206 3
1.2%
7207 2
 
0.8%
7208 1
 
0.4%
7213 2
 
0.8%
7214 3
1.2%
7217 2
 
0.8%
7220 3
1.2%
7222 7
2.9%
ValueCountFrequency (%)
150979 1
0.4%
150958 1
0.4%
150921 1
0.4%
150890 1
0.4%
150871 1
0.4%
150827 1
0.4%
150810 1
0.4%
150715 1
0.4%
150103 1
0.4%
150071 1
0.4%
Distinct243
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2024-05-11T15:10:31.272915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length15
Mean length8.3102041
Min length3

Characters and Unicode

Total characters2036
Distinct characters302
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique241 ?
Unique (%)98.4%

Sample

1st row(주)풍원관광여행사
2nd row(주)서울제주관광여행사
3rd row경원관광(주)
4th row(주)경성항공
5th row(주)엠브이피가족
ValueCountFrequency (%)
주식회사 27
 
9.4%
3
 
1.0%
tour 2
 
0.7%
굿모닝여행사 2
 
0.7%
신원여행사 2
 
0.7%
미래통일교육 1
 
0.3%
주)영등포하나여행사 1
 
0.3%
주)풍원관광여행사 1
 
0.3%
주)오렌지투어 1
 
0.3%
레일투어(주 1
 
0.3%
Other values (245) 245
85.7%
2024-05-11T15:10:31.796058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
188
 
9.2%
( 162
 
8.0%
) 162
 
8.0%
96
 
4.7%
78
 
3.8%
78
 
3.8%
63
 
3.1%
61
 
3.0%
49
 
2.4%
41
 
2.0%
Other values (292) 1058
52.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1628
80.0%
Open Punctuation 162
 
8.0%
Close Punctuation 162
 
8.0%
Space Separator 41
 
2.0%
Uppercase Letter 33
 
1.6%
Lowercase Letter 8
 
0.4%
Other Symbol 1
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
188
 
11.5%
96
 
5.9%
78
 
4.8%
78
 
4.8%
63
 
3.9%
61
 
3.7%
49
 
3.0%
35
 
2.1%
30
 
1.8%
28
 
1.7%
Other values (264) 922
56.6%
Uppercase Letter
ValueCountFrequency (%)
T 6
18.2%
K 3
9.1%
R 3
9.1%
J 2
 
6.1%
B 2
 
6.1%
L 2
 
6.1%
A 2
 
6.1%
S 2
 
6.1%
U 2
 
6.1%
O 2
 
6.1%
Other values (6) 7
21.2%
Lowercase Letter
ValueCountFrequency (%)
e 2
25.0%
i 1
12.5%
k 1
12.5%
r 1
12.5%
a 1
12.5%
v 1
12.5%
l 1
12.5%
Open Punctuation
ValueCountFrequency (%)
( 162
100.0%
Close Punctuation
ValueCountFrequency (%)
) 162
100.0%
Space Separator
ValueCountFrequency (%)
41
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1629
80.0%
Common 366
 
18.0%
Latin 41
 
2.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
188
 
11.5%
96
 
5.9%
78
 
4.8%
78
 
4.8%
63
 
3.9%
61
 
3.7%
49
 
3.0%
35
 
2.1%
30
 
1.8%
28
 
1.7%
Other values (265) 923
56.7%
Latin
ValueCountFrequency (%)
T 6
 
14.6%
K 3
 
7.3%
R 3
 
7.3%
J 2
 
4.9%
B 2
 
4.9%
e 2
 
4.9%
L 2
 
4.9%
A 2
 
4.9%
S 2
 
4.9%
U 2
 
4.9%
Other values (13) 15
36.6%
Common
ValueCountFrequency (%)
( 162
44.3%
) 162
44.3%
41
 
11.2%
& 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1628
80.0%
ASCII 407
 
20.0%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
188
 
11.5%
96
 
5.9%
78
 
4.8%
78
 
4.8%
63
 
3.9%
61
 
3.7%
49
 
3.0%
35
 
2.1%
30
 
1.8%
28
 
1.7%
Other values (264) 922
56.6%
ASCII
ValueCountFrequency (%)
( 162
39.8%
) 162
39.8%
41
 
10.1%
T 6
 
1.5%
K 3
 
0.7%
R 3
 
0.7%
J 2
 
0.5%
B 2
 
0.5%
e 2
 
0.5%
L 2
 
0.5%
Other values (17) 22
 
5.4%
None
ValueCountFrequency (%)
1
100.0%
Distinct226
Distinct (%)92.2%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
Minimum2003-04-18 15:28:10
Maximum2024-04-24 14:30:45
2024-05-11T15:10:32.032516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:10:32.282672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
I
157 
U
88 

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 157
64.1%
U 88
35.9%

Length

2024-05-11T15:10:32.569325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:10:32.813818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 157
64.1%
u 88
35.9%
Distinct72
Distinct (%)29.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 22:06:00
2024-05-11T15:10:33.002288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:10:33.237508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing245
Missing (%)100.0%
Memory size2.3 KiB

좌표정보(X)
Real number (ℝ)

Distinct178
Distinct (%)73.3%
Missing2
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean191923.6
Minimum189549.85
Maximum194632.53
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-05-11T15:10:33.443210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189549.85
5-th percentile190347.45
Q1190940.27
median191580.65
Q3192976.68
95-th percentile193861.27
Maximum194632.53
Range5082.6791
Interquartile range (IQR)2036.4106

Descriptive statistics

Standard deviation1238.1286
Coefficient of variation (CV)0.0064511536
Kurtosis-0.85927867
Mean191923.6
Median Absolute Deviation (MAD)851.13994
Skewness0.40631923
Sum46637434
Variance1532962.5
MonotonicityNot monotonic
2024-05-11T15:10:33.662362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
194561.746032498 5
 
2.0%
193469.554731741 5
 
2.0%
191292.095160096 3
 
1.2%
193057.414953819 3
 
1.2%
193099.563598351 3
 
1.2%
190729.506453391 3
 
1.2%
193282.654266684 3
 
1.2%
193500.284361195 3
 
1.2%
193657.203252183 3
 
1.2%
192931.446800396 3
 
1.2%
Other values (168) 209
85.3%
ValueCountFrequency (%)
189549.847307536 1
 
0.4%
189607.598899153 1
 
0.4%
189639.780967523 1
 
0.4%
189682.022243843 1
 
0.4%
189748.379334427 1
 
0.4%
189921.671894763 1
 
0.4%
189955.804848895 1
 
0.4%
189986.498936099 1
 
0.4%
190023.48828661 3
1.2%
190107.95828772 1
 
0.4%
ValueCountFrequency (%)
194632.526367463 2
 
0.8%
194561.746032498 5
2.0%
194530.535390096 2
 
0.8%
194272.90258815 1
 
0.4%
193882.109246282 1
 
0.4%
193870.812916718 1
 
0.4%
193861.272368256 2
 
0.8%
193844.169062846 2
 
0.8%
193818.18014 2
 
0.8%
193798.948251805 1
 
0.4%

좌표정보(Y)
Real number (ℝ)

Distinct178
Distinct (%)73.3%
Missing2
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean446565.83
Minimum442741.42
Maximum448699.97
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-05-11T15:10:33.864365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum442741.42
5-th percentile443583.54
Q1446272.78
median446660.82
Q3447360.84
95-th percentile448197.62
Maximum448699.97
Range5958.5504
Interquartile range (IQR)1088.0535

Descriptive statistics

Standard deviation1248.0317
Coefficient of variation (CV)0.0027947317
Kurtosis1.478246
Mean446565.83
Median Absolute Deviation (MAD)583.5265
Skewness-1.2442647
Sum1.085155 × 108
Variance1557583.1
MonotonicityNot monotonic
2024-05-11T15:10:34.446334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
446364.318286465 5
 
2.0%
446508.068667777 5
 
2.0%
447892.078672003 3
 
1.2%
447529.082521039 3
 
1.2%
447330.445753577 3
 
1.2%
446227.07504062 3
 
1.2%
447611.552045596 3
 
1.2%
446443.965496834 3
 
1.2%
446493.709452709 3
 
1.2%
447446.454692463 3
 
1.2%
Other values (168) 209
85.3%
ValueCountFrequency (%)
442741.422127303 1
0.4%
442782.832508026 1
0.4%
442854.148764609 1
0.4%
443117.005422211 1
0.4%
443234.638581265 1
0.4%
443267.656589478 1
0.4%
443275.178696938 1
0.4%
443329.954142576 1
0.4%
443358.765096733 1
0.4%
443444.22840271 1
0.4%
ValueCountFrequency (%)
448699.972523898 1
0.4%
448497.695424055 1
0.4%
448495.794800958 1
0.4%
448495.395437399 1
0.4%
448322.935192248 1
0.4%
448246.497733243 1
0.4%
448245.103226554 1
0.4%
448226.051690401 2
0.8%
448224.111919951 1
0.4%
448218.446478138 1
0.4%
Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
국내여행업
209 
<NA>
36 

Length

Max length5
Median length5
Mean length4.8530612
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
국내여행업 209
85.3%
<NA> 36
 
14.7%

Length

2024-05-11T15:10:34.702841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:10:34.862164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국내여행업 209
85.3%
na 36
 
14.7%
Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
135 
관광사업
110 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 135
55.1%
관광사업 110
44.9%

Length

2024-05-11T15:10:35.029721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:10:35.173354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 135
55.1%
관광사업 110
44.9%

지역구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
234 
상업지역
 
5
근린상업지역
 
3
일반상업지역
 
2
자연녹지지역
 
1

Length

Max length6
Median length4
Mean length4.0489796
Min length4

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 234
95.5%
상업지역 5
 
2.0%
근린상업지역 3
 
1.2%
일반상업지역 2
 
0.8%
자연녹지지역 1
 
0.4%

Length

2024-05-11T15:10:35.317622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:10:35.454669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 234
95.5%
상업지역 5
 
2.0%
근린상업지역 3
 
1.2%
일반상업지역 2
 
0.8%
자연녹지지역 1
 
0.4%

총층수
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)4.8%
Missing36
Missing (%)14.7%
Infinite0
Infinite (%)0.0%
Mean0.62200957
Minimum0
Maximum18
Zeros195
Zeros (%)79.6%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-05-11T15:10:35.570429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3.6
Maximum18
Range18
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.72024
Coefficient of variation (CV)4.3733089
Kurtosis23.958976
Mean0.62200957
Median Absolute Deviation (MAD)0
Skewness4.8653936
Sum130
Variance7.3997056
MonotonicityNot monotonic
2024-05-11T15:10:35.718563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 195
79.6%
4 2
 
0.8%
18 2
 
0.8%
3 2
 
0.8%
12 2
 
0.8%
10 2
 
0.8%
2 1
 
0.4%
13 1
 
0.4%
6 1
 
0.4%
15 1
 
0.4%
(Missing) 36
 
14.7%
ValueCountFrequency (%)
0 195
79.6%
2 1
 
0.4%
3 2
 
0.8%
4 2
 
0.8%
6 1
 
0.4%
10 2
 
0.8%
12 2
 
0.8%
13 1
 
0.4%
15 1
 
0.4%
18 2
 
0.8%
ValueCountFrequency (%)
18 2
 
0.8%
15 1
 
0.4%
13 1
 
0.4%
12 2
 
0.8%
10 2
 
0.8%
6 1
 
0.4%
4 2
 
0.8%
3 2
 
0.8%
2 1
 
0.4%
0 195
79.6%

주변환경명
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
232 
기타
 
12
주택가주변
 
1

Length

Max length5
Median length4
Mean length3.9061224
Min length2

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 232
94.7%
기타 12
 
4.9%
주택가주변 1
 
0.4%

Length

2024-05-11T15:10:35.882618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:10:36.006999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 232
94.7%
기타 12
 
4.9%
주택가주변 1
 
0.4%

제작취급품목내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing245
Missing (%)100.0%
Memory size2.3 KiB

보험기관명
Categorical

Distinct22
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
110 
서울보증보험주식회사
31 
서울보증보험
27 
한국관광협회중앙회
15 
한국관광협회중앙회 여행공제회
13 
Other values (17)
49 

Length

Max length22
Median length19
Mean length7.3591837
Min length4

Unique

Unique6 ?
Unique (%)2.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 110
44.9%
서울보증보험주식회사 31
 
12.7%
서울보증보험 27
 
11.0%
한국관광협회중앙회 15
 
6.1%
한국관광협회중앙회 여행공제회 13
 
5.3%
한국관광협회중앙회여행공제회 10
 
4.1%
한국관광협회중앙회 관광공제회 6
 
2.4%
서울특별시관광협회 6
 
2.4%
한국관광협회 6
 
2.4%
서울보증보험(주) 3
 
1.2%
Other values (12) 18
 
7.3%

Length

2024-05-11T15:10:36.151598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 110
41.0%
한국관광협회중앙회 34
 
12.7%
서울보증보험주식회사 31
 
11.6%
서울보증보험 29
 
10.8%
여행공제회 16
 
6.0%
한국관광협회중앙회여행공제회 10
 
3.7%
한국관광협회 7
 
2.6%
관광공제회 6
 
2.2%
서울특별시관광협회 6
 
2.2%
서울보증보험(주 3
 
1.1%
Other values (11) 16
 
6.0%

건물용도명
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
228 
근린생활시설
 
13
사무실
 
3
교육연구시설
 
1

Length

Max length6
Median length4
Mean length4.1020408
Min length3

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 228
93.1%
근린생활시설 13
 
5.3%
사무실 3
 
1.2%
교육연구시설 1
 
0.4%

Length

2024-05-11T15:10:36.343747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:10:36.478172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 228
93.1%
근린생활시설 13
 
5.3%
사무실 3
 
1.2%
교육연구시설 1
 
0.4%

지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)4.3%
Missing36
Missing (%)14.7%
Infinite0
Infinite (%)0.0%
Mean0.54545455
Minimum0
Maximum14
Zeros192
Zeros (%)78.4%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-05-11T15:10:36.609332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum14
Range14
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.1681902
Coefficient of variation (CV)3.9750155
Kurtosis20.585172
Mean0.54545455
Median Absolute Deviation (MAD)0
Skewness4.4937524
Sum114
Variance4.701049
MonotonicityNot monotonic
2024-05-11T15:10:36.775827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 192
78.4%
3 4
 
1.6%
2 3
 
1.2%
8 3
 
1.2%
14 2
 
0.8%
9 2
 
0.8%
10 1
 
0.4%
5 1
 
0.4%
11 1
 
0.4%
(Missing) 36
 
14.7%
ValueCountFrequency (%)
0 192
78.4%
2 3
 
1.2%
3 4
 
1.6%
5 1
 
0.4%
8 3
 
1.2%
9 2
 
0.8%
10 1
 
0.4%
11 1
 
0.4%
14 2
 
0.8%
ValueCountFrequency (%)
14 2
 
0.8%
11 1
 
0.4%
10 1
 
0.4%
9 2
 
0.8%
8 3
 
1.2%
5 1
 
0.4%
3 4
 
1.6%
2 3
 
1.2%
0 192
78.4%

지하층수
Categorical

IMBALANCE 

Distinct6
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
0
198 
<NA>
36 
1
 
3
4
 
3
3
 
3

Length

Max length4
Median length1
Mean length1.4408163
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row1

Common Values

ValueCountFrequency (%)
0 198
80.8%
<NA> 36
 
14.7%
1 3
 
1.2%
4 3
 
1.2%
3 3
 
1.2%
2 2
 
0.8%

Length

2024-05-11T15:10:36.948868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:10:37.092132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 198
80.8%
na 36
 
14.7%
1 3
 
1.2%
4 3
 
1.2%
3 3
 
1.2%
2 2
 
0.8%

객실수
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
0
209 
<NA>
36 

Length

Max length4
Median length1
Mean length1.4408163
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 209
85.3%
<NA> 36
 
14.7%

Length

2024-05-11T15:10:37.258652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:10:37.385389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 209
85.3%
na 36
 
14.7%

건축연면적
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
0
209 
<NA>
36 

Length

Max length4
Median length1
Mean length1.4408163
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 209
85.3%
<NA> 36
 
14.7%

Length

2024-05-11T15:10:37.513521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:10:37.630191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 209
85.3%
na 36
 
14.7%

영문상호명
Text

MISSING 

Distinct9
Distinct (%)100.0%
Missing236
Missing (%)96.3%
Memory size2.0 KiB
2024-05-11T15:10:37.825162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length14
Mean length15.222222
Min length3

Characters and Unicode

Total characters137
Distinct characters38
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)100.0%

Sample

1st rowTOURMART.COM
2nd rowREIM CO., LTD.
3rd rowHiWin - CORP.
4th rowLink and Leave Co.,Ltd.
5th rowGUIDECOOP
ValueCountFrequency (%)
co.,ltd 3
 
13.0%
tour 2
 
8.7%
reim 1
 
4.3%
hyundai 1
 
4.3%
kti 1
 
4.3%
star 1
 
4.3%
small 1
 
4.3%
cashback 1
 
4.3%
korea 1
 
4.3%
guidecoop 1
 
4.3%
Other values (10) 10
43.5%
2024-05-11T15:10:38.249442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
14
 
10.2%
. 9
 
6.6%
O 9
 
6.6%
L 8
 
5.8%
C 8
 
5.8%
T 7
 
5.1%
R 7
 
5.1%
a 5
 
3.6%
U 5
 
3.6%
A 4
 
2.9%
Other values (28) 61
44.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 76
55.5%
Lowercase Letter 33
24.1%
Space Separator 14
 
10.2%
Other Punctuation 13
 
9.5%
Dash Punctuation 1
 
0.7%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
O 9
11.8%
L 8
10.5%
C 8
10.5%
T 7
9.2%
R 7
9.2%
U 5
 
6.6%
A 4
 
5.3%
I 4
 
5.3%
M 4
 
5.3%
D 3
 
3.9%
Other values (10) 17
22.4%
Lowercase Letter
ValueCountFrequency (%)
a 5
15.2%
d 4
12.1%
o 4
12.1%
n 3
9.1%
t 3
9.1%
i 3
9.1%
e 3
9.1%
k 2
 
6.1%
v 1
 
3.0%
r 1
 
3.0%
Other values (4) 4
12.1%
Other Punctuation
ValueCountFrequency (%)
. 9
69.2%
, 4
30.8%
Space Separator
ValueCountFrequency (%)
14
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 109
79.6%
Common 28
 
20.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
O 9
 
8.3%
L 8
 
7.3%
C 8
 
7.3%
T 7
 
6.4%
R 7
 
6.4%
a 5
 
4.6%
U 5
 
4.6%
A 4
 
3.7%
d 4
 
3.7%
I 4
 
3.7%
Other values (24) 48
44.0%
Common
ValueCountFrequency (%)
14
50.0%
. 9
32.1%
, 4
 
14.3%
- 1
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 137
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
14
 
10.2%
. 9
 
6.6%
O 9
 
6.6%
L 8
 
5.8%
C 8
 
5.8%
T 7
 
5.1%
R 7
 
5.1%
a 5
 
3.6%
U 5
 
3.6%
A 4
 
2.9%
Other values (28) 61
44.5%

영문상호주소
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
236 
DOMESTIC TRAVEL BUSINESS
 
8
DOMESTIC TRAVEL BUISNESS
 
1

Length

Max length24
Median length4
Mean length4.7346939
Min length4

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 236
96.3%
DOMESTIC TRAVEL BUSINESS 8
 
3.3%
DOMESTIC TRAVEL BUISNESS 1
 
0.4%

Length

2024-05-11T15:10:38.483551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:10:38.657565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 236
89.7%
domestic 9
 
3.4%
travel 9
 
3.4%
business 8
 
3.0%
buisness 1
 
0.4%

선박총톤수
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
0
209 
<NA>
36 

Length

Max length4
Median length1
Mean length1.4408163
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 209
85.3%
<NA> 36
 
14.7%

Length

2024-05-11T15:10:38.791893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:10:38.920081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 209
85.3%
na 36
 
14.7%

선박척수
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
0
209 
<NA>
36 

Length

Max length4
Median length1
Mean length1.4408163
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 209
85.3%
<NA> 36
 
14.7%

Length

2024-05-11T15:10:39.081513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:10:39.204680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 209
85.3%
na 36
 
14.7%

선박제원
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing245
Missing (%)100.0%
Memory size2.3 KiB

무대면적
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
0
209 
<NA>
36 

Length

Max length4
Median length1
Mean length1.4408163
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 209
85.3%
<NA> 36
 
14.7%

Length

2024-05-11T15:10:39.361019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:10:39.510907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 209
85.3%
na 36
 
14.7%

좌석수
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
0
209 
<NA>
36 

Length

Max length4
Median length1
Mean length1.4408163
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 209
85.3%
<NA> 36
 
14.7%

Length

2024-05-11T15:10:39.698640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:10:39.836760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 209
85.3%
na 36
 
14.7%

기념품종류
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing245
Missing (%)100.0%
Memory size2.3 KiB
Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
0
209 
<NA>
36 

Length

Max length4
Median length1
Mean length1.4408163
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 209
85.3%
<NA> 36
 
14.7%

Length

2024-05-11T15:10:39.964180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:10:40.120828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 209
85.3%
na 36
 
14.7%

시설면적
Real number (ℝ)

MISSING  ZEROS 

Distinct18
Distinct (%)8.6%
Missing36
Missing (%)14.7%
Infinite0
Infinite (%)0.0%
Mean540.51048
Minimum0
Maximum75268
Zeros191
Zeros (%)78.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-05-11T15:10:40.241396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile36.784
Maximum75268
Range75268
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5540.654
Coefficient of variation (CV)10.25078
Kurtosis163.28786
Mean540.51048
Median Absolute Deviation (MAD)0
Skewness12.444463
Sum112966.69
Variance30698847
MonotonicityNot monotonic
2024-05-11T15:10:40.378972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0.0 191
78.0%
4975.09 2
 
0.8%
151.44 1
 
0.4%
40.0 1
 
0.4%
49.0 1
 
0.4%
2.0 1
 
0.4%
14.2 1
 
0.4%
41.4 1
 
0.4%
31.96 1
 
0.4%
84.3 1
 
0.4%
Other values (8) 8
 
3.3%
(Missing) 36
 
14.7%
ValueCountFrequency (%)
0.0 191
78.0%
2.0 1
 
0.4%
3.3 1
 
0.4%
14.2 1
 
0.4%
23.01 1
 
0.4%
28.5 1
 
0.4%
29.7 1
 
0.4%
31.96 1
 
0.4%
40.0 1
 
0.4%
41.0 1
 
0.4%
ValueCountFrequency (%)
75268.0 1
0.4%
27047.7 1
0.4%
4975.09 2
0.8%
161.0 1
0.4%
151.44 1
0.4%
84.3 1
0.4%
49.0 1
0.4%
41.4 1
0.4%
41.0 1
0.4%
40.0 1
0.4%

놀이기구수내역
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing245
Missing (%)100.0%
Memory size2.3 KiB

놀이시설수
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
0
209 
<NA>
36 

Length

Max length4
Median length1
Mean length1.4408163
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 209
85.3%
<NA> 36
 
14.7%

Length

2024-05-11T15:10:40.574905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:10:40.704441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 209
85.3%
na 36
 
14.7%

방송시설유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing245
Missing (%)100.0%
Memory size2.3 KiB

발전시설유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing245
Missing (%)100.0%
Memory size2.3 KiB

의무실유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing245
Missing (%)100.0%
Memory size2.3 KiB

안내소유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing245
Missing (%)100.0%
Memory size2.3 KiB

기획여행보험시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing245
Missing (%)100.0%
Memory size2.3 KiB

기획여행보험종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing245
Missing (%)100.0%
Memory size2.3 KiB

자본금
Real number (ℝ)

MISSING  ZEROS 

Distinct31
Distinct (%)14.8%
Missing36
Missing (%)14.7%
Infinite0
Infinite (%)0.0%
Mean1.9926216 × 108
Minimum0
Maximum3 × 1010
Zeros74
Zeros (%)30.2%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-05-11T15:10:40.837131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median30000000
Q360000000
95-th percentile1.56 × 108
Maximum3 × 1010
Range3 × 1010
Interquartile range (IQR)60000000

Descriptive statistics

Standard deviation2.0738016 × 109
Coefficient of variation (CV)10.407403
Kurtosis207.96703
Mean1.9926216 × 108
Median Absolute Deviation (MAD)30000000
Skewness14.404361
Sum4.1645791 × 1010
Variance4.3006529 × 1018
MonotonicityNot monotonic
2024-05-11T15:10:41.024169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 74
30.2%
30000000 38
15.5%
50000000 29
 
11.8%
150000000 22
 
9.0%
100000000 11
 
4.5%
200000000 4
 
1.6%
300000000 3
 
1.2%
45000000 3
 
1.2%
15000000 2
 
0.8%
90000000 2
 
0.8%
Other values (21) 21
 
8.6%
(Missing) 36
14.7%
ValueCountFrequency (%)
0 74
30.2%
5000000 1
 
0.4%
10000000 1
 
0.4%
15000000 2
 
0.8%
16247671 1
 
0.4%
20000000 1
 
0.4%
20370617 1
 
0.4%
25000000 1
 
0.4%
30000000 38
15.5%
45000000 3
 
1.2%
ValueCountFrequency (%)
30000000000 1
 
0.4%
1225000000 1
 
0.4%
300000000 3
 
1.2%
250000000 1
 
0.4%
200000000 4
 
1.6%
160000000 1
 
0.4%
150000000 22
9.0%
140000000 1
 
0.4%
121000000 1
 
0.4%
100000000 11
4.5%

보험시작일자
Real number (ℝ)

MISSING 

Distinct135
Distinct (%)98.5%
Missing108
Missing (%)44.1%
Infinite0
Infinite (%)0.0%
Mean20144967
Minimum20021119
Maximum20211012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-05-11T15:10:41.219561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20021119
5-th percentile20061121
Q120110219
median20140723
Q320200314
95-th percentile20210407
Maximum20211012
Range189893
Interquartile range (IQR)90095

Descriptive statistics

Standard deviation48711.944
Coefficient of variation (CV)0.0024180702
Kurtosis-0.80090745
Mean20144967
Median Absolute Deviation (MAD)40304
Skewness-0.30342827
Sum2.7598604 × 109
Variance2.3728535 × 109
MonotonicityNot monotonic
2024-05-11T15:10:41.472626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20201005 2
 
0.8%
20140723 2
 
0.8%
20160808 1
 
0.4%
20131019 1
 
0.4%
20140526 1
 
0.4%
20140618 1
 
0.4%
20200702 1
 
0.4%
20150805 1
 
0.4%
20120702 1
 
0.4%
20170619 1
 
0.4%
Other values (125) 125
51.0%
(Missing) 108
44.1%
ValueCountFrequency (%)
20021119 1
0.4%
20030202 1
0.4%
20030514 1
0.4%
20060221 1
0.4%
20060224 1
0.4%
20060623 1
0.4%
20060701 1
0.4%
20061226 1
0.4%
20070308 1
0.4%
20070328 1
0.4%
ValueCountFrequency (%)
20211012 1
0.4%
20210927 1
0.4%
20210721 1
0.4%
20210712 1
0.4%
20210704 1
0.4%
20210625 1
0.4%
20210412 1
0.4%
20210406 1
0.4%
20210309 1
0.4%
20210304 1
0.4%

보험종료일자
Real number (ℝ)

MISSING 

Distinct135
Distinct (%)98.5%
Missing108
Missing (%)44.1%
Infinite0
Infinite (%)0.0%
Mean20155255
Minimum20031119
Maximum20221012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-05-11T15:10:41.691183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20031119
5-th percentile20071121
Q120120218
median20150722
Q320210313
95-th percentile20220406
Maximum20221012
Range189893
Interquartile range (IQR)90095

Descriptive statistics

Standard deviation48772.503
Coefficient of variation (CV)0.0024198405
Kurtosis-0.80783871
Mean20155255
Median Absolute Deviation (MAD)40303
Skewness-0.30602621
Sum2.7612699 × 109
Variance2.378757 × 109
MonotonicityNot monotonic
2024-05-11T15:10:41.986707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20220121 2
 
0.8%
20211204 2
 
0.8%
20160805 1
 
0.4%
20141018 1
 
0.4%
20150525 1
 
0.4%
20150618 1
 
0.4%
20210702 1
 
0.4%
20150723 1
 
0.4%
20170807 1
 
0.4%
20150516 1
 
0.4%
Other values (125) 125
51.0%
(Missing) 108
44.1%
ValueCountFrequency (%)
20031119 1
0.4%
20040202 1
0.4%
20040514 1
0.4%
20070221 1
0.4%
20070224 1
0.4%
20070622 1
0.4%
20070701 1
0.4%
20071226 1
0.4%
20080307 1
0.4%
20080328 1
0.4%
ValueCountFrequency (%)
20221012 1
0.4%
20220926 1
0.4%
20220720 1
0.4%
20220711 1
0.4%
20220703 1
0.4%
20220624 1
0.4%
20220412 1
0.4%
20220405 1
0.4%
20220308 1
0.4%
20220303 1
0.4%

부대시설내역
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing245
Missing (%)100.0%
Memory size2.3 KiB

시설규모
Real number (ℝ)

MISSING  ZEROS 

Distinct17
Distinct (%)8.1%
Missing36
Missing (%)14.7%
Infinite0
Infinite (%)0.0%
Mean540.50718
Minimum0
Maximum75268
Zeros191
Zeros (%)78.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-05-11T15:10:42.207052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile36.8
Maximum75268
Range75268
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5540.6605
Coefficient of variation (CV)10.250855
Kurtosis163.28723
Mean540.50718
Median Absolute Deviation (MAD)0
Skewness12.444439
Sum112966
Variance30698919
MonotonicityNot monotonic
2024-05-11T15:10:42.410069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 191
78.0%
4975 2
 
0.8%
41 2
 
0.8%
75268 1
 
0.4%
30 1
 
0.4%
29 1
 
0.4%
23 1
 
0.4%
161 1
 
0.4%
27048 1
 
0.4%
84 1
 
0.4%
Other values (7) 7
 
2.9%
(Missing) 36
 
14.7%
ValueCountFrequency (%)
0 191
78.0%
2 1
 
0.4%
3 1
 
0.4%
14 1
 
0.4%
23 1
 
0.4%
29 1
 
0.4%
30 1
 
0.4%
32 1
 
0.4%
40 1
 
0.4%
41 2
 
0.8%
ValueCountFrequency (%)
75268 1
0.4%
27048 1
0.4%
4975 2
0.8%
161 1
0.4%
151 1
0.4%
84 1
0.4%
49 1
0.4%
41 2
0.8%
40 1
0.4%
32 1
0.4%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명문화사업자구분명지역구분명총층수주변환경명제작취급품목내용보험기관명건물용도명지상층수지하층수객실수건축연면적영문상호명영문상호주소선박총톤수선박척수선박제원무대면적좌석수기념품종류회의실별동시수용인원시설면적놀이기구수내역놀이시설수방송시설유무발전시설유무의무실유무안내소유무기획여행보험시작일자기획여행보험종료일자자본금보험시작일자보험종료일자부대시설내역시설규모
03180000CDFI226001198300000119831006<NA>3폐업3폐업20000208<NA><NA><NA>823-6774<NA>150045서울특별시 영등포구 당산동5가 11-33번지서울특별시 영등포구 당산로 222 (당산동5가)<NA>(주)풍원관광여행사2003-04-18 15:28:39I2018-08-31 23:59:59.0<NA>191292.09516447892.078672국내여행업관광사업<NA>0<NA><NA><NA><NA>0000<NA><NA>00<NA>00<NA>00.0<NA>0<NA><NA><NA><NA><NA><NA>0<NA><NA><NA>0
13180000CDFI226001198700000119870720<NA>4취소/말소/만료/정지/중지30허가취소<NA><NA><NA><NA>785-0111<NA>150890서울특별시 영등포구 여의도동 44-26번지서울특별시 영등포구 국제금융로8길 19 (여의도동)150890(주)서울제주관광여행사2011-10-30 16:19:19I2018-08-31 23:59:59.0<NA>193657.203252446493.709453국내여행업관광사업<NA>0<NA><NA><NA><NA>0000<NA><NA>00<NA>00<NA>00.0<NA>0<NA><NA><NA><NA><NA><NA>0<NA><NA><NA>0
23180000CDFI226001198900000119891108<NA>3폐업3폐업20040325<NA><NA><NA>831-1235<NA>150814서울특별시 영등포구 대림동 700-1번지서울특별시 영등포구 대림로 154 (대림동)<NA>경원관광(주)2004-03-25 17:20:16I2018-08-31 23:59:59.0<NA>191124.182012443626.294389국내여행업관광사업<NA>0<NA><NA><NA><NA>0000<NA><NA>00<NA>00<NA>00.0<NA>0<NA><NA><NA><NA><NA><NA>0<NA><NA><NA>0
33180000CDFI226001198900000219891222<NA>4취소/말소/만료/정지/중지30허가취소<NA><NA><NA><NA>783-7772<NA>150741서울특별시 영등포구 여의도동 44-26번지 중앙빌딩 101동서울특별시 영등포구 국제금융로8길 19, 101동 (여의도동,중앙빌딩)<NA>(주)경성항공2003-07-18 10:16:25I2018-08-31 23:59:59.0<NA>193657.203252446493.709453국내여행업관광사업<NA>0<NA><NA><NA><NA>0000<NA><NA>00<NA>00<NA>00.0<NA>0<NA><NA><NA><NA><NA><NA>0<NA><NA><NA>0
43180000CDFI226001198900000319890714<NA>3폐업3폐업20141231<NA><NA><NA>02-848-0674<NA>150850서울특별시 영등포구 신길동 425-7번지서울특별시 영등포구 신길로 79-2 (신길동)<NA>(주)엠브이피가족2014-12-30 17:21:36I2018-08-31 23:59:59.0<NA>191827.035483444191.877633국내여행업관광사업상업지역4<NA><NA>서울보증보험근린생활시설3100<NA><NA>00<NA>00<NA>00.0<NA>0<NA><NA><NA><NA><NA><NA>02009071920100718<NA>0
53180000CDFI226001199100000219910621<NA>3폐업3폐업20040616<NA><NA><NA>02-2677-0030<NA>150033서울특별시 영등포구 영등포동3가 10-15번지서울특별시 영등포구 영중로2길 1 (영등포동3가)<NA>(주)크라운항공2004-06-16 17:55:30I2018-08-31 23:59:59.0<NA>191692.056398446077.290265국내여행업관광사업<NA>0<NA><NA>한국관광협회중앙회-서울특별시관광협회<NA>0000<NA><NA>00<NA>00<NA>00.0<NA>0<NA><NA><NA><NA><NA><NA>02003020220040202<NA>0
63180000CDFI226001199200000119920716<NA>3폐업3폐업19990305<NA><NA><NA>2633-5087<NA>150035서울특별시 영등포구 영등포동5가 25-10번지 2,4층서울특별시 영등포구 영중로 46 (영등포동5가,2,4층)<NA>(주)동광여행사2003-04-18 15:28:39I2018-08-31 23:59:59.0<NA>191549.094754446464.05883국내여행업관광사업<NA>0<NA><NA><NA><NA>0000<NA><NA>00<NA>00<NA>00.0<NA>0<NA><NA><NA><NA><NA><NA>0<NA><NA><NA>0
73180000CDFI226001199200000219921021<NA>3폐업3폐업20000603<NA><NA><NA>445-5035<NA>150102서울특별시 영등포구 양평동2가 37-2번지서울특별시 영등포구 영등포로 21 (양평동2가)<NA>(주)유한관광2003-04-18 15:28:39I2018-08-31 23:59:59.0<NA>189682.022244446823.857632국내여행업관광사업<NA>0<NA><NA><NA><NA>0000<NA><NA>00<NA>00<NA>00.0<NA>0<NA><NA><NA><NA><NA><NA>0<NA><NA><NA>0
83180000CDFI226001199200000319920516<NA>3폐업3폐업19990417<NA><NA><NA>780-7848<NA>150874서울특별시 영등포구 여의도동 17-16번지 대성빌딩 601서울특별시 영등포구 국회대로62길 11 (여의도동,대성빌딩 601)<NA>(주)국제써머투어2003-04-18 15:28:10I2018-08-31 23:59:59.0<NA>192562.603704447240.55433국내여행업관광사업<NA>0<NA><NA><NA><NA>0000<NA><NA>00<NA>00<NA>00.0<NA>0<NA><NA><NA><NA><NA><NA>0<NA><NA><NA>0
93180000CDFI226001199400000119940909<NA>3폐업3폐업20010411<NA><NA><NA>842-9000<NA>150825서울특별시 영등포구 대림동 1053-12번지 (2층)서울특별시 영등포구 도림천로 367 (대림동,(2층))<NA>(주)월드중부관광2003-04-18 15:28:39I2018-08-31 23:59:59.0<NA>190735.692079443329.954143국내여행업관광사업<NA>0<NA><NA><NA><NA>0000<NA><NA>00<NA>00<NA>00.0<NA>0<NA><NA><NA><NA><NA><NA>0<NA><NA><NA>0
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명문화사업자구분명지역구분명총층수주변환경명제작취급품목내용보험기관명건물용도명지상층수지하층수객실수건축연면적영문상호명영문상호주소선박총톤수선박척수선박제원무대면적좌석수기념품종류회의실별동시수용인원시설면적놀이기구수내역놀이시설수방송시설유무발전시설유무의무실유무안내소유무기획여행보험시작일자기획여행보험종료일자자본금보험시작일자보험종료일자부대시설내역시설규모
2353180000CDFI226001202100000920211126<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 당산동4가 32-90 202호서울특별시 영등포구 당산로38길 14, 202호 (당산동4가)7220신세계크루즈투어2022-05-06 16:49:38U2021-12-05 00:08:00.0<NA>191061.992687447371.360635<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2363180000CDFI22600120210000102021-12-30<NA>1영업/정상13영업중<NA><NA><NA><NA>1661-8331<NA><NA>서울특별시 영등포구 당산동6가 314 당일빌딩서울특별시 영등포구 당산로47길 8, 당일빌딩 5층 제1호 (당산동6가)7222주식회사 영일레븐2023-03-08 17:18:29U2022-12-02 23:00:00.0<NA>191270.640016448081.07828<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2373180000CDFI22600120220000012022-01-28<NA>3폐업3폐업2023-04-10<NA><NA><NA>070-4776-1611<NA><NA>서울특별시 영등포구 여의도동 61-3 라이프오피스텔 324호서울특별시 영등포구 63로 40, 라이프오피스텔 324호 (여의도동)7345주식회사 다보2023-04-11 16:24:59U2022-12-03 23:03:00.0<NA>194561.746032446364.318286<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2383180000CDFI22600120220000022018-04-25<NA>3폐업3폐업2023-04-04<NA><NA><NA>02-2658-8883<NA><NA>서울특별시 영등포구 영등포동8가 62-1 롯데마트서울특별시 영등포구 영중로 125, 롯데마트 1층 (영등포동8가)7228(주)윤투어2023-04-04 18:33:17U2022-12-04 00:06:00.0<NA>191503.386112447289.548355<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2393180000CDFI22600120220000032022-04-29<NA>1영업/정상13영업중<NA><NA><NA><NA>02-2671-8818<NA><NA>서울특별시 영등포구 신길동 734서울특별시 영등포구 가마산로 580, B2호 (신길동)7391우은 컴퍼니2023-05-31 17:14:47U2022-12-06 00:02:00.0<NA>192916.320127444641.379532<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2403180000CDFI226001202200000420220726<NA>1영업/정상13영업중<NA><NA><NA><NA>02-851-8975<NA><NA>서울특별시 영등포구 대림동 1047-11 대길타운서울특별시 영등포구 도림천로11길 29, 대길타운 (대림동)7419코리안여행사2022-07-26 10:20:29I2021-12-06 22:08:00.0<NA>190940.505761443358.765097<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2413180000CDFI226001202200000520211231<NA>1영업/정상13영업중<NA><NA><NA><NA>02-6598-1259<NA><NA>서울특별시 영등포구 여의도동 23-6 오투타워서울특별시 영등포구 의사당대로 83, 오투타워 8층 (여의도동)7325주식회사 해피투씨유2022-08-23 11:19:00I2021-12-07 22:05:00.0<NA>193165.490137446797.341447<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2423180000CDFI226001202200000620221212<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 대림동 1057-7서울특별시 영등포구 도림천로11길 18 (대림동)7420대한우리여행사2022-12-12 11:56:03I2021-11-01 23:04:00.0<NA>190872.077054443267.656589<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2433180000CDFI22600120230000012023-05-22<NA>5제외/삭제/전출15전출2023-09-08<NA><NA><NA>02-6332-0308<NA><NA>서울특별시 영등포구 양평동5가 62 파크호텔서울특별시 영등포구 양평로 136, 308호 (양평동5가)7205주식회사 웨이비코퍼레이션2023-09-08 17:20:43U2022-12-08 23:00:00.0<NA>190476.526523448495.794801<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2443180000CDFI22600120240000012021-08-18<NA>1영업/정상13영업중<NA><NA><NA><NA>02-569-6333<NA><NA>서울특별시 영등포구 당산동1가 459 생각공장 당산서울특별시 영등포구 영등포로 150, 생각공장 당산 C동 306호 (당산동1가)7292(주)팀즈코리아2024-02-05 16:42:23I2023-12-02 00:07:00.0<NA>190940.034564446461.996<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>