Overview

Dataset statistics

Number of variables60
Number of observations529
Missing cells10708
Missing cells (%)33.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory267.7 KiB
Average record size in memory518.2 B

Variable types

Categorical23
Text9
DateTime4
Numeric12
Unsupported12

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-17595/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 is highly imbalanced (90.2%)Imbalance
주변환경명 is highly imbalanced (85.4%)Imbalance
건물용도명 is highly imbalanced (86.7%)Imbalance
지하층수 is highly imbalanced (59.1%)Imbalance
영문상호주소 is highly imbalanced (87.9%)Imbalance
기획여행보험시작일자 is highly imbalanced (97.5%)Imbalance
기획여행보험종료일자 is highly imbalanced (97.5%)Imbalance
폐업일자 has 278 (52.6%) missing valuesMissing
휴업시작일자 has 523 (98.9%) missing valuesMissing
휴업종료일자 has 523 (98.9%) missing valuesMissing
재개업일자 has 529 (100.0%) missing valuesMissing
전화번호 has 153 (28.9%) missing valuesMissing
소재지면적 has 529 (100.0%) missing valuesMissing
소재지우편번호 has 291 (55.0%) missing valuesMissing
도로명주소 has 10 (1.9%) missing valuesMissing
도로명우편번호 has 148 (28.0%) missing valuesMissing
업태구분명 has 529 (100.0%) missing valuesMissing
지역구분명 has 521 (98.5%) missing valuesMissing
총층수 has 171 (32.3%) missing valuesMissing
제작취급품목내용 has 529 (100.0%) missing valuesMissing
지상층수 has 171 (32.3%) missing valuesMissing
영문상호명 has 512 (96.8%) missing valuesMissing
선박제원 has 529 (100.0%) missing valuesMissing
기념품종류 has 529 (100.0%) missing valuesMissing
시설면적 has 171 (32.3%) missing valuesMissing
놀이기구수내역 has 529 (100.0%) missing valuesMissing
방송시설유무 has 529 (100.0%) missing valuesMissing
발전시설유무 has 529 (100.0%) missing valuesMissing
의무실유무 has 529 (100.0%) missing valuesMissing
안내소유무 has 529 (100.0%) missing valuesMissing
자본금 has 171 (32.3%) missing valuesMissing
보험시작일자 has 268 (50.7%) missing valuesMissing
보험종료일자 has 268 (50.7%) missing valuesMissing
부대시설내역 has 529 (100.0%) missing valuesMissing
시설규모 has 171 (32.3%) 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
부대시설내역 is an unsupported type, check if it needs cleaning or further analysisUnsupported
총층수 has 347 (65.6%) zerosZeros
지상층수 has 346 (65.4%) zerosZeros
시설면적 has 314 (59.4%) zerosZeros
자본금 has 88 (16.6%) zerosZeros
시설규모 has 314 (59.4%) zerosZeros

Reproduction

Analysis started2024-04-29 19:21:56.161699
Analysis finished2024-04-29 19:21:57.418005
Duration1.26 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
3180000
529 

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 529
100.0%

Length

2024-04-30T04:21:57.493102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:21:57.582556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3180000 529
100.0%

관리번호
Text

UNIQUE 

Distinct529
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2024-04-30T04:21:57.742230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters10580
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

Unique529 ?
Unique (%)100.0%

Sample

1st rowCDFI2260021988000001
2nd rowCDFI2260021990000001
3rd rowCDFI2260021990000002
4th rowCDFI2260021990000003
5th rowCDFI2260021991000001
ValueCountFrequency (%)
cdfi2260021988000001 1
 
0.2%
cdfi2260022015000025 1
 
0.2%
cdfi2260022016000009 1
 
0.2%
cdfi2260022016000008 1
 
0.2%
cdfi2260022016000007 1
 
0.2%
cdfi2260022016000006 1
 
0.2%
cdfi2260022016000004 1
 
0.2%
cdfi2260022016000003 1
 
0.2%
cdfi2260022015000036 1
 
0.2%
cdfi2260022015000035 1
 
0.2%
Other values (519) 519
98.1%
2024-04-30T04:21:58.013766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4076
38.5%
2 2415
22.8%
6 624
 
5.9%
1 589
 
5.6%
C 529
 
5.0%
D 529
 
5.0%
F 529
 
5.0%
I 529
 
5.0%
3 185
 
1.7%
9 175
 
1.7%
Other values (4) 400
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8464
80.0%
Uppercase Letter 2116
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4076
48.2%
2 2415
28.5%
6 624
 
7.4%
1 589
 
7.0%
3 185
 
2.2%
9 175
 
2.1%
4 120
 
1.4%
5 97
 
1.1%
7 97
 
1.1%
8 86
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
C 529
25.0%
D 529
25.0%
F 529
25.0%
I 529
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8464
80.0%
Latin 2116
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4076
48.2%
2 2415
28.5%
6 624
 
7.4%
1 589
 
7.0%
3 185
 
2.2%
9 175
 
2.1%
4 120
 
1.4%
5 97
 
1.1%
7 97
 
1.1%
8 86
 
1.0%
Latin
ValueCountFrequency (%)
C 529
25.0%
D 529
25.0%
F 529
25.0%
I 529
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10580
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4076
38.5%
2 2415
22.8%
6 624
 
5.9%
1 589
 
5.6%
C 529
 
5.0%
D 529
 
5.0%
F 529
 
5.0%
I 529
 
5.0%
3 185
 
1.7%
9 175
 
1.7%
Other values (4) 400
 
3.8%
Distinct485
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
Minimum1984-06-11 00:00:00
Maximum2024-02-23 00:00:00
2024-04-30T04:21:58.136974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:21:58.255582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
<NA>
515 
20121210
 
12
20140310
 
1
20190710
 
1

Length

Max length8
Median length4
Mean length4.1058601
Min length4

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 515
97.4%
20121210 12
 
2.3%
20140310 1
 
0.2%
20190710 1
 
0.2%

Length

2024-04-30T04:21:58.369759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:21:58.466773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 515
97.4%
20121210 12
 
2.3%
20140310 1
 
0.2%
20190710 1
 
0.2%
Distinct5
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
1
231 
3
223 
4
41 
5
28 
2
 
6

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 231
43.7%
3 223
42.2%
4 41
 
7.8%
5 28
 
5.3%
2 6
 
1.1%

Length

2024-04-30T04:21:58.579806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:21:58.677549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 231
43.7%
3 223
42.2%
4 41
 
7.8%
5 28
 
5.3%
2 6
 
1.1%

영업상태명
Categorical

Distinct5
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
영업/정상
231 
폐업
223 
취소/말소/만료/정지/중지
41 
제외/삭제/전출
28 
휴업
 
6

Length

Max length14
Median length8
Mean length4.557656
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 231
43.7%
폐업 223
42.2%
취소/말소/만료/정지/중지 41
 
7.8%
제외/삭제/전출 28
 
5.3%
휴업 6
 
1.1%

Length

2024-04-30T04:21:58.772316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:21:58.875856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 231
43.7%
폐업 223
42.2%
취소/말소/만료/정지/중지 41
 
7.8%
제외/삭제/전출 28
 
5.3%
휴업 6
 
1.1%

상세영업상태코드
Real number (ℝ)

Distinct7
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.130435
Minimum2
Maximum35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.8 KiB
2024-04-30T04:21:58.970308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3
Q13
median13
Q313
95-th percentile30
Maximum35
Range33
Interquartile range (IQR)10

Descriptive statistics

Standard deviation7.7295674
Coefficient of variation (CV)0.76300451
Kurtosis1.2681228
Mean10.130435
Median Absolute Deviation (MAD)10
Skewness1.1526488
Sum5359
Variance59.746212
MonotonicityNot monotonic
2024-04-30T04:21:59.064518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
13 231
43.7%
3 223
42.2%
15 28
 
5.3%
30 24
 
4.5%
31 15
 
2.8%
2 6
 
1.1%
35 2
 
0.4%
ValueCountFrequency (%)
2 6
 
1.1%
3 223
42.2%
13 231
43.7%
15 28
 
5.3%
30 24
 
4.5%
31 15
 
2.8%
35 2
 
0.4%
ValueCountFrequency (%)
35 2
 
0.4%
31 15
 
2.8%
30 24
 
4.5%
15 28
 
5.3%
13 231
43.7%
3 223
42.2%
2 6
 
1.1%
Distinct7
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
영업중
231 
폐업
223 
전출
28 
허가취소
24 
등록취소
 
15
Other values (2)
 
8

Length

Max length4
Median length3
Mean length2.5916824
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 231
43.7%
폐업 223
42.2%
전출 28
 
5.3%
허가취소 24
 
4.5%
등록취소 15
 
2.8%
휴업 6
 
1.1%
직권말소 2
 
0.4%

Length

2024-04-30T04:21:59.172101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:21:59.264925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 231
43.7%
폐업 223
42.2%
전출 28
 
5.3%
허가취소 24
 
4.5%
등록취소 15
 
2.8%
휴업 6
 
1.1%
직권말소 2
 
0.4%

폐업일자
Date

MISSING 

Distinct230
Distinct (%)91.6%
Missing278
Missing (%)52.6%
Memory size4.3 KiB
Minimum1997-10-10 00:00:00
Maximum2024-04-19 00:00:00
2024-04-30T04:21:59.374090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:21:59.477391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)100.0%
Missing523
Missing (%)98.9%
Infinite0
Infinite (%)0.0%
Mean20098944
Minimum20060816
Maximum20201104
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.8 KiB
2024-04-30T04:21:59.575437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20060816
5-th percentile20063162
Q120070230
median20080466
Q320098110
95-th percentile20175980
Maximum20201104
Range140288
Interquartile range (IQR)27880.5

Descriptive statistics

Standard deviation52169.417
Coefficient of variation (CV)0.0025956298
Kurtosis4.3716375
Mean20098944
Median Absolute Deviation (MAD)14958
Skewness2.0347248
Sum1.2059366 × 108
Variance2.721648 × 109
MonotonicityStrictly increasing
2024-04-30T04:21:59.690926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
20060816 1
 
0.2%
20070201 1
 
0.2%
20070316 1
 
0.2%
20090617 1
 
0.2%
20100608 1
 
0.2%
20201104 1
 
0.2%
(Missing) 523
98.9%
ValueCountFrequency (%)
20060816 1
0.2%
20070201 1
0.2%
20070316 1
0.2%
20090617 1
0.2%
20100608 1
0.2%
20201104 1
0.2%
ValueCountFrequency (%)
20201104 1
0.2%
20100608 1
0.2%
20090617 1
0.2%
20070316 1
0.2%
20070201 1
0.2%
20060816 1
0.2%

휴업종료일자
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)100.0%
Missing523
Missing (%)98.9%
Infinite0
Infinite (%)0.0%
Mean20104070
Minimum20070731
Maximum20210504
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.8 KiB
2024-04-30T04:21:59.785358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20070731
5-th percentile20070752
Q120070919
median20081131
Q320105339
95-th percentile20185405
Maximum20210504
Range139773
Interquartile range (IQR)34419.75

Descriptive statistics

Standard deviation54461.827
Coefficient of variation (CV)0.0027089951
Kurtosis4.2511314
Mean20104070
Median Absolute Deviation (MAD)10358
Skewness2.03257
Sum1.2062442 × 108
Variance2.9660906 × 109
MonotonicityNot monotonic
2024-04-30T04:21:59.867124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
20070815 1
 
0.2%
20070731 1
 
0.2%
20071231 1
 
0.2%
20091031 1
 
0.2%
20110108 1
 
0.2%
20210504 1
 
0.2%
(Missing) 523
98.9%
ValueCountFrequency (%)
20070731 1
0.2%
20070815 1
0.2%
20071231 1
0.2%
20091031 1
0.2%
20110108 1
0.2%
20210504 1
0.2%
ValueCountFrequency (%)
20210504 1
0.2%
20110108 1
0.2%
20091031 1
0.2%
20071231 1
0.2%
20070815 1
0.2%
20070731 1
0.2%

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing529
Missing (%)100.0%
Memory size4.8 KiB

전화번호
Text

MISSING 

Distinct365
Distinct (%)97.1%
Missing153
Missing (%)28.9%
Memory size4.3 KiB
2024-04-30T04:22:00.087111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length18
Mean length10.178191
Min length7

Characters and Unicode

Total characters3827
Distinct characters16
Distinct categories6 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique355 ?
Unique (%)94.4%

Sample

1st row783-7772
2nd row2679-1205
3rd row421-5429
4th row757-9981
5th row3491-0895
ValueCountFrequency (%)
070-4900-2339 3
 
0.8%
070-4865-6818 2
 
0.5%
02-737-5121 2
 
0.5%
780-3651 2
 
0.5%
2635-2033 2
 
0.5%
070-8827-3660 2
 
0.5%
02 2
 
0.5%
841-6196 2
 
0.5%
02-567-2959 2
 
0.5%
2165-8080 2
 
0.5%
Other values (358) 359
94.5%
2024-04-30T04:22:00.422699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 564
14.7%
0 539
14.1%
2 474
12.4%
7 413
10.8%
8 387
10.1%
6 324
8.5%
3 303
7.9%
1 238
6.2%
5 226
5.9%
4 175
 
4.6%
Other values (6) 184
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3253
85.0%
Dash Punctuation 564
 
14.7%
Space Separator 4
 
0.1%
Math Symbol 3
 
0.1%
Other Punctuation 2
 
0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 539
16.6%
2 474
14.6%
7 413
12.7%
8 387
11.9%
6 324
10.0%
3 303
9.3%
1 238
7.3%
5 226
6.9%
4 175
 
5.4%
9 174
 
5.3%
Math Symbol
ValueCountFrequency (%)
~ 2
66.7%
+ 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 564
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3827
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 564
14.7%
0 539
14.1%
2 474
12.4%
7 413
10.8%
8 387
10.1%
6 324
8.5%
3 303
7.9%
1 238
6.2%
5 226
5.9%
4 175
 
4.6%
Other values (6) 184
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3827
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 564
14.7%
0 539
14.1%
2 474
12.4%
7 413
10.8%
8 387
10.1%
6 324
8.5%
3 303
7.9%
1 238
6.2%
5 226
5.9%
4 175
 
4.6%
Other values (6) 184
 
4.8%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing529
Missing (%)100.0%
Memory size4.8 KiB

소재지우편번호
Text

MISSING 

Distinct99
Distinct (%)41.6%
Missing291
Missing (%)55.0%
Memory size4.3 KiB
2024-04-30T04:22:00.657446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0462185
Min length6

Characters and Unicode

Total characters1439
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

Unique56 ?
Unique (%)23.5%

Sample

1st row150741
2nd row150036
3rd row150890
4th row150872
5th row150708
ValueCountFrequency (%)
150010 12
 
5.0%
150825 10
 
4.2%
150890 9
 
3.8%
150814 9
 
3.8%
150871 9
 
3.8%
150817 7
 
2.9%
150886 7
 
2.9%
150870 6
 
2.5%
150906 6
 
2.5%
150035 6
 
2.5%
Other values (89) 157
66.0%
2024-04-30T04:22:01.000940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 364
25.3%
1 311
21.6%
5 274
19.0%
8 159
11.0%
7 92
 
6.4%
9 58
 
4.0%
3 55
 
3.8%
6 40
 
2.8%
4 39
 
2.7%
2 36
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1428
99.2%
Dash Punctuation 11
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 364
25.5%
1 311
21.8%
5 274
19.2%
8 159
11.1%
7 92
 
6.4%
9 58
 
4.1%
3 55
 
3.9%
6 40
 
2.8%
4 39
 
2.7%
2 36
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1439
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 364
25.3%
1 311
21.6%
5 274
19.0%
8 159
11.0%
7 92
 
6.4%
9 58
 
4.0%
3 55
 
3.8%
6 40
 
2.8%
4 39
 
2.7%
2 36
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1439
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 364
25.3%
1 311
21.6%
5 274
19.0%
8 159
11.0%
7 92
 
6.4%
9 58
 
4.0%
3 55
 
3.8%
6 40
 
2.8%
4 39
 
2.7%
2 36
 
2.5%
Distinct480
Distinct (%)90.7%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2024-04-30T04:22:01.229253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length41
Mean length28.550095
Min length19

Characters and Unicode

Total characters15103
Distinct characters256
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

Unique447 ?
Unique (%)84.5%

Sample

1st row서울특별시 영등포구 여의도동 44-26번지 중앙빌딩 101동
2nd row서울특별시 영등포구 영등포동6가 77-8번지 3층
3rd row서울특별시 영등포구 여의도동 44-32번지 에리트빌딩 703
4th row서울특별시 영등포구 여의도동 15-16번지 산정빌딩 906동
5th row서울특별시 영등포구 여의도동 25-5번지 동화빌딩 1308
ValueCountFrequency (%)
서울특별시 529
19.6%
영등포구 529
19.6%
여의도동 198
 
7.3%
대림동 71
 
2.6%
당산동3가 32
 
1.2%
신길동 29
 
1.1%
문래동3가 24
 
0.9%
당산동6가 20
 
0.7%
양평동4가 19
 
0.7%
1층 17
 
0.6%
Other values (771) 1232
45.6%
2024-04-30T04:22:01.573983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2471
 
16.4%
1 640
 
4.2%
619
 
4.1%
611
 
4.0%
607
 
4.0%
570
 
3.8%
546
 
3.6%
544
 
3.6%
533
 
3.5%
531
 
3.5%
Other values (246) 7431
49.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9184
60.8%
Decimal Number 2916
 
19.3%
Space Separator 2471
 
16.4%
Dash Punctuation 446
 
3.0%
Uppercase Letter 44
 
0.3%
Lowercase Letter 21
 
0.1%
Open Punctuation 8
 
0.1%
Close Punctuation 7
 
< 0.1%
Other Punctuation 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
619
 
6.7%
611
 
6.7%
607
 
6.6%
570
 
6.2%
546
 
5.9%
544
 
5.9%
533
 
5.8%
531
 
5.8%
530
 
5.8%
529
 
5.8%
Other values (207) 3564
38.8%
Uppercase Letter
ValueCountFrequency (%)
K 15
34.1%
C 7
15.9%
B 6
 
13.6%
M 4
 
9.1%
S 2
 
4.5%
E 2
 
4.5%
T 2
 
4.5%
A 1
 
2.3%
V 1
 
2.3%
U 1
 
2.3%
Other values (3) 3
 
6.8%
Decimal Number
ValueCountFrequency (%)
1 640
21.9%
3 385
13.2%
2 382
13.1%
4 323
11.1%
0 297
10.2%
5 270
9.3%
6 229
 
7.9%
7 146
 
5.0%
8 125
 
4.3%
9 119
 
4.1%
Lowercase Letter
ValueCountFrequency (%)
n 8
38.1%
e 5
23.8%
t 2
 
9.5%
r 2
 
9.5%
c 2
 
9.5%
z 1
 
4.8%
i 1
 
4.8%
Other Punctuation
ValueCountFrequency (%)
: 3
50.0%
, 2
33.3%
& 1
 
16.7%
Open Punctuation
ValueCountFrequency (%)
( 7
87.5%
1
 
12.5%
Close Punctuation
ValueCountFrequency (%)
) 6
85.7%
1
 
14.3%
Space Separator
ValueCountFrequency (%)
2471
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 446
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9184
60.8%
Common 5854
38.8%
Latin 65
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
619
 
6.7%
611
 
6.7%
607
 
6.6%
570
 
6.2%
546
 
5.9%
544
 
5.9%
533
 
5.8%
531
 
5.8%
530
 
5.8%
529
 
5.8%
Other values (207) 3564
38.8%
Latin
ValueCountFrequency (%)
K 15
23.1%
n 8
12.3%
C 7
10.8%
B 6
 
9.2%
e 5
 
7.7%
M 4
 
6.2%
S 2
 
3.1%
E 2
 
3.1%
t 2
 
3.1%
r 2
 
3.1%
Other values (10) 12
18.5%
Common
ValueCountFrequency (%)
2471
42.2%
1 640
 
10.9%
- 446
 
7.6%
3 385
 
6.6%
2 382
 
6.5%
4 323
 
5.5%
0 297
 
5.1%
5 270
 
4.6%
6 229
 
3.9%
7 146
 
2.5%
Other values (9) 265
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9184
60.8%
ASCII 5917
39.2%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2471
41.8%
1 640
 
10.8%
- 446
 
7.5%
3 385
 
6.5%
2 382
 
6.5%
4 323
 
5.5%
0 297
 
5.0%
5 270
 
4.6%
6 229
 
3.9%
7 146
 
2.5%
Other values (27) 328
 
5.5%
Hangul
ValueCountFrequency (%)
619
 
6.7%
611
 
6.7%
607
 
6.6%
570
 
6.2%
546
 
5.9%
544
 
5.9%
533
 
5.8%
531
 
5.8%
530
 
5.8%
529
 
5.8%
Other values (207) 3564
38.8%
None
ValueCountFrequency (%)
1
50.0%
1
50.0%

도로명주소
Text

MISSING 

Distinct487
Distinct (%)93.8%
Missing10
Missing (%)1.9%
Memory size4.3 KiB
2024-04-30T04:22:01.816250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length52
Mean length36.801541
Min length24

Characters and Unicode

Total characters19100
Distinct characters272
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique458 ?
Unique (%)88.2%

Sample

1st row서울특별시 영등포구 국제금융로8길 19, 101동 (여의도동,중앙빌딩)
2nd row서울특별시 영등포구 영등포로 189-1 (영등포동6가,3층)
3rd row서울특별시 영등포구 여의대방로65길 12 (여의도동,에리트빌딩 703)
4th row서울특별시 영등포구 국회대로66길 23, 906동 (여의도동,산정빌딩)
5th row서울특별시 영등포구 여의나루로 71 (여의도동,동화빌딩 1308)
ValueCountFrequency (%)
서울특별시 519
 
15.5%
영등포구 519
 
15.5%
여의도동 128
 
3.8%
대림동 60
 
1.8%
신길동 27
 
0.8%
당산동3가 27
 
0.8%
1층 26
 
0.8%
국제금융로6길 25
 
0.7%
4층 23
 
0.7%
2층 22
 
0.7%
Other values (846) 1977
59.0%
2024-04-30T04:22:02.212008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2926
 
15.3%
665
 
3.5%
625
 
3.3%
620
 
3.2%
1 613
 
3.2%
583
 
3.1%
, 561
 
2.9%
548
 
2.9%
539
 
2.8%
) 525
 
2.7%
Other values (262) 10895
57.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11266
59.0%
Decimal Number 3130
 
16.4%
Space Separator 2926
 
15.3%
Other Punctuation 564
 
3.0%
Close Punctuation 526
 
2.8%
Open Punctuation 526
 
2.8%
Dash Punctuation 79
 
0.4%
Uppercase Letter 64
 
0.3%
Lowercase Letter 18
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
665
 
5.9%
625
 
5.5%
620
 
5.5%
583
 
5.2%
548
 
4.9%
539
 
4.8%
524
 
4.7%
522
 
4.6%
520
 
4.6%
519
 
4.6%
Other values (222) 5601
49.7%
Uppercase Letter
ValueCountFrequency (%)
K 17
26.6%
B 14
21.9%
C 6
 
9.4%
A 4
 
6.2%
M 4
 
6.2%
T 3
 
4.7%
V 3
 
4.7%
E 3
 
4.7%
S 3
 
4.7%
I 2
 
3.1%
Other values (5) 5
 
7.8%
Decimal Number
ValueCountFrequency (%)
1 613
19.6%
2 433
13.8%
3 419
13.4%
0 339
10.8%
6 267
8.5%
4 266
8.5%
7 245
 
7.8%
5 205
 
6.5%
8 184
 
5.9%
9 159
 
5.1%
Lowercase Letter
ValueCountFrequency (%)
n 8
44.4%
e 4
22.2%
r 2
 
11.1%
t 2
 
11.1%
c 2
 
11.1%
Other Punctuation
ValueCountFrequency (%)
, 561
99.5%
: 2
 
0.4%
& 1
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 525
99.8%
1
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 525
99.8%
1
 
0.2%
Space Separator
ValueCountFrequency (%)
2926
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 79
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11266
59.0%
Common 7752
40.6%
Latin 82
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
665
 
5.9%
625
 
5.5%
620
 
5.5%
583
 
5.2%
548
 
4.9%
539
 
4.8%
524
 
4.7%
522
 
4.6%
520
 
4.6%
519
 
4.6%
Other values (222) 5601
49.7%
Common
ValueCountFrequency (%)
2926
37.7%
1 613
 
7.9%
, 561
 
7.2%
) 525
 
6.8%
( 525
 
6.8%
2 433
 
5.6%
3 419
 
5.4%
0 339
 
4.4%
6 267
 
3.4%
4 266
 
3.4%
Other values (10) 878
 
11.3%
Latin
ValueCountFrequency (%)
K 17
20.7%
B 14
17.1%
n 8
9.8%
C 6
 
7.3%
e 4
 
4.9%
A 4
 
4.9%
M 4
 
4.9%
T 3
 
3.7%
V 3
 
3.7%
E 3
 
3.7%
Other values (10) 16
19.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11266
59.0%
ASCII 7832
41.0%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2926
37.4%
1 613
 
7.8%
, 561
 
7.2%
) 525
 
6.7%
( 525
 
6.7%
2 433
 
5.5%
3 419
 
5.3%
0 339
 
4.3%
6 267
 
3.4%
4 266
 
3.4%
Other values (28) 958
 
12.2%
Hangul
ValueCountFrequency (%)
665
 
5.9%
625
 
5.5%
620
 
5.5%
583
 
5.2%
548
 
4.9%
539
 
4.8%
524
 
4.7%
522
 
4.6%
520
 
4.6%
519
 
4.6%
Other values (222) 5601
49.7%
None
ValueCountFrequency (%)
1
50.0%
1
50.0%

도로명우편번호
Text

MISSING 

Distinct129
Distinct (%)33.9%
Missing148
Missing (%)28.0%
Memory size4.3 KiB
2024-04-30T04:22:02.462159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.1076115
Min length5

Characters and Unicode

Total characters1946
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

Unique68 ?
Unique (%)17.8%

Sample

1st row150804
2nd row07345
3rd row07237
4th row07333
5th row07250
ValueCountFrequency (%)
07331 20
 
5.2%
07238 19
 
5.0%
07333 15
 
3.9%
07299 14
 
3.7%
07415 12
 
3.1%
07256 12
 
3.1%
07237 10
 
2.6%
07327 10
 
2.6%
07222 10
 
2.6%
07345 10
 
2.6%
Other values (119) 249
65.4%
2024-04-30T04:22:02.836652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 459
23.6%
7 411
21.1%
2 283
14.5%
3 236
12.1%
1 141
 
7.2%
5 131
 
6.7%
4 87
 
4.5%
8 83
 
4.3%
9 68
 
3.5%
6 46
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1945
99.9%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 459
23.6%
7 411
21.1%
2 283
14.6%
3 236
12.1%
1 141
 
7.2%
5 131
 
6.7%
4 87
 
4.5%
8 83
 
4.3%
9 68
 
3.5%
6 46
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1946
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 459
23.6%
7 411
21.1%
2 283
14.5%
3 236
12.1%
1 141
 
7.2%
5 131
 
6.7%
4 87
 
4.5%
8 83
 
4.3%
9 68
 
3.5%
6 46
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1946
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 459
23.6%
7 411
21.1%
2 283
14.5%
3 236
12.1%
1 141
 
7.2%
5 131
 
6.7%
4 87
 
4.5%
8 83
 
4.3%
9 68
 
3.5%
6 46
 
2.4%
Distinct517
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2024-04-30T04:22:03.034144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length30
Mean length8.2022684
Min length3

Characters and Unicode

Total characters4339
Distinct characters420
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique505 ?
Unique (%)95.5%

Sample

1st row(주)경성항공
2nd row(주)미도관광여행사
3rd row세바스
4th row(주)삼풍여행사
5th row(주)씨.엔.씨항공
ValueCountFrequency (%)
주식회사 56
 
8.7%
투어 6
 
0.9%
여행사 5
 
0.8%
tour 3
 
0.5%
트래블 3
 
0.5%
대신여행사 2
 
0.3%
co 2
 
0.3%
ltd 2
 
0.3%
2
 
0.3%
2
 
0.3%
Other values (547) 559
87.1%
2024-04-30T04:22:03.345070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
334
 
7.7%
) 291
 
6.7%
( 290
 
6.7%
205
 
4.7%
169
 
3.9%
168
 
3.9%
149
 
3.4%
143
 
3.3%
113
 
2.6%
102
 
2.4%
Other values (410) 2375
54.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3442
79.3%
Close Punctuation 291
 
6.7%
Open Punctuation 290
 
6.7%
Uppercase Letter 133
 
3.1%
Space Separator 113
 
2.6%
Lowercase Letter 55
 
1.3%
Other Punctuation 13
 
0.3%
Other Symbol 1
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
334
 
9.7%
205
 
6.0%
169
 
4.9%
168
 
4.9%
149
 
4.3%
143
 
4.2%
102
 
3.0%
89
 
2.6%
64
 
1.9%
63
 
1.8%
Other values (358) 1956
56.8%
Uppercase Letter
ValueCountFrequency (%)
A 14
 
10.5%
R 13
 
9.8%
T 12
 
9.0%
O 11
 
8.3%
L 10
 
7.5%
E 9
 
6.8%
C 9
 
6.8%
U 5
 
3.8%
M 5
 
3.8%
N 5
 
3.8%
Other values (15) 40
30.1%
Lowercase Letter
ValueCountFrequency (%)
o 7
12.7%
t 6
10.9%
e 5
9.1%
n 5
9.1%
i 5
9.1%
r 4
 
7.3%
c 3
 
5.5%
l 3
 
5.5%
a 3
 
5.5%
h 2
 
3.6%
Other values (9) 12
21.8%
Other Punctuation
ValueCountFrequency (%)
. 6
46.2%
& 5
38.5%
, 2
 
15.4%
Close Punctuation
ValueCountFrequency (%)
) 291
100.0%
Open Punctuation
ValueCountFrequency (%)
( 290
100.0%
Space Separator
ValueCountFrequency (%)
113
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3438
79.2%
Common 708
 
16.3%
Latin 188
 
4.3%
Han 5
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
334
 
9.7%
205
 
6.0%
169
 
4.9%
168
 
4.9%
149
 
4.3%
143
 
4.2%
102
 
3.0%
89
 
2.6%
64
 
1.9%
63
 
1.8%
Other values (354) 1952
56.8%
Latin
ValueCountFrequency (%)
A 14
 
7.4%
R 13
 
6.9%
T 12
 
6.4%
O 11
 
5.9%
L 10
 
5.3%
E 9
 
4.8%
C 9
 
4.8%
o 7
 
3.7%
t 6
 
3.2%
e 5
 
2.7%
Other values (34) 92
48.9%
Common
ValueCountFrequency (%)
) 291
41.1%
( 290
41.0%
113
 
16.0%
. 6
 
0.8%
& 5
 
0.7%
, 2
 
0.3%
- 1
 
0.1%
Han
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3437
79.2%
ASCII 896
 
20.6%
CJK 4
 
0.1%
None 1
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
334
 
9.7%
205
 
6.0%
169
 
4.9%
168
 
4.9%
149
 
4.3%
143
 
4.2%
102
 
3.0%
89
 
2.6%
64
 
1.9%
63
 
1.8%
Other values (353) 1951
56.8%
ASCII
ValueCountFrequency (%)
) 291
32.5%
( 290
32.4%
113
 
12.6%
A 14
 
1.6%
R 13
 
1.5%
T 12
 
1.3%
O 11
 
1.2%
L 10
 
1.1%
E 9
 
1.0%
C 9
 
1.0%
Other values (41) 124
13.8%
None
ValueCountFrequency (%)
1
100.0%
CJK
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
CJK Compat Ideographs
ValueCountFrequency (%)
1
100.0%
Distinct508
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
Minimum2003-04-18 15:28:10
Maximum2024-04-19 16:07:24
2024-04-30T04:22:03.630580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:22:03.745255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
I
288 
U
241 

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 288
54.4%
U 241
45.6%

Length

2024-04-30T04:22:03.881837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:22:03.961437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 288
54.4%
u 241
45.6%
Distinct162
Distinct (%)30.6%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:06:00
2024-04-30T04:22:04.045494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:22:04.150266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing529
Missing (%)100.0%
Memory size4.8 KiB

좌표정보(X)
Real number (ℝ)

Distinct315
Distinct (%)60.1%
Missing5
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean191978.41
Minimum189682.02
Maximum194632.53
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.8 KiB
2024-04-30T04:22:04.279143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189682.02
5-th percentile190431.87
Q1190891.51
median191566.04
Q3193099.56
95-th percentile193815.3
Maximum194632.53
Range4950.5041
Interquartile range (IQR)2208.0585

Descriptive statistics

Standard deviation1229.4703
Coefficient of variation (CV)0.0064042112
Kurtosis-1.2099591
Mean191978.41
Median Absolute Deviation (MAD)927.21841
Skewness0.31855798
Sum1.0059669 × 108
Variance1511597.1
MonotonicityNot monotonic
2024-04-30T04:22:04.416750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
193469.554731741 22
 
4.2%
193282.654266684 12
 
2.3%
190996.357288859 11
 
2.1%
190586.062540107 10
 
1.9%
194561.746032498 9
 
1.7%
191457.663413167 6
 
1.1%
193500.284361195 6
 
1.1%
193501.453598102 5
 
0.9%
192894.437488166 5
 
0.9%
193099.563598351 5
 
0.9%
Other values (305) 433
81.9%
ValueCountFrequency (%)
189682.022243843 1
 
0.2%
189748.379334427 1
 
0.2%
189883.592752983 1
 
0.2%
189986.498936099 1
 
0.2%
190023.48828661 3
0.6%
190026.251961332 2
0.4%
190063.218859643 1
 
0.2%
190079.219797466 4
0.8%
190161.737344082 2
0.4%
190237.437423451 1
 
0.2%
ValueCountFrequency (%)
194632.526367463 2
 
0.4%
194592.276750438 1
 
0.2%
194561.746032498 9
1.7%
194530.535390096 3
 
0.6%
194028.635844427 1
 
0.2%
193882.109246282 1
 
0.2%
193861.272368256 3
 
0.6%
193844.169062846 1
 
0.2%
193839.302798329 2
 
0.4%
193818.18014 4
0.8%

좌표정보(Y)
Real number (ℝ)

Distinct315
Distinct (%)60.1%
Missing5
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean446323.17
Minimum442756.53
Maximum448699.97
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.8 KiB
2024-04-30T04:22:04.536299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum442756.53
5-th percentile443330.33
Q1445886.79
median446508.07
Q3447333.01
95-th percentile448135.63
Maximum448699.97
Range5943.441
Interquartile range (IQR)1446.2121

Descriptive statistics

Standard deviation1421.9381
Coefficient of variation (CV)0.0031858934
Kurtosis0.13954858
Mean446323.17
Median Absolute Deviation (MAD)708.85683
Skewness-1.0139881
Sum2.3387334 × 108
Variance2021907.9
MonotonicityNot monotonic
2024-04-30T04:22:04.667527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
446508.068667777 22
 
4.2%
447611.552045596 12
 
2.3%
445841.377603245 11
 
2.1%
447216.925498911 10
 
1.9%
446364.318286465 9
 
1.7%
447179.850506981 6
 
1.1%
446443.965496834 6
 
1.1%
446959.020722485 5
 
0.9%
447360.835255288 5
 
0.9%
447330.445753577 5
 
0.9%
Other values (305) 433
81.9%
ValueCountFrequency (%)
442756.531513655 1
0.2%
442972.238395 1
0.2%
442988.625887746 1
0.2%
443006.302183214 1
0.2%
443012.116312639 1
0.2%
443012.232328617 1
0.2%
443017.977832154 1
0.2%
443020.00608597 1
0.2%
443020.758368262 1
0.2%
443045.811115987 1
0.2%
ValueCountFrequency (%)
448699.972523898 1
0.2%
448554.360195644 1
0.2%
448497.695424055 1
0.2%
448495.395437399 1
0.2%
448322.935192248 1
0.2%
448306.736102179 1
0.2%
448303.563751032 1
0.2%
448289.617887109 2
0.4%
448285.408670964 1
0.2%
448277.718260078 1
0.2%
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
국내외여행업
358 
<NA>
171 

Length

Max length6
Median length6
Mean length5.3534972
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
국내외여행업 358
67.7%
<NA> 171
32.3%

Length

2024-04-30T04:22:04.784024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:22:04.875968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국내외여행업 358
67.7%
na 171
32.3%
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
<NA>
362 
관광사업
167 

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> 362
68.4%
관광사업 167
31.6%

Length

2024-04-30T04:22:04.955629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:22:05.030077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 362
68.4%
관광사업 167
31.6%

지역구분명
Text

MISSING 

Distinct4
Distinct (%)50.0%
Missing521
Missing (%)98.5%
Memory size4.3 KiB
2024-04-30T04:22:05.118096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5
Min length4

Characters and Unicode

Total characters40
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)25.0%

Sample

1st row근린상업지역
2nd row상업지역
3rd row상업지역
4th row상업지역
5th row중심상업지역
ValueCountFrequency (%)
상업지역 4
50.0%
근린상업지역 2
25.0%
중심상업지역 1
 
12.5%
일반주거지역 1
 
12.5%
2024-04-30T04:22:05.380592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8
20.0%
8
20.0%
7
17.5%
7
17.5%
2
 
5.0%
2
 
5.0%
1
 
2.5%
1
 
2.5%
1
 
2.5%
1
 
2.5%
Other values (2) 2
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 40
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
8
20.0%
8
20.0%
7
17.5%
7
17.5%
2
 
5.0%
2
 
5.0%
1
 
2.5%
1
 
2.5%
1
 
2.5%
1
 
2.5%
Other values (2) 2
 
5.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 40
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
8
20.0%
8
20.0%
7
17.5%
7
17.5%
2
 
5.0%
2
 
5.0%
1
 
2.5%
1
 
2.5%
1
 
2.5%
1
 
2.5%
Other values (2) 2
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 40
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
8
20.0%
8
20.0%
7
17.5%
7
17.5%
2
 
5.0%
2
 
5.0%
1
 
2.5%
1
 
2.5%
1
 
2.5%
1
 
2.5%
Other values (2) 2
 
5.0%

총층수
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)2.8%
Missing171
Missing (%)32.3%
Infinite0
Infinite (%)0.0%
Mean0.34916201
Minimum0
Maximum24
Zeros347
Zeros (%)65.6%
Negative0
Negative (%)0.0%
Memory size4.8 KiB
2024-04-30T04:22:05.485023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum24
Range24
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.3534674
Coefficient of variation (CV)6.7403306
Kurtosis59.935604
Mean0.34916201
Median Absolute Deviation (MAD)0
Skewness7.5784837
Sum125
Variance5.5388088
MonotonicityNot monotonic
2024-04-30T04:22:05.582459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 347
65.6%
18 2
 
0.4%
4 2
 
0.4%
13 1
 
0.2%
24 1
 
0.2%
19 1
 
0.2%
12 1
 
0.2%
3 1
 
0.2%
1 1
 
0.2%
9 1
 
0.2%
(Missing) 171
32.3%
ValueCountFrequency (%)
0 347
65.6%
1 1
 
0.2%
3 1
 
0.2%
4 2
 
0.4%
9 1
 
0.2%
12 1
 
0.2%
13 1
 
0.2%
18 2
 
0.4%
19 1
 
0.2%
24 1
 
0.2%
ValueCountFrequency (%)
24 1
 
0.2%
19 1
 
0.2%
18 2
 
0.4%
13 1
 
0.2%
12 1
 
0.2%
9 1
 
0.2%
4 2
 
0.4%
3 1
 
0.2%
1 1
 
0.2%
0 347
65.6%

주변환경명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
<NA>
518 
기타
 
11

Length

Max length4
Median length4
Mean length3.9584121
Min length2

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> 518
97.9%
기타 11
 
2.1%

Length

2024-04-30T04:22:05.701802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:22:05.785784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 518
97.9%
기타 11
 
2.1%

제작취급품목내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing529
Missing (%)100.0%
Memory size4.8 KiB

보험기관명
Categorical

Distinct28
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
<NA>
274 
서울보증보험주식회사
72 
서울보증보험
49 
한국관광협회중앙회
32 
한국관광협회중앙회 여행공제회
 
26
Other values (23)
76 

Length

Max length19
Median length4
Mean length6.8903592
Min length4

Unique

Unique12 ?
Unique (%)2.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 274
51.8%
서울보증보험주식회사 72
 
13.6%
서울보증보험 49
 
9.3%
한국관광협회중앙회 32
 
6.0%
한국관광협회중앙회 여행공제회 26
 
4.9%
한국관광협회중앙회여행공제회 20
 
3.8%
한국관광협회 10
 
1.9%
서울보증보험(주) 9
 
1.7%
한국관광협회 중앙회 4
 
0.8%
한국관광협회중앙회 관광공제회 4
 
0.8%
Other values (18) 29
 
5.5%

Length

2024-04-30T04:22:05.882162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 274
48.1%
서울보증보험주식회사 72
 
12.6%
한국관광협회중앙회 62
 
10.9%
서울보증보험 52
 
9.1%
여행공제회 32
 
5.6%
한국관광협회중앙회여행공제회 20
 
3.5%
한국관광협회 16
 
2.8%
서울보증보험(주 9
 
1.6%
중앙회 5
 
0.9%
관광공제회 4
 
0.7%
Other values (15) 24
 
4.2%

건물용도명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
<NA>
510 
근린생활시설
 
12
사무실
 
6
기타
 
1

Length

Max length6
Median length4
Mean length4.0302457
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 510
96.4%
근린생활시설 12
 
2.3%
사무실 6
 
1.1%
기타 1
 
0.2%

Length

2024-04-30T04:22:06.025260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:22:06.121050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 510
96.4%
근린생활시설 12
 
2.3%
사무실 6
 
1.1%
기타 1
 
0.2%

지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)2.2%
Missing171
Missing (%)32.3%
Infinite0
Infinite (%)0.0%
Mean0.27653631
Minimum0
Maximum19
Zeros346
Zeros (%)65.4%
Negative0
Negative (%)0.0%
Memory size4.8 KiB
2024-04-30T04:22:06.197831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum19
Range19
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.8300502
Coefficient of variation (CV)6.6177573
Kurtosis59.898317
Mean0.27653631
Median Absolute Deviation (MAD)0
Skewness7.5445041
Sum99
Variance3.3490838
MonotonicityNot monotonic
2024-04-30T04:22:06.294562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 346
65.4%
14 3
 
0.6%
3 3
 
0.6%
1 2
 
0.4%
10 1
 
0.2%
19 1
 
0.2%
9 1
 
0.2%
8 1
 
0.2%
(Missing) 171
32.3%
ValueCountFrequency (%)
0 346
65.4%
1 2
 
0.4%
3 3
 
0.6%
8 1
 
0.2%
9 1
 
0.2%
10 1
 
0.2%
14 3
 
0.6%
19 1
 
0.2%
ValueCountFrequency (%)
19 1
 
0.2%
14 3
 
0.6%
10 1
 
0.2%
9 1
 
0.2%
8 1
 
0.2%
3 3
 
0.6%
1 2
 
0.4%
0 346
65.4%

지하층수
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
0
349 
<NA>
171 
1
 
3
4
 
2
3
 
2

Length

Max length4
Median length1
Mean length1.9697543
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 349
66.0%
<NA> 171
32.3%
1 3
 
0.6%
4 2
 
0.4%
3 2
 
0.4%
5 2
 
0.4%

Length

2024-04-30T04:22:06.431630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:22:06.543458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 349
66.0%
na 171
32.3%
1 3
 
0.6%
4 2
 
0.4%
3 2
 
0.4%
5 2
 
0.4%

객실수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
0
358 
<NA>
171 

Length

Max length4
Median length1
Mean length1.9697543
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 358
67.7%
<NA> 171
32.3%

Length

2024-04-30T04:22:06.646551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:22:06.738310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 358
67.7%
na 171
32.3%

건축연면적
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
0
358 
<NA>
171 

Length

Max length4
Median length1
Mean length1.9697543
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 358
67.7%
<NA> 171
32.3%

Length

2024-04-30T04:22:06.836029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:22:06.929134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 358
67.7%
na 171
32.3%

영문상호명
Text

MISSING 

Distinct17
Distinct (%)100.0%
Missing512
Missing (%)96.8%
Memory size4.3 KiB
2024-04-30T04:22:07.063869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length20
Mean length17.470588
Min length10

Characters and Unicode

Total characters297
Distinct characters46
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

Unique17 ?
Unique (%)100.0%

Sample

1st rowBANK&FINANCIAL WORLD TRAVEL CO LTD
2nd rowASIA SKYCLUB
3rd rowShinwol Shinyoung Co,.Ltd
4th rowREIM CO., LTD.
5th rowTOURMART.COM
ValueCountFrequency (%)
co 6
 
12.5%
ltd 5
 
10.4%
tour 4
 
8.3%
travel 2
 
4.2%
bank&financial 1
 
2.1%
star 1
 
2.1%
uni-k 1
 
2.1%
co.ltd 1
 
2.1%
hana 1
 
2.1%
free 1
 
2.1%
Other values (25) 25
52.1%
2024-04-30T04:22:07.323308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
31
 
10.4%
L 19
 
6.4%
o 17
 
5.7%
C 16
 
5.4%
A 15
 
5.1%
O 14
 
4.7%
. 12
 
4.0%
T 12
 
4.0%
R 12
 
4.0%
t 10
 
3.4%
Other values (36) 139
46.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 158
53.2%
Lowercase Letter 87
29.3%
Space Separator 31
 
10.4%
Other Punctuation 19
 
6.4%
Dash Punctuation 2
 
0.7%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
L 19
12.0%
C 16
 
10.1%
A 15
 
9.5%
O 14
 
8.9%
T 12
 
7.6%
R 12
 
7.6%
S 8
 
5.1%
N 7
 
4.4%
I 6
 
3.8%
E 6
 
3.8%
Other values (12) 43
27.2%
Lowercase Letter
ValueCountFrequency (%)
o 17
19.5%
t 10
11.5%
i 9
10.3%
n 8
9.2%
r 7
8.0%
d 7
8.0%
a 7
8.0%
l 6
 
6.9%
h 3
 
3.4%
u 2
 
2.3%
Other values (9) 11
12.6%
Other Punctuation
ValueCountFrequency (%)
. 12
63.2%
, 5
26.3%
& 2
 
10.5%
Space Separator
ValueCountFrequency (%)
31
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 245
82.5%
Common 52
 
17.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
L 19
 
7.8%
o 17
 
6.9%
C 16
 
6.5%
A 15
 
6.1%
O 14
 
5.7%
T 12
 
4.9%
R 12
 
4.9%
t 10
 
4.1%
i 9
 
3.7%
S 8
 
3.3%
Other values (31) 113
46.1%
Common
ValueCountFrequency (%)
31
59.6%
. 12
 
23.1%
, 5
 
9.6%
- 2
 
3.8%
& 2
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 297
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
31
 
10.4%
L 19
 
6.4%
o 17
 
5.7%
C 16
 
5.4%
A 15
 
5.1%
O 14
 
4.7%
. 12
 
4.0%
T 12
 
4.0%
R 12
 
4.0%
t 10
 
3.4%
Other values (36) 139
46.8%

영문상호주소
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
<NA>
512 
OVERSEAS TRAVEL BUSINESS
 
12
Overseas travel business
 
3
Overseas Travel Business
 
2

Length

Max length24
Median length4
Mean length4.6427221
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> 512
96.8%
OVERSEAS TRAVEL BUSINESS 12
 
2.3%
Overseas travel business 3
 
0.6%
Overseas Travel Business 2
 
0.4%

Length

2024-04-30T04:22:07.444050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:22:07.548678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 512
90.9%
overseas 17
 
3.0%
travel 17
 
3.0%
business 17
 
3.0%

선박총톤수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
0
358 
<NA>
171 

Length

Max length4
Median length1
Mean length1.9697543
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 358
67.7%
<NA> 171
32.3%

Length

2024-04-30T04:22:07.660987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:22:07.746410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 358
67.7%
na 171
32.3%

선박척수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
0
358 
<NA>
171 

Length

Max length4
Median length1
Mean length1.9697543
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 358
67.7%
<NA> 171
32.3%

Length

2024-04-30T04:22:07.832139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:22:07.915245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 358
67.7%
na 171
32.3%

선박제원
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing529
Missing (%)100.0%
Memory size4.8 KiB

무대면적
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
0
358 
<NA>
171 

Length

Max length4
Median length1
Mean length1.9697543
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 358
67.7%
<NA> 171
32.3%

Length

2024-04-30T04:22:08.038131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:22:08.148170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 358
67.7%
na 171
32.3%

좌석수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
0
358 
<NA>
171 

Length

Max length4
Median length1
Mean length1.9697543
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 358
67.7%
<NA> 171
32.3%

Length

2024-04-30T04:22:08.241999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:22:08.327300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 358
67.7%
na 171
32.3%

기념품종류
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing529
Missing (%)100.0%
Memory size4.8 KiB
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
0
358 
<NA>
171 

Length

Max length4
Median length1
Mean length1.9697543
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 358
67.7%
<NA> 171
32.3%

Length

2024-04-30T04:22:08.427500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:22:08.518183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 358
67.7%
na 171
32.3%

시설면적
Real number (ℝ)

MISSING  ZEROS 

Distinct41
Distinct (%)11.5%
Missing171
Missing (%)32.3%
Infinite0
Infinite (%)0.0%
Mean54.994385
Minimum0
Maximum11191.28
Zeros314
Zeros (%)59.4%
Negative0
Negative (%)0.0%
Memory size4.8 KiB
2024-04-30T04:22:08.808767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile42.192
Maximum11191.28
Range11191.28
Interquartile range (IQR)0

Descriptive statistics

Standard deviation649.55848
Coefficient of variation (CV)11.81136
Kurtosis252.47908
Mean54.994385
Median Absolute Deviation (MAD)0
Skewness15.432598
Sum19687.99
Variance421926.22
MonotonicityNot monotonic
2024-04-30T04:22:08.907246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
0.0 314
59.4%
3.3 3
 
0.6%
9.0 3
 
0.6%
4975.09 1
 
0.2%
66.12 1
 
0.2%
149.45 1
 
0.2%
90.5 1
 
0.2%
28.0 1
 
0.2%
41.4 1
 
0.2%
16.5 1
 
0.2%
Other values (31) 31
 
5.9%
(Missing) 171
32.3%
ValueCountFrequency (%)
0.0 314
59.4%
3.3 3
 
0.6%
3.79 1
 
0.2%
3.97 1
 
0.2%
6.0 1
 
0.2%
9.0 3
 
0.6%
12.16 1
 
0.2%
16.5 1
 
0.2%
17.0 1
 
0.2%
17.09 1
 
0.2%
ValueCountFrequency (%)
11191.28 1
0.2%
4975.09 1
0.2%
1148.71 1
0.2%
450.8 1
0.2%
198.0 1
0.2%
151.44 1
0.2%
150.0 1
0.2%
149.45 1
0.2%
138.81 1
0.2%
132.0 1
0.2%

놀이기구수내역
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing529
Missing (%)100.0%
Memory size4.8 KiB

놀이시설수
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
0
358 
<NA>
171 

Length

Max length4
Median length1
Mean length1.9697543
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 358
67.7%
<NA> 171
32.3%

Length

2024-04-30T04:22:09.008208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:22:09.098814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 358
67.7%
na 171
32.3%

방송시설유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing529
Missing (%)100.0%
Memory size4.8 KiB

발전시설유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing529
Missing (%)100.0%
Memory size4.8 KiB

의무실유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing529
Missing (%)100.0%
Memory size4.8 KiB

안내소유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing529
Missing (%)100.0%
Memory size4.8 KiB

기획여행보험시작일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
<NA>
527 
20180320
 
1
20181210
 
1

Length

Max length8
Median length4
Mean length4.0151229
Min length4

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 527
99.6%
20180320 1
 
0.2%
20181210 1
 
0.2%

Length

2024-04-30T04:22:09.204646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:22:09.306125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 527
99.6%
20180320 1
 
0.2%
20181210 1
 
0.2%

기획여행보험종료일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
<NA>
527 
20190319
 
1
20191209
 
1

Length

Max length8
Median length4
Mean length4.0151229
Min length4

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 527
99.6%
20190319 1
 
0.2%
20191209 1
 
0.2%

Length

2024-04-30T04:22:09.401558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:22:09.500396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 527
99.6%
20190319 1
 
0.2%
20191209 1
 
0.2%

자본금
Real number (ℝ)

MISSING  ZEROS 

Distinct50
Distinct (%)14.0%
Missing171
Missing (%)32.3%
Infinite0
Infinite (%)0.0%
Mean80658596
Minimum0
Maximum1.982895 × 109
Zeros88
Zeros (%)16.6%
Negative0
Negative (%)0.0%
Memory size4.8 KiB
2024-04-30T04:22:09.617508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13250000
median60000000
Q31 × 108
95-th percentile1.5 × 108
Maximum1.982895 × 109
Range1.982895 × 109
Interquartile range (IQR)96750000

Descriptive statistics

Standard deviation1.4782703 × 108
Coefficient of variation (CV)1.8327499
Kurtosis93.946307
Mean80658596
Median Absolute Deviation (MAD)40000000
Skewness8.6884156
Sum2.8875777 × 1010
Variance2.1852832 × 1016
MonotonicityNot monotonic
2024-04-30T04:22:09.761558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 88
16.6%
100000000 87
16.4%
60000000 77
14.6%
150000000 23
 
4.3%
30000000 13
 
2.5%
50000000 7
 
1.3%
90000000 6
 
1.1%
200000000 4
 
0.8%
70000000 3
 
0.6%
65000000 3
 
0.6%
Other values (40) 47
 
8.9%
(Missing) 171
32.3%
ValueCountFrequency (%)
0 88
16.6%
1 1
 
0.2%
1000000 1
 
0.2%
10000000 1
 
0.2%
30000000 13
 
2.5%
31000014 1
 
0.2%
32632831 1
 
0.2%
33703638 1
 
0.2%
42826478 1
 
0.2%
45000000 2
 
0.4%
ValueCountFrequency (%)
1982895000 1
 
0.2%
1225000000 1
 
0.2%
1000000000 2
 
0.4%
350000000 1
 
0.2%
300000000 3
 
0.6%
250000000 2
 
0.4%
210000000 1
 
0.2%
200000000 4
 
0.8%
160000000 1
 
0.2%
150000000 23
4.3%

보험시작일자
Real number (ℝ)

MISSING 

Distinct249
Distinct (%)95.4%
Missing268
Missing (%)50.7%
Infinite0
Infinite (%)0.0%
Mean20137664
Minimum20021031
Maximum20220222
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.8 KiB
2024-04-30T04:22:09.903759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20021031
5-th percentile20060801
Q120101119
median20140303
Q320171208
95-th percentile20210209
Maximum20220222
Range199191
Interquartile range (IQR)70089

Descriptive statistics

Standard deviation45440.035
Coefficient of variation (CV)0.0022564701
Kurtosis-0.90775694
Mean20137664
Median Absolute Deviation (MAD)39184
Skewness-0.053128425
Sum5.2559302 × 109
Variance2.0647968 × 109
MonotonicityNot monotonic
2024-04-30T04:22:10.037057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20121029 2
 
0.4%
20140705 2
 
0.4%
20120626 2
 
0.4%
20140723 2
 
0.4%
20200401 2
 
0.4%
20110118 2
 
0.4%
20140303 2
 
0.4%
20140225 2
 
0.4%
20060224 2
 
0.4%
20140304 2
 
0.4%
Other values (239) 241
45.6%
(Missing) 268
50.7%
ValueCountFrequency (%)
20021031 1
0.2%
20060224 2
0.4%
20060306 1
0.2%
20060307 1
0.2%
20060323 1
0.2%
20060327 1
0.2%
20060419 1
0.2%
20060515 1
0.2%
20060623 1
0.2%
20060628 1
0.2%
ValueCountFrequency (%)
20220222 1
0.2%
20220221 1
0.2%
20211021 1
0.2%
20210917 1
0.2%
20210916 1
0.2%
20210824 1
0.2%
20210802 1
0.2%
20210625 1
0.2%
20210613 1
0.2%
20210604 1
0.2%

보험종료일자
Real number (ℝ)

MISSING 

Distinct251
Distinct (%)96.2%
Missing268
Missing (%)50.7%
Infinite0
Infinite (%)0.0%
Mean20147971
Minimum20031031
Maximum20230222
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.8 KiB
2024-04-30T04:22:10.190995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20031031
5-th percentile20070804
Q120111129
median20150303
Q320190319
95-th percentile20220308
Maximum20230222
Range199191
Interquartile range (IQR)79190

Descriptive statistics

Standard deviation45528.862
Coefficient of variation (CV)0.0022597245
Kurtosis-0.90132073
Mean20147971
Median Absolute Deviation (MAD)39185
Skewness-0.05521991
Sum5.2586204 × 109
Variance2.0728773 × 109
MonotonicityNot monotonic
2024-04-30T04:22:10.325506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20070224 2
 
0.4%
20130621 2
 
0.4%
20150317 2
 
0.4%
20150302 2
 
0.4%
20150722 2
 
0.4%
20150630 2
 
0.4%
20150307 2
 
0.4%
20130626 2
 
0.4%
20150705 2
 
0.4%
20201104 2
 
0.4%
Other values (241) 241
45.6%
(Missing) 268
50.7%
ValueCountFrequency (%)
20031031 1
0.2%
20060423 1
0.2%
20070224 2
0.4%
20070306 1
0.2%
20070327 1
0.2%
20070419 1
0.2%
20070514 1
0.2%
20070622 1
0.2%
20070628 1
0.2%
20070701 1
0.2%
ValueCountFrequency (%)
20230222 1
0.2%
20230220 1
0.2%
20221021 1
0.2%
20220917 1
0.2%
20220915 1
0.2%
20220823 1
0.2%
20220801 1
0.2%
20220624 1
0.2%
20220613 1
0.2%
20220604 1
0.2%

부대시설내역
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing529
Missing (%)100.0%
Memory size4.8 KiB

시설규모
Real number (ℝ)

MISSING  ZEROS 

Distinct36
Distinct (%)10.1%
Missing171
Missing (%)32.3%
Infinite0
Infinite (%)0.0%
Mean54.99162
Minimum0
Maximum11191
Zeros314
Zeros (%)59.4%
Negative0
Negative (%)0.0%
Memory size4.8 KiB
2024-04-30T04:22:10.451086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile41.9
Maximum11191
Range11191
Interquartile range (IQR)0

Descriptive statistics

Standard deviation649.54462
Coefficient of variation (CV)11.811702
Kurtosis252.47575
Mean54.99162
Median Absolute Deviation (MAD)0
Skewness15.432473
Sum19687
Variance421908.21
MonotonicityNot monotonic
2024-04-30T04:22:10.549683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
0 314
59.4%
9 3
 
0.6%
3 3
 
0.6%
23 3
 
0.6%
17 3
 
0.6%
4 2
 
0.4%
4975 1
 
0.2%
50 1
 
0.2%
28 1
 
0.2%
41 1
 
0.2%
Other values (26) 26
 
4.9%
(Missing) 171
32.3%
ValueCountFrequency (%)
0 314
59.4%
3 3
 
0.6%
4 2
 
0.4%
6 1
 
0.2%
9 3
 
0.6%
12 1
 
0.2%
17 3
 
0.6%
18 1
 
0.2%
23 3
 
0.6%
24 1
 
0.2%
ValueCountFrequency (%)
11191 1
0.2%
4975 1
0.2%
1149 1
0.2%
451 1
0.2%
198 1
0.2%
151 1
0.2%
150 1
0.2%
149 1
0.2%
139 1
0.2%
132 1
0.2%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명문화사업자구분명지역구분명총층수주변환경명제작취급품목내용보험기관명건물용도명지상층수지하층수객실수건축연면적영문상호명영문상호주소선박총톤수선박척수선박제원무대면적좌석수기념품종류회의실별동시수용인원시설면적놀이기구수내역놀이시설수방송시설유무발전시설유무의무실유무안내소유무기획여행보험시작일자기획여행보험종료일자자본금보험시작일자보험종료일자부대시설내역시설규모
03180000CDFI226002198800000119880308<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 09:53:50I2018-08-31 23:59:59.0<NA>193657.203252446493.709453국내외여행업관광사업<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
13180000CDFI226002199000000119900503<NA>3폐업3폐업20130709<NA><NA><NA>2679-1205<NA>150036서울특별시 영등포구 영등포동6가 77-8번지 3층서울특별시 영등포구 영등포로 189-1 (영등포동6가,3층)<NA>(주)미도관광여행사2013-07-09 10:41:56I2018-08-31 23:59:59.0<NA>191332.09693446487.614234국내외여행업관광사업<NA>0<NA><NA>서울보증보험<NA>0000<NA><NA>00<NA>00<NA>00.0<NA>0<NA><NA><NA><NA><NA><NA>02011112420121123<NA>0
23180000CDFI226002199000000219900927<NA>4취소/말소/만료/정지/중지31등록취소<NA><NA><NA><NA>421-5429<NA>150890서울특별시 영등포구 여의도동 44-32번지 에리트빌딩 703서울특별시 영등포구 여의대방로65길 12 (여의도동,에리트빌딩 703)<NA>세바스2003-04-18 15:28:39I2018-08-31 23:59:59.0<NA>193745.643373446380.254633국내외여행업관광사업<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
33180000CDFI226002199000000319901115<NA>4취소/말소/만료/정지/중지30허가취소<NA><NA><NA><NA>757-9981<NA>150872서울특별시 영등포구 여의도동 15-16번지 산정빌딩 906동서울특별시 영등포구 국회대로66길 23, 906동 (여의도동,산정빌딩)<NA>(주)삼풍여행사2004-10-14 17:27:25I2018-08-31 23:59:59.0<NA>192845.536926447322.662904국내외여행업관광사업<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
43180000CDFI226002199100000119910502<NA>3폐업3폐업19991229<NA><NA><NA>3491-0895<NA>150708서울특별시 영등포구 여의도동 25-5번지 동화빌딩 1308서울특별시 영등포구 여의나루로 71 (여의도동,동화빌딩 1308)<NA>(주)씨.엔.씨항공2003-04-18 15:28:39I2018-08-31 23:59:59.0<NA>193472.910163446842.048446국내외여행업관광사업<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
53180000CDFI226002199200000119920422<NA>3폐업3폐업20030807<NA><NA><NA>3786-0777<NA>150869서울특별시 영등포구 여의도동 12번지 CCMM빌딩8층서울특별시 영등포구 여의공원로 101 (여의도동,CCMM빌딩8층)<NA>한국능률협회매니지먼트2003-08-07 19:04:56I2018-08-31 23:59:59.0<NA>193293.251953447448.342915국내외여행업관광사업<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
63180000CDFI226002199200000219920420<NA>3폐업3폐업20020830<NA><NA><NA>2631-9122<NA>150806서울특별시 영등포구 당산동4가 93-1번지 동양빌딩2층203호<NA><NA>(주)에코투어2003-04-18 15:28:10I2018-08-31 23:59:59.0<NA>190682.998389447452.686099국내외여행업관광사업<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
73180000CDFI226002199200000319921021<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>189682.022244446823.857632국내외여행업관광사업<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
83180000CDFI226002199300000119931209<NA>3폐업3폐업20030430<NA><NA><NA>786-2255<NA>150890서울특별시 영등포구 여의도동 44-33번지 두일빌딩 301동 409호서울특별시 영등포구 여의대방로67길 9, 301동 409호 (여의도동,두일빌딩)<NA>(주)아카데미여행사2003-05-01 10:37:45I2018-08-31 23:59:59.0<NA>193787.76227446371.610691국내외여행업관광사업<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
93180000CDFI226002199300000219931120<NA>3폐업3폐업20021224<NA><NA><NA>786-8500<NA>150886서울특별시 영등포구 여의도동 36-4번지 오륜빌딩702호서울특별시 영등포구 국제금융로8길 34 (여의도동,오륜빌딩702호)<NA>(주)여명여행사2003-04-18 15:28:39I2018-08-31 23:59:59.0<NA>193500.284361446443.965497국내외여행업관광사업<NA>18기타<NA><NA>근린생활시설14400<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
5193180000CDFI22600220230000182014-06-20<NA>1영업/정상13영업중<NA><NA><NA><NA>02-313-9101<NA><NA>서울특별시 영등포구 양평동3가 5-4 에이스 하이테크시티3서울특별시 영등포구 선유로 130, 에이스 하이테크시티3 301~304호 내 55호 (양평동3가)07255(주)조이스투어리스트서비스2023-07-07 15:55:42U2022-12-07 00:09:00.0<NA>190325.849378447033.87348<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>
5203180000CDFI22600220230000192023-07-24<NA>1영업/정상13영업중<NA><NA><NA><NA>070-8221-3056<NA><NA>서울특별시 영등포구 당산동6가 1-2서울특별시 영등포구 양평로 2 (당산동6가)07223주식회사 오픈놀2023-07-24 11:18:09I2022-12-06 22:06:00.0<NA>191599.744649447780.986259<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>
5213180000CDFI22600220230000202023-09-06<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 당산동3가 398-20서울특별시 영등포구 당산로29길 3, 201호 (당산동3가)07261그래서여행2023-09-06 14:07:41I2022-12-09 00:08:00.0<NA>190628.811062447070.241331<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>
5223180000CDFI22600220230000212023-10-10<NA>1영업/정상13영업중<NA><NA><NA><NA>070-8019-0321<NA><NA>서울특별시 영등포구 영등포동3가 31 영등포시장지하도상가서울특별시 영등포구 영등포로 지하 221, 영등포시장지하도상가 13호 (영등포동3가)07250지금괌 주식회사2023-10-10 15:28:48I2022-10-30 23:02:00.0<NA>191614.686144446322.714551<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>
5233180000CDFI22600220230000222023-11-24<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 당산동4가 32-41서울특별시 영등포구 당산로38길 9-3, 402호 (당산동4가)07220주식회사 나르샤투어2023-12-21 15:59:03U2022-11-01 22:03:00.0<NA>191044.790077447450.192307<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>
5243180000CDFI22600220230000232023-12-19<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 여의도동 47 여의도자이서울특별시 영등포구 여의동로3길 10, 상가동 1층 112호 (여의도동, 여의도자이)07324도넛투어2024-01-05 16:26:08U2023-12-01 00:07:00.0<NA>193393.096554446218.443828<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>
5253180000CDFI22600220240000012024-01-15<NA>1영업/정상13영업중<NA><NA><NA><NA>02-849-1008<NA><NA>서울특별시 영등포구 영등포동 618-607서울특별시 영등포구 영신로19길 24-1, 4층 (영등포동)07366(주)청송관광여행사2024-01-16 18:06:34I2023-11-30 23:08:00.0<NA>191555.84781445729.762463<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>
5263180000CDFI22600220240000022024-02-23<NA>1영업/정상13영업중<NA><NA><NA><NA>02-6403-7700<NA><NA>서울특별시 영등포구 문래동1가 96-4 한양빌딩서울특별시 영등포구 경인로 706, 한양빌딩 6층 6210호 (문래동1가)07371주식회사 성호투어2024-02-23 16:15:57I2023-12-01 22:05:00.0<NA>190431.86613445424.772798<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>
5273180000CDFI22600220240000032017-11-23<NA>1영업/정상13영업중<NA><NA><NA><NA>02-6094-0820<NA><NA>서울특별시 영등포구 여의도동 36-4 오륜빌딩서울특별시 영등포구 국제금융로8길 34, 오륜빌딩 605호 (여의도동)07331와이앤지투어2024-03-21 17:22:04I2023-12-02 22:03:00.0<NA>193500.284361446443.965497<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>
5283180000CDFI22600220240000042009-06-29<NA>1영업/정상13영업중<NA><NA><NA><NA>02-563-5390<NA><NA>서울특별시 영등포구 여의도동 13 여의도파라곤서울특별시 영등포구 국회대로 800, 여의도파라곤 435호 (여의도동)07238(주)와이비투어2024-04-18 17:30:48U2023-12-03 22:00:00.0<NA>192959.271161447637.656082<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>