Overview

Dataset statistics

Number of variables60
Number of observations393
Missing cells10659
Missing cells (%)45.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory199.3 KiB
Average record size in memory519.3 B

Variable types

Categorical21
Text11
DateTime4
Unsupported16
Numeric8

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
Author강서구
URLhttps://data.seoul.go.kr/dataList/OA-17617/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
총층수 is highly imbalanced (90.5%)Imbalance
보험기관명 is highly imbalanced (63.3%)Imbalance
지하층수 is highly imbalanced (89.3%)Imbalance
객실수 is highly imbalanced (87.1%)Imbalance
건축연면적 is highly imbalanced (87.1%)Imbalance
영문상호주소 is highly imbalanced (78.1%)Imbalance
선박총톤수 is highly imbalanced (87.1%)Imbalance
선박척수 is highly imbalanced (87.1%)Imbalance
무대면적 is highly imbalanced (87.1%)Imbalance
좌석수 is highly imbalanced (87.1%)Imbalance
회의실별동시수용인원 is highly imbalanced (87.1%)Imbalance
놀이시설수 is highly imbalanced (87.1%)Imbalance
기획여행보험시작일자 is highly imbalanced (97.4%)Imbalance
기획여행보험종료일자 is highly imbalanced (97.4%)Imbalance
인허가취소일자 has 393 (100.0%) missing valuesMissing
폐업일자 has 317 (80.7%) missing valuesMissing
휴업시작일자 has 393 (100.0%) missing valuesMissing
휴업종료일자 has 393 (100.0%) missing valuesMissing
재개업일자 has 393 (100.0%) missing valuesMissing
전화번호 has 192 (48.9%) missing valuesMissing
소재지면적 has 393 (100.0%) missing valuesMissing
소재지우편번호 has 348 (88.5%) missing valuesMissing
도로명우편번호 has 16 (4.1%) missing valuesMissing
업태구분명 has 393 (100.0%) missing valuesMissing
좌표정보(X) has 51 (13.0%) missing valuesMissing
좌표정보(Y) has 51 (13.0%) missing valuesMissing
문화사업자구분명 has 393 (100.0%) missing valuesMissing
지역구분명 has 389 (99.0%) missing valuesMissing
주변환경명 has 391 (99.5%) missing valuesMissing
제작취급품목내용 has 393 (100.0%) missing valuesMissing
건물용도명 has 389 (99.0%) missing valuesMissing
지상층수 has 379 (96.4%) missing valuesMissing
영문상호명 has 354 (90.1%) missing valuesMissing
선박제원 has 393 (100.0%) missing valuesMissing
기념품종류 has 393 (100.0%) missing valuesMissing
시설면적 has 336 (85.5%) missing valuesMissing
놀이기구수내역 has 393 (100.0%) missing valuesMissing
방송시설유무 has 393 (100.0%) missing valuesMissing
발전시설유무 has 393 (100.0%) missing valuesMissing
의무실유무 has 393 (100.0%) missing valuesMissing
안내소유무 has 393 (100.0%) missing valuesMissing
자본금 has 251 (63.9%) missing valuesMissing
보험시작일자 has 285 (72.5%) missing valuesMissing
보험종료일자 has 285 (72.5%) missing valuesMissing
부대시설내역 has 393 (100.0%) missing valuesMissing
시설규모 has 336 (85.5%) missing valuesMissing
관리번호 has unique valuesUnique
최종수정일자 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
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
문화사업자구분명 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
지상층수 has 8 (2.0%) zerosZeros
시설면적 has 8 (2.0%) zerosZeros
시설규모 has 8 (2.0%) zerosZeros

Reproduction

Analysis started2024-05-11 08:00:35.751549
Analysis finished2024-05-11 08:00:38.235090
Duration2.48 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
3150000
393 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3150000
2nd row3150000
3rd row3150000
4th row3150000
5th row3150000

Common Values

ValueCountFrequency (%)
3150000 393
100.0%

Length

2024-05-11T08:00:38.854795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:00:39.264536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3150000 393
100.0%

관리번호
Text

UNIQUE 

Distinct393
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2024-05-11T08:00:39.722828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters7860
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

Unique393 ?
Unique (%)100.0%

Sample

1st rowCDFI2260041990000001
2nd rowCDFI2260041998000001
3rd rowCDFI2260041998000002
4th rowCDFI2260042000000001
5th rowCDFI2260042001000001
ValueCountFrequency (%)
cdfi2260041990000001 1
 
0.3%
cdfi2260042022000027 1
 
0.3%
cdfi2260042022000025 1
 
0.3%
cdfi2260042022000024 1
 
0.3%
cdfi2260042022000023 1
 
0.3%
cdfi2260042022000022 1
 
0.3%
cdfi2260042022000021 1
 
0.3%
cdfi2260042022000020 1
 
0.3%
cdfi2260042022000019 1
 
0.3%
cdfi2260042022000018 1
 
0.3%
Other values (383) 383
97.5%
2024-05-11T08:00:40.873011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2956
37.6%
2 1560
19.8%
4 506
 
6.4%
6 461
 
5.9%
C 393
 
5.0%
D 393
 
5.0%
F 393
 
5.0%
I 393
 
5.0%
1 347
 
4.4%
3 163
 
2.1%
Other values (4) 295
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6288
80.0%
Uppercase Letter 1572
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2956
47.0%
2 1560
24.8%
4 506
 
8.0%
6 461
 
7.3%
1 347
 
5.5%
3 163
 
2.6%
9 95
 
1.5%
8 73
 
1.2%
5 68
 
1.1%
7 59
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
C 393
25.0%
D 393
25.0%
F 393
25.0%
I 393
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6288
80.0%
Latin 1572
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2956
47.0%
2 1560
24.8%
4 506
 
8.0%
6 461
 
7.3%
1 347
 
5.5%
3 163
 
2.6%
9 95
 
1.5%
8 73
 
1.2%
5 68
 
1.1%
7 59
 
0.9%
Latin
ValueCountFrequency (%)
C 393
25.0%
D 393
25.0%
F 393
25.0%
I 393
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7860
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2956
37.6%
2 1560
19.8%
4 506
 
6.4%
6 461
 
5.9%
C 393
 
5.0%
D 393
 
5.0%
F 393
 
5.0%
I 393
 
5.0%
1 347
 
4.4%
3 163
 
2.1%
Other values (4) 295
 
3.8%
Distinct360
Distinct (%)91.6%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
Minimum1987-08-20 00:00:00
Maximum2024-05-02 00:00:00
2024-05-11T08:00:41.386242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:00:42.008027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing393
Missing (%)100.0%
Memory size3.6 KiB
Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
1
317 
3
46 
5
 
30

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 317
80.7%
3 46
 
11.7%
5 30
 
7.6%

Length

2024-05-11T08:00:42.629043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:00:43.072917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 317
80.7%
3 46
 
11.7%
5 30
 
7.6%

영업상태명
Categorical

Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
영업/정상
317 
폐업
46 
제외/삭제/전출
 
30

Length

Max length8
Median length5
Mean length4.8778626
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 317
80.7%
폐업 46
 
11.7%
제외/삭제/전출 30
 
7.6%

Length

2024-05-11T08:00:43.574116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:00:44.074503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 317
80.7%
폐업 46
 
11.7%
제외/삭제/전출 30
 
7.6%
Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
13
317 
3
46 
15
 
30

Length

Max length2
Median length2
Mean length1.8829517
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row13
2nd row13
3rd row13
4th row13
5th row3

Common Values

ValueCountFrequency (%)
13 317
80.7%
3 46
 
11.7%
15 30
 
7.6%

Length

2024-05-11T08:00:44.468074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:00:44.856647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13 317
80.7%
3 46
 
11.7%
15 30
 
7.6%
Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
영업중
317 
폐업
46 
전출
 
30

Length

Max length3
Median length3
Mean length2.8066158
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 317
80.7%
폐업 46
 
11.7%
전출 30
 
7.6%

Length

2024-05-11T08:00:45.315306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:00:45.685033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 317
80.7%
폐업 46
 
11.7%
전출 30
 
7.6%

폐업일자
Date

MISSING 

Distinct73
Distinct (%)96.1%
Missing317
Missing (%)80.7%
Memory size3.2 KiB
Minimum2010-12-31 00:00:00
Maximum2024-04-04 00:00:00
2024-05-11T08:00:46.088975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:00:46.471914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing393
Missing (%)100.0%
Memory size3.6 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing393
Missing (%)100.0%
Memory size3.6 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing393
Missing (%)100.0%
Memory size3.6 KiB

전화번호
Text

MISSING 

Distinct199
Distinct (%)99.0%
Missing192
Missing (%)48.9%
Memory size3.2 KiB
2024-05-11T08:00:47.085019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.512438
Min length8

Characters and Unicode

Total characters2314
Distinct characters14
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique197 ?
Unique (%)98.0%

Sample

1st row02-2602-1960
2nd row02-3663-1245
3rd row02-3272-1411
4th row02-730-1501
5th row02-725-7824
ValueCountFrequency (%)
02 6
 
2.8%
2661-4077 2
 
0.9%
070 2
 
0.9%
02-753-1126 2
 
0.9%
02-6232-1079 1
 
0.5%
02-2135-1311 1
 
0.5%
02-549-0851 1
 
0.5%
02-2602-1960 1
 
0.5%
02-719-9975 1
 
0.5%
02-556-6665 1
 
0.5%
Other values (193) 193
91.5%
2024-05-11T08:00:48.121220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 377
16.3%
- 353
15.3%
0 346
15.0%
6 237
10.2%
3 193
8.3%
8 159
6.9%
1 158
6.8%
7 154
6.7%
5 119
 
5.1%
9 114
 
4.9%
Other values (4) 104
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1944
84.0%
Dash Punctuation 353
 
15.3%
Space Separator 14
 
0.6%
Close Punctuation 2
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 377
19.4%
0 346
17.8%
6 237
12.2%
3 193
9.9%
8 159
8.2%
1 158
8.1%
7 154
7.9%
5 119
 
6.1%
9 114
 
5.9%
4 87
 
4.5%
Dash Punctuation
ValueCountFrequency (%)
- 353
100.0%
Space Separator
ValueCountFrequency (%)
14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2314
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 377
16.3%
- 353
15.3%
0 346
15.0%
6 237
10.2%
3 193
8.3%
8 159
6.9%
1 158
6.8%
7 154
6.7%
5 119
 
5.1%
9 114
 
4.9%
Other values (4) 104
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2314
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 377
16.3%
- 353
15.3%
0 346
15.0%
6 237
10.2%
3 193
8.3%
8 159
6.9%
1 158
6.8%
7 154
6.7%
5 119
 
5.1%
9 114
 
4.9%
Other values (4) 104
 
4.5%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing393
Missing (%)100.0%
Memory size3.6 KiB

소재지우편번호
Text

MISSING 

Distinct31
Distinct (%)68.9%
Missing348
Missing (%)88.5%
Memory size3.2 KiB
2024-05-11T08:00:48.547734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0888889
Min length6

Characters and Unicode

Total characters274
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

Unique22 ?
Unique (%)48.9%

Sample

1st row157010
2nd row157804
3rd row157864
4th row157853
5th row157812
ValueCountFrequency (%)
157840 4
 
8.9%
157812 3
 
6.7%
157811 3
 
6.7%
157861 3
 
6.7%
157240 2
 
4.4%
157866 2
 
4.4%
157839 2
 
4.4%
157853 2
 
4.4%
157030 2
 
4.4%
157-040 1
 
2.2%
Other values (21) 21
46.7%
2024-05-11T08:00:49.455248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 65
23.7%
5 51
18.6%
7 48
17.5%
8 30
10.9%
0 24
 
8.8%
2 13
 
4.7%
3 11
 
4.0%
4 10
 
3.6%
6 10
 
3.6%
9 8
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 270
98.5%
Dash Punctuation 4
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 65
24.1%
5 51
18.9%
7 48
17.8%
8 30
11.1%
0 24
 
8.9%
2 13
 
4.8%
3 11
 
4.1%
4 10
 
3.7%
6 10
 
3.7%
9 8
 
3.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 274
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 65
23.7%
5 51
18.6%
7 48
17.5%
8 30
10.9%
0 24
 
8.8%
2 13
 
4.7%
3 11
 
4.0%
4 10
 
3.6%
6 10
 
3.6%
9 8
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 274
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 65
23.7%
5 51
18.6%
7 48
17.5%
8 30
10.9%
0 24
 
8.8%
2 13
 
4.7%
3 11
 
4.0%
4 10
 
3.6%
6 10
 
3.6%
9 8
 
2.9%
Distinct341
Distinct (%)86.8%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2024-05-11T08:00:50.050864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length39
Mean length29.437659
Min length15

Characters and Unicode

Total characters11569
Distinct characters225
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique309 ?
Unique (%)78.6%

Sample

1st row서울특별시 강서구 방화동 820번지
2nd row서울특별시 강서구 화곡동 24-571번지 천일빌딩 601호
3rd row서울특별시 강서구 가양동 449-21번지 한화비즈메트로2차
4th row서울특별시 강서구 마곡동 773 힐스테이트에코마곡역
5th row서울특별시 강서구 염창동 281-22번지 염창한화꿈에그린 105-301
ValueCountFrequency (%)
서울특별시 393
 
17.9%
강서구 393
 
17.9%
마곡동 206
 
9.4%
등촌동 49
 
2.2%
가양동 33
 
1.5%
화곡동 31
 
1.4%
방화동 26
 
1.2%
a동 26
 
1.2%
공항동 23
 
1.0%
염창동 15
 
0.7%
Other values (541) 1004
45.7%
2024-05-11T08:00:50.891419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1866
 
16.1%
802
 
6.9%
444
 
3.8%
412
 
3.6%
407
 
3.5%
1 399
 
3.4%
7 399
 
3.4%
396
 
3.4%
393
 
3.4%
393
 
3.4%
Other values (215) 5658
48.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6874
59.4%
Decimal Number 2390
 
20.7%
Space Separator 1866
 
16.1%
Dash Punctuation 329
 
2.8%
Uppercase Letter 72
 
0.6%
Letter Number 36
 
0.3%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
802
 
11.7%
444
 
6.5%
412
 
6.0%
407
 
5.9%
396
 
5.8%
393
 
5.7%
393
 
5.7%
393
 
5.7%
303
 
4.4%
276
 
4.0%
Other values (184) 2655
38.6%
Uppercase Letter
ValueCountFrequency (%)
A 28
38.9%
B 17
23.6%
W 8
 
11.1%
M 4
 
5.6%
P 3
 
4.2%
I 2
 
2.8%
C 2
 
2.8%
V 2
 
2.8%
T 1
 
1.4%
O 1
 
1.4%
Other values (4) 4
 
5.6%
Decimal Number
ValueCountFrequency (%)
1 399
16.7%
7 399
16.7%
9 260
10.9%
2 248
10.4%
0 231
9.7%
4 223
9.3%
5 169
7.1%
3 164
6.9%
6 155
 
6.5%
8 142
 
5.9%
Letter Number
ValueCountFrequency (%)
20
55.6%
14
38.9%
1
 
2.8%
1
 
2.8%
Space Separator
ValueCountFrequency (%)
1866
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 329
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6874
59.4%
Common 4587
39.6%
Latin 108
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
802
 
11.7%
444
 
6.5%
412
 
6.0%
407
 
5.9%
396
 
5.8%
393
 
5.7%
393
 
5.7%
393
 
5.7%
303
 
4.4%
276
 
4.0%
Other values (184) 2655
38.6%
Latin
ValueCountFrequency (%)
A 28
25.9%
20
18.5%
B 17
15.7%
14
13.0%
W 8
 
7.4%
M 4
 
3.7%
P 3
 
2.8%
I 2
 
1.9%
C 2
 
1.9%
V 2
 
1.9%
Other values (8) 8
 
7.4%
Common
ValueCountFrequency (%)
1866
40.7%
1 399
 
8.7%
7 399
 
8.7%
- 329
 
7.2%
9 260
 
5.7%
2 248
 
5.4%
0 231
 
5.0%
4 223
 
4.9%
5 169
 
3.7%
3 164
 
3.6%
Other values (3) 299
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6874
59.4%
ASCII 4659
40.3%
Number Forms 36
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1866
40.1%
1 399
 
8.6%
7 399
 
8.6%
- 329
 
7.1%
9 260
 
5.6%
2 248
 
5.3%
0 231
 
5.0%
4 223
 
4.8%
5 169
 
3.6%
3 164
 
3.5%
Other values (17) 371
 
8.0%
Hangul
ValueCountFrequency (%)
802
 
11.7%
444
 
6.5%
412
 
6.0%
407
 
5.9%
396
 
5.8%
393
 
5.7%
393
 
5.7%
393
 
5.7%
303
 
4.4%
276
 
4.0%
Other values (184) 2655
38.6%
Number Forms
ValueCountFrequency (%)
20
55.6%
14
38.9%
1
 
2.8%
1
 
2.8%
Distinct377
Distinct (%)96.2%
Missing1
Missing (%)0.3%
Memory size3.2 KiB
2024-05-11T08:00:51.470680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length47
Mean length38.492347
Min length23

Characters and Unicode

Total characters15089
Distinct characters255
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique362 ?
Unique (%)92.3%

Sample

1st row서울특별시 강서구 금낭화로 170, 1층 (방화동)
2nd row서울특별시 강서구 화곡로 266, 601호 (화곡동, 천일빌딩)
3rd row서울특별시 강서구 양천로 551-24 (가양동, 1203)
4th row서울특별시 강서구 마곡중앙로 76, 힐스테이트에코마곡역 307호 (마곡동)
5th row서울특별시 강서구 공항대로75길 17 (염창동,염창한화꿈에그린 105-301)
ValueCountFrequency (%)
서울특별시 392
 
14.1%
강서구 392
 
14.1%
마곡동 206
 
7.4%
공항대로 77
 
2.8%
양천로 55
 
2.0%
등촌동 47
 
1.7%
마곡중앙로 41
 
1.5%
마곡중앙6로 37
 
1.3%
가양동 33
 
1.2%
a동 31
 
1.1%
Other values (650) 1462
52.7%
2024-05-11T08:00:53.201072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2389
 
15.8%
843
 
5.6%
1 615
 
4.1%
475
 
3.1%
, 452
 
3.0%
448
 
3.0%
440
 
2.9%
407
 
2.7%
407
 
2.7%
403
 
2.7%
Other values (245) 8210
54.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8627
57.2%
Decimal Number 2591
 
17.2%
Space Separator 2389
 
15.8%
Other Punctuation 452
 
3.0%
Close Punctuation 394
 
2.6%
Open Punctuation 394
 
2.6%
Dash Punctuation 97
 
0.6%
Uppercase Letter 97
 
0.6%
Letter Number 39
 
0.3%
Lowercase Letter 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
843
 
9.8%
475
 
5.5%
448
 
5.2%
440
 
5.1%
407
 
4.7%
407
 
4.7%
403
 
4.7%
395
 
4.6%
392
 
4.5%
392
 
4.5%
Other values (206) 4025
46.7%
Uppercase Letter
ValueCountFrequency (%)
A 35
36.1%
B 26
26.8%
W 8
 
8.2%
C 6
 
6.2%
M 4
 
4.1%
P 3
 
3.1%
V 2
 
2.1%
I 2
 
2.1%
G 2
 
2.1%
D 2
 
2.1%
Other values (5) 7
 
7.2%
Decimal Number
ValueCountFrequency (%)
1 615
23.7%
2 338
13.0%
0 322
12.4%
5 242
 
9.3%
6 233
 
9.0%
4 215
 
8.3%
3 209
 
8.1%
7 149
 
5.8%
8 135
 
5.2%
9 133
 
5.1%
Letter Number
ValueCountFrequency (%)
21
53.8%
16
41.0%
1
 
2.6%
1
 
2.6%
Lowercase Letter
ValueCountFrequency (%)
f 2
40.0%
c 1
20.0%
i 1
20.0%
e 1
20.0%
Space Separator
ValueCountFrequency (%)
2389
100.0%
Other Punctuation
ValueCountFrequency (%)
, 452
100.0%
Close Punctuation
ValueCountFrequency (%)
) 394
100.0%
Open Punctuation
ValueCountFrequency (%)
( 394
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 97
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8627
57.2%
Common 6321
41.9%
Latin 141
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
843
 
9.8%
475
 
5.5%
448
 
5.2%
440
 
5.1%
407
 
4.7%
407
 
4.7%
403
 
4.7%
395
 
4.6%
392
 
4.5%
392
 
4.5%
Other values (206) 4025
46.7%
Latin
ValueCountFrequency (%)
A 35
24.8%
B 26
18.4%
21
14.9%
16
11.3%
W 8
 
5.7%
C 6
 
4.3%
M 4
 
2.8%
P 3
 
2.1%
V 2
 
1.4%
I 2
 
1.4%
Other values (13) 18
12.8%
Common
ValueCountFrequency (%)
2389
37.8%
1 615
 
9.7%
, 452
 
7.2%
) 394
 
6.2%
( 394
 
6.2%
2 338
 
5.3%
0 322
 
5.1%
5 242
 
3.8%
6 233
 
3.7%
4 215
 
3.4%
Other values (6) 727
 
11.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8627
57.2%
ASCII 6423
42.6%
Number Forms 39
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2389
37.2%
1 615
 
9.6%
, 452
 
7.0%
) 394
 
6.1%
( 394
 
6.1%
2 338
 
5.3%
0 322
 
5.0%
5 242
 
3.8%
6 233
 
3.6%
4 215
 
3.3%
Other values (25) 829
 
12.9%
Hangul
ValueCountFrequency (%)
843
 
9.8%
475
 
5.5%
448
 
5.2%
440
 
5.1%
407
 
4.7%
407
 
4.7%
403
 
4.7%
395
 
4.6%
392
 
4.5%
392
 
4.5%
Other values (206) 4025
46.7%
Number Forms
ValueCountFrequency (%)
21
53.8%
16
41.0%
1
 
2.6%
1
 
2.6%

도로명우편번호
Text

MISSING 

Distinct96
Distinct (%)25.5%
Missing16
Missing (%)4.1%
Memory size3.2 KiB
2024-05-11T08:00:54.090217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.0397878
Min length5

Characters and Unicode

Total characters1900
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 (%)14.9%

Sample

1st row07508
2nd row157010
3rd row07532
4th row07801
5th row07774
ValueCountFrequency (%)
07788 40
 
10.6%
07631 36
 
9.5%
07803 32
 
8.5%
07802 30
 
8.0%
07807 24
 
6.4%
07801 19
 
5.0%
07532 16
 
4.2%
07573 16
 
4.2%
07806 13
 
3.4%
07528 7
 
1.9%
Other values (86) 144
38.2%
2024-05-11T08:00:55.366838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 517
27.2%
7 517
27.2%
8 239
12.6%
5 148
 
7.8%
6 125
 
6.6%
3 122
 
6.4%
1 101
 
5.3%
2 79
 
4.2%
9 26
 
1.4%
4 25
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1899
99.9%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 517
27.2%
7 517
27.2%
8 239
12.6%
5 148
 
7.8%
6 125
 
6.6%
3 122
 
6.4%
1 101
 
5.3%
2 79
 
4.2%
9 26
 
1.4%
4 25
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1900
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 517
27.2%
7 517
27.2%
8 239
12.6%
5 148
 
7.8%
6 125
 
6.6%
3 122
 
6.4%
1 101
 
5.3%
2 79
 
4.2%
9 26
 
1.4%
4 25
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1900
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 517
27.2%
7 517
27.2%
8 239
12.6%
5 148
 
7.8%
6 125
 
6.6%
3 122
 
6.4%
1 101
 
5.3%
2 79
 
4.2%
9 26
 
1.4%
4 25
 
1.3%
Distinct389
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2024-05-11T08:00:56.154991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length17
Mean length8.9898219
Min length3

Characters and Unicode

Total characters3533
Distinct characters368
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique385 ?
Unique (%)98.0%

Sample

1st row(주)김포운송
2nd row(주)강서관광여행사
3rd row(주)도우관광
4th row주식회사 대웅여행사
5th row(주)덕양로지스틱
ValueCountFrequency (%)
주식회사 104
 
19.5%
tour 4
 
0.7%
투어 3
 
0.6%
아이비티에스코리아 2
 
0.4%
world 2
 
0.4%
inc 2
 
0.4%
코리아 2
 
0.4%
여행사 2
 
0.4%
글로벌 2
 
0.4%
월드에어텍 2
 
0.4%
Other values (407) 409
76.6%
2024-05-11T08:00:57.376136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
310
 
8.8%
) 214
 
6.1%
( 214
 
6.1%
163
 
4.6%
141
 
4.0%
118
 
3.3%
108
 
3.1%
106
 
3.0%
105
 
3.0%
95
 
2.7%
Other values (358) 1959
55.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2833
80.2%
Close Punctuation 214
 
6.1%
Open Punctuation 214
 
6.1%
Space Separator 141
 
4.0%
Uppercase Letter 72
 
2.0%
Lowercase Letter 53
 
1.5%
Decimal Number 3
 
0.1%
Other Punctuation 2
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
310
 
10.9%
163
 
5.8%
118
 
4.2%
108
 
3.8%
106
 
3.7%
105
 
3.7%
95
 
3.4%
90
 
3.2%
72
 
2.5%
71
 
2.5%
Other values (310) 1595
56.3%
Uppercase Letter
ValueCountFrequency (%)
O 10
13.9%
T 9
12.5%
C 5
 
6.9%
E 4
 
5.6%
U 4
 
5.6%
R 4
 
5.6%
N 4
 
5.6%
J 4
 
5.6%
I 4
 
5.6%
K 4
 
5.6%
Other values (12) 20
27.8%
Lowercase Letter
ValueCountFrequency (%)
r 8
15.1%
o 6
11.3%
a 6
11.3%
e 6
11.3%
i 4
 
7.5%
l 3
 
5.7%
u 3
 
5.7%
n 3
 
5.7%
h 2
 
3.8%
k 2
 
3.8%
Other values (8) 10
18.9%
Decimal Number
ValueCountFrequency (%)
0 1
33.3%
5 1
33.3%
1 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 214
100.0%
Open Punctuation
ValueCountFrequency (%)
( 214
100.0%
Space Separator
ValueCountFrequency (%)
141
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2833
80.2%
Common 575
 
16.3%
Latin 125
 
3.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
310
 
10.9%
163
 
5.8%
118
 
4.2%
108
 
3.8%
106
 
3.7%
105
 
3.7%
95
 
3.4%
90
 
3.2%
72
 
2.5%
71
 
2.5%
Other values (310) 1595
56.3%
Latin
ValueCountFrequency (%)
O 10
 
8.0%
T 9
 
7.2%
r 8
 
6.4%
o 6
 
4.8%
a 6
 
4.8%
e 6
 
4.8%
C 5
 
4.0%
E 4
 
3.2%
U 4
 
3.2%
R 4
 
3.2%
Other values (30) 63
50.4%
Common
ValueCountFrequency (%)
) 214
37.2%
( 214
37.2%
141
24.5%
. 2
 
0.3%
0 1
 
0.2%
5 1
 
0.2%
1 1
 
0.2%
- 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2833
80.2%
ASCII 700
 
19.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
310
 
10.9%
163
 
5.8%
118
 
4.2%
108
 
3.8%
106
 
3.7%
105
 
3.7%
95
 
3.4%
90
 
3.2%
72
 
2.5%
71
 
2.5%
Other values (310) 1595
56.3%
ASCII
ValueCountFrequency (%)
) 214
30.6%
( 214
30.6%
141
20.1%
O 10
 
1.4%
T 9
 
1.3%
r 8
 
1.1%
o 6
 
0.9%
a 6
 
0.9%
e 6
 
0.9%
C 5
 
0.7%
Other values (38) 81
 
11.6%

최종수정일자
Date

UNIQUE 

Distinct393
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
Minimum2010-12-31 15:33:54
Maximum2024-05-07 14:33:07
2024-05-11T08:00:57.905979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:00:58.396776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
U
260 
I
133 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 260
66.2%
I 133
33.8%

Length

2024-05-11T08:00:58.827374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:00:59.308427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 260
66.2%
i 133
33.8%
Distinct221
Distinct (%)56.2%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T08:00:59.708638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:01:00.340612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing393
Missing (%)100.0%
Memory size3.6 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct188
Distinct (%)55.0%
Missing51
Missing (%)13.0%
Infinite0
Infinite (%)0.0%
Mean185452.91
Minimum182141.21
Maximum189124.44
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2024-05-11T08:01:00.749706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum182141.21
5-th percentile183102.79
Q1184572.41
median185146.45
Q3186501.23
95-th percentile187950.8
Maximum189124.44
Range6983.2357
Interquartile range (IQR)1928.8193

Descriptive statistics

Standard deviation1516.7892
Coefficient of variation (CV)0.0081788371
Kurtosis-0.6120959
Mean185452.91
Median Absolute Deviation (MAD)832.81033
Skewness0.17297851
Sum63424896
Variance2300649.3
MonotonicityNot monotonic
2024-05-11T08:01:01.287629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
187733.160920858 12
 
3.1%
184655.264279055 11
 
2.8%
187952.560027898 8
 
2.0%
184526.084367975 7
 
1.8%
186501.110937132 6
 
1.5%
186501.233192961 6
 
1.5%
185032.421148111 5
 
1.3%
185292.76664368 5
 
1.3%
185150.32136415 5
 
1.3%
184733.0 5
 
1.3%
Other values (178) 272
69.2%
(Missing) 51
 
13.0%
ValueCountFrequency (%)
182141.205465089 4
1.0%
182449.847149564 1
 
0.3%
182524.823835629 2
0.5%
182675.360086075 1
 
0.3%
182876.367858149 1
 
0.3%
182879.610355768 1
 
0.3%
182895.668483962 1
 
0.3%
182914.770762913 1
 
0.3%
182941.05762285 1
 
0.3%
182974.850127567 1
 
0.3%
ValueCountFrequency (%)
189124.441211963 2
 
0.5%
188923.593727873 1
 
0.3%
188783.060728518 1
 
0.3%
188720.150596497 1
 
0.3%
188139.035116622 1
 
0.3%
188095.242884925 1
 
0.3%
188023.60012538 1
 
0.3%
187999.32555627 2
 
0.5%
187952.560027898 8
2.0%
187917.439597431 2
 
0.5%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct188
Distinct (%)55.0%
Missing51
Missing (%)13.0%
Infinite0
Infinite (%)0.0%
Mean450822.47
Minimum447414.07
Maximum453136.45
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2024-05-11T08:01:01.692196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum447414.07
5-th percentile447890.68
Q1450700.71
median450844.14
Q3451380.64
95-th percentile452140.12
Maximum453136.45
Range5722.3774
Interquartile range (IQR)679.9299

Descriptive statistics

Standard deviation1009.142
Coefficient of variation (CV)0.0022384466
Kurtosis3.4342508
Mean450822.47
Median Absolute Deviation (MAD)282.11649
Skewness-1.4709165
Sum1.5418128 × 108
Variance1018367.6
MonotonicityNot monotonic
2024-05-11T08:01:02.337338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
450747.952249309 12
 
3.1%
451864.298152252 11
 
2.8%
450562.020225978 8
 
2.0%
451722.650631223 7
 
1.8%
451334.591084256 6
 
1.5%
451485.251875922 6
 
1.5%
450836.071292455 5
 
1.3%
450863.026923918 5
 
1.3%
450822.870557532 5
 
1.3%
451884.0 5
 
1.3%
Other values (178) 272
69.2%
(Missing) 51
 
13.0%
ValueCountFrequency (%)
447414.070766476 1
0.3%
447456.838723466 1
0.3%
447473.568819772 1
0.3%
447494.051343402 1
0.3%
447539.991114893 1
0.3%
447565.350302185 1
0.3%
447576.805180714 1
0.3%
447641.974705858 1
0.3%
447644.452386583 1
0.3%
447651.06118753 1
0.3%
ValueCountFrequency (%)
453136.448166169 1
0.3%
452915.963722565 1
0.3%
452906.521290095 1
0.3%
452817.469477897 1
0.3%
452801.707821111 1
0.3%
452733.334890155 1
0.3%
452713.505241493 1
0.3%
452409.286327287 1
0.3%
452340.255955496 2
0.5%
452306.846703758 1
0.3%
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
231 
종합여행업
162 

Length

Max length5
Median length4
Mean length4.4122137
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 231
58.8%
종합여행업 162
41.2%

Length

2024-05-11T08:01:02.762161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:01:03.147261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 231
58.8%
종합여행업 162
41.2%

문화사업자구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing393
Missing (%)100.0%
Memory size3.6 KiB

지역구분명
Text

MISSING 

Distinct4
Distinct (%)100.0%
Missing389
Missing (%)99.0%
Memory size3.2 KiB
2024-05-11T08:01:03.477308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5.5
Mean length5.5
Min length5

Characters and Unicode

Total characters22
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

Unique4 ?
Unique (%)100.0%

Sample

1st row준공업지역
2nd row준주거지역
3rd row일반주거지역
4th row근린상업지역
ValueCountFrequency (%)
준공업지역 1
25.0%
준주거지역 1
25.0%
일반주거지역 1
25.0%
근린상업지역 1
25.0%
2024-05-11T08:01:04.323596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4
18.2%
4
18.2%
2
9.1%
2
9.1%
2
9.1%
2
9.1%
1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
Other values (2) 2
9.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4
18.2%
4
18.2%
2
9.1%
2
9.1%
2
9.1%
2
9.1%
1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
Other values (2) 2
9.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4
18.2%
4
18.2%
2
9.1%
2
9.1%
2
9.1%
2
9.1%
1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
Other values (2) 2
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
4
18.2%
4
18.2%
2
9.1%
2
9.1%
2
9.1%
2
9.1%
1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
Other values (2) 2
9.1%

총층수
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
381 
0
 
8
16
 
1
15
 
1
6
 
1

Length

Max length4
Median length4
Mean length3.913486
Min length1

Unique

Unique4 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 381
96.9%
0 8
 
2.0%
16 1
 
0.3%
15 1
 
0.3%
6 1
 
0.3%
3 1
 
0.3%

Length

2024-05-11T08:01:04.761299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:01:05.134707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 381
96.9%
0 8
 
2.0%
16 1
 
0.3%
15 1
 
0.3%
6 1
 
0.3%
3 1
 
0.3%

주변환경명
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing391
Missing (%)99.5%
Memory size3.2 KiB
2024-05-11T08:01:05.616294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3.5
Mean length3.5
Min length2

Characters and Unicode

Total characters7
Distinct characters6
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 (%)100.0%

Sample

1st row기타
2nd row주택가주변
ValueCountFrequency (%)
기타 1
50.0%
주택가주변 1
50.0%
2024-05-11T08:01:06.510694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2
28.6%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2
28.6%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2
28.6%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2
28.6%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

제작취급품목내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing393
Missing (%)100.0%
Memory size3.6 KiB

보험기관명
Categorical

IMBALANCE 

Distinct16
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
288 
서울보증보험
59 
한국관광협회중앙회 여행공제회
 
14
한국관광협회중앙회
 
9
서울보증보험주식회사
 
6
Other values (11)
 
17

Length

Max length18
Median length4
Mean length5.2722646
Min length4

Unique

Unique7 ?
Unique (%)1.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 288
73.3%
서울보증보험 59
 
15.0%
한국관광협회중앙회 여행공제회 14
 
3.6%
한국관광협회중앙회 9
 
2.3%
서울보증보험주식회사 6
 
1.5%
서울보증보험(5천만원) 3
 
0.8%
서울보증보험(50,000,000) 3
 
0.8%
서울보증보험(주) 2
 
0.5%
한국여행업협회 2
 
0.5%
서울보증보험(5천만) 1
 
0.3%
Other values (6) 6
 
1.5%

Length

2024-05-11T08:01:07.124569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 288
70.6%
서울보증보험 59
 
14.5%
한국관광협회중앙회 23
 
5.6%
여행공제회 14
 
3.4%
서울보증보험주식회사 6
 
1.5%
서울보증보험(5천만원 3
 
0.7%
서울보증보험(50,000,000 3
 
0.7%
한국여행업협회 2
 
0.5%
서울보증보험(주 2
 
0.5%
서울보증보험(5천만 1
 
0.2%
Other values (7) 7
 
1.7%

건물용도명
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing389
Missing (%)99.0%
Memory size3.2 KiB
2024-05-11T08:01:07.528189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4.5
Mean length4.5
Min length3

Characters and Unicode

Total characters18
Distinct characters9
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

Unique0 ?
Unique (%)0.0%

Sample

1st row근린생활시설
2nd row사무실
3rd row근린생활시설
4th row사무실
ValueCountFrequency (%)
근린생활시설 2
50.0%
사무실 2
50.0%
2024-05-11T08:01:08.502136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2
11.1%
2
11.1%
2
11.1%
2
11.1%
2
11.1%
2
11.1%
2
11.1%
2
11.1%
2
11.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2
11.1%
2
11.1%
2
11.1%
2
11.1%
2
11.1%
2
11.1%
2
11.1%
2
11.1%
2
11.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2
11.1%
2
11.1%
2
11.1%
2
11.1%
2
11.1%
2
11.1%
2
11.1%
2
11.1%
2
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2
11.1%
2
11.1%
2
11.1%
2
11.1%
2
11.1%
2
11.1%
2
11.1%
2
11.1%
2
11.1%

지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)50.0%
Missing379
Missing (%)96.4%
Infinite0
Infinite (%)0.0%
Mean3.4285714
Minimum0
Maximum15
Zeros8
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2024-05-11T08:01:08.899982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q35.25
95-th percentile13.05
Maximum15
Range15
Interquartile range (IQR)5.25

Descriptive statistics

Standard deviation5.2140975
Coefficient of variation (CV)1.5207785
Kurtosis0.52100802
Mean3.4285714
Median Absolute Deviation (MAD)0
Skewness1.3639876
Sum48
Variance27.186813
MonotonicityNot monotonic
2024-05-11T08:01:09.290893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 8
 
2.0%
15 1
 
0.3%
10 1
 
0.3%
6 1
 
0.3%
2 1
 
0.3%
3 1
 
0.3%
12 1
 
0.3%
(Missing) 379
96.4%
ValueCountFrequency (%)
0 8
2.0%
2 1
 
0.3%
3 1
 
0.3%
6 1
 
0.3%
10 1
 
0.3%
12 1
 
0.3%
15 1
 
0.3%
ValueCountFrequency (%)
15 1
 
0.3%
12 1
 
0.3%
10 1
 
0.3%
6 1
 
0.3%
3 1
 
0.3%
2 1
 
0.3%
0 8
2.0%

지하층수
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
382 
0
 
8
1
 
2
5
 
1

Length

Max length4
Median length4
Mean length3.9160305
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 382
97.2%
0 8
 
2.0%
1 2
 
0.5%
5 1
 
0.3%

Length

2024-05-11T08:01:09.863396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:01:10.434734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 382
97.2%
0 8
 
2.0%
1 2
 
0.5%
5 1
 
0.3%

객실수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
386 
0
 
7

Length

Max length4
Median length4
Mean length3.9465649
Min length1

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> 386
98.2%
0 7
 
1.8%

Length

2024-05-11T08:01:10.815490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:01:11.117477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 386
98.2%
0 7
 
1.8%

건축연면적
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
386 
0
 
7

Length

Max length4
Median length4
Mean length3.9465649
Min length1

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> 386
98.2%
0 7
 
1.8%

Length

2024-05-11T08:01:11.718256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:01:12.201949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 386
98.2%
0 7
 
1.8%

영문상호명
Text

MISSING 

Distinct39
Distinct (%)100.0%
Missing354
Missing (%)90.1%
Memory size3.2 KiB
2024-05-11T08:01:12.827159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length26
Mean length19.410256
Min length10

Characters and Unicode

Total characters757
Distinct characters49
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)100.0%

Sample

1st rowDowoo Travel Service Co., Ltd.
2nd rowNissho Korea Tour
3rd rowHan Gang Express Tourism
4th rowGSDATA Travel Co.
5th rowSp Travel.
ValueCountFrequency (%)
co 18
 
13.8%
ltd 17
 
13.1%
travel 13
 
10.0%
tour 13
 
10.0%
korea 5
 
3.8%
international 3
 
2.3%
co.,ltd 2
 
1.5%
design 2
 
1.5%
express 2
 
1.5%
global 2
 
1.5%
Other values (50) 53
40.8%
2024-05-11T08:01:14.182295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
95
 
12.5%
T 44
 
5.8%
o 40
 
5.3%
. 38
 
5.0%
L 34
 
4.5%
C 29
 
3.8%
e 28
 
3.7%
r 27
 
3.6%
a 27
 
3.6%
E 26
 
3.4%
Other values (39) 369
48.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 331
43.7%
Lowercase Letter 272
35.9%
Space Separator 95
 
12.5%
Other Punctuation 59
 
7.8%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T 44
13.3%
L 34
10.3%
C 29
8.8%
E 26
 
7.9%
O 26
 
7.9%
A 25
 
7.6%
R 23
 
6.9%
N 20
 
6.0%
I 17
 
5.1%
D 15
 
4.5%
Other values (13) 72
21.8%
Lowercase Letter
ValueCountFrequency (%)
o 40
14.7%
e 28
10.3%
r 27
9.9%
a 27
9.9%
t 24
8.8%
d 19
 
7.0%
n 18
 
6.6%
l 13
 
4.8%
s 11
 
4.0%
g 11
 
4.0%
Other values (12) 54
19.9%
Other Punctuation
ValueCountFrequency (%)
. 38
64.4%
, 19
32.2%
& 2
 
3.4%
Space Separator
ValueCountFrequency (%)
95
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 603
79.7%
Common 154
 
20.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
T 44
 
7.3%
o 40
 
6.6%
L 34
 
5.6%
C 29
 
4.8%
e 28
 
4.6%
r 27
 
4.5%
a 27
 
4.5%
E 26
 
4.3%
O 26
 
4.3%
A 25
 
4.1%
Other values (35) 297
49.3%
Common
ValueCountFrequency (%)
95
61.7%
. 38
 
24.7%
, 19
 
12.3%
& 2
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 757
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
95
 
12.5%
T 44
 
5.8%
o 40
 
5.3%
. 38
 
5.0%
L 34
 
4.5%
C 29
 
3.8%
e 28
 
3.7%
r 27
 
3.6%
a 27
 
3.6%
E 26
 
3.4%
Other values (39) 369
48.7%

영문상호주소
Categorical

IMBALANCE 

Distinct7
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
354 
GENERAL TRAVEL BUSINESS
 
26
General Travel Business
 
8
General travel business
 
2
GENERAL TRAVEL BUSINESS
 
1
Other values (2)
 
2

Length

Max length26
Median length4
Mean length5.8982188
Min length4

Unique

Unique3 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 354
90.1%
GENERAL TRAVEL BUSINESS 26
 
6.6%
General Travel Business 8
 
2.0%
General travel business 2
 
0.5%
GENERAL TRAVEL BUSINESS 1
 
0.3%
GENERAL TRAVEL BUSINESS 1
 
0.3%
Genaral Travel Business 1
 
0.3%

Length

2024-05-11T08:01:14.703416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:01:15.131047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 354
75.2%
travel 39
 
8.3%
business 39
 
8.3%
general 38
 
8.1%
genaral 1
 
0.2%

선박총톤수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
386 
0
 
7

Length

Max length4
Median length4
Mean length3.9465649
Min length1

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> 386
98.2%
0 7
 
1.8%

Length

2024-05-11T08:01:15.590310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:01:15.942272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 386
98.2%
0 7
 
1.8%

선박척수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
386 
0
 
7

Length

Max length4
Median length4
Mean length3.9465649
Min length1

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> 386
98.2%
0 7
 
1.8%

Length

2024-05-11T08:01:16.410880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:01:16.755712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 386
98.2%
0 7
 
1.8%

선박제원
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing393
Missing (%)100.0%
Memory size3.6 KiB

무대면적
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
386 
0
 
7

Length

Max length4
Median length4
Mean length3.9465649
Min length1

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> 386
98.2%
0 7
 
1.8%

Length

2024-05-11T08:01:17.204541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:01:17.550286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 386
98.2%
0 7
 
1.8%

좌석수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
386 
0
 
7

Length

Max length4
Median length4
Mean length3.9465649
Min length1

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> 386
98.2%
0 7
 
1.8%

Length

2024-05-11T08:01:17.971475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:01:18.371237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 386
98.2%
0 7
 
1.8%

기념품종류
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing393
Missing (%)100.0%
Memory size3.6 KiB

회의실별동시수용인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
386 
0
 
7

Length

Max length4
Median length4
Mean length3.9465649
Min length1

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> 386
98.2%
0 7
 
1.8%

Length

2024-05-11T08:01:18.818103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:01:19.219894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 386
98.2%
0 7
 
1.8%

시설면적
Real number (ℝ)

MISSING  ZEROS 

Distinct47
Distinct (%)82.5%
Missing336
Missing (%)85.5%
Infinite0
Infinite (%)0.0%
Mean43.747193
Minimum0
Maximum291.5
Zeros8
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2024-05-11T08:01:19.678861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q120
median30.7
Q352
95-th percentile113.944
Maximum291.5
Range291.5
Interquartile range (IQR)32

Descriptive statistics

Standard deviation51.905076
Coefficient of variation (CV)1.1864779
Kurtosis12.06165
Mean43.747193
Median Absolute Deviation (MAD)16.5
Skewness3.128123
Sum2493.59
Variance2694.1369
MonotonicityNot monotonic
2024-05-11T08:01:20.219410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
0.0 8
 
2.0%
20.0 3
 
0.8%
27.37 2
 
0.5%
29.0 1
 
0.3%
22.0 1
 
0.3%
47.0 1
 
0.3%
52.0 1
 
0.3%
30.7 1
 
0.3%
44.11 1
 
0.3%
30.77 1
 
0.3%
Other values (37) 37
 
9.4%
(Missing) 336
85.5%
ValueCountFrequency (%)
0.0 8
2.0%
3.96 1
 
0.3%
6.6 1
 
0.3%
8.0 1
 
0.3%
10.07 1
 
0.3%
14.0 1
 
0.3%
18.0 1
 
0.3%
20.0 3
 
0.8%
22.0 1
 
0.3%
22.05 1
 
0.3%
ValueCountFrequency (%)
291.5 1
0.3%
246.0 1
0.3%
127.0 1
0.3%
110.68 1
0.3%
87.8 1
0.3%
86.0 1
0.3%
85.0 1
0.3%
72.25 1
0.3%
70.0 1
0.3%
66.1 1
0.3%

놀이기구수내역
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing393
Missing (%)100.0%
Memory size3.6 KiB

놀이시설수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
386 
0
 
7

Length

Max length4
Median length4
Mean length3.9465649
Min length1

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> 386
98.2%
0 7
 
1.8%

Length

2024-05-11T08:01:20.751918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:01:21.076887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 386
98.2%
0 7
 
1.8%

방송시설유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing393
Missing (%)100.0%
Memory size3.6 KiB

발전시설유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing393
Missing (%)100.0%
Memory size3.6 KiB

의무실유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing393
Missing (%)100.0%
Memory size3.6 KiB

안내소유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing393
Missing (%)100.0%
Memory size3.6 KiB

기획여행보험시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
392 
20170605
 
1

Length

Max length8
Median length4
Mean length4.0101781
Min length4

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 392
99.7%
20170605 1
 
0.3%

Length

2024-05-11T08:01:21.448376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:01:21.834230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 392
99.7%
20170605 1
 
0.3%

기획여행보험종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
392 
20180604
 
1

Length

Max length8
Median length4
Mean length4.0101781
Min length4

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 392
99.7%
20180604 1
 
0.3%

Length

2024-05-11T08:01:22.357377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:01:22.712598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 392
99.7%
20180604 1
 
0.3%

자본금
Real number (ℝ)

MISSING 

Distinct29
Distinct (%)20.4%
Missing251
Missing (%)63.9%
Infinite0
Infinite (%)0.0%
Mean2.2239435 × 108
Minimum0
Maximum1.5 × 109
Zeros1
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2024-05-11T08:01:23.064493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1 × 108
Q11 × 108
median2 × 108
Q32.2799635 × 108
95-th percentile4 × 108
Maximum1.5 × 109
Range1.5 × 109
Interquartile range (IQR)1.2799635 × 108

Descriptive statistics

Standard deviation1.8867597 × 108
Coefficient of variation (CV)0.84838471
Kurtosis20.750742
Mean2.2239435 × 108
Median Absolute Deviation (MAD)1 × 108
Skewness3.9540625
Sum3.1579998 × 1010
Variance3.5598621 × 1016
MonotonicityNot monotonic
2024-05-11T08:01:23.685908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
100000000 46
 
11.7%
200000000 43
 
10.9%
350000000 16
 
4.1%
300000000 6
 
1.5%
210000000 4
 
1.0%
400000000 2
 
0.5%
700000000 2
 
0.5%
110000000 2
 
0.5%
325355117 1
 
0.3%
103000000 1
 
0.3%
Other values (19) 19
 
4.8%
(Missing) 251
63.9%
ValueCountFrequency (%)
0 1
 
0.3%
100000000 46
11.7%
100300000 1
 
0.3%
103000000 1
 
0.3%
110000000 2
 
0.5%
115371721 1
 
0.3%
150000000 1
 
0.3%
155000000 1
 
0.3%
167476934 1
 
0.3%
200000000 43
10.9%
ValueCountFrequency (%)
1500000000 1
 
0.3%
1200000000 1
 
0.3%
1000000000 1
 
0.3%
700000000 2
 
0.5%
500000000 1
 
0.3%
480000000 1
 
0.3%
400000000 2
 
0.5%
350000000 16
4.1%
329589073 1
 
0.3%
325355117 1
 
0.3%

보험시작일자
Real number (ℝ)

MISSING 

Distinct105
Distinct (%)97.2%
Missing285
Missing (%)72.5%
Infinite0
Infinite (%)0.0%
Mean20175857
Minimum20100725
Maximum20211103
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2024-05-11T08:01:24.342960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20100725
5-th percentile20110783
Q120170222
median20181026
Q320190821
95-th percentile20200580
Maximum20211103
Range110378
Interquartile range (IQR)20598.75

Descriptive statistics

Standard deviation23914.405
Coefficient of variation (CV)0.0011852981
Kurtosis2.3729228
Mean20175857
Median Absolute Deviation (MAD)10048.5
Skewness-1.583555
Sum2.1789925 × 109
Variance5.7189875 × 108
MonotonicityNot monotonic
2024-05-11T08:01:24.857669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20190701 2
 
0.5%
20190611 2
 
0.5%
20190827 2
 
0.5%
20170912 1
 
0.3%
20180416 1
 
0.3%
20200415 1
 
0.3%
20180620 1
 
0.3%
20200402 1
 
0.3%
20190207 1
 
0.3%
20190510 1
 
0.3%
Other values (95) 95
 
24.2%
(Missing) 285
72.5%
ValueCountFrequency (%)
20100725 1
0.3%
20101006 1
0.3%
20110118 1
0.3%
20110206 1
0.3%
20110419 1
0.3%
20110713 1
0.3%
20110914 1
0.3%
20120806 1
0.3%
20130718 1
0.3%
20140721 1
0.3%
ValueCountFrequency (%)
20211103 1
0.3%
20210721 1
0.3%
20210311 1
0.3%
20201107 1
0.3%
20201005 1
0.3%
20200608 1
0.3%
20200528 1
0.3%
20200415 1
0.3%
20200402 1
0.3%
20200401 1
0.3%

보험종료일자
Real number (ℝ)

MISSING 

Distinct105
Distinct (%)97.2%
Missing285
Missing (%)72.5%
Infinite0
Infinite (%)0.0%
Mean20185770
Minimum20110725
Maximum20221103
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2024-05-11T08:01:25.502974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20110725
5-th percentile20120783
Q120180221
median20191024
Q320200820
95-th percentile20210580
Maximum20221103
Range110378
Interquartile range (IQR)20599.5

Descriptive statistics

Standard deviation23981.792
Coefficient of variation (CV)0.0011880543
Kurtosis2.2972887
Mean20185770
Median Absolute Deviation (MAD)10049
Skewness-1.567096
Sum2.1800632 × 109
Variance5.7512636 × 108
MonotonicityNot monotonic
2024-05-11T08:01:26.182903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20200630 2
 
0.5%
20200610 2
 
0.5%
20190416 2
 
0.5%
20170205 1
 
0.3%
20200829 1
 
0.3%
20200521 1
 
0.3%
20210414 1
 
0.3%
20190620 1
 
0.3%
20210401 1
 
0.3%
20200206 1
 
0.3%
Other values (95) 95
 
24.2%
(Missing) 285
72.5%
ValueCountFrequency (%)
20110725 1
0.3%
20111005 1
0.3%
20120118 1
0.3%
20120206 1
0.3%
20120418 1
0.3%
20120713 1
0.3%
20120914 1
0.3%
20130806 1
0.3%
20140717 1
0.3%
20150721 1
0.3%
ValueCountFrequency (%)
20221103 1
0.3%
20220720 1
0.3%
20220311 1
0.3%
20211106 1
0.3%
20211004 1
0.3%
20210608 1
0.3%
20210527 1
0.3%
20210414 1
0.3%
20210401 1
0.3%
20210331 1
0.3%

부대시설내역
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing393
Missing (%)100.0%
Memory size3.6 KiB

시설규모
Real number (ℝ)

MISSING  ZEROS 

Distinct37
Distinct (%)64.9%
Missing336
Missing (%)85.5%
Infinite0
Infinite (%)0.0%
Mean43.719298
Minimum0
Maximum292
Zeros8
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2024-05-11T08:01:26.813057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q120
median31
Q352
95-th percentile114.2
Maximum292
Range292
Interquartile range (IQR)32

Descriptive statistics

Standard deviation51.953191
Coefficient of variation (CV)1.1883354
Kurtosis12.09675
Mean43.719298
Median Absolute Deviation (MAD)16
Skewness3.1339454
Sum2492
Variance2699.1341
MonotonicityNot monotonic
2024-05-11T08:01:27.433006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
0 8
 
2.0%
20 3
 
0.8%
27 3
 
0.8%
44 3
 
0.8%
22 2
 
0.5%
23 2
 
0.5%
29 2
 
0.5%
31 2
 
0.5%
47 2
 
0.5%
62 2
 
0.5%
Other values (27) 28
 
7.1%
(Missing) 336
85.5%
ValueCountFrequency (%)
0 8
2.0%
4 1
 
0.3%
7 1
 
0.3%
8 1
 
0.3%
10 1
 
0.3%
14 1
 
0.3%
18 1
 
0.3%
20 3
 
0.8%
22 2
 
0.5%
23 2
 
0.5%
ValueCountFrequency (%)
292 1
0.3%
246 1
0.3%
127 1
0.3%
111 1
0.3%
88 1
0.3%
86 1
0.3%
85 1
0.3%
72 1
0.3%
70 1
0.3%
66 2
0.5%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명문화사업자구분명지역구분명총층수주변환경명제작취급품목내용보험기관명건물용도명지상층수지하층수객실수건축연면적영문상호명영문상호주소선박총톤수선박척수선박제원무대면적좌석수기념품종류회의실별동시수용인원시설면적놀이기구수내역놀이시설수방송시설유무발전시설유무의무실유무안내소유무기획여행보험시작일자기획여행보험종료일자자본금보험시작일자보험종료일자부대시설내역시설규모
03150000CDFI226004199000000119900115<NA>1영업/정상13영업중<NA><NA><NA><NA>02-2602-1960<NA><NA>서울특별시 강서구 방화동 820번지서울특별시 강서구 금낭화로 170, 1층 (방화동)07508(주)김포운송2020-05-15 15:18:40U2020-05-19 02:40:00.0<NA>183545.236313453136.448166종합여행업<NA><NA><NA><NA><NA>서울보증보험<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>15000000002019033120200330<NA><NA>
13150000CDFI226004199800000119980914<NA>1영업/정상13영업중<NA><NA><NA><NA>02-3663-1245<NA>157010서울특별시 강서구 화곡동 24-571번지 천일빌딩 601호서울특별시 강서구 화곡로 266, 601호 (화곡동, 천일빌딩)157010(주)강서관광여행사2017-05-18 13:04:50I2018-08-31 23:59:59.0<NA>186412.970138449581.397185종합여행업<NA><NA><NA><NA><NA>서울보증보험<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>4000000002017022320180222<NA><NA>
23150000CDFI226004199800000219980716<NA>1영업/정상13영업중<NA><NA><NA><NA>02-3272-1411<NA>157804서울특별시 강서구 가양동 449-21번지 한화비즈메트로2차서울특별시 강서구 양천로 551-24 (가양동, 1203)07532(주)도우관광2016-08-08 10:42:01I2018-08-31 23:59:59.0<NA>187733.160921450747.952249종합여행업<NA><NA><NA><NA><NA>한국관광협회중앙회<NA><NA><NA><NA><NA>Dowoo Travel Service Co., Ltd.GENERAL TRAVEL BUSINESS<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>3500000002011091420120914<NA><NA>
33150000CDFI22600420000000012000-01-10<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강서구 마곡동 773 힐스테이트에코마곡역서울특별시 강서구 마곡중앙로 76, 힐스테이트에코마곡역 307호 (마곡동)07801주식회사 대웅여행사2024-03-29 11:03:57U2023-12-02 21:01:00.0<NA>184691.008477450919.92508<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>
43150000CDFI226004200100000120010328<NA>3폐업3폐업20181115<NA><NA><NA>02-730-1501<NA>157864서울특별시 강서구 염창동 281-22번지 염창한화꿈에그린 105-301서울특별시 강서구 공항대로75길 17 (염창동,염창한화꿈에그린 105-301)<NA>(주)덕양로지스틱2018-11-15 16:17:53U2018-11-17 02:36:35.0<NA>188720.150596449554.356732종합여행업<NA><NA><NA><NA><NA>한국관광협회중앙회<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>3500000002010072520110725<NA><NA>
53150000CDFI226004200500000120050705<NA>1영업/정상13영업중<NA><NA><NA><NA>02-725-7824<NA>157853서울특별시 강서구 방화동 621-24번지 동아빌딩 301호서울특별시 강서구 개화동로 565 (방화동,동아빌딩 301호)<NA>(주)수트래블2016-08-08 11:08:37I2018-08-31 23:59:59.0<NA>182914.770763451105.609041종합여행업<NA><NA><NA><NA><NA>서울보증보험<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2010100620111005<NA><NA>
63150000CDFI226004200600000120060124<NA>1영업/정상13영업중<NA><NA><NA><NA>2666-0114<NA>157812서울특별시 강서구 공항동 69-29서울특별시 강서구 남부순환로 29 (공항동)<NA>(주)에이엔씨인터내셔날2021-02-18 09:24:56U2021-02-20 02:40:00.0<NA>182988.023478450782.774565종합여행업<NA><NA><NA><NA><NA>한국관광협회중앙회 여행공제회<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>5000000002011020620120206<NA><NA>
73150000CDFI226004200700000120071130<NA>3폐업3폐업20120507<NA><NA><NA>3664-1346<NA>157030서울특별시 강서구 등촌동 673-6번지 등촌성원상떼뷰 오피스텔 510호서울특별시 강서구 공항대로 291 (등촌동,등촌성원상떼뷰 오피스텔 510호)<NA>(주)트래블칼라2012-05-07 10:18:31I2018-08-31 23:59:59.0<NA>185796.522249450735.884713종합여행업<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>350000000<NA><NA><NA><NA>
83150000CDFI226004200700000220070807<NA>1영업/정상13영업중<NA><NA><NA><NA>499-9555<NA>157818서울특별시 강서구 공항동 686-2번지 에스디빌딩 3층서울특별시 강서구 송정로 4 (공항동,에스디빌딩 3층)<NA>(주)서울레저항공2012-07-04 09:16:47I2018-08-31 23:59:59.0<NA>183373.705347450387.98369종합여행업<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>480000000<NA><NA><NA><NA>
93150000CDFI226004200800000120081226<NA>3폐업3폐업20151230<NA><NA><NA>739-1312<NA>157861서울특별시 강서구 염창동 240-21번지 우림블루나인 비즈니스센터 A동 2501호서울특별시 강서구 양천로 583 (염창동,우림블루나인 비즈니스센터 A동 2501호)<NA>(주)동성그린투어2015-12-30 14:58:56I2018-08-31 23:59:59.0<NA>187952.560028450562.020226종합여행업<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>350000000<NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명문화사업자구분명지역구분명총층수주변환경명제작취급품목내용보험기관명건물용도명지상층수지하층수객실수건축연면적영문상호명영문상호주소선박총톤수선박척수선박제원무대면적좌석수기념품종류회의실별동시수용인원시설면적놀이기구수내역놀이시설수방송시설유무발전시설유무의무실유무안내소유무기획여행보험시작일자기획여행보험종료일자자본금보험시작일자보험종료일자부대시설내역시설규모
3833150000CDFI22600420240000202024-04-02<NA>1영업/정상13영업중<NA><NA><NA><NA>02-6341-5050<NA><NA>서울특별시 강서구 가양동 449-12서울특별시 강서구 양천로 547, 705-6호 (가양동)07532주식회사 플래닝5012024-04-02 12:57:59I2023-12-04 00:04:00.0<NA>187582.144681450728.898515<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>
3843150000CDFI22600420240000212023-08-14<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강서구 염창동 240-21 우림블루나인비즈니스센터서울특별시 강서구 양천로 583, 우림블루나인비즈니스센터 A동 1904호 (염창동)07547주식회사 제이엠커넥티드2024-04-04 15:52:21I2023-12-04 00:07:00.0<NA>187952.560028450562.020226<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>
3853150000CDFI22600420240000222018-10-23<NA>1영업/정상13영업중<NA><NA><NA><NA>02-1800-4826<NA><NA>서울특별시 강서구 등촌동 773서울특별시 강서구 양천로 364 (등촌동)07573에이치디투어존 주식회사2024-04-16 09:31:06I2023-12-03 23:08:00.0<NA>186026.901278451688.493849<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>
3863150000CDFI22600420240000232023-06-22<NA>1영업/정상13영업중<NA><NA><NA><NA>02-565-5277<NA><NA>서울특별시 강서구 마곡동 800-4 발산W타워서울특별시 강서구 공항대로 222, 발산W타워 713호 (마곡동)07806엘리세노2024-04-16 18:59:07I2023-12-03 23:08:00.0<NA>185104.201678450725.785084<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>
3873150000CDFI22600420240000242024-04-19<NA>1영업/정상13영업중<NA><NA><NA><NA>070-7119-9807<NA><NA>서울특별시 강서구 마곡동 797 에이스타워 마곡서울특별시 강서구 공항대로 237, 에이스타워 마곡 911~914호 (마곡동)07803주식회사 지앤엘에스티2024-04-24 15:50:56U2023-12-03 22:07:00.0<NA>185253.478151450811.037606<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>
3883150000CDFI22600420240000252024-04-19<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강서구 마곡동 799-3 문영 퀸즈파크12차서울특별시 강서구 공항대로 194, 문영 퀸즈파크12차 1204호 (마곡동)07631스카이플래티늄항공 주식회사2024-04-19 14:45:03I2023-12-03 22:01:00.0<NA>184825.67632450763.336623<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>
3893150000CDFI22600420240000262024-04-25<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강서구 마곡동 774-2 보타닉파크타워2서울특별시 강서구 공항대로 213, 보타닉파크타워2 302-1호 (마곡동)07802(주)제이아이씨투어2024-04-25 18:05:11I2023-12-03 22:07:00.0<NA>185032.421148450836.071292<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>
3903150000CDFI22600420240000272024-04-30<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강서구 마곡동 798-3 747서울특별시 강서구 공항대로 168, 747 1304호 (마곡동)07807나인투어2024-04-30 10:12:23I2023-12-05 00:02:00.0<NA>184572.413912450792.481823<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>
3913150000CDFI22600420240000282024-05-02<NA>1영업/정상13영업중<NA><NA><NA><NA>02-778-7399<NA><NA>서울특별시 강서구 마곡동 759-1 두산더랜드타워서울특별시 강서구 마곡서로 152, 두산더랜드타워 B동 923호 (마곡동)07788주식회사 스캔코리아항공2024-05-02 11:55:38I2023-12-05 00:04:00.0<NA>184526.084368451722.650631<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>
3923150000CDFI22600420240000292024-05-02<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강서구 마곡동 797-10 엠팰리체서울특별시 강서구 마곡동로4길 15, 엠팰리체 612호 (마곡동)07803주식회사 정명여행사2024-05-07 14:33:07U2023-12-05 00:09:00.0<NA>185373.875552450852.521846<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>