Overview

Dataset statistics

Number of variables60
Number of observations9872
Missing cells252305
Missing cells (%)42.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.8 MiB
Average record size in memory514.0 B

Variable types

Numeric13
Text9
DateTime7
Categorical19
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
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-16050/S/1/datasetView.do

Alerts

지역구분명 is highly imbalanced (88.9%)Imbalance
주변환경명 is highly imbalanced (90.5%)Imbalance
건물용도명 is highly imbalanced (86.9%)Imbalance
건축연면적 is highly imbalanced (59.9%)Imbalance
영문상호주소 is highly imbalanced (95.9%)Imbalance
인허가취소일자 has 8799 (89.1%) missing valuesMissing
폐업일자 has 5101 (51.7%) missing valuesMissing
휴업시작일자 has 9817 (99.4%) missing valuesMissing
휴업종료일자 has 9817 (99.4%) missing valuesMissing
재개업일자 has 9872 (100.0%) missing valuesMissing
전화번호 has 3071 (31.1%) missing valuesMissing
소재지면적 has 9872 (100.0%) missing valuesMissing
소재지우편번호 has 4492 (45.5%) missing valuesMissing
도로명주소 has 391 (4.0%) missing valuesMissing
도로명우편번호 has 4019 (40.7%) missing valuesMissing
업태구분명 has 9872 (100.0%) missing valuesMissing
좌표정보(X) has 294 (3.0%) missing valuesMissing
좌표정보(Y) has 294 (3.0%) missing valuesMissing
총층수 has 7566 (76.6%) missing valuesMissing
제작취급품목내용 has 9872 (100.0%) missing valuesMissing
보험기관명 has 5686 (57.6%) missing valuesMissing
지상층수 has 7487 (75.8%) missing valuesMissing
지하층수 has 7655 (77.5%) missing valuesMissing
영문상호명 has 9664 (97.9%) missing valuesMissing
선박제원 has 9872 (100.0%) missing valuesMissing
기념품종류 has 9872 (100.0%) missing valuesMissing
시설면적 has 6951 (70.4%) missing valuesMissing
놀이기구수내역 has 9872 (100.0%) missing valuesMissing
방송시설유무 has 9872 (100.0%) missing valuesMissing
발전시설유무 has 9872 (100.0%) missing valuesMissing
의무실유무 has 9872 (100.0%) missing valuesMissing
안내소유무 has 9872 (100.0%) missing valuesMissing
기획여행보험시작일자 has 9801 (99.3%) missing valuesMissing
기획여행보험종료일자 has 9801 (99.3%) missing valuesMissing
자본금 has 5136 (52.0%) missing valuesMissing
보험시작일자 has 5565 (56.4%) missing valuesMissing
보험종료일자 has 5483 (55.5%) missing valuesMissing
부대시설내역 has 9872 (100.0%) missing valuesMissing
시설규모 has 6951 (70.4%) missing valuesMissing
시설면적 is highly skewed (γ1 = 28.96027572)Skewed
자본금 is highly skewed (γ1 = 36.07423817)Skewed
시설규모 is highly skewed (γ1 = 28.96042191)Skewed
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 1970 (20.0%) zerosZeros
지상층수 has 1965 (19.9%) zerosZeros
지하층수 has 1997 (20.2%) zerosZeros
시설면적 has 2158 (21.9%) zerosZeros
자본금 has 413 (4.2%) zerosZeros
시설규모 has 2158 (21.9%) zerosZeros

Reproduction

Analysis started2024-05-11 06:14:26.664132
Analysis finished2024-05-11 06:14:31.721088
Duration5.06 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Real number (ℝ)

Distinct25
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3108765.2
Minimum3000000
Maximum3240000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size86.9 KiB
2024-05-11T15:14:31.819785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3000000
Q13010000
median3130000
Q33210000
95-th percentile3230000
Maximum3240000
Range240000
Interquartile range (IQR)200000

Descriptive statistics

Standard deviation90542.019
Coefficient of variation (CV)0.029124753
Kurtosis-1.6749232
Mean3108765.2
Median Absolute Deviation (MAD)90000
Skewness-0.0068304843
Sum3.068973 × 1010
Variance8.1978571 × 109
MonotonicityNot monotonic
2024-05-11T15:14:32.142756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
3000000 1830
18.5%
3010000 1597
16.2%
3220000 1361
13.8%
3210000 873
8.8%
3130000 871
8.8%
3180000 530
 
5.4%
3230000 365
 
3.7%
3150000 294
 
3.0%
3120000 231
 
2.3%
3020000 216
 
2.2%
Other values (15) 1704
17.3%
ValueCountFrequency (%)
3000000 1830
18.5%
3010000 1597
16.2%
3020000 216
 
2.2%
3030000 126
 
1.3%
3040000 143
 
1.4%
3050000 120
 
1.2%
3060000 65
 
0.7%
3070000 99
 
1.0%
3080000 66
 
0.7%
3090000 50
 
0.5%
ValueCountFrequency (%)
3240000 133
 
1.3%
3230000 365
 
3.7%
3220000 1361
13.8%
3210000 873
8.8%
3200000 100
 
1.0%
3190000 82
 
0.8%
3180000 530
 
5.4%
3170000 177
 
1.8%
3160000 198
 
2.0%
3150000 294
 
3.0%
Distinct2780
Distinct (%)28.2%
Missing0
Missing (%)0.0%
Memory size77.3 KiB
2024-05-11T15:14:32.493854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters197440
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

Unique809 ?
Unique (%)8.2%

Sample

1st rowCDFI2260022006000002
2nd rowCDFI2260022017000001
3rd rowCDFI2260022024000007
4th rowCDFI2260022001000001
5th rowCDFI2260022014000030
ValueCountFrequency (%)
cdfi2260022023000001 25
 
0.3%
cdfi2260022021000001 24
 
0.2%
cdfi2260022024000001 24
 
0.2%
cdfi2260022022000003 23
 
0.2%
cdfi2260022022000001 23
 
0.2%
cdfi2260022023000002 23
 
0.2%
cdfi2260022020000002 23
 
0.2%
cdfi2260022021000003 22
 
0.2%
cdfi2260022022000002 22
 
0.2%
cdfi2260022023000003 22
 
0.2%
Other values (2770) 9641
97.7%
2024-05-11T15:14:33.137715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 76133
38.6%
2 43486
22.0%
6 12154
 
6.2%
C 9872
 
5.0%
D 9872
 
5.0%
F 9872
 
5.0%
I 9872
 
5.0%
1 9344
 
4.7%
9 4122
 
2.1%
3 3184
 
1.6%
Other values (4) 9529
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 157952
80.0%
Uppercase Letter 39488
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 76133
48.2%
2 43486
27.5%
6 12154
 
7.7%
1 9344
 
5.9%
9 4122
 
2.6%
3 3184
 
2.0%
4 2702
 
1.7%
5 2436
 
1.5%
7 2264
 
1.4%
8 2127
 
1.3%
Uppercase Letter
ValueCountFrequency (%)
C 9872
25.0%
D 9872
25.0%
F 9872
25.0%
I 9872
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 157952
80.0%
Latin 39488
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 76133
48.2%
2 43486
27.5%
6 12154
 
7.7%
1 9344
 
5.9%
9 4122
 
2.6%
3 3184
 
2.0%
4 2702
 
1.7%
5 2436
 
1.5%
7 2264
 
1.4%
8 2127
 
1.3%
Latin
ValueCountFrequency (%)
C 9872
25.0%
D 9872
25.0%
F 9872
25.0%
I 9872
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 197440
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 76133
38.6%
2 43486
22.0%
6 12154
 
6.2%
C 9872
 
5.0%
D 9872
 
5.0%
F 9872
 
5.0%
I 9872
 
5.0%
1 9344
 
4.7%
9 4122
 
2.1%
3 3184
 
1.6%
Other values (4) 9529
 
4.8%
Distinct5082
Distinct (%)51.5%
Missing0
Missing (%)0.0%
Memory size77.3 KiB
Minimum1982-09-15 00:00:00
Maximum2024-05-02 00:00:00
2024-05-11T15:14:33.389767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:14:33.700583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Date

MISSING 

Distinct218
Distinct (%)20.3%
Missing8799
Missing (%)89.1%
Memory size77.3 KiB
Minimum2002-09-02 00:00:00
Maximum2023-08-16 00:00:00
2024-05-11T15:14:33.923265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:14:34.395747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size77.3 KiB
3
4160 
1
3277 
4
1926 
5
463 
2
 
46

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 4160
42.1%
1 3277
33.2%
4 1926
19.5%
5 463
 
4.7%
2 46
 
0.5%

Length

2024-05-11T15:14:34.663829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:34.852625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 4160
42.1%
1 3277
33.2%
4 1926
19.5%
5 463
 
4.7%
2 46
 
0.5%

영업상태명
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size77.3 KiB
폐업
4160 
영업/정상
3277 
취소/말소/만료/정지/중지
1926 
제외/삭제/전출
463 
휴업
 
46

Length

Max length14
Median length8
Mean length5.6184157
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 4160
42.1%
영업/정상 3277
33.2%
취소/말소/만료/정지/중지 1926
19.5%
제외/삭제/전출 463
 
4.7%
휴업 46
 
0.5%

Length

2024-05-11T15:14:35.043255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:35.205108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 4160
42.1%
영업/정상 3277
33.2%
취소/말소/만료/정지/중지 1926
19.5%
제외/삭제/전출 463
 
4.7%
휴업 46
 
0.5%
Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size77.3 KiB
03
4160 
13
3265 
31
1396 
15
463 
30
 
281
Other values (7)
 
307

Length

Max length4
Median length2
Mean length2.0004052
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
03 4160
42.1%
13 3265
33.1%
31 1396
 
14.1%
15 463
 
4.7%
30 281
 
2.8%
35 175
 
1.8%
32 54
 
0.5%
02 46
 
0.5%
25 14
 
0.1%
14 10
 
0.1%
Other values (2) 8
 
0.1%

Length

2024-05-11T15:14:35.415210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
03 4160
42.1%
13 3265
33.1%
31 1396
 
14.1%
15 463
 
4.7%
30 281
 
2.8%
35 175
 
1.8%
32 54
 
0.5%
02 46
 
0.5%
25 14
 
0.1%
14 10
 
0.1%
Other values (2) 8
 
0.1%
Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size77.3 KiB
폐업
4160 
영업중
3265 
등록취소
1396 
전출
463 
허가취소
 
281
Other values (7)
 
307

Length

Max length4
Median length3
Mean length2.7213331
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 4160
42.1%
영업중 3265
33.1%
등록취소 1396
 
14.1%
전출 463
 
4.7%
허가취소 281
 
2.8%
직권말소 175
 
1.8%
신고취소 54
 
0.5%
휴업 46
 
0.5%
영업정지 14
 
0.1%
전입 10
 
0.1%
Other values (2) 8
 
0.1%

Length

2024-05-11T15:14:35.666146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
폐업 4160
42.1%
영업중 3265
33.1%
등록취소 1396
 
14.1%
전출 463
 
4.7%
허가취소 281
 
2.8%
직권말소 175
 
1.8%
신고취소 54
 
0.5%
휴업 46
 
0.5%
영업정지 14
 
0.1%
전입 10
 
0.1%
Other values (2) 8
 
0.1%

폐업일자
Date

MISSING 

Distinct3050
Distinct (%)63.9%
Missing5101
Missing (%)51.7%
Memory size77.3 KiB
Minimum1995-05-09 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T15:14:35.938628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:14:36.187061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Date

MISSING 

Distinct50
Distinct (%)90.9%
Missing9817
Missing (%)99.4%
Memory size77.3 KiB
Minimum1998-03-16 00:00:00
Maximum2024-03-01 00:00:00
2024-05-11T15:14:36.503961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:14:36.751941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업종료일자
Date

MISSING 

Distinct49
Distinct (%)89.1%
Missing9817
Missing (%)99.4%
Memory size77.3 KiB
Minimum1998-09-15 00:00:00
Maximum2026-02-07 00:00:00
2024-05-11T15:14:37.005543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:14:37.249559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9872
Missing (%)100.0%
Memory size86.9 KiB

전화번호
Text

MISSING 

Distinct6437
Distinct (%)94.6%
Missing3071
Missing (%)31.1%
Memory size77.3 KiB
2024-05-11T15:14:37.652495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length9.6531392
Min length4

Characters and Unicode

Total characters65651
Distinct characters19
Distinct categories7 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6121 ?
Unique (%)90.0%

Sample

1st row02-975-2001
2nd row070-7691-5701
3rd row02-1599-1659
4th row02-736-9990
5th row02-2088-3522
ValueCountFrequency (%)
02 75
 
1.1%
62553017 16
 
0.2%
070 6
 
0.1%
070-4900-2339 5
 
0.1%
777-4400 4
 
0.1%
735-5174 4
 
0.1%
02-734-2611 4
 
0.1%
070-7017-2240 4
 
0.1%
02-6927-0090 4
 
0.1%
733-7500 3
 
< 0.1%
Other values (6475) 6810
98.2%
2024-05-11T15:14:38.388413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9092
13.8%
- 8844
13.5%
2 8099
12.3%
7 7696
11.7%
3 5900
9.0%
5 5494
8.4%
1 4496
6.8%
8 4342
6.6%
6 4204
6.4%
4 4135
6.3%
Other values (9) 3349
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 56498
86.1%
Dash Punctuation 8844
 
13.5%
Space Separator 182
 
0.3%
Close Punctuation 40
 
0.1%
Other Punctuation 35
 
0.1%
Math Symbol 31
 
< 0.1%
Open Punctuation 21
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9092
16.1%
2 8099
14.3%
7 7696
13.6%
3 5900
10.4%
5 5494
9.7%
1 4496
8.0%
8 4342
7.7%
6 4204
7.4%
4 4135
7.3%
9 3040
 
5.4%
Other Punctuation
ValueCountFrequency (%)
, 26
74.3%
. 5
 
14.3%
/ 4
 
11.4%
Math Symbol
ValueCountFrequency (%)
~ 30
96.8%
+ 1
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 8844
100.0%
Space Separator
ValueCountFrequency (%)
182
100.0%
Close Punctuation
ValueCountFrequency (%)
) 40
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 65651
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9092
13.8%
- 8844
13.5%
2 8099
12.3%
7 7696
11.7%
3 5900
9.0%
5 5494
8.4%
1 4496
6.8%
8 4342
6.6%
6 4204
6.4%
4 4135
6.3%
Other values (9) 3349
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 65651
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9092
13.8%
- 8844
13.5%
2 8099
12.3%
7 7696
11.7%
3 5900
9.0%
5 5494
8.4%
1 4496
6.8%
8 4342
6.6%
6 4204
6.4%
4 4135
6.3%
Other values (9) 3349
 
5.1%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9872
Missing (%)100.0%
Memory size86.9 KiB

소재지우편번호
Text

MISSING 

Distinct1566
Distinct (%)29.1%
Missing4492
Missing (%)45.5%
Memory size77.3 KiB
2024-05-11T15:14:39.016572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0572491
Min length6

Characters and Unicode

Total characters32588
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

Unique827 ?
Unique (%)15.4%

Sample

1st row139-942
2nd row150-803
3rd row120-012
4th row139-942
5th row110-111
ValueCountFrequency (%)
100170 180
 
3.3%
110070 118
 
2.2%
110130 106
 
2.0%
100180 88
 
1.6%
110111 63
 
1.2%
110061 59
 
1.1%
100814 58
 
1.1%
110858 56
 
1.0%
137856 53
 
1.0%
100101 49
 
0.9%
Other values (1556) 4550
84.6%
2024-05-11T15:14:39.906742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 9495
29.1%
0 6413
19.7%
8 3455
 
10.6%
3 2975
 
9.1%
5 2447
 
7.5%
7 2274
 
7.0%
2 2015
 
6.2%
9 1197
 
3.7%
4 1158
 
3.6%
6 851
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 32280
99.1%
Dash Punctuation 308
 
0.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 9495
29.4%
0 6413
19.9%
8 3455
 
10.7%
3 2975
 
9.2%
5 2447
 
7.6%
7 2274
 
7.0%
2 2015
 
6.2%
9 1197
 
3.7%
4 1158
 
3.6%
6 851
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 308
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 32588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 9495
29.1%
0 6413
19.7%
8 3455
 
10.6%
3 2975
 
9.1%
5 2447
 
7.5%
7 2274
 
7.0%
2 2015
 
6.2%
9 1197
 
3.7%
4 1158
 
3.6%
6 851
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 32588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 9495
29.1%
0 6413
19.7%
8 3455
 
10.6%
3 2975
 
9.1%
5 2447
 
7.5%
7 2274
 
7.0%
2 2015
 
6.2%
9 1197
 
3.7%
4 1158
 
3.6%
6 851
 
2.6%
Distinct8903
Distinct (%)90.2%
Missing0
Missing (%)0.0%
Memory size77.3 KiB
2024-05-11T15:14:40.648175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length49
Mean length28.457152
Min length8

Characters and Unicode

Total characters280929
Distinct characters614
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8390 ?
Unique (%)85.0%

Sample

1st row서울특별시 관악구 남현동 1061-18 르메이에르강남타운2
2nd row서울특별시 노원구 상계동 330-29 1018호
3rd row서울특별시 중구 순화동 5-2 순화빌딩
4th row서울특별시 노원구 상계동 709-1 은성빌딩 402호
5th row서울특별시 영등포구 당산동3가 249
ValueCountFrequency (%)
서울특별시 9863
 
18.3%
종로구 1837
 
3.4%
중구 1601
 
3.0%
강남구 1368
 
2.5%
마포구 866
 
1.6%
서초구 842
 
1.6%
영등포구 532
 
1.0%
서초동 516
 
1.0%
역삼동 471
 
0.9%
송파구 370
 
0.7%
Other values (10333) 35492
66.0%
2024-05-11T15:14:41.591712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
48635
 
17.3%
1 13064
 
4.7%
12371
 
4.4%
10308
 
3.7%
10283
 
3.7%
10162
 
3.6%
9945
 
3.5%
9891
 
3.5%
9867
 
3.5%
2 7538
 
2.7%
Other values (604) 138865
49.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 166201
59.2%
Decimal Number 57065
 
20.3%
Space Separator 48635
 
17.3%
Dash Punctuation 7386
 
2.6%
Uppercase Letter 880
 
0.3%
Lowercase Letter 424
 
0.2%
Other Punctuation 111
 
< 0.1%
Open Punctuation 103
 
< 0.1%
Close Punctuation 101
 
< 0.1%
Letter Number 13
 
< 0.1%
Other values (3) 10
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
12371
 
7.4%
10308
 
6.2%
10283
 
6.2%
10162
 
6.1%
9945
 
6.0%
9891
 
6.0%
9867
 
5.9%
6626
 
4.0%
5890
 
3.5%
4889
 
2.9%
Other values (529) 75969
45.7%
Uppercase Letter
ValueCountFrequency (%)
B 177
20.1%
A 92
10.5%
C 79
 
9.0%
K 63
 
7.2%
S 62
 
7.0%
P 53
 
6.0%
I 43
 
4.9%
T 42
 
4.8%
L 35
 
4.0%
G 28
 
3.2%
Other values (15) 206
23.4%
Lowercase Letter
ValueCountFrequency (%)
e 115
27.1%
n 49
11.6%
a 41
 
9.7%
r 41
 
9.7%
c 40
 
9.4%
t 39
 
9.2%
l 32
 
7.5%
s 14
 
3.3%
i 9
 
2.1%
b 7
 
1.7%
Other values (12) 37
 
8.7%
Decimal Number
ValueCountFrequency (%)
1 13064
22.9%
2 7538
13.2%
0 6591
11.5%
3 6149
10.8%
5 4954
 
8.7%
4 4814
 
8.4%
6 3875
 
6.8%
7 3706
 
6.5%
8 3303
 
5.8%
9 3071
 
5.4%
Other Punctuation
ValueCountFrequency (%)
, 80
72.1%
. 11
 
9.9%
/ 8
 
7.2%
& 6
 
5.4%
? 3
 
2.7%
: 3
 
2.7%
Open Punctuation
ValueCountFrequency (%)
( 101
98.1%
[ 1
 
1.0%
1
 
1.0%
Close Punctuation
ValueCountFrequency (%)
) 100
99.0%
1
 
1.0%
Letter Number
ValueCountFrequency (%)
8
61.5%
5
38.5%
Space Separator
ValueCountFrequency (%)
48635
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7386
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 2
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 166201
59.2%
Common 113410
40.4%
Latin 1317
 
0.5%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
12371
 
7.4%
10308
 
6.2%
10283
 
6.2%
10162
 
6.1%
9945
 
6.0%
9891
 
6.0%
9867
 
5.9%
6626
 
4.0%
5890
 
3.5%
4889
 
2.9%
Other values (529) 75969
45.7%
Latin
ValueCountFrequency (%)
B 177
 
13.4%
e 115
 
8.7%
A 92
 
7.0%
C 79
 
6.0%
K 63
 
4.8%
S 62
 
4.7%
P 53
 
4.0%
n 49
 
3.7%
I 43
 
3.3%
T 42
 
3.2%
Other values (39) 542
41.2%
Common
ValueCountFrequency (%)
48635
42.9%
1 13064
 
11.5%
2 7538
 
6.6%
- 7386
 
6.5%
0 6591
 
5.8%
3 6149
 
5.4%
5 4954
 
4.4%
4 4814
 
4.2%
6 3875
 
3.4%
7 3706
 
3.3%
Other values (15) 6698
 
5.9%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 166199
59.2%
ASCII 114712
40.8%
Number Forms 13
 
< 0.1%
None 3
 
< 0.1%
CJK 1
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
48635
42.4%
1 13064
 
11.4%
2 7538
 
6.6%
- 7386
 
6.4%
0 6591
 
5.7%
3 6149
 
5.4%
5 4954
 
4.3%
4 4814
 
4.2%
6 3875
 
3.4%
7 3706
 
3.2%
Other values (60) 8000
 
7.0%
Hangul
ValueCountFrequency (%)
12371
 
7.4%
10308
 
6.2%
10283
 
6.2%
10162
 
6.1%
9945
 
6.0%
9891
 
6.0%
9867
 
5.9%
6626
 
4.0%
5890
 
3.5%
4889
 
2.9%
Other values (527) 75967
45.7%
Number Forms
ValueCountFrequency (%)
8
61.5%
5
38.5%
CJK
ValueCountFrequency (%)
1
100.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%
None
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

도로명주소
Text

MISSING 

Distinct9008
Distinct (%)95.0%
Missing391
Missing (%)4.0%
Memory size77.3 KiB
2024-05-11T15:14:42.084633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length57
Mean length35.692016
Min length20

Characters and Unicode

Total characters338396
Distinct characters647
Distinct categories14 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8619 ?
Unique (%)90.9%

Sample

1st row서울특별시 관악구 과천대로 939, 르메이에르강남타운2 제1층 1-지-1호 (남현동)
2nd row서울특별시 노원구 노해로85길 10-55, 1018호 (상계동, 소담빌)
3rd row서울특별시 중구 서소문로 89, 순화빌딩 S-1752호 (순화동)
4th row서울특별시 노원구 노해로 457, 402호 (상계동,은성빌딩)
5th row서울특별시 영등포구 당산로28길 9, 3층 (당산동3가)
ValueCountFrequency (%)
서울특별시 9476
 
15.3%
종로구 1700
 
2.7%
중구 1516
 
2.4%
강남구 1354
 
2.2%
마포구 837
 
1.4%
서초구 802
 
1.3%
영등포구 522
 
0.8%
2층 494
 
0.8%
3층 453
 
0.7%
송파구 357
 
0.6%
Other values (9647) 44488
71.8%
2024-05-11T15:14:42.917493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
55402
 
16.4%
1 12839
 
3.8%
12522
 
3.7%
12341
 
3.6%
, 11406
 
3.4%
10982
 
3.2%
10004
 
3.0%
9859
 
2.9%
9578
 
2.8%
) 9565
 
2.8%
Other values (637) 183898
54.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 193330
57.1%
Decimal Number 56357
 
16.7%
Space Separator 55402
 
16.4%
Other Punctuation 11435
 
3.4%
Close Punctuation 9566
 
2.8%
Open Punctuation 9566
 
2.8%
Dash Punctuation 1224
 
0.4%
Uppercase Letter 1164
 
0.3%
Lowercase Letter 318
 
0.1%
Letter Number 16
 
< 0.1%
Other values (4) 18
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
12522
 
6.5%
12341
 
6.4%
10982
 
5.7%
10004
 
5.2%
9859
 
5.1%
9578
 
5.0%
9503
 
4.9%
9480
 
4.9%
6438
 
3.3%
4225
 
2.2%
Other values (562) 98398
50.9%
Uppercase Letter
ValueCountFrequency (%)
B 248
21.3%
A 148
12.7%
S 90
 
7.7%
C 82
 
7.0%
K 77
 
6.6%
I 57
 
4.9%
T 54
 
4.6%
P 47
 
4.0%
L 44
 
3.8%
E 41
 
3.5%
Other values (15) 276
23.7%
Lowercase Letter
ValueCountFrequency (%)
e 81
25.5%
n 37
11.6%
a 30
 
9.4%
r 29
 
9.1%
c 29
 
9.1%
t 28
 
8.8%
l 22
 
6.9%
s 13
 
4.1%
o 8
 
2.5%
p 7
 
2.2%
Other values (10) 34
10.7%
Decimal Number
ValueCountFrequency (%)
1 12839
22.8%
2 7892
14.0%
0 6955
12.3%
3 6951
12.3%
4 4446
 
7.9%
5 4397
 
7.8%
6 3668
 
6.5%
8 3160
 
5.6%
7 3149
 
5.6%
9 2900
 
5.1%
Other Punctuation
ValueCountFrequency (%)
, 11406
99.7%
. 9
 
0.1%
& 8
 
0.1%
/ 6
 
0.1%
? 3
 
< 0.1%
: 2
 
< 0.1%
# 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
9
56.2%
6
37.5%
1
 
6.2%
Close Punctuation
ValueCountFrequency (%)
) 9565
> 99.9%
1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 9565
> 99.9%
1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
55402
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1224
100.0%
Math Symbol
ValueCountFrequency (%)
~ 14
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 193331
57.1%
Common 143567
42.4%
Latin 1498
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
12522
 
6.5%
12341
 
6.4%
10982
 
5.7%
10004
 
5.2%
9859
 
5.1%
9578
 
5.0%
9503
 
4.9%
9480
 
4.9%
6438
 
3.3%
4225
 
2.2%
Other values (563) 98399
50.9%
Latin
ValueCountFrequency (%)
B 248
16.6%
A 148
 
9.9%
S 90
 
6.0%
C 82
 
5.5%
e 81
 
5.4%
K 77
 
5.1%
I 57
 
3.8%
T 54
 
3.6%
P 47
 
3.1%
L 44
 
2.9%
Other values (38) 570
38.1%
Common
ValueCountFrequency (%)
55402
38.6%
1 12839
 
8.9%
, 11406
 
7.9%
) 9565
 
6.7%
( 9565
 
6.7%
2 7892
 
5.5%
0 6955
 
4.8%
3 6951
 
4.8%
4 4446
 
3.1%
5 4397
 
3.1%
Other values (16) 14149
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 193330
57.1%
ASCII 145047
42.9%
Number Forms 16
 
< 0.1%
None 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
55402
38.2%
1 12839
 
8.9%
, 11406
 
7.9%
) 9565
 
6.6%
( 9565
 
6.6%
2 7892
 
5.4%
0 6955
 
4.8%
3 6951
 
4.8%
4 4446
 
3.1%
5 4397
 
3.0%
Other values (59) 15629
 
10.8%
Hangul
ValueCountFrequency (%)
12522
 
6.5%
12341
 
6.4%
10982
 
5.7%
10004
 
5.2%
9859
 
5.1%
9578
 
5.0%
9503
 
4.9%
9480
 
4.9%
6438
 
3.3%
4225
 
2.2%
Other values (562) 98398
50.9%
Number Forms
ValueCountFrequency (%)
9
56.2%
6
37.5%
1
 
6.2%
None
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

도로명우편번호
Text

MISSING 

Distinct1993
Distinct (%)34.1%
Missing4019
Missing (%)40.7%
Memory size77.3 KiB
2024-05-11T15:14:43.416952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.0803007
Min length5

Characters and Unicode

Total characters29735
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

Unique1130 ?
Unique (%)19.3%

Sample

1st row08807
2nd row01695
3rd row04516
4th row07259
5th row01170
ValueCountFrequency (%)
04522 145
 
2.5%
03150 99
 
1.7%
03157 82
 
1.4%
03182 81
 
1.4%
03186 67
 
1.1%
03173 67
 
1.1%
04520 65
 
1.1%
04516 58
 
1.0%
04521 52
 
0.9%
03162 44
 
0.8%
Other values (1983) 5093
87.0%
2024-05-11T15:14:44.060828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7512
25.3%
1 3465
11.7%
3 3034
10.2%
5 2804
 
9.4%
6 2684
 
9.0%
4 2514
 
8.5%
2 2480
 
8.3%
7 2288
 
7.7%
8 1773
 
6.0%
9 1165
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 29719
99.9%
Dash Punctuation 16
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7512
25.3%
1 3465
11.7%
3 3034
10.2%
5 2804
 
9.4%
6 2684
 
9.0%
4 2514
 
8.5%
2 2480
 
8.3%
7 2288
 
7.7%
8 1773
 
6.0%
9 1165
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 29735
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7512
25.3%
1 3465
11.7%
3 3034
10.2%
5 2804
 
9.4%
6 2684
 
9.0%
4 2514
 
8.5%
2 2480
 
8.3%
7 2288
 
7.7%
8 1773
 
6.0%
9 1165
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 29735
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7512
25.3%
1 3465
11.7%
3 3034
10.2%
5 2804
 
9.4%
6 2684
 
9.0%
4 2514
 
8.5%
2 2480
 
8.3%
7 2288
 
7.7%
8 1773
 
6.0%
9 1165
 
3.9%
Distinct9142
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Memory size77.3 KiB
2024-05-11T15:14:44.483776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length34
Mean length8.525628
Min length2

Characters and Unicode

Total characters84165
Distinct characters904
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8501 ?
Unique (%)86.1%

Sample

1st row(주)매크로투어
2nd row위즈유럽
3rd row여행기록
4th row(주)롯데관광노원
5th row알고마스 여행제작소
ValueCountFrequency (%)
주식회사 903
 
7.6%
국외 310
 
2.6%
여행사 79
 
0.7%
투어 77
 
0.6%
tour 54
 
0.5%
36
 
0.3%
트래블 26
 
0.2%
여행 13
 
0.1%
travel 11
 
0.1%
co 10
 
0.1%
Other values (9292) 10333
87.2%
2024-05-11T15:14:45.009387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7389
 
8.8%
) 6928
 
8.2%
( 6850
 
8.1%
2929
 
3.5%
2925
 
3.5%
2762
 
3.3%
2502
 
3.0%
2476
 
2.9%
2464
 
2.9%
1982
 
2.4%
Other values (894) 44958
53.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 66090
78.5%
Close Punctuation 6935
 
8.2%
Open Punctuation 6856
 
8.1%
Space Separator 1982
 
2.4%
Uppercase Letter 1349
 
1.6%
Lowercase Letter 682
 
0.8%
Other Punctuation 121
 
0.1%
Decimal Number 85
 
0.1%
Dash Punctuation 63
 
0.1%
Other Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7389
 
11.2%
2929
 
4.4%
2925
 
4.4%
2762
 
4.2%
2502
 
3.8%
2476
 
3.7%
2464
 
3.7%
1904
 
2.9%
1338
 
2.0%
1074
 
1.6%
Other values (822) 38327
58.0%
Uppercase Letter
ValueCountFrequency (%)
T 160
 
11.9%
R 115
 
8.5%
O 109
 
8.1%
A 101
 
7.5%
C 80
 
5.9%
E 75
 
5.6%
U 72
 
5.3%
I 68
 
5.0%
L 67
 
5.0%
S 67
 
5.0%
Other values (15) 435
32.2%
Lowercase Letter
ValueCountFrequency (%)
o 101
14.8%
r 80
11.7%
e 67
9.8%
n 52
 
7.6%
t 49
 
7.2%
u 47
 
6.9%
a 47
 
6.9%
i 41
 
6.0%
l 32
 
4.7%
d 23
 
3.4%
Other values (14) 143
21.0%
Decimal Number
ValueCountFrequency (%)
2 22
25.9%
1 18
21.2%
5 12
14.1%
0 10
11.8%
3 7
 
8.2%
7 6
 
7.1%
6 4
 
4.7%
4 3
 
3.5%
9 3
 
3.5%
Other Punctuation
ValueCountFrequency (%)
. 58
47.9%
& 43
35.5%
, 17
 
14.0%
? 2
 
1.7%
1
 
0.8%
Close Punctuation
ValueCountFrequency (%)
) 6928
99.9%
] 6
 
0.1%
} 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 6850
99.9%
[ 6
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
- 61
96.8%
2
 
3.2%
Space Separator
ValueCountFrequency (%)
1982
100.0%
Other Symbol
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 66079
78.5%
Common 16042
 
19.1%
Latin 2031
 
2.4%
Han 13
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7389
 
11.2%
2929
 
4.4%
2925
 
4.4%
2762
 
4.2%
2502
 
3.8%
2476
 
3.7%
2464
 
3.7%
1904
 
2.9%
1338
 
2.0%
1074
 
1.6%
Other values (813) 38316
58.0%
Latin
ValueCountFrequency (%)
T 160
 
7.9%
R 115
 
5.7%
O 109
 
5.4%
o 101
 
5.0%
A 101
 
5.0%
C 80
 
3.9%
r 80
 
3.9%
E 75
 
3.7%
U 72
 
3.5%
I 68
 
3.3%
Other values (39) 1070
52.7%
Common
ValueCountFrequency (%)
) 6928
43.2%
( 6850
42.7%
1982
 
12.4%
- 61
 
0.4%
. 58
 
0.4%
& 43
 
0.3%
2 22
 
0.1%
1 18
 
0.1%
, 17
 
0.1%
5 12
 
0.1%
Other values (12) 51
 
0.3%
Han
ValueCountFrequency (%)
2
15.4%
2
15.4%
2
15.4%
1
7.7%
1
7.7%
1
7.7%
1
7.7%
1
7.7%
1
7.7%
1
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 66077
78.5%
ASCII 18070
 
21.5%
CJK 11
 
< 0.1%
None 5
 
< 0.1%
CJK Compat Ideographs 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
7389
 
11.2%
2929
 
4.4%
2925
 
4.4%
2762
 
4.2%
2502
 
3.8%
2476
 
3.7%
2464
 
3.7%
1904
 
2.9%
1338
 
2.0%
1074
 
1.6%
Other values (812) 38314
58.0%
ASCII
ValueCountFrequency (%)
) 6928
38.3%
( 6850
37.9%
1982
 
11.0%
T 160
 
0.9%
R 115
 
0.6%
O 109
 
0.6%
o 101
 
0.6%
A 101
 
0.6%
C 80
 
0.4%
r 80
 
0.4%
Other values (59) 1564
 
8.7%
None
ValueCountFrequency (%)
2
40.0%
2
40.0%
1
20.0%
CJK
ValueCountFrequency (%)
2
18.2%
2
18.2%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
CJK Compat Ideographs
ValueCountFrequency (%)
2
100.0%
Distinct9125
Distinct (%)92.4%
Missing0
Missing (%)0.0%
Memory size77.3 KiB
Minimum2002-10-22 17:51:16
Maximum2024-05-09 18:11:47
2024-05-11T15:14:45.174446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:14:45.346434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size77.3 KiB
I
5151 
U
4718 
D
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 5151
52.2%
U 4718
47.8%
D 3
 
< 0.1%

Length

2024-05-11T15:14:45.489930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:45.596650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 5151
52.2%
u 4718
47.8%
d 3
 
< 0.1%
Distinct1198
Distinct (%)12.1%
Missing0
Missing (%)0.0%
Memory size77.3 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T15:14:45.726922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:14:46.278521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9872
Missing (%)100.0%
Memory size86.9 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct4745
Distinct (%)49.5%
Missing294
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean198670.47
Minimum166870.89
Maximum215641.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size86.9 KiB
2024-05-11T15:14:46.478841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum166870.89
5-th percentile189369.54
Q1195703.43
median198284.08
Q3202425.73
95-th percentile208186.17
Maximum215641.7
Range48770.815
Interquartile range (IQR)6722.3047

Descriptive statistics

Standard deviation5517.8586
Coefficient of variation (CV)0.027773924
Kurtosis0.45600308
Mean198670.47
Median Absolute Deviation (MAD)3703.8016
Skewness-0.13259922
Sum1.9028658 × 109
Variance30446764
MonotonicityNot monotonic
2024-05-11T15:14:46.680671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
198324.653631679 129
 
1.3%
198150.300374121 102
 
1.0%
197567.747824202 77
 
0.8%
198137.354306134 73
 
0.7%
195703.425296812 69
 
0.7%
197465.223921125 66
 
0.7%
198068.059896866 64
 
0.6%
197713.264872835 63
 
0.6%
198300.022318698 56
 
0.6%
197607.398336321 55
 
0.6%
Other values (4735) 8824
89.4%
(Missing) 294
 
3.0%
ValueCountFrequency (%)
166870.887070091 2
< 0.1%
173752.381184223 1
< 0.1%
182524.823835629 1
< 0.1%
182794.441839414 2
< 0.1%
182859.059692916 1
< 0.1%
182876.367858149 2
< 0.1%
182879.610355768 1
< 0.1%
182895.668483962 2
< 0.1%
182914.598086861 1
< 0.1%
182914.770762913 2
< 0.1%
ValueCountFrequency (%)
215641.701931 1
< 0.1%
215313.230134197 1
< 0.1%
215008.531272849 1
< 0.1%
214958.713997465 1
< 0.1%
213809.759558339 1
< 0.1%
213700.877714971 2
< 0.1%
213698.007355762 1
< 0.1%
213646.900696177 1
< 0.1%
213522.288105074 1
< 0.1%
213279.781081276 1
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct4744
Distinct (%)49.5%
Missing294
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean448859.12
Minimum417086.15
Maximum464731.76
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size86.9 KiB
2024-05-11T15:14:46.878713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum417086.15
5-th percentile442392.65
Q1445141.77
median449944.58
Q3451854.82
95-th percentile454372.92
Maximum464731.76
Range47645.608
Interquartile range (IQR)6713.0505

Descriptive statistics

Standard deviation4159.7872
Coefficient of variation (CV)0.0092674671
Kurtosis0.36887923
Mean448859.12
Median Absolute Deviation (MAD)2403.3912
Skewness0.051376901
Sum4.2991727 × 109
Variance17303829
MonotonicityNot monotonic
2024-05-11T15:14:47.074035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
452252.812389497 129
 
1.3%
452019.212642931 102
 
1.0%
452347.973860449 77
 
0.8%
451759.123871901 73
 
0.7%
449330.800717721 69
 
0.7%
452366.613899898 66
 
0.7%
451666.732613608 64
 
0.6%
451938.037709964 63
 
0.6%
451702.546231816 56
 
0.6%
452120.026024435 55
 
0.6%
Other values (4734) 8824
89.4%
(Missing) 294
 
3.0%
ValueCountFrequency (%)
417086.15355621 1
 
< 0.1%
430831.889183026 1
 
< 0.1%
434263.681539619 1
 
< 0.1%
434329.255701773 2
 
< 0.1%
437752.768322431 1
 
< 0.1%
437914.06299827 8
0.1%
438334.581605252 1
 
< 0.1%
438458.097193512 1
 
< 0.1%
438690.814038292 1
 
< 0.1%
438756.598068106 1
 
< 0.1%
ValueCountFrequency (%)
464731.761130542 1
 
< 0.1%
464280.157316989 1
 
< 0.1%
464208.305428933 1
 
< 0.1%
464199.048415229 5
0.1%
463963.394402186 1
 
< 0.1%
463930.060025748 1
 
< 0.1%
463928.107318353 1
 
< 0.1%
463892.861101303 1
 
< 0.1%
463887.942604325 1
 
< 0.1%
463884.895275557 1
 
< 0.1%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size77.3 KiB
국내외여행업
6128 
<NA>
3241 
국외여행업
 
503

Length

Max length6
Median length6
Mean length5.2924433
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 (%)
국내외여행업 6128
62.1%
<NA> 3241
32.8%
국외여행업 503
 
5.1%

Length

2024-05-11T15:14:47.278322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:47.479017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국내외여행업 6128
62.1%
na 3241
32.8%
국외여행업 503
 
5.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size77.3 KiB
<NA>
5619 
관광사업
4253 

Length

Max length4
Median length4
Mean length4
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> 5619
56.9%
관광사업 4253
43.1%

Length

2024-05-11T15:14:47.665339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:47.829354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5619
56.9%
관광사업 4253
43.1%

지역구분명
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size77.3 KiB
<NA>
9433 
일반주거지역
 
93
근린상업지역
 
87
준주거지역
 
79
주거지역
 
64
Other values (6)
 
116

Length

Max length6
Median length4
Mean length4.0585494
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9433
95.6%
일반주거지역 93
 
0.9%
근린상업지역 87
 
0.9%
준주거지역 79
 
0.8%
주거지역 64
 
0.6%
일반상업지역 59
 
0.6%
상업지역 37
 
0.4%
준공업지역 13
 
0.1%
중심상업지역 4
 
< 0.1%
공업지역 2
 
< 0.1%

Length

2024-05-11T15:14:48.030560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 9433
95.6%
일반주거지역 93
 
0.9%
근린상업지역 87
 
0.9%
준주거지역 79
 
0.8%
주거지역 64
 
0.6%
일반상업지역 59
 
0.6%
상업지역 37
 
0.4%
준공업지역 13
 
0.1%
중심상업지역 4
 
< 0.1%
공업지역 2
 
< 0.1%

총층수
Real number (ℝ)

MISSING  ZEROS 

Distinct35
Distinct (%)1.5%
Missing7566
Missing (%)76.6%
Infinite0
Infinite (%)0.0%
Mean1.1383348
Minimum0
Maximum51
Zeros1970
Zeros (%)20.0%
Negative0
Negative (%)0.0%
Memory size86.9 KiB
2024-05-11T15:14:48.284810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile7
Maximum51
Range51
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4.0213568
Coefficient of variation (CV)3.5326662
Kurtosis40.552066
Mean1.1383348
Median Absolute Deviation (MAD)0
Skewness5.5937407
Sum2625
Variance16.171311
MonotonicityNot monotonic
2024-05-11T15:14:48.632565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
0 1970
 
20.0%
5 47
 
0.5%
4 43
 
0.4%
1 36
 
0.4%
6 34
 
0.3%
3 28
 
0.3%
2 27
 
0.3%
7 17
 
0.2%
10 14
 
0.1%
8 10
 
0.1%
Other values (25) 80
 
0.8%
(Missing) 7566
76.6%
ValueCountFrequency (%)
0 1970
20.0%
1 36
 
0.4%
2 27
 
0.3%
3 28
 
0.3%
4 43
 
0.4%
5 47
 
0.5%
6 34
 
0.3%
7 17
 
0.2%
8 10
 
0.1%
9 9
 
0.1%
ValueCountFrequency (%)
51 1
 
< 0.1%
46 1
 
< 0.1%
41 1
 
< 0.1%
36 2
< 0.1%
35 1
 
< 0.1%
32 1
 
< 0.1%
30 3
< 0.1%
27 2
< 0.1%
26 1
 
< 0.1%
25 1
 
< 0.1%

주변환경명
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size77.3 KiB
<NA>
9517 
기타
 
272
주택가주변
 
45
아파트지역
 
20
유흥업소밀집지역
 
13
Other values (2)
 
5

Length

Max length8
Median length4
Mean length3.958671
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9517
96.4%
기타 272
 
2.8%
주택가주변 45
 
0.5%
아파트지역 20
 
0.2%
유흥업소밀집지역 13
 
0.1%
학교정화(상대) 4
 
< 0.1%
결혼예식장주변 1
 
< 0.1%

Length

2024-05-11T15:14:48.916894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:49.091513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9517
96.4%
기타 272
 
2.8%
주택가주변 45
 
0.5%
아파트지역 20
 
0.2%
유흥업소밀집지역 13
 
0.1%
학교정화(상대 4
 
< 0.1%
결혼예식장주변 1
 
< 0.1%

제작취급품목내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9872
Missing (%)100.0%
Memory size86.9 KiB

보험기관명
Text

MISSING 

Distinct281
Distinct (%)6.7%
Missing5686
Missing (%)57.6%
Memory size77.3 KiB
2024-05-11T15:14:49.382101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length26
Mean length9.7090301
Min length2

Characters and Unicode

Total characters40642
Distinct characters93
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique180 ?
Unique (%)4.3%

Sample

1st row서울보증보험(30,000,000)
2nd row서울보증보험(30,000,000)
3rd row서울보증보험
4th row서울보증보험(30,000,000)
5th row서울보증보험(30,000,000)
ValueCountFrequency (%)
서울보증보험 1020
22.3%
여행공제회 659
14.4%
한국관광협회중앙회 468
10.2%
한국관광협회 447
9.8%
서울보증보험주식회사 326
 
7.1%
서울보증보험(3천만원 297
 
6.5%
서울보증보험(30,000,000 194
 
4.2%
서울보증보험(3천만 93
 
2.0%
서울보증보험(주 89
 
1.9%
서울특별시관광협회 62
 
1.4%
Other values (259) 912
20.0%
2024-05-11T15:14:49.984290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4931
 
12.1%
3056
 
7.5%
0 2684
 
6.6%
2612
 
6.4%
2610
 
6.4%
2476
 
6.1%
2432
 
6.0%
( 1310
 
3.2%
) 1310
 
3.2%
1285
 
3.2%
Other values (83) 15936
39.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 32532
80.0%
Decimal Number 4280
 
10.5%
Open Punctuation 1310
 
3.2%
Close Punctuation 1310
 
3.2%
Other Punctuation 715
 
1.8%
Space Separator 382
 
0.9%
Dash Punctuation 110
 
0.3%
Uppercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4931
15.2%
3056
 
9.4%
2612
 
8.0%
2610
 
8.0%
2476
 
7.6%
2432
 
7.5%
1285
 
3.9%
1285
 
3.9%
1275
 
3.9%
1091
 
3.4%
Other values (62) 9479
29.1%
Decimal Number
ValueCountFrequency (%)
0 2684
62.7%
3 916
 
21.4%
4 202
 
4.7%
5 125
 
2.9%
1 98
 
2.3%
2 90
 
2.1%
8 59
 
1.4%
7 40
 
0.9%
6 38
 
0.9%
9 28
 
0.7%
Other Punctuation
ValueCountFrequency (%)
, 674
94.3%
. 26
 
3.6%
/ 12
 
1.7%
: 3
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
I 1
33.3%
G 1
33.3%
S 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 1310
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1310
100.0%
Space Separator
ValueCountFrequency (%)
382
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 110
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 32532
80.0%
Common 8107
 
19.9%
Latin 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4931
15.2%
3056
 
9.4%
2612
 
8.0%
2610
 
8.0%
2476
 
7.6%
2432
 
7.5%
1285
 
3.9%
1285
 
3.9%
1275
 
3.9%
1091
 
3.4%
Other values (62) 9479
29.1%
Common
ValueCountFrequency (%)
0 2684
33.1%
( 1310
16.2%
) 1310
16.2%
3 916
 
11.3%
, 674
 
8.3%
382
 
4.7%
4 202
 
2.5%
5 125
 
1.5%
- 110
 
1.4%
1 98
 
1.2%
Other values (8) 296
 
3.7%
Latin
ValueCountFrequency (%)
I 1
33.3%
G 1
33.3%
S 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 32532
80.0%
ASCII 8110
 
20.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
4931
15.2%
3056
 
9.4%
2612
 
8.0%
2610
 
8.0%
2476
 
7.6%
2432
 
7.5%
1285
 
3.9%
1285
 
3.9%
1275
 
3.9%
1091
 
3.4%
Other values (62) 9479
29.1%
ASCII
ValueCountFrequency (%)
0 2684
33.1%
( 1310
16.2%
) 1310
16.2%
3 916
 
11.3%
, 674
 
8.3%
382
 
4.7%
4 202
 
2.5%
5 125
 
1.5%
- 110
 
1.4%
1 98
 
1.2%
Other values (11) 299
 
3.7%

건물용도명
Categorical

IMBALANCE 

Distinct13
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size77.3 KiB
<NA>
9138 
근린생활시설
 
416
사무실
 
280
기타
 
8
다가구용 주택(공동주택적용)
 
7
Other values (8)
 
23

Length

Max length15
Median length4
Mean length4.0645259
Min length2

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9138
92.6%
근린생활시설 416
 
4.2%
사무실 280
 
2.8%
기타 8
 
0.1%
다가구용 주택(공동주택적용) 7
 
0.1%
유통시설 7
 
0.1%
아파트 6
 
0.1%
교육연구시설 3
 
< 0.1%
다중주택(공동주택적용) 2
 
< 0.1%
시장(재래시장) 2
 
< 0.1%
Other values (3) 3
 
< 0.1%

Length

2024-05-11T15:14:50.206681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 9138
92.5%
근린생활시설 416
 
4.2%
사무실 280
 
2.8%
기타 8
 
0.1%
다가구용 7
 
0.1%
주택(공동주택적용 7
 
0.1%
유통시설 7
 
0.1%
아파트 6
 
0.1%
교육연구시설 3
 
< 0.1%
다중주택(공동주택적용 2
 
< 0.1%
Other values (4) 5
 
0.1%

지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct31
Distinct (%)1.3%
Missing7487
Missing (%)75.8%
Infinite0
Infinite (%)0.0%
Mean1.0914046
Minimum0
Maximum46
Zeros1965
Zeros (%)19.9%
Negative0
Negative (%)0.0%
Memory size86.9 KiB
2024-05-11T15:14:50.507057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum46
Range46
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.5242493
Coefficient of variation (CV)3.2290951
Kurtosis43.857178
Mean1.0914046
Median Absolute Deviation (MAD)0
Skewness5.6588722
Sum2603
Variance12.420333
MonotonicityNot monotonic
2024-05-11T15:14:50.741703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 1965
 
19.9%
4 70
 
0.7%
3 65
 
0.7%
2 60
 
0.6%
5 53
 
0.5%
1 37
 
0.4%
8 18
 
0.2%
7 17
 
0.2%
6 17
 
0.2%
15 16
 
0.2%
Other values (21) 67
 
0.7%
(Missing) 7487
75.8%
ValueCountFrequency (%)
0 1965
19.9%
1 37
 
0.4%
2 60
 
0.6%
3 65
 
0.7%
4 70
 
0.7%
5 53
 
0.5%
6 17
 
0.2%
7 17
 
0.2%
8 18
 
0.2%
9 7
 
0.1%
ValueCountFrequency (%)
46 1
 
< 0.1%
41 1
 
< 0.1%
36 3
< 0.1%
35 1
 
< 0.1%
30 1
 
< 0.1%
27 1
 
< 0.1%
25 1
 
< 0.1%
24 2
< 0.1%
22 1
 
< 0.1%
21 2
< 0.1%

지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)0.5%
Missing7655
Missing (%)77.5%
Infinite0
Infinite (%)0.0%
Mean0.22598106
Minimum0
Maximum17
Zeros1997
Zeros (%)20.2%
Negative0
Negative (%)0.0%
Memory size86.9 KiB
2024-05-11T15:14:50.896256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum17
Range17
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.94901229
Coefficient of variation (CV)4.1995214
Kurtosis73.009308
Mean0.22598106
Median Absolute Deviation (MAD)0
Skewness7.0381472
Sum501
Variance0.90062432
MonotonicityNot monotonic
2024-05-11T15:14:51.067122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 1997
 
20.2%
1 126
 
1.3%
2 30
 
0.3%
5 18
 
0.2%
3 17
 
0.2%
4 12
 
0.1%
6 10
 
0.1%
7 3
 
< 0.1%
8 2
 
< 0.1%
17 1
 
< 0.1%
(Missing) 7655
77.5%
ValueCountFrequency (%)
0 1997
20.2%
1 126
 
1.3%
2 30
 
0.3%
3 17
 
0.2%
4 12
 
0.1%
5 18
 
0.2%
6 10
 
0.1%
7 3
 
< 0.1%
8 2
 
< 0.1%
12 1
 
< 0.1%
ValueCountFrequency (%)
17 1
 
< 0.1%
12 1
 
< 0.1%
8 2
 
< 0.1%
7 3
 
< 0.1%
6 10
 
0.1%
5 18
 
0.2%
4 12
 
0.1%
3 17
 
0.2%
2 30
 
0.3%
1 126
1.3%

객실수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size77.3 KiB
<NA>
8291 
0
1581 

Length

Max length4
Median length4
Mean length3.5195502
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> 8291
84.0%
0 1581
 
16.0%

Length

2024-05-11T15:14:51.237820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:51.379935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8291
84.0%
0 1581
 
16.0%

건축연면적
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size77.3 KiB
<NA>
8290 
0
1581 
23
 
1

Length

Max length4
Median length4
Mean length3.5193476
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8290
84.0%
0 1581
 
16.0%
23 1
 
< 0.1%

Length

2024-05-11T15:14:51.554119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:51.743315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8290
84.0%
0 1581
 
16.0%
23 1
 
< 0.1%

영문상호명
Text

MISSING 

Distinct206
Distinct (%)99.0%
Missing9664
Missing (%)97.9%
Memory size77.3 KiB
2024-05-11T15:14:52.139217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length28
Mean length16.668269
Min length1

Characters and Unicode

Total characters3467
Distinct characters65
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique205 ?
Unique (%)98.6%

Sample

1st rowFunTrip Co., Ltd.
2nd rowTieup
3rd rowTOURVILL
4th row20100827
5th row0
ValueCountFrequency (%)
ltd 59
 
10.2%
co 58
 
10.0%
tour 47
 
8.1%
co.,ltd 31
 
5.4%
travel 30
 
5.2%
korea 16
 
2.8%
inc 11
 
1.9%
service 7
 
1.2%
6
 
1.0%
co.ltd 5
 
0.9%
Other values (269) 308
53.3%
2024-05-11T15:14:52.769610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
371
 
10.7%
o 194
 
5.6%
. 185
 
5.3%
T 178
 
5.1%
L 168
 
4.8%
C 131
 
3.8%
t 124
 
3.6%
r 118
 
3.4%
A 114
 
3.3%
O 114
 
3.3%
Other values (55) 1770
51.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1518
43.8%
Lowercase Letter 1254
36.2%
Space Separator 371
 
10.7%
Other Punctuation 293
 
8.5%
Decimal Number 21
 
0.6%
Dash Punctuation 8
 
0.2%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 194
15.5%
t 124
9.9%
r 118
9.4%
a 107
8.5%
e 105
8.4%
d 103
8.2%
i 77
 
6.1%
n 75
 
6.0%
l 67
 
5.3%
u 53
 
4.2%
Other values (16) 231
18.4%
Uppercase Letter
ValueCountFrequency (%)
T 178
11.7%
L 168
11.1%
C 131
 
8.6%
A 114
 
7.5%
O 114
 
7.5%
R 111
 
7.3%
E 98
 
6.5%
I 87
 
5.7%
N 73
 
4.8%
U 63
 
4.2%
Other values (14) 381
25.1%
Decimal Number
ValueCountFrequency (%)
0 9
42.9%
2 5
23.8%
7 2
 
9.5%
8 2
 
9.5%
1 1
 
4.8%
9 1
 
4.8%
6 1
 
4.8%
Other Punctuation
ValueCountFrequency (%)
. 185
63.1%
, 94
32.1%
& 13
 
4.4%
' 1
 
0.3%
Space Separator
ValueCountFrequency (%)
371
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2772
80.0%
Common 695
 
20.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 194
 
7.0%
T 178
 
6.4%
L 168
 
6.1%
C 131
 
4.7%
t 124
 
4.5%
r 118
 
4.3%
A 114
 
4.1%
O 114
 
4.1%
R 111
 
4.0%
a 107
 
3.9%
Other values (40) 1413
51.0%
Common
ValueCountFrequency (%)
371
53.4%
. 185
26.6%
, 94
 
13.5%
& 13
 
1.9%
0 9
 
1.3%
- 8
 
1.2%
2 5
 
0.7%
7 2
 
0.3%
8 2
 
0.3%
1 1
 
0.1%
Other values (5) 5
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3467
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
371
 
10.7%
o 194
 
5.6%
. 185
 
5.3%
T 178
 
5.1%
L 168
 
4.8%
C 131
 
3.8%
t 124
 
3.6%
r 118
 
3.4%
A 114
 
3.3%
O 114
 
3.3%
Other values (55) 1770
51.1%

영문상호주소
Categorical

IMBALANCE 

Distinct23
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size77.3 KiB
<NA>
9675 
OVERSEAS TRAVEL BUSINESS
 
77
Overseas travel business
 
59
Overseas Travel Business
 
41
Overseas Travel Agency
 
2
Other values (18)
 
18

Length

Max length35
Median length4
Mean length4.3990073
Min length4

Unique

Unique18 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9675
98.0%
OVERSEAS TRAVEL BUSINESS 77
 
0.8%
Overseas travel business 59
 
0.6%
Overseas Travel Business 41
 
0.4%
Overseas Travel Agency 2
 
< 0.1%
OverseasTravel Business 1
 
< 0.1%
OVERSEA TRAVEL BUSINESS 1
 
< 0.1%
Inbound Travel Agency 1
 
< 0.1%
Foreign tourism 1
 
< 0.1%
Abroad Travel Business 1
 
< 0.1%
Other values (13) 13
 
0.1%

Length

2024-05-11T15:14:53.019920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 9675
94.2%
travel 192
 
1.9%
business 192
 
1.9%
overseas 184
 
1.8%
agency 3
 
< 0.1%
foreign 3
 
< 0.1%
oversea 2
 
< 0.1%
outbound 2
 
< 0.1%
travle 1
 
< 0.1%
domestic 1
 
< 0.1%
Other values (11) 11
 
0.1%

선박총톤수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size77.3 KiB
<NA>
8291 
0
1581 

Length

Max length4
Median length4
Mean length3.5195502
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> 8291
84.0%
0 1581
 
16.0%

Length

2024-05-11T15:14:53.216417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:53.377361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8291
84.0%
0 1581
 
16.0%

선박척수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size77.3 KiB
<NA>
8291 
0
1581 

Length

Max length4
Median length4
Mean length3.5195502
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> 8291
84.0%
0 1581
 
16.0%

Length

2024-05-11T15:14:53.545955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:53.692115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8291
84.0%
0 1581
 
16.0%

선박제원
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9872
Missing (%)100.0%
Memory size86.9 KiB

무대면적
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size77.3 KiB
<NA>
8291 
0
1581 

Length

Max length4
Median length4
Mean length3.5195502
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> 8291
84.0%
0 1581
 
16.0%

Length

2024-05-11T15:14:53.853130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:54.011863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8291
84.0%
0 1581
 
16.0%

좌석수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size77.3 KiB
<NA>
8291 
0
1581 

Length

Max length4
Median length4
Mean length3.5195502
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> 8291
84.0%
0 1581
 
16.0%

Length

2024-05-11T15:14:54.186181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:54.354450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8291
84.0%
0 1581
 
16.0%

기념품종류
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9872
Missing (%)100.0%
Memory size86.9 KiB
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size77.3 KiB
<NA>
8291 
0
1581 

Length

Max length4
Median length4
Mean length3.5195502
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> 8291
84.0%
0 1581
 
16.0%

Length

2024-05-11T15:14:54.533650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:54.683417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8291
84.0%
0 1581
 
16.0%

시설면적
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct513
Distinct (%)17.6%
Missing6951
Missing (%)70.4%
Infinite0
Infinite (%)0.0%
Mean32.245488
Minimum0
Maximum11191.28
Zeros2158
Zeros (%)21.9%
Negative0
Negative (%)0.0%
Memory size86.9 KiB
2024-05-11T15:14:54.858692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q36.6
95-th percentile102.23
Maximum11191.28
Range11191.28
Interquartile range (IQR)6.6

Descriptive statistics

Standard deviation326.85735
Coefficient of variation (CV)10.13653
Kurtosis938.17093
Mean32.245488
Median Absolute Deviation (MAD)0
Skewness28.960276
Sum94189.07
Variance106835.73
MonotonicityNot monotonic
2024-05-11T15:14:55.084115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 2158
 
21.9%
33.0 22
 
0.2%
10.0 15
 
0.2%
66.0 11
 
0.1%
30.0 11
 
0.1%
132.0 9
 
0.1%
15.0 9
 
0.1%
50.0 7
 
0.1%
26.4 7
 
0.1%
4.0 7
 
0.1%
Other values (503) 665
 
6.7%
(Missing) 6951
70.4%
ValueCountFrequency (%)
0.0 2158
21.9%
1.0 1
 
< 0.1%
1.3 3
 
< 0.1%
2.0 1
 
< 0.1%
3.05 1
 
< 0.1%
3.3 6
 
0.1%
3.38 1
 
< 0.1%
3.63 1
 
< 0.1%
3.79 1
 
< 0.1%
3.97 1
 
< 0.1%
ValueCountFrequency (%)
11191.28 1
< 0.1%
11088.0 1
< 0.1%
4975.09 1
< 0.1%
3480.0 1
< 0.1%
3078.0 1
< 0.1%
2177.25 1
< 0.1%
1650.92 1
< 0.1%
1154.88 1
< 0.1%
1148.71 1
< 0.1%
789.7 1
< 0.1%

놀이기구수내역
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9872
Missing (%)100.0%
Memory size86.9 KiB

놀이시설수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size77.3 KiB
<NA>
8291 
0
1581 

Length

Max length4
Median length4
Mean length3.5195502
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> 8291
84.0%
0 1581
 
16.0%

Length

2024-05-11T15:14:55.347270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:14:55.531216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8291
84.0%
0 1581
 
16.0%

방송시설유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9872
Missing (%)100.0%
Memory size86.9 KiB

발전시설유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9872
Missing (%)100.0%
Memory size86.9 KiB

의무실유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9872
Missing (%)100.0%
Memory size86.9 KiB

안내소유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9872
Missing (%)100.0%
Memory size86.9 KiB

기획여행보험시작일자
Real number (ℝ)

MISSING 

Distinct70
Distinct (%)98.6%
Missing9801
Missing (%)99.3%
Infinite0
Infinite (%)0.0%
Mean20166940
Minimum20110414
Maximum20210721
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size86.9 KiB
2024-05-11T15:14:55.754427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20110414
5-th percentile20130517
Q120150757
median20170116
Q320190112
95-th percentile20200114
Maximum20210721
Range100307
Interquartile range (IQR)39355

Descriptive statistics

Standard deviation23032.384
Coefficient of variation (CV)0.0011420862
Kurtosis-0.67294745
Mean20166940
Median Absolute Deviation (MAD)19612
Skewness-0.26629068
Sum1.4318528 × 109
Variance5.3049072 × 108
MonotonicityNot monotonic
2024-05-11T15:14:55.946394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20151202 2
 
< 0.1%
20210721 1
 
< 0.1%
20121201 1
 
< 0.1%
20190109 1
 
< 0.1%
20121123 1
 
< 0.1%
20180424 1
 
< 0.1%
20180415 1
 
< 0.1%
20130619 1
 
< 0.1%
20150805 1
 
< 0.1%
20171016 1
 
< 0.1%
Other values (60) 60
 
0.6%
(Missing) 9801
99.3%
ValueCountFrequency (%)
20110414 1
< 0.1%
20121123 1
< 0.1%
20121201 1
< 0.1%
20130510 1
< 0.1%
20130524 1
< 0.1%
20130619 1
< 0.1%
20140108 1
< 0.1%
20140123 1
< 0.1%
20140304 1
< 0.1%
20140702 1
< 0.1%
ValueCountFrequency (%)
20210721 1
< 0.1%
20210509 1
< 0.1%
20200216 1
< 0.1%
20200128 1
< 0.1%
20200101 1
< 0.1%
20191118 1
< 0.1%
20191108 1
< 0.1%
20191102 1
< 0.1%
20190801 1
< 0.1%
20190713 1
< 0.1%

기획여행보험종료일자
Real number (ℝ)

MISSING 

Distinct70
Distinct (%)98.6%
Missing9801
Missing (%)99.3%
Infinite0
Infinite (%)0.0%
Mean20176963
Minimum20120413
Maximum20220720
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size86.9 KiB
2024-05-11T15:14:56.207559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20120413
5-th percentile20140516
Q120160654
median20180313
Q320200111
95-th percentile20210130
Maximum20220720
Range100307
Interquartile range (IQR)39457.5

Descriptive statistics

Standard deviation23167.355
Coefficient of variation (CV)0.0011482082
Kurtosis-0.70230994
Mean20176963
Median Absolute Deviation (MAD)19801
Skewness-0.27941845
Sum1.4325644 × 109
Variance5.3672635 × 108
MonotonicityNot monotonic
2024-05-11T15:14:56.457442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20161201 2
 
< 0.1%
20220720 1
 
< 0.1%
20131130 1
 
< 0.1%
20200108 1
 
< 0.1%
20131122 1
 
< 0.1%
20190423 1
 
< 0.1%
20190414 1
 
< 0.1%
20140618 1
 
< 0.1%
20160804 1
 
< 0.1%
20181015 1
 
< 0.1%
Other values (60) 60
 
0.6%
(Missing) 9801
99.3%
ValueCountFrequency (%)
20120413 1
< 0.1%
20131122 1
< 0.1%
20131130 1
< 0.1%
20140509 1
< 0.1%
20140523 1
< 0.1%
20140618 1
< 0.1%
20150107 1
< 0.1%
20150122 1
< 0.1%
20150303 1
< 0.1%
20150702 1
< 0.1%
ValueCountFrequency (%)
20220720 1
< 0.1%
20220508 1
< 0.1%
20210215 1
< 0.1%
20210131 1
< 0.1%
20210128 1
< 0.1%
20201231 1
< 0.1%
20201117 1
< 0.1%
20201107 1
< 0.1%
20201101 1
< 0.1%
20200731 1
< 0.1%

자본금
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct492
Distinct (%)10.4%
Missing5136
Missing (%)52.0%
Infinite0
Infinite (%)0.0%
Mean1.2040259 × 108
Minimum0
Maximum2.85 × 1010
Zeros413
Zeros (%)4.2%
Negative0
Negative (%)0.0%
Memory size86.9 KiB
2024-05-11T15:14:57.086596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q160000000
median1 × 108
Q31 × 108
95-th percentile2 × 108
Maximum2.85 × 1010
Range2.85 × 1010
Interquartile range (IQR)40000000

Descriptive statistics

Standard deviation5.5930364 × 108
Coefficient of variation (CV)4.6452792
Kurtosis1595.2488
Mean1.2040259 × 108
Median Absolute Deviation (MAD)40000000
Skewness36.074238
Sum5.7022666 × 1011
Variance3.1282056 × 1017
MonotonicityNot monotonic
2024-05-11T15:14:57.290917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100000000 1890
 
19.1%
60000000 746
 
7.6%
150000000 421
 
4.3%
0 413
 
4.2%
30000000 254
 
2.6%
90000000 87
 
0.9%
200000000 70
 
0.7%
50000000 59
 
0.6%
300000000 50
 
0.5%
70000000 24
 
0.2%
Other values (482) 722
 
7.3%
(Missing) 5136
52.0%
ValueCountFrequency (%)
0 413
4.2%
1 2
 
< 0.1%
100000 1
 
< 0.1%
1000000 2
 
< 0.1%
3000000 1
 
< 0.1%
6000000 3
 
< 0.1%
9000000 1
 
< 0.1%
9211151 1
 
< 0.1%
10000000 22
 
0.2%
11000000 1
 
< 0.1%
ValueCountFrequency (%)
28500000000 1
< 0.1%
16000000000 1
< 0.1%
11040000000 1
< 0.1%
10000000000 1
< 0.1%
5761041745 1
< 0.1%
5737699413 1
< 0.1%
5098647178 1
< 0.1%
5095972285 1
< 0.1%
4100000000 1
< 0.1%
2219359948 1
< 0.1%

보험시작일자
Real number (ℝ)

MISSING 

Distinct2986
Distinct (%)69.3%
Missing5565
Missing (%)56.4%
Infinite0
Infinite (%)0.0%
Mean20126692
Minimum19980819
Maximum20220328
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size86.9 KiB
2024-05-11T15:14:57.546617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19980819
5-th percentile20041029
Q120080728
median20130507
Q320170608
95-th percentile20200721
Maximum20220328
Range239509
Interquartile range (IQR)89880

Descriptive statistics

Standard deviation51223.678
Coefficient of variation (CV)0.0025450619
Kurtosis-1.0753817
Mean20126692
Median Absolute Deviation (MAD)40603
Skewness-0.14192535
Sum8.6685664 × 1010
Variance2.6238652 × 109
MonotonicityNot monotonic
2024-05-11T15:14:57.801581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20190401 8
 
0.1%
20150401 7
 
0.1%
20131101 6
 
0.1%
20200401 6
 
0.1%
20160921 6
 
0.1%
20210331 6
 
0.1%
20160401 6
 
0.1%
20140701 6
 
0.1%
20161101 5
 
0.1%
20070511 5
 
0.1%
Other values (2976) 4246
43.0%
(Missing) 5565
56.4%
ValueCountFrequency (%)
19980819 1
< 0.1%
19990116 1
< 0.1%
19990907 1
< 0.1%
20010511 1
< 0.1%
20010629 1
< 0.1%
20010821 1
< 0.1%
20020123 1
< 0.1%
20020215 1
< 0.1%
20020227 1
< 0.1%
20020423 1
< 0.1%
ValueCountFrequency (%)
20220328 1
 
< 0.1%
20220319 1
 
< 0.1%
20220303 1
 
< 0.1%
20220222 3
< 0.1%
20220221 1
 
< 0.1%
20220216 1
 
< 0.1%
20220211 1
 
< 0.1%
20220207 1
 
< 0.1%
20220202 1
 
< 0.1%
20220201 1
 
< 0.1%

보험종료일자
Real number (ℝ)

MISSING 

Distinct3062
Distinct (%)69.8%
Missing5483
Missing (%)55.5%
Infinite0
Infinite (%)0.0%
Mean20134766
Minimum19960911
Maximum20240612
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size86.9 KiB
2024-05-11T15:14:58.024169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19960911
5-th percentile20041028
Q120090601
median20140322
Q320180531
95-th percentile20210776
Maximum20240612
Range279701
Interquartile range (IQR)89930

Descriptive statistics

Standard deviation53623.067
Coefficient of variation (CV)0.0026632079
Kurtosis-0.8792221
Mean20134766
Median Absolute Deviation (MAD)49202
Skewness-0.23578173
Sum8.8371486 × 1010
Variance2.8754333 × 109
MonotonicityNot monotonic
2024-05-11T15:14:58.268376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20200331 8
 
0.1%
20170331 8
 
0.1%
20220331 6
 
0.1%
20160331 6
 
0.1%
20200318 6
 
0.1%
20150630 6
 
0.1%
20190731 6
 
0.1%
20081130 5
 
0.1%
20090213 5
 
0.1%
20100112 5
 
0.1%
Other values (3052) 4328
43.8%
(Missing) 5483
55.5%
ValueCountFrequency (%)
19960911 1
< 0.1%
19980306 1
< 0.1%
19980310 1
< 0.1%
19980413 1
< 0.1%
19990201 1
< 0.1%
19990225 1
< 0.1%
19990306 2
< 0.1%
19990429 1
< 0.1%
19990506 1
< 0.1%
19990817 1
< 0.1%
ValueCountFrequency (%)
20240612 1
< 0.1%
20240519 1
< 0.1%
20240511 1
< 0.1%
20230811 1
< 0.1%
20230327 1
< 0.1%
20230319 1
< 0.1%
20230314 1
< 0.1%
20230302 2
< 0.1%
20230222 1
< 0.1%
20230221 2
< 0.1%

부대시설내역
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9872
Missing (%)100.0%
Memory size86.9 KiB

시설규모
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct194
Distinct (%)6.6%
Missing6951
Missing (%)70.4%
Infinite0
Infinite (%)0.0%
Mean32.244437
Minimum0
Maximum11191
Zeros2158
Zeros (%)21.9%
Negative0
Negative (%)0.0%
Memory size86.9 KiB
2024-05-11T15:14:58.503651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q37
95-th percentile102
Maximum11191
Range11191
Interquartile range (IQR)7

Descriptive statistics

Standard deviation326.85263
Coefficient of variation (CV)10.136714
Kurtosis938.17738
Mean32.244437
Median Absolute Deviation (MAD)0
Skewness28.960422
Sum94186
Variance106832.64
MonotonicityNot monotonic
2024-05-11T15:14:58.717485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2158
 
21.9%
33 36
 
0.4%
30 23
 
0.2%
10 18
 
0.2%
66 18
 
0.2%
25 16
 
0.2%
23 15
 
0.2%
50 14
 
0.1%
17 14
 
0.1%
40 14
 
0.1%
Other values (184) 595
 
6.0%
(Missing) 6951
70.4%
ValueCountFrequency (%)
0 2158
21.9%
1 4
 
< 0.1%
2 1
 
< 0.1%
3 8
 
0.1%
4 10
 
0.1%
5 3
 
< 0.1%
6 6
 
0.1%
7 8
 
0.1%
8 7
 
0.1%
9 9
 
0.1%
ValueCountFrequency (%)
11191 1
< 0.1%
11088 1
< 0.1%
4975 1
< 0.1%
3480 1
< 0.1%
3078 1
< 0.1%
2177 1
< 0.1%
1651 1
< 0.1%
1155 1
< 0.1%
1149 1
< 0.1%
790 1
< 0.1%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명문화사업자구분명지역구분명총층수주변환경명제작취급품목내용보험기관명건물용도명지상층수지하층수객실수건축연면적영문상호명영문상호주소선박총톤수선박척수선박제원무대면적좌석수기념품종류회의실별동시수용인원시설면적놀이기구수내역놀이시설수방송시설유무발전시설유무의무실유무안내소유무기획여행보험시작일자기획여행보험종료일자자본금보험시작일자보험종료일자부대시설내역시설규모
03200000CDFI22600220060000022006-09-07<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 관악구 남현동 1061-18 르메이에르강남타운2서울특별시 관악구 과천대로 939, 르메이에르강남타운2 제1층 1-지-1호 (남현동)08807(주)매크로투어2023-02-28 10:39:33U2022-12-03 00:03:00.0<NA>198284.078546441368.909287<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
13100000CDFI22600220170000012017-01-26<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 노원구 상계동 330-29 1018호서울특별시 노원구 노해로85길 10-55, 1018호 (상계동, 소담빌)01695위즈유럽2023-03-06 17:34:35U2022-12-03 00:08:00.0<NA>205767.862144461566.481688<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23010000CDFI22600220240000072024-02-06<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 중구 순화동 5-2 순화빌딩서울특별시 중구 서소문로 89, 순화빌딩 S-1752호 (순화동)04516여행기록2024-04-04 16:21:28U2023-12-04 00:06:00.0<NA>197346.664858451164.449754<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
33100000CDFI22600220010000012001-06-26<NA>1영업/정상13영업중<NA><NA><NA><NA>02-975-2001<NA>139-942서울특별시 노원구 상계동 709-1 은성빌딩 402호서울특별시 노원구 노해로 457, 402호 (상계동,은성빌딩)<NA>(주)롯데관광노원2023-03-06 17:31:06U2022-12-03 00:08:00.0<NA>205114.407299461315.44396<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
43180000CDFI22600220140000302014-08-05<NA>1영업/정상13영업중<NA><NA><NA><NA>070-7691-5701<NA>150-803서울특별시 영등포구 당산동3가 249서울특별시 영등포구 당산로28길 9, 3층 (당산동3가)07259알고마스 여행제작소2023-03-08 17:54:20U2022-12-02 23:00:00.0<NA>190867.253415446953.74985<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
53080000CDFI22600220220000042022-04-21<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강북구 미아동 304-2 상아빌딩서울특별시 강북구 도봉로 191, 상아빌딩 4층 279호 (미아동)01170트래블스티커2024-04-30 11:01:31U2023-12-05 00:02:00.0<NA>202228.431718458158.105668<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
63220000CDFI22600220220000062022-02-21<NA>1영업/정상13영업중<NA><NA><NA><NA>02-1599-1659<NA><NA>서울특별시 강남구 역삼동 736 성홍타워 705호서울특별시 강남구 테헤란로 138, 성홍타워 705호 (역삼동)06236(주)크루즈여행닷컴2024-02-14 17:48:03U2023-12-01 23:06:00.0<NA>202960.555444159.715<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
73080000CDFI22600220180000082018-08-06<NA>3폐업03폐업2023-03-20<NA><NA><NA><NA><NA><NA>서울특별시 강북구 수유동 472-193 건우빌딩 334호서울특별시 강북구 삼양로 328, 건우빌딩 3층 334호 (수유동)01111엠-미디어(M-MEDIA)2023-03-20 13:40:28U2022-12-02 22:02:00.0<NA>201505.406518458926.401527<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
83240000CDFI226002202200000420220421<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강동구 성내동 163-16 경남빌딩 304호서울특별시 강동구 천호대로 1082, 경남빌딩 3층 304호 (성내동)05380주식회사 보스투어2022-04-21 13:27:07I2021-12-03 22:03:00.0<NA>211573.770265448168.954893<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
93010000CDFI22600220220000072022-02-18<NA>5제외/삭제/전출15전출2023-02-07<NA><NA><NA><NA><NA><NA>서울특별시 중구 다동 97 508호서울특별시 중구 을지로3길 34, 508호 (다동)04522져스트래블2023-02-07 15:26:46U2022-12-02 00:09:00.0<NA>198300.022319451702.546232<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명문화사업자구분명지역구분명총층수주변환경명제작취급품목내용보험기관명건물용도명지상층수지하층수객실수건축연면적영문상호명영문상호주소선박총톤수선박척수선박제원무대면적좌석수기념품종류회의실별동시수용인원시설면적놀이기구수내역놀이시설수방송시설유무발전시설유무의무실유무안내소유무기획여행보험시작일자기획여행보험종료일자자본금보험시작일자보험종료일자부대시설내역시설규모
98623000000CDFI22600220020000052002-01-15<NA>1영업/정상13영업중<NA><NA><NA><NA>02-723-8822<NA><NA>서울특별시 종로구 수송동 58 두산위브파빌리온 1021호서울특별시 종로구 삼봉로 81, 두산위브파빌리온 1021호 (수송동)03150(주)블루투어2023-05-04 18:41:28U2022-12-05 00:07:00.0<NA>198324.653632452252.812389<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
98633220000CDFI22600220140000292014-05-26<NA>5제외/삭제/전출15전출2023-05-22<NA><NA><NA>02-542-2692<NA><NA>서울특별시 강남구 역삼동 776-13 성원빌딩 B1-02호서울특별시 강남구 논현로 320, 성원빌딩 B1층 02호 (역삼동)06228(주)유닉투어2023-05-22 11:04:55U2022-12-04 22:04:00.0<NA>203520.088244443518.888342<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
98643210000CDFI22600220110000592011-12-23<NA>1영업/정상13영업중<NA><NA><NA><NA>02-511-5240<NA><NA>서울특별시 서초구 서초동 1445-3 국제전자센터서울특별시 서초구 효령로 304, 국제전자센터 5층 34호 (서초동)06720(주)투어비지니스2024-05-07 18:19:09U2023-12-05 00:09:00.0<NA>201501.67266442505.573143<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
98653040000CDFI22600220220000052022-05-02<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 광진구 광장동 145-8 워커힐아파트서울특별시 광진구 아차산로 635, 워커힐아파트 120-2호 (광장동)04964주식회사 한신제네럴2023-11-24 11:31:28U2022-10-31 22:06:00.0<NA>209345.941766449811.718208<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
98663000000CDFI22600220060000742006-04-26<NA>1영업/정상13영업중<NA><NA><NA><NA>02-733-7633<NA><NA>서울특별시 종로구 종로2가 56-6서울특별시 종로구 종로 96, 한올타워 5층 (종로2가)03191이굿투어(주)2024-04-22 13:22:30U2023-12-03 22:04:00.0<NA>198892.023011451952.062116<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
98673210000CDFI22600220070000192007-05-08<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 서초구 서초동 1302-1 서초오피스텔서울특별시 서초구 서운로 226, 서초오피스텔 5층 524호 (서초동)06609지니인터내셔널2024-05-07 18:53:28U2023-12-05 00:09:00.0<NA>201853.889909444549.81239<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
98683170000CDFI226002202200000220220513<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 금천구 가산동 60-11 스타밸리 1401호서울특별시 금천구 디지털로9길 99, 스타밸리 1401호 (가산동)08510월드차터서비스2022-06-09 16:43:12U2021-12-05 23:01:00.0<NA>189748.024164442174.424112<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
98693010000CDFI226002202000002720200410<NA>5제외/삭제/전출15전출20220513<NA><NA><NA>02-3789-0550<NA><NA>서울특별시 중구 다동 92 513호서울특별시 중구 다동길 46, 513호 (다동)04522티아이 투어2022-05-13 09:54:39U2021-12-04 23:05:00.0<NA>198345.022154451737.693395<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
98703120000CDFI22600220220000042020-04-10<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 서대문구 합동 116 SK리쳄블서울특별시 서대문구 서소문로 45, SK리쳄블 14층 1402호 (합동)03741티아이 투어2024-02-21 13:13:27U2023-12-01 22:03:00.0<NA>196945.454641451003.162676<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
98713000000CDFI22600220210000132021-04-30<NA>5제외/삭제/전출15전출2024-04-24<NA><NA><NA>02-736-4840<NA><NA>서울특별시 종로구 인사동 194-4 하나로빌딩 808호서울특별시 종로구 인사동5길 25, 하나로빌딩 808호 (인사동)03162(주)나폴레옹투어2024-04-24 14:18:43U2023-12-03 22:06:00.0<NA>198643.543485452199.798612<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>