Overview

Dataset statistics

Number of variables64
Number of observations1261
Missing cells28052
Missing cells (%)34.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory676.2 KiB
Average record size in memory549.1 B

Variable types

Numeric13
Categorical23
Text8
DateTime7
Unsupported13

Dataset

Description2023-08-01
Author지방행정인허가공개데이터
URLhttps://bigdata.busan.go.kr/data/bigDataDetailView.do?menuCode=M00000000007&hdfs_file_sn=20230901050101123072

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
문화체육업종명 has constant value ""Constant
상세영업상태명 is highly imbalanced (58.2%)Imbalance
지역구분명 is highly imbalanced (68.8%)Imbalance
주변환경명 is highly imbalanced (73.5%)Imbalance
건물용도명 is highly imbalanced (71.9%)Imbalance
영문상호주소 is highly imbalanced (93.3%)Imbalance
기획여행보험시작일자 is highly imbalanced (99.1%)Imbalance
기획여행보험종료일자 is highly imbalanced (99.1%)Imbalance
인허가취소일자 has 1215 (96.4%) missing valuesMissing
폐업일자 has 372 (29.5%) missing valuesMissing
휴업시작일자 has 1256 (99.6%) missing valuesMissing
휴업종료일자 has 1256 (99.6%) missing valuesMissing
재개업일자 has 1261 (100.0%) missing valuesMissing
소재지전화 has 340 (27.0%) missing valuesMissing
소재지면적 has 1261 (100.0%) missing valuesMissing
소재지우편번호 has 606 (48.1%) missing valuesMissing
도로명전체주소 has 56 (4.4%) missing valuesMissing
도로명우편번호 has 399 (31.6%) missing valuesMissing
업태구분명 has 1261 (100.0%) missing valuesMissing
좌표정보(x) has 40 (3.2%) missing valuesMissing
좌표정보(y) has 40 (3.2%) missing valuesMissing
총층수 has 748 (59.3%) missing valuesMissing
제작취급품목내용 has 1261 (100.0%) missing valuesMissing
지상층수 has 724 (57.4%) missing valuesMissing
지하층수 has 807 (64.0%) missing valuesMissing
영문상호명 has 1230 (97.5%) missing valuesMissing
선박제원 has 1261 (100.0%) missing valuesMissing
기념품종류 has 1261 (100.0%) missing valuesMissing
시설면적 has 692 (54.9%) missing valuesMissing
놀이기구수내역 has 1261 (100.0%) missing valuesMissing
방송시설유무 has 1261 (100.0%) missing valuesMissing
발전시설유무 has 1261 (100.0%) missing valuesMissing
의무실유무 has 1261 (100.0%) missing valuesMissing
안내소유무 has 1261 (100.0%) missing valuesMissing
자본금 has 353 (28.0%) missing valuesMissing
보험시작일자 has 417 (33.1%) missing valuesMissing
보험종료일자 has 416 (33.0%) missing valuesMissing
부대시설내역 has 1261 (100.0%) missing valuesMissing
시설규모 has 692 (54.9%) missing valuesMissing
Unnamed: 63 has 1261 (100.0%) missing valuesMissing
자본금 is highly skewed (γ1 = 20.53385693)Skewed
번호 has unique valuesUnique
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
제작취급품목내용 is an unsupported type, check if it needs cleaning or further analysisUnsupported
선박제원 is an unsupported type, check if it needs cleaning or further analysisUnsupported
기념품종류 is an unsupported type, check if it needs cleaning or further analysisUnsupported
놀이기구수내역 is an unsupported type, check if it needs cleaning or further analysisUnsupported
방송시설유무 is an unsupported type, check if it needs cleaning or further analysisUnsupported
발전시설유무 is an unsupported type, check if it needs cleaning or further analysisUnsupported
의무실유무 is an unsupported type, check if it needs cleaning or further analysisUnsupported
안내소유무 is an unsupported type, check if it needs cleaning or further analysisUnsupported
부대시설내역 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 63 is an unsupported type, check if it needs cleaning or further analysisUnsupported
총층수 has 314 (24.9%) zerosZeros
지상층수 has 314 (24.9%) zerosZeros
지하층수 has 357 (28.3%) zerosZeros
시설면적 has 285 (22.6%) zerosZeros
자본금 has 82 (6.5%) zerosZeros
시설규모 has 285 (22.6%) zerosZeros

Reproduction

Analysis started2024-04-16 06:43:48.367988
Analysis finished2024-04-16 06:43:49.530425
Duration1.16 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct1261
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean631
Minimum1
Maximum1261
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.2 KiB
2024-04-16T15:43:49.790543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile64
Q1316
median631
Q3946
95-th percentile1198
Maximum1261
Range1260
Interquartile range (IQR)630

Descriptive statistics

Standard deviation364.16365
Coefficient of variation (CV)0.57712148
Kurtosis-1.2
Mean631
Median Absolute Deviation (MAD)315
Skewness0
Sum795691
Variance132615.17
MonotonicityStrictly increasing
2024-04-16T15:43:49.902707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
839 1
 
0.1%
846 1
 
0.1%
845 1
 
0.1%
844 1
 
0.1%
843 1
 
0.1%
842 1
 
0.1%
841 1
 
0.1%
840 1
 
0.1%
838 1
 
0.1%
Other values (1251) 1251
99.2%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
1261 1
0.1%
1260 1
0.1%
1259 1
0.1%
1258 1
0.1%
1257 1
0.1%
1256 1
0.1%
1255 1
0.1%
1254 1
0.1%
1253 1
0.1%
1252 1
0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
국내여행업
1261 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
국내여행업 1261
100.0%

Length

2024-04-16T15:43:50.023890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:43:50.095329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국내여행업 1261
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
03_12_01_P
1261 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row03_12_01_P
2nd row03_12_01_P
3rd row03_12_01_P
4th row03_12_01_P
5th row03_12_01_P

Common Values

ValueCountFrequency (%)
03_12_01_P 1261
100.0%

Length

2024-04-16T15:43:50.173544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:43:50.243034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
03_12_01_p 1261
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3310491.7
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.2 KiB
2024-04-16T15:43:50.307248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3250000
Q13290000
median3300000
Q33340000
95-th percentile3380000
Maximum3400000
Range150000
Interquartile range (IQR)50000

Descriptive statistics

Standard deviation41228.122
Coefficient of variation (CV)0.012453776
Kurtosis-0.85906173
Mean3310491.7
Median Absolute Deviation (MAD)30000
Skewness0.37050294
Sum4.17453 × 109
Variance1.6997581 × 109
MonotonicityIncreasing
2024-04-16T15:43:50.396333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3290000 270
21.4%
3250000 144
11.4%
3330000 142
11.3%
3270000 132
10.5%
3370000 100
 
7.9%
3300000 98
 
7.8%
3310000 77
 
6.1%
3350000 62
 
4.9%
3380000 59
 
4.7%
3340000 37
 
2.9%
Other values (6) 140
11.1%
ValueCountFrequency (%)
3250000 144
11.4%
3260000 13
 
1.0%
3270000 132
10.5%
3280000 20
 
1.6%
3290000 270
21.4%
3300000 98
 
7.8%
3310000 77
 
6.1%
3320000 35
 
2.8%
3330000 142
11.3%
3340000 37
 
2.9%
ValueCountFrequency (%)
3400000 16
 
1.3%
3390000 34
 
2.7%
3380000 59
4.7%
3370000 100
7.9%
3360000 22
 
1.7%
3350000 62
4.9%
3340000 37
 
2.9%
3330000 142
11.3%
3320000 35
 
2.8%
3310000 77
6.1%
Distinct366
Distinct (%)29.0%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
2024-04-16T15:43:50.562046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters25220
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

Unique117 ?
Unique (%)9.3%

Sample

1st rowCDFI2260012007000013
2nd rowCDFI2260012019000002
3rd rowCDFI2260012019000003
4th rowCDFI2260012019000006
5th rowCDFI2260012016000001
ValueCountFrequency (%)
cdfi2260012011000001 15
 
1.2%
cdfi2260012020000001 14
 
1.1%
cdfi2260012016000001 13
 
1.0%
cdfi2260012019000001 13
 
1.0%
cdfi2260012018000002 12
 
1.0%
cdfi2260012001000001 12
 
1.0%
cdfi2260012021000003 12
 
1.0%
cdfi2260012019000002 11
 
0.9%
cdfi2260012017000002 11
 
0.9%
cdfi2260012017000001 11
 
0.9%
Other values (356) 1137
90.2%
2024-04-16T15:43:50.847286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10358
41.1%
2 4177
16.6%
1 2577
 
10.2%
6 1489
 
5.9%
C 1261
 
5.0%
D 1261
 
5.0%
F 1261
 
5.0%
I 1261
 
5.0%
9 423
 
1.7%
3 256
 
1.0%
Other values (4) 896
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20176
80.0%
Uppercase Letter 5044
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10358
51.3%
2 4177
20.7%
1 2577
 
12.8%
6 1489
 
7.4%
9 423
 
2.1%
3 256
 
1.3%
4 255
 
1.3%
5 244
 
1.2%
7 226
 
1.1%
8 171
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
C 1261
25.0%
D 1261
25.0%
F 1261
25.0%
I 1261
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 20176
80.0%
Latin 5044
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10358
51.3%
2 4177
20.7%
1 2577
 
12.8%
6 1489
 
7.4%
9 423
 
2.1%
3 256
 
1.3%
4 255
 
1.3%
5 244
 
1.2%
7 226
 
1.1%
8 171
 
0.8%
Latin
ValueCountFrequency (%)
C 1261
25.0%
D 1261
25.0%
F 1261
25.0%
I 1261
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25220
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10358
41.1%
2 4177
16.6%
1 2577
 
10.2%
6 1489
 
5.9%
C 1261
 
5.0%
D 1261
 
5.0%
F 1261
 
5.0%
I 1261
 
5.0%
9 423
 
1.7%
3 256
 
1.0%
Other values (4) 896
 
3.6%
Distinct1114
Distinct (%)88.3%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
Minimum1984-09-24 00:00:00
Maximum2023-07-06 00:00:00
2024-04-16T15:43:50.960464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T15:43:51.061771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Date

MISSING 

Distinct40
Distinct (%)87.0%
Missing1215
Missing (%)96.4%
Memory size10.0 KiB
Minimum2003-08-22 00:00:00
Maximum2020-02-26 00:00:00
2024-04-16T15:43:51.207423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T15:43:51.338849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
Distinct4
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
3
885 
1
305 
4
 
66
2
 
5

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row3
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 885
70.2%
1 305
 
24.2%
4 66
 
5.2%
2 5
 
0.4%

Length

2024-04-16T15:43:51.442217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:43:51.521412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 885
70.2%
1 305
 
24.2%
4 66
 
5.2%
2 5
 
0.4%

영업상태명
Categorical

Distinct4
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
폐업
885 
영업/정상
305 
취소/말소/만료/정지/중지
 
66
휴업
 
5

Length

Max length14
Median length2
Mean length3.3536875
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 885
70.2%
영업/정상 305
 
24.2%
취소/말소/만료/정지/중지 66
 
5.2%
휴업 5
 
0.4%

Length

2024-04-16T15:43:51.606892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:43:51.689269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 885
70.2%
영업/정상 305
 
24.2%
취소/말소/만료/정지/중지 66
 
5.2%
휴업 5
 
0.4%

상세영업상태코드
Real number (ℝ)

Distinct7
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.8858049
Minimum2
Maximum35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.2 KiB
2024-04-16T15:43:51.757914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3
Q13
median3
Q313
95-th percentile30
Maximum35
Range33
Interquartile range (IQR)10

Descriptive statistics

Standard deviation7.1102182
Coefficient of variation (CV)1.0325907
Kurtosis4.392851
Mean6.8858049
Median Absolute Deviation (MAD)0
Skewness2.1281771
Sum8683
Variance50.555203
MonotonicityNot monotonic
2024-04-16T15:43:51.834112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
3 885
70.2%
13 305
 
24.2%
31 45
 
3.6%
30 15
 
1.2%
2 5
 
0.4%
35 5
 
0.4%
33 1
 
0.1%
ValueCountFrequency (%)
2 5
 
0.4%
3 885
70.2%
13 305
 
24.2%
30 15
 
1.2%
31 45
 
3.6%
33 1
 
0.1%
35 5
 
0.4%
ValueCountFrequency (%)
35 5
 
0.4%
33 1
 
0.1%
31 45
 
3.6%
30 15
 
1.2%
13 305
 
24.2%
3 885
70.2%
2 5
 
0.4%

상세영업상태명
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
폐업
885 
영업중
305 
등록취소
 
45
허가취소
 
15
휴업
 
5
Other values (2)
 
6

Length

Max length4
Median length2
Mean length2.3465504
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 885
70.2%
영업중 305
 
24.2%
등록취소 45
 
3.6%
허가취소 15
 
1.2%
휴업 5
 
0.4%
직권말소 5
 
0.4%
지정취소 1
 
0.1%

Length

2024-04-16T15:43:51.928668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:43:52.026780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 885
70.2%
영업중 305
 
24.2%
등록취소 45
 
3.6%
허가취소 15
 
1.2%
휴업 5
 
0.4%
직권말소 5
 
0.4%
지정취소 1
 
0.1%

폐업일자
Date

MISSING 

Distinct736
Distinct (%)82.8%
Missing372
Missing (%)29.5%
Memory size10.0 KiB
Minimum1997-12-11 00:00:00
Maximum2023-07-11 00:00:00
2024-04-16T15:43:52.137228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T15:43:52.276691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Date

MISSING 

Distinct5
Distinct (%)100.0%
Missing1256
Missing (%)99.6%
Memory size10.0 KiB
Minimum2013-05-10 00:00:00
Maximum2021-01-01 00:00:00
2024-04-16T15:43:52.384851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T15:43:52.484532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)

휴업종료일자
Date

MISSING 

Distinct5
Distinct (%)100.0%
Missing1256
Missing (%)99.6%
Memory size10.0 KiB
Minimum2014-05-09 00:00:00
Maximum2022-11-30 00:00:00
2024-04-16T15:43:52.577291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T15:43:52.680663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1261
Missing (%)100.0%
Memory size11.2 KiB

소재지전화
Text

MISSING 

Distinct894
Distinct (%)97.1%
Missing340
Missing (%)27.0%
Memory size10.0 KiB
2024-04-16T15:43:52.885786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length12
Mean length10.736156
Min length7

Characters and Unicode

Total characters9888
Distinct characters16
Distinct categories6 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique868 ?
Unique (%)94.2%

Sample

1st row051-469-7731
2nd row051241 0909
3rd row051-852-2088
4th row051-464-6464
5th row051-463-0926
ValueCountFrequency (%)
051 27
 
2.8%
740-6353 3
 
0.3%
637-6200 2
 
0.2%
809 2
 
0.2%
818-8001 2
 
0.2%
051-816-0019 2
 
0.2%
051-526-8686 2
 
0.2%
051-743-1159 2
 
0.2%
051-612-7788 2
 
0.2%
051-555-1780 2
 
0.2%
Other values (908) 927
95.3%
2024-04-16T15:43:53.181931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1567
15.8%
- 1425
14.4%
1 1330
13.5%
5 1302
13.2%
6 721
7.3%
8 715
7.2%
4 668
6.8%
2 621
 
6.3%
7 599
 
6.1%
3 487
 
4.9%
Other values (6) 453
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8381
84.8%
Dash Punctuation 1425
 
14.4%
Space Separator 52
 
0.5%
Close Punctuation 16
 
0.2%
Other Punctuation 10
 
0.1%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1567
18.7%
1 1330
15.9%
5 1302
15.5%
6 721
8.6%
8 715
8.5%
4 668
8.0%
2 621
 
7.4%
7 599
 
7.1%
3 487
 
5.8%
9 371
 
4.4%
Other Punctuation
ValueCountFrequency (%)
. 7
70.0%
, 3
30.0%
Dash Punctuation
ValueCountFrequency (%)
- 1425
100.0%
Space Separator
ValueCountFrequency (%)
52
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9888
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1567
15.8%
- 1425
14.4%
1 1330
13.5%
5 1302
13.2%
6 721
7.3%
8 715
7.2%
4 668
6.8%
2 621
 
6.3%
7 599
 
6.1%
3 487
 
4.9%
Other values (6) 453
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9888
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1567
15.8%
- 1425
14.4%
1 1330
13.5%
5 1302
13.2%
6 721
7.3%
8 715
7.2%
4 668
6.8%
2 621
 
6.3%
7 599
 
6.1%
3 487
 
4.9%
Other values (6) 453
 
4.6%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1261
Missing (%)100.0%
Memory size11.2 KiB

소재지우편번호
Text

MISSING 

Distinct301
Distinct (%)46.0%
Missing606
Missing (%)48.1%
Memory size10.0 KiB
2024-04-16T15:43:53.439474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters4585
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

Unique183 ?
Unique (%)27.9%

Sample

1st row600-815
2nd row600-045
3rd row600-046
4th row600-815
5th row600-814
ValueCountFrequency (%)
600-815 17
 
2.6%
614-854 16
 
2.4%
614-844 11
 
1.7%
614-849 11
 
1.7%
612-824 10
 
1.5%
601-839 10
 
1.5%
607-827 10
 
1.5%
601-715 9
 
1.4%
614-828 9
 
1.4%
601-010 8
 
1.2%
Other values (291) 544
83.1%
2024-04-16T15:43:53.790836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 767
16.7%
0 686
15.0%
1 676
14.7%
- 655
14.3%
8 566
12.3%
4 323
7.0%
2 314
6.8%
7 214
 
4.7%
3 155
 
3.4%
5 125
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3930
85.7%
Dash Punctuation 655
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 767
19.5%
0 686
17.5%
1 676
17.2%
8 566
14.4%
4 323
8.2%
2 314
8.0%
7 214
 
5.4%
3 155
 
3.9%
5 125
 
3.2%
9 104
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 655
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4585
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 767
16.7%
0 686
15.0%
1 676
14.7%
- 655
14.3%
8 566
12.3%
4 323
7.0%
2 314
6.8%
7 214
 
4.7%
3 155
 
3.4%
5 125
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4585
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 767
16.7%
0 686
15.0%
1 676
14.7%
- 655
14.3%
8 566
12.3%
4 323
7.0%
2 314
6.8%
7 214
 
4.7%
3 155
 
3.4%
5 125
 
2.7%
Distinct1178
Distinct (%)93.4%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
2024-04-16T15:43:54.037178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length39
Mean length25.755749
Min length12

Characters and Unicode

Total characters32478
Distinct characters390
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

Unique1120 ?
Unique (%)88.8%

Sample

1st row부산광역시 중구 중앙동4가 53-30
2nd row부산광역시 중구 남포동4가 44-3번지
3rd row부산광역시 중구 대창동1가 51
4th row부산광역시 중구 중앙동4가 15-3번지
5th row부산광역시 중구 대창동1가 51
ValueCountFrequency (%)
부산광역시 1258
 
20.1%
부산진구 270
 
4.3%
중구 144
 
2.3%
해운대구 142
 
2.3%
동구 133
 
2.1%
연제구 100
 
1.6%
동래구 99
 
1.6%
부전동 94
 
1.5%
초량동 91
 
1.5%
남구 76
 
1.2%
Other values (1812) 3867
61.6%
2024-04-16T15:43:54.438436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5013
 
15.4%
1702
 
5.2%
1655
 
5.1%
1 1612
 
5.0%
1602
 
4.9%
1304
 
4.0%
1293
 
4.0%
1273
 
3.9%
1267
 
3.9%
- 1104
 
3.4%
Other values (380) 14653
45.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19055
58.7%
Decimal Number 6964
 
21.4%
Space Separator 5013
 
15.4%
Dash Punctuation 1104
 
3.4%
Uppercase Letter 156
 
0.5%
Lowercase Letter 140
 
0.4%
Close Punctuation 17
 
0.1%
Open Punctuation 17
 
0.1%
Other Punctuation 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1702
 
8.9%
1655
 
8.7%
1602
 
8.4%
1304
 
6.8%
1293
 
6.8%
1273
 
6.7%
1267
 
6.6%
686
 
3.6%
642
 
3.4%
370
 
1.9%
Other values (325) 7261
38.1%
Uppercase Letter
ValueCountFrequency (%)
S 33
21.2%
T 18
11.5%
K 14
9.0%
C 13
 
8.3%
B 11
 
7.1%
A 10
 
6.4%
E 8
 
5.1%
I 8
 
5.1%
V 6
 
3.8%
O 6
 
3.8%
Other values (11) 29
18.6%
Lowercase Letter
ValueCountFrequency (%)
e 30
21.4%
o 19
13.6%
l 11
 
7.9%
i 10
 
7.1%
p 10
 
7.1%
m 9
 
6.4%
d 9
 
6.4%
a 9
 
6.4%
n 9
 
6.4%
w 9
 
6.4%
Other values (7) 15
10.7%
Decimal Number
ValueCountFrequency (%)
1 1612
23.1%
2 967
13.9%
3 766
11.0%
4 693
10.0%
0 650
9.3%
5 512
 
7.4%
7 482
 
6.9%
8 482
 
6.9%
6 461
 
6.6%
9 339
 
4.9%
Other Punctuation
ValueCountFrequency (%)
/ 7
58.3%
, 4
33.3%
@ 1
 
8.3%
Space Separator
ValueCountFrequency (%)
5013
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1104
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19055
58.7%
Common 13127
40.4%
Latin 296
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1702
 
8.9%
1655
 
8.7%
1602
 
8.4%
1304
 
6.8%
1293
 
6.8%
1273
 
6.7%
1267
 
6.6%
686
 
3.6%
642
 
3.4%
370
 
1.9%
Other values (325) 7261
38.1%
Latin
ValueCountFrequency (%)
S 33
 
11.1%
e 30
 
10.1%
o 19
 
6.4%
T 18
 
6.1%
K 14
 
4.7%
C 13
 
4.4%
l 11
 
3.7%
B 11
 
3.7%
i 10
 
3.4%
A 10
 
3.4%
Other values (28) 127
42.9%
Common
ValueCountFrequency (%)
5013
38.2%
1 1612
 
12.3%
- 1104
 
8.4%
2 967
 
7.4%
3 766
 
5.8%
4 693
 
5.3%
0 650
 
5.0%
5 512
 
3.9%
7 482
 
3.7%
8 482
 
3.7%
Other values (7) 846
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19055
58.7%
ASCII 13423
41.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5013
37.3%
1 1612
 
12.0%
- 1104
 
8.2%
2 967
 
7.2%
3 766
 
5.7%
4 693
 
5.2%
0 650
 
4.8%
5 512
 
3.8%
7 482
 
3.6%
8 482
 
3.6%
Other values (45) 1142
 
8.5%
Hangul
ValueCountFrequency (%)
1702
 
8.9%
1655
 
8.7%
1602
 
8.4%
1304
 
6.8%
1293
 
6.8%
1273
 
6.7%
1267
 
6.6%
686
 
3.6%
642
 
3.4%
370
 
1.9%
Other values (325) 7261
38.1%

도로명전체주소
Text

MISSING 

Distinct1163
Distinct (%)96.5%
Missing56
Missing (%)4.4%
Memory size10.0 KiB
2024-04-16T15:43:54.741811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length47
Mean length33.653942
Min length21

Characters and Unicode

Total characters40553
Distinct characters428
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1128 ?
Unique (%)93.6%

Sample

1st row부산광역시 중구 중앙대로81번길 2 (중앙동4가)
2nd row부산광역시 중구 자갈치해안로 60 (남포동4가)
3rd row부산광역시 중구 해관로 89, 중앙빌딩 707호 (대창동1가)
4th row부산광역시 중구 충장대로 24, 부산항연안여객터미널 1층 (중앙동4가)
5th row부산광역시 중구 해관로 89, 610호 (대창동1가, 중앙빌딩)
ValueCountFrequency (%)
부산광역시 1203
 
15.8%
부산진구 253
 
3.3%
중앙대로 172
 
2.3%
중구 142
 
1.9%
해운대구 140
 
1.8%
2층 135
 
1.8%
동구 118
 
1.5%
연제구 100
 
1.3%
동래구 96
 
1.3%
남구 73
 
1.0%
Other values (1882) 5202
68.1%
2024-04-16T15:43:55.158653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6701
 
16.5%
1671
 
4.1%
1657
 
4.1%
1597
 
3.9%
1 1434
 
3.5%
1301
 
3.2%
1263
 
3.1%
, 1262
 
3.1%
1234
 
3.0%
1211
 
3.0%
Other values (418) 21222
52.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 23293
57.4%
Space Separator 6701
 
16.5%
Decimal Number 6401
 
15.8%
Other Punctuation 1268
 
3.1%
Open Punctuation 1202
 
3.0%
Close Punctuation 1202
 
3.0%
Dash Punctuation 182
 
0.4%
Uppercase Letter 162
 
0.4%
Lowercase Letter 141
 
0.3%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1671
 
7.2%
1657
 
7.1%
1597
 
6.9%
1301
 
5.6%
1263
 
5.4%
1234
 
5.3%
1211
 
5.2%
1208
 
5.2%
807
 
3.5%
572
 
2.5%
Other values (363) 10772
46.2%
Uppercase Letter
ValueCountFrequency (%)
S 33
20.4%
T 16
9.9%
C 15
9.3%
K 15
9.3%
B 13
 
8.0%
A 12
 
7.4%
E 9
 
5.6%
I 8
 
4.9%
V 6
 
3.7%
W 5
 
3.1%
Other values (11) 30
18.5%
Lowercase Letter
ValueCountFrequency (%)
e 31
22.0%
o 19
13.5%
l 11
 
7.8%
i 10
 
7.1%
p 10
 
7.1%
a 9
 
6.4%
x 9
 
6.4%
m 9
 
6.4%
w 9
 
6.4%
d 9
 
6.4%
Other values (7) 15
10.6%
Decimal Number
ValueCountFrequency (%)
1 1434
22.4%
2 1001
15.6%
3 802
12.5%
0 716
11.2%
4 522
 
8.2%
5 474
 
7.4%
6 420
 
6.6%
7 368
 
5.7%
8 337
 
5.3%
9 327
 
5.1%
Other Punctuation
ValueCountFrequency (%)
, 1262
99.5%
/ 6
 
0.5%
Space Separator
ValueCountFrequency (%)
6701
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1202
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1202
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 182
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 23293
57.4%
Common 16957
41.8%
Latin 303
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1671
 
7.2%
1657
 
7.1%
1597
 
6.9%
1301
 
5.6%
1263
 
5.4%
1234
 
5.3%
1211
 
5.2%
1208
 
5.2%
807
 
3.5%
572
 
2.5%
Other values (363) 10772
46.2%
Latin
ValueCountFrequency (%)
S 33
 
10.9%
e 31
 
10.2%
o 19
 
6.3%
T 16
 
5.3%
C 15
 
5.0%
K 15
 
5.0%
B 13
 
4.3%
A 12
 
4.0%
l 11
 
3.6%
i 10
 
3.3%
Other values (28) 128
42.2%
Common
ValueCountFrequency (%)
6701
39.5%
1 1434
 
8.5%
, 1262
 
7.4%
( 1202
 
7.1%
) 1202
 
7.1%
2 1001
 
5.9%
3 802
 
4.7%
0 716
 
4.2%
4 522
 
3.1%
5 474
 
2.8%
Other values (7) 1641
 
9.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 23293
57.4%
ASCII 17260
42.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6701
38.8%
1 1434
 
8.3%
, 1262
 
7.3%
( 1202
 
7.0%
) 1202
 
7.0%
2 1001
 
5.8%
3 802
 
4.6%
0 716
 
4.1%
4 522
 
3.0%
5 474
 
2.7%
Other values (45) 1944
 
11.3%
Hangul
ValueCountFrequency (%)
1671
 
7.2%
1657
 
7.1%
1597
 
6.9%
1301
 
5.6%
1263
 
5.4%
1234
 
5.3%
1211
 
5.2%
1208
 
5.2%
807
 
3.5%
572
 
2.5%
Other values (363) 10772
46.2%

도로명우편번호
Text

MISSING 

Distinct480
Distinct (%)55.7%
Missing399
Missing (%)31.6%
Memory size10.0 KiB
2024-04-16T15:43:55.432484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.187935
Min length5

Characters and Unicode

Total characters4472
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

Unique319 ?
Unique (%)37.0%

Sample

1st row48984
2nd row48924
3rd row48940
4th row48924
5th row48947
ValueCountFrequency (%)
47216 16
 
1.9%
48059 10
 
1.2%
48092 10
 
1.2%
47246 10
 
1.2%
49037 9
 
1.0%
48924 9
 
1.0%
47257 9
 
1.0%
48508 8
 
0.9%
48095 8
 
0.9%
48741 7
 
0.8%
Other values (470) 766
88.9%
2024-04-16T15:43:55.818913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 1020
22.8%
8 578
12.9%
7 536
12.0%
2 445
10.0%
6 354
 
7.9%
0 328
 
7.3%
1 311
 
7.0%
9 306
 
6.8%
5 283
 
6.3%
3 230
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4391
98.2%
Dash Punctuation 81
 
1.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 1020
23.2%
8 578
13.2%
7 536
12.2%
2 445
10.1%
6 354
 
8.1%
0 328
 
7.5%
1 311
 
7.1%
9 306
 
7.0%
5 283
 
6.4%
3 230
 
5.2%
Dash Punctuation
ValueCountFrequency (%)
- 81
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4472
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 1020
22.8%
8 578
12.9%
7 536
12.0%
2 445
10.0%
6 354
 
7.9%
0 328
 
7.3%
1 311
 
7.0%
9 306
 
6.8%
5 283
 
6.3%
3 230
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4472
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 1020
22.8%
8 578
12.9%
7 536
12.0%
2 445
10.0%
6 354
 
7.9%
0 328
 
7.3%
1 311
 
7.0%
9 306
 
6.8%
5 283
 
6.3%
3 230
 
5.1%
Distinct1217
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
2024-04-16T15:43:56.063639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length24
Mean length8.1237113
Min length2

Characters and Unicode

Total characters10244
Distinct characters495
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1177 ?
Unique (%)93.3%

Sample

1st row(주)팔성국제관광
2nd row부산남항유람선 자갈치크루즈
3rd row(주)태진투어
4th row(주)마린크루즈
5th row(주)모바일트래블
ValueCountFrequency (%)
주식회사 94
 
6.2%
여행사 30
 
2.0%
투어 16
 
1.1%
15
 
1.0%
tour 6
 
0.4%
여행 6
 
0.4%
부산투어 5
 
0.3%
협동조합 5
 
0.3%
우리여행사 3
 
0.2%
선경항공여행사 3
 
0.2%
Other values (1274) 1332
87.9%
2024-04-16T15:43:56.431229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
871
 
8.5%
( 772
 
7.5%
) 772
 
7.5%
511
 
5.0%
509
 
5.0%
508
 
5.0%
414
 
4.0%
407
 
4.0%
254
 
2.5%
179
 
1.7%
Other values (485) 5047
49.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8248
80.5%
Open Punctuation 772
 
7.5%
Close Punctuation 772
 
7.5%
Space Separator 254
 
2.5%
Uppercase Letter 119
 
1.2%
Lowercase Letter 38
 
0.4%
Other Punctuation 18
 
0.2%
Decimal Number 15
 
0.1%
Dash Punctuation 5
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
871
 
10.6%
511
 
6.2%
509
 
6.2%
508
 
6.2%
414
 
5.0%
407
 
4.9%
179
 
2.2%
175
 
2.1%
171
 
2.1%
170
 
2.1%
Other values (430) 4333
52.5%
Uppercase Letter
ValueCountFrequency (%)
T 24
20.2%
O 13
 
10.9%
B 7
 
5.9%
U 6
 
5.0%
L 6
 
5.0%
I 6
 
5.0%
R 6
 
5.0%
W 6
 
5.0%
H 6
 
5.0%
G 5
 
4.2%
Other values (12) 34
28.6%
Lowercase Letter
ValueCountFrequency (%)
r 7
18.4%
o 5
13.2%
u 4
10.5%
t 3
 
7.9%
e 3
 
7.9%
s 2
 
5.3%
a 2
 
5.3%
i 2
 
5.3%
l 1
 
2.6%
v 1
 
2.6%
Other values (8) 8
21.1%
Other Punctuation
ValueCountFrequency (%)
. 10
55.6%
& 5
27.8%
, 2
 
11.1%
: 1
 
5.6%
Decimal Number
ValueCountFrequency (%)
1 7
46.7%
2 5
33.3%
8 2
 
13.3%
0 1
 
6.7%
Math Symbol
ValueCountFrequency (%)
> 1
50.0%
1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 772
100.0%
Close Punctuation
ValueCountFrequency (%)
) 772
100.0%
Space Separator
ValueCountFrequency (%)
254
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8249
80.5%
Common 1838
 
17.9%
Latin 157
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
871
 
10.6%
511
 
6.2%
509
 
6.2%
508
 
6.2%
414
 
5.0%
407
 
4.9%
179
 
2.2%
175
 
2.1%
171
 
2.1%
170
 
2.1%
Other values (431) 4334
52.5%
Latin
ValueCountFrequency (%)
T 24
 
15.3%
O 13
 
8.3%
r 7
 
4.5%
B 7
 
4.5%
U 6
 
3.8%
L 6
 
3.8%
I 6
 
3.8%
R 6
 
3.8%
W 6
 
3.8%
H 6
 
3.8%
Other values (30) 70
44.6%
Common
ValueCountFrequency (%)
( 772
42.0%
) 772
42.0%
254
 
13.8%
. 10
 
0.5%
1 7
 
0.4%
& 5
 
0.3%
2 5
 
0.3%
- 5
 
0.3%
8 2
 
0.1%
, 2
 
0.1%
Other values (4) 4
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8244
80.5%
ASCII 1994
 
19.5%
Compat Jamo 4
 
< 0.1%
Arrows 1
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
871
 
10.6%
511
 
6.2%
509
 
6.2%
508
 
6.2%
414
 
5.0%
407
 
4.9%
179
 
2.2%
175
 
2.1%
171
 
2.1%
170
 
2.1%
Other values (427) 4329
52.5%
ASCII
ValueCountFrequency (%)
( 772
38.7%
) 772
38.7%
254
 
12.7%
T 24
 
1.2%
O 13
 
0.7%
. 10
 
0.5%
r 7
 
0.4%
1 7
 
0.4%
B 7
 
0.4%
U 6
 
0.3%
Other values (43) 122
 
6.1%
Compat Jamo
ValueCountFrequency (%)
2
50.0%
1
25.0%
1
25.0%
Arrows
ValueCountFrequency (%)
1
100.0%
None
ValueCountFrequency (%)
1
100.0%
Distinct1231
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
Minimum2002-10-18 13:15:15
Maximum2023-07-11 17:19:54
2024-04-16T15:43:56.545966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T15:43:56.650170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
U
677 
I
584 

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 (%)
U 677
53.7%
I 584
46.3%

Length

2024-04-16T15:43:56.752491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:43:56.824556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 677
53.7%
i 584
46.3%
Distinct455
Distinct (%)36.1%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
Minimum2018-08-31 23:59:59
Maximum2023-07-13 02:40:00
2024-04-16T15:43:56.908275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T15:43:57.029537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1261
Missing (%)100.0%
Memory size11.2 KiB

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct889
Distinct (%)72.8%
Missing40
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean388455.35
Minimum345960.71
Maximum419502.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.2 KiB
2024-04-16T15:43:57.135934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum345960.71
5-th percentile380581.16
Q1385759.7
median388099.05
Q3390440.37
95-th percentile397041.26
Maximum419502.8
Range73542.098
Interquartile range (IQR)4680.6763

Descriptive statistics

Standard deviation4762.1874
Coefficient of variation (CV)0.012259292
Kurtosis7.2812213
Mean388455.35
Median Absolute Deviation (MAD)2341.3231
Skewness-0.23314575
Sum4.7430398 × 108
Variance22678429
MonotonicityNot monotonic
2024-04-16T15:43:57.472926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
391411.179584558 16
 
1.3%
387225.613588405 13
 
1.0%
385507.640529964 11
 
0.9%
386093.674147239 10
 
0.8%
385754.477259156 9
 
0.7%
396180.621245267 8
 
0.6%
385502.492320068 7
 
0.6%
393284.046237794 7
 
0.6%
388922.806889486 7
 
0.6%
385473.576410347 6
 
0.5%
Other values (879) 1127
89.4%
(Missing) 40
 
3.2%
ValueCountFrequency (%)
345960.705738627 1
0.1%
371478.346756674 1
0.1%
373016.981172742 1
0.1%
373099.680011584 1
0.1%
373350.085112444 1
0.1%
373506.567424523 1
0.1%
374028.336209521 1
0.1%
374032.128682348 1
0.1%
374559.888606959 1
0.1%
374846.363500911 2
0.2%
ValueCountFrequency (%)
419502.803662759 1
0.1%
407681.842815605 1
0.1%
405161.575903041 1
0.1%
402013.571482491 2
0.2%
401991.886648924 1
0.1%
401723.132056378 1
0.1%
401654.448094696 1
0.1%
401510.614024228 1
0.1%
401502.4147474 1
0.1%
401448.811950828 1
0.1%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct889
Distinct (%)72.8%
Missing40
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean186473.32
Minimum174307.15
Maximum265785.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.2 KiB
2024-04-16T15:43:57.578126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum174307.15
5-th percentile179644.67
Q1182552.27
median186489.96
Q3189109.7
95-th percentile194733.01
Maximum265785.6
Range91478.456
Interquartile range (IQR)6557.4294

Descriptive statistics

Standard deviation5329.9915
Coefficient of variation (CV)0.028583131
Kurtosis42.1497
Mean186473.32
Median Absolute Deviation (MAD)3014.6768
Skewness3.319076
Sum2.2768393 × 108
Variance28408809
MonotonicityNot monotonic
2024-04-16T15:43:57.679227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
184052.403123326 16
 
1.3%
186408.726533861 13
 
1.0%
180548.792611588 11
 
0.9%
182068.358104572 10
 
0.8%
179113.980448491 9
 
0.7%
186522.350475257 8
 
0.6%
180297.579330875 7
 
0.6%
187432.534573096 7
 
0.6%
188106.837170815 7
 
0.6%
180297.978228543 6
 
0.5%
Other values (879) 1127
89.4%
(Missing) 40
 
3.2%
ValueCountFrequency (%)
174307.148168245 1
0.1%
174856.056137804 1
0.1%
175087.296427656 2
0.2%
176115.246760365 1
0.1%
176897.907425947 1
0.1%
177354.376036871 1
0.1%
177441.748341131 1
0.1%
177442.817428718 1
0.1%
177527.376138393 1
0.1%
177532.283470077 2
0.2%
ValueCountFrequency (%)
265785.603884031 1
0.1%
226490.138380316 1
0.1%
206488.089795797 1
0.1%
205732.232965666 1
0.1%
204665.784677421 1
0.1%
204621.655738547 1
0.1%
204592.491613115 1
0.1%
204214.040987968 1
0.1%
204186.113952008 1
0.1%
199051.512822937 1
0.1%

문화체육업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
국내여행업
1261 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
국내여행업 1261
100.0%

Length

2024-04-16T15:43:57.779115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:43:57.870271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국내여행업 1261
100.0%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
<NA>
729 
관광사업
532 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 729
57.8%
관광사업 532
42.2%

Length

2024-04-16T15:43:57.952857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:43:58.027258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 729
57.8%
관광사업 532
42.2%

지역구분명
Categorical

IMBALANCE 

Distinct14
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
<NA>
1033 
일반주거지역
 
64
일반상업지역
 
41
상업지역
 
34
근린상업지역
 
31
Other values (9)
 
58

Length

Max length6
Median length4
Mean length4.2545599
Min length4

Unique

Unique5 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1033
81.9%
일반주거지역 64
 
5.1%
일반상업지역 41
 
3.3%
상업지역 34
 
2.7%
근린상업지역 31
 
2.5%
준주거지역 28
 
2.2%
주거지역 14
 
1.1%
준공업지역 7
 
0.6%
자연녹지지역 4
 
0.3%
녹지지역 1
 
0.1%
Other values (4) 4
 
0.3%

Length

2024-04-16T15:43:58.115136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1033
81.9%
일반주거지역 64
 
5.1%
일반상업지역 41
 
3.3%
상업지역 34
 
2.7%
근린상업지역 31
 
2.5%
준주거지역 28
 
2.2%
주거지역 14
 
1.1%
준공업지역 7
 
0.6%
자연녹지지역 4
 
0.3%
녹지지역 1
 
0.1%
Other values (4) 4
 
0.3%

총층수
Real number (ℝ)

MISSING  ZEROS 

Distinct24
Distinct (%)4.7%
Missing748
Missing (%)59.3%
Infinite0
Infinite (%)0.0%
Mean2.2787524
Minimum0
Maximum50
Zeros314
Zeros (%)24.9%
Negative0
Negative (%)0.0%
Memory size11.2 KiB
2024-04-16T15:43:58.208204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile10
Maximum50
Range50
Interquartile range (IQR)3

Descriptive statistics

Standard deviation4.9857489
Coefficient of variation (CV)2.1879292
Kurtosis30.312302
Mean2.2787524
Median Absolute Deviation (MAD)0
Skewness4.7175637
Sum1169
Variance24.857692
MonotonicityNot monotonic
2024-04-16T15:43:58.330030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 314
24.9%
2 36
 
2.9%
4 34
 
2.7%
3 29
 
2.3%
5 21
 
1.7%
6 16
 
1.3%
1 15
 
1.2%
7 10
 
0.8%
10 7
 
0.6%
8 7
 
0.6%
Other values (14) 24
 
1.9%
(Missing) 748
59.3%
ValueCountFrequency (%)
0 314
24.9%
1 15
 
1.2%
2 36
 
2.9%
3 29
 
2.3%
4 34
 
2.7%
5 21
 
1.7%
6 16
 
1.3%
7 10
 
0.8%
8 7
 
0.6%
9 3
 
0.2%
ValueCountFrequency (%)
50 1
 
0.1%
37 1
 
0.1%
33 1
 
0.1%
31 3
0.2%
27 1
 
0.1%
21 1
 
0.1%
20 1
 
0.1%
19 1
 
0.1%
15 1
 
0.1%
14 1
 
0.1%

주변환경명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
<NA>
1103 
기타
 
85
학교정화(상대)
 
22
주택가주변
 
21
아파트지역
 
19
Other values (3)
 
11

Length

Max length8
Median length4
Mean length3.998414
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1103
87.5%
기타 85
 
6.7%
학교정화(상대) 22
 
1.7%
주택가주변 21
 
1.7%
아파트지역 19
 
1.5%
유흥업소밀집지역 5
 
0.4%
결혼예식장주변 4
 
0.3%
학교정화(절대) 2
 
0.2%

Length

2024-04-16T15:43:58.447418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:43:58.548119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1103
87.5%
기타 85
 
6.7%
학교정화(상대 22
 
1.7%
주택가주변 21
 
1.7%
아파트지역 19
 
1.5%
유흥업소밀집지역 5
 
0.4%
결혼예식장주변 4
 
0.3%
학교정화(절대 2
 
0.2%

제작취급품목내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1261
Missing (%)100.0%
Memory size11.2 KiB

보험기관명
Categorical

Distinct31
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
<NA>
448 
서울보증보험주식회사
260 
서울보증보험
247 
한국관광협회중앙회 여행공제회
83 
한국관광협회중앙회
66 
Other values (26)
157 

Length

Max length19
Median length16
Mean length7.1633624
Min length4

Unique

Unique15 ?
Unique (%)1.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 448
35.5%
서울보증보험주식회사 260
20.6%
서울보증보험 247
19.6%
한국관광협회중앙회 여행공제회 83
 
6.6%
한국관광협회중앙회 66
 
5.2%
한국관광협회 57
 
4.5%
서울보증보험(주) 19
 
1.5%
부산광역시관광협회 15
 
1.2%
한국관광협회중앙회여행공제회 11
 
0.9%
한국관광협회중앙회 관광공제회 10
 
0.8%
Other values (21) 45
 
3.6%

Length

2024-04-16T15:43:58.664436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 448
32.8%
서울보증보험주식회사 260
19.0%
서울보증보험 248
18.1%
한국관광협회중앙회 161
 
11.8%
여행공제회 84
 
6.1%
한국관광협회 58
 
4.2%
서울보증보험(주 19
 
1.4%
관광공제회 19
 
1.4%
부산광역시관광협회 15
 
1.1%
한국관광협회중앙회여행공제회 11
 
0.8%
Other values (20) 44
 
3.2%

건물용도명
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
<NA>
1015 
근린생활시설
172 
사무실
 
55
교육연구시설
 
6
기타
 
5
Other values (6)
 
8

Length

Max length15
Median length4
Mean length4.2394925
Min length2

Unique

Unique4 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1015
80.5%
근린생활시설 172
 
13.6%
사무실 55
 
4.4%
교육연구시설 6
 
0.5%
기타 5
 
0.4%
아파트 2
 
0.2%
유통시설 2
 
0.2%
다가구용 주택(공동주택적용) 1
 
0.1%
콘도미니엄 1
 
0.1%
복지시설 1
 
0.1%

Length

2024-04-16T15:43:58.762472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1015
80.4%
근린생활시설 172
 
13.6%
사무실 55
 
4.4%
교육연구시설 6
 
0.5%
기타 5
 
0.4%
아파트 2
 
0.2%
유통시설 2
 
0.2%
다가구용 1
 
0.1%
주택(공동주택적용 1
 
0.1%
콘도미니엄 1
 
0.1%
Other values (2) 2
 
0.2%

지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct25
Distinct (%)4.7%
Missing724
Missing (%)57.4%
Infinite0
Infinite (%)0.0%
Mean2.1806331
Minimum0
Maximum43
Zeros314
Zeros (%)24.9%
Negative0
Negative (%)0.0%
Memory size11.2 KiB
2024-04-16T15:43:58.850061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile9
Maximum43
Range43
Interquartile range (IQR)3

Descriptive statistics

Standard deviation4.548552
Coefficient of variation (CV)2.085886
Kurtosis23.50238
Mean2.1806331
Median Absolute Deviation (MAD)0
Skewness4.1934129
Sum1171
Variance20.689326
MonotonicityNot monotonic
2024-04-16T15:43:58.955724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0 314
24.9%
2 60
 
4.8%
3 39
 
3.1%
4 26
 
2.1%
5 24
 
1.9%
1 18
 
1.4%
6 10
 
0.8%
9 8
 
0.6%
7 8
 
0.6%
10 6
 
0.5%
Other values (15) 24
 
1.9%
(Missing) 724
57.4%
ValueCountFrequency (%)
0 314
24.9%
1 18
 
1.4%
2 60
 
4.8%
3 39
 
3.1%
4 26
 
2.1%
5 24
 
1.9%
6 10
 
0.8%
7 8
 
0.6%
8 4
 
0.3%
9 8
 
0.6%
ValueCountFrequency (%)
43 1
 
0.1%
32 1
 
0.1%
29 1
 
0.1%
26 3
0.2%
24 1
 
0.1%
23 1
 
0.1%
22 1
 
0.1%
20 1
 
0.1%
17 1
 
0.1%
16 2
0.2%

지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)1.8%
Missing807
Missing (%)64.0%
Infinite0
Infinite (%)0.0%
Mean0.34361233
Minimum0
Maximum7
Zeros357
Zeros (%)28.3%
Negative0
Negative (%)0.0%
Memory size11.2 KiB
2024-04-16T15:43:59.055871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.87948971
Coefficient of variation (CV)2.5595406
Kurtosis19.477618
Mean0.34361233
Median Absolute Deviation (MAD)0
Skewness3.9841253
Sum156
Variance0.77350215
MonotonicityNot monotonic
2024-04-16T15:43:59.157640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 357
28.3%
1 70
 
5.6%
2 14
 
1.1%
5 5
 
0.4%
3 4
 
0.3%
4 2
 
0.2%
6 1
 
0.1%
7 1
 
0.1%
(Missing) 807
64.0%
ValueCountFrequency (%)
0 357
28.3%
1 70
 
5.6%
2 14
 
1.1%
3 4
 
0.3%
4 2
 
0.2%
5 5
 
0.4%
6 1
 
0.1%
7 1
 
0.1%
ValueCountFrequency (%)
7 1
 
0.1%
6 1
 
0.1%
5 5
 
0.4%
4 2
 
0.2%
3 4
 
0.3%
2 14
 
1.1%
1 70
 
5.6%
0 357
28.3%

객실수
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
<NA>
904 
0
357 

Length

Max length4
Median length4
Mean length3.1506741
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 904
71.7%
0 357
 
28.3%

Length

2024-04-16T15:43:59.269578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:43:59.367190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 904
71.7%
0 357
 
28.3%

건축연면적
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
<NA>
904 
0
357 

Length

Max length4
Median length4
Mean length3.1506741
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 904
71.7%
0 357
 
28.3%

Length

2024-04-16T15:43:59.470482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:43:59.566171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 904
71.7%
0 357
 
28.3%

영문상호명
Text

MISSING 

Distinct31
Distinct (%)100.0%
Missing1230
Missing (%)97.5%
Memory size10.0 KiB
2024-04-16T15:43:59.732555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length25
Mean length20.258065
Min length7

Characters and Unicode

Total characters628
Distinct characters52
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)100.0%

Sample

1st rowSEOKWANG Travel
2nd rowEMTCO Limited
3rd rowBus Tour Travel Agency
4th rowLeaders Tour
5th rowGORYE AIR TRAVEL Co., Ltd
ValueCountFrequency (%)
tour 14
 
13.2%
travel 10
 
9.4%
co 7
 
6.6%
ltd 7
 
6.6%
co.,ltd 5
 
4.7%
agency 4
 
3.8%
inc 4
 
3.8%
service 3
 
2.8%
air 2
 
1.9%
busan 2
 
1.9%
Other values (45) 48
45.3%
2024-04-16T15:44:00.014175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
75
 
11.9%
T 39
 
6.2%
R 31
 
4.9%
O 31
 
4.9%
E 30
 
4.8%
L 29
 
4.6%
A 27
 
4.3%
. 23
 
3.7%
C 22
 
3.5%
a 19
 
3.0%
Other values (42) 302
48.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 351
55.9%
Lowercase Letter 164
26.1%
Space Separator 75
 
11.9%
Other Punctuation 36
 
5.7%
Open Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T 39
11.1%
R 31
 
8.8%
O 31
 
8.8%
E 30
 
8.5%
L 29
 
8.3%
A 27
 
7.7%
C 22
 
6.3%
S 19
 
5.4%
U 19
 
5.4%
I 18
 
5.1%
Other values (14) 86
24.5%
Lowercase Letter
ValueCountFrequency (%)
a 19
11.6%
e 17
10.4%
n 17
10.4%
r 16
9.8%
o 16
9.8%
t 11
 
6.7%
c 10
 
6.1%
d 10
 
6.1%
u 9
 
5.5%
l 7
 
4.3%
Other values (12) 32
19.5%
Other Punctuation
ValueCountFrequency (%)
. 23
63.9%
, 11
30.6%
& 2
 
5.6%
Space Separator
ValueCountFrequency (%)
75
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 515
82.0%
Common 113
 
18.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
T 39
 
7.6%
R 31
 
6.0%
O 31
 
6.0%
E 30
 
5.8%
L 29
 
5.6%
A 27
 
5.2%
C 22
 
4.3%
a 19
 
3.7%
S 19
 
3.7%
U 19
 
3.7%
Other values (36) 249
48.3%
Common
ValueCountFrequency (%)
75
66.4%
. 23
 
20.4%
, 11
 
9.7%
& 2
 
1.8%
( 1
 
0.9%
) 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 628
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
75
 
11.9%
T 39
 
6.2%
R 31
 
4.9%
O 31
 
4.9%
E 30
 
4.8%
L 29
 
4.6%
A 27
 
4.3%
. 23
 
3.7%
C 22
 
3.5%
a 19
 
3.0%
Other values (42) 302
48.1%

영문상호주소
Categorical

IMBALANCE 

Distinct13
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
<NA>
1230 
Domestic travel business
 
8
DOMESTIC TRAVEL BUSINESS
 
4
DOMESTIC TRAVEL AGENCY
 
3
Domestic Travel Agency
 
3
Other values (8)
 
13

Length

Max length30
Median length4
Mean length4.4773989
Min length4

Unique

Unique5 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1230
97.5%
Domestic travel business 8
 
0.6%
DOMESTIC TRAVEL BUSINESS 4
 
0.3%
DOMESTIC TRAVEL AGENCY 3
 
0.2%
Domestic Travel Agency 3
 
0.2%
Domestic Traval Agency 3
 
0.2%
Inland Travel Business 3
 
0.2%
WITHIN A COUNTRY TRAVEL AGENCY 2
 
0.2%
Domestic Travel Industry 1
 
0.1%
Domestic Travel Business 1
 
0.1%
Other values (3) 3
 
0.2%

Length

2024-04-16T15:44:00.126435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1230
92.8%
travel 28
 
2.1%
domestic 24
 
1.8%
business 17
 
1.3%
agency 12
 
0.9%
traval 3
 
0.2%
inland 3
 
0.2%
within 2
 
0.2%
a 2
 
0.2%
country 2
 
0.2%
Other values (3) 3
 
0.2%

선박총톤수
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
<NA>
904 
0
357 

Length

Max length4
Median length4
Mean length3.1506741
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 904
71.7%
0 357
 
28.3%

Length

2024-04-16T15:44:00.217489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:44:00.294579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 904
71.7%
0 357
 
28.3%

선박척수
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
<NA>
904 
0
357 

Length

Max length4
Median length4
Mean length3.1506741
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 904
71.7%
0 357
 
28.3%

Length

2024-04-16T15:44:00.375364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:44:00.464423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 904
71.7%
0 357
 
28.3%

선박제원
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1261
Missing (%)100.0%
Memory size11.2 KiB

무대면적
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
<NA>
904 
0
357 

Length

Max length4
Median length4
Mean length3.1506741
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 904
71.7%
0 357
 
28.3%

Length

2024-04-16T15:44:00.552762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:44:00.630474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 904
71.7%
0 357
 
28.3%

좌석수
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
<NA>
904 
0
357 

Length

Max length4
Median length4
Mean length3.1506741
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 904
71.7%
0 357
 
28.3%

Length

2024-04-16T15:44:00.723716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:44:00.799535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 904
71.7%
0 357
 
28.3%

기념품종류
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1261
Missing (%)100.0%
Memory size11.2 KiB
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
<NA>
904 
0
357 

Length

Max length4
Median length4
Mean length3.1506741
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 904
71.7%
0 357
 
28.3%

Length

2024-04-16T15:44:00.878627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:44:00.955809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 904
71.7%
0 357
 
28.3%

시설면적
Real number (ℝ)

MISSING  ZEROS 

Distinct225
Distinct (%)39.5%
Missing692
Missing (%)54.9%
Infinite0
Infinite (%)0.0%
Mean164.41035
Minimum0
Maximum43511
Zeros285
Zeros (%)22.6%
Negative0
Negative (%)0.0%
Memory size11.2 KiB
2024-04-16T15:44:01.043824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q352.14
95-th percentile152.288
Maximum43511
Range43511
Interquartile range (IQR)52.14

Descriptive statistics

Standard deviation1996.6649
Coefficient of variation (CV)12.144399
Kurtosis405.15567
Mean164.41035
Median Absolute Deviation (MAD)0
Skewness19.490854
Sum93549.49
Variance3986670.6
MonotonicityNot monotonic
2024-04-16T15:44:01.142516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 285
22.6%
33.0 12
 
1.0%
30.0 7
 
0.6%
50.0 6
 
0.5%
66.0 6
 
0.5%
20.0 5
 
0.4%
25.0 3
 
0.2%
49.5 3
 
0.2%
12.0 3
 
0.2%
15.0 3
 
0.2%
Other values (215) 236
 
18.7%
(Missing) 692
54.9%
ValueCountFrequency (%)
0.0 285
22.6%
2.58 1
 
0.1%
4.05 1
 
0.1%
6.0 1
 
0.1%
6.6 1
 
0.1%
6.71 1
 
0.1%
8.0 1
 
0.1%
8.4 1
 
0.1%
10.0 1
 
0.1%
12.0 3
 
0.2%
ValueCountFrequency (%)
43511.0 1
0.1%
18592.0 1
0.1%
3920.67 1
0.1%
3480.76 1
0.1%
2988.0 1
0.1%
1022.9 1
0.1%
1013.0 1
0.1%
716.97 1
0.1%
268.5 1
0.1%
258.15 1
0.1%

놀이기구수내역
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1261
Missing (%)100.0%
Memory size11.2 KiB

놀이시설수
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
<NA>
904 
0
357 

Length

Max length4
Median length4
Mean length3.1506741
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 904
71.7%
0 357
 
28.3%

Length

2024-04-16T15:44:01.239903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:44:01.320620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 904
71.7%
0 357
 
28.3%

방송시설유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1261
Missing (%)100.0%
Memory size11.2 KiB

발전시설유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1261
Missing (%)100.0%
Memory size11.2 KiB

의무실유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1261
Missing (%)100.0%
Memory size11.2 KiB

안내소유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1261
Missing (%)100.0%
Memory size11.2 KiB

기획여행보험시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
<NA>
1260 
20200205
 
1

Length

Max length8
Median length4
Mean length4.0031721
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> 1260
99.9%
20200205 1
 
0.1%

Length

2024-04-16T15:44:01.437086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:44:01.530671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1260
99.9%
20200205 1
 
0.1%

기획여행보험종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
<NA>
1260 
20210204
 
1

Length

Max length8
Median length4
Mean length4.0031721
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> 1260
99.9%
20210204 1
 
0.1%

Length

2024-04-16T15:44:01.618793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:44:01.702365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1260
99.9%
20210204 1
 
0.1%

자본금
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct148
Distinct (%)16.3%
Missing353
Missing (%)28.0%
Infinite0
Infinite (%)0.0%
Mean78788213
Minimum0
Maximum6.5122084 × 109
Zeros82
Zeros (%)6.5%
Negative0
Negative (%)0.0%
Memory size11.2 KiB
2024-04-16T15:44:01.785776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q130000000
median50000000
Q31 × 108
95-th percentile1.5 × 108
Maximum6.5122084 × 109
Range6.5122084 × 109
Interquartile range (IQR)70000000

Descriptive statistics

Standard deviation2.5512378 × 108
Coefficient of variation (CV)3.2380958
Kurtosis482.1043
Mean78788213
Median Absolute Deviation (MAD)33623277
Skewness20.533857
Sum7.1539697 × 1010
Variance6.5088144 × 1016
MonotonicityNot monotonic
2024-04-16T15:44:01.890100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50000000 192
15.2%
30000000 107
 
8.5%
150000000 103
 
8.2%
0 82
 
6.5%
100000000 72
 
5.7%
15000000 66
 
5.2%
90000000 53
 
4.2%
45000000 21
 
1.7%
20000000 18
 
1.4%
60000000 16
 
1.3%
Other values (138) 178
14.1%
(Missing) 353
28.0%
ValueCountFrequency (%)
0 82
6.5%
5000 1
 
0.1%
5300 1
 
0.1%
30000 1
 
0.1%
1500000 1
 
0.1%
1750000 1
 
0.1%
3000000 4
 
0.3%
5000000 1
 
0.1%
10000000 2
 
0.2%
15000000 66
5.2%
ValueCountFrequency (%)
6512208375 1
 
0.1%
3500000000 1
 
0.1%
1000000000 1
 
0.1%
950000000 1
 
0.1%
714165250 1
 
0.1%
505000000 1
 
0.1%
500000000 5
0.4%
490000000 1
 
0.1%
375256000 1
 
0.1%
300000000 3
0.2%

보험시작일자
Real number (ℝ)

MISSING 

Distinct704
Distinct (%)83.4%
Missing417
Missing (%)33.1%
Infinite0
Infinite (%)0.0%
Mean20190558
Minimum20021021
Maximum20230703
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.2 KiB
2024-04-16T15:44:01.997949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20021021
5-th percentile20110920
Q120180289
median20200808
Q320210912
95-th percentile20230101
Maximum20230703
Range209682
Interquartile range (IQR)30623

Descriptive statistics

Standard deviation34780.018
Coefficient of variation (CV)0.0017225882
Kurtosis2.9622982
Mean20190558
Median Absolute Deviation (MAD)19510.5
Skewness-1.6234768
Sum1.7040831 × 1010
Variance1.2096496 × 109
MonotonicityNot monotonic
2024-04-16T15:44:02.101647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20210401 5
 
0.4%
20220401 5
 
0.4%
20210201 4
 
0.3%
20190705 4
 
0.3%
20210323 4
 
0.3%
20210224 3
 
0.2%
20200723 3
 
0.2%
20210901 3
 
0.2%
20220517 3
 
0.2%
20191125 3
 
0.2%
Other values (694) 807
64.0%
(Missing) 417
33.1%
ValueCountFrequency (%)
20021021 1
0.1%
20030812 1
0.1%
20030925 1
0.1%
20040420 1
0.1%
20051201 1
0.1%
20070111 1
0.1%
20070601 1
0.1%
20070802 1
0.1%
20071116 1
0.1%
20080303 1
0.1%
ValueCountFrequency (%)
20230703 1
0.1%
20230701 1
0.1%
20230629 1
0.1%
20230626 1
0.1%
20230621 1
0.1%
20230620 1
0.1%
20230615 1
0.1%
20230610 1
0.1%
20230609 1
0.1%
20230604 1
0.1%

보험종료일자
Real number (ℝ)

MISSING 

Distinct698
Distinct (%)82.6%
Missing416
Missing (%)33.0%
Infinite0
Infinite (%)0.0%
Mean20200752
Minimum20031021
Maximum20271110
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.2 KiB
2024-04-16T15:44:02.201719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20031021
5-th percentile20122926
Q120190316
median20210815
Q320220914
95-th percentile20240104
Maximum20271110
Range240089
Interquartile range (IQR)30598

Descriptive statistics

Standard deviation34731.337
Coefficient of variation (CV)0.0017193091
Kurtosis2.9254353
Mean20200752
Median Absolute Deviation (MAD)19510
Skewness-1.6007521
Sum1.7069635 × 1010
Variance1.2062657 × 109
MonotonicityNot monotonic
2024-04-16T15:44:02.311487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20220705 5
 
0.4%
20220331 5
 
0.4%
20230517 5
 
0.4%
20220223 4
 
0.3%
20230331 4
 
0.3%
20211231 4
 
0.3%
20200704 4
 
0.3%
20220322 4
 
0.3%
20211130 4
 
0.3%
20210717 3
 
0.2%
Other values (688) 803
63.7%
(Missing) 416
33.0%
ValueCountFrequency (%)
20031021 1
0.1%
20040812 1
0.1%
20040925 1
0.1%
20050420 1
0.1%
20061201 1
0.1%
20080111 1
0.1%
20080601 1
0.1%
20080802 1
0.1%
20081115 1
0.1%
20090704 1
0.1%
ValueCountFrequency (%)
20271110 1
0.1%
20240703 1
0.1%
20240630 1
0.1%
20240628 1
0.1%
20240625 1
0.1%
20240620 2
0.2%
20240615 1
0.1%
20240610 1
0.1%
20240608 1
0.1%
20240604 1
0.1%

부대시설내역
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1261
Missing (%)100.0%
Memory size11.2 KiB

시설규모
Real number (ℝ)

MISSING  ZEROS 

Distinct131
Distinct (%)23.0%
Missing692
Missing (%)54.9%
Infinite0
Infinite (%)0.0%
Mean164.42355
Minimum0
Maximum43511
Zeros285
Zeros (%)22.6%
Negative0
Negative (%)0.0%
Memory size11.2 KiB
2024-04-16T15:44:02.720466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q352
95-th percentile152
Maximum43511
Range43511
Interquartile range (IQR)52

Descriptive statistics

Standard deviation1996.666
Coefficient of variation (CV)12.143431
Kurtosis405.15423
Mean164.42355
Median Absolute Deviation (MAD)0
Skewness19.490805
Sum93557
Variance3986675.1
MonotonicityNot monotonic
2024-04-16T15:44:02.825074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 285
22.6%
33 16
 
1.3%
50 13
 
1.0%
30 9
 
0.7%
20 9
 
0.7%
66 8
 
0.6%
40 7
 
0.6%
15 6
 
0.5%
26 5
 
0.4%
32 5
 
0.4%
Other values (121) 206
 
16.3%
(Missing) 692
54.9%
ValueCountFrequency (%)
0 285
22.6%
3 1
 
0.1%
4 1
 
0.1%
6 1
 
0.1%
7 2
 
0.2%
8 2
 
0.2%
10 1
 
0.1%
12 3
 
0.2%
13 3
 
0.2%
15 6
 
0.5%
ValueCountFrequency (%)
43511 1
0.1%
18592 1
0.1%
3921 1
0.1%
3481 1
0.1%
2988 1
0.1%
1023 1
0.1%
1013 1
0.1%
717 1
0.1%
269 1
0.1%
258 1
0.1%

Unnamed: 63
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1261
Missing (%)100.0%
Memory size11.2 KiB

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)문화체육업종명문화사업자구분명지역구분명총층수주변환경명제작취급품목내용보험기관명건물용도명지상층수지하층수객실수건축연면적영문상호명영문상호주소선박총톤수선박척수선박제원무대면적좌석수기념품종류회의실별동시수용인원시설면적놀이기구수내역놀이시설수방송시설유무발전시설유무의무실유무안내소유무기획여행보험시작일자기획여행보험종료일자자본금보험시작일자보험종료일자부대시설내역시설규모Unnamed: 63
01국내여행업03_12_01_P3250000CDFI22600120070000132007-11-09<NA>2휴업2휴업<NA>2021-01-012021-12-31<NA>051-469-7731<NA>600-815부산광역시 중구 중앙동4가 53-30부산광역시 중구 중앙대로81번길 2 (중앙동4가)<NA>(주)팔성국제관광2021-09-26 17:50:02U2021-09-28 02:40:00<NA>385556.341486180343.213568국내여행업관광사업<NA>0<NA><NA>서울보증보험<NA>0000<NA><NA>00<NA>00<NA>00.0<NA>0<NA><NA><NA><NA><NA><NA>1500000002018110920191108<NA>0<NA>
12국내여행업03_12_01_P3250000CDFI22600120190000022019-01-10<NA>3폐업3폐업2020-01-06<NA><NA><NA>051241 0909<NA><NA>부산광역시 중구 남포동4가 44-3번지부산광역시 중구 자갈치해안로 60 (남포동4가)48984부산남항유람선 자갈치크루즈2020-01-06 15:03:26U2020-01-08 02:40:00<NA>385191.013393179401.283402국내여행업<NA><NA><NA><NA><NA>서울보증보험주식회사<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>162433582019011420200113<NA><NA><NA>
23국내여행업03_12_01_P3250000CDFI22600120190000032016-07-25<NA>3폐업3폐업2021-12-21<NA><NA><NA>051-852-2088<NA><NA>부산광역시 중구 대창동1가 51부산광역시 중구 해관로 89, 중앙빌딩 707호 (대창동1가)48924(주)태진투어2021-12-21 17:45:38U2021-12-23 02:40:00<NA>385507.64053180548.792612국내여행업<NA><NA>0<NA><NA>서울보증보험주식회사<NA>0000<NA><NA>00<NA>00<NA>00.0<NA>0<NA><NA><NA><NA><NA><NA>200000002021072520220724<NA>0<NA>
34국내여행업03_12_01_P3250000CDFI22600120190000062019-08-29<NA>3폐업3폐업2019-09-24<NA><NA><NA>051-464-6464<NA><NA>부산광역시 중구 중앙동4가 15-3번지부산광역시 중구 충장대로 24, 부산항연안여객터미널 1층 (중앙동4가)48940(주)마린크루즈2019-09-24 16:58:41U2019-09-26 02:40:00<NA>386032.236799180263.270671국내여행업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>15000000<NA><NA><NA><NA><NA>
45국내여행업03_12_01_P3250000CDFI22600120160000012016-01-12<NA>3폐업3폐업2021-12-20<NA><NA><NA>051-463-0926<NA><NA>부산광역시 중구 대창동1가 51부산광역시 중구 해관로 89, 610호 (대창동1가, 중앙빌딩)48924(주)모바일트래블2021-12-21 10:39:23U2021-12-23 02:40:00<NA>385507.64053180548.792612국내여행업<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>900000002021012020220119<NA><NA><NA>
56국내여행업03_12_01_P3250000CDFI22600120160000032016-02-18<NA>3폐업3폐업2021-11-09<NA><NA><NA>051-244-6318<NA><NA>부산광역시 중구 신창동1가 17-2부산광역시 중구 광복로49번길 19, 2층 (신창동1가)48947스타투어여행사2021-11-10 10:17:05U2021-11-12 02:40:00<NA>385057.531776179860.881541국내여행업<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>1090000002021022220220221<NA><NA><NA>
67국내여행업03_12_01_P3250000CDFI22600119970000061997-04-21<NA>3폐업3폐업2006-07-04<NA><NA><NA>254-4061<NA>600-045부산광역시 중구 남포동5가 39-6번지부산광역시 중구 중구로 2 (남포동5가)<NA>(주)초이스관광여행사2006-07-04 16:29:46I2018-08-31 23:59:59<NA>384877.272224179536.794609국내여행업관광사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
78국내여행업03_12_01_P3250000CDFI22600119940000011994-09-29<NA>3폐업3폐업2020-03-17<NA><NA><NA>246-1003<NA>600-046부산광역시 중구 남포동6가 113-1번지부산광역시 중구 구덕로 87-1 (남포동6가)<NA>(주)미래투어2020-03-17 17:33:18U2020-03-19 02:40:00<NA>384708.848958179404.943227국내여행업관광사업<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>2018100820191017<NA><NA><NA>
89국내여행업03_12_01_P3250000CDFI22600119970000071997-08-01<NA>3폐업3폐업2006-05-17<NA><NA><NA>442-5020<NA>600-815부산광역시 중구 중앙동4가 37-16번지 동아제일빌딩 903호부산광역시 중구 중앙대로81번길 9, 903호 (중앙동4가,동아제일빌딩)<NA>(주)세진여행사2006-05-17 16:51:32I2018-08-31 23:59:59<NA>385473.57641180297.978229국내여행업관광사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
910국내여행업03_12_01_P3250000CDFI22600119980000011998-02-02<NA>3폐업3폐업2009-01-29<NA><NA><NA>462-6661<NA>600-814부산광역시 중구 중앙동4가 89-1번지부산광역시 중구 중앙대로 94 (중앙동4가)<NA>(주)아주좋은여행사2009-01-29 18:09:02I2018-08-31 23:59:59<NA>385624.46871180447.914514국내여행업관광사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)문화체육업종명문화사업자구분명지역구분명총층수주변환경명제작취급품목내용보험기관명건물용도명지상층수지하층수객실수건축연면적영문상호명영문상호주소선박총톤수선박척수선박제원무대면적좌석수기념품종류회의실별동시수용인원시설면적놀이기구수내역놀이시설수방송시설유무발전시설유무의무실유무안내소유무기획여행보험시작일자기획여행보험종료일자자본금보험시작일자보험종료일자부대시설내역시설규모Unnamed: 63
12511252국내여행업03_12_01_P3400000CDFI22600120160000022015-11-18<NA>3폐업3폐업2016-12-06<NA><NA><NA>051.746.4232<NA><NA>부산광역시 기장군 기장읍 청강리 114-1번지 405호부산광역시 기장군 기장읍 기장대로 482-5 (비룡 벨로스텔라)46080(주)동부산여행사2016-12-06 14:01:06I2018-08-31 23:59:59<NA>402013.571482195503.645679국내여행업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2016072820170727<NA><NA><NA>
12521253국내여행업03_12_01_P3400000CDFI22600120190000022019-01-15<NA>3폐업3폐업2020-04-21<NA><NA><NA><NA><NA><NA>부산광역시 기장군 정관읍 달산리 1024-11번지 205호부산광역시 기장군 정관읍 달산1길 37-1, 205호46024원여행사2020-04-21 19:56:54U2020-04-23 02:40:00<NA>398367.581911204186.113952국내여행업<NA><NA><NA><NA><NA>서울보증보험주식회사<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2019112520201124<NA><NA><NA>
12531254국내여행업03_12_01_P3400000CDFI22600120110000012011-10-20<NA>1영업/정상13영업중<NA><NA><NA><NA>051-728-0903<NA><NA>부산광역시 기장군 정관읍 매학리 717-8부산광역시 기장군 정관읍 정관7로 34 (서진프라자)46015주식회사 유민여행사2022-08-30 11:19:04U2022-09-01 02:40:00<NA>398043.112671204665.784677국내여행업<NA><NA>0<NA><NA>서울보증보험주식회사근린생활시설0000<NA><NA>00<NA>00<NA>012.0<NA>0<NA><NA><NA><NA><NA><NA>300000002022060120230531<NA>12<NA>
12541255국내여행업03_12_01_P3400000CDFI22600120200000012020-05-11<NA>1영업/정상13영업중<NA><NA><NA><NA>051-243-4972<NA><NA>부산광역시 기장군 정관읍 매학리 717-3부산광역시 기장군 정관읍 정관로 583, 503호46015여행이필요할때 생각나는남자(여필남)2023-01-03 10:53:17U2023-01-05 02:40:00<NA>397967.170797204592.491613국내여행업<NA><NA>0<NA><NA>서울보증보험주식회사<NA>0000<NA><NA>00<NA>00<NA>00.0<NA>0<NA><NA><NA><NA><NA><NA>150000002022073120230730<NA>0<NA>
12551256국내여행업03_12_01_P3400000CDFI22600120230000012022-05-18<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>부산광역시 기장군 기장읍 청강리 114-1 비룡 벨로스텔라부산광역시 기장군 기장읍 기장대로 482-5, 303호 (비룡 벨로스텔라)46080대박2023-03-28 09:27:40I2023-03-29 00:41:29<NA>402013.571482195503.645679국내여행업<NA><NA>6<NA><NA>서울보증보험근린생활시설5100<NA><NA>00<NA>00<NA>0716.97<NA>0<NA><NA><NA><NA><NA><NA>150437652022051820230517<NA>717<NA>
12561257국내여행업03_12_01_P3400000CDFI22600120230000022011-08-17<NA>1영업/정상13영업중<NA><NA><NA><NA>051-704-9936<NA><NA>부산광역시 기장군 장안읍 반룡리 897-1 경동오토필드부산광역시 기장군 장안읍 반룡산단3로 95, 경동오토필드 504호46034주식회사 투어파크2023-03-29 15:19:06U2023-04-01 02:40:00<NA>405161.575903206488.089796국내여행업<NA><NA>0<NA><NA>서울보증보험주식회사<NA>0000<NA><NA>00<NA>00<NA>00.0<NA>0<NA><NA><NA><NA><NA><NA>1000000002023021320240212<NA>0<NA>
12571258국내여행업03_12_01_P3400000CDFI22600120210000012021-06-03<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>부산광역시 기장군 정관읍 매학리 717-6부산광역시 기장군 정관읍 정관중앙로 45, 2층 205호46015비와이컴퍼니2021-07-02 15:27:00U2021-07-04 02:40:00<NA>398024.244822204621.655739국내여행업<NA><NA><NA><NA><NA>서울보증보험주식회사<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>150000002021060320220602<NA><NA><NA>
12581259국내여행업03_12_01_P3400000CDFI22600120200000032018-05-17<NA>1영업/정상13영업중<NA><NA><NA><NA>051-611-7979<NA><NA>부산광역시 기장군 기장읍 청강리 111-8부산광역시 기장군 기장읍 기장대로 495, 2301호46072주식회사 여행나무2022-08-30 11:36:34U2022-09-01 02:40:00<NA>401991.886649195612.173827국내여행업<NA><NA>0<NA><NA>서울보증보험주식회사<NA>0000<NA><NA>00<NA>00<NA>062.95<NA>0<NA><NA><NA><NA><NA><NA>150000002022051820230517<NA>63<NA>
12591260국내여행업03_12_01_P3400000CDFI22600120200000042020-10-26<NA>1영업/정상13영업중<NA><NA><NA><NA>051-721-4331<NA><NA>부산광역시 기장군 기장읍 동부리 394-6 부산공인중개사부산광역시 기장군 기장읍 반송로 160146056다된다투어2021-11-16 15:12:38U2021-11-18 02:40:00<NA>401448.811951196699.415019국내여행업<NA><NA>0<NA><NA><NA><NA>0000<NA><NA>00<NA>00<NA>00.0<NA>0<NA><NA><NA><NA><NA><NA>500000002021102820221027<NA>0<NA>
12601261국내여행업03_12_01_P3400000CDFI22600120220000021995-02-18<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>부산광역시 기장군 기장읍 동부리 331-9 아토건설부산광역시 기장군 기장읍 반송로 1576, 아토건설 3층46060(주)세명항공여행사2022-06-21 10:02:01I2022-06-22 00:22:40<NA>401235.137491196516.098555국내여행업관광사업<NA>0<NA><NA>한국관광협회중앙회<NA>0000<NA><NA>00<NA>00<NA>00.0<NA>0<NA><NA><NA><NA><NA><NA>1500000002021070520220705<NA>0<NA>