Overview

Dataset statistics

Number of variables65
Number of observations251
Missing cells7502
Missing cells (%)46.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory138.6 KiB
Average record size in memory565.5 B

Variable types

Numeric18
Categorical17
Text8
Unsupported21
DateTime1

Dataset

Description2021-02-01
Author지방행정인허가공개데이터
URLhttps://bigdata.busan.go.kr/data/bigDataDetailView.do?menuCode=M00000000007&hdfs_file_sn=20230901050101123064

Alerts

개방서비스명 has constant value ""Constant
개방서비스id has constant value ""Constant
문화체육업종명 has constant value ""Constant
인허가취소일자 is highly imbalanced (95.3%)Imbalance
영업상태구분코드 is highly imbalanced (50.5%)Imbalance
영업상태명 is highly imbalanced (50.5%)Imbalance
상세영업상태코드 is highly imbalanced (50.5%)Imbalance
상세영업상태명 is highly imbalanced (50.5%)Imbalance
휴업종료일자 is highly imbalanced (91.6%)Imbalance
보험시작일자 is highly imbalanced (95.3%)Imbalance
보험종료일자 is highly imbalanced (95.3%)Imbalance
폐업일자 has 195 (77.7%) missing valuesMissing
휴업시작일자 has 245 (97.6%) missing valuesMissing
재개업일자 has 251 (100.0%) missing valuesMissing
소재지전화 has 82 (32.7%) missing valuesMissing
소재지면적 has 251 (100.0%) missing valuesMissing
소재지우편번호 has 158 (62.9%) missing valuesMissing
도로명우편번호 has 41 (16.3%) missing valuesMissing
업태구분명 has 251 (100.0%) missing valuesMissing
좌표정보(x) has 4 (1.6%) missing valuesMissing
좌표정보(y) has 4 (1.6%) missing valuesMissing
총층수 has 94 (37.5%) missing valuesMissing
제작취급품목내용 has 251 (100.0%) missing valuesMissing
보험기관명 has 226 (90.0%) missing valuesMissing
지상층수 has 96 (38.2%) missing valuesMissing
지하층수 has 129 (51.4%) missing valuesMissing
객실수 has 55 (21.9%) missing valuesMissing
건축연면적 has 168 (66.9%) missing valuesMissing
영문상호명 has 218 (86.9%) missing valuesMissing
영문상호주소 has 220 (87.6%) missing valuesMissing
선박총톤수 has 251 (100.0%) missing valuesMissing
선박척수 has 251 (100.0%) missing valuesMissing
선박제원 has 251 (100.0%) missing valuesMissing
무대면적 has 251 (100.0%) missing valuesMissing
좌석수 has 251 (100.0%) missing valuesMissing
기념품종류 has 251 (100.0%) missing valuesMissing
회의실별동시수용인원 has 251 (100.0%) missing valuesMissing
시설면적 has 66 (26.3%) missing valuesMissing
놀이기구수내역 has 251 (100.0%) missing valuesMissing
놀이시설수 has 251 (100.0%) missing valuesMissing
방송시설유무 has 251 (100.0%) missing valuesMissing
발전시설유무 has 251 (100.0%) missing valuesMissing
의무실유무 has 251 (100.0%) missing valuesMissing
안내소유무 has 251 (100.0%) missing valuesMissing
기획여행보험시작일자 has 251 (100.0%) missing valuesMissing
기획여행보험종료일자 has 251 (100.0%) missing valuesMissing
자본금 has 162 (64.5%) missing valuesMissing
부대시설내역 has 251 (100.0%) missing valuesMissing
시설규모 has 66 (26.3%) missing valuesMissing
Unnamed: 64 has 251 (100.0%) missing valuesMissing
번호 has unique valuesUnique
최종수정시점 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
선박총톤수 is an unsupported type, check if it needs cleaning or further analysisUnsupported
선박척수 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
무대면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
좌석수 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
회의실별동시수용인원 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
놀이시설수 is an unsupported type, check if it needs cleaning or further analysisUnsupported
방송시설유무 is an unsupported type, check if it needs cleaning or further analysisUnsupported
발전시설유무 is an unsupported type, check if it needs cleaning or further analysisUnsupported
의무실유무 is an unsupported type, check if it needs cleaning or further analysisUnsupported
안내소유무 is an unsupported type, check if it needs cleaning or further analysisUnsupported
기획여행보험시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
기획여행보험종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
부대시설내역 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 64 is an unsupported type, check if it needs cleaning or further analysisUnsupported
지하층수 has 7 (2.8%) zerosZeros

Reproduction

Analysis started2024-04-21 20:22:54.646774
Analysis finished2024-04-21 20:22:55.997809
Duration1.35 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct251
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126
Minimum1
Maximum251
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-22T05:22:56.130560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile13.5
Q163.5
median126
Q3188.5
95-th percentile238.5
Maximum251
Range250
Interquartile range (IQR)125

Descriptive statistics

Standard deviation72.601653
Coefficient of variation (CV)0.57620359
Kurtosis-1.2
Mean126
Median Absolute Deviation (MAD)63
Skewness0
Sum31626
Variance5271
MonotonicityStrictly increasing
2024-04-22T05:22:56.389833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
174 1
 
0.4%
161 1
 
0.4%
162 1
 
0.4%
163 1
 
0.4%
164 1
 
0.4%
165 1
 
0.4%
166 1
 
0.4%
167 1
 
0.4%
168 1
 
0.4%
Other values (241) 241
96.0%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
251 1
0.4%
250 1
0.4%
249 1
0.4%
248 1
0.4%
247 1
0.4%
246 1
0.4%
245 1
0.4%
244 1
0.4%
243 1
0.4%
242 1
0.4%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
관광숙박업
251 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
관광숙박업 251
100.0%

Length

2024-04-22T05:22:56.617201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T05:22:56.775318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
관광숙박업 251
100.0%

개방서비스id
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
03_11_01_P
251 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row03_11_01_P
2nd row03_11_01_P
3rd row03_11_01_P
4th row03_11_01_P
5th row03_11_01_P

Common Values

ValueCountFrequency (%)
03_11_01_P 251
100.0%

Length

2024-04-22T05:22:56.939507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T05:22:57.101370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
03_11_01_p 251
100.0%

개방자치단체코드
Real number (ℝ)

Distinct15
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3333386.5
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-22T05:22:57.251054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3250000
Q13300000
median3330000
Q33380000
95-th percentile3385000
Maximum3400000
Range150000
Interquartile range (IQR)80000

Descriptive statistics

Standard deviation44164.307
Coefficient of variation (CV)0.013249081
Kurtosis-0.93367891
Mean3333386.5
Median Absolute Deviation (MAD)40000
Skewness-0.36541469
Sum8.3668 × 108
Variance1.9504861 × 109
MonotonicityNot monotonic
2024-04-22T05:22:57.459184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
3330000 79
31.5%
3380000 70
27.9%
3290000 19
 
7.6%
3250000 18
 
7.2%
3270000 15
 
6.0%
3400000 10
 
4.0%
3370000 8
 
3.2%
3300000 7
 
2.8%
3340000 6
 
2.4%
3260000 6
 
2.4%
Other values (5) 13
 
5.2%
ValueCountFrequency (%)
3250000 18
 
7.2%
3260000 6
 
2.4%
3270000 15
 
6.0%
3280000 2
 
0.8%
3290000 19
 
7.6%
3300000 7
 
2.8%
3310000 3
 
1.2%
3320000 4
 
1.6%
3330000 79
31.5%
3340000 6
 
2.4%
ValueCountFrequency (%)
3400000 10
 
4.0%
3390000 3
 
1.2%
3380000 70
27.9%
3370000 8
 
3.2%
3350000 1
 
0.4%
3340000 6
 
2.4%
3330000 79
31.5%
3320000 4
 
1.6%
3310000 3
 
1.2%
3300000 7
 
2.8%
Distinct124
Distinct (%)49.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-04-22T05:22:58.164070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters5020
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

Unique57 ?
Unique (%)22.7%

Sample

1st rowCDFI2260032015000004
2nd rowCDFI2260031987000001
3rd rowCDFI2260032014000004
4th rowCDFI2260032014000002
5th rowCDFI2260032017000007
ValueCountFrequency (%)
cdfi2260032017000001 9
 
3.6%
cdfi2260032020000001 8
 
3.2%
cdfi2260032016000001 7
 
2.8%
cdfi2260032018000001 6
 
2.4%
cdfi2260032015000001 5
 
2.0%
cdfi2260032016000002 5
 
2.0%
cdfi2260032014000001 5
 
2.0%
cdfi2260031987000001 5
 
2.0%
cdfi2260032019000001 5
 
2.0%
cdfi2260032017000002 5
 
2.0%
Other values (114) 191
76.1%
2024-04-22T05:22:59.078133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2017
40.2%
2 793
 
15.8%
1 326
 
6.5%
6 295
 
5.9%
3 281
 
5.6%
C 251
 
5.0%
D 251
 
5.0%
F 251
 
5.0%
I 251
 
5.0%
9 91
 
1.8%
Other values (4) 213
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4016
80.0%
Uppercase Letter 1004
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2017
50.2%
2 793
 
19.7%
1 326
 
8.1%
6 295
 
7.3%
3 281
 
7.0%
9 91
 
2.3%
7 70
 
1.7%
8 59
 
1.5%
5 44
 
1.1%
4 40
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
C 251
25.0%
D 251
25.0%
F 251
25.0%
I 251
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4016
80.0%
Latin 1004
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2017
50.2%
2 793
 
19.7%
1 326
 
8.1%
6 295
 
7.3%
3 281
 
7.0%
9 91
 
2.3%
7 70
 
1.7%
8 59
 
1.5%
5 44
 
1.1%
4 40
 
1.0%
Latin
ValueCountFrequency (%)
C 251
25.0%
D 251
25.0%
F 251
25.0%
I 251
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5020
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2017
40.2%
2 793
 
15.8%
1 326
 
6.5%
6 295
 
5.9%
3 281
 
5.6%
C 251
 
5.0%
D 251
 
5.0%
F 251
 
5.0%
I 251
 
5.0%
9 91
 
1.8%
Other values (4) 213
 
4.2%

인허가일자
Real number (ℝ)

Distinct240
Distinct (%)95.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20104336
Minimum19630422
Maximum20201105
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-22T05:22:59.342736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19630422
5-th percentile19850959
Q120066016
median20160407
Q320180160
95-th percentile20200727
Maximum20201105
Range570683
Interquartile range (IQR)114143

Descriptive statistics

Standard deviation119772
Coefficient of variation (CV)0.0059575207
Kurtosis1.9648298
Mean20104336
Median Absolute Deviation (MAD)20811
Skewness-1.6740489
Sum5.0461883 × 109
Variance1.4345331 × 1010
MonotonicityNot monotonic
2024-04-22T05:22:59.586356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20171016 2
 
0.8%
20201015 2
 
0.8%
20200727 2
 
0.8%
20171220 2
 
0.8%
20161230 2
 
0.8%
20161125 2
 
0.8%
20200928 2
 
0.8%
20160104 2
 
0.8%
20170616 2
 
0.8%
20090619 2
 
0.8%
Other values (230) 231
92.0%
ValueCountFrequency (%)
19630422 1
0.4%
19720101 1
0.4%
19740613 1
0.4%
19740907 1
0.4%
19750819 1
0.4%
19761204 1
0.4%
19770425 1
0.4%
19780425 1
0.4%
19780515 1
0.4%
19811121 1
0.4%
ValueCountFrequency (%)
20201105 1
0.4%
20201015 2
0.8%
20201006 1
0.4%
20200928 2
0.8%
20200922 1
0.4%
20200907 1
0.4%
20200827 1
0.4%
20200821 1
0.4%
20200812 1
0.4%
20200728 1
0.4%

인허가취소일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
249 
20180827
 
1
20190220
 
1

Length

Max length8
Median length4
Mean length4.0318725
Min length4

Unique

Unique2 ?
Unique (%)0.8%

Sample

1st row20180827
2nd row20190220
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 249
99.2%
20180827 1
 
0.4%
20190220 1
 
0.4%

Length

2024-04-22T05:22:59.837919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T05:23:00.028608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 249
99.2%
20180827 1
 
0.4%
20190220 1
 
0.4%

영업상태구분코드
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
1
186 
3
57 
2
 
6
4
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 186
74.1%
3 57
 
22.7%
2 6
 
2.4%
4 2
 
0.8%

Length

2024-04-22T05:23:00.204280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T05:23:00.375120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 186
74.1%
3 57
 
22.7%
2 6
 
2.4%
4 2
 
0.8%

영업상태명
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
영업/정상
186 
폐업
57 
휴업
 
6
취소/말소/만료/정지/중지
 
2

Length

Max length14
Median length5
Mean length4.3187251
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 186
74.1%
폐업 57
 
22.7%
휴업 6
 
2.4%
취소/말소/만료/정지/중지 2
 
0.8%

Length

2024-04-22T05:23:00.571590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T05:23:00.752005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 186
74.1%
폐업 57
 
22.7%
휴업 6
 
2.4%
취소/말소/만료/정지/중지 2
 
0.8%

상세영업상태코드
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
13
186 
3
57 
2
 
6
31
 
2

Length

Max length2
Median length2
Mean length1.749004
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row31
2nd row31
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
13 186
74.1%
3 57
 
22.7%
2 6
 
2.4%
31 2
 
0.8%

Length

2024-04-22T05:23:00.952160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T05:23:01.133894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13 186
74.1%
3 57
 
22.7%
2 6
 
2.4%
31 2
 
0.8%

상세영업상태명
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
영업중
186 
폐업
57 
휴업
 
6
등록취소
 
2

Length

Max length4
Median length3
Mean length2.7569721
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 186
74.1%
폐업 57
 
22.7%
휴업 6
 
2.4%
등록취소 2
 
0.8%

Length

2024-04-22T05:23:01.347289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T05:23:01.545143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 186
74.1%
폐업 57
 
22.7%
휴업 6
 
2.4%
등록취소 2
 
0.8%

폐업일자
Real number (ℝ)

MISSING 

Distinct56
Distinct (%)100.0%
Missing195
Missing (%)77.7%
Infinite0
Infinite (%)0.0%
Mean20147481
Minimum20050620
Maximum20200414
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-22T05:23:01.756084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20050620
5-th percentile20058133
Q120108544
median20170415
Q320183438
95-th percentile20191222
Maximum20200414
Range149794
Interquartile range (IQR)74894.25

Descriptive statistics

Standard deviation49031.65
Coefficient of variation (CV)0.0024336368
Kurtosis-0.66783004
Mean20147481
Median Absolute Deviation (MAD)20286.5
Skewness-0.92744525
Sum1.1282589 × 109
Variance2.4041027 × 109
MonotonicityNot monotonic
2024-04-22T05:23:02.021652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20050727 1
 
0.4%
20161231 1
 
0.4%
20100108 1
 
0.4%
20200414 1
 
0.4%
20191219 1
 
0.4%
20170102 1
 
0.4%
20170517 1
 
0.4%
20181123 1
 
0.4%
20060602 1
 
0.4%
20061020 1
 
0.4%
Other values (46) 46
 
18.3%
(Missing) 195
77.7%
ValueCountFrequency (%)
20050620 1
0.4%
20050711 1
0.4%
20050727 1
0.4%
20060602 1
0.4%
20060628 1
0.4%
20060927 1
0.4%
20060928 1
0.4%
20061020 1
0.4%
20070126 1
0.4%
20080324 1
0.4%
ValueCountFrequency (%)
20200414 1
0.4%
20200323 1
0.4%
20191231 1
0.4%
20191219 1
0.4%
20191029 1
0.4%
20191017 1
0.4%
20190917 1
0.4%
20190729 1
0.4%
20190702 1
0.4%
20190701 1
0.4%

휴업시작일자
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)100.0%
Missing245
Missing (%)97.6%
Infinite0
Infinite (%)0.0%
Mean20132396
Minimum20060406
Maximum20210101
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-22T05:23:02.237430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20060406
5-th percentile20060562
Q120061030
median20130966
Q320200908
95-th percentile20207803
Maximum20210101
Range149695
Interquartile range (IQR)139877.5

Descriptive statistics

Standard deviation78477.767
Coefficient of variation (CV)0.0038980837
Kurtosis-3.3109845
Mean20132396
Median Absolute Deviation (MAD)69940
Skewness0.0075856542
Sum1.2079438 × 108
Variance6.1587599 × 109
MonotonicityNot monotonic
2024-04-22T05:23:02.426240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
20061031 1
 
0.4%
20060406 1
 
0.4%
20061030 1
 
0.4%
20200901 1
 
0.4%
20200910 1
 
0.4%
20210101 1
 
0.4%
(Missing) 245
97.6%
ValueCountFrequency (%)
20060406 1
0.4%
20061030 1
0.4%
20061031 1
0.4%
20200901 1
0.4%
20200910 1
0.4%
20210101 1
0.4%
ValueCountFrequency (%)
20210101 1
0.4%
20200910 1
0.4%
20200901 1
0.4%
20061031 1
0.4%
20061030 1
0.4%
20060406 1
0.4%

휴업종료일자
Categorical

IMBALANCE 

Distinct6
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
245 
20071030
 
2
20061005
 
1
20210831
 
1
20210930
 
1

Length

Max length8
Median length4
Mean length4.0956175
Min length4

Unique

Unique4 ?
Unique (%)1.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 245
97.6%
20071030 2
 
0.8%
20061005 1
 
0.4%
20210831 1
 
0.4%
20210930 1
 
0.4%
20211231 1
 
0.4%

Length

2024-04-22T05:23:02.669435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T05:23:02.875397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 245
97.6%
20071030 2
 
0.8%
20061005 1
 
0.4%
20210831 1
 
0.4%
20210930 1
 
0.4%
20211231 1
 
0.4%

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing251
Missing (%)100.0%
Memory size2.3 KiB

소재지전화
Text

MISSING 

Distinct169
Distinct (%)100.0%
Missing82
Missing (%)32.7%
Memory size2.1 KiB
2024-04-22T05:23:03.654752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length12
Mean length11.597633
Min length8

Characters and Unicode

Total characters1960
Distinct characters14
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique169 ?
Unique (%)100.0%

Sample

1st row051-552-9511
2nd row051-913-0804
3rd row051 731 2120
4th row051 744 4514
5th row741-8200
ValueCountFrequency (%)
051 7
 
3.8%
051-337-8811 1
 
0.5%
051-753-3288 1
 
0.5%
051-751-2266 1
 
0.5%
0516230920 1
 
0.5%
051-759-1011 1
 
0.5%
051-755-0055 1
 
0.5%
051-753-1340 1
 
0.5%
051-757-9901 1
 
0.5%
0517564139 1
 
0.5%
Other values (167) 167
91.3%
2024-04-22T05:23:04.691136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 376
19.2%
1 302
15.4%
- 290
14.8%
5 254
13.0%
7 138
 
7.0%
2 123
 
6.3%
8 102
 
5.2%
3 101
 
5.2%
4 97
 
4.9%
6 92
 
4.7%
Other values (4) 85
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1652
84.3%
Dash Punctuation 290
 
14.8%
Space Separator 14
 
0.7%
Math Symbol 3
 
0.2%
Other Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 376
22.8%
1 302
18.3%
5 254
15.4%
7 138
 
8.4%
2 123
 
7.4%
8 102
 
6.2%
3 101
 
6.1%
4 97
 
5.9%
6 92
 
5.6%
9 67
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 290
100.0%
Space Separator
ValueCountFrequency (%)
14
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1960
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 376
19.2%
1 302
15.4%
- 290
14.8%
5 254
13.0%
7 138
 
7.0%
2 123
 
6.3%
8 102
 
5.2%
3 101
 
5.2%
4 97
 
4.9%
6 92
 
4.7%
Other values (4) 85
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1960
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 376
19.2%
1 302
15.4%
- 290
14.8%
5 254
13.0%
7 138
 
7.0%
2 123
 
6.3%
8 102
 
5.2%
3 101
 
5.2%
4 97
 
4.9%
6 92
 
4.7%
Other values (4) 85
 
4.3%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing251
Missing (%)100.0%
Memory size2.3 KiB

소재지우편번호
Real number (ℝ)

MISSING 

Distinct52
Distinct (%)55.9%
Missing158
Missing (%)62.9%
Infinite0
Infinite (%)0.0%
Mean610046.7
Minimum600022
Maximum617829
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-22T05:23:04.938330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum600022
5-th percentile600075
Q1606804
median612040
Q3613805
95-th percentile614847
Maximum617829
Range17807
Interquartile range (IQR)7001

Descriptive statistics

Standard deviation5087.8952
Coefficient of variation (CV)0.0083401732
Kurtosis-0.67524911
Mean610046.7
Median Absolute Deviation (MAD)1787
Skewness-0.87156135
Sum56734343
Variance25886677
MonotonicityNot monotonic
2024-04-22T05:23:05.195573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
612040 7
 
2.8%
614847 6
 
2.4%
613805 6
 
2.4%
612821 6
 
2.4%
612846 5
 
2.0%
612824 3
 
1.2%
612020 3
 
1.2%
600045 3
 
1.2%
613828 3
 
1.2%
600811 2
 
0.8%
Other values (42) 49
 
19.5%
(Missing) 158
62.9%
ValueCountFrequency (%)
600022 1
 
0.4%
600045 3
1.2%
600051 1
 
0.4%
600091 1
 
0.4%
600811 2
0.8%
601807 2
0.8%
601808 1
 
0.4%
601812 1
 
0.4%
601829 1
 
0.4%
601837 1
 
0.4%
ValueCountFrequency (%)
617829 1
 
0.4%
617809 1
 
0.4%
616816 1
 
0.4%
614847 6
2.4%
614846 1
 
0.4%
614845 1
 
0.4%
613830 1
 
0.4%
613828 3
1.2%
613827 1
 
0.4%
613815 1
 
0.4%
Distinct231
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-04-22T05:23:06.416837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length35
Mean length22.027888
Min length13

Characters and Unicode

Total characters5529
Distinct characters164
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

Unique218 ?
Unique (%)86.9%

Sample

1st row부산광역시 수영구 민락동 178-13번지
2nd row부산광역시 동래구 온천동 210-82번지
3rd row부산광역시 해운대구 송정동 312-6번지 프롬 게스트하우스 3,4동
4th row부산광역시 해운대구 우동 1510번지 센텀드림월드
5th row부산광역시 해운대구 우동 648-9번지
ValueCountFrequency (%)
부산광역시 251
23.7%
해운대구 79
 
7.4%
수영구 70
 
6.6%
민락동 40
 
3.8%
송정동 28
 
2.6%
우동 26
 
2.5%
광안동 24
 
2.3%
중동 23
 
2.2%
부산진구 19
 
1.8%
중구 18
 
1.7%
Other values (328) 483
45.5%
2024-04-22T05:23:07.856874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
810
 
14.7%
295
 
5.3%
283
 
5.1%
283
 
5.1%
1 279
 
5.0%
268
 
4.8%
256
 
4.6%
251
 
4.5%
242
 
4.4%
- 220
 
4.0%
Other values (154) 2342
42.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3382
61.2%
Decimal Number 1101
 
19.9%
Space Separator 810
 
14.7%
Dash Punctuation 220
 
4.0%
Uppercase Letter 7
 
0.1%
Other Punctuation 3
 
0.1%
Math Symbol 2
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
295
 
8.7%
283
 
8.4%
283
 
8.4%
268
 
7.9%
256
 
7.6%
251
 
7.4%
242
 
7.2%
184
 
5.4%
174
 
5.1%
91
 
2.7%
Other values (133) 1055
31.2%
Decimal Number
ValueCountFrequency (%)
1 279
25.3%
2 128
11.6%
4 121
11.0%
5 109
 
9.9%
3 100
 
9.1%
0 87
 
7.9%
8 81
 
7.4%
7 71
 
6.4%
6 67
 
6.1%
9 58
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
K 2
28.6%
A 2
28.6%
O 1
14.3%
T 1
14.3%
G 1
14.3%
Space Separator
ValueCountFrequency (%)
810
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 220
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3382
61.2%
Common 2140
38.7%
Latin 7
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
295
 
8.7%
283
 
8.4%
283
 
8.4%
268
 
7.9%
256
 
7.6%
251
 
7.4%
242
 
7.2%
184
 
5.4%
174
 
5.1%
91
 
2.7%
Other values (133) 1055
31.2%
Common
ValueCountFrequency (%)
810
37.9%
1 279
 
13.0%
- 220
 
10.3%
2 128
 
6.0%
4 121
 
5.7%
5 109
 
5.1%
3 100
 
4.7%
0 87
 
4.1%
8 81
 
3.8%
7 71
 
3.3%
Other values (6) 134
 
6.3%
Latin
ValueCountFrequency (%)
K 2
28.6%
A 2
28.6%
O 1
14.3%
T 1
14.3%
G 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3382
61.2%
ASCII 2147
38.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
810
37.7%
1 279
 
13.0%
- 220
 
10.2%
2 128
 
6.0%
4 121
 
5.6%
5 109
 
5.1%
3 100
 
4.7%
0 87
 
4.1%
8 81
 
3.8%
7 71
 
3.3%
Other values (11) 141
 
6.6%
Hangul
ValueCountFrequency (%)
295
 
8.7%
283
 
8.4%
283
 
8.4%
268
 
7.9%
256
 
7.6%
251
 
7.4%
242
 
7.2%
184
 
5.4%
174
 
5.1%
91
 
2.7%
Other values (133) 1055
31.2%
Distinct247
Distinct (%)99.2%
Missing2
Missing (%)0.8%
Memory size2.1 KiB
2024-04-22T05:23:09.047635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length42
Mean length29.353414
Min length20

Characters and Unicode

Total characters7309
Distinct characters215
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

Unique245 ?
Unique (%)98.4%

Sample

1st row부산광역시 수영구 광안해변로 249, 7층 (민락동, 홍윤빌딩)
2nd row부산광역시 동래구 금강로 110 (온천동)
3rd row부산광역시 해운대구 송정광어골로 15-1, 3,4층 (송정동, 프롬 게스트하우스)
4th row부산광역시 해운대구 센텀2로 25, 14층 (우동, 센텀드림월드)
5th row부산광역시 해운대구 해운대해변로209번가길 25 (우동, 노비오스모텔)
ValueCountFrequency (%)
부산광역시 249
 
17.9%
해운대구 79
 
5.7%
수영구 70
 
5.0%
민락동 41
 
2.9%
송정동 28
 
2.0%
광안동 25
 
1.8%
우동 24
 
1.7%
중동 23
 
1.7%
부산진구 19
 
1.4%
중구 18
 
1.3%
Other values (424) 817
58.7%
2024-04-22T05:23:10.960569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1163
 
15.9%
342
 
4.7%
299
 
4.1%
285
 
3.9%
283
 
3.9%
258
 
3.5%
251
 
3.4%
250
 
3.4%
) 240
 
3.3%
( 240
 
3.3%
Other values (205) 3698
50.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4503
61.6%
Space Separator 1163
 
15.9%
Decimal Number 969
 
13.3%
Close Punctuation 240
 
3.3%
Open Punctuation 240
 
3.3%
Other Punctuation 125
 
1.7%
Dash Punctuation 34
 
0.5%
Math Symbol 21
 
0.3%
Uppercase Letter 14
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
342
 
7.6%
299
 
6.6%
285
 
6.3%
283
 
6.3%
258
 
5.7%
251
 
5.6%
250
 
5.6%
235
 
5.2%
178
 
4.0%
151
 
3.4%
Other values (181) 1971
43.8%
Decimal Number
ValueCountFrequency (%)
1 201
20.7%
2 149
15.4%
3 117
12.1%
7 90
9.3%
4 86
8.9%
6 80
 
8.3%
5 73
 
7.5%
9 65
 
6.7%
0 57
 
5.9%
8 51
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
A 4
28.6%
B 2
14.3%
K 2
14.3%
C 2
14.3%
O 1
 
7.1%
G 1
 
7.1%
T 1
 
7.1%
M 1
 
7.1%
Space Separator
ValueCountFrequency (%)
1163
100.0%
Close Punctuation
ValueCountFrequency (%)
) 240
100.0%
Open Punctuation
ValueCountFrequency (%)
( 240
100.0%
Other Punctuation
ValueCountFrequency (%)
, 125
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 34
100.0%
Math Symbol
ValueCountFrequency (%)
~ 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4503
61.6%
Common 2792
38.2%
Latin 14
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
342
 
7.6%
299
 
6.6%
285
 
6.3%
283
 
6.3%
258
 
5.7%
251
 
5.6%
250
 
5.6%
235
 
5.2%
178
 
4.0%
151
 
3.4%
Other values (181) 1971
43.8%
Common
ValueCountFrequency (%)
1163
41.7%
) 240
 
8.6%
( 240
 
8.6%
1 201
 
7.2%
2 149
 
5.3%
, 125
 
4.5%
3 117
 
4.2%
7 90
 
3.2%
4 86
 
3.1%
6 80
 
2.9%
Other values (6) 301
 
10.8%
Latin
ValueCountFrequency (%)
A 4
28.6%
B 2
14.3%
K 2
14.3%
C 2
14.3%
O 1
 
7.1%
G 1
 
7.1%
T 1
 
7.1%
M 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4503
61.6%
ASCII 2806
38.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1163
41.4%
) 240
 
8.6%
( 240
 
8.6%
1 201
 
7.2%
2 149
 
5.3%
, 125
 
4.5%
3 117
 
4.2%
7 90
 
3.2%
4 86
 
3.1%
6 80
 
2.9%
Other values (14) 315
 
11.2%
Hangul
ValueCountFrequency (%)
342
 
7.6%
299
 
6.6%
285
 
6.3%
283
 
6.3%
258
 
5.7%
251
 
5.6%
250
 
5.6%
235
 
5.2%
178
 
4.0%
151
 
3.4%
Other values (181) 1971
43.8%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct90
Distinct (%)42.9%
Missing41
Missing (%)16.3%
Infinite0
Infinite (%)0.0%
Mean53348.09
Minimum46027
Maximum602831
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-22T05:23:11.353864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46027
5-th percentile46397.3
Q148073
median48100
Q348303
95-th percentile48974.9
Maximum602831
Range556804
Interquartile range (IQR)230

Descriptive statistics

Standard deviation53964.895
Coefficient of variation (CV)1.0115619
Kurtosis102.42942
Mean53348.09
Median Absolute Deviation (MAD)184
Skewness10.170414
Sum11203099
Variance2.9122099 × 109
MonotonicityNot monotonic
2024-04-22T05:23:11.766046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
48283 23
 
9.2%
48073 22
 
8.8%
48303 18
 
7.2%
48093 10
 
4.0%
48099 7
 
2.8%
48284 6
 
2.4%
48290 5
 
2.0%
48094 5
 
2.0%
48072 4
 
1.6%
47287 4
 
1.6%
Other values (80) 106
42.2%
(Missing) 41
 
16.3%
ValueCountFrequency (%)
46027 1
 
0.4%
46032 1
 
0.4%
46044 3
1.2%
46079 1
 
0.4%
46082 1
 
0.4%
46083 2
0.8%
46084 1
 
0.4%
46274 1
 
0.4%
46548 1
 
0.4%
46567 1
 
0.4%
ValueCountFrequency (%)
602831 1
0.4%
601829 1
0.4%
49312 1
0.4%
49311 1
0.4%
49275 1
0.4%
49269 1
0.4%
49264 2
0.8%
49037 1
0.4%
48983 2
0.8%
48965 1
0.4%
Distinct246
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-04-22T05:23:12.697126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length20
Mean length8.5498008
Min length2

Characters and Unicode

Total characters2146
Distinct characters302
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique241 ?
Unique (%)96.0%

Sample

1st row지니게스트하우스2
2nd row동방관광호텔
3rd row프롬 게스트하우스
4th row스테이7 센텀 비지니스 호스텔
5th rowARK BLUE HOTEL
ValueCountFrequency (%)
호텔 18
 
4.6%
부산 11
 
2.8%
호스텔 10
 
2.6%
관광호텔 8
 
2.1%
해운대 7
 
1.8%
게스트하우스 7
 
1.8%
브라운도트호텔 6
 
1.5%
브라운도트 5
 
1.3%
hotel 4
 
1.0%
토요코인 3
 
0.8%
Other values (292) 309
79.6%
2024-04-22T05:23:14.040311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
163
 
7.6%
163
 
7.6%
137
 
6.4%
112
 
5.2%
61
 
2.8%
52
 
2.4%
52
 
2.4%
48
 
2.2%
( 38
 
1.8%
38
 
1.8%
Other values (292) 1282
59.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1728
80.5%
Space Separator 137
 
6.4%
Uppercase Letter 111
 
5.2%
Decimal Number 42
 
2.0%
Open Punctuation 39
 
1.8%
Close Punctuation 39
 
1.8%
Lowercase Letter 39
 
1.8%
Other Punctuation 6
 
0.3%
Dash Punctuation 3
 
0.1%
Letter Number 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
163
 
9.4%
163
 
9.4%
112
 
6.5%
61
 
3.5%
52
 
3.0%
52
 
3.0%
48
 
2.8%
38
 
2.2%
34
 
2.0%
33
 
1.9%
Other values (238) 972
56.2%
Uppercase Letter
ValueCountFrequency (%)
E 15
13.5%
A 11
9.9%
L 10
 
9.0%
H 9
 
8.1%
T 9
 
8.1%
B 7
 
6.3%
N 7
 
6.3%
G 7
 
6.3%
O 6
 
5.4%
S 4
 
3.6%
Other values (11) 26
23.4%
Lowercase Letter
ValueCountFrequency (%)
e 7
17.9%
o 5
12.8%
s 4
10.3%
l 4
10.3%
t 3
7.7%
u 3
7.7%
g 3
7.7%
i 2
 
5.1%
d 2
 
5.1%
h 2
 
5.1%
Other values (4) 4
10.3%
Decimal Number
ValueCountFrequency (%)
2 7
16.7%
5 7
16.7%
3 7
16.7%
9 5
11.9%
1 4
9.5%
6 4
9.5%
7 3
7.1%
8 2
 
4.8%
4 2
 
4.8%
0 1
 
2.4%
Open Punctuation
ValueCountFrequency (%)
( 38
97.4%
[ 1
 
2.6%
Close Punctuation
ValueCountFrequency (%)
) 38
97.4%
] 1
 
2.6%
Other Punctuation
ValueCountFrequency (%)
& 3
50.0%
. 3
50.0%
Space Separator
ValueCountFrequency (%)
137
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Letter Number
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1728
80.5%
Common 266
 
12.4%
Latin 152
 
7.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
163
 
9.4%
163
 
9.4%
112
 
6.5%
61
 
3.5%
52
 
3.0%
52
 
3.0%
48
 
2.8%
38
 
2.2%
34
 
2.0%
33
 
1.9%
Other values (238) 972
56.2%
Latin
ValueCountFrequency (%)
E 15
 
9.9%
A 11
 
7.2%
L 10
 
6.6%
H 9
 
5.9%
T 9
 
5.9%
e 7
 
4.6%
B 7
 
4.6%
N 7
 
4.6%
G 7
 
4.6%
O 6
 
3.9%
Other values (26) 64
42.1%
Common
ValueCountFrequency (%)
137
51.5%
( 38
 
14.3%
) 38
 
14.3%
2 7
 
2.6%
5 7
 
2.6%
3 7
 
2.6%
9 5
 
1.9%
1 4
 
1.5%
6 4
 
1.5%
7 3
 
1.1%
Other values (8) 16
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1728
80.5%
ASCII 416
 
19.4%
Number Forms 2
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
163
 
9.4%
163
 
9.4%
112
 
6.5%
61
 
3.5%
52
 
3.0%
52
 
3.0%
48
 
2.8%
38
 
2.2%
34
 
2.0%
33
 
1.9%
Other values (238) 972
56.2%
ASCII
ValueCountFrequency (%)
137
32.9%
( 38
 
9.1%
) 38
 
9.1%
E 15
 
3.6%
A 11
 
2.6%
L 10
 
2.4%
H 9
 
2.2%
T 9
 
2.2%
e 7
 
1.7%
2 7
 
1.7%
Other values (43) 135
32.5%
Number Forms
ValueCountFrequency (%)
2
100.0%

최종수정시점
Real number (ℝ)

UNIQUE 

Distinct251
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0183437 × 1013
Minimum2.0050621 × 1013
Maximum2.0201229 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-22T05:23:14.453708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0050621 × 1013
5-th percentile2.0080467 × 1013
Q12.0181212 × 1013
median2.0200211 × 1013
Q32.020071 × 1013
95-th percentile2.0201212 × 1013
Maximum2.0201229 × 1013
Range1.5060798 × 1011
Interquartile range (IQR)1.9498001 × 1010

Descriptive statistics

Standard deviation3.4194469 × 1010
Coefficient of variation (CV)0.0016941846
Kurtosis6.9012688
Mean2.0183437 × 1013
Median Absolute Deviation (MAD)1.0149975 × 109
Skewness-2.77087
Sum5.0660428 × 1015
Variance1.1692617 × 1021
MonotonicityNot monotonic
2024-04-22T05:23:14.916683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20180827102326 1
 
0.4%
20181219104323 1
 
0.4%
20190603101233 1
 
0.4%
20171120193904 1
 
0.4%
20190625115914 1
 
0.4%
20190910154403 1
 
0.4%
20190808133900 1
 
0.4%
20181031103541 1
 
0.4%
20180124153831 1
 
0.4%
20190808134050 1
 
0.4%
Other values (241) 241
96.0%
ValueCountFrequency (%)
20050621104507 1
0.4%
20050711162144 1
0.4%
20050727133220 1
0.4%
20060602145220 1
0.4%
20060628142421 1
0.4%
20060731144015 1
0.4%
20060927180940 1
0.4%
20060929162709 1
0.4%
20061020155727 1
0.4%
20061031180359 1
0.4%
ValueCountFrequency (%)
20201229085600 1
0.4%
20201226162114 1
0.4%
20201226162040 1
0.4%
20201226162009 1
0.4%
20201226161909 1
0.4%
20201226161849 1
0.4%
20201226161825 1
0.4%
20201224143334 1
0.4%
20201222170456 1
0.4%
20201222092517 1
0.4%
Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
U
189 
I
62 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 189
75.3%
I 62
 
24.7%

Length

2024-04-22T05:23:15.339378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T05:23:15.643688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 189
75.3%
i 62
 
24.7%
Distinct117
Distinct (%)46.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
Minimum2018-08-31 23:59:59
Maximum2020-12-31 02:40:00
2024-04-22T05:23:15.972380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T05:23:16.411919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing251
Missing (%)100.0%
Memory size2.3 KiB

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct225
Distinct (%)91.1%
Missing4
Missing (%)1.6%
Infinite0
Infinite (%)0.0%
Mean392473.81
Minimum379032.34
Maximum404842.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-22T05:23:16.840638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum379032.34
5-th percentile383791.31
Q1387513.6
median393184.26
Q3396695.26
95-th percentile400616.4
Maximum404842.8
Range25810.454
Interquartile range (IQR)9181.6588

Descriptive statistics

Standard deviation5642.5716
Coefficient of variation (CV)0.014376938
Kurtosis-0.60027773
Mean392473.81
Median Absolute Deviation (MAD)4031.0941
Skewness-0.24251849
Sum96941031
Variance31838614
MonotonicityNot monotonic
2024-04-22T05:23:17.288924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
393521.998603867 7
 
2.8%
397494.828591053 3
 
1.2%
395574.958778256 3
 
1.2%
397022.971550345 3
 
1.2%
400209.911813606 2
 
0.8%
384719.60881858 2
 
0.8%
392732.161638137 2
 
0.8%
392578.29664069 2
 
0.8%
393475.046553126 2
 
0.8%
396200.686719735 2
 
0.8%
Other values (215) 219
87.3%
(Missing) 4
 
1.6%
ValueCountFrequency (%)
379032.341485035 1
0.4%
379146.456410293 1
0.4%
379166.258036809 1
0.4%
379217.521019149 1
0.4%
379527.59641944 1
0.4%
379731.953370869 1
0.4%
380460.313281968 1
0.4%
380690.195137444 1
0.4%
381753.509588417 1
0.4%
382619.443760653 1
0.4%
ValueCountFrequency (%)
404842.795477 1
0.4%
403158.948088181 1
0.4%
403138.677972054 1
0.4%
402899.903247998 1
0.4%
402877.316530715 1
0.4%
402350.452980965 1
0.4%
402144.440463941 1
0.4%
401110.03747854 1
0.4%
400817.585616257 1
0.4%
400768.055656637 1
0.4%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct225
Distinct (%)91.1%
Missing4
Missing (%)1.6%
Infinite0
Infinite (%)0.0%
Mean186202.53
Minimum174765.31
Maximum207516.98
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-22T05:23:17.690933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum174765.31
5-th percentile179593.14
Q1185526.96
median186199.79
Q3187521.49
95-th percentile192711.77
Maximum207516.98
Range32751.676
Interquartile range (IQR)1994.5323

Descriptive statistics

Standard deviation3989.0851
Coefficient of variation (CV)0.021423367
Kurtosis4.9378199
Mean186202.53
Median Absolute Deviation (MAD)902.87581
Skewness0.76182054
Sum45992025
Variance15912800
MonotonicityNot monotonic
2024-04-22T05:23:18.127486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
185933.100965604 7
 
2.8%
187231.036757478 3
 
1.2%
186053.656022508 3
 
1.2%
186692.06462196 3
 
1.2%
188930.337546361 2
 
0.8%
178090.566769083 2
 
0.8%
185542.452702234 2
 
0.8%
185333.165354711 2
 
0.8%
186049.671295774 2
 
0.8%
186216.650203359 2
 
0.8%
Other values (215) 219
87.3%
(Missing) 4
 
1.6%
ValueCountFrequency (%)
174765.307900471 1
0.4%
175776.950578959 1
0.4%
176944.175666118 1
0.4%
177210.05114787 1
0.4%
177272.599070061 1
0.4%
178090.566769083 2
0.8%
179018.65381904 1
0.4%
179296.177935356 1
0.4%
179447.226505734 1
0.4%
179482.336622982 1
0.4%
ValueCountFrequency (%)
207516.984282 1
0.4%
204037.010296474 1
0.4%
198055.522421124 1
0.4%
198007.244770813 1
0.4%
195952.674076618 1
0.4%
194554.94940589 1
0.4%
193732.986829639 1
0.4%
193209.131530013 1
0.4%
193171.650339148 1
0.4%
192996.253435511 1
0.4%

문화체육업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
관광숙박업
251 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
관광숙박업 251
100.0%

Length

2024-04-22T05:23:18.541768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T05:23:18.835784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
관광숙박업 251
100.0%
Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
186 
관광사업
65 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 186
74.1%
관광사업 65
 
25.9%

Length

2024-04-22T05:23:19.160095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T05:23:19.467631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 186
74.1%
관광사업 65
 
25.9%

지역구분명
Categorical

Distinct10
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
89 
일반상업지역
77 
준주거지역
46 
상업지역
21 
일반주거지역
Other values (5)

Length

Max length6
Median length5
Mean length4.9003984
Min length4

Unique

Unique2 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 89
35.5%
일반상업지역 77
30.7%
준주거지역 46
18.3%
상업지역 21
 
8.4%
일반주거지역 9
 
3.6%
주거지역 3
 
1.2%
자연녹지지역 2
 
0.8%
준공업지역 2
 
0.8%
공업지역 1
 
0.4%
중심상업지역 1
 
0.4%

Length

2024-04-22T05:23:19.832924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T05:23:20.213019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 89
35.5%
일반상업지역 77
30.7%
준주거지역 46
18.3%
상업지역 21
 
8.4%
일반주거지역 9
 
3.6%
주거지역 3
 
1.2%
자연녹지지역 2
 
0.8%
준공업지역 2
 
0.8%
공업지역 1
 
0.4%
중심상업지역 1
 
0.4%

총층수
Real number (ℝ)

MISSING 

Distinct26
Distinct (%)16.6%
Missing94
Missing (%)37.5%
Infinite0
Infinite (%)0.0%
Mean10.178344
Minimum1
Maximum47
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-22T05:23:20.607136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q16
median9
Q312
95-th percentile21
Maximum47
Range46
Interquartile range (IQR)6

Descriptive statistics

Standard deviation6.4345852
Coefficient of variation (CV)0.6321839
Kurtosis8.4785404
Mean10.178344
Median Absolute Deviation (MAD)3
Skewness2.2114995
Sum1598
Variance41.403887
MonotonicityNot monotonic
2024-04-22T05:23:20.987228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
10 22
 
8.8%
7 14
 
5.6%
5 13
 
5.2%
8 13
 
5.2%
11 13
 
5.2%
9 11
 
4.4%
12 10
 
4.0%
6 10
 
4.0%
2 7
 
2.8%
4 7
 
2.8%
Other values (16) 37
 
14.7%
(Missing) 94
37.5%
ValueCountFrequency (%)
1 2
 
0.8%
2 7
 
2.8%
3 3
 
1.2%
4 7
 
2.8%
5 13
5.2%
6 10
4.0%
7 14
5.6%
8 13
5.2%
9 11
4.4%
10 22
8.8%
ValueCountFrequency (%)
47 1
 
0.4%
39 1
 
0.4%
28 1
 
0.4%
25 2
 
0.8%
24 2
 
0.8%
21 2
 
0.8%
20 1
 
0.4%
19 5
2.0%
18 3
1.2%
17 5
2.0%

주변환경명
Categorical

Distinct5
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
166 
기타
52 
유흥업소밀집지역
 
15
학교정화(상대)
 
13
주택가주변
 
5

Length

Max length8
Median length4
Mean length4.0517928
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 166
66.1%
기타 52
 
20.7%
유흥업소밀집지역 15
 
6.0%
학교정화(상대) 13
 
5.2%
주택가주변 5
 
2.0%

Length

2024-04-22T05:23:21.400095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T05:23:21.733747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 166
66.1%
기타 52
 
20.7%
유흥업소밀집지역 15
 
6.0%
학교정화(상대 13
 
5.2%
주택가주변 5
 
2.0%

제작취급품목내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing251
Missing (%)100.0%
Memory size2.3 KiB

보험기관명
Text

MISSING 

Distinct16
Distinct (%)64.0%
Missing226
Missing (%)90.0%
Memory size2.1 KiB
2024-04-22T05:23:22.330542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length13
Mean length7.44
Min length2

Characters and Unicode

Total characters186
Distinct characters35
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)48.0%

Sample

1st row재난배상책임보험
2nd row메리츠화재
3rd row동부
4th row한화손해보험
5th row현대
ValueCountFrequency (%)
재난배상책임보험 5
19.2%
한화손해보험 4
15.4%
메리츠화재 3
11.5%
농협손해보험주식회사 2
 
7.7%
현대해상화재보험 1
 
3.8%
동부 1
 
3.8%
현대 1
 
3.8%
메리츠보험 1
 
3.8%
수협 1
 
3.8%
삼성화재해상보험주식회사 1
 
3.8%
Other values (6) 6
23.1%
2024-04-22T05:23:23.379506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17
 
9.1%
17
 
9.1%
16
 
8.6%
13
 
7.0%
11
 
5.9%
10
 
5.4%
7
 
3.8%
7
 
3.8%
7
 
3.8%
7
 
3.8%
Other values (25) 74
39.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 179
96.2%
Open Punctuation 2
 
1.1%
Close Punctuation 2
 
1.1%
Uppercase Letter 2
 
1.1%
Space Separator 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
17
 
9.5%
17
 
9.5%
16
 
8.9%
13
 
7.3%
11
 
6.1%
10
 
5.6%
7
 
3.9%
7
 
3.9%
7
 
3.9%
7
 
3.9%
Other values (20) 67
37.4%
Uppercase Letter
ValueCountFrequency (%)
N 1
50.0%
H 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 179
96.2%
Common 5
 
2.7%
Latin 2
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
17
 
9.5%
17
 
9.5%
16
 
8.9%
13
 
7.3%
11
 
6.1%
10
 
5.6%
7
 
3.9%
7
 
3.9%
7
 
3.9%
7
 
3.9%
Other values (20) 67
37.4%
Common
ValueCountFrequency (%)
( 2
40.0%
) 2
40.0%
1
20.0%
Latin
ValueCountFrequency (%)
N 1
50.0%
H 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 179
96.2%
ASCII 7
 
3.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
17
 
9.5%
17
 
9.5%
16
 
8.9%
13
 
7.3%
11
 
6.1%
10
 
5.6%
7
 
3.9%
7
 
3.9%
7
 
3.9%
7
 
3.9%
Other values (20) 67
37.4%
ASCII
ValueCountFrequency (%)
( 2
28.6%
) 2
28.6%
N 1
14.3%
H 1
14.3%
1
14.3%

건물용도명
Categorical

Distinct6
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
125 
숙박시설
82 
호텔
38 
근린생활시설
 
3
콘도미니엄
 
2

Length

Max length6
Median length4
Mean length3.7211155
Min length2

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 125
49.8%
숙박시설 82
32.7%
호텔 38
 
15.1%
근린생활시설 3
 
1.2%
콘도미니엄 2
 
0.8%
기타 1
 
0.4%

Length

2024-04-22T05:23:23.814391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T05:23:24.164320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 125
49.8%
숙박시설 82
32.7%
호텔 38
 
15.1%
근린생활시설 3
 
1.2%
콘도미니엄 2
 
0.8%
기타 1
 
0.4%

지상층수
Real number (ℝ)

MISSING 

Distinct23
Distinct (%)14.8%
Missing96
Missing (%)38.2%
Infinite0
Infinite (%)0.0%
Mean9.7870968
Minimum2
Maximum43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-22T05:23:24.515839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3
Q16
median9
Q311
95-th percentile20
Maximum43
Range41
Interquartile range (IQR)5

Descriptive statistics

Standard deviation5.9706937
Coefficient of variation (CV)0.61005769
Kurtosis8.8991779
Mean9.7870968
Median Absolute Deviation (MAD)3
Skewness2.339875
Sum1517
Variance35.649183
MonotonicityNot monotonic
2024-04-22T05:23:24.890003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
10 21
 
8.4%
8 20
 
8.0%
9 17
 
6.8%
6 14
 
5.6%
4 12
 
4.8%
7 12
 
4.8%
15 9
 
3.6%
3 7
 
2.8%
5 7
 
2.8%
11 7
 
2.8%
Other values (13) 29
 
11.6%
(Missing) 96
38.2%
ValueCountFrequency (%)
2 3
 
1.2%
3 7
 
2.8%
4 12
4.8%
5 7
 
2.8%
6 14
5.6%
7 12
4.8%
8 20
8.0%
9 17
6.8%
10 21
8.4%
11 7
 
2.8%
ValueCountFrequency (%)
43 1
 
0.4%
39 1
 
0.4%
26 1
 
0.4%
24 1
 
0.4%
23 1
 
0.4%
22 2
 
0.8%
20 2
 
0.8%
19 5
2.0%
17 2
 
0.8%
16 2
 
0.8%

지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)4.9%
Missing129
Missing (%)51.4%
Infinite0
Infinite (%)0.0%
Mean1.6885246
Minimum0
Maximum5
Zeros7
Zeros (%)2.8%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-22T05:23:25.229587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.05
Q11
median1
Q32
95-th percentile4
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.0990752
Coefficient of variation (CV)0.65090864
Kurtosis0.67023882
Mean1.6885246
Median Absolute Deviation (MAD)0.5
Skewness1.0648966
Sum206
Variance1.2079664
MonotonicityNot monotonic
2024-04-22T05:23:25.583431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 61
24.3%
2 31
 
12.4%
3 11
 
4.4%
4 10
 
4.0%
0 7
 
2.8%
5 2
 
0.8%
(Missing) 129
51.4%
ValueCountFrequency (%)
0 7
 
2.8%
1 61
24.3%
2 31
12.4%
3 11
 
4.4%
4 10
 
4.0%
5 2
 
0.8%
ValueCountFrequency (%)
5 2
 
0.8%
4 10
 
4.0%
3 11
 
4.4%
2 31
12.4%
1 61
24.3%
0 7
 
2.8%

객실수
Real number (ℝ)

MISSING 

Distinct100
Distinct (%)51.0%
Missing55
Missing (%)21.9%
Infinite0
Infinite (%)0.0%
Mean71.408163
Minimum1
Maximum650
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-22T05:23:25.954782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q17
median32
Q362
95-th percentile319.5
Maximum650
Range649
Interquartile range (IQR)55

Descriptive statistics

Standard deviation111.91598
Coefficient of variation (CV)1.5672715
Kurtosis7.0538919
Mean71.408163
Median Absolute Deviation (MAD)25
Skewness2.5902094
Sum13996
Variance12525.186
MonotonicityNot monotonic
2024-04-22T05:23:26.392422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7 12
 
4.8%
5 9
 
3.6%
6 9
 
3.6%
3 7
 
2.8%
2 7
 
2.8%
8 7
 
2.8%
40 5
 
2.0%
4 5
 
2.0%
48 4
 
1.6%
45 4
 
1.6%
Other values (90) 127
50.6%
(Missing) 55
21.9%
ValueCountFrequency (%)
1 2
 
0.8%
2 7
2.8%
3 7
2.8%
4 5
2.0%
5 9
3.6%
6 9
3.6%
7 12
4.8%
8 7
2.8%
9 3
 
1.2%
10 2
 
0.8%
ValueCountFrequency (%)
650 1
0.4%
528 1
0.4%
510 1
0.4%
491 1
0.4%
417 1
0.4%
407 1
0.4%
393 1
0.4%
350 1
0.4%
331 1
0.4%
330 1
0.4%

건축연면적
Real number (ℝ)

MISSING 

Distinct81
Distinct (%)97.6%
Missing168
Missing (%)66.9%
Infinite0
Infinite (%)0.0%
Mean9209.3614
Minimum114
Maximum183804
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-22T05:23:26.804210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum114
5-th percentile340
Q11349.5
median2737
Q37143
95-th percentile20571
Maximum183804
Range183690
Interquartile range (IQR)5793.5

Descriptive statistics

Standard deviation24114.201
Coefficient of variation (CV)2.6184444
Kurtosis36.229497
Mean9209.3614
Median Absolute Deviation (MAD)1749
Skewness5.6625897
Sum764377
Variance5.8149468 × 108
MonotonicityNot monotonic
2024-04-22T05:23:27.519559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20571 2
 
0.8%
821 2
 
0.8%
1321 1
 
0.4%
3419 1
 
0.4%
2324 1
 
0.4%
547 1
 
0.4%
1198 1
 
0.4%
1781 1
 
0.4%
3655 1
 
0.4%
616 1
 
0.4%
Other values (71) 71
28.3%
(Missing) 168
66.9%
ValueCountFrequency (%)
114 1
0.4%
119 1
0.4%
302 1
0.4%
320 1
0.4%
334 1
0.4%
394 1
0.4%
427 1
0.4%
530 1
0.4%
547 1
0.4%
616 1
0.4%
ValueCountFrequency (%)
183804 1
0.4%
93982 1
0.4%
84753 1
0.4%
29599 1
0.4%
20571 2
0.8%
19952 1
0.4%
19846 1
0.4%
18393 1
0.4%
17033 1
0.4%
16175 1
0.4%

영문상호명
Text

MISSING 

Distinct33
Distinct (%)100.0%
Missing218
Missing (%)86.9%
Memory size2.1 KiB
2024-04-22T05:23:28.295884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length26
Mean length19.393939
Min length8

Characters and Unicode

Total characters640
Distinct characters50
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)100.0%

Sample

1st rowRIO TOURIST HOTEL
2nd rowSolaria Nishitetsu Hotel Busan
3rd rowNEW CONTINENTAL TOURIST HOTEL
4th rowTOURIST HOTEL MIRABO Inc
5th rowFour Seansons Guest House
ValueCountFrequency (%)
hotel 23
22.8%
busan 5
 
5.0%
tourist 5
 
5.0%
house 3
 
3.0%
city 2
 
2.0%
hostel 2
 
2.0%
brown-dot 2
 
2.0%
b 1
 
1.0%
toyoko 1
 
1.0%
rio 1
 
1.0%
Other values (56) 56
55.4%
2024-04-22T05:23:29.469325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
68
 
10.6%
O 47
 
7.3%
T 39
 
6.1%
H 35
 
5.5%
E 31
 
4.8%
e 27
 
4.2%
S 27
 
4.2%
L 26
 
4.1%
o 26
 
4.1%
N 26
 
4.1%
Other values (40) 288
45.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 364
56.9%
Lowercase Letter 192
30.0%
Space Separator 68
 
10.6%
Other Punctuation 8
 
1.2%
Dash Punctuation 5
 
0.8%
Final Punctuation 1
 
0.2%
Open Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
O 47
12.9%
T 39
10.7%
H 35
9.6%
E 31
 
8.5%
S 27
 
7.4%
L 26
 
7.1%
N 26
 
7.1%
A 21
 
5.8%
I 17
 
4.7%
U 16
 
4.4%
Other values (12) 79
21.7%
Lowercase Letter
ValueCountFrequency (%)
e 27
14.1%
o 26
13.5%
t 24
12.5%
n 16
8.3%
s 15
7.8%
a 13
6.8%
l 13
6.8%
u 12
6.2%
i 12
6.2%
r 6
 
3.1%
Other values (10) 28
14.6%
Other Punctuation
ValueCountFrequency (%)
, 4
50.0%
. 3
37.5%
& 1
 
12.5%
Space Separator
ValueCountFrequency (%)
68
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Final Punctuation
ValueCountFrequency (%)
1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 556
86.9%
Common 84
 
13.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
O 47
 
8.5%
T 39
 
7.0%
H 35
 
6.3%
E 31
 
5.6%
e 27
 
4.9%
S 27
 
4.9%
L 26
 
4.7%
o 26
 
4.7%
N 26
 
4.7%
t 24
 
4.3%
Other values (32) 248
44.6%
Common
ValueCountFrequency (%)
68
81.0%
- 5
 
6.0%
, 4
 
4.8%
. 3
 
3.6%
1
 
1.2%
( 1
 
1.2%
) 1
 
1.2%
& 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 639
99.8%
Punctuation 1
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
68
 
10.6%
O 47
 
7.4%
T 39
 
6.1%
H 35
 
5.5%
E 31
 
4.9%
e 27
 
4.2%
S 27
 
4.2%
L 26
 
4.1%
o 26
 
4.1%
N 26
 
4.1%
Other values (39) 287
44.9%
Punctuation
ValueCountFrequency (%)
1
100.0%

영문상호주소
Text

MISSING 

Distinct16
Distinct (%)51.6%
Missing220
Missing (%)87.6%
Memory size2.1 KiB
2024-04-22T05:23:30.031949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length39
Mean length26.903226
Min length6

Characters and Unicode

Total characters834
Distinct characters37
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)29.0%

Sample

1st rowTOURIST ACCOMMODATION(TOURIST HOTEL)
2nd rowTourist Hotel
3rd rowTOURIST ACCOMMODATION (TOURIST HOTEL)
4th rowTOURIST HOTEL
5th rowHostel
ValueCountFrequency (%)
tourist 26
30.6%
hotel 21
24.7%
accommodation(tourist 9
 
10.6%
accommodation 7
 
8.2%
business 5
 
5.9%
hostel 5
 
5.9%
tourism 4
 
4.7%
accommodation(hostel 2
 
2.4%
certificate 1
 
1.2%
of 1
 
1.2%
Other values (4) 4
 
4.7%
2024-04-22T05:23:31.032806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
T 106
 
12.7%
O 99
 
11.9%
I 54
 
6.5%
53
 
6.4%
S 38
 
4.6%
A 36
 
4.3%
C 36
 
4.3%
M 36
 
4.3%
R 35
 
4.2%
U 33
 
4.0%
Other values (27) 308
36.9%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 575
68.9%
Lowercase Letter 170
 
20.4%
Space Separator 53
 
6.4%
Open Punctuation 17
 
2.0%
Close Punctuation 17
 
2.0%
Control 1
 
0.1%
Decimal Number 1
 
0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T 106
18.4%
O 99
17.2%
I 54
9.4%
S 38
 
6.6%
A 36
 
6.3%
C 36
 
6.3%
M 36
 
6.3%
R 35
 
6.1%
U 33
 
5.7%
H 26
 
4.5%
Other values (7) 76
13.2%
Lowercase Letter
ValueCountFrequency (%)
o 27
15.9%
s 26
15.3%
t 23
13.5%
e 16
9.4%
i 15
8.8%
u 13
7.6%
l 12
7.1%
r 9
 
5.3%
m 6
 
3.5%
n 6
 
3.5%
Other values (5) 17
10.0%
Space Separator
ValueCountFrequency (%)
53
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Control
ValueCountFrequency (%)
1
100.0%
Decimal Number
ValueCountFrequency (%)
0 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 745
89.3%
Common 89
 
10.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
T 106
14.2%
O 99
13.3%
I 54
 
7.2%
S 38
 
5.1%
A 36
 
4.8%
C 36
 
4.8%
M 36
 
4.8%
R 35
 
4.7%
U 33
 
4.4%
o 27
 
3.6%
Other values (22) 245
32.9%
Common
ValueCountFrequency (%)
53
59.6%
( 17
 
19.1%
) 17
 
19.1%
1
 
1.1%
0 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 834
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
T 106
 
12.7%
O 99
 
11.9%
I 54
 
6.5%
53
 
6.4%
S 38
 
4.6%
A 36
 
4.3%
C 36
 
4.3%
M 36
 
4.3%
R 35
 
4.2%
U 33
 
4.0%
Other values (27) 308
36.9%

선박총톤수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing251
Missing (%)100.0%
Memory size2.3 KiB

선박척수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing251
Missing (%)100.0%
Memory size2.3 KiB

선박제원
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing251
Missing (%)100.0%
Memory size2.3 KiB

무대면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing251
Missing (%)100.0%
Memory size2.3 KiB

좌석수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing251
Missing (%)100.0%
Memory size2.3 KiB

기념품종류
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing251
Missing (%)100.0%
Memory size2.3 KiB

회의실별동시수용인원
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing251
Missing (%)100.0%
Memory size2.3 KiB

시설면적
Real number (ℝ)

MISSING 

Distinct181
Distinct (%)97.8%
Missing66
Missing (%)26.3%
Infinite0
Infinite (%)0.0%
Mean4223.7826
Minimum60.65
Maximum93981.55
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-22T05:23:31.437155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum60.65
5-th percentile111.382
Q1342.65
median1084.37
Q33419.18
95-th percentile17841.648
Maximum93981.55
Range93920.9
Interquartile range (IQR)3076.53

Descriptive statistics

Standard deviation10486.873
Coefficient of variation (CV)2.4828156
Kurtosis47.421792
Mean4223.7826
Median Absolute Deviation (MAD)918.43
Skewness6.2877391
Sum781399.78
Variance1.0997451 × 108
MonotonicityNot monotonic
2024-04-22T05:23:31.863272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
165.94 2
 
0.8%
218.85 2
 
0.8%
414.76 2
 
0.8%
415.74 2
 
0.8%
120.07 1
 
0.4%
1382.35 1
 
0.4%
225.16 1
 
0.4%
313.04 1
 
0.4%
3655.72 1
 
0.4%
624.75 1
 
0.4%
Other values (171) 171
68.1%
(Missing) 66
 
26.3%
ValueCountFrequency (%)
60.65 1
0.4%
65.77 1
0.4%
70.39 1
0.4%
75.8 1
0.4%
82.97 1
0.4%
83.37 1
0.4%
107.91 1
0.4%
108.35 1
0.4%
108.39 1
0.4%
109.21 1
0.4%
ValueCountFrequency (%)
93981.55 1
0.4%
84752.66 1
0.4%
30869.96 1
0.4%
28385.0 1
0.4%
27553.0 1
0.4%
25876.24 1
0.4%
24574.5 1
0.4%
19846.0 1
0.4%
18393.47 1
0.4%
18203.31 1
0.4%

놀이기구수내역
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing251
Missing (%)100.0%
Memory size2.3 KiB

놀이시설수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing251
Missing (%)100.0%
Memory size2.3 KiB

방송시설유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing251
Missing (%)100.0%
Memory size2.3 KiB

발전시설유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing251
Missing (%)100.0%
Memory size2.3 KiB

의무실유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing251
Missing (%)100.0%
Memory size2.3 KiB

안내소유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing251
Missing (%)100.0%
Memory size2.3 KiB

기획여행보험시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing251
Missing (%)100.0%
Memory size2.3 KiB

기획여행보험종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing251
Missing (%)100.0%
Memory size2.3 KiB

자본금
Real number (ℝ)

MISSING 

Distinct62
Distinct (%)69.7%
Missing162
Missing (%)64.5%
Infinite0
Infinite (%)0.0%
Mean3.5449526 × 109
Minimum5000000
Maximum7 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-22T05:23:32.274691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5000000
5-th percentile23200000
Q11 × 108
median3.5 × 108
Q32.606 × 109
95-th percentile1.11 × 1010
Maximum7 × 1010
Range6.9995 × 1010
Interquartile range (IQR)2.506 × 109

Descriptive statistics

Standard deviation9.7698124 × 109
Coefficient of variation (CV)2.7559783
Kurtosis29.555061
Mean3.5449526 × 109
Median Absolute Deviation (MAD)3.15 × 108
Skewness5.1609491
Sum3.1550078 × 1011
Variance9.5449235 × 1019
MonotonicityNot monotonic
2024-04-22T05:23:32.730860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100000000 8
 
3.2%
200000000 6
 
2.4%
2000000000 3
 
1.2%
800000000 3
 
1.2%
300000000 3
 
1.2%
150000000 3
 
1.2%
50000000 2
 
0.8%
250000000 2
 
0.8%
5000000000 2
 
0.8%
70000000 2
 
0.8%
Other values (52) 55
 
21.9%
(Missing) 162
64.5%
ValueCountFrequency (%)
5000000 2
0.8%
12000000 1
0.4%
12500000 1
0.4%
20000000 1
0.4%
28000000 1
0.4%
30000000 1
0.4%
35000000 1
0.4%
40000000 1
0.4%
50000000 2
0.8%
59000000 1
0.4%
ValueCountFrequency (%)
70000000000 1
0.4%
48000000000 1
0.4%
35300000000 1
0.4%
15000000000 1
0.4%
12000000000 1
0.4%
9750000000 1
0.4%
9000000000 1
0.4%
8000000000 1
0.4%
7600000000 1
0.4%
7000000000 1
0.4%

보험시작일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
249 
20180124
 
1
20190628
 
1

Length

Max length8
Median length4
Mean length4.0318725
Min length4

Unique

Unique2 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 249
99.2%
20180124 1
 
0.4%
20190628 1
 
0.4%

Length

2024-04-22T05:23:33.188239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T05:23:33.523409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 249
99.2%
20180124 1
 
0.4%
20190628 1
 
0.4%

보험종료일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
249 
20190124
 
1
20200628
 
1

Length

Max length8
Median length4
Mean length4.0318725
Min length4

Unique

Unique2 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 249
99.2%
20190124 1
 
0.4%
20200628 1
 
0.4%

Length

2024-04-22T05:23:33.891958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T05:23:34.232315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 249
99.2%
20190124 1
 
0.4%
20200628 1
 
0.4%

부대시설내역
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing251
Missing (%)100.0%
Memory size2.3 KiB

시설규모
Real number (ℝ)

MISSING 

Distinct174
Distinct (%)94.1%
Missing66
Missing (%)26.3%
Infinite0
Infinite (%)0.0%
Mean4223.7568
Minimum61
Maximum93982
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-22T05:23:34.576864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum61
5-th percentile111.2
Q1343
median1084
Q33419
95-th percentile17841.4
Maximum93982
Range93921
Interquartile range (IQR)3076

Descriptive statistics

Standard deviation10486.917
Coefficient of variation (CV)2.4828411
Kurtosis47.42195
Mean4223.7568
Median Absolute Deviation (MAD)918
Skewness6.2877508
Sum781395
Variance1.0997543 × 108
MonotonicityNot monotonic
2024-04-22T05:23:34.999827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
108 3
 
1.2%
416 3
 
1.2%
120 2
 
0.8%
219 2
 
0.8%
415 2
 
0.8%
166 2
 
0.8%
83 2
 
0.8%
208 2
 
0.8%
334 2
 
0.8%
3653 1
 
0.4%
Other values (164) 164
65.3%
(Missing) 66
26.3%
ValueCountFrequency (%)
61 1
 
0.4%
66 1
 
0.4%
70 1
 
0.4%
76 1
 
0.4%
83 2
0.8%
108 3
1.2%
109 1
 
0.4%
120 2
0.8%
130 1
 
0.4%
131 1
 
0.4%
ValueCountFrequency (%)
93982 1
0.4%
84753 1
0.4%
30870 1
0.4%
28385 1
0.4%
27553 1
0.4%
25876 1
0.4%
24575 1
0.4%
19846 1
0.4%
18393 1
0.4%
18203 1
0.4%
Distinct6
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
관광호텔업
108 
호스텔업
102 
<NA>
29 
휴양콘도미니엄업
 
6
소형호텔업
 
5

Length

Max length8
Median length4
Mean length4.5498008
Min length4

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
관광호텔업 108
43.0%
호스텔업 102
40.6%
<NA> 29
 
11.6%
휴양콘도미니엄업 6
 
2.4%
소형호텔업 5
 
2.0%
가족호텔업 1
 
0.4%

Length

2024-04-22T05:23:35.438343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T05:23:35.797474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
관광호텔업 108
43.0%
호스텔업 102
40.6%
na 29
 
11.6%
휴양콘도미니엄업 6
 
2.4%
소형호텔업 5
 
2.0%
가족호텔업 1
 
0.4%

Unnamed: 64
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing251
Missing (%)100.0%
Memory size2.3 KiB

Sample

번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)문화체육업종명문화사업자구분명지역구분명총층수주변환경명제작취급품목내용보험기관명건물용도명지상층수지하층수객실수건축연면적영문상호명영문상호주소선박총톤수선박척수선박제원무대면적좌석수기념품종류회의실별동시수용인원시설면적놀이기구수내역놀이시설수방송시설유무발전시설유무의무실유무안내소유무기획여행보험시작일자기획여행보험종료일자자본금보험시작일자보험종료일자부대시설내역시설규모관광숙박업상세명Unnamed: 64
01관광숙박업03_11_01_P3380000CDFI226003201500000420150630201808274취소/말소/만료/정지/중지31등록취소<NA><NA><NA><NA><NA><NA>613828부산광역시 수영구 민락동 178-13번지부산광역시 수영구 광안해변로 249, 7층 (민락동, 홍윤빌딩)48284지니게스트하우스220180827102326I2018-08-31 23:59:59.0<NA>393213.33657186059.23575관광숙박업<NA>일반상업지역10기타<NA><NA>숙박시설1017<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>208.14<NA><NA><NA><NA><NA><NA><NA><NA>150000000<NA><NA><NA>208호스텔업<NA>
12관광숙박업03_11_01_P3300000CDFI226003198700000119870307201902204취소/말소/만료/정지/중지31등록취소<NA><NA><NA><NA>051-552-9511<NA>607833부산광역시 동래구 온천동 210-82번지부산광역시 동래구 금강로 110 (온천동)<NA>동방관광호텔20190311142043U2019-03-13 02:40:00.0<NA>389291.717213192996.253436관광숙박업관광사업<NA>10<NA><NA><NA>숙박시설82403735<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23관광숙박업03_11_01_P3330000CDFI226003201400000420140731<NA>3폐업3폐업20190522<NA><NA><NA><NA><NA>612040부산광역시 해운대구 송정동 312-6번지 프롬 게스트하우스 3,4동부산광역시 해운대구 송정광어골로 15-1, 3,4층 (송정동, 프롬 게스트하우스)48073프롬 게스트하우스20190522162143U2019-05-24 02:40:00.0<NA>400211.697272188918.077386관광숙박업<NA>준주거지역5기타<NA><NA>근린생활시설<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>656.26<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>656호스텔업<NA>
34관광숙박업03_11_01_P3330000CDFI226003201400000220140623<NA>3폐업3폐업20200323<NA><NA><NA>051-913-0804<NA>612889부산광역시 해운대구 우동 1510번지 센텀드림월드부산광역시 해운대구 센텀2로 25, 14층 (우동, 센텀드림월드)48060스테이7 센텀 비지니스 호스텔20200323154223U2020-03-25 02:40:00.0<NA>394259.857138187389.720344관광숙박업<NA>일반상업지역14유흥업소밀집지역<NA><NA><NA><NA><NA>23<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>797.27<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>797호스텔업<NA>
45관광숙박업03_11_01_P3330000CDFI226003201700000720170607<NA>3폐업3폐업20190701<NA><NA><NA><NA><NA><NA>부산광역시 해운대구 우동 648-9번지부산광역시 해운대구 해운대해변로209번가길 25 (우동, 노비오스모텔)48093ARK BLUE HOTEL20191209172321U2019-12-11 02:40:00.0<NA>396428.114069186620.794349관광숙박업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>270.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>270호스텔업<NA>
56관광숙박업03_11_01_P3330000CDFI226003201700000620170417<NA>3폐업3폐업20191029<NA><NA><NA>051 731 2120<NA><NA>부산광역시 해운대구 우동 626-14번지부산광역시 해운대구 해운대로570번길 55 (우동, 스카이비치)48094문동이네20191029094343U2019-10-31 02:40:00.0<NA>396749.296704186683.351832관광숙박업<NA>일반상업지역6<NA><NA><NA>근린생활시설<NA><NA>8334<NA><NA><NA><NA><NA><NA><NA><NA><NA>334.0<NA><NA><NA><NA><NA><NA><NA><NA>200000000<NA><NA><NA>334호스텔업<NA>
67관광숙박업03_11_01_P3330000CDFI226003201500000920151210<NA>3폐업3폐업20170921<NA><NA><NA>051 744 4514<NA><NA>부산광역시 해운대구 중동부산광역시 해운대구 해운대해변로 315, 11~14층 (중동, 메리얼타워)48095메리얼 관광호텔20170921163840I2018-08-31 23:59:59.0<NA>397148.05247186910.164106관광숙박업<NA>일반상업지역17학교정화(상대)<NA><NA>숙박시설143<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>400000000<NA><NA><NA><NA>관광호텔업<NA>
78관광숙박업03_11_01_P3330000CDFI226003201500000620150827<NA>3폐업3폐업20170913<NA><NA><NA><NA><NA><NA>부산광역시 해운대구 중동부산광역시 해운대구 달맞이길 193, 2층 (중동)48115썬앤문 게스트하우스20180628131922I2018-08-31 23:59:59.0<NA>398791.041408186530.146494관광숙박업<NA>일반주거지역<NA>주택가주변<NA><NA>숙박시설2<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>호스텔업<NA>
89관광숙박업03_11_01_P3330000CDFI226003201500000220150522<NA>3폐업3폐업20190702<NA><NA><NA><NA><NA>612040부산광역시 해운대구 송정동 288-4번지부산광역시 해운대구 송정해변로 10 (송정동)48072플랫비(FLAT B)20190702161253U2019-07-04 02:40:00.0<NA>400768.055657189089.148394관광숙박업<NA>일반상업지역5<NA><NA><NA>숙박시설<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>793.23<NA><NA><NA><NA><NA><NA><NA><NA>70000000<NA><NA><NA>793호스텔업<NA>
910관광숙박업03_11_01_P3330000CDFI226003201400000520140814<NA>3폐업3폐업20170313<NA><NA><NA><NA><NA>612821부산광역시 해운대구 우동 646-10번지 해운대비지니스호텔 GT부산광역시 해운대구 해운대해변로221번길 19 (우동, 해운대비지니스호텔 GT)48093(주)아이액츠지티호텔[해운대비지니스호텔GT]20170313162154I2018-08-31 23:59:59.0<NA>396389.836404186703.403767관광숙박업<NA>일반상업지역9유흥업소밀집지역<NA><NA><NA>90<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>관광호텔업<NA>
번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)문화체육업종명문화사업자구분명지역구분명총층수주변환경명제작취급품목내용보험기관명건물용도명지상층수지하층수객실수건축연면적영문상호명영문상호주소선박총톤수선박척수선박제원무대면적좌석수기념품종류회의실별동시수용인원시설면적놀이기구수내역놀이시설수방송시설유무발전시설유무의무실유무안내소유무기획여행보험시작일자기획여행보험종료일자자본금보험시작일자보험종료일자부대시설내역시설규모관광숙박업상세명Unnamed: 64
241242관광숙박업03_11_01_P3250000CDFI226003201600000120161229<NA>1영업/정상13영업중<NA><NA><NA><NA>051-462-8008<NA><NA>부산광역시 중구 중앙동4가 52-8번지부산광역시 중구 해관로 79-1 (중앙동4가, 반달호텔)48928반달호텔20191205174136U2019-12-07 02:40:00.0<NA>385488.794607180448.886029관광숙박업<NA>일반상업지역<NA><NA><NA>삼성화재<NA><NA><NA>28<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>994.0<NA><NA><NA><NA><NA><NA><NA><NA>4800000000<NA><NA><NA>994소형호텔업<NA>
242243관광숙박업03_11_01_P3250000CDFI226003197400000119740613<NA>1영업/정상13영업중<NA><NA><NA><NA>051-466-9101<NA>600811부산광역시 중구 영주동 742-13부산광역시 중구 중구로 151 (영주동)48912(주)코모도호텔20201031171251U2020-11-03 02:40:00.0<NA>385475.54305180776.20099관광숙박업관광사업<NA>18<NA><NA><NA>숙박시설153312<NA>COMMODORET0URIST ACCOMMODATION(TOURIST HOTEL)<NA><NA><NA><NA><NA><NA><NA>27553.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>27553관광호텔업<NA>
243244관광숙박업03_11_01_P3250000CDFI226003201800000120180109<NA>1영업/정상13영업중<NA><NA><NA><NA>051-464-8532<NA><NA>부산광역시 중구 대청동2가 7-1부산광역시 중구 대청로 107 (대청동2가)48933넘버25호텔 대청점20201226162009U2020-12-29 02:40:00.0<NA>385176.391701180113.825158관광숙박업<NA><NA>8<NA><NA><NA><NA>6260<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>4277.42<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>4277관광호텔업<NA>
244245관광숙박업03_11_01_P3250000CDFI226003201700000220170814<NA>1영업/정상13영업중<NA><NA><NA><NA>051-795-7700<NA><NA>부산광역시 중구 남포동5가 56-1번지부산광역시 중구 구덕로 53 (남포동5가)48983스탠포드 인 부산20200120134434U2020-01-22 02:40:00.0<NA>385027.185256179533.7497관광숙박업<NA>일반상업지역17<NA><NA><NA><NA>152132<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>4437.88<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>4438관광호텔업<NA>
245246관광숙박업03_11_01_P3250000CDFI226003201700000120170324<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>부산광역시 중구 영주동 20-10부산광역시 중구 초량중로 8-1, 2층 (영주동)48911첵앤아웃호스텔20201226162114U2020-12-29 02:40:00.0<NA>385580.190351181198.150721관광숙박업<NA>상업지역2<NA><NA>동부화재 재난배상책임보험숙박시설2<NA>2<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>60.65<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>61호스텔업<NA>
246247관광숙박업03_11_01_P3250000CDFI226003200800000120080416<NA>1영업/정상13영업중<NA><NA><NA><NA>051-442-1045<NA><NA>부산광역시 중구 대창동1가 22-4부산광역시 중구 중앙대로 125 (대창동1가)48924토요코인부산역Ⅱ20201226161909U2020-12-29 02:40:00.0<NA>385610.773395180783.859472관광숙박업관광사업<NA>25<NA><NA><NA><NA>232491<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>12168.64<NA><NA><NA><NA><NA><NA><NA><NA>35300000000<NA><NA><NA>12169관광호텔업<NA>
247248관광숙박업03_11_01_P3250000CDFI226003198900000119890111<NA>1영업/정상13영업중<NA><NA><NA><NA>051-253-0371<NA>600045부산광역시 중구 남포동5가 80-1부산광역시 중구 자갈치로47번길 3-1 (남포동5가)48983호텔노아20201226161849U2020-12-29 02:40:00.0<NA>384966.283935179482.336623관광숙박업관광사업<NA>10<NA><NA><NA><NA>9151<NA>CORP. KYUNG WON, HOTEL NOAHTOURIST ACCOMMODATION(TOURIST HOTEL)<NA><NA><NA><NA><NA><NA><NA>3186.56<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>3187관광호텔업<NA>
248249관광숙박업03_11_01_P3250000CDFI226003197800000119780515<NA>1영업/정상13영업중<NA><NA><NA><NA>051-250-6002<NA><NA>부산광역시 중구 동광동3가 20부산광역시 중구 백산길 20 (동광동3가, 타워호텔)48951타워힐관광호텔20201226161825U2020-12-29 02:40:00.0<NA>385421.890633179905.806117관광숙박업관광사업<NA>7<NA><NA><NA><NA>61116<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>5658.34<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>5658관광호텔업<NA>
249250관광숙박업03_11_01_P3250000CDFI226003197400000219740907<NA>1영업/정상13영업중<NA><NA><NA><NA>051-241-4301<NA>600022부산광역시 중구 동광동2가 12-1부산광역시 중구 광복로97번길 23 (동광동2가)48951(주)부산관광호텔20201226162040U2020-12-29 02:40:00.0<NA>385447.404485179824.590338관광숙박업관광사업<NA>14<NA><NA><NA><NA>14<NA>273<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>16395.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>16395관광호텔업<NA>
250251관광숙박업03_11_01_P3250000CDFI226003201900000120191112<NA>1영업/정상13영업중<NA><NA><NA><NA>051-246-3657<NA><NA>부산광역시 중구 중앙동1가 21-12번지부산광역시 중구 중앙대로41번길 3-1 (중앙동1가)48957수이호스텔20191206093553U2019-12-08 02:40:00.0<NA>385574.520466179902.860301관광숙박업<NA>일반상업지역5<NA><NA>현대해상숙박시설5<NA>7530<NA><NA><NA><NA><NA><NA><NA><NA><NA>530.39<NA><NA><NA><NA><NA><NA><NA><NA>1500000000<NA><NA><NA>530호스텔업<NA>