Overview

Dataset statistics

Number of variables60
Number of observations5058
Missing cells134335
Missing cells (%)44.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 MiB
Average record size in memory517.0 B

Variable types

Numeric12
Text10
DateTime6
Categorical17
Unsupported15

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),문화체육업종명,문화사업자구분명,지역구분명,총층수,주변환경명,제작취급품목내용,보험기관명,건물용도명,지상층수,지하층수,객실수,건축연면적,영문상호명,영문상호주소,선박총톤수,선박척수,선박제원,무대면적,좌석수,기념품종류,회의실별동시수용인원,시설면적,놀이기구수내역,놀이시설수,방송시설유무,발전시설유무,의무실유무,안내소유무,기획여행보험시작일자,기획여행보험종료일자,자본금,보험시작일자,보험종료일자,부대시설내역,시설규모
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-16045/S/1/datasetView.do

Alerts

상세영업상태코드 is highly imbalanced (53.0%)Imbalance
상세영업상태명 is highly imbalanced (53.0%)Imbalance
지역구분명 is highly imbalanced (59.6%)Imbalance
주변환경명 is highly imbalanced (65.5%)Imbalance
보험시작일자 is highly imbalanced (99.4%)Imbalance
보험종료일자 is highly imbalanced (99.4%)Imbalance
인허가취소일자 has 5024 (99.3%) missing valuesMissing
폐업일자 has 3042 (60.1%) missing valuesMissing
휴업시작일자 has 5019 (99.2%) missing valuesMissing
휴업종료일자 has 5019 (99.2%) missing valuesMissing
재개업일자 has 5058 (100.0%) missing valuesMissing
전화번호 has 4648 (91.9%) missing valuesMissing
소재지면적 has 5058 (100.0%) missing valuesMissing
소재지우편번호 has 4368 (86.4%) missing valuesMissing
도로명우편번호 has 828 (16.4%) missing valuesMissing
업태구분명 has 5058 (100.0%) missing valuesMissing
문화사업자구분명 has 5058 (100.0%) missing valuesMissing
총층수 has 2596 (51.3%) missing valuesMissing
제작취급품목내용 has 5058 (100.0%) missing valuesMissing
보험기관명 has 3863 (76.4%) missing valuesMissing
지상층수 has 2617 (51.7%) missing valuesMissing
지하층수 has 3079 (60.9%) missing valuesMissing
객실수 has 2354 (46.5%) missing valuesMissing
건축연면적 has 3312 (65.5%) missing valuesMissing
영문상호명 has 3403 (67.3%) missing valuesMissing
영문상호주소 has 3426 (67.7%) missing valuesMissing
선박제원 has 5058 (100.0%) missing valuesMissing
기념품종류 has 5058 (100.0%) missing valuesMissing
시설면적 has 1353 (26.7%) missing valuesMissing
놀이기구수내역 has 5058 (100.0%) missing valuesMissing
방송시설유무 has 5058 (100.0%) missing valuesMissing
발전시설유무 has 5058 (100.0%) missing valuesMissing
의무실유무 has 5058 (100.0%) missing valuesMissing
안내소유무 has 5058 (100.0%) missing valuesMissing
기획여행보험시작일자 has 5058 (100.0%) missing valuesMissing
기획여행보험종료일자 has 5058 (100.0%) missing valuesMissing
자본금 has 3098 (61.2%) missing valuesMissing
부대시설내역 has 5058 (100.0%) missing valuesMissing
시설규모 has 1353 (26.7%) missing valuesMissing
건축연면적 is highly skewed (γ1 = 28.09935566)Skewed
시설면적 is highly skewed (γ1 = 42.80609009)Skewed
시설규모 is highly skewed (γ1 = 42.80608084)Skewed
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
문화사업자구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
제작취급품목내용 is an unsupported type, check if it needs cleaning or further analysisUnsupported
선박제원 is an unsupported type, check if it needs cleaning or further analysisUnsupported
기념품종류 is an unsupported type, check if it needs cleaning or further analysisUnsupported
놀이기구수내역 is an unsupported type, check if it needs cleaning or further analysisUnsupported
방송시설유무 is an unsupported type, check if it needs cleaning or further analysisUnsupported
발전시설유무 is an unsupported type, check if it needs cleaning or further analysisUnsupported
의무실유무 is an unsupported type, check if it needs cleaning or further analysisUnsupported
안내소유무 is an unsupported type, check if it needs cleaning or further analysisUnsupported
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
총층수 has 1125 (22.2%) zerosZeros
지상층수 has 1205 (23.8%) zerosZeros
지하층수 has 1595 (31.5%) zerosZeros
객실수 has 656 (13.0%) zerosZeros
건축연면적 has 1592 (31.5%) zerosZeros
시설면적 has 140 (2.8%) zerosZeros
자본금 has 1356 (26.8%) zerosZeros
시설규모 has 140 (2.8%) zerosZeros

Reproduction

Analysis started2024-05-10 23:52:24.062472
Analysis finished2024-05-10 23:52:28.742782
Duration4.68 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Real number (ℝ)

Distinct138
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3456756.7
Minimum3000000
Maximum5710000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size44.6 KiB
2024-05-10T23:52:29.014105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3010000
Q13120000
median3130000
Q33490000
95-th percentile4836000
Maximum5710000
Range2710000
Interquartile range (IQR)370000

Descriptive statistics

Standard deviation632189.71
Coefficient of variation (CV)0.18288522
Kurtosis1.8050356
Mean3456756.7
Median Absolute Deviation (MAD)110000
Skewness1.71658
Sum1.7484276 × 1010
Variance3.9966382 × 1011
MonotonicityNot monotonic
2024-05-10T23:52:29.563848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3130000 1215
24.0%
3020000 468
 
9.3%
3010000 297
 
5.9%
4640000 229
 
4.5%
3000000 191
 
3.8%
3220000 185
 
3.7%
3120000 154
 
3.0%
3230000 131
 
2.6%
4201000 113
 
2.2%
3200000 97
 
1.9%
Other values (128) 1978
39.1%
ValueCountFrequency (%)
3000000 191
3.8%
3010000 297
5.9%
3020000 468
9.3%
3030000 42
 
0.8%
3040000 57
 
1.1%
3050000 56
 
1.1%
3060000 11
 
0.2%
3070000 65
 
1.3%
3080000 8
 
0.2%
3090000 11
 
0.2%
ValueCountFrequency (%)
5710000 9
 
0.2%
5700000 1
 
< 0.1%
5690000 5
 
0.1%
5680000 1
 
< 0.1%
5670000 12
0.2%
5590000 2
 
< 0.1%
5580000 1
 
< 0.1%
5530000 4
 
0.1%
5380000 2
 
< 0.1%
5370000 24
0.5%
Distinct1246
Distinct (%)24.6%
Missing0
Missing (%)0.0%
Memory size39.6 KiB
2024-05-10T23:52:30.285444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters101160
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

Unique704 ?
Unique (%)13.9%

Sample

1st rowCDFI2262212023000101
2nd rowCDFI2262212023000103
3rd rowCDFI2262212023000102
4th rowCDFI2262212023000096
5th rowCDFI2262212023000007
ValueCountFrequency (%)
cdfi2262212023000001 84
 
1.7%
cdfi2262212019000001 75
 
1.5%
cdfi2262212018000001 75
 
1.5%
cdfi2262212022000001 73
 
1.4%
cdfi2262212017000001 69
 
1.4%
cdfi2262212016000001 68
 
1.3%
cdfi2262212015000001 68
 
1.3%
cdfi2262212020000001 60
 
1.2%
cdfi2262212021000001 58
 
1.1%
cdfi2262212014000001 58
 
1.1%
Other values (1236) 4370
86.4%
2024-05-10T23:52:31.566478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 28996
28.7%
0 28512
28.2%
1 10438
 
10.3%
6 6056
 
6.0%
C 5058
 
5.0%
D 5058
 
5.0%
F 5058
 
5.0%
I 5058
 
5.0%
3 1893
 
1.9%
4 1389
 
1.4%
Other values (4) 3644
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 80928
80.0%
Uppercase Letter 20232
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 28996
35.8%
0 28512
35.2%
1 10438
 
12.9%
6 6056
 
7.5%
3 1893
 
2.3%
4 1389
 
1.7%
5 1050
 
1.3%
7 892
 
1.1%
9 891
 
1.1%
8 811
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
C 5058
25.0%
D 5058
25.0%
F 5058
25.0%
I 5058
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 80928
80.0%
Latin 20232
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 28996
35.8%
0 28512
35.2%
1 10438
 
12.9%
6 6056
 
7.5%
3 1893
 
2.3%
4 1389
 
1.7%
5 1050
 
1.3%
7 892
 
1.1%
9 891
 
1.1%
8 811
 
1.0%
Latin
ValueCountFrequency (%)
C 5058
25.0%
D 5058
25.0%
F 5058
25.0%
I 5058
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 101160
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 28996
28.7%
0 28512
28.2%
1 10438
 
10.3%
6 6056
 
6.0%
C 5058
 
5.0%
D 5058
 
5.0%
F 5058
 
5.0%
I 5058
 
5.0%
3 1893
 
1.9%
4 1389
 
1.4%
Other values (4) 3644
 
3.6%
Distinct2206
Distinct (%)43.6%
Missing0
Missing (%)0.0%
Memory size39.6 KiB
Minimum2012-01-27 00:00:00
Maximum2024-05-09 00:00:00
2024-05-10T23:52:32.145660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:52:32.610447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Real number (ℝ)

MISSING 

Distinct19
Distinct (%)55.9%
Missing5024
Missing (%)99.3%
Infinite0
Infinite (%)0.0%
Mean20195013
Minimum20120821
Maximum20221014
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size44.6 KiB
2024-05-10T23:52:33.105184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20120821
5-th percentile20160286
Q120191215
median20200629
Q320200688
95-th percentile20220453
Maximum20221014
Range100193
Interquartile range (IQR)9473

Descriptive statistics

Standard deviation22293.849
Coefficient of variation (CV)0.0011039285
Kurtosis2.5091195
Mean20195013
Median Absolute Deviation (MAD)9408.5
Skewness-1.4407143
Sum6.8663043 × 108
Variance4.9701572 × 108
MonotonicityNot monotonic
2024-05-10T23:52:33.503419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
20200629 11
 
0.2%
20160322 3
 
0.1%
20210628 2
 
< 0.1%
20220113 2
 
< 0.1%
20200427 2
 
< 0.1%
20191210 1
 
< 0.1%
20120821 1
 
< 0.1%
20160219 1
 
< 0.1%
20170704 1
 
< 0.1%
20220705 1
 
< 0.1%
Other values (9) 9
 
0.2%
(Missing) 5024
99.3%
ValueCountFrequency (%)
20120821 1
 
< 0.1%
20160219 1
 
< 0.1%
20160322 3
0.1%
20170704 1
 
< 0.1%
20170818 1
 
< 0.1%
20191101 1
 
< 0.1%
20191210 1
 
< 0.1%
20191231 1
 
< 0.1%
20200427 2
< 0.1%
20200615 1
 
< 0.1%
ValueCountFrequency (%)
20221014 1
 
< 0.1%
20220705 1
 
< 0.1%
20220318 1
 
< 0.1%
20220127 1
 
< 0.1%
20220113 2
 
< 0.1%
20210628 2
 
< 0.1%
20200708 1
 
< 0.1%
20200629 11
0.2%
20200618 1
 
< 0.1%
20200615 1
 
< 0.1%
Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size39.6 KiB
1
2965 
3
2017 
2
 
39
4
 
37

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 2965
58.6%
3 2017
39.9%
2 39
 
0.8%
4 37
 
0.7%

Length

2024-05-10T23:52:33.908714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:52:34.366835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 2965
58.6%
3 2017
39.9%
2 39
 
0.8%
4 37
 
0.7%

영업상태명
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size39.6 KiB
영업/정상
2965 
폐업
2017 
휴업
 
39
취소/말소/만료/정지/중지
 
37

Length

Max length14
Median length5
Mean length3.846382
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 2965
58.6%
폐업 2017
39.9%
휴업 39
 
0.8%
취소/말소/만료/정지/중지 37
 
0.7%

Length

2024-05-10T23:52:34.797921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:52:35.275920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 2965
58.6%
폐업 2017
39.9%
휴업 39
 
0.8%
취소/말소/만료/정지/중지 37
 
0.7%

상세영업상태코드
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size39.6 KiB
13
2965 
3
2017 
2
 
39
31
 
31
33
 
6

Length

Max length2
Median length2
Mean length1.5935152
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
13 2965
58.6%
3 2017
39.9%
2 39
 
0.8%
31 31
 
0.6%
33 6
 
0.1%

Length

2024-05-10T23:52:35.798305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:52:36.317674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13 2965
58.6%
3 2017
39.9%
2 39
 
0.8%
31 31
 
0.6%
33 6
 
0.1%

상세영업상태명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size39.6 KiB
영업중
2965 
폐업
2017 
휴업
 
39
등록취소
 
31
지정취소
 
6

Length

Max length4
Median length3
Mean length2.6008304
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 2965
58.6%
폐업 2017
39.9%
휴업 39
 
0.8%
등록취소 31
 
0.6%
지정취소 6
 
0.1%

Length

2024-05-10T23:52:36.948688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:52:37.479492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 2965
58.6%
폐업 2017
39.9%
휴업 39
 
0.8%
등록취소 31
 
0.6%
지정취소 6
 
0.1%

폐업일자
Date

MISSING 

Distinct1278
Distinct (%)63.4%
Missing3042
Missing (%)60.1%
Memory size39.6 KiB
Minimum2012-06-18 00:00:00
Maximum2024-04-30 00:00:00
2024-05-10T23:52:38.014872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:52:38.741435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Date

MISSING 

Distinct38
Distinct (%)97.4%
Missing5019
Missing (%)99.2%
Memory size39.6 KiB
Minimum2016-07-22 00:00:00
Maximum2024-01-12 00:00:00
2024-05-10T23:52:39.286908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:52:39.681375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)

휴업종료일자
Date

MISSING 

Distinct37
Distinct (%)94.9%
Missing5019
Missing (%)99.2%
Memory size39.6 KiB
Minimum2017-07-21 00:00:00
Maximum2027-12-14 00:00:00
2024-05-10T23:52:40.161344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:52:40.719734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5058
Missing (%)100.0%
Memory size44.6 KiB

전화번호
Text

MISSING 

Distinct399
Distinct (%)97.3%
Missing4648
Missing (%)91.9%
Memory size39.6 KiB
2024-05-10T23:52:41.730019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length10.787805
Min length7

Characters and Unicode

Total characters4423
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

Unique390 ?
Unique (%)95.1%

Sample

1st row070-7792-2121
2nd row07074311565
3rd row02-797-2331
4th row02-445-6443
5th row02-511-7422
ValueCountFrequency (%)
051-207-1212 4
 
0.9%
02 3
 
0.7%
033 3
 
0.7%
566-2840 2
 
0.5%
031-406-0553 2
 
0.5%
02-318-2323 2
 
0.5%
02-774-0351 2
 
0.5%
070-7516-5565 2
 
0.5%
02-745-3930 2
 
0.5%
02-563-7941 2
 
0.5%
Other values (399) 400
94.3%
2024-05-10T23:52:43.218028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 649
14.7%
- 629
14.2%
2 503
11.4%
7 428
9.7%
3 355
8.0%
5 343
7.8%
1 338
7.6%
8 330
7.5%
4 309
7.0%
6 279
6.3%
Other values (4) 260
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3775
85.3%
Dash Punctuation 629
 
14.2%
Space Separator 16
 
0.4%
Close Punctuation 2
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 649
17.2%
2 503
13.3%
7 428
11.3%
3 355
9.4%
5 343
9.1%
1 338
9.0%
8 330
8.7%
4 309
8.2%
6 279
7.4%
9 241
 
6.4%
Dash Punctuation
ValueCountFrequency (%)
- 629
100.0%
Space Separator
ValueCountFrequency (%)
16
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4423
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 649
14.7%
- 629
14.2%
2 503
11.4%
7 428
9.7%
3 355
8.0%
5 343
7.8%
1 338
7.6%
8 330
7.5%
4 309
7.0%
6 279
6.3%
Other values (4) 260
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4423
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 649
14.7%
- 629
14.2%
2 503
11.4%
7 428
9.7%
3 355
8.0%
5 343
7.8%
1 338
7.6%
8 330
7.5%
4 309
7.0%
6 279
6.3%
Other values (4) 260
5.9%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5058
Missing (%)100.0%
Memory size44.6 KiB

소재지우편번호
Text

MISSING 

Distinct464
Distinct (%)67.2%
Missing4368
Missing (%)86.4%
Memory size39.6 KiB
2024-05-10T23:52:44.365620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters4830
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

Unique374 ?
Unique (%)54.2%

Sample

1st row100-876
2nd row121-818
3rd row135-811
4th row120-170
5th row100-888
ValueCountFrequency (%)
121-836 19
 
2.8%
121-869 15
 
2.2%
100-042 13
 
1.9%
121-818 12
 
1.7%
121-865 11
 
1.6%
121-816 9
 
1.3%
560-070 8
 
1.2%
650-140 8
 
1.2%
121-895 7
 
1.0%
100-876 7
 
1.0%
Other values (454) 581
84.2%
2024-05-10T23:52:46.176375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 903
18.7%
0 762
15.8%
- 690
14.3%
8 458
9.5%
2 440
9.1%
3 316
 
6.5%
5 301
 
6.2%
4 276
 
5.7%
7 267
 
5.5%
6 263
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4140
85.7%
Dash Punctuation 690
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 903
21.8%
0 762
18.4%
8 458
11.1%
2 440
10.6%
3 316
 
7.6%
5 301
 
7.3%
4 276
 
6.7%
7 267
 
6.4%
6 263
 
6.4%
9 154
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 690
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4830
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 903
18.7%
0 762
15.8%
- 690
14.3%
8 458
9.5%
2 440
9.1%
3 316
 
6.5%
5 301
 
6.2%
4 276
 
5.7%
7 267
 
5.5%
6 263
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4830
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 903
18.7%
0 762
15.8%
- 690
14.3%
8 458
9.5%
2 440
9.1%
3 316
 
6.5%
5 301
 
6.2%
4 276
 
5.7%
7 267
 
5.5%
6 263
 
5.4%
Distinct4555
Distinct (%)90.1%
Missing0
Missing (%)0.0%
Memory size39.6 KiB
2024-05-10T23:52:47.319584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length44
Mean length22.916172
Min length11

Characters and Unicode

Total characters115910
Distinct characters498
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4212 ?
Unique (%)83.3%

Sample

1st row서울특별시 마포구 망원동 479-28
2nd row서울특별시 마포구 서교동 330-32
3rd row서울특별시 마포구 서교동 330-32
4th row서울특별시 마포구 망원동 435-1
5th row서울특별시 성북구 동소문동4가 15
ValueCountFrequency (%)
서울특별시 3339
 
14.3%
마포구 1215
 
5.2%
용산구 468
 
2.0%
중구 393
 
1.7%
연남동 384
 
1.6%
부산광역시 335
 
1.4%
서교동 315
 
1.3%
전라북도 283
 
1.2%
전주시 229
 
1.0%
동교동 221
 
0.9%
Other values (6230) 16229
69.3%
2024-05-10T23:52:48.865820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18353
 
15.8%
6054
 
5.2%
1 5365
 
4.6%
5096
 
4.4%
4568
 
3.9%
4287
 
3.7%
- 4271
 
3.7%
2 3811
 
3.3%
3559
 
3.1%
3558
 
3.1%
Other values (488) 56988
49.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 66915
57.7%
Decimal Number 26035
 
22.5%
Space Separator 18353
 
15.8%
Dash Punctuation 4271
 
3.7%
Uppercase Letter 159
 
0.1%
Other Punctuation 59
 
0.1%
Math Symbol 49
 
< 0.1%
Lowercase Letter 36
 
< 0.1%
Open Punctuation 15
 
< 0.1%
Close Punctuation 15
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6054
 
9.0%
5096
 
7.6%
4568
 
6.8%
4287
 
6.4%
3559
 
5.3%
3558
 
5.3%
3377
 
5.0%
1726
 
2.6%
1553
 
2.3%
1552
 
2.3%
Other values (431) 31585
47.2%
Uppercase Letter
ValueCountFrequency (%)
B 40
25.2%
A 13
 
8.2%
I 11
 
6.9%
S 11
 
6.9%
C 10
 
6.3%
L 10
 
6.3%
K 9
 
5.7%
E 6
 
3.8%
V 5
 
3.1%
G 5
 
3.1%
Other values (13) 39
24.5%
Lowercase Letter
ValueCountFrequency (%)
e 6
16.7%
i 5
13.9%
d 4
11.1%
s 4
11.1%
o 4
11.1%
u 3
8.3%
t 2
 
5.6%
n 2
 
5.6%
g 1
 
2.8%
l 1
 
2.8%
Other values (4) 4
11.1%
Decimal Number
ValueCountFrequency (%)
1 5365
20.6%
2 3811
14.6%
3 3122
12.0%
0 2644
10.2%
4 2436
9.4%
5 2061
 
7.9%
6 1897
 
7.3%
7 1695
 
6.5%
8 1528
 
5.9%
9 1476
 
5.7%
Other Punctuation
ValueCountFrequency (%)
, 51
86.4%
. 5
 
8.5%
@ 3
 
5.1%
Letter Number
ValueCountFrequency (%)
2
66.7%
1
33.3%
Space Separator
ValueCountFrequency (%)
18353
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4271
100.0%
Math Symbol
ValueCountFrequency (%)
~ 49
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 66913
57.7%
Common 48797
42.1%
Latin 198
 
0.2%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6054
 
9.0%
5096
 
7.6%
4568
 
6.8%
4287
 
6.4%
3559
 
5.3%
3558
 
5.3%
3377
 
5.0%
1726
 
2.6%
1553
 
2.3%
1552
 
2.3%
Other values (430) 31583
47.2%
Latin
ValueCountFrequency (%)
B 40
20.2%
A 13
 
6.6%
I 11
 
5.6%
S 11
 
5.6%
C 10
 
5.1%
L 10
 
5.1%
K 9
 
4.5%
e 6
 
3.0%
E 6
 
3.0%
V 5
 
2.5%
Other values (29) 77
38.9%
Common
ValueCountFrequency (%)
18353
37.6%
1 5365
 
11.0%
- 4271
 
8.8%
2 3811
 
7.8%
3 3122
 
6.4%
0 2644
 
5.4%
4 2436
 
5.0%
5 2061
 
4.2%
6 1897
 
3.9%
7 1695
 
3.5%
Other values (8) 3142
 
6.4%
Han
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 66913
57.7%
ASCII 48992
42.3%
Number Forms 3
 
< 0.1%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18353
37.5%
1 5365
 
11.0%
- 4271
 
8.7%
2 3811
 
7.8%
3 3122
 
6.4%
0 2644
 
5.4%
4 2436
 
5.0%
5 2061
 
4.2%
6 1897
 
3.9%
7 1695
 
3.5%
Other values (45) 3337
 
6.8%
Hangul
ValueCountFrequency (%)
6054
 
9.0%
5096
 
7.6%
4568
 
6.8%
4287
 
6.4%
3559
 
5.3%
3558
 
5.3%
3377
 
5.0%
1726
 
2.6%
1553
 
2.3%
1552
 
2.3%
Other values (430) 31583
47.2%
Number Forms
ValueCountFrequency (%)
2
66.7%
1
33.3%
CJK
ValueCountFrequency (%)
2
100.0%
Distinct4837
Distinct (%)95.7%
Missing5
Missing (%)0.1%
Memory size39.6 KiB
2024-05-10T23:52:49.929910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length54
Mean length32.821492
Min length19

Characters and Unicode

Total characters165847
Distinct characters602
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4636 ?
Unique (%)91.7%

Sample

1st row서울특별시 마포구 망원로7길 44, 3층 (망원동)
2nd row서울특별시 마포구 와우산로29길 48-21, 301호 (서교동)
3rd row서울특별시 마포구 와우산로29길 48-21, 302호 (서교동)
4th row서울특별시 마포구 방울내로 67, 4층 (망원동)
5th row서울특별시 성북구 동소문로13가길 71-1 (동소문동4가)
ValueCountFrequency (%)
서울특별시 3339
 
10.5%
마포구 1215
 
3.8%
2층 514
 
1.6%
용산구 468
 
1.5%
중구 390
 
1.2%
연남동 384
 
1.2%
1층 338
 
1.1%
부산광역시 335
 
1.1%
서교동 315
 
1.0%
3층 285
 
0.9%
Other values (6633) 24193
76.1%
2024-05-10T23:52:51.647212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
26724
 
16.1%
1 7100
 
4.3%
6871
 
4.1%
2 5456
 
3.3%
5131
 
3.1%
) 5079
 
3.1%
( 5079
 
3.1%
, 4694
 
2.8%
4684
 
2.8%
4652
 
2.8%
Other values (592) 90377
54.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 91104
54.9%
Decimal Number 30421
 
18.3%
Space Separator 26724
 
16.1%
Close Punctuation 5079
 
3.1%
Open Punctuation 5079
 
3.1%
Other Punctuation 4801
 
2.9%
Dash Punctuation 2167
 
1.3%
Uppercase Letter 301
 
0.2%
Math Symbol 101
 
0.1%
Lowercase Letter 65
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6871
 
7.5%
5131
 
5.6%
4684
 
5.1%
4652
 
5.1%
4503
 
4.9%
4024
 
4.4%
3562
 
3.9%
3558
 
3.9%
3427
 
3.8%
2215
 
2.4%
Other values (529) 48477
53.2%
Uppercase Letter
ValueCountFrequency (%)
B 133
44.2%
A 38
 
12.6%
I 14
 
4.7%
C 12
 
4.0%
L 11
 
3.7%
S 11
 
3.7%
K 10
 
3.3%
M 7
 
2.3%
H 7
 
2.3%
D 6
 
2.0%
Other values (13) 52
 
17.3%
Lowercase Letter
ValueCountFrequency (%)
e 12
18.5%
i 7
10.8%
s 6
9.2%
o 6
9.2%
d 6
9.2%
t 5
7.7%
u 4
 
6.2%
h 4
 
6.2%
n 3
 
4.6%
b 3
 
4.6%
Other values (7) 9
13.8%
Decimal Number
ValueCountFrequency (%)
1 7100
23.3%
2 5456
17.9%
3 3680
12.1%
0 3661
12.0%
4 2516
 
8.3%
5 2002
 
6.6%
6 1790
 
5.9%
7 1537
 
5.1%
8 1420
 
4.7%
9 1259
 
4.1%
Other Punctuation
ValueCountFrequency (%)
, 4694
97.8%
: 98
 
2.0%
. 6
 
0.1%
? 1
 
< 0.1%
@ 1
 
< 0.1%
# 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
4
80.0%
1
 
20.0%
Space Separator
ValueCountFrequency (%)
26724
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5079
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5079
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2167
100.0%
Math Symbol
ValueCountFrequency (%)
~ 101
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 91102
54.9%
Common 74372
44.8%
Latin 371
 
0.2%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6871
 
7.5%
5131
 
5.6%
4684
 
5.1%
4652
 
5.1%
4503
 
4.9%
4024
 
4.4%
3562
 
3.9%
3558
 
3.9%
3427
 
3.8%
2215
 
2.4%
Other values (528) 48475
53.2%
Latin
ValueCountFrequency (%)
B 133
35.8%
A 38
 
10.2%
I 14
 
3.8%
C 12
 
3.2%
e 12
 
3.2%
L 11
 
3.0%
S 11
 
3.0%
K 10
 
2.7%
M 7
 
1.9%
H 7
 
1.9%
Other values (32) 116
31.3%
Common
ValueCountFrequency (%)
26724
35.9%
1 7100
 
9.5%
2 5456
 
7.3%
) 5079
 
6.8%
( 5079
 
6.8%
, 4694
 
6.3%
3 3680
 
4.9%
0 3661
 
4.9%
4 2516
 
3.4%
- 2167
 
2.9%
Other values (11) 8216
 
11.0%
Han
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 91102
54.9%
ASCII 74738
45.1%
Number Forms 5
 
< 0.1%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
26724
35.8%
1 7100
 
9.5%
2 5456
 
7.3%
) 5079
 
6.8%
( 5079
 
6.8%
, 4694
 
6.3%
3 3680
 
4.9%
0 3661
 
4.9%
4 2516
 
3.4%
- 2167
 
2.9%
Other values (51) 8582
 
11.5%
Hangul
ValueCountFrequency (%)
6871
 
7.5%
5131
 
5.6%
4684
 
5.1%
4652
 
5.1%
4503
 
4.9%
4024
 
4.4%
3562
 
3.9%
3558
 
3.9%
3427
 
3.8%
2215
 
2.4%
Other values (528) 48475
53.2%
Number Forms
ValueCountFrequency (%)
4
80.0%
1
 
20.0%
CJK
ValueCountFrequency (%)
2
100.0%

도로명우편번호
Text

MISSING 

Distinct1986
Distinct (%)47.0%
Missing828
Missing (%)16.4%
Memory size39.6 KiB
2024-05-10T23:52:52.729887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length4.5397163
Min length4

Characters and Unicode

Total characters19203
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

Unique1374 ?
Unique (%)32.5%

Sample

1st row03964
2nd row04052
3rd row04052
4th row03961
5th row02832
ValueCountFrequency (%)
3982 79
 
1.9%
4056 60
 
1.4%
4053 56
 
1.3%
4052 52
 
1.2%
3985 52
 
1.2%
4303 48
 
1.1%
3990 47
 
1.1%
4630 39
 
0.9%
3991 35
 
0.8%
4391 34
 
0.8%
Other values (1976) 3728
88.1%
2024-05-10T23:52:54.168773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3023
15.7%
4 2844
14.8%
3 2660
13.9%
5 2122
11.1%
2 1612
8.4%
9 1594
8.3%
6 1410
7.3%
1 1364
7.1%
8 1363
7.1%
7 1201
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 19193
99.9%
Dash Punctuation 10
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3023
15.8%
4 2844
14.8%
3 2660
13.9%
5 2122
11.1%
2 1612
8.4%
9 1594
8.3%
6 1410
7.3%
1 1364
7.1%
8 1363
7.1%
7 1201
 
6.3%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 19203
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3023
15.7%
4 2844
14.8%
3 2660
13.9%
5 2122
11.1%
2 1612
8.4%
9 1594
8.3%
6 1410
7.3%
1 1364
7.1%
8 1363
7.1%
7 1201
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19203
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3023
15.7%
4 2844
14.8%
3 2660
13.9%
5 2122
11.1%
2 1612
8.4%
9 1594
8.3%
6 1410
7.3%
1 1364
7.1%
8 1363
7.1%
7 1201
 
6.3%
Distinct4853
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Memory size39.6 KiB
2024-05-10T23:52:55.323781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length36
Mean length8.7534599
Min length1

Characters and Unicode

Total characters44275
Distinct characters844
Distinct categories15 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4681 ?
Unique (%)92.5%

Sample

1st row스테이 포포
2nd row스테이온 2
3rd row스테이온 3
4th row프라이빗 하우스
5th row소담소담
ValueCountFrequency (%)
house 526
 
6.1%
게스트하우스 483
 
5.6%
하우스 267
 
3.1%
스테이 159
 
1.8%
stay 118
 
1.4%
guest 80
 
0.9%
guesthouse 77
 
0.9%
home 41
 
0.5%
the 40
 
0.5%
서울 39
 
0.4%
Other values (5150) 6847
78.9%
2024-05-10T23:52:56.579436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3629
 
8.2%
3563
 
8.0%
1923
 
4.3%
1903
 
4.3%
e 1506
 
3.4%
o 1276
 
2.9%
s 1147
 
2.6%
1057
 
2.4%
1002
 
2.3%
u 954
 
2.2%
Other values (834) 26315
59.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 23397
52.8%
Lowercase Letter 10019
22.6%
Uppercase Letter 5022
 
11.3%
Space Separator 3629
 
8.2%
Decimal Number 790
 
1.8%
Open Punctuation 494
 
1.1%
Close Punctuation 492
 
1.1%
Other Punctuation 326
 
0.7%
Dash Punctuation 64
 
0.1%
Connector Punctuation 17
 
< 0.1%
Other values (5) 25
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3563
 
15.2%
1923
 
8.2%
1903
 
8.1%
1057
 
4.5%
1002
 
4.3%
879
 
3.8%
501
 
2.1%
369
 
1.6%
216
 
0.9%
194
 
0.8%
Other values (742) 11790
50.4%
Lowercase Letter
ValueCountFrequency (%)
e 1506
15.0%
o 1276
12.7%
s 1147
11.4%
u 954
9.5%
a 834
8.3%
n 612
 
6.1%
t 557
 
5.6%
h 450
 
4.5%
i 410
 
4.1%
y 348
 
3.5%
Other values (16) 1925
19.2%
Uppercase Letter
ValueCountFrequency (%)
H 625
 
12.4%
S 558
 
11.1%
E 355
 
7.1%
O 338
 
6.7%
A 297
 
5.9%
G 250
 
5.0%
U 248
 
4.9%
B 231
 
4.6%
T 227
 
4.5%
N 221
 
4.4%
Other values (16) 1672
33.3%
Other Punctuation
ValueCountFrequency (%)
' 150
46.0%
& 68
20.9%
. 46
 
14.1%
, 30
 
9.2%
: 9
 
2.8%
# 8
 
2.5%
? 5
 
1.5%
; 4
 
1.2%
@ 2
 
0.6%
% 1
 
0.3%
Other values (3) 3
 
0.9%
Decimal Number
ValueCountFrequency (%)
2 217
27.5%
1 147
18.6%
3 90
11.4%
0 88
11.1%
5 52
 
6.6%
4 50
 
6.3%
7 45
 
5.7%
9 39
 
4.9%
8 36
 
4.6%
6 26
 
3.3%
Letter Number
ValueCountFrequency (%)
9
52.9%
4
23.5%
2
 
11.8%
1
 
5.9%
1
 
5.9%
Open Punctuation
ValueCountFrequency (%)
( 491
99.4%
[ 3
 
0.6%
Close Punctuation
ValueCountFrequency (%)
) 489
99.4%
] 3
 
0.6%
Math Symbol
ValueCountFrequency (%)
~ 1
50.0%
+ 1
50.0%
Space Separator
ValueCountFrequency (%)
3629
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 64
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 17
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 3
100.0%
Final Punctuation
ValueCountFrequency (%)
2
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 23373
52.8%
Latin 15058
34.0%
Common 5820
 
13.1%
Han 24
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3563
 
15.2%
1923
 
8.2%
1903
 
8.1%
1057
 
4.5%
1002
 
4.3%
879
 
3.8%
501
 
2.1%
369
 
1.6%
216
 
0.9%
194
 
0.8%
Other values (724) 11766
50.3%
Latin
ValueCountFrequency (%)
e 1506
 
10.0%
o 1276
 
8.5%
s 1147
 
7.6%
u 954
 
6.3%
a 834
 
5.5%
H 625
 
4.2%
n 612
 
4.1%
S 558
 
3.7%
t 557
 
3.7%
h 450
 
3.0%
Other values (47) 6539
43.4%
Common
ValueCountFrequency (%)
3629
62.4%
( 491
 
8.4%
) 489
 
8.4%
2 217
 
3.7%
' 150
 
2.6%
1 147
 
2.5%
3 90
 
1.5%
0 88
 
1.5%
& 68
 
1.2%
- 64
 
1.1%
Other values (25) 387
 
6.6%
Han
ValueCountFrequency (%)
4
16.7%
2
 
8.3%
2
 
8.3%
2
 
8.3%
1
 
4.2%
1
 
4.2%
1
 
4.2%
1
 
4.2%
1
 
4.2%
1
 
4.2%
Other values (8) 8
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 23373
52.8%
ASCII 20857
47.1%
CJK 24
 
0.1%
Number Forms 17
 
< 0.1%
Punctuation 2
 
< 0.1%
Misc Symbols 1
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3629
 
17.4%
e 1506
 
7.2%
o 1276
 
6.1%
s 1147
 
5.5%
u 954
 
4.6%
a 834
 
4.0%
H 625
 
3.0%
n 612
 
2.9%
S 558
 
2.7%
t 557
 
2.7%
Other values (74) 9159
43.9%
Hangul
ValueCountFrequency (%)
3563
 
15.2%
1923
 
8.2%
1903
 
8.1%
1057
 
4.5%
1002
 
4.3%
879
 
3.8%
501
 
2.1%
369
 
1.6%
216
 
0.9%
194
 
0.8%
Other values (724) 11766
50.3%
Number Forms
ValueCountFrequency (%)
9
52.9%
4
23.5%
2
 
11.8%
1
 
5.9%
1
 
5.9%
CJK
ValueCountFrequency (%)
4
16.7%
2
 
8.3%
2
 
8.3%
2
 
8.3%
1
 
4.2%
1
 
4.2%
1
 
4.2%
1
 
4.2%
1
 
4.2%
1
 
4.2%
Other values (8) 8
33.3%
Punctuation
ValueCountFrequency (%)
2
100.0%
Misc Symbols
ValueCountFrequency (%)
1
100.0%
None
ValueCountFrequency (%)
1
100.0%
Distinct2464
Distinct (%)48.7%
Missing0
Missing (%)0.0%
Memory size39.6 KiB
Minimum2012-06-22 00:00:00
Maximum2024-05-09 17:01:58
2024-05-10T23:52:57.106980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:52:57.567170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size39.6 KiB
U
2788 
I
2269 
D
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
U 2788
55.1%
I 2269
44.9%
D 1
 
< 0.1%

Length

2024-05-10T23:52:57.994222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:52:58.298096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 2788
55.1%
i 2269
44.9%
d 1
 
< 0.1%
Distinct1498
Distinct (%)29.6%
Missing0
Missing (%)0.0%
Memory size39.6 KiB
Minimum2018-08-31 23:59:00
Maximum2023-12-05 00:09:00
2024-05-10T23:52:58.638299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:52:59.114249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5058
Missing (%)100.0%
Memory size44.6 KiB

좌표정보(X)
Real number (ℝ)

Distinct4172
Distinct (%)83.0%
Missing29
Missing (%)0.6%
Infinite0
Infinite (%)0.0%
Mean227467.43
Minimum142052.79
Maximum426936.81
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size44.6 KiB
2024-05-10T23:52:59.510304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum142052.79
5-th percentile180983.87
Q1193265.2
median198535.36
Q3211019.48
95-th percentile392479.31
Maximum426936.81
Range284884.02
Interquartile range (IQR)17754.281

Descriptive statistics

Standard deviation67753.68
Coefficient of variation (CV)0.29786101
Kurtosis1.3828029
Mean227467.43
Median Absolute Deviation (MAD)5718.3178
Skewness1.7326234
Sum1.1439337 × 109
Variance4.5905612 × 109
MonotonicityNot monotonic
2024-05-10T23:52:59.903093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
197097.9903 23
 
0.5%
192725.698 12
 
0.2%
198535.3649 11
 
0.2%
192804.1254 9
 
0.2%
196838.683 9
 
0.2%
193003.7799 8
 
0.2%
357170.3825 8
 
0.2%
205271.2753 7
 
0.1%
193313.2645 6
 
0.1%
198483.8116 6
 
0.1%
Other values (4162) 4930
97.5%
(Missing) 29
 
0.6%
ValueCountFrequency (%)
142052.7904 1
< 0.1%
142206.7442 1
< 0.1%
142767.2866 1
< 0.1%
142806.7006 1
< 0.1%
142836.7045 1
< 0.1%
142901.1798 1
< 0.1%
142934.9891 1
< 0.1%
142943.1382 1
< 0.1%
142955.5723 1
< 0.1%
142989.055 1
< 0.1%
ValueCountFrequency (%)
426936.8126 1
< 0.1%
420596.2611 1
< 0.1%
420281.9467 1
< 0.1%
420205.7027 1
< 0.1%
419908.0178 1
< 0.1%
419898.0556 1
< 0.1%
419777.6238 1
< 0.1%
419751.5915 1
< 0.1%
419625.0121 1
< 0.1%
417252.9516 1
< 0.1%

좌표정보(Y)
Real number (ℝ)

Distinct4172
Distinct (%)83.0%
Missing29
Missing (%)0.6%
Infinite0
Infinite (%)0.0%
Mean396639.62
Minimum114788.39
Maximum525326.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size44.6 KiB
2024-05-10T23:53:00.342760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum114788.39
5-th percentile180311.01
Q1421767.04
median449564.75
Q3450921.7
95-th percentile462100.72
Maximum525326.4
Range410538
Interquartile range (IQR)29154.657

Descriptive statistics

Standard deviation101125.87
Coefficient of variation (CV)0.25495656
Kurtosis0.35837237
Mean396639.62
Median Absolute Deviation (MAD)3189.7212
Skewness-1.427171
Sum1.9947006 × 109
Variance1.0226442 × 1010
MonotonicityNot monotonic
2024-05-10T23:53:00.902577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
450012.7962 23
 
0.5%
450812.431 12
 
0.2%
450672.3915 11
 
0.2%
451002.794 9
 
0.2%
450945.3304 9
 
0.2%
450934.1672 8
 
0.2%
151649.9621 8
 
0.2%
445852.6388 7
 
0.1%
451039.5227 6
 
0.1%
450642.3149 6
 
0.1%
Other values (4162) 4930
97.5%
(Missing) 29
 
0.6%
ValueCountFrequency (%)
114788.3926 1
< 0.1%
136304.0244 1
< 0.1%
136984.1102 1
< 0.1%
137081.4002 1
< 0.1%
137976.9934 1
< 0.1%
138008.8377 1
< 0.1%
138078.0018 1
< 0.1%
138143.5235 1
< 0.1%
138174.3346 1
< 0.1%
138234.8912 1
< 0.1%
ValueCountFrequency (%)
525326.3956 1
< 0.1%
524682.313 1
< 0.1%
524454.2787 2
< 0.1%
524369.0544 1
< 0.1%
524347.1096 1
< 0.1%
523448.1749 1
< 0.1%
523172.772 1
< 0.1%
522394.4873 1
< 0.1%
522039.0642 1
< 0.1%
521939.7664 1
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.6 KiB
외국인관광 도시민박업
4139 
<NA>
919 

Length

Max length11
Median length11
Mean length9.7281534
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
외국인관광 도시민박업 4139
81.8%
<NA> 919
 
18.2%

Length

2024-05-10T23:53:01.454190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:53:01.873671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
외국인관광 4139
45.0%
도시민박업 4139
45.0%
na 919
 
10.0%

문화사업자구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5058
Missing (%)100.0%
Memory size44.6 KiB

지역구분명
Categorical

IMBALANCE 

Distinct14
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size39.6 KiB
<NA>
3348 
일반주거지역
1072 
주거지역
 
292
일반상업지역
 
151
준주거지역
 
62
Other values (9)
 
133

Length

Max length6
Median length4
Mean length4.5361803
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> 3348
66.2%
일반주거지역 1072
 
21.2%
주거지역 292
 
5.8%
일반상업지역 151
 
3.0%
준주거지역 62
 
1.2%
자연녹지지역 48
 
0.9%
전용주거지역 30
 
0.6%
상업지역 24
 
0.5%
보전녹지지역 9
 
0.2%
준공업지역 8
 
0.2%
Other values (4) 14
 
0.3%

Length

2024-05-10T23:53:02.311161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 3348
66.2%
일반주거지역 1072
 
21.2%
주거지역 292
 
5.8%
일반상업지역 151
 
3.0%
준주거지역 62
 
1.2%
자연녹지지역 48
 
0.9%
전용주거지역 30
 
0.6%
상업지역 24
 
0.5%
보전녹지지역 9
 
0.2%
준공업지역 8
 
0.2%
Other values (4) 14
 
0.3%

총층수
Real number (ℝ)

MISSING  ZEROS 

Distinct35
Distinct (%)1.4%
Missing2596
Missing (%)51.3%
Infinite0
Infinite (%)0.0%
Mean1.9853777
Minimum0
Maximum46
Zeros1125
Zeros (%)22.2%
Negative0
Negative (%)0.0%
Memory size44.6 KiB
2024-05-10T23:53:02.828858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile6
Maximum46
Range46
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.9595411
Coefficient of variation (CV)1.9943515
Kurtosis35.53347
Mean1.9853777
Median Absolute Deviation (MAD)1
Skewness5.1359121
Sum4888
Variance15.677966
MonotonicityNot monotonic
2024-05-10T23:53:03.239506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
0 1125
22.2%
2 374
 
7.4%
1 313
 
6.2%
3 286
 
5.7%
4 164
 
3.2%
5 67
 
1.3%
6 27
 
0.5%
15 12
 
0.2%
20 11
 
0.2%
7 10
 
0.2%
Other values (25) 73
 
1.4%
(Missing) 2596
51.3%
ValueCountFrequency (%)
0 1125
22.2%
1 313
 
6.2%
2 374
 
7.4%
3 286
 
5.7%
4 164
 
3.2%
5 67
 
1.3%
6 27
 
0.5%
7 10
 
0.2%
8 7
 
0.1%
9 5
 
0.1%
ValueCountFrequency (%)
46 2
 
< 0.1%
42 1
 
< 0.1%
40 1
 
< 0.1%
37 1
 
< 0.1%
33 1
 
< 0.1%
30 1
 
< 0.1%
29 1
 
< 0.1%
27 2
 
< 0.1%
26 3
0.1%
25 5
0.1%

주변환경명
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size39.6 KiB
<NA>
4196 
주택가주변
454 
아파트지역
 
166
기타
 
127
학교정화(상대)
 
102
Other values (2)
 
13

Length

Max length8
Median length4
Mean length4.1633057
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> 4196
83.0%
주택가주변 454
 
9.0%
아파트지역 166
 
3.3%
기타 127
 
2.5%
학교정화(상대) 102
 
2.0%
학교정화(절대) 8
 
0.2%
유흥업소밀집지역 5
 
0.1%

Length

2024-05-10T23:53:03.801397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:53:04.347717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4196
83.0%
주택가주변 454
 
9.0%
아파트지역 166
 
3.3%
기타 127
 
2.5%
학교정화(상대 102
 
2.0%
학교정화(절대 8
 
0.2%
유흥업소밀집지역 5
 
0.1%

제작취급품목내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5058
Missing (%)100.0%
Memory size44.6 KiB

보험기관명
Text

MISSING 

Distinct208
Distinct (%)17.4%
Missing3863
Missing (%)76.4%
Memory size39.6 KiB
2024-05-10T23:53:05.238093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length6
Mean length5.8761506
Min length2

Characters and Unicode

Total characters7022
Distinct characters99
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique112 ?
Unique (%)9.4%

Sample

1st row명동
2nd row명동
3rd row신당동
4th row필동
5th row광희동
ValueCountFrequency (%)
1실(4명 118
 
9.6%
1실(2명 104
 
8.5%
2실(6명 90
 
7.3%
명동 76
 
6.2%
1실(3명 74
 
6.0%
2실(4명 65
 
5.3%
2실(5명 49
 
4.0%
2실(8명 46
 
3.7%
2실(3명 22
 
1.8%
1실(6명 21
 
1.7%
Other values (208) 564
45.9%
2024-05-10T23:53:06.710011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1063
15.1%
1013
14.4%
( 975
13.9%
) 975
13.9%
2 634
9.0%
1 587
8.4%
4 289
 
4.1%
3 248
 
3.5%
6 194
 
2.8%
145
 
2.1%
Other values (89) 899
12.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2607
37.1%
Decimal Number 2371
33.8%
Open Punctuation 975
 
13.9%
Close Punctuation 975
 
13.9%
Other Punctuation 55
 
0.8%
Space Separator 34
 
0.5%
Uppercase Letter 4
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1063
40.8%
1013
38.9%
145
 
5.6%
45
 
1.7%
43
 
1.6%
32
 
1.2%
20
 
0.8%
16
 
0.6%
15
 
0.6%
15
 
0.6%
Other values (66) 200
 
7.7%
Decimal Number
ValueCountFrequency (%)
2 634
26.7%
1 587
24.8%
4 289
12.2%
3 248
 
10.5%
6 194
 
8.2%
5 128
 
5.4%
8 107
 
4.5%
0 92
 
3.9%
7 62
 
2.6%
9 30
 
1.3%
Other Punctuation
ValueCountFrequency (%)
/ 29
52.7%
: 13
23.6%
, 6
 
10.9%
. 5
 
9.1%
* 2
 
3.6%
Uppercase Letter
ValueCountFrequency (%)
G 1
25.0%
D 1
25.0%
B 1
25.0%
M 1
25.0%
Open Punctuation
ValueCountFrequency (%)
( 975
100.0%
Close Punctuation
ValueCountFrequency (%)
) 975
100.0%
Space Separator
ValueCountFrequency (%)
34
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4411
62.8%
Hangul 2607
37.1%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1063
40.8%
1013
38.9%
145
 
5.6%
45
 
1.7%
43
 
1.6%
32
 
1.2%
20
 
0.8%
16
 
0.6%
15
 
0.6%
15
 
0.6%
Other values (66) 200
 
7.7%
Common
ValueCountFrequency (%)
( 975
22.1%
) 975
22.1%
2 634
14.4%
1 587
13.3%
4 289
 
6.6%
3 248
 
5.6%
6 194
 
4.4%
5 128
 
2.9%
8 107
 
2.4%
0 92
 
2.1%
Other values (9) 182
 
4.1%
Latin
ValueCountFrequency (%)
G 1
25.0%
D 1
25.0%
B 1
25.0%
M 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4415
62.9%
Hangul 2607
37.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1063
40.8%
1013
38.9%
145
 
5.6%
45
 
1.7%
43
 
1.6%
32
 
1.2%
20
 
0.8%
16
 
0.6%
15
 
0.6%
15
 
0.6%
Other values (66) 200
 
7.7%
ASCII
ValueCountFrequency (%)
( 975
22.1%
) 975
22.1%
2 634
14.4%
1 587
13.3%
4 289
 
6.5%
3 248
 
5.6%
6 194
 
4.4%
5 128
 
2.9%
8 107
 
2.4%
0 92
 
2.1%
Other values (13) 186
 
4.2%

건물용도명
Categorical

Distinct14
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size39.6 KiB
<NA>
2563 
단독주택
1172 
다가구용 주택(공동주택적용)
633 
아파트
353 
다세대주택
 
255
Other values (9)
 
82

Length

Max length15
Median length4
Mean length5.381376
Min length2

Unique

Unique5 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2563
50.7%
단독주택 1172
23.2%
다가구용 주택(공동주택적용) 633
 
12.5%
아파트 353
 
7.0%
다세대주택 255
 
5.0%
연립주택 50
 
1.0%
근린생활시설 13
 
0.3%
다중주택(공동주택적용) 12
 
0.2%
기타 2
 
< 0.1%
식품위생시설 1
 
< 0.1%
Other values (4) 4
 
0.1%

Length

2024-05-10T23:53:07.456117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2563
45.0%
단독주택 1172
20.6%
다가구용 633
 
11.1%
주택(공동주택적용 633
 
11.1%
아파트 353
 
6.2%
다세대주택 255
 
4.5%
연립주택 50
 
0.9%
근린생활시설 13
 
0.2%
다중주택(공동주택적용 12
 
0.2%
기타 2
 
< 0.1%
Other values (5) 5
 
0.1%

지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct32
Distinct (%)1.3%
Missing2617
Missing (%)51.7%
Infinite0
Infinite (%)0.0%
Mean1.8635805
Minimum0
Maximum41
Zeros1205
Zeros (%)23.8%
Negative0
Negative (%)0.0%
Memory size44.6 KiB
2024-05-10T23:53:08.030771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile6
Maximum41
Range41
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.7917929
Coefficient of variation (CV)2.0346816
Kurtosis30.46788
Mean1.8635805
Median Absolute Deviation (MAD)1
Skewness4.7981033
Sum4549
Variance14.377694
MonotonicityNot monotonic
2024-05-10T23:53:08.624146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
0 1205
23.8%
2 457
 
9.0%
1 246
 
4.9%
3 211
 
4.2%
4 125
 
2.5%
5 57
 
1.1%
6 27
 
0.5%
15 15
 
0.3%
20 10
 
0.2%
7 10
 
0.2%
Other values (22) 78
 
1.5%
(Missing) 2617
51.7%
ValueCountFrequency (%)
0 1205
23.8%
1 246
 
4.9%
2 457
 
9.0%
3 211
 
4.2%
4 125
 
2.5%
5 57
 
1.1%
6 27
 
0.5%
7 10
 
0.2%
8 6
 
0.1%
9 7
 
0.1%
ValueCountFrequency (%)
41 2
 
< 0.1%
40 1
 
< 0.1%
35 2
 
< 0.1%
29 1
 
< 0.1%
28 1
 
< 0.1%
27 1
 
< 0.1%
25 6
0.1%
24 2
 
< 0.1%
23 4
0.1%
22 2
 
< 0.1%

지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)0.5%
Missing3079
Missing (%)60.9%
Infinite0
Infinite (%)0.0%
Mean0.2481051
Minimum0
Maximum24
Zeros1595
Zeros (%)31.5%
Negative0
Negative (%)0.0%
Memory size44.6 KiB
2024-05-10T23:53:09.140755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum24
Range24
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.83259568
Coefficient of variation (CV)3.3558184
Kurtosis387.88873
Mean0.2481051
Median Absolute Deviation (MAD)0
Skewness15.623339
Sum491
Variance0.69321557
MonotonicityNot monotonic
2024-05-10T23:53:09.571426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 1595
31.5%
1 340
 
6.7%
2 27
 
0.5%
3 9
 
0.2%
5 3
 
0.1%
6 2
 
< 0.1%
15 1
 
< 0.1%
4 1
 
< 0.1%
24 1
 
< 0.1%
(Missing) 3079
60.9%
ValueCountFrequency (%)
0 1595
31.5%
1 340
 
6.7%
2 27
 
0.5%
3 9
 
0.2%
4 1
 
< 0.1%
5 3
 
0.1%
6 2
 
< 0.1%
15 1
 
< 0.1%
24 1
 
< 0.1%
ValueCountFrequency (%)
24 1
 
< 0.1%
15 1
 
< 0.1%
6 2
 
< 0.1%
5 3
 
0.1%
4 1
 
< 0.1%
3 9
 
0.2%
2 27
 
0.5%
1 340
 
6.7%
0 1595
31.5%

객실수
Real number (ℝ)

MISSING  ZEROS 

Distinct17
Distinct (%)0.6%
Missing2354
Missing (%)46.5%
Infinite0
Infinite (%)0.0%
Mean1.9153107
Minimum0
Maximum17
Zeros656
Zeros (%)13.0%
Negative0
Negative (%)0.0%
Memory size44.6 KiB
2024-05-10T23:53:10.082237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q32
95-th percentile6
Maximum17
Range17
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.008639
Coefficient of variation (CV)1.0487275
Kurtosis5.6069333
Mean1.9153107
Median Absolute Deviation (MAD)1
Skewness1.9464103
Sum5179
Variance4.0346305
MonotonicityNot monotonic
2024-05-10T23:53:10.628165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
1 697
 
13.8%
2 683
 
13.5%
0 656
 
13.0%
3 275
 
5.4%
4 115
 
2.3%
5 105
 
2.1%
6 58
 
1.1%
7 54
 
1.1%
8 21
 
0.4%
9 16
 
0.3%
Other values (7) 24
 
0.5%
(Missing) 2354
46.5%
ValueCountFrequency (%)
0 656
13.0%
1 697
13.8%
2 683
13.5%
3 275
 
5.4%
4 115
 
2.3%
5 105
 
2.1%
6 58
 
1.1%
7 54
 
1.1%
8 21
 
0.4%
9 16
 
0.3%
ValueCountFrequency (%)
17 1
 
< 0.1%
16 1
 
< 0.1%
14 1
 
< 0.1%
13 1
 
< 0.1%
12 2
 
< 0.1%
11 4
 
0.1%
10 14
 
0.3%
9 16
 
0.3%
8 21
 
0.4%
7 54
1.1%

건축연면적
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct113
Distinct (%)6.5%
Missing3312
Missing (%)65.5%
Infinite0
Infinite (%)0.0%
Mean45.485109
Minimum0
Maximum26452
Zeros1592
Zeros (%)31.5%
Negative0
Negative (%)0.0%
Memory size44.6 KiB
2024-05-10T23:53:11.125018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile97.75
Maximum26452
Range26452
Interquartile range (IQR)0

Descriptive statistics

Standard deviation828.19255
Coefficient of variation (CV)18.207993
Kurtosis824.33922
Mean45.485109
Median Absolute Deviation (MAD)0
Skewness28.099356
Sum79417
Variance685902.89
MonotonicityNot monotonic
2024-05-10T23:53:11.679445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1592
31.5%
85 7
 
0.1%
63 4
 
0.1%
46 4
 
0.1%
83 3
 
0.1%
99 3
 
0.1%
228 2
 
< 0.1%
61 2
 
< 0.1%
146 2
 
< 0.1%
50 2
 
< 0.1%
Other values (103) 125
 
2.5%
(Missing) 3312
65.5%
ValueCountFrequency (%)
0 1592
31.5%
18 1
 
< 0.1%
29 2
 
< 0.1%
32 1
 
< 0.1%
33 1
 
< 0.1%
34 1
 
< 0.1%
36 1
 
< 0.1%
37 1
 
< 0.1%
39 1
 
< 0.1%
44 1
 
< 0.1%
ValueCountFrequency (%)
26452 1
< 0.1%
20872 1
< 0.1%
7071 1
< 0.1%
3029 1
< 0.1%
861 1
< 0.1%
733 1
< 0.1%
717 1
< 0.1%
678 1
< 0.1%
560 1
< 0.1%
465 1
< 0.1%

영문상호명
Text

MISSING 

Distinct1611
Distinct (%)97.3%
Missing3403
Missing (%)67.3%
Memory size39.6 KiB
2024-05-10T23:53:12.914537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length31
Mean length13.117221
Min length1

Characters and Unicode

Total characters21709
Distinct characters85
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1567 ?
Unique (%)94.7%

Sample

1st rowJ.Garden
2nd rowOlive Hostel W
3rd rowPlan A Hostel
4th rowMujigae GuestHouse
5th rowFirst House
ValueCountFrequency (%)
house 528
 
14.6%
guesthouse 261
 
7.2%
stay 95
 
2.6%
guest 94
 
2.6%
the 50
 
1.4%
hongdae 49
 
1.4%
seoul 45
 
1.2%
home 35
 
1.0%
2 34
 
0.9%
in 21
 
0.6%
Other values (1545) 2401
66.5%
2024-05-10T23:53:14.934461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 2100
 
9.7%
1961
 
9.0%
o 1691
 
7.8%
s 1492
 
6.9%
u 1401
 
6.5%
a 1002
 
4.6%
n 830
 
3.8%
H 761
 
3.5%
t 756
 
3.5%
h 659
 
3.0%
Other values (75) 9056
41.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 13358
61.5%
Uppercase Letter 5796
26.7%
Space Separator 1961
 
9.0%
Decimal Number 334
 
1.5%
Other Punctuation 187
 
0.9%
Dash Punctuation 49
 
0.2%
Letter Number 8
 
< 0.1%
Open Punctuation 6
 
< 0.1%
Close Punctuation 6
 
< 0.1%
Final Punctuation 2
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2100
15.7%
o 1691
12.7%
s 1492
11.2%
u 1401
10.5%
a 1002
7.5%
n 830
 
6.2%
t 756
 
5.7%
h 659
 
4.9%
i 558
 
4.2%
r 420
 
3.1%
Other values (16) 2449
18.3%
Uppercase Letter
ValueCountFrequency (%)
H 761
13.1%
S 610
 
10.5%
G 479
 
8.3%
O 453
 
7.8%
E 418
 
7.2%
A 339
 
5.8%
U 325
 
5.6%
N 276
 
4.8%
T 241
 
4.2%
M 240
 
4.1%
Other values (16) 1654
28.5%
Decimal Number
ValueCountFrequency (%)
2 103
30.8%
1 58
17.4%
3 40
 
12.0%
0 32
 
9.6%
5 27
 
8.1%
4 20
 
6.0%
9 19
 
5.7%
7 18
 
5.4%
8 11
 
3.3%
6 6
 
1.8%
Other Punctuation
ValueCountFrequency (%)
' 118
63.1%
. 29
 
15.5%
& 25
 
13.4%
: 6
 
3.2%
# 4
 
2.1%
, 2
 
1.1%
; 1
 
0.5%
! 1
 
0.5%
% 1
 
0.5%
Letter Number
ValueCountFrequency (%)
3
37.5%
2
25.0%
1
 
12.5%
1
 
12.5%
1
 
12.5%
Open Punctuation
ValueCountFrequency (%)
( 4
66.7%
[ 2
33.3%
Close Punctuation
ValueCountFrequency (%)
) 4
66.7%
] 2
33.3%
Space Separator
ValueCountFrequency (%)
1961
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 49
100.0%
Final Punctuation
ValueCountFrequency (%)
2
100.0%
Other Letter
ValueCountFrequency (%)
1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 19162
88.3%
Common 2546
 
11.7%
Han 1
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2100
 
11.0%
o 1691
 
8.8%
s 1492
 
7.8%
u 1401
 
7.3%
a 1002
 
5.2%
n 830
 
4.3%
H 761
 
4.0%
t 756
 
3.9%
h 659
 
3.4%
S 610
 
3.2%
Other values (47) 7860
41.0%
Common
ValueCountFrequency (%)
1961
77.0%
' 118
 
4.6%
2 103
 
4.0%
1 58
 
2.3%
- 49
 
1.9%
3 40
 
1.6%
0 32
 
1.3%
. 29
 
1.1%
5 27
 
1.1%
& 25
 
1.0%
Other values (17) 104
 
4.1%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21698
99.9%
Number Forms 8
 
< 0.1%
Punctuation 2
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 2100
 
9.7%
1961
 
9.0%
o 1691
 
7.8%
s 1492
 
6.9%
u 1401
 
6.5%
a 1002
 
4.6%
n 830
 
3.8%
H 761
 
3.5%
t 756
 
3.5%
h 659
 
3.0%
Other values (68) 9045
41.7%
Number Forms
ValueCountFrequency (%)
3
37.5%
2
25.0%
1
 
12.5%
1
 
12.5%
1
 
12.5%
Punctuation
ValueCountFrequency (%)
2
100.0%
CJK
ValueCountFrequency (%)
1
100.0%

영문상호주소
Text

MISSING 

Distinct112
Distinct (%)6.9%
Missing3426
Missing (%)67.7%
Memory size39.6 KiB
2024-05-10T23:53:15.698490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length61
Mean length36.064951
Min length7

Characters and Unicode

Total characters58858
Distinct characters59
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique65 ?
Unique (%)4.0%

Sample

1st rowUrban private room rental business for foreign tourists
2nd rowUrban private room rental business for foreign tourists
3rd rowTourist Service Facility
4th rowTourist Service Facility
5th rowTourist Service Facility
ValueCountFrequency (%)
for 1431
16.8%
foreign 1342
15.8%
urban 1326
15.6%
homestay 1049
12.3%
tourists 832
9.8%
tourist 668
7.9%
business 219
 
2.6%
home 173
 
2.0%
private 163
 
1.9%
room 163
 
1.9%
Other values (69) 1138
13.4%
2024-05-10T23:53:17.036442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6887
 
11.7%
O 4148
 
7.0%
R 4050
 
6.9%
T 3372
 
5.7%
S 2843
 
4.8%
r 2548
 
4.3%
U 2397
 
4.1%
F 2355
 
4.0%
o 2207
 
3.7%
I 2133
 
3.6%
Other values (49) 25918
44.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 33033
56.1%
Lowercase Letter 18828
32.0%
Space Separator 6887
 
11.7%
Dash Punctuation 76
 
0.1%
Other Punctuation 14
 
< 0.1%
Decimal Number 10
 
< 0.1%
Open Punctuation 5
 
< 0.1%
Close Punctuation 5
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
O 4148
12.6%
R 4050
12.3%
T 3372
10.2%
S 2843
8.6%
U 2397
7.3%
F 2355
7.1%
I 2133
 
6.5%
E 2101
 
6.4%
N 2029
 
6.1%
A 1993
 
6.0%
Other values (12) 5612
17.0%
Lowercase Letter
ValueCountFrequency (%)
r 2548
13.5%
o 2207
11.7%
e 1860
9.9%
i 1790
9.5%
s 1770
9.4%
t 1540
8.2%
n 1449
7.7%
a 994
 
5.3%
u 911
 
4.8%
f 672
 
3.6%
Other values (12) 3087
16.4%
Decimal Number
ValueCountFrequency (%)
1 2
20.0%
5 2
20.0%
9 2
20.0%
3 1
10.0%
7 1
10.0%
4 1
10.0%
0 1
10.0%
Other Punctuation
ValueCountFrequency (%)
, 8
57.1%
& 4
28.6%
# 1
 
7.1%
' 1
 
7.1%
Space Separator
ValueCountFrequency (%)
6887
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 76
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 51861
88.1%
Common 6997
 
11.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
O 4148
 
8.0%
R 4050
 
7.8%
T 3372
 
6.5%
S 2843
 
5.5%
r 2548
 
4.9%
U 2397
 
4.6%
F 2355
 
4.5%
o 2207
 
4.3%
I 2133
 
4.1%
E 2101
 
4.1%
Other values (34) 23707
45.7%
Common
ValueCountFrequency (%)
6887
98.4%
- 76
 
1.1%
, 8
 
0.1%
( 5
 
0.1%
) 5
 
0.1%
& 4
 
0.1%
1 2
 
< 0.1%
5 2
 
< 0.1%
9 2
 
< 0.1%
# 1
 
< 0.1%
Other values (5) 5
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 58858
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6887
 
11.7%
O 4148
 
7.0%
R 4050
 
6.9%
T 3372
 
5.7%
S 2843
 
4.8%
r 2548
 
4.3%
U 2397
 
4.1%
F 2355
 
4.0%
o 2207
 
3.7%
I 2133
 
3.6%
Other values (49) 25918
44.0%

선박총톤수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.6 KiB
<NA>
3395 
0
1663 

Length

Max length4
Median length4
Mean length3.0136418
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3395
67.1%
0 1663
32.9%

Length

2024-05-10T23:53:17.861627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:53:18.260919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3395
67.1%
0 1663
32.9%

선박척수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.6 KiB
<NA>
3395 
0
1663 

Length

Max length4
Median length4
Mean length3.0136418
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3395
67.1%
0 1663
32.9%

Length

2024-05-10T23:53:18.773301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:53:19.253831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3395
67.1%
0 1663
32.9%

선박제원
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5058
Missing (%)100.0%
Memory size44.6 KiB

무대면적
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.6 KiB
<NA>
3395 
0
1663 

Length

Max length4
Median length4
Mean length3.0136418
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3395
67.1%
0 1663
32.9%

Length

2024-05-10T23:53:19.756372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:53:20.221393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3395
67.1%
0 1663
32.9%

좌석수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.6 KiB
<NA>
3395 
0
1663 

Length

Max length4
Median length4
Mean length3.0136418
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3395
67.1%
0 1663
32.9%

Length

2024-05-10T23:53:20.741913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:53:21.198262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3395
67.1%
0 1663
32.9%

기념품종류
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5058
Missing (%)100.0%
Memory size44.6 KiB
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.6 KiB
<NA>
3395 
0
1663 

Length

Max length4
Median length4
Mean length3.0136418
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3395
67.1%
0 1663
32.9%

Length

2024-05-10T23:53:21.941911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:53:22.321668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3395
67.1%
0 1663
32.9%

시설면적
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct2639
Distinct (%)71.2%
Missing1353
Missing (%)26.7%
Infinite0
Infinite (%)0.0%
Mean141.45641
Minimum0
Maximum95311
Zeros140
Zeros (%)2.8%
Negative0
Negative (%)0.0%
Memory size44.6 KiB
2024-05-10T23:53:22.680829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile24.076
Q150.82
median78.51
Q3118.43
95-th percentile195
Maximum95311
Range95311
Interquartile range (IQR)67.61

Descriptive statistics

Standard deviation2102.7847
Coefficient of variation (CV)14.865249
Kurtosis1848.2458
Mean141.45641
Median Absolute Deviation (MAD)30.76
Skewness42.80609
Sum524096.01
Variance4421703.6
MonotonicityNot monotonic
2024-05-10T23:53:23.340813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 140
 
2.8%
40.0 16
 
0.3%
84.0 13
 
0.3%
84.96 12
 
0.2%
84.97 11
 
0.2%
36.0 11
 
0.2%
49.0 11
 
0.2%
66.0 11
 
0.2%
56.0 10
 
0.2%
35.0 9
 
0.2%
Other values (2629) 3461
68.4%
(Missing) 1353
 
26.7%
ValueCountFrequency (%)
0.0 140
2.8%
4.2 1
 
< 0.1%
7.02 1
 
< 0.1%
8.6 1
 
< 0.1%
9.45 1
 
< 0.1%
10.4 1
 
< 0.1%
11.0 1
 
< 0.1%
11.09 1
 
< 0.1%
11.1 1
 
< 0.1%
12.5 1
 
< 0.1%
ValueCountFrequency (%)
95311.0 1
< 0.1%
84981.0 1
< 0.1%
9041.0 1
< 0.1%
4478.0 1
< 0.1%
1905.0 1
< 0.1%
1462.0 1
< 0.1%
330.5 1
< 0.1%
270.11 1
< 0.1%
250.1 1
< 0.1%
236.0 1
< 0.1%

놀이기구수내역
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5058
Missing (%)100.0%
Memory size44.6 KiB

놀이시설수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.6 KiB
<NA>
3395 
0
1663 

Length

Max length4
Median length4
Mean length3.0136418
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3395
67.1%
0 1663
32.9%

Length

2024-05-10T23:53:23.964829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:53:24.414556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3395
67.1%
0 1663
32.9%

방송시설유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5058
Missing (%)100.0%
Memory size44.6 KiB

발전시설유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5058
Missing (%)100.0%
Memory size44.6 KiB

의무실유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5058
Missing (%)100.0%
Memory size44.6 KiB

안내소유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5058
Missing (%)100.0%
Memory size44.6 KiB

기획여행보험시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5058
Missing (%)100.0%
Memory size44.6 KiB

기획여행보험종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5058
Missing (%)100.0%
Memory size44.6 KiB

자본금
Real number (ℝ)

MISSING  ZEROS 

Distinct80
Distinct (%)4.1%
Missing3098
Missing (%)61.2%
Infinite0
Infinite (%)0.0%
Mean21066820
Minimum0
Maximum9 × 108
Zeros1356
Zeros (%)26.8%
Negative0
Negative (%)0.0%
Memory size44.6 KiB
2024-05-10T23:53:25.102840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q310000000
95-th percentile1.2 × 108
Maximum9 × 108
Range9 × 108
Interquartile range (IQR)10000000

Descriptive statistics

Standard deviation73173718
Coefficient of variation (CV)3.4734107
Kurtosis53.879473
Mean21066820
Median Absolute Deviation (MAD)0
Skewness6.4248033
Sum4.1290967 × 1010
Variance5.354393 × 1015
MonotonicityNot monotonic
2024-05-10T23:53:25.868790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1356
26.8%
10000000 115
 
2.3%
20000000 63
 
1.2%
30000000 59
 
1.2%
50000000 56
 
1.1%
5000000 41
 
0.8%
100000000 33
 
0.7%
1000000 23
 
0.5%
200000000 23
 
0.5%
15000000 17
 
0.3%
Other values (70) 174
 
3.4%
(Missing) 3098
61.2%
ValueCountFrequency (%)
0 1356
26.8%
1000 1
 
< 0.1%
2000 1
 
< 0.1%
3500 1
 
< 0.1%
7000 1
 
< 0.1%
300000 2
 
< 0.1%
500000 2
 
< 0.1%
1000000 23
 
0.5%
1500000 1
 
< 0.1%
2000000 8
 
0.2%
ValueCountFrequency (%)
900000000 3
0.1%
800000000 1
 
< 0.1%
650000000 1
 
< 0.1%
600000000 1
 
< 0.1%
550000000 1
 
< 0.1%
540000000 1
 
< 0.1%
500000000 6
0.1%
430000000 1
 
< 0.1%
400000000 3
0.1%
356000000 1
 
< 0.1%

보험시작일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size39.6 KiB
<NA>
5054 
20220422
 
3
20220914
 
1

Length

Max length8
Median length4
Mean length4.0031633
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> 5054
99.9%
20220422 3
 
0.1%
20220914 1
 
< 0.1%

Length

2024-05-10T23:53:26.326301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:53:26.688080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5054
99.9%
20220422 3
 
0.1%
20220914 1
 
< 0.1%

보험종료일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size39.6 KiB
<NA>
5054 
20230422
 
3
20230914
 
1

Length

Max length8
Median length4
Mean length4.0031633
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> 5054
99.9%
20230422 3
 
0.1%
20230914 1
 
< 0.1%

Length

2024-05-10T23:53:27.284495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:53:27.614525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5054
99.9%
20230422 3
 
0.1%
20230914 1
 
< 0.1%

부대시설내역
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5058
Missing (%)100.0%
Memory size44.6 KiB

시설규모
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct233
Distinct (%)6.3%
Missing1353
Missing (%)26.7%
Infinite0
Infinite (%)0.0%
Mean141.4726
Minimum0
Maximum95311
Zeros140
Zeros (%)2.8%
Negative0
Negative (%)0.0%
Memory size44.6 KiB
2024-05-10T23:53:28.048094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile24
Q151
median79
Q3118
95-th percentile195
Maximum95311
Range95311
Interquartile range (IQR)67

Descriptive statistics

Standard deviation2102.7845
Coefficient of variation (CV)14.863546
Kurtosis1848.2453
Mean141.4726
Median Absolute Deviation (MAD)31
Skewness42.806081
Sum524156
Variance4421702.7
MonotonicityNot monotonic
2024-05-10T23:53:28.680090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 140
 
2.8%
85 125
 
2.5%
60 80
 
1.6%
50 75
 
1.5%
40 52
 
1.0%
49 50
 
1.0%
84 50
 
1.0%
45 46
 
0.9%
66 46
 
0.9%
63 42
 
0.8%
Other values (223) 2999
59.3%
(Missing) 1353
26.7%
ValueCountFrequency (%)
0 140
2.8%
4 1
 
< 0.1%
7 1
 
< 0.1%
9 2
 
< 0.1%
10 1
 
< 0.1%
11 3
 
0.1%
13 2
 
< 0.1%
14 2
 
< 0.1%
15 2
 
< 0.1%
16 4
 
0.1%
ValueCountFrequency (%)
95311 1
< 0.1%
84981 1
< 0.1%
9041 1
< 0.1%
4478 1
< 0.1%
1905 1
< 0.1%
1462 1
< 0.1%
331 1
< 0.1%
270 1
< 0.1%
250 1
< 0.1%
236 1
< 0.1%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명문화사업자구분명지역구분명총층수주변환경명제작취급품목내용보험기관명건물용도명지상층수지하층수객실수건축연면적영문상호명영문상호주소선박총톤수선박척수선박제원무대면적좌석수기념품종류회의실별동시수용인원시설면적놀이기구수내역놀이시설수방송시설유무발전시설유무의무실유무안내소유무기획여행보험시작일자기획여행보험종료일자자본금보험시작일자보험종료일자부대시설내역시설규모
03130000CDFI22622120230001012023-08-04<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 망원동 479-28서울특별시 마포구 망원로7길 44, 3층 (망원동)03964스테이 포포2023-08-04 09:50:32I2022-12-08 00:06:00.0<NA>191521.233101450799.67231<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
13130000CDFI22622120230001032023-08-04<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 서교동 330-32서울특별시 마포구 와우산로29길 48-21, 301호 (서교동)04052스테이온 22023-08-04 13:53:15I2022-12-08 00:06:00.0<NA>193523.766775450441.778025<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23130000CDFI22622120230001022023-08-04<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 서교동 330-32서울특별시 마포구 와우산로29길 48-21, 302호 (서교동)04052스테이온 32023-08-04 13:53:37I2022-12-08 00:06:00.0<NA>193523.766775450441.778025<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
33130000CDFI22622120230000962023-07-25<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 망원동 435-1서울특별시 마포구 방울내로 67, 4층 (망원동)03961프라이빗 하우스2023-08-04 10:01:41U2022-12-08 00:06:00.0<NA>191339.639553450879.451466<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
43070000CDFI22622120230000072023-08-07<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 성북구 동소문동4가 15서울특별시 성북구 동소문로13가길 71-1 (동소문동4가)02832소담소담2023-08-07 09:50:16I2022-12-08 00:09:00.0<NA>200759.743486454238.399541<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
53020000CDFI22622120230000562023-08-10<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 용산구 동자동 21-13서울특별시 용산구 한강대로104다길 28 (동자동)04333클라라 하우스(Clara House)2023-08-10 10:07:27I2022-12-07 23:02:00.0<NA>197674.455264449711.230699<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
63020000CDFI22622120230000592023-08-10<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 용산구 동자동 19-47서울특별시 용산구 한강대로104길 41-8, 2층 (동자동)04324마르페게스트하우스2023-08-10 13:50:54I2022-12-07 23:02:00.0<NA>197686.443524449839.909005<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
73020000CDFI22622120230000582023-08-10<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 용산구 이태원동 260-60 이태원맨션서울특별시 용산구 회나무로13나길 31, 2층 (이태원동, 이태원맨션)04342K stay2023-08-10 13:50:05I2022-12-07 23:02:00.0<NA>199183.181099448808.035555<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
83020000CDFI22622120230000572023-08-10<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 용산구 갈월동 45-8서울특별시 용산구 한강대로96길 52, 101호 (갈월동)04334로지칙스2023-08-10 10:12:43I2022-12-07 23:02:00.0<NA>197686.119327449385.562724<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
93020000CDFI22622120230000602023-08-10<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 용산구 동빙고동 250-3서울특별시 용산구 서빙고로67길 48-10, 2층 (동빙고동)04398House Bong2023-08-10 16:02:01I2022-12-07 23:02:00.0<NA>199460.750601446738.259398<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명문화사업자구분명지역구분명총층수주변환경명제작취급품목내용보험기관명건물용도명지상층수지하층수객실수건축연면적영문상호명영문상호주소선박총톤수선박척수선박제원무대면적좌석수기념품종류회의실별동시수용인원시설면적놀이기구수내역놀이시설수방송시설유무발전시설유무의무실유무안내소유무기획여행보험시작일자기획여행보험종료일자자본금보험시작일자보험종료일자부대시설내역시설규모
50483230000CDFI226221201600001120160830<NA>2휴업2휴업<NA>2021122020221219<NA><NA><NA><NA>서울특별시 송파구 방이동 119-19 401호서울특별시 송파구 오금로23길 13, 401호 (방이동)5642Songpa lovely room2021-12-30U2022-01-01 02:40:00.0<NA>210195.9121445285.9129외국인관광 도시민박업<NA>주거지역<NA><NA><NA><NA>다가구용 주택(공동주택적용)<NA><NA>1<NA>Sognpa lovely roomURBAN PRIVATE ROOM RENTAL BUSINESS FOR FOREIGN TOURISTS<NA><NA><NA><NA><NA><NA><NA>105.85<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>106
50493120000CDFI226221201800000520180622<NA>2휴업2휴업<NA>2021110520230630<NA><NA><NA><NA>서울특별시 서대문구 연희동 446-144서울특별시 서대문구 성산로7길 23 (연희동)3706기분전환2021-11-11U2021-11-13 02:40:00.0<NA>192842.2233451773.4325외국인관광 도시민박업<NA>전용주거지역4기타<NA><NA>단독주택312<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>212.79<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>213
50503020000CDFI226221201300000820130108<NA>2휴업2휴업<NA>2016072220170721<NA><NA><NA>140-731서울특별시 용산구 이태원동 22-2번지 청화아파트 4동 1101호서울특별시 용산구 장문로 27 (이태원동, 22-2 청화아파트 4동 1101호)<NA>Guest house Itawon hills2016-09-05I2018-08-31 23:59:00.0<NA>199471.3097447522.747외국인관광 도시민박업<NA>일반주거지역12아파트지역<NA><NA>아파트11<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>142.68<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>143
50513130000CDFI226221201800009920181114<NA>2휴업2휴업<NA>2023013020241231<NA><NA><NA><NA>서울특별시 마포구 연남동 366-13서울특별시 마포구 연남로7길 6, 2층 (연남동)3975주니스 게스트하우스2023-01-31U2023-02-02 02:40:00.0<NA>192844.566451332.0116외국인관광 도시민박업<NA><NA><NA><NA><NA>2실(5명)다가구용 주택(공동주택적용)<NA><NA>2<NA>Juny's GuesthouseURBAN HOMESTAY FOR FOREIGN TOURISTS<NA><NA><NA><NA><NA><NA><NA>59.6<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>60
50523210000CDFI226221201400000220140220<NA>3폐업3폐업20220110<NA><NA><NA><NA><NA><NA>서울특별시 서초구 서초동 1472-2 더샵오데움 105동 501호서울특별시 서초구 효령로46길 45, 105동 501호 (서초동, 더샵오데움)6709COREA2022-01-10U2022-01-12 02:40:00.0<NA>200737.9543442131.2046외국인관광 도시민박업<NA>일반주거지역6<NA><NA><NA>다세대주택4220COREAUrban homestay facilities for foreign tourist00<NA>00<NA>0132.26<NA>0<NA><NA><NA><NA><NA><NA>0<NA><NA><NA>132
50533040000CDFI226221201600000220160202<NA>3폐업3폐업20210831<NA><NA><NA><NA><NA><NA>서울특별시 광진구 자양동 227-315 더샵스타시티 C동 3606호서울특별시 광진구 아차산로 262, C동 3606호 (자양동, 더샵스타시티)<NA>36스카이뷰2021-08-31U2021-09-02 02:40:00.0<NA>206420.7668448267.4071외국인관광 도시민박업<NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
50543380000CDFI226221202000000120201111<NA>3폐업3폐업20230109<NA><NA><NA><NA><NA><NA>부산광역시 수영구 민락동 715-1부산광역시 수영구 광안로61번나길 8, 2~3층 (민락동)48284WETEVER(?에버)2023-01-09U2023-01-11 02:40:00.0<NA>393123.3841186084.6489외국인관광 도시민박업<NA>일반주거지역3<NA><NA><NA><NA>3<NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>67.56<NA><NA><NA><NA><NA><NA><NA><NA>1000000<NA><NA><NA>68
50553020000CDFI226221201900006020191105<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 용산구 서계동 53-11서울특별시 용산구 청파로 359-16 (서계동)4303읿스 네스트(Syun's Nest)2020-10-29U2020-10-31 02:40:00.0<NA>197164.924449963.323외국인관광 도시민박업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>60.07<NA><NA><NA><NA><NA><NA><NA><NA>3000000<NA><NA><NA>60
50564640000CDFI226221202200000620220318<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>전라북도 전주시 덕진구 금암동 1583-28전라북도 전주시 덕진구 매봉8길 15-3, 2층 (금암동)54922스?런지하우스2022-03-18I2022-03-20 00:22:00.0<NA>212561.5218260014.6326외국인관광 도시민박업<NA><NA>0<NA><NA><NA><NA>20167SquatLunge houseUrban-Home Stay for Foreign Tourists00<NA>00<NA>067.34<NA>0<NA><NA><NA><NA><NA><NA>0<NA><NA><NA>67
50573940000CDFI226221201300000620130404<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA>410-811경기도 고양시 일산동구 마두동 강촌마을 706동 601호경기도 고양시 일산동구 강석로 152, 706동 6층 1호 (마두동, 강촌마을)<NA>화이트 스톤집(햇?에 반짝이는 집)2022-08-09U2022-08-11 02:40:00.0<NA>180429.5949461366.248외국인관광 도시민박업<NA><NA>0<NA><NA><NA><NA>0000<NA><NA>00<NA>00<NA>0187.0<NA>0<NA><NA><NA><NA><NA><NA>0<NA><NA><NA>187