Overview

Dataset statistics

Number of variables47
Number of observations648
Missing cells7735
Missing cells (%)25.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory255.8 KiB
Average record size in memory404.2 B

Variable types

Categorical15
Text7
DateTime4
Unsupported7
Numeric12
Boolean2

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),위생업태명,건물지상층수,건물지하층수,사용시작지상층,사용끝지상층,사용시작지하층,사용끝지하층,한실수,양실수,욕실수,발한실여부,좌석수,조건부허가신고사유,조건부허가시작일자,조건부허가종료일자,건물소유구분명,세탁기수,여성종사자수,남성종사자수,회수건조수,침대수,다중이용업소여부
Author중구
URLhttps://data.seoul.go.kr/dataList/OA-17428/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
좌석수 is highly imbalanced (60.9%)Imbalance
다중이용업소여부 is highly imbalanced (94.4%)Imbalance
인허가취소일자 has 648 (100.0%) missing valuesMissing
폐업일자 has 349 (53.9%) missing valuesMissing
휴업시작일자 has 648 (100.0%) missing valuesMissing
휴업종료일자 has 648 (100.0%) missing valuesMissing
재개업일자 has 648 (100.0%) missing valuesMissing
전화번호 has 106 (16.4%) missing valuesMissing
도로명주소 has 202 (31.2%) missing valuesMissing
도로명우편번호 has 206 (31.8%) missing valuesMissing
좌표정보(X) has 156 (24.1%) missing valuesMissing
좌표정보(Y) has 156 (24.1%) missing valuesMissing
건물지상층수 has 184 (28.4%) missing valuesMissing
건물지하층수 has 184 (28.4%) missing valuesMissing
사용시작지상층 has 184 (28.4%) missing valuesMissing
사용끝지상층 has 184 (28.4%) missing valuesMissing
사용시작지하층 has 184 (28.4%) missing valuesMissing
사용끝지하층 has 184 (28.4%) missing valuesMissing
한실수 has 184 (28.4%) missing valuesMissing
양실수 has 184 (28.4%) missing valuesMissing
욕실수 has 184 (28.4%) missing valuesMissing
발한실여부 has 184 (28.4%) missing valuesMissing
조건부허가신고사유 has 648 (100.0%) missing valuesMissing
조건부허가시작일자 has 648 (100.0%) missing valuesMissing
조건부허가종료일자 has 648 (100.0%) missing valuesMissing
다중이용업소여부 has 184 (28.4%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가신고사유 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물지상층수 has 243 (37.5%) zerosZeros
건물지하층수 has 418 (64.5%) zerosZeros
사용시작지상층 has 319 (49.2%) zerosZeros
사용끝지상층 has 249 (38.4%) zerosZeros
사용시작지하층 has 437 (67.4%) zerosZeros
사용끝지하층 has 439 (67.7%) zerosZeros
한실수 has 382 (59.0%) zerosZeros
양실수 has 147 (22.7%) zerosZeros
욕실수 has 429 (66.2%) zerosZeros

Reproduction

Analysis started2024-05-11 00:43:30.333236
Analysis finished2024-05-11 00:43:31.961894
Duration1.63 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
3010000
648 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3010000
2nd row3010000
3rd row3010000
4th row3010000
5th row3010000

Common Values

ValueCountFrequency (%)
3010000 648
100.0%

Length

2024-05-11T00:43:32.135198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:43:32.402295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3010000 648
100.0%

관리번호
Text

UNIQUE 

Distinct648
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
2024-05-11T00:43:32.790016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters14256
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

Unique648 ?
Unique (%)100.0%

Sample

1st row3010000-201-1949-00071
2nd row3010000-201-1960-00012
3rd row3010000-201-1960-00023
4th row3010000-201-1960-00053
5th row3010000-201-1960-00058
ValueCountFrequency (%)
3010000-201-1949-00071 1
 
0.2%
3010000-201-2014-00005 1
 
0.2%
3010000-201-2013-00003 1
 
0.2%
3010000-201-2013-00011 1
 
0.2%
3010000-201-2013-00004 1
 
0.2%
3010000-201-2013-00005 1
 
0.2%
3010000-201-2013-00006 1
 
0.2%
3010000-201-2013-00007 1
 
0.2%
3010000-201-2013-00008 1
 
0.2%
3010000-201-2013-00009 1
 
0.2%
Other values (638) 638
98.5%
2024-05-11T00:43:33.660532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6558
46.0%
1 2086
 
14.6%
- 1944
 
13.6%
2 1391
 
9.8%
3 939
 
6.6%
9 362
 
2.5%
6 246
 
1.7%
7 218
 
1.5%
4 189
 
1.3%
8 167
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12312
86.4%
Dash Punctuation 1944
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6558
53.3%
1 2086
 
16.9%
2 1391
 
11.3%
3 939
 
7.6%
9 362
 
2.9%
6 246
 
2.0%
7 218
 
1.8%
4 189
 
1.5%
8 167
 
1.4%
5 156
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 1944
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14256
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6558
46.0%
1 2086
 
14.6%
- 1944
 
13.6%
2 1391
 
9.8%
3 939
 
6.6%
9 362
 
2.5%
6 246
 
1.7%
7 218
 
1.5%
4 189
 
1.3%
8 167
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14256
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6558
46.0%
1 2086
 
14.6%
- 1944
 
13.6%
2 1391
 
9.8%
3 939
 
6.6%
9 362
 
2.5%
6 246
 
1.7%
7 218
 
1.5%
4 189
 
1.3%
8 167
 
1.2%
Distinct541
Distinct (%)83.5%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
Minimum1949-07-05 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T00:43:34.040970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:43:34.430024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing648
Missing (%)100.0%
Memory size5.8 KiB
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
1
349 
3
299 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 349
53.9%
3 299
46.1%

Length

2024-05-11T00:43:34.877880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:43:35.190163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 349
53.9%
3 299
46.1%

영업상태명
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
영업/정상
349 
폐업
299 

Length

Max length5
Median length5
Mean length3.6157407
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 349
53.9%
폐업 299
46.1%

Length

2024-05-11T00:43:35.542105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:43:35.902619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 349
53.9%
폐업 299
46.1%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
1
349 
2
299 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row1

Common Values

ValueCountFrequency (%)
1 349
53.9%
2 299
46.1%

Length

2024-05-11T00:43:36.322955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:43:36.682039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 349
53.9%
2 299
46.1%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
영업
349 
폐업
299 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 349
53.9%
폐업 299
46.1%

Length

2024-05-11T00:43:37.086849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:43:37.483014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 349
53.9%
폐업 299
46.1%

폐업일자
Date

MISSING 

Distinct212
Distinct (%)70.9%
Missing349
Missing (%)53.9%
Memory size5.2 KiB
Minimum1989-01-04 00:00:00
Maximum2024-04-23 00:00:00
2024-05-11T00:43:38.273773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:43:38.869744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing648
Missing (%)100.0%
Memory size5.8 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing648
Missing (%)100.0%
Memory size5.8 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing648
Missing (%)100.0%
Memory size5.8 KiB

전화번호
Text

MISSING 

Distinct434
Distinct (%)80.1%
Missing106
Missing (%)16.4%
Memory size5.2 KiB
2024-05-11T00:43:39.893485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.9391144
Min length6

Characters and Unicode

Total characters5387
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

Unique414 ?
Unique (%)76.4%

Sample

1st row7579632
2nd row02 00000
3rd row0200000000
4th row0222785000
5th row0222654186
ValueCountFrequency (%)
02 220
27.1%
00000 55
 
6.8%
0200000000 37
 
4.6%
070 7
 
0.9%
778 5
 
0.6%
777 5
 
0.6%
7539433 3
 
0.4%
775 3
 
0.4%
1500 2
 
0.2%
22346148 2
 
0.2%
Other values (452) 473
58.3%
2024-05-11T00:43:41.779288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1377
25.6%
2 1070
19.9%
7 510
 
9.5%
474
 
8.8%
3 363
 
6.7%
5 331
 
6.1%
1 300
 
5.6%
6 299
 
5.6%
8 284
 
5.3%
9 210
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4913
91.2%
Space Separator 474
 
8.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1377
28.0%
2 1070
21.8%
7 510
 
10.4%
3 363
 
7.4%
5 331
 
6.7%
1 300
 
6.1%
6 299
 
6.1%
8 284
 
5.8%
9 210
 
4.3%
4 169
 
3.4%
Space Separator
ValueCountFrequency (%)
474
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5387
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1377
25.6%
2 1070
19.9%
7 510
 
9.5%
474
 
8.8%
3 363
 
6.7%
5 331
 
6.1%
1 300
 
5.6%
6 299
 
5.6%
8 284
 
5.3%
9 210
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5387
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1377
25.6%
2 1070
19.9%
7 510
 
9.5%
474
 
8.8%
3 363
 
6.7%
5 331
 
6.1%
1 300
 
5.6%
6 299
 
5.6%
8 284
 
5.3%
9 210
 
3.9%
Distinct519
Distinct (%)80.1%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
2024-05-11T00:43:42.838791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length6
Mean length5.8564815
Min length3

Characters and Unicode

Total characters3795
Distinct characters12
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

Unique490 ?
Unique (%)75.6%

Sample

1st row165.00
2nd row.00
3rd row.00
4th row.00
5th row165.00
ValueCountFrequency (%)
00 94
 
14.5%
165.00 6
 
0.9%
394.32 4
 
0.6%
72.90 3
 
0.5%
330.00 3
 
0.5%
57.60 2
 
0.3%
310.00 2
 
0.3%
832.90 2
 
0.3%
335.14 2
 
0.3%
262.32 2
 
0.3%
Other values (509) 528
81.5%
2024-05-11T00:43:44.233915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 648
17.1%
0 632
16.7%
1 335
8.8%
2 314
8.3%
4 287
7.6%
3 275
7.2%
5 271
7.1%
6 238
 
6.3%
7 238
 
6.3%
9 235
 
6.2%
Other values (2) 322
8.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3050
80.4%
Other Punctuation 745
 
19.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 632
20.7%
1 335
11.0%
2 314
10.3%
4 287
9.4%
3 275
9.0%
5 271
8.9%
6 238
 
7.8%
7 238
 
7.8%
9 235
 
7.7%
8 225
 
7.4%
Other Punctuation
ValueCountFrequency (%)
. 648
87.0%
, 97
 
13.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3795
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 648
17.1%
0 632
16.7%
1 335
8.8%
2 314
8.3%
4 287
7.6%
3 275
7.2%
5 271
7.1%
6 238
 
6.3%
7 238
 
6.3%
9 235
 
6.2%
Other values (2) 322
8.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3795
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 648
17.1%
0 632
16.7%
1 335
8.8%
2 314
8.3%
4 287
7.6%
3 275
7.2%
5 271
7.1%
6 238
 
6.3%
7 238
 
6.3%
9 235
 
6.2%
Other values (2) 322
8.5%
Distinct170
Distinct (%)26.2%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
2024-05-11T00:43:45.131960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1851852
Min length6

Characters and Unicode

Total characters4008
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)8.6%

Sample

1st row100800
2nd row100420
3rd row100330
4th row100193
5th row100340
ValueCountFrequency (%)
100411 24
 
3.7%
100080 19
 
2.9%
100450 18
 
2.8%
100873 16
 
2.5%
100412 15
 
2.3%
100051 14
 
2.2%
100196 13
 
2.0%
100869 13
 
2.0%
100860 12
 
1.9%
100195 12
 
1.9%
Other values (160) 492
75.9%
2024-05-11T00:43:46.588212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1704
42.5%
1 964
24.1%
8 309
 
7.7%
4 190
 
4.7%
3 144
 
3.6%
2 144
 
3.6%
5 129
 
3.2%
- 120
 
3.0%
9 116
 
2.9%
6 113
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3888
97.0%
Dash Punctuation 120
 
3.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1704
43.8%
1 964
24.8%
8 309
 
7.9%
4 190
 
4.9%
3 144
 
3.7%
2 144
 
3.7%
5 129
 
3.3%
9 116
 
3.0%
6 113
 
2.9%
7 75
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 120
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4008
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1704
42.5%
1 964
24.1%
8 309
 
7.7%
4 190
 
4.7%
3 144
 
3.6%
2 144
 
3.6%
5 129
 
3.2%
- 120
 
3.0%
9 116
 
2.9%
6 113
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4008
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1704
42.5%
1 964
24.1%
8 309
 
7.7%
4 190
 
4.7%
3 144
 
3.6%
2 144
 
3.6%
5 129
 
3.2%
- 120
 
3.0%
9 116
 
2.9%
6 113
 
2.8%
Distinct606
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
2024-05-11T00:43:47.288336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length40
Mean length22.373457
Min length14

Characters and Unicode

Total characters14498
Distinct characters172
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique574 ?
Unique (%)88.6%

Sample

1st row서울특별시 중구 남대문로5가 14-5번지
2nd row서울특별시 중구 무학동 28-0번지
3rd row서울특별시 중구 주교동 111-0번지
4th row서울특별시 중구 을지로3가 291-45번지
5th row서울특별시 중구 산림동 84-4번지
ValueCountFrequency (%)
서울특별시 648
23.0%
중구 648
23.0%
신당동 54
 
1.9%
회현동1가 44
 
1.6%
황학동 41
 
1.5%
광희동1가 31
 
1.1%
남대문로5가 27
 
1.0%
충무로2가 27
 
1.0%
북창동 25
 
0.9%
을지로6가 22
 
0.8%
Other values (765) 1248
44.3%
2024-05-11T00:43:48.440305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2633
18.2%
1 772
 
5.3%
665
 
4.6%
650
 
4.5%
649
 
4.5%
649
 
4.5%
648
 
4.5%
648
 
4.5%
648
 
4.5%
- 540
 
3.7%
Other values (162) 5996
41.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8106
55.9%
Decimal Number 3044
 
21.0%
Space Separator 2633
 
18.2%
Dash Punctuation 540
 
3.7%
Math Symbol 73
 
0.5%
Other Punctuation 64
 
0.4%
Uppercase Letter 18
 
0.1%
Lowercase Letter 10
 
0.1%
Open Punctuation 5
 
< 0.1%
Close Punctuation 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
665
 
8.2%
650
 
8.0%
649
 
8.0%
649
 
8.0%
648
 
8.0%
648
 
8.0%
648
 
8.0%
494
 
6.1%
461
 
5.7%
397
 
4.9%
Other values (124) 2197
27.1%
Uppercase Letter
ValueCountFrequency (%)
F 3
16.7%
B 3
16.7%
I 2
11.1%
A 1
 
5.6%
K 1
 
5.6%
O 1
 
5.6%
J 1
 
5.6%
S 1
 
5.6%
N 1
 
5.6%
T 1
 
5.6%
Other values (3) 3
16.7%
Decimal Number
ValueCountFrequency (%)
1 772
25.4%
2 536
17.6%
3 337
11.1%
5 282
 
9.3%
4 248
 
8.1%
0 212
 
7.0%
6 181
 
5.9%
7 165
 
5.4%
8 157
 
5.2%
9 154
 
5.1%
Lowercase Letter
ValueCountFrequency (%)
d 2
20.0%
n 2
20.0%
i 2
20.0%
l 1
10.0%
a 1
10.0%
u 1
10.0%
g 1
10.0%
Other Punctuation
ValueCountFrequency (%)
, 61
95.3%
/ 2
 
3.1%
? 1
 
1.6%
Space Separator
ValueCountFrequency (%)
2633
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 540
100.0%
Math Symbol
ValueCountFrequency (%)
~ 73
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8106
55.9%
Common 6364
43.9%
Latin 28
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
665
 
8.2%
650
 
8.0%
649
 
8.0%
649
 
8.0%
648
 
8.0%
648
 
8.0%
648
 
8.0%
494
 
6.1%
461
 
5.7%
397
 
4.9%
Other values (124) 2197
27.1%
Latin
ValueCountFrequency (%)
F 3
 
10.7%
B 3
 
10.7%
I 2
 
7.1%
d 2
 
7.1%
n 2
 
7.1%
i 2
 
7.1%
A 1
 
3.6%
K 1
 
3.6%
l 1
 
3.6%
O 1
 
3.6%
Other values (10) 10
35.7%
Common
ValueCountFrequency (%)
2633
41.4%
1 772
 
12.1%
- 540
 
8.5%
2 536
 
8.4%
3 337
 
5.3%
5 282
 
4.4%
4 248
 
3.9%
0 212
 
3.3%
6 181
 
2.8%
7 165
 
2.6%
Other values (8) 458
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8106
55.9%
ASCII 6392
44.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2633
41.2%
1 772
 
12.1%
- 540
 
8.4%
2 536
 
8.4%
3 337
 
5.3%
5 282
 
4.4%
4 248
 
3.9%
0 212
 
3.3%
6 181
 
2.8%
7 165
 
2.6%
Other values (28) 486
 
7.6%
Hangul
ValueCountFrequency (%)
665
 
8.2%
650
 
8.0%
649
 
8.0%
649
 
8.0%
648
 
8.0%
648
 
8.0%
648
 
8.0%
494
 
6.1%
461
 
5.7%
397
 
4.9%
Other values (124) 2197
27.1%

도로명주소
Text

MISSING 

Distinct436
Distinct (%)97.8%
Missing202
Missing (%)31.2%
Memory size5.2 KiB
2024-05-11T00:43:49.180816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length43
Mean length28.737668
Min length20

Characters and Unicode

Total characters12817
Distinct characters184
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique426 ?
Unique (%)95.5%

Sample

1st row서울특별시 중구 창경궁로5가길 27-4 (산림동)
2nd row서울특별시 중구 퇴계로8길 2-1 (회현동1가)
3rd row서울특별시 중구 퇴계로10길 20-3 (회현동1가)
4th row서울특별시 중구 퇴계로 176 (남학동)
5th row서울특별시 중구 세종대로2길 17 (남대문로5가)
ValueCountFrequency (%)
서울특별시 446
 
18.0%
중구 446
 
18.0%
퇴계로 42
 
1.7%
신당동 32
 
1.3%
회현동1가 28
 
1.1%
충무로2가 25
 
1.0%
광희동1가 22
 
0.9%
황학동 21
 
0.8%
북창동 19
 
0.8%
명동8가길 18
 
0.7%
Other values (634) 1385
55.8%
2024-05-11T00:43:50.571203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2039
 
15.9%
537
 
4.2%
1 516
 
4.0%
457
 
3.6%
450
 
3.5%
449
 
3.5%
449
 
3.5%
( 448
 
3.5%
) 448
 
3.5%
447
 
3.5%
Other values (174) 6577
51.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6986
54.5%
Decimal Number 2323
 
18.1%
Space Separator 2039
 
15.9%
Open Punctuation 448
 
3.5%
Close Punctuation 448
 
3.5%
Other Punctuation 292
 
2.3%
Dash Punctuation 142
 
1.1%
Math Symbol 112
 
0.9%
Uppercase Letter 17
 
0.1%
Lowercase Letter 10
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
537
 
7.7%
457
 
6.5%
450
 
6.4%
449
 
6.4%
449
 
6.4%
447
 
6.4%
446
 
6.4%
446
 
6.4%
390
 
5.6%
322
 
4.6%
Other values (136) 2593
37.1%
Uppercase Letter
ValueCountFrequency (%)
B 3
17.6%
F 3
17.6%
A 1
 
5.9%
K 1
 
5.9%
J 1
 
5.9%
S 1
 
5.9%
I 1
 
5.9%
N 1
 
5.9%
T 1
 
5.9%
O 1
 
5.9%
Other values (3) 3
17.6%
Decimal Number
ValueCountFrequency (%)
1 516
22.2%
2 421
18.1%
3 297
12.8%
4 233
10.0%
5 221
9.5%
6 148
 
6.4%
7 136
 
5.9%
8 134
 
5.8%
0 118
 
5.1%
9 99
 
4.3%
Lowercase Letter
ValueCountFrequency (%)
i 2
20.0%
n 2
20.0%
d 2
20.0%
a 1
10.0%
u 1
10.0%
l 1
10.0%
g 1
10.0%
Other Punctuation
ValueCountFrequency (%)
, 290
99.3%
/ 1
 
0.3%
? 1
 
0.3%
Space Separator
ValueCountFrequency (%)
2039
100.0%
Open Punctuation
ValueCountFrequency (%)
( 448
100.0%
Close Punctuation
ValueCountFrequency (%)
) 448
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 142
100.0%
Math Symbol
ValueCountFrequency (%)
~ 112
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6986
54.5%
Common 5804
45.3%
Latin 27
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
537
 
7.7%
457
 
6.5%
450
 
6.4%
449
 
6.4%
449
 
6.4%
447
 
6.4%
446
 
6.4%
446
 
6.4%
390
 
5.6%
322
 
4.6%
Other values (136) 2593
37.1%
Latin
ValueCountFrequency (%)
B 3
 
11.1%
F 3
 
11.1%
i 2
 
7.4%
n 2
 
7.4%
d 2
 
7.4%
A 1
 
3.7%
K 1
 
3.7%
J 1
 
3.7%
a 1
 
3.7%
S 1
 
3.7%
Other values (10) 10
37.0%
Common
ValueCountFrequency (%)
2039
35.1%
1 516
 
8.9%
( 448
 
7.7%
) 448
 
7.7%
2 421
 
7.3%
3 297
 
5.1%
, 290
 
5.0%
4 233
 
4.0%
5 221
 
3.8%
6 148
 
2.5%
Other values (8) 743
 
12.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6986
54.5%
ASCII 5831
45.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2039
35.0%
1 516
 
8.8%
( 448
 
7.7%
) 448
 
7.7%
2 421
 
7.2%
3 297
 
5.1%
, 290
 
5.0%
4 233
 
4.0%
5 221
 
3.8%
6 148
 
2.5%
Other values (28) 770
 
13.2%
Hangul
ValueCountFrequency (%)
537
 
7.7%
457
 
6.5%
450
 
6.4%
449
 
6.4%
449
 
6.4%
447
 
6.4%
446
 
6.4%
446
 
6.4%
390
 
5.6%
322
 
4.6%
Other values (136) 2593
37.1%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct84
Distinct (%)19.0%
Missing206
Missing (%)31.8%
Infinite0
Infinite (%)0.0%
Mean4564.5385
Minimum4502
Maximum4637
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 KiB
2024-05-11T00:43:51.006540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4502
5-th percentile4517.1
Q14537
median4557
Q34577
95-th percentile4633.95
Maximum4637
Range135
Interquartile range (IQR)40

Descriptive statistics

Standard deviation36.932796
Coefficient of variation (CV)0.0080912443
Kurtosis-0.69767455
Mean4564.5385
Median Absolute Deviation (MAD)20
Skewness0.65114199
Sum2017526
Variance1364.0314
MonotonicityNot monotonic
2024-05-11T00:43:51.539329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4561 30
 
4.6%
4537 28
 
4.3%
4526 28
 
4.3%
4536 20
 
3.1%
4634 16
 
2.5%
4565 16
 
2.5%
4559 10
 
1.5%
4547 9
 
1.4%
4534 9
 
1.4%
4556 9
 
1.4%
Other values (74) 267
41.2%
(Missing) 206
31.8%
ValueCountFrequency (%)
4502 3
0.5%
4506 1
 
0.2%
4507 5
0.8%
4508 4
0.6%
4510 1
 
0.2%
4511 2
 
0.3%
4512 3
0.5%
4513 1
 
0.2%
4515 1
 
0.2%
4516 1
 
0.2%
ValueCountFrequency (%)
4637 5
 
0.8%
4635 2
 
0.3%
4634 16
2.5%
4633 8
1.2%
4632 1
 
0.2%
4631 9
1.4%
4630 6
 
0.9%
4629 4
 
0.6%
4627 5
 
0.8%
4626 2
 
0.3%
Distinct614
Distinct (%)94.8%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
2024-05-11T00:43:52.292626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length35
Mean length7.191358
Min length2

Characters and Unicode

Total characters4660
Distinct characters374
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

Unique583 ?
Unique (%)90.0%

Sample

1st row궁전여관
2nd row동화
3rd row황평
4th row을지장
5th row화성여관
ValueCountFrequency (%)
호텔 47
 
4.7%
명동 45
 
4.5%
서울 24
 
2.4%
동대문 13
 
1.3%
호스텔 10
 
1.0%
게스트하우스 9
 
0.9%
hotel 9
 
0.9%
레지던스 7
 
0.7%
스위트 6
 
0.6%
stay 6
 
0.6%
Other values (699) 818
82.3%
2024-05-11T00:43:53.717874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
346
 
7.4%
233
 
5.0%
210
 
4.5%
187
 
4.0%
146
 
3.1%
142
 
3.0%
127
 
2.7%
106
 
2.3%
94
 
2.0%
82
 
1.8%
Other values (364) 2987
64.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3476
74.6%
Space Separator 346
 
7.4%
Lowercase Letter 320
 
6.9%
Uppercase Letter 303
 
6.5%
Open Punctuation 71
 
1.5%
Close Punctuation 71
 
1.5%
Decimal Number 57
 
1.2%
Dash Punctuation 6
 
0.1%
Other Punctuation 6
 
0.1%
Letter Number 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
233
 
6.7%
210
 
6.0%
187
 
5.4%
146
 
4.2%
142
 
4.1%
127
 
3.7%
106
 
3.0%
94
 
2.7%
82
 
2.4%
81
 
2.3%
Other values (299) 2068
59.5%
Uppercase Letter
ValueCountFrequency (%)
T 30
 
9.9%
H 28
 
9.2%
L 25
 
8.3%
E 25
 
8.3%
O 23
 
7.6%
S 19
 
6.3%
I 18
 
5.9%
A 18
 
5.9%
M 14
 
4.6%
N 13
 
4.3%
Other values (14) 90
29.7%
Lowercase Letter
ValueCountFrequency (%)
o 51
15.9%
e 38
11.9%
t 32
10.0%
n 31
9.7%
a 24
 
7.5%
l 20
 
6.2%
s 19
 
5.9%
g 16
 
5.0%
y 14
 
4.4%
m 12
 
3.8%
Other values (12) 63
19.7%
Decimal Number
ValueCountFrequency (%)
2 17
29.8%
5 10
17.5%
1 9
15.8%
7 6
 
10.5%
4 5
 
8.8%
3 4
 
7.0%
8 3
 
5.3%
9 2
 
3.5%
6 1
 
1.8%
Other Punctuation
ValueCountFrequency (%)
& 2
33.3%
. 2
33.3%
' 1
16.7%
, 1
16.7%
Letter Number
ValueCountFrequency (%)
3
75.0%
1
 
25.0%
Space Separator
ValueCountFrequency (%)
346
100.0%
Open Punctuation
ValueCountFrequency (%)
( 71
100.0%
Close Punctuation
ValueCountFrequency (%)
) 71
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3476
74.6%
Latin 627
 
13.5%
Common 557
 
12.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
233
 
6.7%
210
 
6.0%
187
 
5.4%
146
 
4.2%
142
 
4.1%
127
 
3.7%
106
 
3.0%
94
 
2.7%
82
 
2.4%
81
 
2.3%
Other values (299) 2068
59.5%
Latin
ValueCountFrequency (%)
o 51
 
8.1%
e 38
 
6.1%
t 32
 
5.1%
n 31
 
4.9%
T 30
 
4.8%
H 28
 
4.5%
L 25
 
4.0%
E 25
 
4.0%
a 24
 
3.8%
O 23
 
3.7%
Other values (38) 320
51.0%
Common
ValueCountFrequency (%)
346
62.1%
( 71
 
12.7%
) 71
 
12.7%
2 17
 
3.1%
5 10
 
1.8%
1 9
 
1.6%
7 6
 
1.1%
- 6
 
1.1%
4 5
 
0.9%
3 4
 
0.7%
Other values (7) 12
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3476
74.6%
ASCII 1180
 
25.3%
Number Forms 4
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
346
29.3%
( 71
 
6.0%
) 71
 
6.0%
o 51
 
4.3%
e 38
 
3.2%
t 32
 
2.7%
n 31
 
2.6%
T 30
 
2.5%
H 28
 
2.4%
L 25
 
2.1%
Other values (53) 457
38.7%
Hangul
ValueCountFrequency (%)
233
 
6.7%
210
 
6.0%
187
 
5.4%
146
 
4.2%
142
 
4.1%
127
 
3.7%
106
 
3.0%
94
 
2.7%
82
 
2.4%
81
 
2.3%
Other values (299) 2068
59.5%
Number Forms
ValueCountFrequency (%)
3
75.0%
1
 
25.0%
Distinct516
Distinct (%)79.6%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
Minimum1999-06-25 00:00:00
Maximum2024-05-08 09:16:44
2024-05-11T00:43:54.415395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:43:54.872676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
I
357 
U
291 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 357
55.1%
U 291
44.9%

Length

2024-05-11T00:43:55.312229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:43:55.866565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 357
55.1%
u 291
44.9%
Distinct232
Distinct (%)35.8%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:05:00
2024-05-11T00:43:56.476099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:43:57.159974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct6
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
여관업
336 
관광호텔
106 
일반호텔
83 
여인숙업
57 
숙박업(생활)
39 

Length

Max length7
Median length3
Mean length3.7453704
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row여관업
2nd row여인숙업
3rd row여인숙업
4th row여관업
5th row여관업

Common Values

ValueCountFrequency (%)
여관업 336
51.9%
관광호텔 106
 
16.4%
일반호텔 83
 
12.8%
여인숙업 57
 
8.8%
숙박업(생활) 39
 
6.0%
숙박업 기타 27
 
4.2%

Length

2024-05-11T00:43:57.918407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:43:58.378821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 336
49.8%
관광호텔 106
 
15.7%
일반호텔 83
 
12.3%
여인숙업 57
 
8.4%
숙박업(생활 39
 
5.8%
숙박업 27
 
4.0%
기타 27
 
4.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct413
Distinct (%)83.9%
Missing156
Missing (%)24.1%
Infinite0
Infinite (%)0.0%
Mean199390.97
Minimum197065.35
Maximum201980.07
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 KiB
2024-05-11T00:43:58.841487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum197065.35
5-th percentile197627.26
Q1198359.59
median199245.26
Q3200458.21
95-th percentile201579.83
Maximum201980.07
Range4914.7251
Interquartile range (IQR)2098.6162

Descriptive statistics

Standard deviation1276.8679
Coefficient of variation (CV)0.0064038403
Kurtosis-0.954087
Mean199390.97
Median Absolute Deviation (MAD)1069.5159
Skewness0.25621452
Sum98100357
Variance1630391.7
MonotonicityNot monotonic
2024-05-11T00:43:59.308167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
199397.013822421 6
 
0.9%
198562.632745775 5
 
0.8%
199345.466097151 5
 
0.8%
198636.142124311 5
 
0.8%
197462.198757043 4
 
0.6%
201540.899631646 4
 
0.6%
199367.549270744 3
 
0.5%
198113.932337497 3
 
0.5%
198841.348970952 3
 
0.5%
197986.895692742 3
 
0.5%
Other values (403) 451
69.6%
(Missing) 156
 
24.1%
ValueCountFrequency (%)
197065.349004477 1
0.2%
197075.630934475 1
0.2%
197079.818300026 1
0.2%
197082.952948543 1
0.2%
197084.506700916 1
0.2%
197087.48042135 1
0.2%
197096.20089389 1
0.2%
197102.760762166 1
0.2%
197133.181826761 1
0.2%
197134.4537839 1
0.2%
ValueCountFrequency (%)
201980.074138496 1
0.2%
201962.64374267 1
0.2%
201959.495784099 1
0.2%
201950.057171173 1
0.2%
201949.390409959 1
0.2%
201933.988731333 1
0.2%
201922.608948858 2
0.3%
201914.067926656 1
0.2%
201862.528820135 1
0.2%
201830.544707615 1
0.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct413
Distinct (%)83.9%
Missing156
Missing (%)24.1%
Infinite0
Infinite (%)0.0%
Mean451169.97
Minimum449646.64
Maximum452008.36
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 KiB
2024-05-11T00:43:59.869965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum449646.64
5-th percentile450529.64
Q1450949.23
median451204.73
Q3451450.88
95-th percentile451752.15
Maximum452008.36
Range2361.7235
Interquartile range (IQR)501.65039

Descriptive statistics

Standard deviation398.59245
Coefficient of variation (CV)0.00088346405
Kurtosis0.66031603
Mean451169.97
Median Absolute Deviation (MAD)247.22638
Skewness-0.61819749
Sum2.2197563 × 108
Variance158875.94
MonotonicityNot monotonic
2024-05-11T00:44:00.328677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
451070.763689185 6
 
0.9%
450975.116406048 5
 
0.8%
451233.36978053 5
 
0.8%
451325.229841133 5
 
0.8%
450878.211786274 4
 
0.6%
451623.103928058 4
 
0.6%
451152.070282241 3
 
0.5%
450944.445248143 3
 
0.5%
451075.90120027 3
 
0.5%
451089.662576161 3
 
0.5%
Other values (403) 451
69.6%
(Missing) 156
 
24.1%
ValueCountFrequency (%)
449646.639622415 2
0.3%
449705.528993868 1
0.2%
449784.759561479 1
0.2%
449809.744684888 1
0.2%
450160.928263879 1
0.2%
450231.27615702 2
0.3%
450266.263776586 1
0.2%
450337.580626313 1
0.2%
450376.322126299 1
0.2%
450378.984261156 1
0.2%
ValueCountFrequency (%)
452008.363110583 1
0.2%
452007.833351759 1
0.2%
451956.230791489 1
0.2%
451945.363649973 2
0.3%
451930.591349609 1
0.2%
451905.283137586 1
0.2%
451869.434784339 1
0.2%
451845.46073582 1
0.2%
451837.481623546 1
0.2%
451836.610001238 1
0.2%

위생업태명
Categorical

Distinct7
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
여관업
280 
<NA>
184 
관광호텔
66 
여인숙업
55 
일반호텔
43 
Other values (2)
 
20

Length

Max length7
Median length4
Mean length3.6419753
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row여관업
2nd row여인숙업
3rd row여인숙업
4th row여관업
5th row여관업

Common Values

ValueCountFrequency (%)
여관업 280
43.2%
<NA> 184
28.4%
관광호텔 66
 
10.2%
여인숙업 55
 
8.5%
일반호텔 43
 
6.6%
숙박업 기타 12
 
1.9%
숙박업(생활) 8
 
1.2%

Length

2024-05-11T00:44:00.796367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:44:01.190457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 280
42.4%
na 184
27.9%
관광호텔 66
 
10.0%
여인숙업 55
 
8.3%
일반호텔 43
 
6.5%
숙박업 12
 
1.8%
기타 12
 
1.8%
숙박업(생활 8
 
1.2%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct23
Distinct (%)5.0%
Missing184
Missing (%)28.4%
Infinite0
Infinite (%)0.0%
Mean2.3297414
Minimum0
Maximum27
Zeros243
Zeros (%)37.5%
Negative0
Negative (%)0.0%
Memory size5.8 KiB
2024-05-11T00:44:01.513478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile9.7
Maximum27
Range27
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.9882521
Coefficient of variation (CV)1.7118862
Kurtosis12.573521
Mean2.3297414
Median Absolute Deviation (MAD)0
Skewness3.1739759
Sum1081
Variance15.906155
MonotonicityNot monotonic
2024-05-11T00:44:01.821480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 243
37.5%
3 60
 
9.3%
2 43
 
6.6%
4 38
 
5.9%
5 24
 
3.7%
1 11
 
1.7%
6 10
 
1.5%
7 6
 
0.9%
8 5
 
0.8%
10 5
 
0.8%
Other values (13) 19
 
2.9%
(Missing) 184
28.4%
ValueCountFrequency (%)
0 243
37.5%
1 11
 
1.7%
2 43
 
6.6%
3 60
 
9.3%
4 38
 
5.9%
5 24
 
3.7%
6 10
 
1.5%
7 6
 
0.9%
8 5
 
0.8%
10 5
 
0.8%
ValueCountFrequency (%)
27 2
0.3%
23 1
0.2%
22 2
0.3%
20 1
0.2%
19 2
0.3%
18 1
0.2%
17 1
0.2%
16 2
0.3%
15 2
0.3%
14 2
0.3%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)1.7%
Missing184
Missing (%)28.4%
Infinite0
Infinite (%)0.0%
Mean0.2262931
Minimum0
Maximum10
Zeros418
Zeros (%)64.5%
Negative0
Negative (%)0.0%
Memory size5.8 KiB
2024-05-11T00:44:02.056458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum10
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.89543988
Coefficient of variation (CV)3.9569915
Kurtosis42.603157
Mean0.2262931
Median Absolute Deviation (MAD)0
Skewness5.7753982
Sum105
Variance0.80181258
MonotonicityNot monotonic
2024-05-11T00:44:02.400017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 418
64.5%
1 24
 
3.7%
3 7
 
1.1%
2 6
 
0.9%
5 4
 
0.6%
4 3
 
0.5%
10 1
 
0.2%
6 1
 
0.2%
(Missing) 184
28.4%
ValueCountFrequency (%)
0 418
64.5%
1 24
 
3.7%
2 6
 
0.9%
3 7
 
1.1%
4 3
 
0.5%
5 4
 
0.6%
6 1
 
0.2%
10 1
 
0.2%
ValueCountFrequency (%)
10 1
 
0.2%
6 1
 
0.2%
5 4
 
0.6%
4 3
 
0.5%
3 7
 
1.1%
2 6
 
0.9%
1 24
 
3.7%
0 418
64.5%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct17
Distinct (%)3.7%
Missing184
Missing (%)28.4%
Infinite0
Infinite (%)0.0%
Mean1.2068966
Minimum0
Maximum21
Zeros319
Zeros (%)49.2%
Negative0
Negative (%)0.0%
Memory size5.8 KiB
2024-05-11T00:44:02.691227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile7
Maximum21
Range21
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.7424107
Coefficient of variation (CV)2.2722831
Kurtosis15.670457
Mean1.2068966
Median Absolute Deviation (MAD)0
Skewness3.5666309
Sum560
Variance7.5208163
MonotonicityNot monotonic
2024-05-11T00:44:03.069631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 319
49.2%
1 40
 
6.2%
2 29
 
4.5%
3 25
 
3.9%
4 14
 
2.2%
5 8
 
1.2%
8 5
 
0.8%
6 4
 
0.6%
7 4
 
0.6%
9 4
 
0.6%
Other values (7) 12
 
1.9%
(Missing) 184
28.4%
ValueCountFrequency (%)
0 319
49.2%
1 40
 
6.2%
2 29
 
4.5%
3 25
 
3.9%
4 14
 
2.2%
5 8
 
1.2%
6 4
 
0.6%
7 4
 
0.6%
8 5
 
0.8%
9 4
 
0.6%
ValueCountFrequency (%)
21 1
 
0.2%
18 1
 
0.2%
17 2
 
0.3%
14 1
 
0.2%
12 2
 
0.3%
11 2
 
0.3%
10 3
0.5%
9 4
0.6%
8 5
0.8%
7 4
0.6%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct24
Distinct (%)5.2%
Missing184
Missing (%)28.4%
Infinite0
Infinite (%)0.0%
Mean3.137931
Minimum0
Maximum25
Zeros249
Zeros (%)38.4%
Negative0
Negative (%)0.0%
Memory size5.8 KiB
2024-05-11T00:44:03.463674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34
95-th percentile15
Maximum25
Range25
Interquartile range (IQR)4

Descriptive statistics

Standard deviation5.0682539
Coefficient of variation (CV)1.6151578
Kurtosis4.6687138
Mean3.137931
Median Absolute Deviation (MAD)0
Skewness2.179178
Sum1456
Variance25.687197
MonotonicityNot monotonic
2024-05-11T00:44:03.864594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 249
38.4%
3 41
 
6.3%
4 30
 
4.6%
5 29
 
4.5%
2 24
 
3.7%
6 13
 
2.0%
8 12
 
1.9%
7 8
 
1.2%
20 8
 
1.2%
1 7
 
1.1%
Other values (14) 43
 
6.6%
(Missing) 184
28.4%
ValueCountFrequency (%)
0 249
38.4%
1 7
 
1.1%
2 24
 
3.7%
3 41
 
6.3%
4 30
 
4.6%
5 29
 
4.5%
6 13
 
2.0%
7 8
 
1.2%
8 12
 
1.9%
9 6
 
0.9%
ValueCountFrequency (%)
25 3
 
0.5%
22 2
 
0.3%
21 1
 
0.2%
20 8
1.2%
19 2
 
0.3%
18 3
 
0.5%
17 2
 
0.3%
16 2
 
0.3%
15 2
 
0.3%
14 5
0.8%

사용시작지하층
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)1.3%
Missing184
Missing (%)28.4%
Infinite0
Infinite (%)0.0%
Mean0.1012931
Minimum0
Maximum5
Zeros437
Zeros (%)67.4%
Negative0
Negative (%)0.0%
Memory size5.8 KiB
2024-05-11T00:44:04.229715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.50105553
Coefficient of variation (CV)4.9465907
Kurtosis47.696323
Mean0.1012931
Median Absolute Deviation (MAD)0
Skewness6.5043433
Sum47
Variance0.25105664
MonotonicityNot monotonic
2024-05-11T00:44:04.616889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 437
67.4%
1 18
 
2.8%
2 3
 
0.5%
4 3
 
0.5%
3 2
 
0.3%
5 1
 
0.2%
(Missing) 184
28.4%
ValueCountFrequency (%)
0 437
67.4%
1 18
 
2.8%
2 3
 
0.5%
3 2
 
0.3%
4 3
 
0.5%
5 1
 
0.2%
ValueCountFrequency (%)
5 1
 
0.2%
4 3
 
0.5%
3 2
 
0.3%
2 3
 
0.5%
1 18
 
2.8%
0 437
67.4%

사용끝지하층
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)1.5%
Missing184
Missing (%)28.4%
Infinite0
Infinite (%)0.0%
Mean0.13146552
Minimum0
Maximum9
Zeros439
Zeros (%)67.7%
Negative0
Negative (%)0.0%
Memory size5.8 KiB
2024-05-11T00:44:04.969354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum9
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.70324856
Coefficient of variation (CV)5.3493005
Kurtosis70.799587
Mean0.13146552
Median Absolute Deviation (MAD)0
Skewness7.5568505
Sum61
Variance0.49455854
MonotonicityNot monotonic
2024-05-11T00:44:05.313268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 439
67.7%
1 11
 
1.7%
2 5
 
0.8%
4 3
 
0.5%
3 3
 
0.5%
5 2
 
0.3%
9 1
 
0.2%
(Missing) 184
28.4%
ValueCountFrequency (%)
0 439
67.7%
1 11
 
1.7%
2 5
 
0.8%
3 3
 
0.5%
4 3
 
0.5%
5 2
 
0.3%
9 1
 
0.2%
ValueCountFrequency (%)
9 1
 
0.2%
5 2
 
0.3%
4 3
 
0.5%
3 3
 
0.5%
2 5
 
0.8%
1 11
 
1.7%
0 439
67.7%

한실수
Real number (ℝ)

MISSING  ZEROS 

Distinct23
Distinct (%)5.0%
Missing184
Missing (%)28.4%
Infinite0
Infinite (%)0.0%
Mean1.424569
Minimum0
Maximum78
Zeros382
Zeros (%)59.0%
Negative0
Negative (%)0.0%
Memory size5.8 KiB
2024-05-11T00:44:05.652231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile10
Maximum78
Range78
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5.2128268
Coefficient of variation (CV)3.6592309
Kurtosis104.3176
Mean1.424569
Median Absolute Deviation (MAD)0
Skewness8.3357406
Sum661
Variance27.173564
MonotonicityNot monotonic
2024-05-11T00:44:06.076039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 382
59.0%
1 13
 
2.0%
2 12
 
1.9%
3 10
 
1.5%
7 5
 
0.8%
10 5
 
0.8%
12 5
 
0.8%
5 5
 
0.8%
17 4
 
0.6%
8 4
 
0.6%
Other values (13) 19
 
2.9%
(Missing) 184
28.4%
ValueCountFrequency (%)
0 382
59.0%
1 13
 
2.0%
2 12
 
1.9%
3 10
 
1.5%
4 2
 
0.3%
5 5
 
0.8%
6 3
 
0.5%
7 5
 
0.8%
8 4
 
0.6%
9 2
 
0.3%
ValueCountFrequency (%)
78 1
 
0.2%
30 1
 
0.2%
24 1
 
0.2%
22 1
 
0.2%
19 1
 
0.2%
18 2
0.3%
17 4
0.6%
16 1
 
0.2%
15 1
 
0.2%
14 1
 
0.2%

양실수
Real number (ℝ)

MISSING  ZEROS 

Distinct103
Distinct (%)22.2%
Missing184
Missing (%)28.4%
Infinite0
Infinite (%)0.0%
Mean35.25431
Minimum0
Maximum479
Zeros147
Zeros (%)22.7%
Negative0
Negative (%)0.0%
Memory size5.8 KiB
2024-05-11T00:44:06.527105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median12
Q325
95-th percentile218.4
Maximum479
Range479
Interquartile range (IQR)25

Descriptive statistics

Standard deviation74.67687
Coefficient of variation (CV)2.1182338
Kurtosis12.435363
Mean35.25431
Median Absolute Deviation (MAD)12
Skewness3.4501844
Sum16358
Variance5576.635
MonotonicityNot monotonic
2024-05-11T00:44:06.997305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 147
22.7%
15 19
 
2.9%
12 19
 
2.9%
11 17
 
2.6%
13 17
 
2.6%
10 16
 
2.5%
16 12
 
1.9%
20 11
 
1.7%
17 10
 
1.5%
25 9
 
1.4%
Other values (93) 187
28.9%
(Missing) 184
28.4%
ValueCountFrequency (%)
0 147
22.7%
1 3
 
0.5%
3 3
 
0.5%
4 5
 
0.8%
5 2
 
0.3%
6 5
 
0.8%
7 8
 
1.2%
8 7
 
1.1%
9 8
 
1.2%
10 16
 
2.5%
ValueCountFrequency (%)
479 1
0.2%
463 1
0.2%
409 1
0.2%
408 2
0.3%
352 1
0.2%
339 1
0.2%
334 1
0.2%
331 2
0.3%
312 1
0.2%
302 1
0.2%

욕실수
Real number (ℝ)

MISSING  ZEROS 

Distinct20
Distinct (%)4.3%
Missing184
Missing (%)28.4%
Infinite0
Infinite (%)0.0%
Mean1.3081897
Minimum0
Maximum95
Zeros429
Zeros (%)66.2%
Negative0
Negative (%)0.0%
Memory size5.8 KiB
2024-05-11T00:44:07.419745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile10
Maximum95
Range95
Interquartile range (IQR)0

Descriptive statistics

Standard deviation6.2193402
Coefficient of variation (CV)4.7541579
Kurtosis116.05388
Mean1.3081897
Median Absolute Deviation (MAD)0
Skewness9.0391945
Sum607
Variance38.680192
MonotonicityNot monotonic
2024-05-11T00:44:07.900526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0 429
66.2%
16 4
 
0.6%
10 4
 
0.6%
9 3
 
0.5%
12 3
 
0.5%
6 3
 
0.5%
7 2
 
0.3%
26 2
 
0.3%
8 2
 
0.3%
17 2
 
0.3%
Other values (10) 10
 
1.5%
(Missing) 184
28.4%
ValueCountFrequency (%)
0 429
66.2%
6 3
 
0.5%
7 2
 
0.3%
8 2
 
0.3%
9 3
 
0.5%
10 4
 
0.6%
11 1
 
0.2%
12 3
 
0.5%
16 4
 
0.6%
17 2
 
0.3%
ValueCountFrequency (%)
95 1
0.2%
34 1
0.2%
30 1
0.2%
28 1
0.2%
26 2
0.3%
24 1
0.2%
23 1
0.2%
22 1
0.2%
21 1
0.2%
18 1
0.2%

발한실여부
Boolean

MISSING 

Distinct2
Distinct (%)0.4%
Missing184
Missing (%)28.4%
Memory size1.4 KiB
False
243 
True
221 
(Missing)
184 
ValueCountFrequency (%)
False 243
37.5%
True 221
34.1%
(Missing) 184
28.4%
2024-05-11T00:44:08.253901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
0
461 
<NA>
184 
1
 
1
36
 
1
12
 
1

Length

Max length4
Median length1
Mean length1.8549383
Min length1

Unique

Unique3 ?
Unique (%)0.5%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 461
71.1%
<NA> 184
 
28.4%
1 1
 
0.2%
36 1
 
0.2%
12 1
 
0.2%

Length

2024-05-11T00:44:08.722639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:44:09.091454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 461
71.1%
na 184
 
28.4%
1 1
 
0.2%
36 1
 
0.2%
12 1
 
0.2%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing648
Missing (%)100.0%
Memory size5.8 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing648
Missing (%)100.0%
Memory size5.8 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing648
Missing (%)100.0%
Memory size5.8 KiB
Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
<NA>
459 
임대
98 
자가
91 

Length

Max length4
Median length4
Mean length3.4166667
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 459
70.8%
임대 98
 
15.1%
자가 91
 
14.0%

Length

2024-05-11T00:44:09.522621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:44:10.042000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 459
70.8%
임대 98
 
15.1%
자가 91
 
14.0%

세탁기수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
0
464 
<NA>
184 

Length

Max length4
Median length1
Mean length1.8518519
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 464
71.6%
<NA> 184
 
28.4%

Length

2024-05-11T00:44:10.483072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:44:10.861693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 464
71.6%
na 184
 
28.4%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
0
464 
<NA>
184 

Length

Max length4
Median length1
Mean length1.8518519
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 464
71.6%
<NA> 184
 
28.4%

Length

2024-05-11T00:44:11.332674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:44:11.684923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 464
71.6%
na 184
 
28.4%
Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
0
463 
<NA>
184 
8
 
1

Length

Max length4
Median length1
Mean length1.8518519
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 463
71.5%
<NA> 184
 
28.4%
8 1
 
0.2%

Length

2024-05-11T00:44:12.133103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:44:13.148083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 463
71.5%
na 184
 
28.4%
8 1
 
0.2%

회수건조수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
0
464 
<NA>
184 

Length

Max length4
Median length1
Mean length1.8518519
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 464
71.6%
<NA> 184
 
28.4%

Length

2024-05-11T00:44:13.553504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:44:13.927642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 464
71.6%
na 184
 
28.4%

침대수
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
0
464 
<NA>
184 

Length

Max length4
Median length1
Mean length1.8518519
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 464
71.6%
<NA> 184
 
28.4%

Length

2024-05-11T00:44:14.511708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:44:15.111961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 464
71.6%
na 184
 
28.4%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.4%
Missing184
Missing (%)28.4%
Memory size1.4 KiB
False
461 
True
 
3
(Missing)
184 
ValueCountFrequency (%)
False 461
71.1%
True 3
 
0.5%
(Missing) 184
 
28.4%
2024-05-11T00:44:15.635229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
030100003010000-201-1949-0007119490705<NA>3폐업2폐업20060327<NA><NA><NA>7579632165.00100800서울특별시 중구 남대문로5가 14-5번지<NA><NA>궁전여관2005-03-23 00:00:00I2018-08-31 23:59:59.0여관업197682.585999450645.119698여관업000000000Y0<NA><NA><NA>자가00000N
130100003010000-201-1960-0001219601208<NA>3폐업2폐업19940613<NA><NA><NA>02 00000.00100420서울특별시 중구 무학동 28-0번지<NA><NA>동화2001-10-08 00:00:00I2018-08-31 23:59:59.0여인숙업<NA><NA>여인숙업000000000Y0<NA><NA><NA><NA>00000N
230100003010000-201-1960-0002319601230<NA>3폐업2폐업19950926<NA><NA><NA>0200000000.00100330서울특별시 중구 주교동 111-0번지<NA><NA>황평2001-10-08 00:00:00I2018-08-31 23:59:59.0여인숙업<NA><NA>여인숙업000000000Y0<NA><NA><NA><NA>00000N
330100003010000-201-1960-0005319601230<NA>3폐업2폐업20030226<NA><NA><NA>0222785000.00100193서울특별시 중구 을지로3가 291-45번지<NA><NA>을지장2003-04-09 00:00:00I2018-08-31 23:59:59.0여관업<NA><NA>여관업0000000100Y0<NA><NA><NA><NA>00000N
430100003010000-201-1960-0005819601230<NA>1영업/정상1영업<NA><NA><NA><NA>0222654186165.00100340서울특별시 중구 산림동 84-4번지서울특별시 중구 창경궁로5가길 27-4 (산림동)4545화성여관2017-11-29 10:17:39I2018-08-31 23:59:59.0여관업199652.811108451759.471842여관업2000001110Y0<NA><NA><NA><NA>00000N
530100003010000-201-1960-0006119601230<NA>1영업/정상1영업<NA><NA><NA><NA>02 775020275.00100874서울특별시 중구 회현동1가 185-2서울특별시 중구 퇴계로8길 2-1 (회현동1가)4634명동 킹콩호텔(KingKong Hotel)2022-12-27 16:16:20U2021-11-01 22:09:00.0여관업198152.671298450753.484811<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
630100003010000-201-1960-0011619601228<NA>3폐업2폐업20061204<NA><NA><NA>022252845072.27100825서울특별시 중구 신당동 310-11번지<NA><NA>보성여관2005-03-23 00:00:00I2018-08-31 23:59:59.0여관업201153.401706450815.26151여관업1000000100Y0<NA><NA><NA><NA>00000N
730100003010000-201-1960-0014019601228<NA>3폐업2폐업20030226<NA><NA><NA>020000000045.08100450서울특별시 중구 신당동 95-8번지<NA><NA>남양2003-04-09 00:00:00I2018-08-31 23:59:59.0여관업<NA><NA>여관업000000000Y0<NA><NA><NA><NA>00000N
830100003010000-201-1960-0017419601230<NA>3폐업2폐업19980728<NA><NA><NA>0200000000.00100022서울특별시 중구 명동2가 94-1번지<NA><NA>자현2001-10-08 00:00:00I2018-08-31 23:59:59.0여관업<NA><NA>여관업000000000Y0<NA><NA><NA><NA>00000N
930100003010000-201-1960-001841960-12-30<NA>1영업/정상1영업<NA><NA><NA><NA>02 7778553280.77100-051서울특별시 중구 회현동1가 70-0서울특별시 중구 퇴계로10길 20-3 (회현동1가)4634미도호텔2024-02-27 10:36:06U2023-12-01 22:09:00.0일반호텔198212.188791450689.354073<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)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
63830100003010000-214-2023-000052023-03-31<NA>1영업/정상1영업<NA><NA><NA><NA>0222757790650.93100-400서울특별시 중구 쌍림동 25-16서울특별시 중구 퇴계로53길 8, 2~10층 (쌍림동)4560위코스테이 동대문2023-04-03 08:25:14U2022-12-04 00:05:00.0숙박업(생활)200281.871689451298.458157<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
63930100003010000-214-2023-000062023-04-06<NA>1영업/정상1영업<NA><NA><NA><NA><NA>335.14100-860서울특별시 중구 충무로2가 12-8서울특별시 중구 명동8가길 51, 2,3,4층 (충무로2가)4537유에이치스위트 더명동32023-08-18 20:17:34U2022-12-07 22:00:00.0숙박업(생활)198867.059917451076.969961<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
64030100003010000-214-2023-000072023-06-01<NA>1영업/정상1영업<NA><NA><NA><NA><NA>428.89100-197서울특별시 중구 을지로7가 81-2서울특별시 중구 퇴계로63길 10, 5-11층 (을지로7가)4565세승빌딩2023-08-18 14:02:23U2022-12-07 22:00:00.0숙박업(생활)200698.774907451404.813039<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
64130100003010000-214-2023-000082023-09-12<NA>1영업/정상1영업<NA><NA><NA><NA><NA>33.60100-197서울특별시 중구 을지로7가 52서울특별시 중구 퇴계로67길 13-2, 1층 (을지로7가)4565도도 게스트하우스2023-09-12 14:29:38I2022-12-08 23:04:00.0숙박업(생활)200735.52586451431.548272<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
64230100003010000-214-2023-000092023-09-25<NA>1영업/정상1영업<NA><NA><NA><NA>02 22630203234.12100-411서울특별시 중구 광희동1가 240-2 태성빌딩서울특별시 중구 퇴계로 303-3, 태성빌딩 2,3,4층 (광희동1가)4560독립주택2023-09-25 16:02:07I2022-12-08 22:07:00.0숙박업(생활)200395.396906451314.582899<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
64330100003010000-214-2023-000102023-09-27<NA>1영업/정상1영업<NA><NA><NA><NA>022039213912459.14100-014서울특별시 중구 충무로4가 308서울특별시 중구 충무로2길 9, 3층~14층 (충무로4가)4556솔라고호텔2024-05-02 13:34:36U2023-12-05 00:04:00.0숙박업(생활)199367.549271451152.070282<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
64430100003010000-214-2023-000112023-10-13<NA>1영업/정상1영업<NA><NA><NA><NA>02227577901006.08100-014서울특별시 중구 충무로4가 308서울특별시 중구 충무로2길 9, 6층~14층 (충무로4가)4556위코스테이 충무로2024-02-22 14:07:57U2023-12-01 22:04:00.0숙박업(생활)199367.549271451152.070282<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
64530100003010000-214-2023-000122023-11-01<NA>1영업/정상1영업<NA><NA><NA><NA>0215336240919.51100-014서울특별시 중구 충무로4가 308서울특별시 중구 충무로2길 9, 6~14층 (충무로4가)4556인더시티 명동(Inn The City Myeongdong)2024-03-04 09:02:35U2023-12-03 00:06:00.0숙박업(생활)199367.549271451152.070282<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
64630100003010000-214-2024-000012024-03-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>910.46100-195서울특별시 중구 을지로5가 270-9 무아데자뷰서울특별시 중구 동호로35길 28, 무아데자뷰 (을지로5가)4547무아데쟈뷰2024-03-07 11:07:52I2023-12-03 00:09:00.0숙박업(생활)199980.685641451563.016233<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
64730100003010000-214-2024-000022024-04-15<NA>1영업/정상1영업<NA><NA><NA><NA>070 49430548653.75100-864서울특별시 중구 태평로2가 68-9서울특별시 중구 세종대로 80, 2-6층 (태평로2가)4526유에이치스위트 서울덕수궁2024-04-15 13:37:55I2023-12-03 23:07:00.0숙박업(생활)197897.899998451220.481025<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>