Overview

Dataset statistics

Number of variables47
Number of observations10000
Missing cells126908
Missing cells (%)27.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.9 MiB
Average record size in memory411.0 B

Variable types

Numeric14
Text7
DateTime4
Unsupported4
Categorical16
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
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-16119/S/1/datasetView.do

Alerts

업태구분명 is highly imbalanced (92.3%)Imbalance
위생업태명 is highly imbalanced (52.1%)Imbalance
발한실여부 is highly imbalanced (99.2%)Imbalance
좌석수 is highly imbalanced (56.8%)Imbalance
조건부허가신고사유 is highly imbalanced (99.3%)Imbalance
다중이용업소여부 is highly imbalanced (99.3%)Imbalance
인허가취소일자 has 10000 (100.0%) missing valuesMissing
폐업일자 has 3063 (30.6%) missing valuesMissing
휴업시작일자 has 10000 (100.0%) missing valuesMissing
휴업종료일자 has 10000 (100.0%) missing valuesMissing
재개업일자 has 10000 (100.0%) missing valuesMissing
전화번호 has 2589 (25.9%) missing valuesMissing
도로명주소 has 3110 (31.1%) missing valuesMissing
도로명우편번호 has 3176 (31.8%) missing valuesMissing
좌표정보(X) has 290 (2.9%) missing valuesMissing
좌표정보(Y) has 290 (2.9%) missing valuesMissing
건물지상층수 has 3744 (37.4%) missing valuesMissing
건물지하층수 has 4134 (41.3%) missing valuesMissing
사용시작지상층 has 4896 (49.0%) missing valuesMissing
사용끝지상층 has 5699 (57.0%) missing valuesMissing
사용시작지하층 has 7568 (75.7%) missing valuesMissing
사용끝지하층 has 8157 (81.6%) missing valuesMissing
발한실여부 has 2113 (21.1%) missing valuesMissing
조건부허가시작일자 has 9989 (99.9%) missing valuesMissing
조건부허가종료일자 has 9989 (99.9%) missing valuesMissing
여성종사자수 has 8087 (80.9%) missing valuesMissing
남성종사자수 has 8043 (80.4%) missing valuesMissing
다중이용업소여부 has 1871 (18.7%) missing valuesMissing
사용시작지상층 is highly skewed (γ1 = 46.90402388)Skewed
사용시작지하층 is highly skewed (γ1 = 42.50202532)Skewed
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
건물지상층수 has 4168 (41.7%) zerosZeros
건물지하층수 has 4648 (46.5%) zerosZeros
사용시작지상층 has 1039 (10.4%) zerosZeros
사용끝지상층 has 587 (5.9%) zerosZeros
사용시작지하층 has 1949 (19.5%) zerosZeros
사용끝지하층 has 1398 (14.0%) zerosZeros
여성종사자수 has 1551 (15.5%) zerosZeros
남성종사자수 has 1352 (13.5%) zerosZeros

Reproduction

Analysis started2024-05-11 05:30:34.039873
Analysis finished2024-05-11 05:30:37.985047
Duration3.95 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Real number (ℝ)

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3147703
Minimum3000000
Maximum3240000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T14:30:38.087510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3010000
Q13090000
median3170000
Q33220000
95-th percentile3230000
Maximum3240000
Range240000
Interquartile range (IQR)130000

Descriptive statistics

Standard deviation75182.571
Coefficient of variation (CV)0.0238849
Kurtosis-1.0009805
Mean3147703
Median Absolute Deviation (MAD)50000
Skewness-0.6023461
Sum3.147703 × 1010
Variance5.652419 × 109
MonotonicityNot monotonic
2024-05-11T14:30:38.283040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
3220000 1297
 
13.0%
3210000 951
 
9.5%
3230000 819
 
8.2%
3180000 804
 
8.0%
3130000 518
 
5.2%
3150000 442
 
4.4%
3010000 428
 
4.3%
3160000 412
 
4.1%
3240000 395
 
4.0%
3170000 328
 
3.3%
Other values (15) 3606
36.1%
ValueCountFrequency (%)
3000000 296
3.0%
3010000 428
4.3%
3020000 265
2.6%
3030000 286
2.9%
3040000 324
3.2%
3050000 285
2.9%
3060000 259
2.6%
3070000 191
1.9%
3080000 139
 
1.4%
3090000 162
 
1.6%
ValueCountFrequency (%)
3240000 395
 
4.0%
3230000 819
8.2%
3220000 1297
13.0%
3210000 951
9.5%
3200000 304
 
3.0%
3190000 263
 
2.6%
3180000 804
8.0%
3170000 328
 
3.3%
3160000 412
 
4.1%
3150000 442
 
4.4%

관리번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T14:30:38.596675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters220000
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

Unique10000 ?
Unique (%)100.0%

Sample

1st row3000000-206-1999-01741
2nd row3060000-206-2022-00002
3rd row3130000-206-2012-00008
4th row3220000-206-2012-00035
5th row3000000-206-1999-01748
ValueCountFrequency (%)
3000000-206-1999-01741 1
 
< 0.1%
3180000-206-2020-00005 1
 
< 0.1%
3040000-206-2016-00008 1
 
< 0.1%
3010000-206-1992-01703 1
 
< 0.1%
3120000-206-1997-00911 1
 
< 0.1%
3060000-206-2015-00007 1
 
< 0.1%
3140000-206-2005-00002 1
 
< 0.1%
3040000-206-1999-01939 1
 
< 0.1%
3220000-206-2019-00004 1
 
< 0.1%
3020000-206-2005-00012 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-05-11T14:30:39.141542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 99654
45.3%
- 30000
 
13.6%
2 29215
 
13.3%
1 15796
 
7.2%
3 15078
 
6.9%
6 12832
 
5.8%
9 5143
 
2.3%
4 3591
 
1.6%
8 2969
 
1.3%
5 2968
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 190000
86.4%
Dash Punctuation 30000
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 99654
52.4%
2 29215
 
15.4%
1 15796
 
8.3%
3 15078
 
7.9%
6 12832
 
6.8%
9 5143
 
2.7%
4 3591
 
1.9%
8 2969
 
1.6%
5 2968
 
1.6%
7 2754
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 30000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 99654
45.3%
- 30000
 
13.6%
2 29215
 
13.3%
1 15796
 
7.2%
3 15078
 
6.9%
6 12832
 
5.8%
9 5143
 
2.3%
4 3591
 
1.6%
8 2969
 
1.3%
5 2968
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 99654
45.3%
- 30000
 
13.6%
2 29215
 
13.3%
1 15796
 
7.2%
3 15078
 
6.9%
6 12832
 
5.8%
9 5143
 
2.3%
4 3591
 
1.6%
8 2969
 
1.3%
5 2968
 
1.3%
Distinct5030
Distinct (%)50.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1976-10-07 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T14:30:39.334107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:30:39.553223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3
6937 
1
3063 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 6937
69.4%
1 3063
30.6%

Length

2024-05-11T14:30:39.982494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:30:40.197315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 6937
69.4%
1 3063
30.6%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
6937 
영업/정상
3063 

Length

Max length5
Median length2
Mean length2.9189
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 6937
69.4%
영업/정상 3063
30.6%

Length

2024-05-11T14:30:40.397478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:30:40.563750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 6937
69.4%
영업/정상 3063
30.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
6937 
1
3063 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 6937
69.4%
1 3063
30.6%

Length

2024-05-11T14:30:40.723652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:30:40.873746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 6937
69.4%
1 3063
30.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
6937 
영업
3063 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 6937
69.4%
영업 3063
30.6%

Length

2024-05-11T14:30:41.037262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:30:41.175700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 6937
69.4%
영업 3063
30.6%

폐업일자
Date

MISSING 

Distinct3654
Distinct (%)52.7%
Missing3063
Missing (%)30.6%
Memory size156.2 KiB
Minimum1990-03-29 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T14:30:41.367098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:30:41.659240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

전화번호
Text

MISSING 

Distinct6338
Distinct (%)85.5%
Missing2589
Missing (%)25.9%
Memory size156.2 KiB
2024-05-11T14:30:42.148006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.41209
Min length2

Characters and Unicode

Total characters77164
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5537 ?
Unique (%)74.7%

Sample

1st row02 7222054
2nd row02 8626025
3rd row02 553 1825
4th row0232171295
5th row0203388555
ValueCountFrequency (%)
02 4527
33.1%
070 146
 
1.1%
031 66
 
0.5%
0 22
 
0.2%
0200000000 16
 
0.1%
521 15
 
0.1%
577 14
 
0.1%
032 13
 
0.1%
575 13
 
0.1%
587 12
 
0.1%
Other values (6704) 8839
64.6%
2024-05-11T14:30:42.900892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13182
17.1%
2 12919
16.7%
8385
10.9%
3 5954
7.7%
5 5875
7.6%
7 5642
7.3%
4 5422
7.0%
1 5415
7.0%
8 5077
 
6.6%
6 5049
 
6.5%
Other values (2) 4244
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68778
89.1%
Space Separator 8385
 
10.9%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13182
19.2%
2 12919
18.8%
3 5954
8.7%
5 5875
8.5%
7 5642
8.2%
4 5422
7.9%
1 5415
7.9%
8 5077
 
7.4%
6 5049
 
7.3%
9 4243
 
6.2%
Space Separator
ValueCountFrequency (%)
8385
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 77164
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 13182
17.1%
2 12919
16.7%
8385
10.9%
3 5954
7.7%
5 5875
7.6%
7 5642
7.3%
4 5422
7.0%
1 5415
7.0%
8 5077
 
6.6%
6 5049
 
6.5%
Other values (2) 4244
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 77164
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13182
17.1%
2 12919
16.7%
8385
10.9%
3 5954
7.7%
5 5875
7.6%
7 5642
7.3%
4 5422
7.0%
1 5415
7.0%
8 5077
 
6.6%
6 5049
 
6.5%
Other values (2) 4244
 
5.5%
Distinct4150
Distinct (%)41.5%
Missing12
Missing (%)0.1%
Memory size156.2 KiB
2024-05-11T14:30:43.395982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length5.0165198
Min length3

Characters and Unicode

Total characters50105
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

Unique3160 ?
Unique (%)31.6%

Sample

1st row112.00
2nd row22.00
3rd row20.00
4th row10.00
5th row18,369.28
ValueCountFrequency (%)
00 829
 
8.3%
33.00 281
 
2.8%
66.00 208
 
2.1%
30.00 159
 
1.6%
20.00 117
 
1.2%
10.00 108
 
1.1%
50.00 104
 
1.0%
60.00 99
 
1.0%
3.30 88
 
0.9%
15.00 87
 
0.9%
Other values (4140) 7908
79.2%
2024-05-11T14:30:44.210762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12516
25.0%
. 9988
19.9%
1 4054
 
8.1%
2 3664
 
7.3%
3 3645
 
7.3%
6 3289
 
6.6%
5 3099
 
6.2%
4 2858
 
5.7%
8 2449
 
4.9%
9 2420
 
4.8%
Other values (2) 2123
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 40027
79.9%
Other Punctuation 10078
 
20.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12516
31.3%
1 4054
 
10.1%
2 3664
 
9.2%
3 3645
 
9.1%
6 3289
 
8.2%
5 3099
 
7.7%
4 2858
 
7.1%
8 2449
 
6.1%
9 2420
 
6.0%
7 2033
 
5.1%
Other Punctuation
ValueCountFrequency (%)
. 9988
99.1%
, 90
 
0.9%

Most occurring scripts

ValueCountFrequency (%)
Common 50105
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12516
25.0%
. 9988
19.9%
1 4054
 
8.1%
2 3664
 
7.3%
3 3645
 
7.3%
6 3289
 
6.6%
5 3099
 
6.2%
4 2858
 
5.7%
8 2449
 
4.9%
9 2420
 
4.8%
Other values (2) 2123
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 50105
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12516
25.0%
. 9988
19.9%
1 4054
 
8.1%
2 3664
 
7.3%
3 3645
 
7.3%
6 3289
 
6.6%
5 3099
 
6.2%
4 2858
 
5.7%
8 2449
 
4.9%
9 2420
 
4.8%
Other values (2) 2123
 
4.2%
Distinct2728
Distinct (%)27.4%
Missing44
Missing (%)0.4%
Memory size156.2 KiB
2024-05-11T14:30:44.722020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1181197
Min length6

Characters and Unicode

Total characters60912
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

Unique1097 ?
Unique (%)11.0%

Sample

1st row110092
2nd row131-852
3rd row121894
4th row135846
5th row110794
ValueCountFrequency (%)
157210 69
 
0.7%
153863 49
 
0.5%
138888 46
 
0.5%
152848 41
 
0.4%
137876 38
 
0.4%
157930 36
 
0.4%
153803 35
 
0.4%
157-210 32
 
0.3%
138828 30
 
0.3%
137860 30
 
0.3%
Other values (2718) 9550
95.9%
2024-05-11T14:30:45.346283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14046
23.1%
8 9697
15.9%
3 8008
13.1%
0 6238
10.2%
5 6103
10.0%
2 4033
 
6.6%
7 3442
 
5.7%
4 3228
 
5.3%
9 2640
 
4.3%
6 2301
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59736
98.1%
Dash Punctuation 1176
 
1.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14046
23.5%
8 9697
16.2%
3 8008
13.4%
0 6238
10.4%
5 6103
10.2%
2 4033
 
6.8%
7 3442
 
5.8%
4 3228
 
5.4%
9 2640
 
4.4%
6 2301
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 1176
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 60912
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 14046
23.1%
8 9697
15.9%
3 8008
13.1%
0 6238
10.2%
5 6103
10.0%
2 4033
 
6.6%
7 3442
 
5.7%
4 3228
 
5.3%
9 2640
 
4.3%
6 2301
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 60912
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14046
23.1%
8 9697
15.9%
3 8008
13.1%
0 6238
10.2%
5 6103
10.0%
2 4033
 
6.6%
7 3442
 
5.7%
4 3228
 
5.3%
9 2640
 
4.3%
6 2301
 
3.8%
Distinct9372
Distinct (%)94.1%
Missing44
Missing (%)0.4%
Memory size156.2 KiB
2024-05-11T14:30:45.824412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length48
Mean length26.352551
Min length14

Characters and Unicode

Total characters262366
Distinct characters625
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8928 ?
Unique (%)89.7%

Sample

1st row서울특별시 종로구 홍파동 20-9 경기빌딩5층
2nd row서울특별시 중랑구 묵동 240-186
3rd row서울특별시 마포구 서교동 379-18
4th row서울특별시 강남구 대치동 945-22
5th row서울특별시 종로구 인사동 194-4 하나로빌딩516호
ValueCountFrequency (%)
서울특별시 9953
 
19.3%
강남구 1298
 
2.5%
서초구 952
 
1.8%
송파구 817
 
1.6%
영등포구 790
 
1.5%
마포구 516
 
1.0%
2층 491
 
1.0%
강서구 442
 
0.9%
중구 427
 
0.8%
구로구 404
 
0.8%
Other values (11151) 35388
68.7%
2024-05-11T14:30:46.600114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
48323
18.4%
12219
 
4.7%
1 11990
 
4.6%
11760
 
4.5%
10783
 
4.1%
10284
 
3.9%
9999
 
3.8%
9966
 
3.8%
9953
 
3.8%
- 8644
 
3.3%
Other values (615) 118445
45.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 145736
55.5%
Decimal Number 57285
 
21.8%
Space Separator 48323
 
18.4%
Dash Punctuation 8644
 
3.3%
Uppercase Letter 784
 
0.3%
Close Punctuation 585
 
0.2%
Open Punctuation 583
 
0.2%
Other Punctuation 298
 
0.1%
Lowercase Letter 80
 
< 0.1%
Letter Number 25
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
12219
 
8.4%
11760
 
8.1%
10783
 
7.4%
10284
 
7.1%
9999
 
6.9%
9966
 
6.8%
9953
 
6.8%
3669
 
2.5%
3034
 
2.1%
2476
 
1.7%
Other values (538) 61593
42.3%
Uppercase Letter
ValueCountFrequency (%)
B 204
26.0%
A 86
11.0%
K 71
 
9.1%
T 62
 
7.9%
D 49
 
6.2%
S 41
 
5.2%
C 33
 
4.2%
G 26
 
3.3%
I 24
 
3.1%
L 23
 
2.9%
Other values (16) 165
21.0%
Lowercase Letter
ValueCountFrequency (%)
e 18
22.5%
c 8
10.0%
r 7
 
8.8%
s 6
 
7.5%
b 5
 
6.2%
o 5
 
6.2%
n 5
 
6.2%
t 5
 
6.2%
k 4
 
5.0%
w 3
 
3.8%
Other values (8) 14
17.5%
Decimal Number
ValueCountFrequency (%)
1 11990
20.9%
2 8153
14.2%
3 6584
11.5%
0 5932
10.4%
4 5429
9.5%
5 4700
 
8.2%
6 4229
 
7.4%
7 3706
 
6.5%
9 3338
 
5.8%
8 3224
 
5.6%
Other Punctuation
ValueCountFrequency (%)
, 213
71.5%
. 36
 
12.1%
/ 34
 
11.4%
& 7
 
2.3%
@ 5
 
1.7%
? 3
 
1.0%
Letter Number
ValueCountFrequency (%)
13
52.0%
6
24.0%
4
 
16.0%
1
 
4.0%
1
 
4.0%
Math Symbol
ValueCountFrequency (%)
~ 16
69.6%
< 3
 
13.0%
> 3
 
13.0%
1
 
4.3%
Close Punctuation
ValueCountFrequency (%)
) 546
93.3%
] 37
 
6.3%
2
 
0.3%
Open Punctuation
ValueCountFrequency (%)
( 544
93.3%
[ 37
 
6.3%
2
 
0.3%
Space Separator
ValueCountFrequency (%)
48323
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8644
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 145736
55.5%
Common 115741
44.1%
Latin 889
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
12219
 
8.4%
11760
 
8.1%
10783
 
7.4%
10284
 
7.1%
9999
 
6.9%
9966
 
6.8%
9953
 
6.8%
3669
 
2.5%
3034
 
2.1%
2476
 
1.7%
Other values (538) 61593
42.3%
Latin
ValueCountFrequency (%)
B 204
22.9%
A 86
 
9.7%
K 71
 
8.0%
T 62
 
7.0%
D 49
 
5.5%
S 41
 
4.6%
C 33
 
3.7%
G 26
 
2.9%
I 24
 
2.7%
L 23
 
2.6%
Other values (39) 270
30.4%
Common
ValueCountFrequency (%)
48323
41.8%
1 11990
 
10.4%
- 8644
 
7.5%
2 8153
 
7.0%
3 6584
 
5.7%
0 5932
 
5.1%
4 5429
 
4.7%
5 4700
 
4.1%
6 4229
 
3.7%
7 3706
 
3.2%
Other values (18) 8051
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 145736
55.5%
ASCII 116600
44.4%
Number Forms 25
 
< 0.1%
None 4
 
< 0.1%
Math Operators 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
48323
41.4%
1 11990
 
10.3%
- 8644
 
7.4%
2 8153
 
7.0%
3 6584
 
5.6%
0 5932
 
5.1%
4 5429
 
4.7%
5 4700
 
4.0%
6 4229
 
3.6%
7 3706
 
3.2%
Other values (59) 8910
 
7.6%
Hangul
ValueCountFrequency (%)
12219
 
8.4%
11760
 
8.1%
10783
 
7.4%
10284
 
7.1%
9999
 
6.9%
9966
 
6.8%
9953
 
6.8%
3669
 
2.5%
3034
 
2.1%
2476
 
1.7%
Other values (538) 61593
42.3%
Number Forms
ValueCountFrequency (%)
13
52.0%
6
24.0%
4
 
16.0%
1
 
4.0%
1
 
4.0%
None
ValueCountFrequency (%)
2
50.0%
2
50.0%
Math Operators
ValueCountFrequency (%)
1
100.0%

도로명주소
Text

MISSING 

Distinct6730
Distinct (%)97.7%
Missing3110
Missing (%)31.1%
Memory size156.2 KiB
2024-05-11T14:30:47.167055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length68
Median length56
Mean length35.374165
Min length19

Characters and Unicode

Total characters243728
Distinct characters635
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6577 ?
Unique (%)95.5%

Sample

1st row서울특별시 중랑구 봉화산로3길 194, 1층 (묵동)
2nd row서울특별시 마포구 잔다리로7길 19, 302호 (서교동, 두원빌딩)
3rd row서울특별시 강남구 영동대로85길 20-5, 지상6층 (대치동, 수륙빌딩)
4th row서울특별시 마포구 성지길 46 (합정동)
5th row서울특별시 강동구 명일로 228, 그린하우스 301호 (길동)
ValueCountFrequency (%)
서울특별시 6887
 
14.9%
강남구 789
 
1.7%
서초구 700
 
1.5%
송파구 648
 
1.4%
2층 630
 
1.4%
영등포구 575
 
1.2%
3층 527
 
1.1%
1층 523
 
1.1%
강서구 356
 
0.8%
마포구 353
 
0.8%
Other values (8609) 34207
74.0%
2024-05-11T14:30:47.933797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
39323
 
16.1%
1 9491
 
3.9%
8998
 
3.7%
8916
 
3.7%
, 8101
 
3.3%
7621
 
3.1%
7548
 
3.1%
7292
 
3.0%
) 7136
 
2.9%
( 7135
 
2.9%
Other values (625) 132167
54.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 138080
56.7%
Decimal Number 41858
 
17.2%
Space Separator 39323
 
16.1%
Other Punctuation 8143
 
3.3%
Close Punctuation 7150
 
2.9%
Open Punctuation 7149
 
2.9%
Dash Punctuation 1099
 
0.5%
Uppercase Letter 820
 
0.3%
Lowercase Letter 67
 
< 0.1%
Letter Number 24
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
8998
 
6.5%
8916
 
6.5%
7621
 
5.5%
7548
 
5.5%
7292
 
5.3%
6936
 
5.0%
6900
 
5.0%
6887
 
5.0%
4346
 
3.1%
4332
 
3.1%
Other values (556) 68304
49.5%
Uppercase Letter
ValueCountFrequency (%)
B 232
28.3%
A 105
12.8%
K 71
 
8.7%
T 61
 
7.4%
C 53
 
6.5%
S 42
 
5.1%
D 37
 
4.5%
I 20
 
2.4%
E 19
 
2.3%
L 19
 
2.3%
Other values (16) 161
19.6%
Lowercase Letter
ValueCountFrequency (%)
e 14
20.9%
s 7
10.4%
r 6
9.0%
c 6
9.0%
b 5
 
7.5%
o 5
 
7.5%
a 4
 
6.0%
n 4
 
6.0%
t 4
 
6.0%
k 3
 
4.5%
Other values (6) 9
13.4%
Decimal Number
ValueCountFrequency (%)
1 9491
22.7%
2 6438
15.4%
3 4965
11.9%
0 4865
11.6%
4 3641
 
8.7%
5 3205
 
7.7%
6 2751
 
6.6%
7 2401
 
5.7%
8 2211
 
5.3%
9 1890
 
4.5%
Other Punctuation
ValueCountFrequency (%)
, 8101
99.5%
/ 17
 
0.2%
. 16
 
0.2%
& 6
 
0.1%
@ 3
 
< 0.1%
Letter Number
ValueCountFrequency (%)
12
50.0%
6
25.0%
4
 
16.7%
1
 
4.2%
1
 
4.2%
Close Punctuation
ValueCountFrequency (%)
) 7136
99.8%
] 14
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 7135
99.8%
[ 14
 
0.2%
Space Separator
ValueCountFrequency (%)
39323
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1099
100.0%
Math Symbol
ValueCountFrequency (%)
~ 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 138080
56.7%
Common 104737
43.0%
Latin 911
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
8998
 
6.5%
8916
 
6.5%
7621
 
5.5%
7548
 
5.5%
7292
 
5.3%
6936
 
5.0%
6900
 
5.0%
6887
 
5.0%
4346
 
3.1%
4332
 
3.1%
Other values (556) 68304
49.5%
Latin
ValueCountFrequency (%)
B 232
25.5%
A 105
11.5%
K 71
 
7.8%
T 61
 
6.7%
C 53
 
5.8%
S 42
 
4.6%
D 37
 
4.1%
I 20
 
2.2%
E 19
 
2.1%
L 19
 
2.1%
Other values (37) 252
27.7%
Common
ValueCountFrequency (%)
39323
37.5%
1 9491
 
9.1%
, 8101
 
7.7%
) 7136
 
6.8%
( 7135
 
6.8%
2 6438
 
6.1%
3 4965
 
4.7%
0 4865
 
4.6%
4 3641
 
3.5%
5 3205
 
3.1%
Other values (12) 10437
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 138080
56.7%
ASCII 105624
43.3%
Number Forms 24
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
39323
37.2%
1 9491
 
9.0%
, 8101
 
7.7%
) 7136
 
6.8%
( 7135
 
6.8%
2 6438
 
6.1%
3 4965
 
4.7%
0 4865
 
4.6%
4 3641
 
3.4%
5 3205
 
3.0%
Other values (54) 11324
 
10.7%
Hangul
ValueCountFrequency (%)
8998
 
6.5%
8916
 
6.5%
7621
 
5.5%
7548
 
5.5%
7292
 
5.3%
6936
 
5.0%
6900
 
5.0%
6887
 
5.0%
4346
 
3.1%
4332
 
3.1%
Other values (556) 68304
49.5%
Number Forms
ValueCountFrequency (%)
12
50.0%
6
25.0%
4
 
16.7%
1
 
4.2%
1
 
4.2%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct2563
Distinct (%)37.6%
Missing3176
Missing (%)31.8%
Infinite0
Infinite (%)0.0%
Mean5625.6647
Minimum1006
Maximum61087
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T14:30:48.187246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1006
5-th percentile1827.45
Q14337
median6012.5
Q37226
95-th percentile8569.4
Maximum61087
Range60081
Interquartile range (IQR)2889

Descriptive statistics

Standard deviation2099.7581
Coefficient of variation (CV)0.37324622
Kurtosis70.479262
Mean5625.6647
Median Absolute Deviation (MAD)1320.5
Skewness2.3263427
Sum38389536
Variance4408984
MonotonicityNot monotonic
2024-05-11T14:30:48.426797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8639 59
 
0.6%
5838 31
 
0.3%
4808 29
 
0.3%
6775 28
 
0.3%
7333 27
 
0.3%
5836 25
 
0.2%
7788 23
 
0.2%
7238 23
 
0.2%
7222 21
 
0.2%
7803 21
 
0.2%
Other values (2553) 6537
65.4%
(Missing) 3176
31.8%
ValueCountFrequency (%)
1006 1
< 0.1%
1009 2
< 0.1%
1013 1
< 0.1%
1014 1
< 0.1%
1021 1
< 0.1%
1030 1
< 0.1%
1033 1
< 0.1%
1036 1
< 0.1%
1040 1
< 0.1%
1041 1
< 0.1%
ValueCountFrequency (%)
61087 1
 
< 0.1%
17154 1
 
< 0.1%
12927 1
 
< 0.1%
8865 1
 
< 0.1%
8861 1
 
< 0.1%
8860 3
< 0.1%
8859 3
< 0.1%
8855 2
< 0.1%
8854 1
 
< 0.1%
8849 1
 
< 0.1%
Distinct8356
Distinct (%)83.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T14:30:48.813925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length34
Mean length7.9863
Min length2

Characters and Unicode

Total characters79863
Distinct characters775
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7062 ?
Unique (%)70.6%

Sample

1st row오대개발주식회사
2nd row미래환경산업
3rd row(주)그린피아한성
4th row(주)에스크린
5th row금강안전(주)
ValueCountFrequency (%)
주식회사 992
 
8.5%
106
 
0.9%
크린 23
 
0.2%
사회복지법인 19
 
0.2%
유한회사 16
 
0.1%
사단법인 16
 
0.1%
클린 15
 
0.1%
서비스 12
 
0.1%
협동조합 12
 
0.1%
사회적협동조합 11
 
0.1%
Other values (8561) 10435
89.5%
2024-05-11T14:30:49.490775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7390
 
9.3%
) 6159
 
7.7%
( 6114
 
7.7%
2979
 
3.7%
2102
 
2.6%
1861
 
2.3%
1667
 
2.1%
1648
 
2.1%
1479
 
1.9%
1387
 
1.7%
Other values (765) 47077
58.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 64709
81.0%
Close Punctuation 6159
 
7.7%
Open Punctuation 6114
 
7.7%
Space Separator 1667
 
2.1%
Uppercase Letter 651
 
0.8%
Lowercase Letter 285
 
0.4%
Decimal Number 115
 
0.1%
Other Punctuation 114
 
0.1%
Dash Punctuation 49
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7390
 
11.4%
2979
 
4.6%
2102
 
3.2%
1861
 
2.9%
1648
 
2.5%
1479
 
2.3%
1387
 
2.1%
1221
 
1.9%
909
 
1.4%
907
 
1.4%
Other values (695) 42826
66.2%
Uppercase Letter
ValueCountFrequency (%)
C 97
14.9%
S 93
14.3%
M 60
 
9.2%
N 40
 
6.1%
B 34
 
5.2%
E 33
 
5.1%
G 31
 
4.8%
O 30
 
4.6%
K 27
 
4.1%
T 27
 
4.1%
Other values (15) 179
27.5%
Lowercase Letter
ValueCountFrequency (%)
e 41
14.4%
i 25
 
8.8%
a 24
 
8.4%
t 20
 
7.0%
n 20
 
7.0%
o 19
 
6.7%
l 18
 
6.3%
r 18
 
6.3%
s 17
 
6.0%
c 16
 
5.6%
Other values (15) 67
23.5%
Decimal Number
ValueCountFrequency (%)
1 34
29.6%
2 24
20.9%
9 11
 
9.6%
5 10
 
8.7%
3 10
 
8.7%
6 9
 
7.8%
4 9
 
7.8%
0 5
 
4.3%
7 2
 
1.7%
8 1
 
0.9%
Other Punctuation
ValueCountFrequency (%)
. 71
62.3%
& 35
30.7%
, 5
 
4.4%
? 1
 
0.9%
1
 
0.9%
/ 1
 
0.9%
Close Punctuation
ValueCountFrequency (%)
) 6159
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6114
100.0%
Space Separator
ValueCountFrequency (%)
1667
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 49
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 64707
81.0%
Common 14218
 
17.8%
Latin 936
 
1.2%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7390
 
11.4%
2979
 
4.6%
2102
 
3.2%
1861
 
2.9%
1648
 
2.5%
1479
 
2.3%
1387
 
2.1%
1221
 
1.9%
909
 
1.4%
907
 
1.4%
Other values (693) 42824
66.2%
Latin
ValueCountFrequency (%)
C 97
 
10.4%
S 93
 
9.9%
M 60
 
6.4%
e 41
 
4.4%
N 40
 
4.3%
B 34
 
3.6%
E 33
 
3.5%
G 31
 
3.3%
O 30
 
3.2%
K 27
 
2.9%
Other values (40) 450
48.1%
Common
ValueCountFrequency (%)
) 6159
43.3%
( 6114
43.0%
1667
 
11.7%
. 71
 
0.5%
- 49
 
0.3%
& 35
 
0.2%
1 34
 
0.2%
2 24
 
0.2%
9 11
 
0.1%
5 10
 
0.1%
Other values (10) 44
 
0.3%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 64707
81.0%
ASCII 15153
 
19.0%
CJK 2
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
7390
 
11.4%
2979
 
4.6%
2102
 
3.2%
1861
 
2.9%
1648
 
2.5%
1479
 
2.3%
1387
 
2.1%
1221
 
1.9%
909
 
1.4%
907
 
1.4%
Other values (693) 42824
66.2%
ASCII
ValueCountFrequency (%)
) 6159
40.6%
( 6114
40.3%
1667
 
11.0%
C 97
 
0.6%
S 93
 
0.6%
. 71
 
0.5%
M 60
 
0.4%
- 49
 
0.3%
e 41
 
0.3%
N 40
 
0.3%
Other values (59) 762
 
5.0%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%
None
ValueCountFrequency (%)
1
100.0%
Distinct8556
Distinct (%)85.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1998-12-30 00:00:00
Maximum2024-05-09 17:21:53
2024-05-11T14:30:49.689979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:30:49.950840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
I
6825 
U
3175 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 6825
68.2%
U 3175
31.8%

Length

2024-05-11T14:30:50.128506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:30:50.252083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 6825
68.2%
u 3175
31.8%
Distinct1523
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T14:30:50.438595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:30:50.659759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
건물위생관리업
9906 
건물위생관리업 기타
 
94

Length

Max length10
Median length7
Mean length7.0282
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 9906
99.1%
건물위생관리업 기타 94
 
0.9%

Length

2024-05-11T14:30:50.834187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:30:50.942407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 10000
99.1%
기타 94
 
0.9%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct6837
Distinct (%)70.4%
Missing290
Missing (%)2.9%
Infinite0
Infinite (%)0.0%
Mean199590.5
Minimum182141.21
Maximum219054.81
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T14:30:51.059021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum182141.21
5-th percentile186884.17
Q1192881.2
median201196.63
Q3204994.57
95-th percentile211130.69
Maximum219054.81
Range36913.607
Interquartile range (IQR)12113.371

Descriptive statistics

Standard deviation7498.2242
Coefficient of variation (CV)0.037568041
Kurtosis-0.9188426
Mean199590.5
Median Absolute Deviation (MAD)5861.6877
Skewness-0.1859373
Sum1.9380238 × 109
Variance56223366
MonotonicityNot monotonic
2024-05-11T14:30:51.581053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
191226.287379467 78
 
0.8%
210986.460698452 24
 
0.2%
208937.760652081 15
 
0.1%
190555.768991595 13
 
0.1%
194561.746032498 13
 
0.1%
193469.554731741 13
 
0.1%
202155.401317068 12
 
0.1%
211542.314116941 12
 
0.1%
190541.499138217 12
 
0.1%
201753.303709664 12
 
0.1%
Other values (6827) 9506
95.1%
(Missing) 290
 
2.9%
ValueCountFrequency (%)
182141.205465089 1
< 0.1%
182154.410343287 1
< 0.1%
182243.855587728 1
< 0.1%
182297.683890108 1
< 0.1%
182456.194080179 1
< 0.1%
182478.394935408 1
< 0.1%
182742.537963411 1
< 0.1%
182801.931637762 2
< 0.1%
182853.820302804 1
< 0.1%
182865.612372488 2
< 0.1%
ValueCountFrequency (%)
219054.812242672 1
 
< 0.1%
218366.202136734 1
 
< 0.1%
215474.513482379 1
 
< 0.1%
215339.644961398 1
 
< 0.1%
215327.573332527 1
 
< 0.1%
215313.230134197 1
 
< 0.1%
215289.815449411 2
< 0.1%
215254.0 3
< 0.1%
215231.341426541 1
 
< 0.1%
215212.625424847 4
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct6836
Distinct (%)70.4%
Missing290
Missing (%)2.9%
Infinite0
Infinite (%)0.0%
Mean447777.7
Minimum189707.52
Maximum465042.49
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T14:30:51.834177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189707.52
5-th percentile441562.36
Q1443795.03
median446897.71
Q3451032.16
95-th percentile457712.94
Maximum465042.49
Range275334.97
Interquartile range (IQR)7237.1206

Descriptive statistics

Standard deviation5761.2943
Coefficient of variation (CV)0.012866416
Kurtosis414.21395
Mean447777.7
Median Absolute Deviation (MAD)3544.2592
Skewness-8.6859031
Sum4.3479214 × 109
Variance33192512
MonotonicityNot monotonic
2024-05-11T14:30:52.031584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
437914.06299827 78
 
0.8%
441725.293491662 24
 
0.2%
442873.588039887 15
 
0.1%
446698.814322782 13
 
0.1%
446364.318286465 13
 
0.1%
446508.068667777 13
 
0.1%
442708.140860448 12
 
0.1%
448273.114107211 12
 
0.1%
459411.940883021 12
 
0.1%
446369.332313077 12
 
0.1%
Other values (6826) 9506
95.1%
(Missing) 290
 
2.9%
ValueCountFrequency (%)
189707.523875 1
 
< 0.1%
414646.396157047 1
 
< 0.1%
436888.773525926 1
 
< 0.1%
436953.782824253 1
 
< 0.1%
437044.063129093 1
 
< 0.1%
437562.242368734 2
 
< 0.1%
437720.936273177 1
 
< 0.1%
437914.06299827 78
0.8%
437968.892025771 1
 
< 0.1%
438251.799466626 1
 
< 0.1%
ValueCountFrequency (%)
465042.493324016 4
< 0.1%
464978.535 1
 
< 0.1%
464828.911640695 1
 
< 0.1%
464814.717432497 4
< 0.1%
464768.43323261 1
 
< 0.1%
464725.202550965 1
 
< 0.1%
464621.491955908 1
 
< 0.1%
464472.810888981 2
< 0.1%
464295.628375287 1
 
< 0.1%
464212.297931928 1
 
< 0.1%

위생업태명
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
건물위생관리업
8051 
<NA>
1871 
건물위생관리업 기타
 
78

Length

Max length10
Median length7
Mean length6.4621
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 8051
80.5%
<NA> 1871
 
18.7%
건물위생관리업 기타 78
 
0.8%

Length

2024-05-11T14:30:52.241444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:30:52.363634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 8129
80.7%
na 1871
 
18.6%
기타 78
 
0.8%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct36
Distinct (%)0.6%
Missing3744
Missing (%)37.4%
Infinite0
Infinite (%)0.0%
Mean1.9518862
Minimum0
Maximum54
Zeros4168
Zeros (%)41.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T14:30:52.549072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile10
Maximum54
Range54
Interquartile range (IQR)3

Descriptive statistics

Standard deviation4.0500568
Coefficient of variation (CV)2.0749452
Kurtosis23.247411
Mean1.9518862
Median Absolute Deviation (MAD)0
Skewness3.8204569
Sum12211
Variance16.40296
MonotonicityNot monotonic
2024-05-11T14:30:52.801890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
0 4168
41.7%
4 416
 
4.2%
5 393
 
3.9%
3 374
 
3.7%
2 202
 
2.0%
6 118
 
1.2%
1 113
 
1.1%
10 71
 
0.7%
7 56
 
0.6%
8 55
 
0.5%
Other values (26) 290
 
2.9%
(Missing) 3744
37.4%
ValueCountFrequency (%)
0 4168
41.7%
1 113
 
1.1%
2 202
 
2.0%
3 374
 
3.7%
4 416
 
4.2%
5 393
 
3.9%
6 118
 
1.2%
7 56
 
0.6%
8 55
 
0.5%
9 40
 
0.4%
ValueCountFrequency (%)
54 2
< 0.1%
46 1
 
< 0.1%
45 1
 
< 0.1%
39 1
 
< 0.1%
33 1
 
< 0.1%
31 2
< 0.1%
30 2
< 0.1%
28 2
< 0.1%
27 2
< 0.1%
26 3
< 0.1%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)0.2%
Missing4134
Missing (%)41.3%
Infinite0
Infinite (%)0.0%
Mean0.36941698
Minimum0
Maximum32
Zeros4648
Zeros (%)46.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T14:30:53.004174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum32
Range32
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.0821715
Coefficient of variation (CV)2.9294039
Kurtosis146.02514
Mean0.36941698
Median Absolute Deviation (MAD)0
Skewness7.9177187
Sum2167
Variance1.1710952
MonotonicityNot monotonic
2024-05-11T14:30:53.167536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 4648
46.5%
1 875
 
8.8%
2 118
 
1.2%
4 69
 
0.7%
3 64
 
0.6%
5 35
 
0.4%
6 33
 
0.3%
7 14
 
0.1%
8 7
 
0.1%
14 1
 
< 0.1%
Other values (2) 2
 
< 0.1%
(Missing) 4134
41.3%
ValueCountFrequency (%)
0 4648
46.5%
1 875
 
8.8%
2 118
 
1.2%
3 64
 
0.6%
4 69
 
0.7%
5 35
 
0.4%
6 33
 
0.3%
7 14
 
0.1%
8 7
 
0.1%
14 1
 
< 0.1%
ValueCountFrequency (%)
32 1
 
< 0.1%
15 1
 
< 0.1%
14 1
 
< 0.1%
8 7
 
0.1%
7 14
 
0.1%
6 33
 
0.3%
5 35
 
0.4%
4 69
0.7%
3 64
0.6%
2 118
1.2%

사용시작지상층
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct30
Distinct (%)0.6%
Missing4896
Missing (%)49.0%
Infinite0
Infinite (%)0.0%
Mean3.4233934
Minimum0
Maximum803
Zeros1039
Zeros (%)10.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T14:30:53.347936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q34
95-th percentile10
Maximum803
Range803
Interquartile range (IQR)3

Descriptive statistics

Standard deviation13.910425
Coefficient of variation (CV)4.0633438
Kurtosis2473.1353
Mean3.4233934
Median Absolute Deviation (MAD)2
Skewness46.904024
Sum17473
Variance193.49991
MonotonicityNot monotonic
2024-05-11T14:30:53.531863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0 1039
 
10.4%
2 931
 
9.3%
3 770
 
7.7%
1 735
 
7.3%
4 536
 
5.4%
5 333
 
3.3%
6 170
 
1.7%
7 108
 
1.1%
8 103
 
1.0%
10 82
 
0.8%
Other values (20) 297
 
3.0%
(Missing) 4896
49.0%
ValueCountFrequency (%)
0 1039
10.4%
1 735
7.3%
2 931
9.3%
3 770
7.7%
4 536
5.4%
5 333
 
3.3%
6 170
 
1.7%
7 108
 
1.1%
8 103
 
1.0%
9 78
 
0.8%
ValueCountFrequency (%)
803 1
 
< 0.1%
503 1
 
< 0.1%
201 1
 
< 0.1%
39 1
 
< 0.1%
35 1
 
< 0.1%
25 1
 
< 0.1%
24 2
< 0.1%
22 3
< 0.1%
21 3
< 0.1%
20 4
< 0.1%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct50
Distinct (%)1.2%
Missing5699
Missing (%)57.0%
Infinite0
Infinite (%)0.0%
Mean6.5356894
Minimum0
Maximum910
Zeros587
Zeros (%)5.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T14:30:53.739631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q34
95-th percentile11
Maximum910
Range910
Interquartile range (IQR)3

Descriptive statistics

Standard deviation38.843017
Coefficient of variation (CV)5.9432165
Kurtosis271.37911
Mean6.5356894
Median Absolute Deviation (MAD)2
Skewness15.293911
Sum28110
Variance1508.7799
MonotonicityNot monotonic
2024-05-11T14:30:53.960299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 869
 
8.7%
3 740
 
7.4%
1 610
 
6.1%
0 587
 
5.9%
4 478
 
4.8%
5 313
 
3.1%
6 142
 
1.4%
7 96
 
1.0%
8 90
 
0.9%
10 71
 
0.7%
Other values (40) 305
 
3.0%
(Missing) 5699
57.0%
ValueCountFrequency (%)
0 587
5.9%
1 610
6.1%
2 869
8.7%
3 740
7.4%
4 478
4.8%
5 313
 
3.1%
6 142
 
1.4%
7 96
 
1.0%
8 90
 
0.9%
9 69
 
0.7%
ValueCountFrequency (%)
910 1
< 0.1%
904 1
< 0.1%
803 1
< 0.1%
706 1
< 0.1%
614 2
< 0.1%
509 2
< 0.1%
508 1
< 0.1%
503 2
< 0.1%
403 1
< 0.1%
334 2
< 0.1%

사용시작지하층
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct10
Distinct (%)0.4%
Missing7568
Missing (%)75.7%
Infinite0
Infinite (%)0.0%
Mean0.28988487
Minimum0
Maximum103
Zeros1949
Zeros (%)19.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T14:30:54.153342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum103
Range103
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.1935014
Coefficient of variation (CV)7.566802
Kurtosis1980.4666
Mean0.28988487
Median Absolute Deviation (MAD)0
Skewness42.502025
Sum705
Variance4.8114484
MonotonicityNot monotonic
2024-05-11T14:30:54.318183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 1949
 
19.5%
1 434
 
4.3%
2 22
 
0.2%
3 9
 
0.1%
4 9
 
0.1%
6 3
 
< 0.1%
5 2
 
< 0.1%
13 2
 
< 0.1%
103 1
 
< 0.1%
7 1
 
< 0.1%
(Missing) 7568
75.7%
ValueCountFrequency (%)
0 1949
19.5%
1 434
 
4.3%
2 22
 
0.2%
3 9
 
0.1%
4 9
 
0.1%
5 2
 
< 0.1%
6 3
 
< 0.1%
7 1
 
< 0.1%
13 2
 
< 0.1%
103 1
 
< 0.1%
ValueCountFrequency (%)
103 1
 
< 0.1%
13 2
 
< 0.1%
7 1
 
< 0.1%
6 3
 
< 0.1%
5 2
 
< 0.1%
4 9
 
0.1%
3 9
 
0.1%
2 22
 
0.2%
1 434
 
4.3%
0 1949
19.5%

사용끝지하층
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)0.5%
Missing8157
Missing (%)81.6%
Infinite0
Infinite (%)0.0%
Mean0.31090613
Minimum0
Maximum13
Zeros1398
Zeros (%)14.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T14:30:54.468426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum13
Range13
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.78353399
Coefficient of variation (CV)2.5201625
Kurtosis86.475051
Mean0.31090613
Median Absolute Deviation (MAD)0
Skewness7.0532795
Sum573
Variance0.61392551
MonotonicityNot monotonic
2024-05-11T14:30:54.600852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 1398
 
14.0%
1 394
 
3.9%
2 26
 
0.3%
4 10
 
0.1%
3 5
 
0.1%
6 4
 
< 0.1%
5 3
 
< 0.1%
13 2
 
< 0.1%
7 1
 
< 0.1%
(Missing) 8157
81.6%
ValueCountFrequency (%)
0 1398
14.0%
1 394
 
3.9%
2 26
 
0.3%
3 5
 
0.1%
4 10
 
0.1%
5 3
 
< 0.1%
6 4
 
< 0.1%
7 1
 
< 0.1%
13 2
 
< 0.1%
ValueCountFrequency (%)
13 2
 
< 0.1%
7 1
 
< 0.1%
6 4
 
< 0.1%
5 3
 
< 0.1%
4 10
 
0.1%
3 5
 
0.1%
2 26
 
0.3%
1 394
 
3.9%
0 1398
14.0%

한실수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
5353 
<NA>
4647 

Length

Max length4
Median length1
Mean length2.3941
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 5353
53.5%
<NA> 4647
46.5%

Length

2024-05-11T14:30:54.761920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:30:54.874152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5353
53.5%
na 4647
46.5%

양실수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
5353 
<NA>
4647 

Length

Max length4
Median length1
Mean length2.3941
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 5353
53.5%
<NA> 4647
46.5%

Length

2024-05-11T14:30:54.989501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:30:55.165201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5353
53.5%
na 4647
46.5%

욕실수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
5353 
<NA>
4647 

Length

Max length4
Median length1
Mean length2.3941
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 5353
53.5%
<NA> 4647
46.5%

Length

2024-05-11T14:30:55.398128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:30:55.567664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5353
53.5%
na 4647
46.5%

발한실여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing2113
Missing (%)21.1%
Memory size97.7 KiB
False
7882 
True
 
5
(Missing)
2113 
ValueCountFrequency (%)
False 7882
78.8%
True 5
 
0.1%
(Missing) 2113
 
21.1%
2024-05-11T14:30:55.714519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
5316 
<NA>
4679 
3
 
3
2
 
1
8
 
1

Length

Max length4
Median length1
Mean length2.4037
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 5316
53.2%
<NA> 4679
46.8%
3 3
 
< 0.1%
2 1
 
< 0.1%
8 1
 
< 0.1%

Length

2024-05-11T14:30:55.892179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:30:56.057559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5316
53.2%
na 4679
46.8%
3 3
 
< 0.1%
2 1
 
< 0.1%
8 1
 
< 0.1%

조건부허가신고사유
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9989 
공중위생관리법시행령 제3조제1호의 규정에 의한 건축물규모 이하의 건축물만 청소
 
9
임시사용승인기간 한.
 
1
외국인체류기간동안만 한시적 영업 가능
 
1

Length

Max length43
Median length4
Mean length4.0374
Min length4

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9989
99.9%
공중위생관리법시행령 제3조제1호의 규정에 의한 건축물규모 이하의 건축물만 청소 9
 
0.1%
임시사용승인기간 한. 1
 
< 0.1%
외국인체류기간동안만 한시적 영업 가능 1
 
< 0.1%

Length

2024-05-11T14:30:56.245306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:30:56.427698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9989
99.2%
공중위생관리법시행령 9
 
0.1%
제3조제1호의 9
 
0.1%
규정에 9
 
0.1%
의한 9
 
0.1%
건축물규모 9
 
0.1%
이하의 9
 
0.1%
건축물만 9
 
0.1%
청소 9
 
0.1%
임시사용승인기간 1
 
< 0.1%
Other values (5) 5
 
< 0.1%

조건부허가시작일자
Real number (ℝ)

MISSING 

Distinct9
Distinct (%)81.8%
Missing9989
Missing (%)99.9%
Infinite0
Infinite (%)0.0%
Mean20071516
Minimum20060316
Maximum20181113
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T14:30:56.553187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20060316
5-th percentile20060316
Q120060365
median20060509
Q320060912
95-th percentile20121020
Maximum20181113
Range120797
Interquartile range (IQR)547.5

Descriptive statistics

Standard deviation36350.202
Coefficient of variation (CV)0.0018110342
Kurtosis10.998647
Mean20071516
Median Absolute Deviation (MAD)193
Skewness3.3163446
Sum2.2078667 × 108
Variance1.3213372 × 109
MonotonicityNot monotonic
2024-05-11T14:30:56.698865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
20060410 2
 
< 0.1%
20060316 2
 
< 0.1%
20060919 1
 
< 0.1%
20060320 1
 
< 0.1%
20060906 1
 
< 0.1%
20060509 1
 
< 0.1%
20060524 1
 
< 0.1%
20060928 1
 
< 0.1%
20181113 1
 
< 0.1%
(Missing) 9989
99.9%
ValueCountFrequency (%)
20060316 2
< 0.1%
20060320 1
< 0.1%
20060410 2
< 0.1%
20060509 1
< 0.1%
20060524 1
< 0.1%
20060906 1
< 0.1%
20060919 1
< 0.1%
20060928 1
< 0.1%
20181113 1
< 0.1%
ValueCountFrequency (%)
20181113 1
< 0.1%
20060928 1
< 0.1%
20060919 1
< 0.1%
20060906 1
< 0.1%
20060524 1
< 0.1%
20060509 1
< 0.1%
20060410 2
< 0.1%
20060320 1
< 0.1%
20060316 2
< 0.1%

조건부허가종료일자
Real number (ℝ)

MISSING 

Distinct9
Distinct (%)81.8%
Missing9989
Missing (%)99.9%
Infinite0
Infinite (%)0.0%
Mean20238788
Minimum20060320
Maximum20360928
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T14:30:56.827295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20060320
5-th percentile20065414
Q120160316
median20260906
Q320360410
95-th percentile20360726
Maximum20360928
Range300608
Interquartile range (IQR)200094

Descriptive statistics

Standard deviation115564.44
Coefficient of variation (CV)0.0057100477
Kurtosis-1.3162682
Mean20238788
Median Absolute Deviation (MAD)99618
Skewness-0.33192584
Sum2.2262667 × 108
Variance1.3355141 × 1010
MonotonicityNot monotonic
2024-05-11T14:30:56.980017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
20360410 2
 
< 0.1%
20160316 2
 
< 0.1%
20260919 1
 
< 0.1%
20060320 1
 
< 0.1%
20260906 1
 
< 0.1%
20070508 1
 
< 0.1%
20360524 1
 
< 0.1%
20360928 1
 
< 0.1%
20211110 1
 
< 0.1%
(Missing) 9989
99.9%
ValueCountFrequency (%)
20060320 1
< 0.1%
20070508 1
< 0.1%
20160316 2
< 0.1%
20211110 1
< 0.1%
20260906 1
< 0.1%
20260919 1
< 0.1%
20360410 2
< 0.1%
20360524 1
< 0.1%
20360928 1
< 0.1%
ValueCountFrequency (%)
20360928 1
< 0.1%
20360524 1
< 0.1%
20360410 2
< 0.1%
20260919 1
< 0.1%
20260906 1
< 0.1%
20211110 1
< 0.1%
20160316 2
< 0.1%
20070508 1
< 0.1%
20060320 1
< 0.1%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7191 
임대
2712 
자가
 
97

Length

Max length4
Median length4
Mean length3.4382
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> 7191
71.9%
임대 2712
 
27.1%
자가 97
 
1.0%

Length

2024-05-11T14:30:57.154756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:30:57.337648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7191
71.9%
임대 2712
 
27.1%
자가 97
 
1.0%

세탁기수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5284 
0
4716 

Length

Max length4
Median length4
Mean length2.5852
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5284
52.8%
0 4716
47.2%

Length

2024-05-11T14:30:57.506690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:30:57.671565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5284
52.8%
0 4716
47.2%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct39
Distinct (%)2.0%
Missing8087
Missing (%)80.9%
Infinite0
Infinite (%)0.0%
Mean2.0313643
Minimum0
Maximum350
Zeros1551
Zeros (%)15.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T14:30:57.806322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5
Maximum350
Range350
Interquartile range (IQR)0

Descriptive statistics

Standard deviation14.864347
Coefficient of variation (CV)7.3174203
Kurtosis240.33791
Mean2.0313643
Median Absolute Deviation (MAD)0
Skewness13.817378
Sum3886
Variance220.94881
MonotonicityNot monotonic
2024-05-11T14:30:57.994534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
0 1551
 
15.5%
1 166
 
1.7%
2 55
 
0.5%
5 24
 
0.2%
3 23
 
0.2%
4 17
 
0.2%
10 9
 
0.1%
6 8
 
0.1%
15 6
 
0.1%
7 5
 
0.1%
Other values (29) 49
 
0.5%
(Missing) 8087
80.9%
ValueCountFrequency (%)
0 1551
15.5%
1 166
 
1.7%
2 55
 
0.5%
3 23
 
0.2%
4 17
 
0.2%
5 24
 
0.2%
6 8
 
0.1%
7 5
 
0.1%
8 3
 
< 0.1%
9 4
 
< 0.1%
ValueCountFrequency (%)
350 1
< 0.1%
250 1
< 0.1%
200 1
< 0.1%
150 1
< 0.1%
142 1
< 0.1%
141 1
< 0.1%
139 1
< 0.1%
137 1
< 0.1%
130 1
< 0.1%
100 2
< 0.1%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct45
Distinct (%)2.3%
Missing8043
Missing (%)80.4%
Infinite0
Infinite (%)0.0%
Mean2.5666837
Minimum0
Maximum300
Zeros1352
Zeros (%)13.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T14:30:58.226540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile8
Maximum300
Range300
Interquartile range (IQR)1

Descriptive statistics

Standard deviation13.948902
Coefficient of variation (CV)5.4346009
Kurtosis187.49018
Mean2.5666837
Median Absolute Deviation (MAD)0
Skewness12.131256
Sum5023
Variance194.57185
MonotonicityNot monotonic
2024-05-11T14:30:58.410880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
0 1352
 
13.5%
1 218
 
2.2%
2 100
 
1.0%
3 79
 
0.8%
4 40
 
0.4%
5 36
 
0.4%
6 17
 
0.2%
10 16
 
0.2%
7 15
 
0.1%
8 10
 
0.1%
Other values (35) 74
 
0.7%
(Missing) 8043
80.4%
ValueCountFrequency (%)
0 1352
13.5%
1 218
 
2.2%
2 100
 
1.0%
3 79
 
0.8%
4 40
 
0.4%
5 36
 
0.4%
6 17
 
0.2%
7 15
 
0.1%
8 10
 
0.1%
9 4
 
< 0.1%
ValueCountFrequency (%)
300 1
 
< 0.1%
228 1
 
< 0.1%
200 1
 
< 0.1%
150 1
 
< 0.1%
140 1
 
< 0.1%
130 1
 
< 0.1%
120 2
< 0.1%
110 1
 
< 0.1%
101 3
< 0.1%
90 1
 
< 0.1%

회수건조수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5751 
0
4249 

Length

Max length4
Median length4
Mean length2.7253
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5751
57.5%
0 4249
42.5%

Length

2024-05-11T14:30:58.651103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:30:58.812612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5751
57.5%
0 4249
42.5%

침대수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5926 
0
4074 

Length

Max length4
Median length4
Mean length2.7778
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5926
59.3%
0 4074
40.7%

Length

2024-05-11T14:30:59.000299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:30:59.205627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5926
59.3%
0 4074
40.7%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1871
Missing (%)18.7%
Memory size97.7 KiB
False
8124 
True
 
5
(Missing)
1871 
ValueCountFrequency (%)
False 8124
81.2%
True 5
 
0.1%
(Missing) 1871
 
18.7%
2024-05-11T14:30:59.349597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
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