Overview

Dataset statistics

Number of variables47
Number of observations10000
Missing cells122681
Missing cells (%)26.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.9 MiB
Average record size in memory411.0 B

Variable types

Numeric11
Text9
DateTime3
Unsupported6
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-16064/S/1/datasetView.do

Alerts

조건부허가신고사유 has constant value ""Constant
데이터갱신구분 is highly imbalanced (60.3%)Imbalance
업태구분명 is highly imbalanced (94.5%)Imbalance
위생업태명 is highly imbalanced (74.2%)Imbalance
발한실여부 is highly imbalanced (99.6%)Imbalance
건물소유구분명 is highly imbalanced (60.5%)Imbalance
여성종사자수 is highly imbalanced (65.8%)Imbalance
남성종사자수 is highly imbalanced (69.5%)Imbalance
침대수 is highly imbalanced (68.6%)Imbalance
다중이용업소여부 is highly imbalanced (97.6%)Imbalance
인허가취소일자 has 10000 (100.0%) missing valuesMissing
폐업일자 has 1571 (15.7%) 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 2247 (22.5%) missing valuesMissing
도로명주소 has 6602 (66.0%) missing valuesMissing
도로명우편번호 has 6663 (66.6%) missing valuesMissing
좌표정보(X) has 1064 (10.6%) missing valuesMissing
좌표정보(Y) has 1064 (10.6%) missing valuesMissing
건물지상층수 has 3366 (33.7%) missing valuesMissing
건물지하층수 has 3731 (37.3%) missing valuesMissing
사용시작지상층 has 4314 (43.1%) missing valuesMissing
사용끝지상층 has 6837 (68.4%) missing valuesMissing
사용시작지하층 has 5029 (50.3%) missing valuesMissing
사용끝지하층 has 7445 (74.5%) missing valuesMissing
발한실여부 has 803 (8.0%) missing valuesMissing
좌석수 has 1230 (12.3%) missing valuesMissing
조건부허가신고사유 has 9999 (> 99.9%) missing valuesMissing
조건부허가시작일자 has 10000 (100.0%) missing valuesMissing
조건부허가종료일자 has 10000 (100.0%) missing valuesMissing
다중이용업소여부 has 702 (7.0%) missing valuesMissing
건물지하층수 is highly skewed (γ1 = 53.07257754)Skewed
사용끝지상층 is highly skewed (γ1 = 29.73031347)Skewed
좌석수 is highly skewed (γ1 = 49.80864765)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
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 4769 (47.7%) zerosZeros
건물지하층수 has 4997 (50.0%) zerosZeros
사용시작지상층 has 3631 (36.3%) zerosZeros
사용끝지상층 has 1280 (12.8%) zerosZeros
사용시작지하층 has 3929 (39.3%) zerosZeros
사용끝지하층 has 1495 (14.9%) zerosZeros
좌석수 has 349 (3.5%) zerosZeros

Reproduction

Analysis started2024-05-11 03:50:43.745543
Analysis finished2024-05-11 03:50:49.717645
Duration5.97 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%
Mean3129677
Minimum3000000
Maximum3240000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T03:50:49.926404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3010000
Q13070000
median3140000
Q33200000
95-th percentile3230000
Maximum3240000
Range240000
Interquartile range (IQR)130000

Descriptive statistics

Standard deviation74057.506
Coefficient of variation (CV)0.023662987
Kurtosis-1.2496403
Mean3129677
Median Absolute Deviation (MAD)70000
Skewness-0.15817038
Sum3.129677 × 1010
Variance5.4845141 × 109
MonotonicityNot monotonic
2024-05-11T03:50:50.317611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
3220000 679
 
6.8%
3230000 629
 
6.3%
3180000 585
 
5.9%
3070000 494
 
4.9%
3150000 492
 
4.9%
3200000 454
 
4.5%
3240000 450
 
4.5%
3060000 441
 
4.4%
3140000 424
 
4.2%
3160000 399
 
4.0%
Other values (15) 4953
49.5%
ValueCountFrequency (%)
3000000 361
3.6%
3010000 393
3.9%
3020000 292
2.9%
3030000 372
3.7%
3040000 327
3.3%
3050000 287
2.9%
3060000 441
4.4%
3070000 494
4.9%
3080000 356
3.6%
3090000 271
2.7%
ValueCountFrequency (%)
3240000 450
4.5%
3230000 629
6.3%
3220000 679
6.8%
3210000 393
3.9%
3200000 454
4.5%
3190000 328
3.3%
3180000 585
5.9%
3170000 246
 
2.5%
3160000 399
4.0%
3150000 492
4.9%

관리번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T03:50:50.864254image/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 row3240000-203-1984-01684
2nd row3000000-203-2002-00010
3rd row3230000-203-1999-02086
4th row3160000-203-2002-00006
5th row3100000-203-2006-00003
ValueCountFrequency (%)
3240000-203-1984-01684 1
 
< 0.1%
3060000-203-1996-00576 1
 
< 0.1%
3010000-203-2004-00014 1
 
< 0.1%
3080000-203-1983-01554 1
 
< 0.1%
3140000-203-1971-00144 1
 
< 0.1%
3140000-203-2013-00004 1
 
< 0.1%
3220000-203-1998-01952 1
 
< 0.1%
3210000-203-2018-00001 1
 
< 0.1%
3110000-203-2023-00012 1
 
< 0.1%
3220000-203-2009-00009 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-05-11T03:50:51.925051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 87588
39.8%
- 30000
 
13.6%
3 25534
 
11.6%
2 23391
 
10.6%
1 19472
 
8.9%
9 11711
 
5.3%
8 5680
 
2.6%
4 4574
 
2.1%
7 4164
 
1.9%
5 3945
 
1.8%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 87588
46.1%
3 25534
 
13.4%
2 23391
 
12.3%
1 19472
 
10.2%
9 11711
 
6.2%
8 5680
 
3.0%
4 4574
 
2.4%
7 4164
 
2.2%
5 3945
 
2.1%
6 3941
 
2.1%
Dash Punctuation
ValueCountFrequency (%)
- 30000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 87588
39.8%
- 30000
 
13.6%
3 25534
 
11.6%
2 23391
 
10.6%
1 19472
 
8.9%
9 11711
 
5.3%
8 5680
 
2.6%
4 4574
 
2.1%
7 4164
 
1.9%
5 3945
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 87588
39.8%
- 30000
 
13.6%
3 25534
 
11.6%
2 23391
 
10.6%
1 19472
 
8.9%
9 11711
 
5.3%
8 5680
 
2.6%
4 4574
 
2.1%
7 4164
 
1.9%
5 3945
 
1.8%

인허가일자
Date

Distinct6423
Distinct (%)64.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1900-01-01 00:00:00
Maximum2024-04-29 00:00:00
2024-05-11T03:50:52.484047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:50:53.071055image/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

영업상태코드
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3
8429 
1
1571 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 8429
84.3%
1 1571
 
15.7%

Length

2024-05-11T03:50:53.622859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:50:53.894786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 8429
84.3%
1 1571
 
15.7%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
8429 
영업/정상
1571 

Length

Max length5
Median length2
Mean length2.4713
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 8429
84.3%
영업/정상 1571
 
15.7%

Length

2024-05-11T03:50:54.252199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:50:54.569731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 8429
84.3%
영업/정상 1571
 
15.7%

상세영업상태코드
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
8429 
1
1571 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 8429
84.3%
1 1571
 
15.7%

Length

2024-05-11T03:50:54.928058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:50:55.350240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 8429
84.3%
1 1571
 
15.7%

상세영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
8429 
영업
1571 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 8429
84.3%
영업 1571
 
15.7%

Length

2024-05-11T03:50:55.857255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:50:56.211985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 8429
84.3%
영업 1571
 
15.7%

폐업일자
Text

MISSING 

Distinct4623
Distinct (%)54.8%
Missing1571
Missing (%)15.7%
Memory size156.2 KiB
2024-05-11T03:50:56.926798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.042947
Min length8

Characters and Unicode

Total characters67794
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

Unique2716 ?
Unique (%)32.2%

Sample

1st row19960419
2nd row20040324
3rd row20000530
4th row20141231
5th row20100621
ValueCountFrequency (%)
20030225 228
 
2.7%
20030226 146
 
1.7%
20030220 39
 
0.5%
20030218 30
 
0.4%
20030215 25
 
0.3%
20020126 24
 
0.3%
20030207 22
 
0.3%
20021009 22
 
0.3%
20030703 21
 
0.2%
20030709 21
 
0.2%
Other values (4613) 7851
93.1%
2024-05-11T03:50:58.322750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 22229
32.8%
2 13852
20.4%
1 11028
16.3%
9 5170
 
7.6%
3 3557
 
5.2%
5 2465
 
3.6%
6 2425
 
3.6%
4 2313
 
3.4%
7 2305
 
3.4%
8 2087
 
3.1%
Other values (2) 363
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 67431
99.5%
Dash Punctuation 362
 
0.5%
Space Separator 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 22229
33.0%
2 13852
20.5%
1 11028
16.4%
9 5170
 
7.7%
3 3557
 
5.3%
5 2465
 
3.7%
6 2425
 
3.6%
4 2313
 
3.4%
7 2305
 
3.4%
8 2087
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 362
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 67794
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 22229
32.8%
2 13852
20.4%
1 11028
16.3%
9 5170
 
7.6%
3 3557
 
5.2%
5 2465
 
3.6%
6 2425
 
3.6%
4 2313
 
3.4%
7 2305
 
3.4%
8 2087
 
3.1%
Other values (2) 363
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 67794
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 22229
32.8%
2 13852
20.4%
1 11028
16.3%
9 5170
 
7.6%
3 3557
 
5.2%
5 2465
 
3.6%
6 2425
 
3.6%
4 2313
 
3.4%
7 2305
 
3.4%
8 2087
 
3.1%
Other values (2) 363
 
0.5%

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 

Distinct6654
Distinct (%)85.8%
Missing2247
Missing (%)22.5%
Memory size156.2 KiB
2024-05-11T03:50:59.600775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.744228
Min length2

Characters and Unicode

Total characters75547
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

Unique6378 ?
Unique (%)82.3%

Sample

1st row02 4739247
2nd row02 9848147
3rd row02 4158173
4th row02 8692050
5th row02 4980934
ValueCountFrequency (%)
02 4947
38.5%
0200000000 247
 
1.9%
00000 223
 
1.7%
0 132
 
1.0%
070 20
 
0.2%
9902660 4
 
< 0.1%
7427565 4
 
< 0.1%
449 4
 
< 0.1%
420 4
 
< 0.1%
718 4
 
< 0.1%
Other values (6867) 7269
56.5%
2024-05-11T03:51:01.583618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15779
20.9%
2 13272
17.6%
6178
 
8.2%
4 5579
 
7.4%
3 5443
 
7.2%
9 5195
 
6.9%
6 5194
 
6.9%
8 5096
 
6.7%
5 4991
 
6.6%
7 4843
 
6.4%
Other values (2) 3977
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 69363
91.8%
Space Separator 6178
 
8.2%
Dash Punctuation 6
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15779
22.7%
2 13272
19.1%
4 5579
 
8.0%
3 5443
 
7.8%
9 5195
 
7.5%
6 5194
 
7.5%
8 5096
 
7.3%
5 4991
 
7.2%
7 4843
 
7.0%
1 3971
 
5.7%
Space Separator
ValueCountFrequency (%)
6178
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 75547
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 15779
20.9%
2 13272
17.6%
6178
 
8.2%
4 5579
 
7.4%
3 5443
 
7.2%
9 5195
 
6.9%
6 5194
 
6.9%
8 5096
 
6.7%
5 4991
 
6.6%
7 4843
 
6.4%
Other values (2) 3977
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 75547
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 15779
20.9%
2 13272
17.6%
6178
 
8.2%
4 5579
 
7.4%
3 5443
 
7.2%
9 5195
 
6.9%
6 5194
 
6.9%
8 5096
 
6.7%
5 4991
 
6.6%
7 4843
 
6.4%
Other values (2) 3977
 
5.3%

소재지면적
Text

Distinct3111
Distinct (%)31.1%
Missing3
Missing (%)< 0.1%
Memory size156.2 KiB
2024-05-11T03:51:02.576328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length4.7694308
Min length3

Characters and Unicode

Total characters47680
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

Unique1879 ?
Unique (%)18.8%

Sample

1st row54.60
2nd row6.00
3rd row9.36
4th row45.00
5th row15.00
ValueCountFrequency (%)
00 790
 
7.9%
10.00 191
 
1.9%
33.00 165
 
1.7%
9.90 148
 
1.5%
6.60 137
 
1.4%
16.50 130
 
1.3%
20.00 110
 
1.1%
13.20 107
 
1.1%
15.00 100
 
1.0%
19.80 96
 
1.0%
Other values (3101) 8023
80.3%
2024-05-11T03:51:03.819062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10498
22.0%
. 9997
21.0%
1 5260
11.0%
2 4249
8.9%
3 2943
 
6.2%
6 2828
 
5.9%
5 2738
 
5.7%
4 2619
 
5.5%
8 2402
 
5.0%
9 2320
 
4.9%
Other values (2) 1826
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 37680
79.0%
Other Punctuation 10000
 
21.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10498
27.9%
1 5260
14.0%
2 4249
11.3%
3 2943
 
7.8%
6 2828
 
7.5%
5 2738
 
7.3%
4 2619
 
7.0%
8 2402
 
6.4%
9 2320
 
6.2%
7 1823
 
4.8%
Other Punctuation
ValueCountFrequency (%)
. 9997
> 99.9%
, 3
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 47680
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10498
22.0%
. 9997
21.0%
1 5260
11.0%
2 4249
8.9%
3 2943
 
6.2%
6 2828
 
5.9%
5 2738
 
5.7%
4 2619
 
5.5%
8 2402
 
5.0%
9 2320
 
4.9%
Other values (2) 1826
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 47680
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10498
22.0%
. 9997
21.0%
1 5260
11.0%
2 4249
8.9%
3 2943
 
6.2%
6 2828
 
5.9%
5 2738
 
5.7%
4 2619
 
5.5%
8 2402
 
5.0%
9 2320
 
4.9%
Other values (2) 1826
 
3.8%

소재지우편번호
Text

Distinct2513
Distinct (%)25.1%
Missing6
Missing (%)0.1%
Memory size156.2 KiB
2024-05-11T03:51:04.750644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.039924
Min length6

Characters and Unicode

Total characters60363
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

Unique807 ?
Unique (%)8.1%

Sample

1st row134830
2nd row110862
3rd row138210
4th row152800
5th row139800
ValueCountFrequency (%)
138210 98
 
1.0%
100450 35
 
0.4%
139240 31
 
0.3%
150841 29
 
0.3%
110320 27
 
0.3%
153801 27
 
0.3%
134830 25
 
0.3%
157930 23
 
0.2%
136865 21
 
0.2%
158860 20
 
0.2%
Other values (2503) 9658
96.6%
2024-05-11T03:51:06.187625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14399
23.9%
8 9894
16.4%
3 7342
12.2%
0 6657
11.0%
5 5532
 
9.2%
2 4853
 
8.0%
4 3535
 
5.9%
7 2716
 
4.5%
6 2572
 
4.3%
9 2464
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59964
99.3%
Dash Punctuation 399
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14399
24.0%
8 9894
16.5%
3 7342
12.2%
0 6657
11.1%
5 5532
 
9.2%
2 4853
 
8.1%
4 3535
 
5.9%
7 2716
 
4.5%
6 2572
 
4.3%
9 2464
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 399
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 60363
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 14399
23.9%
8 9894
16.4%
3 7342
12.2%
0 6657
11.0%
5 5532
 
9.2%
2 4853
 
8.0%
4 3535
 
5.9%
7 2716
 
4.5%
6 2572
 
4.3%
9 2464
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 60363
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14399
23.9%
8 9894
16.4%
3 7342
12.2%
0 6657
11.0%
5 5532
 
9.2%
2 4853
 
8.0%
4 3535
 
5.9%
7 2716
 
4.5%
6 2572
 
4.3%
9 2464
 
4.1%

지번주소
Text

Distinct9196
Distinct (%)92.0%
Missing5
Missing (%)< 0.1%
Memory size156.2 KiB
2024-05-11T03:51:07.060572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length53
Mean length24.547674
Min length16

Characters and Unicode

Total characters245354
Distinct characters537
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8501 ?
Unique (%)85.1%

Sample

1st row서울특별시 강동구 명일동 341-5번지
2nd row서울특별시 종로구 숭인동 55-6번지
3rd row서울특별시 송파구 장지동 산 315-1번지
4th row서울특별시 구로구 가리봉동 106-62번지
5th row서울특별시 노원구 공릉동 238-53번지 태릉사우나(내)
ValueCountFrequency (%)
서울특별시 9995
 
22.3%
강남구 679
 
1.5%
송파구 629
 
1.4%
영등포구 582
 
1.3%
성북구 493
 
1.1%
강서구 492
 
1.1%
관악구 454
 
1.0%
강동구 450
 
1.0%
중랑구 441
 
1.0%
양천구 424
 
0.9%
Other values (9898) 30194
67.3%
2024-05-11T03:51:08.664060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
43895
17.9%
동 11630
 
4.7%
서 11441
 
4.7%
구 10704
 
4.4%
1 10326
 
4.2%
시 10170
 
4.1%
지 10048
 
4.1%
울 10019
 
4.1%
별 9998
 
4.1%
특 9996
 
4.1%
Other values (527) 107127
43.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 143473
58.5%
Decimal Number 47471
 
19.3%
Space Separator 43895
 
17.9%
Dash Punctuation 9133
 
3.7%
Close Punctuation 497
 
0.2%
Open Punctuation 495
 
0.2%
Uppercase Letter 217
 
0.1%
Other Punctuation 135
 
0.1%
Math Symbol 19
 
< 0.1%
Lowercase Letter 17
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 11630
 
8.1%
서 11441
 
8.0%
구 10704
 
7.5%
시 10170
 
7.1%
지 10048
 
7.0%
울 10019
 
7.0%
별 9998
 
7.0%
특 9996
 
7.0%
번 8632
 
6.0%
강 2064
 
1.4%
Other values (472) 48771
34.0%
Uppercase Letter
ValueCountFrequency (%)
B 91
41.9%
A 42
19.4%
S 18
 
8.3%
K 14
 
6.5%
T 9
 
4.1%
P 9
 
4.1%
D 7
 
3.2%
C 5
 
2.3%
G 4
 
1.8%
M 4
 
1.8%
Other values (9) 14
 
6.5%
Lowercase Letter
ValueCountFrequency (%)
b 3
17.6%
a 2
11.8%
t 2
11.8%
e 2
11.8%
s 2
11.8%
p 1
 
5.9%
r 1
 
5.9%
m 1
 
5.9%
y 1
 
5.9%
g 1
 
5.9%
Decimal Number
ValueCountFrequency (%)
1 10326
21.8%
2 6482
13.7%
3 5072
10.7%
4 4336
9.1%
5 4024
 
8.5%
0 4011
 
8.4%
6 3805
 
8.0%
7 3251
 
6.8%
9 3182
 
6.7%
8 2982
 
6.3%
Other Punctuation
ValueCountFrequency (%)
, 96
71.1%
. 24
 
17.8%
@ 8
 
5.9%
/ 5
 
3.7%
: 2
 
1.5%
Math Symbol
ValueCountFrequency (%)
< 8
42.1%
> 8
42.1%
~ 3
 
15.8%
Close Punctuation
ValueCountFrequency (%)
) 464
93.4%
] 33
 
6.6%
Open Punctuation
ValueCountFrequency (%)
( 462
93.3%
[ 33
 
6.7%
Space Separator
ValueCountFrequency (%)
43895
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9133
100.0%
Letter Number
ValueCountFrequency (%)
Ⅲ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 143471
58.5%
Common 101645
41.4%
Latin 236
 
0.1%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 11630
 
8.1%
서 11441
 
8.0%
구 10704
 
7.5%
시 10170
 
7.1%
지 10048
 
7.0%
울 10019
 
7.0%
별 9998
 
7.0%
특 9996
 
7.0%
번 8632
 
6.0%
강 2064
 
1.4%
Other values (470) 48769
34.0%
Latin
ValueCountFrequency (%)
B 91
38.6%
A 42
17.8%
S 18
 
7.6%
K 14
 
5.9%
T 9
 
3.8%
P 9
 
3.8%
D 7
 
3.0%
C 5
 
2.1%
G 4
 
1.7%
M 4
 
1.7%
Other values (21) 33
 
14.0%
Common
ValueCountFrequency (%)
43895
43.2%
1 10326
 
10.2%
- 9133
 
9.0%
2 6482
 
6.4%
3 5072
 
5.0%
4 4336
 
4.3%
5 4024
 
4.0%
0 4011
 
3.9%
6 3805
 
3.7%
7 3251
 
3.2%
Other values (14) 7310
 
7.2%
Han
ValueCountFrequency (%)
內 1
50.0%
家 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 143471
58.5%
ASCII 101879
41.5%
Number Forms 2
 
< 0.1%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
43895
43.1%
1 10326
 
10.1%
- 9133
 
9.0%
2 6482
 
6.4%
3 5072
 
5.0%
4 4336
 
4.3%
5 4024
 
3.9%
0 4011
 
3.9%
6 3805
 
3.7%
7 3251
 
3.2%
Other values (44) 7544
 
7.4%
Hangul
ValueCountFrequency (%)
동 11630
 
8.1%
서 11441
 
8.0%
구 10704
 
7.5%
시 10170
 
7.1%
지 10048
 
7.0%
울 10019
 
7.0%
별 9998
 
7.0%
특 9996
 
7.0%
번 8632
 
6.0%
강 2064
 
1.4%
Other values (470) 48769
34.0%
Number Forms
ValueCountFrequency (%)
Ⅲ 2
100.0%
CJK
ValueCountFrequency (%)
內 1
50.0%
家 1
50.0%

도로명주소
Text

MISSING 

Distinct3312
Distinct (%)97.5%
Missing6602
Missing (%)66.0%
Memory size156.2 KiB
2024-05-11T03:51:09.929735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length53
Mean length30.957916
Min length20

Characters and Unicode

Total characters105195
Distinct characters519
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3238 ?
Unique (%)95.3%

Sample

1st row서울특별시 구로구 구로동로2길 34 (가리봉동)
2nd row서울특별시 강서구 마곡중앙8로 90, 마곡아이파크 2층 206호 (마곡동)
3rd row서울특별시 중구 동호로12길 55, 1층 (신당동)
4th row서울특별시 노원구 동일로178길 29-19, 1층 (공릉동, 584-5)
5th row서울특별시 강북구 삼양로54길 48 (미아동)
ValueCountFrequency (%)
서울특별시 3398
 
16.6%
1층 703
 
3.4%
지하1층 231
 
1.1%
송파구 202
 
1.0%
영등포구 198
 
1.0%
2층 192
 
0.9%
강서구 186
 
0.9%
강남구 168
 
0.8%
은평구 168
 
0.8%
성북구 158
 
0.8%
Other values (4530) 14838
72.6%
2024-05-11T03:51:11.824349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17052
 
16.2%
1 4503
 
4.3%
동 4421
 
4.2%
서 4101
 
3.9%
구 3694
 
3.5%
로 3648
 
3.5%
) 3538
 
3.4%
( 3538
 
3.4%
시 3532
 
3.4%
울 3429
 
3.3%
Other values (509) 53739
51.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 61987
58.9%
Space Separator 17052
 
16.2%
Decimal Number 15858
 
15.1%
Close Punctuation 3539
 
3.4%
Open Punctuation 3539
 
3.4%
Other Punctuation 2555
 
2.4%
Dash Punctuation 494
 
0.5%
Uppercase Letter 159
 
0.2%
Lowercase Letter 8
 
< 0.1%
Letter Number 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 4421
 
7.1%
서 4101
 
6.6%
구 3694
 
6.0%
로 3648
 
5.9%
시 3532
 
5.7%
울 3429
 
5.5%
별 3400
 
5.5%
특 3399
 
5.5%
길 2143
 
3.5%
층 1752
 
2.8%
Other values (464) 28468
45.9%
Uppercase Letter
ValueCountFrequency (%)
B 75
47.2%
A 23
 
14.5%
K 11
 
6.9%
S 11
 
6.9%
C 7
 
4.4%
M 6
 
3.8%
G 4
 
2.5%
T 4
 
2.5%
R 3
 
1.9%
P 3
 
1.9%
Other values (7) 12
 
7.5%
Decimal Number
ValueCountFrequency (%)
1 4503
28.4%
2 2419
15.3%
3 1746
 
11.0%
4 1358
 
8.6%
0 1220
 
7.7%
5 1148
 
7.2%
6 988
 
6.2%
7 933
 
5.9%
8 807
 
5.1%
9 736
 
4.6%
Lowercase Letter
ValueCountFrequency (%)
s 2
25.0%
e 2
25.0%
t 1
12.5%
a 1
12.5%
b 1
12.5%
k 1
12.5%
Other Punctuation
ValueCountFrequency (%)
, 2547
99.7%
. 5
 
0.2%
@ 2
 
0.1%
/ 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 3538
> 99.9%
] 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 3538
> 99.9%
[ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
17052
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 494
100.0%
Letter Number
ValueCountFrequency (%)
Ⅲ 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 61985
58.9%
Common 43039
40.9%
Latin 169
 
0.2%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 4421
 
7.1%
서 4101
 
6.6%
구 3694
 
6.0%
로 3648
 
5.9%
시 3532
 
5.7%
울 3429
 
5.5%
별 3400
 
5.5%
특 3399
 
5.5%
길 2143
 
3.5%
층 1752
 
2.8%
Other values (462) 28466
45.9%
Latin
ValueCountFrequency (%)
B 75
44.4%
A 23
 
13.6%
K 11
 
6.5%
S 11
 
6.5%
C 7
 
4.1%
M 6
 
3.6%
G 4
 
2.4%
T 4
 
2.4%
R 3
 
1.8%
P 3
 
1.8%
Other values (14) 22
 
13.0%
Common
ValueCountFrequency (%)
17052
39.6%
1 4503
 
10.5%
) 3538
 
8.2%
( 3538
 
8.2%
, 2547
 
5.9%
2 2419
 
5.6%
3 1746
 
4.1%
4 1358
 
3.2%
0 1220
 
2.8%
5 1148
 
2.7%
Other values (11) 3970
 
9.2%
Han
ValueCountFrequency (%)
家 1
50.0%
內 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 61985
58.9%
ASCII 43206
41.1%
Number Forms 2
 
< 0.1%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17052
39.5%
1 4503
 
10.4%
) 3538
 
8.2%
( 3538
 
8.2%
, 2547
 
5.9%
2 2419
 
5.6%
3 1746
 
4.0%
4 1358
 
3.1%
0 1220
 
2.8%
5 1148
 
2.7%
Other values (34) 4137
 
9.6%
Hangul
ValueCountFrequency (%)
동 4421
 
7.1%
서 4101
 
6.6%
구 3694
 
6.0%
로 3648
 
5.9%
시 3532
 
5.7%
울 3429
 
5.5%
별 3400
 
5.5%
특 3399
 
5.5%
길 2143
 
3.5%
층 1752
 
2.8%
Other values (462) 28466
45.9%
Number Forms
ValueCountFrequency (%)
Ⅲ 2
100.0%
CJK
ValueCountFrequency (%)
家 1
50.0%
內 1
50.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct2091
Distinct (%)62.7%
Missing6663
Missing (%)66.6%
Infinite0
Infinite (%)0.0%
Mean5069.5511
Minimum1002
Maximum8864
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T03:51:12.324872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1002
5-th percentile1410.8
Q13116
median5057
Q37251
95-th percentile8620
Maximum8864
Range7862
Interquartile range (IQR)4135

Descriptive statistics

Standard deviation2301.0323
Coefficient of variation (CV)0.45389272
Kurtosis-1.2148668
Mean5069.5511
Median Absolute Deviation (MAD)2156
Skewness-0.028369864
Sum16917092
Variance5294749.8
MonotonicityNot monotonic
2024-05-11T03:51:12.891212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7250 11
 
0.1%
2737 10
 
0.1%
3462 10
 
0.1%
4710 9
 
0.1%
4564 8
 
0.1%
2176 8
 
0.1%
3336 8
 
0.1%
3140 8
 
0.1%
6164 7
 
0.1%
7604 7
 
0.1%
Other values (2081) 3251
32.5%
(Missing) 6663
66.6%
ValueCountFrequency (%)
1002 1
 
< 0.1%
1005 1
 
< 0.1%
1015 1
 
< 0.1%
1024 3
< 0.1%
1026 2
< 0.1%
1030 1
 
< 0.1%
1031 1
 
< 0.1%
1035 1
 
< 0.1%
1039 2
< 0.1%
1041 1
 
< 0.1%
ValueCountFrequency (%)
8864 1
< 0.1%
8863 1
< 0.1%
8862 1
< 0.1%
8859 1
< 0.1%
8858 1
< 0.1%
8857 2
< 0.1%
8856 1
< 0.1%
8854 2
< 0.1%
8852 1
< 0.1%
8850 1
< 0.1%

사업장명
Text

Distinct5501
Distinct (%)55.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T03:51:13.665531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length35
Mean length4.2121
Min length1

Characters and Unicode

Total characters42121
Distinct characters735
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4186 ?
Unique (%)41.9%

Sample

1st row삼원
2nd row수석사우나
3rd row장수목욕탕이용소
4th row은성
5th row태릉사우나이용원
ValueCountFrequency (%)
이용원 189
 
1.7%
현대 101
 
0.9%
바버샵 97
 
0.9%
대성 60
 
0.5%
내 53
 
0.5%
중앙 52
 
0.5%
태후사랑 48
 
0.4%
제일 46
 
0.4%
태양 43
 
0.4%
이발소 42
 
0.4%
Other values (5502) 10279
93.4%
2024-05-11T03:51:15.222115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 3955
 
9.4%
용 2791
 
6.6%
원 2619
 
6.2%
성 1049
 
2.5%
발 1030
 
2.4%
1013
 
2.4%
우 846
 
2.0%
대 774
 
1.8%
관 659
 
1.6%
사 641
 
1.5%
Other values (725) 26744
63.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 38981
92.5%
Space Separator 1013
 
2.4%
Uppercase Letter 739
 
1.8%
Lowercase Letter 640
 
1.5%
Close Punctuation 248
 
0.6%
Open Punctuation 248
 
0.6%
Decimal Number 152
 
0.4%
Other Punctuation 55
 
0.1%
Modifier Symbol 40
 
0.1%
Dash Punctuation 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 3955
 
10.1%
용 2791
 
7.2%
원 2619
 
6.7%
성 1049
 
2.7%
발 1030
 
2.6%
우 846
 
2.2%
대 774
 
2.0%
관 659
 
1.7%
사 641
 
1.6%
나 624
 
1.6%
Other values (654) 23993
61.6%
Uppercase Letter
ValueCountFrequency (%)
B 111
15.0%
R 71
 
9.6%
E 63
 
8.5%
O 62
 
8.4%
S 62
 
8.4%
A 56
 
7.6%
H 41
 
5.5%
M 32
 
4.3%
P 32
 
4.3%
T 26
 
3.5%
Other values (15) 183
24.8%
Lowercase Letter
ValueCountFrequency (%)
r 93
14.5%
o 66
10.3%
a 63
9.8%
e 62
9.7%
h 50
7.8%
b 48
 
7.5%
s 47
 
7.3%
p 42
 
6.6%
n 23
 
3.6%
i 23
 
3.6%
Other values (14) 123
19.2%
Decimal Number
ValueCountFrequency (%)
2 37
24.3%
1 28
18.4%
3 16
10.5%
4 16
10.5%
8 14
 
9.2%
0 14
 
9.2%
9 10
 
6.6%
7 8
 
5.3%
6 7
 
4.6%
5 2
 
1.3%
Other Punctuation
ValueCountFrequency (%)
. 28
50.9%
? 14
25.5%
' 4
 
7.3%
& 4
 
7.3%
, 2
 
3.6%
# 2
 
3.6%
! 1
 
1.8%
Space Separator
ValueCountFrequency (%)
1013
100.0%
Close Punctuation
ValueCountFrequency (%)
) 248
100.0%
Open Punctuation
ValueCountFrequency (%)
( 248
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 40
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 38977
92.5%
Common 1761
 
4.2%
Latin 1379
 
3.3%
Han 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 3955
 
10.1%
용 2791
 
7.2%
원 2619
 
6.7%
성 1049
 
2.7%
발 1030
 
2.6%
우 846
 
2.2%
대 774
 
2.0%
관 659
 
1.7%
사 641
 
1.6%
나 624
 
1.6%
Other values (651) 23989
61.5%
Latin
ValueCountFrequency (%)
B 111
 
8.0%
r 93
 
6.7%
R 71
 
5.1%
o 66
 
4.8%
E 63
 
4.6%
a 63
 
4.6%
O 62
 
4.5%
e 62
 
4.5%
S 62
 
4.5%
A 56
 
4.1%
Other values (39) 670
48.6%
Common
ValueCountFrequency (%)
1013
57.5%
) 248
 
14.1%
( 248
 
14.1%
` 40
 
2.3%
2 37
 
2.1%
. 28
 
1.6%
1 28
 
1.6%
3 16
 
0.9%
4 16
 
0.9%
8 14
 
0.8%
Other values (12) 73
 
4.1%
Han
ValueCountFrequency (%)
美 2
50.0%
內 1
25.0%
髮 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 38977
92.5%
ASCII 3140
 
7.5%
CJK 4
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 3955
 
10.1%
용 2791
 
7.2%
원 2619
 
6.7%
성 1049
 
2.7%
발 1030
 
2.6%
우 846
 
2.2%
대 774
 
2.0%
관 659
 
1.7%
사 641
 
1.6%
나 624
 
1.6%
Other values (651) 23989
61.5%
ASCII
ValueCountFrequency (%)
1013
32.3%
) 248
 
7.9%
( 248
 
7.9%
B 111
 
3.5%
r 93
 
3.0%
R 71
 
2.3%
o 66
 
2.1%
E 63
 
2.0%
a 63
 
2.0%
O 62
 
2.0%
Other values (61) 1102
35.1%
CJK
ValueCountFrequency (%)
美 2
50.0%
內 1
25.0%
髮 1
25.0%

최종수정일자
Date

Distinct5300
Distinct (%)53.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1998-12-28 00:00:00
Maximum2024-05-07 14:04:19
2024-05-11T03:51:15.704225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:51:16.392069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
I
8424 
U
1575 
D
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
I 8424
84.2%
U 1575
 
15.8%
D 1
 
< 0.1%

Length

2024-05-11T03:51:16.968047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:51:17.336054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 8424
84.2%
u 1575
 
15.8%
d 1
 
< 0.1%

데이터갱신일자
Date

Distinct1009
Distinct (%)10.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T03:51:17.694978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:51:18.291188image/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
일반이용업
9937 
이용업 기타
 
63

Length

Max length6
Median length5
Mean length5.0063
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반이용업 9937
99.4%
이용업 기타 63
 
0.6%

Length

2024-05-11T03:51:18.967138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:51:19.531852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 9937
98.7%
이용업 63
 
0.6%
기타 63
 
0.6%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct7145
Distinct (%)80.0%
Missing1064
Missing (%)10.6%
Infinite0
Infinite (%)0.0%
Mean199177.75
Minimum182824.24
Maximum215784.23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T03:51:20.132905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum182824.24
5-th percentile186189.33
Q1192606.36
median200929.9
Q3205085.03
95-th percentile211167.97
Maximum215784.23
Range32959.987
Interquartile range (IQR)12478.672

Descriptive statistics

Standard deviation7676.5168
Coefficient of variation (CV)0.038541036
Kurtosis-0.98903436
Mean199177.75
Median Absolute Deviation (MAD)6118.2423
Skewness-0.16895804
Sum1.7798524 × 109
Variance58928910
MonotonicityNot monotonic
2024-05-11T03:51:20.978328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
200573.641273539 8
 
0.1%
208826.080479215 8
 
0.1%
201778.047712477 8
 
0.1%
208589.363343145 8
 
0.1%
198097.13526738 7
 
0.1%
189151.208015925 7
 
0.1%
203109.497601817 7
 
0.1%
205784.868811814 7
 
0.1%
198966.466796388 6
 
0.1%
184806.911534822 6
 
0.1%
Other values (7135) 8864
88.6%
(Missing) 1064
 
10.6%
ValueCountFrequency (%)
182824.239159965 1
 
< 0.1%
182846.62641593 1
 
< 0.1%
182895.668483962 2
< 0.1%
182914.598086861 2
< 0.1%
182914.770762913 1
 
< 0.1%
182952.663773451 3
< 0.1%
182965.529 1
 
< 0.1%
182974.850127567 1
 
< 0.1%
182987.898184342 1
 
< 0.1%
182988.912846535 1
 
< 0.1%
ValueCountFrequency (%)
215784.2264 1
< 0.1%
215529.243568958 1
< 0.1%
215262.790485979 1
< 0.1%
215205.312340831 1
< 0.1%
215150.132527852 2
< 0.1%
215146.854075218 1
< 0.1%
215073.592252889 1
< 0.1%
215051.474081395 1
< 0.1%
215026.052279284 1
< 0.1%
215022.205774223 1
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct7145
Distinct (%)80.0%
Missing1064
Missing (%)10.6%
Infinite0
Infinite (%)0.0%
Mean449443.32
Minimum436909.87
Maximum465103.76
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T03:51:21.640083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum436909.87
5-th percentile441872.6
Q1444759.44
median448767.35
Q3453125.38
95-th percentile460125.43
Maximum465103.76
Range28193.885
Interquartile range (IQR)8365.9318

Descriptive statistics

Standard deviation5616.635
Coefficient of variation (CV)0.01249687
Kurtosis-0.473117
Mean449443.32
Median Absolute Deviation (MAD)4135.4105
Skewness0.47275836
Sum4.0162255 × 109
Variance31546588
MonotonicityNot monotonic
2024-05-11T03:51:22.236512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
451621.036467544 8
 
0.1%
455184.106068148 8
 
0.1%
453855.56648031 8
 
0.1%
445455.90405262 8
 
0.1%
441468.017877057 7
 
0.1%
448200.067716589 7
 
0.1%
456180.732746123 7
 
0.1%
450883.524006222 7
 
0.1%
452608.062544497 6
 
0.1%
448551.489178583 6
 
0.1%
Other values (7135) 8864
88.6%
(Missing) 1064
 
10.6%
ValueCountFrequency (%)
436909.870493711 1
 
< 0.1%
436991.446935421 1
 
< 0.1%
437199.30787957 1
 
< 0.1%
437571.204954672 1
 
< 0.1%
437656.844199862 1
 
< 0.1%
437749.431223746 1
 
< 0.1%
437773.987067282 1
 
< 0.1%
437777.824339474 1
 
< 0.1%
437811.811502379 1
 
< 0.1%
437914.06299827 5
0.1%
ValueCountFrequency (%)
465103.755134816 1
< 0.1%
464905.033086911 1
< 0.1%
464819.528370118 1
< 0.1%
464814.717432497 2
< 0.1%
464771.812601885 1
< 0.1%
464731.761130542 1
< 0.1%
464649.181808576 1
< 0.1%
464638.133327247 1
< 0.1%
464625.423162623 2
< 0.1%
464621.700290709 1
< 0.1%

위생업태명
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
일반이용업
9251 
<NA>
 
702
이용업 기타
 
47

Length

Max length6
Median length5
Mean length4.9345
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반이용업 9251
92.5%
<NA> 702
 
7.0%
이용업 기타 47
 
0.5%

Length

2024-05-11T03:51:22.679533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:51:23.002556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 9251
92.1%
na 702
 
7.0%
이용업 47
 
0.5%
기타 47
 
0.5%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct31
Distinct (%)0.5%
Missing3366
Missing (%)33.7%
Infinite0
Infinite (%)0.0%
Mean1.0717516
Minimum0
Maximum63
Zeros4769
Zeros (%)47.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T03:51:23.372231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile5
Maximum63
Range63
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.5804074
Coefficient of variation (CV)2.4076544
Kurtosis102.76015
Mean1.0717516
Median Absolute Deviation (MAD)0
Skewness7.0410423
Sum7110
Variance6.6585024
MonotonicityNot monotonic
2024-05-11T03:51:23.789629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 4769
47.7%
3 554
 
5.5%
2 364
 
3.6%
4 328
 
3.3%
1 234
 
2.3%
5 157
 
1.6%
6 60
 
0.6%
7 38
 
0.4%
8 25
 
0.2%
10 20
 
0.2%
Other values (21) 85
 
0.9%
(Missing) 3366
33.7%
ValueCountFrequency (%)
0 4769
47.7%
1 234
 
2.3%
2 364
 
3.6%
3 554
 
5.5%
4 328
 
3.3%
5 157
 
1.6%
6 60
 
0.6%
7 38
 
0.4%
8 25
 
0.2%
9 18
 
0.2%
ValueCountFrequency (%)
63 1
< 0.1%
54 1
< 0.1%
37 1
< 0.1%
36 1
< 0.1%
27 1
< 0.1%
26 2
< 0.1%
25 1
< 0.1%
24 2
< 0.1%
23 1
< 0.1%
21 1
< 0.1%

건물지하층수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct12
Distinct (%)0.2%
Missing3731
Missing (%)37.3%
Infinite0
Infinite (%)0.0%
Mean0.28744616
Minimum0
Maximum101
Zeros4997
Zeros (%)50.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T03:51:24.166963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum101
Range101
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.4607185
Coefficient of variation (CV)5.0817115
Kurtosis3611.1457
Mean0.28744616
Median Absolute Deviation (MAD)0
Skewness53.072578
Sum1802
Variance2.1336985
MonotonicityNot monotonic
2024-05-11T03:51:24.532848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 4997
50.0%
1 1066
 
10.7%
2 106
 
1.1%
3 41
 
0.4%
4 28
 
0.3%
5 16
 
0.2%
6 8
 
0.1%
7 3
 
< 0.1%
9 1
 
< 0.1%
101 1
 
< 0.1%
Other values (2) 2
 
< 0.1%
(Missing) 3731
37.3%
ValueCountFrequency (%)
0 4997
50.0%
1 1066
 
10.7%
2 106
 
1.1%
3 41
 
0.4%
4 28
 
0.3%
5 16
 
0.2%
6 8
 
0.1%
7 3
 
< 0.1%
9 1
 
< 0.1%
12 1
 
< 0.1%
ValueCountFrequency (%)
101 1
 
< 0.1%
18 1
 
< 0.1%
12 1
 
< 0.1%
9 1
 
< 0.1%
7 3
 
< 0.1%
6 8
 
0.1%
5 16
 
0.2%
4 28
 
0.3%
3 41
 
0.4%
2 106
1.1%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct18
Distinct (%)0.3%
Missing4314
Missing (%)43.1%
Infinite0
Infinite (%)0.0%
Mean0.58037285
Minimum0
Maximum28
Zeros3631
Zeros (%)36.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T03:51:24.843876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum28
Range28
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.1609878
Coefficient of variation (CV)2.0004171
Kurtosis93.584922
Mean0.58037285
Median Absolute Deviation (MAD)0
Skewness6.6017085
Sum3300
Variance1.3478926
MonotonicityNot monotonic
2024-05-11T03:51:25.202650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 3631
36.3%
1 1355
 
13.6%
2 473
 
4.7%
3 132
 
1.3%
4 34
 
0.3%
5 20
 
0.2%
6 14
 
0.1%
7 10
 
0.1%
8 4
 
< 0.1%
9 3
 
< 0.1%
Other values (8) 10
 
0.1%
(Missing) 4314
43.1%
ValueCountFrequency (%)
0 3631
36.3%
1 1355
 
13.6%
2 473
 
4.7%
3 132
 
1.3%
4 34
 
0.3%
5 20
 
0.2%
6 14
 
0.1%
7 10
 
0.1%
8 4
 
< 0.1%
9 3
 
< 0.1%
ValueCountFrequency (%)
28 1
 
< 0.1%
18 1
 
< 0.1%
17 1
 
< 0.1%
16 1
 
< 0.1%
15 1
 
< 0.1%
14 1
 
< 0.1%
12 3
< 0.1%
10 1
 
< 0.1%
9 3
< 0.1%
8 4
< 0.1%

사용끝지상층
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct19
Distinct (%)0.6%
Missing6837
Missing (%)68.4%
Infinite0
Infinite (%)0.0%
Mean0.98545684
Minimum0
Maximum102
Zeros1280
Zeros (%)12.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T03:51:25.654304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile3
Maximum102
Range102
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.256576
Coefficient of variation (CV)2.289878
Kurtosis1280.1609
Mean0.98545684
Median Absolute Deviation (MAD)1
Skewness29.730313
Sum3117
Variance5.092135
MonotonicityNot monotonic
2024-05-11T03:51:26.019806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 1280
 
12.8%
1 1237
 
12.4%
2 439
 
4.4%
3 125
 
1.2%
4 29
 
0.3%
5 17
 
0.2%
6 10
 
0.1%
7 9
 
0.1%
8 4
 
< 0.1%
9 3
 
< 0.1%
Other values (9) 10
 
0.1%
(Missing) 6837
68.4%
ValueCountFrequency (%)
0 1280
12.8%
1 1237
12.4%
2 439
 
4.4%
3 125
 
1.2%
4 29
 
0.3%
5 17
 
0.2%
6 10
 
0.1%
7 9
 
0.1%
8 4
 
< 0.1%
9 3
 
< 0.1%
ValueCountFrequency (%)
102 1
 
< 0.1%
28 1
 
< 0.1%
18 1
 
< 0.1%
17 1
 
< 0.1%
16 1
 
< 0.1%
15 1
 
< 0.1%
14 1
 
< 0.1%
12 2
< 0.1%
10 1
 
< 0.1%
9 3
< 0.1%

사용시작지하층
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.1%
Missing5029
Missing (%)50.3%
Infinite0
Infinite (%)0.0%
Mean0.24260712
Minimum0
Maximum6
Zeros3929
Zeros (%)39.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T03:51:26.552371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.51485299
Coefficient of variation (CV)2.1221677
Kurtosis9.5042296
Mean0.24260712
Median Absolute Deviation (MAD)0
Skewness2.5253202
Sum1206
Variance0.2650736
MonotonicityNot monotonic
2024-05-11T03:51:26.892991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 3929
39.3%
1 905
 
9.0%
2 117
 
1.2%
3 16
 
0.2%
4 2
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
(Missing) 5029
50.3%
ValueCountFrequency (%)
0 3929
39.3%
1 905
 
9.0%
2 117
 
1.2%
3 16
 
0.2%
4 2
 
< 0.1%
5 1
 
< 0.1%
6 1
 
< 0.1%
ValueCountFrequency (%)
6 1
 
< 0.1%
5 1
 
< 0.1%
4 2
 
< 0.1%
3 16
 
0.2%
2 117
 
1.2%
1 905
 
9.0%
0 3929
39.3%

사용끝지하층
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.3%
Missing7445
Missing (%)74.5%
Infinite0
Infinite (%)0.0%
Mean0.48219178
Minimum0
Maximum6
Zeros1495
Zeros (%)14.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T03:51:27.177553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum6
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.64421397
Coefficient of variation (CV)1.3360119
Kurtosis4.2446951
Mean0.48219178
Median Absolute Deviation (MAD)0
Skewness1.4865544
Sum1232
Variance0.41501164
MonotonicityNot monotonic
2024-05-11T03:51:27.518383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 1495
 
14.9%
1 915
 
9.2%
2 126
 
1.3%
3 14
 
0.1%
4 3
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
(Missing) 7445
74.5%
ValueCountFrequency (%)
0 1495
14.9%
1 915
9.2%
2 126
 
1.3%
3 14
 
0.1%
4 3
 
< 0.1%
5 1
 
< 0.1%
6 1
 
< 0.1%
ValueCountFrequency (%)
6 1
 
< 0.1%
5 1
 
< 0.1%
4 3
 
< 0.1%
3 14
 
0.1%
2 126
 
1.3%
1 915
9.2%
0 1495
14.9%

한실수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
5424 
<NA>
4576 

Length

Max length4
Median length1
Mean length2.3728
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 5424
54.2%
<NA> 4576
45.8%

Length

2024-05-11T03:51:28.001684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:51:28.325111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5424
54.2%
na 4576
45.8%

양실수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
5424 
<NA>
4576 

Length

Max length4
Median length1
Mean length2.3728
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 5424
54.2%
<NA> 4576
45.8%

Length

2024-05-11T03:51:28.669318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:51:29.023778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5424
54.2%
na 4576
45.8%

욕실수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
5424 
<NA>
4576 

Length

Max length4
Median length1
Mean length2.3728
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 5424
54.2%
<NA> 4576
45.8%

Length

2024-05-11T03:51:29.484430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:51:30.099906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5424
54.2%
na 4576
45.8%

발한실여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing803
Missing (%)8.0%
Memory size97.7 KiB
False
9194 
True
 
3
(Missing)
 
803
ValueCountFrequency (%)
False 9194
91.9%
True 3
 
< 0.1%
(Missing) 803
 
8.0%
2024-05-11T03:51:30.460361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct20
Distinct (%)0.2%
Missing1230
Missing (%)12.3%
Infinite0
Infinite (%)0.0%
Mean4.0290764
Minimum0
Maximum433
Zeros349
Zeros (%)3.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T03:51:30.775994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q35
95-th percentile9
Maximum433
Range433
Interquartile range (IQR)3

Descriptive statistics

Standard deviation5.9678462
Coefficient of variation (CV)1.4811946
Kurtosis3277.9475
Mean4.0290764
Median Absolute Deviation (MAD)1
Skewness49.808648
Sum35335
Variance35.615188
MonotonicityNot monotonic
2024-05-11T03:51:31.308233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
3 2351
23.5%
2 2176
21.8%
4 1072
10.7%
5 571
 
5.7%
7 502
 
5.0%
8 422
 
4.2%
6 418
 
4.2%
0 349
 
3.5%
9 325
 
3.2%
1 268
 
2.7%
Other values (10) 316
 
3.2%
(Missing) 1230
12.3%
ValueCountFrequency (%)
0 349
 
3.5%
1 268
 
2.7%
2 2176
21.8%
3 2351
23.5%
4 1072
10.7%
5 571
 
5.7%
6 418
 
4.2%
7 502
 
5.0%
8 422
 
4.2%
9 325
 
3.2%
ValueCountFrequency (%)
433 1
 
< 0.1%
194 2
 
< 0.1%
35 1
 
< 0.1%
16 1
 
< 0.1%
15 8
 
0.1%
14 2
 
< 0.1%
13 10
 
0.1%
12 30
 
0.3%
11 76
0.8%
10 185
1.8%

조건부허가신고사유
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing9999
Missing (%)> 99.9%
Memory size156.2 KiB
2024-05-11T03:51:31.757553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters22
Distinct characters19
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row시설기준위반 유선통보(2008.5.29)
ValueCountFrequency (%)
시설기준위반 1
50.0%
유선통보(2008.5.29 1
50.0%
2024-05-11T03:51:32.802357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 2
 
9.1%
0 2
 
9.1%
2 2
 
9.1%
시 1
 
4.5%
보 1
 
4.5%
9 1
 
4.5%
5 1
 
4.5%
8 1
 
4.5%
( 1
 
4.5%
통 1
 
4.5%
Other values (9) 9
40.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10
45.5%
Decimal Number 7
31.8%
Other Punctuation 2
 
9.1%
Open Punctuation 1
 
4.5%
Space Separator 1
 
4.5%
Close Punctuation 1
 
4.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 1
10.0%
보 1
10.0%
통 1
10.0%
설 1
10.0%
선 1
10.0%
유 1
10.0%
반 1
10.0%
위 1
10.0%
준 1
10.0%
기 1
10.0%
Decimal Number
ValueCountFrequency (%)
0 2
28.6%
2 2
28.6%
9 1
14.3%
5 1
14.3%
8 1
14.3%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12
54.5%
Hangul 10
45.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 1
10.0%
보 1
10.0%
통 1
10.0%
설 1
10.0%
선 1
10.0%
유 1
10.0%
반 1
10.0%
위 1
10.0%
준 1
10.0%
기 1
10.0%
Common
ValueCountFrequency (%)
. 2
16.7%
0 2
16.7%
2 2
16.7%
9 1
8.3%
5 1
8.3%
8 1
8.3%
( 1
8.3%
1
8.3%
) 1
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12
54.5%
Hangul 10
45.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 2
16.7%
0 2
16.7%
2 2
16.7%
9 1
8.3%
5 1
8.3%
8 1
8.3%
( 1
8.3%
1
8.3%
) 1
8.3%
Hangul
ValueCountFrequency (%)
시 1
10.0%
보 1
10.0%
통 1
10.0%
설 1
10.0%
선 1
10.0%
유 1
10.0%
반 1
10.0%
위 1
10.0%
준 1
10.0%
기 1
10.0%

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8519 
임대
1451 
자가
 
30

Length

Max length4
Median length4
Mean length3.7038
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> 8519
85.2%
임대 1451
 
14.5%
자가 30
 
0.3%

Length

2024-05-11T03:51:33.467236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:51:33.954116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8519
85.2%
임대 1451
 
14.5%
자가 30
 
0.3%

세탁기수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7315 
0
2685 

Length

Max length4
Median length4
Mean length3.1945
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7315
73.2%
0 2685
 
26.9%

Length

2024-05-11T03:51:34.313432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:51:34.674803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7315
73.2%
0 2685
 
26.9%

여성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8299 
0
1667 
1
 
30
2
 
4

Length

Max length4
Median length4
Mean length3.4897
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8299
83.0%
0 1667
 
16.7%
1 30
 
0.3%
2 4
 
< 0.1%

Length

2024-05-11T03:51:35.081751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:51:35.454539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8299
83.0%
0 1667
 
16.7%
1 30
 
0.3%
2 4
 
< 0.1%

남성종사자수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8293 
0
1626 
1
 
78
2
 
2
3
 
1

Length

Max length4
Median length4
Mean length3.4879
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8293
82.9%
0 1626
 
16.3%
1 78
 
0.8%
2 2
 
< 0.1%
3 1
 
< 0.1%

Length

2024-05-11T03:51:35.956791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:51:36.389014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8293
82.9%
0 1626
 
16.3%
1 78
 
0.8%
2 2
 
< 0.1%
3 1
 
< 0.1%

회수건조수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7541 
0
2459 

Length

Max length4
Median length4
Mean length3.2623
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7541
75.4%
0 2459
 
24.6%

Length

2024-05-11T03:51:36.840192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:51:37.231282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7541
75.4%
0 2459
 
24.6%

침대수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7565 
0
2424 
1
 
7
2
 
2
6
 
1

Length

Max length4
Median length4
Mean length3.2695
Min length1

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> 7565
75.6%
0 2424
 
24.2%
1 7
 
0.1%
2 2
 
< 0.1%
6 1
 
< 0.1%
4 1
 
< 0.1%

Length

2024-05-11T03:51:37.648614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:51:38.115000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7565
75.6%
0 2424
 
24.2%
1 7
 
0.1%
2 2
 
< 0.1%
6 1
 
< 0.1%
4 1
 
< 0.1%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing702
Missing (%)7.0%
Memory size97.7 KiB
False
9276 
True
 
22
(Missing)
 
702
ValueCountFrequency (%)
False 9276
92.8%
True 22
 
0.2%
(Missing) 702
 
7.0%
2024-05-11T03:51:38.602267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

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