Overview

Dataset statistics

Number of variables47
Number of observations3919
Missing cells40381
Missing cells (%)21.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 MiB
Average record size in memory403.0 B

Variable types

Numeric11
Text8
DateTime4
Unsupported4
Categorical18
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-16146/S/1/datasetView.do

Alerts

업태구분명 is highly imbalanced (55.2%)Imbalance
좌석수 is highly imbalanced (56.5%)Imbalance
조건부허가시작일자 is highly imbalanced (99.6%)Imbalance
조건부허가종료일자 is highly imbalanced (99.6%)Imbalance
여성종사자수 is highly imbalanced (87.6%)Imbalance
남성종사자수 is highly imbalanced (87.4%)Imbalance
다중이용업소여부 is highly imbalanced (93.8%)Imbalance
인허가취소일자 has 3919 (100.0%) missing valuesMissing
폐업일자 has 677 (17.3%) missing valuesMissing
휴업시작일자 has 3919 (100.0%) missing valuesMissing
휴업종료일자 has 3919 (100.0%) missing valuesMissing
재개업일자 has 3919 (100.0%) missing valuesMissing
전화번호 has 211 (5.4%) missing valuesMissing
도로명주소 has 2449 (62.5%) missing valuesMissing
도로명우편번호 has 2499 (63.8%) missing valuesMissing
좌표정보(X) has 404 (10.3%) missing valuesMissing
좌표정보(Y) has 404 (10.3%) missing valuesMissing
건물지상층수 has 1310 (33.4%) missing valuesMissing
건물지하층수 has 1448 (36.9%) missing valuesMissing
사용시작지상층 has 1696 (43.3%) missing valuesMissing
사용끝지상층 has 2788 (71.1%) missing valuesMissing
사용시작지하층 has 1768 (45.1%) missing valuesMissing
사용끝지하층 has 2889 (73.7%) missing valuesMissing
욕실수 has 1497 (38.2%) missing valuesMissing
발한실여부 has 368 (9.4%) missing valuesMissing
조건부허가신고사유 has 3916 (99.9%) missing valuesMissing
다중이용업소여부 has 367 (9.4%) missing valuesMissing
사용끝지하층 is highly skewed (γ1 = 28.99344434)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 1674 (42.7%) zerosZeros
건물지하층수 has 1714 (43.7%) zerosZeros
사용시작지상층 has 1537 (39.2%) zerosZeros
사용끝지상층 has 398 (10.2%) zerosZeros
사용시작지하층 has 1511 (38.6%) zerosZeros
사용끝지하층 has 351 (9.0%) zerosZeros
욕실수 has 1582 (40.4%) zerosZeros

Reproduction

Analysis started2024-05-18 03:30:59.979083
Analysis finished2024-05-18 03:31:04.091583
Duration4.11 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Real number (ℝ)

Distinct25
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3127828.5
Minimum3000000
Maximum3240000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size34.6 KiB
2024-05-18T12:31:04.358816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3010000
Q13060000
median3130000
Q33210000
95-th percentile3230000
Maximum3240000
Range240000
Interquartile range (IQR)150000

Descriptive statistics

Standard deviation77745.512
Coefficient of variation (CV)0.024856066
Kurtosis-1.376058
Mean3127828.5
Median Absolute Deviation (MAD)70000
Skewness-0.1344949
Sum1.225796 × 1010
Variance6.0443647 × 109
MonotonicityNot monotonic
2024-05-18T12:31:04.880711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
3220000 404
 
10.3%
3230000 229
 
5.8%
3070000 201
 
5.1%
3010000 187
 
4.8%
3210000 187
 
4.8%
3020000 170
 
4.3%
3180000 166
 
4.2%
3000000 164
 
4.2%
3240000 162
 
4.1%
3200000 161
 
4.1%
Other values (15) 1888
48.2%
ValueCountFrequency (%)
3000000 164
4.2%
3010000 187
4.8%
3020000 170
4.3%
3030000 158
4.0%
3040000 155
4.0%
3050000 109
2.8%
3060000 125
3.2%
3070000 201
5.1%
3080000 126
3.2%
3090000 90
2.3%
ValueCountFrequency (%)
3240000 162
4.1%
3230000 229
5.8%
3220000 404
10.3%
3210000 187
4.8%
3200000 161
 
4.1%
3190000 117
 
3.0%
3180000 166
4.2%
3170000 90
 
2.3%
3160000 131
 
3.3%
3150000 156
 
4.0%

관리번호
Text

UNIQUE 

Distinct3919
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size30.7 KiB
2024-05-18T12:31:05.704973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters86218
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

Unique3919 ?
Unique (%)100.0%

Sample

1st row3200000-202-2021-00001
2nd row3160000-202-2002-00002
3rd row3180000-202-2002-00010
4th row3150000-202-2000-00032
5th row3140000-202-1987-00071
ValueCountFrequency (%)
3200000-202-2021-00001 1
 
< 0.1%
3180000-202-2001-00481 1
 
< 0.1%
3180000-202-1985-00417 1
 
< 0.1%
3180000-202-2000-00009 1
 
< 0.1%
3180000-202-2003-00014 1
 
< 0.1%
3180000-202-1970-00412 1
 
< 0.1%
3180000-202-2003-00001 1
 
< 0.1%
3180000-202-1997-00493 1
 
< 0.1%
3180000-202-1995-00495 1
 
< 0.1%
3180000-202-1985-00397 1
 
< 0.1%
Other values (3909) 3909
99.7%
2024-05-18T12:31:07.012895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 35867
41.6%
2 13212
 
15.3%
- 11757
 
13.6%
1 6634
 
7.7%
3 6310
 
7.3%
9 4263
 
4.9%
8 2300
 
2.7%
4 1768
 
2.1%
7 1574
 
1.8%
6 1292
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 74461
86.4%
Dash Punctuation 11757
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 35867
48.2%
2 13212
 
17.7%
1 6634
 
8.9%
3 6310
 
8.5%
9 4263
 
5.7%
8 2300
 
3.1%
4 1768
 
2.4%
7 1574
 
2.1%
6 1292
 
1.7%
5 1241
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 11757
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 86218
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 35867
41.6%
2 13212
 
15.3%
- 11757
 
13.6%
1 6634
 
7.7%
3 6310
 
7.3%
9 4263
 
4.9%
8 2300
 
2.7%
4 1768
 
2.1%
7 1574
 
1.8%
6 1292
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 86218
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 35867
41.6%
2 13212
 
15.3%
- 11757
 
13.6%
1 6634
 
7.7%
3 6310
 
7.3%
9 4263
 
4.9%
8 2300
 
2.7%
4 1768
 
2.1%
7 1574
 
1.8%
6 1292
 
1.5%
Distinct3073
Distinct (%)78.4%
Missing0
Missing (%)0.0%
Memory size30.7 KiB
Minimum1900-01-01 00:00:00
Maximum2024-04-23 00:00:00
2024-05-18T12:31:07.741879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T12:31:08.489595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3919
Missing (%)100.0%
Memory size34.6 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.7 KiB
3
3242 
1
677 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 3242
82.7%
1 677
 
17.3%

Length

2024-05-18T12:31:08.966152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T12:31:09.288718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 3242
82.7%
1 677
 
17.3%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.7 KiB
폐업
3242 
영업/정상
677 

Length

Max length5
Median length2
Mean length2.5182445
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 3242
82.7%
영업/정상 677
 
17.3%

Length

2024-05-18T12:31:09.670429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T12:31:10.034896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3242
82.7%
영업/정상 677
 
17.3%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.7 KiB
2
3242 
1
677 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 3242
82.7%
1 677
 
17.3%

Length

2024-05-18T12:31:10.411495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T12:31:10.743103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 3242
82.7%
1 677
 
17.3%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.7 KiB
폐업
3242 
영업
677 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 3242
82.7%
영업 677
 
17.3%

Length

2024-05-18T12:31:11.180867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T12:31:11.644531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3242
82.7%
영업 677
 
17.3%

폐업일자
Date

MISSING 

Distinct2316
Distinct (%)71.4%
Missing677
Missing (%)17.3%
Memory size30.7 KiB
Minimum1900-01-01 00:00:00
Maximum2024-05-10 00:00:00
2024-05-18T12:31:12.002312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T12:31:12.466834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3919
Missing (%)100.0%
Memory size34.6 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3919
Missing (%)100.0%
Memory size34.6 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3919
Missing (%)100.0%
Memory size34.6 KiB

전화번호
Text

MISSING 

Distinct3422
Distinct (%)92.3%
Missing211
Missing (%)5.4%
Memory size30.7 KiB
2024-05-18T12:31:13.391387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.9687163
Min length2

Characters and Unicode

Total characters36964
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

Unique3290 ?
Unique (%)88.7%

Sample

1st row0260125234
2nd row02 8545522
3rd row02 8315117
4th row0226912240
5th row0226493214
ValueCountFrequency (%)
02 2117
34.9%
0200000000 59
 
1.0%
00000 49
 
0.8%
0 12
 
0.2%
0211111111 6
 
0.1%
4590573 4
 
0.1%
542 4
 
0.1%
547 4
 
0.1%
932 4
 
0.1%
749 4
 
0.1%
Other values (3589) 3800
62.7%
2024-05-18T12:31:14.807809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7359
19.9%
2 6519
17.6%
2780
 
7.5%
3 2780
 
7.5%
5 2718
 
7.4%
4 2665
 
7.2%
6 2487
 
6.7%
8 2483
 
6.7%
7 2440
 
6.6%
1 2380
 
6.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 34184
92.5%
Space Separator 2780
 
7.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7359
21.5%
2 6519
19.1%
3 2780
 
8.1%
5 2718
 
8.0%
4 2665
 
7.8%
6 2487
 
7.3%
8 2483
 
7.3%
7 2440
 
7.1%
1 2380
 
7.0%
9 2353
 
6.9%
Space Separator
ValueCountFrequency (%)
2780
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 36964
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7359
19.9%
2 6519
17.6%
2780
 
7.5%
3 2780
 
7.5%
5 2718
 
7.4%
4 2665
 
7.2%
6 2487
 
6.7%
8 2483
 
6.7%
7 2440
 
6.6%
1 2380
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 36964
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7359
19.9%
2 6519
17.6%
2780
 
7.5%
3 2780
 
7.5%
5 2718
 
7.4%
4 2665
 
7.2%
6 2487
 
6.7%
8 2483
 
6.7%
7 2440
 
6.6%
1 2380
 
6.4%
Distinct3157
Distinct (%)80.6%
Missing4
Missing (%)0.1%
Memory size30.7 KiB
2024-05-18T12:31:15.716975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length6
Mean length5.9463602
Min length3

Characters and Unicode

Total characters23280
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

Unique2901 ?
Unique (%)74.1%

Sample

1st row390.19
2nd row1,620.00
3rd row640.00
4th row381.90
5th row390.35
ValueCountFrequency (%)
00 322
 
8.2%
198.00 18
 
0.5%
330.00 13
 
0.3%
660.00 13
 
0.3%
231.00 12
 
0.3%
450.00 10
 
0.3%
264.00 9
 
0.2%
495.00 8
 
0.2%
363.00 7
 
0.2%
297.00 7
 
0.2%
Other values (3147) 3496
89.3%
2024-05-18T12:31:17.411853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 3915
16.8%
0 3773
16.2%
2 2327
10.0%
1 2187
9.4%
3 1769
7.6%
4 1600
6.9%
6 1567
6.7%
5 1537
 
6.6%
8 1430
 
6.1%
7 1417
 
6.1%
Other values (2) 1758
7.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18977
81.5%
Other Punctuation 4303
 
18.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3773
19.9%
2 2327
12.3%
1 2187
11.5%
3 1769
9.3%
4 1600
8.4%
6 1567
8.3%
5 1537
8.1%
8 1430
 
7.5%
7 1417
 
7.5%
9 1370
 
7.2%
Other Punctuation
ValueCountFrequency (%)
. 3915
91.0%
, 388
 
9.0%

Most occurring scripts

ValueCountFrequency (%)
Common 23280
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 3915
16.8%
0 3773
16.2%
2 2327
10.0%
1 2187
9.4%
3 1769
7.6%
4 1600
6.9%
6 1567
6.7%
5 1537
 
6.6%
8 1430
 
6.1%
7 1417
 
6.1%
Other values (2) 1758
7.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23280
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 3915
16.8%
0 3773
16.2%
2 2327
10.0%
1 2187
9.4%
3 1769
7.6%
4 1600
6.9%
6 1567
6.7%
5 1537
 
6.6%
8 1430
 
6.1%
7 1417
 
6.1%
Other values (2) 1758
7.6%
Distinct1852
Distinct (%)47.3%
Missing5
Missing (%)0.1%
Memory size30.7 KiB
2024-05-18T12:31:18.404168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0505876
Min length6

Characters and Unicode

Total characters23682
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

Unique917 ?
Unique (%)23.4%

Sample

1st row151-830
2nd row152872
3rd row150-857
4th row157-884
5th row158-808
ValueCountFrequency (%)
138210 60
 
1.5%
100450 23
 
0.6%
135545 14
 
0.4%
136865 12
 
0.3%
135892 12
 
0.3%
140892 11
 
0.3%
150841 11
 
0.3%
135819 10
 
0.3%
140893 10
 
0.3%
134867 9
 
0.2%
Other values (1842) 3742
95.6%
2024-05-18T12:31:19.592239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 5550
23.4%
8 3728
15.7%
3 2942
12.4%
0 2756
11.6%
5 2183
 
9.2%
2 1857
 
7.8%
4 1466
 
6.2%
7 1023
 
4.3%
9 993
 
4.2%
6 986
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 23484
99.2%
Dash Punctuation 198
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 5550
23.6%
8 3728
15.9%
3 2942
12.5%
0 2756
11.7%
5 2183
 
9.3%
2 1857
 
7.9%
4 1466
 
6.2%
7 1023
 
4.4%
9 993
 
4.2%
6 986
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 198
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 23682
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 5550
23.4%
8 3728
15.7%
3 2942
12.4%
0 2756
11.6%
5 2183
 
9.2%
2 1857
 
7.8%
4 1466
 
6.2%
7 1023
 
4.3%
9 993
 
4.2%
6 986
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23682
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 5550
23.4%
8 3728
15.7%
3 2942
12.4%
0 2756
11.6%
5 2183
 
9.2%
2 1857
 
7.8%
4 1466
 
6.2%
7 1023
 
4.3%
9 993
 
4.2%
6 986
 
4.2%
Distinct3627
Distinct (%)92.7%
Missing5
Missing (%)0.1%
Memory size30.7 KiB
2024-05-18T12:31:20.524318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length88
Median length58
Mean length24.40649
Min length15

Characters and Unicode

Total characters95527
Distinct characters429
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

Unique3374 ?
Unique (%)86.2%

Sample

1st row서울특별시 관악구 봉천동 702-49
2nd row서울특별시 구로구 구로동 731-1
3rd row서울특별시 영등포구 신길동 4936 푸른숲마을상가 지하
4th row서울특별시 강서구 화곡동 370-39
5th row서울특별시 양천구 목동 513-3 지하1층
ValueCountFrequency (%)
서울특별시 3914
 
22.4%
강남구 404
 
2.3%
송파구 229
 
1.3%
성북구 201
 
1.2%
중구 187
 
1.1%
서초구 187
 
1.1%
지하1층 182
 
1.0%
용산구 170
 
1.0%
영등포구 165
 
0.9%
강동구 162
 
0.9%
Other values (4520) 11665
66.8%
2024-05-18T12:31:21.859639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17060
17.9%
4507
 
4.7%
4492
 
4.7%
4152
 
4.3%
1 4025
 
4.2%
3976
 
4.2%
3959
 
4.1%
3921
 
4.1%
3915
 
4.1%
3915
 
4.1%
Other values (419) 41605
43.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 55740
58.3%
Decimal Number 18370
 
19.2%
Space Separator 17060
 
17.9%
Dash Punctuation 3546
 
3.7%
Other Punctuation 299
 
0.3%
Uppercase Letter 155
 
0.2%
Open Punctuation 154
 
0.2%
Close Punctuation 152
 
0.2%
Math Symbol 43
 
< 0.1%
Lowercase Letter 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4507
 
8.1%
4492
 
8.1%
4152
 
7.4%
3976
 
7.1%
3959
 
7.1%
3921
 
7.0%
3915
 
7.0%
3915
 
7.0%
3250
 
5.8%
886
 
1.6%
Other values (375) 18767
33.7%
Uppercase Letter
ValueCountFrequency (%)
B 98
63.2%
A 11
 
7.1%
K 9
 
5.8%
S 8
 
5.2%
T 6
 
3.9%
D 6
 
3.9%
P 5
 
3.2%
J 3
 
1.9%
L 2
 
1.3%
R 1
 
0.6%
Other values (6) 6
 
3.9%
Decimal Number
ValueCountFrequency (%)
1 4025
21.9%
2 2596
14.1%
3 1997
10.9%
4 1652
9.0%
5 1589
 
8.6%
0 1505
 
8.2%
6 1438
 
7.8%
7 1273
 
6.9%
9 1169
 
6.4%
8 1126
 
6.1%
Other Punctuation
ValueCountFrequency (%)
, 276
92.3%
. 16
 
5.4%
/ 4
 
1.3%
: 2
 
0.7%
@ 1
 
0.3%
Lowercase Letter
ValueCountFrequency (%)
a 2
33.3%
r 1
16.7%
e 1
16.7%
w 1
16.7%
o 1
16.7%
Open Punctuation
ValueCountFrequency (%)
( 142
92.2%
[ 12
 
7.8%
Close Punctuation
ValueCountFrequency (%)
) 141
92.8%
] 11
 
7.2%
Space Separator
ValueCountFrequency (%)
17060
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3546
100.0%
Math Symbol
ValueCountFrequency (%)
~ 43
100.0%
Letter Number
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 55740
58.3%
Common 39624
41.5%
Latin 163
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4507
 
8.1%
4492
 
8.1%
4152
 
7.4%
3976
 
7.1%
3959
 
7.1%
3921
 
7.0%
3915
 
7.0%
3915
 
7.0%
3250
 
5.8%
886
 
1.6%
Other values (375) 18767
33.7%
Common
ValueCountFrequency (%)
17060
43.1%
1 4025
 
10.2%
- 3546
 
8.9%
2 2596
 
6.6%
3 1997
 
5.0%
4 1652
 
4.2%
5 1589
 
4.0%
0 1505
 
3.8%
6 1438
 
3.6%
7 1273
 
3.2%
Other values (12) 2943
 
7.4%
Latin
ValueCountFrequency (%)
B 98
60.1%
A 11
 
6.7%
K 9
 
5.5%
S 8
 
4.9%
T 6
 
3.7%
D 6
 
3.7%
P 5
 
3.1%
J 3
 
1.8%
2
 
1.2%
a 2
 
1.2%
Other values (12) 13
 
8.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 55740
58.3%
ASCII 39785
41.6%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17060
42.9%
1 4025
 
10.1%
- 3546
 
8.9%
2 2596
 
6.5%
3 1997
 
5.0%
4 1652
 
4.2%
5 1589
 
4.0%
0 1505
 
3.8%
6 1438
 
3.6%
7 1273
 
3.2%
Other values (33) 3104
 
7.8%
Hangul
ValueCountFrequency (%)
4507
 
8.1%
4492
 
8.1%
4152
 
7.4%
3976
 
7.1%
3959
 
7.1%
3921
 
7.0%
3915
 
7.0%
3915
 
7.0%
3250
 
5.8%
886
 
1.6%
Other values (375) 18767
33.7%
Number Forms
ValueCountFrequency (%)
2
100.0%

도로명주소
Text

MISSING 

Distinct1444
Distinct (%)98.2%
Missing2449
Missing (%)62.5%
Memory size30.7 KiB
2024-05-18T12:31:22.708734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length66
Median length56
Mean length30.64898
Min length20

Characters and Unicode

Total characters45054
Distinct characters452
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

Unique1421 ?
Unique (%)96.7%

Sample

1st row서울특별시 관악구 보라매로 13, B101호 (봉천동)
2nd row서울특별시 구로구 구로동로26길 8 (구로동)
3rd row서울특별시 영등포구 가마산로79길 46 (신길동,푸른숲마을상가 지하)
4th row서울특별시 강서구 월정로30길 55 (화곡동)
5th row서울특별시 양천구 공항대로 612, 지하1층 (목동)
ValueCountFrequency (%)
서울특별시 1470
 
17.2%
강남구 198
 
2.3%
지하1층 157
 
1.8%
서초구 103
 
1.2%
영등포구 75
 
0.9%
강서구 74
 
0.9%
송파구 73
 
0.9%
중구 66
 
0.8%
지하 61
 
0.7%
성북구 57
 
0.7%
Other values (2560) 6213
72.7%
2024-05-18T12:31:24.108091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7083
 
15.7%
1850
 
4.1%
1826
 
4.1%
1 1633
 
3.6%
1588
 
3.5%
1579
 
3.5%
1531
 
3.4%
( 1528
 
3.4%
) 1527
 
3.4%
1481
 
3.3%
Other values (442) 23428
52.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 26893
59.7%
Space Separator 7083
 
15.7%
Decimal Number 6561
 
14.6%
Open Punctuation 1530
 
3.4%
Close Punctuation 1529
 
3.4%
Other Punctuation 1108
 
2.5%
Dash Punctuation 169
 
0.4%
Uppercase Letter 132
 
0.3%
Math Symbol 41
 
0.1%
Lowercase Letter 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1850
 
6.9%
1826
 
6.8%
1588
 
5.9%
1579
 
5.9%
1531
 
5.7%
1481
 
5.5%
1470
 
5.5%
1470
 
5.5%
770
 
2.9%
679
 
2.5%
Other values (401) 12649
47.0%
Uppercase Letter
ValueCountFrequency (%)
B 88
66.7%
A 10
 
7.6%
S 8
 
6.1%
K 8
 
6.1%
T 4
 
3.0%
D 3
 
2.3%
P 2
 
1.5%
L 2
 
1.5%
G 1
 
0.8%
F 1
 
0.8%
Other values (5) 5
 
3.8%
Decimal Number
ValueCountFrequency (%)
1 1633
24.9%
2 1055
16.1%
3 780
11.9%
0 554
 
8.4%
4 553
 
8.4%
5 521
 
7.9%
6 414
 
6.3%
7 397
 
6.1%
8 367
 
5.6%
9 287
 
4.4%
Lowercase Letter
ValueCountFrequency (%)
a 2
33.3%
e 1
16.7%
r 1
16.7%
w 1
16.7%
o 1
16.7%
Other Punctuation
ValueCountFrequency (%)
, 1098
99.1%
. 7
 
0.6%
/ 3
 
0.3%
Open Punctuation
ValueCountFrequency (%)
( 1528
99.9%
[ 2
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 1527
99.9%
] 2
 
0.1%
Space Separator
ValueCountFrequency (%)
7083
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 169
100.0%
Math Symbol
ValueCountFrequency (%)
~ 41
100.0%
Letter Number
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 26893
59.7%
Common 18021
40.0%
Latin 140
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1850
 
6.9%
1826
 
6.8%
1588
 
5.9%
1579
 
5.9%
1531
 
5.7%
1481
 
5.5%
1470
 
5.5%
1470
 
5.5%
770
 
2.9%
679
 
2.5%
Other values (401) 12649
47.0%
Latin
ValueCountFrequency (%)
B 88
62.9%
A 10
 
7.1%
S 8
 
5.7%
K 8
 
5.7%
T 4
 
2.9%
D 3
 
2.1%
a 2
 
1.4%
P 2
 
1.4%
2
 
1.4%
L 2
 
1.4%
Other values (11) 11
 
7.9%
Common
ValueCountFrequency (%)
7083
39.3%
1 1633
 
9.1%
( 1528
 
8.5%
) 1527
 
8.5%
, 1098
 
6.1%
2 1055
 
5.9%
3 780
 
4.3%
0 554
 
3.1%
4 553
 
3.1%
5 521
 
2.9%
Other values (10) 1689
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 26893
59.7%
ASCII 18159
40.3%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7083
39.0%
1 1633
 
9.0%
( 1528
 
8.4%
) 1527
 
8.4%
, 1098
 
6.0%
2 1055
 
5.8%
3 780
 
4.3%
0 554
 
3.1%
4 553
 
3.0%
5 521
 
2.9%
Other values (30) 1827
 
10.1%
Hangul
ValueCountFrequency (%)
1850
 
6.9%
1826
 
6.8%
1588
 
5.9%
1579
 
5.9%
1531
 
5.7%
1481
 
5.5%
1470
 
5.5%
1470
 
5.5%
770
 
2.9%
679
 
2.5%
Other values (401) 12649
47.0%
Number Forms
ValueCountFrequency (%)
2
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct1129
Distinct (%)79.5%
Missing2499
Missing (%)63.8%
Infinite0
Infinite (%)0.0%
Mean5269.6007
Minimum1000
Maximum8856
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size34.6 KiB
2024-05-18T12:31:24.709533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1000
5-th percentile1488.35
Q13487
median5565
Q36933.5
95-th percentile8568.25
Maximum8856
Range7856
Interquartile range (IQR)3446.5

Descriptive statistics

Standard deviation2135.3323
Coefficient of variation (CV)0.40521709
Kurtosis-0.9596806
Mean5269.6007
Median Absolute Deviation (MAD)1685
Skewness-0.21857954
Sum7482833
Variance4559643.9
MonotonicityNot monotonic
2024-05-18T12:31:25.183223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3346 6
 
0.2%
6226 6
 
0.2%
6120 5
 
0.1%
6199 5
 
0.1%
4537 5
 
0.1%
3628 4
 
0.1%
7250 4
 
0.1%
6038 4
 
0.1%
6062 4
 
0.1%
7663 4
 
0.1%
Other values (1119) 1373
35.0%
(Missing) 2499
63.8%
ValueCountFrequency (%)
1000 1
< 0.1%
1002 1
< 0.1%
1024 1
< 0.1%
1036 1
< 0.1%
1039 1
< 0.1%
1041 1
< 0.1%
1048 1
< 0.1%
1054 2
0.1%
1066 1
< 0.1%
1068 1
< 0.1%
ValueCountFrequency (%)
8856 1
< 0.1%
8854 1
< 0.1%
8852 1
< 0.1%
8848 1
< 0.1%
8846 1
< 0.1%
8845 1
< 0.1%
8843 1
< 0.1%
8832 1
< 0.1%
8831 1
< 0.1%
8814 1
< 0.1%
Distinct2873
Distinct (%)73.3%
Missing0
Missing (%)0.0%
Memory size30.7 KiB
2024-05-18T12:31:26.235632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length23
Mean length4.9017607
Min length1

Characters and Unicode

Total characters19210
Distinct characters565
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2375 ?
Unique (%)60.6%

Sample

1st row샤워 인 더 하우스
2nd row구로대중탕
3rd row푸른숲헬스사우나
4th row태영탕
5th row월드파크
ValueCountFrequency (%)
사우나 67
 
1.6%
수정탕 28
 
0.7%
청수탕 19
 
0.4%
현대탕 19
 
0.4%
제일탕 18
 
0.4%
약수탕 17
 
0.4%
스파 17
 
0.4%
목욕탕 15
 
0.4%
장수탕 13
 
0.3%
중앙탕 12
 
0.3%
Other values (2957) 4020
94.7%
2024-05-18T12:31:27.679150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1991
 
10.4%
960
 
5.0%
884
 
4.6%
880
 
4.6%
547
 
2.8%
481
 
2.5%
464
 
2.4%
398
 
2.1%
349
 
1.8%
346
 
1.8%
Other values (555) 11910
62.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18296
95.2%
Space Separator 329
 
1.7%
Decimal Number 150
 
0.8%
Uppercase Letter 117
 
0.6%
Close Punctuation 113
 
0.6%
Open Punctuation 111
 
0.6%
Lowercase Letter 73
 
0.4%
Other Punctuation 19
 
0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1991
 
10.9%
960
 
5.2%
884
 
4.8%
880
 
4.8%
547
 
3.0%
481
 
2.6%
464
 
2.5%
398
 
2.2%
349
 
1.9%
346
 
1.9%
Other values (497) 10996
60.1%
Uppercase Letter
ValueCountFrequency (%)
C 13
11.1%
M 12
 
10.3%
A 12
 
10.3%
S 11
 
9.4%
T 7
 
6.0%
P 7
 
6.0%
O 6
 
5.1%
K 6
 
5.1%
N 6
 
5.1%
E 6
 
5.1%
Other values (12) 31
26.5%
Lowercase Letter
ValueCountFrequency (%)
a 13
17.8%
n 9
12.3%
e 8
11.0%
s 8
11.0%
u 7
9.6%
p 3
 
4.1%
l 3
 
4.1%
m 3
 
4.1%
i 3
 
4.1%
y 3
 
4.1%
Other values (9) 13
17.8%
Decimal Number
ValueCountFrequency (%)
2 65
43.3%
4 51
34.0%
1 11
 
7.3%
5 9
 
6.0%
3 4
 
2.7%
6 3
 
2.0%
0 3
 
2.0%
8 2
 
1.3%
9 2
 
1.3%
Other Punctuation
ValueCountFrequency (%)
. 9
47.4%
& 7
36.8%
? 2
 
10.5%
, 1
 
5.3%
Space Separator
ValueCountFrequency (%)
329
100.0%
Close Punctuation
ValueCountFrequency (%)
) 113
100.0%
Open Punctuation
ValueCountFrequency (%)
( 111
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18294
95.2%
Common 724
 
3.8%
Latin 190
 
1.0%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1991
 
10.9%
960
 
5.2%
884
 
4.8%
880
 
4.8%
547
 
3.0%
481
 
2.6%
464
 
2.5%
398
 
2.2%
349
 
1.9%
346
 
1.9%
Other values (495) 10994
60.1%
Latin
ValueCountFrequency (%)
a 13
 
6.8%
C 13
 
6.8%
M 12
 
6.3%
A 12
 
6.3%
S 11
 
5.8%
n 9
 
4.7%
e 8
 
4.2%
s 8
 
4.2%
u 7
 
3.7%
T 7
 
3.7%
Other values (31) 90
47.4%
Common
ValueCountFrequency (%)
329
45.4%
) 113
 
15.6%
( 111
 
15.3%
2 65
 
9.0%
4 51
 
7.0%
1 11
 
1.5%
. 9
 
1.2%
5 9
 
1.2%
& 7
 
1.0%
3 4
 
0.6%
Other values (7) 15
 
2.1%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18294
95.2%
ASCII 914
 
4.8%
CJK 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1991
 
10.9%
960
 
5.2%
884
 
4.8%
880
 
4.8%
547
 
3.0%
481
 
2.6%
464
 
2.5%
398
 
2.2%
349
 
1.9%
346
 
1.9%
Other values (495) 10994
60.1%
ASCII
ValueCountFrequency (%)
329
36.0%
) 113
 
12.4%
( 111
 
12.1%
2 65
 
7.1%
4 51
 
5.6%
a 13
 
1.4%
C 13
 
1.4%
M 12
 
1.3%
A 12
 
1.3%
1 11
 
1.2%
Other values (48) 184
20.1%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%
Distinct2454
Distinct (%)62.6%
Missing0
Missing (%)0.0%
Memory size30.7 KiB
Minimum1999-01-08 00:00:00
Maximum2024-05-16 16:03:35
2024-05-18T12:31:28.282613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T12:31:28.770191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.7 KiB
I
3056 
U
863 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 3056
78.0%
U 863
 
22.0%

Length

2024-05-18T12:31:29.283389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T12:31:29.715452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 3056
78.0%
u 863
 
22.0%
Distinct599
Distinct (%)15.3%
Missing0
Missing (%)0.0%
Memory size30.7 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:08:00
2024-05-18T12:31:30.212477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T12:31:31.289819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.7 KiB
공동탕업
3184 
공동탕업+찜질시설서비스영업
334 
한증막업
 
162
목욕장업 기타
 
146
찜질시설서비스영업
 
93

Length

Max length14
Median length4
Mean length5.0826742
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row공동탕업
2nd row한증막업
3rd row공동탕업
4th row공동탕업
5th row공동탕업

Common Values

ValueCountFrequency (%)
공동탕업 3184
81.2%
공동탕업+찜질시설서비스영업 334
 
8.5%
한증막업 162
 
4.1%
목욕장업 기타 146
 
3.7%
찜질시설서비스영업 93
 
2.4%

Length

2024-05-18T12:31:31.943205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T12:31:32.328460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 3184
78.3%
공동탕업+찜질시설서비스영업 334
 
8.2%
한증막업 162
 
4.0%
목욕장업 146
 
3.6%
기타 146
 
3.6%
찜질시설서비스영업 93
 
2.3%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct2860
Distinct (%)81.4%
Missing404
Missing (%)10.3%
Infinite0
Infinite (%)0.0%
Mean199614.55
Minimum182895.67
Maximum215512.98
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size34.6 KiB
2024-05-18T12:31:32.778814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum182895.67
5-th percentile186799.17
Q1193646.05
median201290.05
Q3204664.3
95-th percentile211041.87
Maximum215512.98
Range32617.307
Interquartile range (IQR)11018.251

Descriptive statistics

Standard deviation7148.5531
Coefficient of variation (CV)0.035811784
Kurtosis-0.73856379
Mean199614.55
Median Absolute Deviation (MAD)5116.4347
Skewness-0.27005647
Sum7.0164515 × 108
Variance51101812
MonotonicityNot monotonic
2024-05-18T12:31:33.394423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
208589.363343145 7
 
0.2%
199974.400997613 6
 
0.2%
202651.538047427 5
 
0.1%
208644.819209521 5
 
0.1%
192554.043312022 5
 
0.1%
202378.390574465 5
 
0.1%
198966.466796388 5
 
0.1%
203848.249311066 5
 
0.1%
203901.878812978 5
 
0.1%
201876.521665604 4
 
0.1%
Other values (2850) 3463
88.4%
(Missing) 404
 
10.3%
ValueCountFrequency (%)
182895.668483962 1
 
< 0.1%
183007.220061564 1
 
< 0.1%
183049.525160207 1
 
< 0.1%
183090.805509245 1
 
< 0.1%
183118.598958412 1
 
< 0.1%
183131.028798764 2
0.1%
183215.287450855 1
 
< 0.1%
183269.526391991 2
0.1%
183271.311495807 1
 
< 0.1%
183306.751602566 3
0.1%
ValueCountFrequency (%)
215512.97537469 2
0.1%
215400.574803 1
< 0.1%
215073.592252889 2
0.1%
214856.492433065 1
< 0.1%
214830.790078856 1
< 0.1%
214556.263493741 1
< 0.1%
214500.427256388 1
< 0.1%
214395.085383506 1
< 0.1%
213628.354436887 2
0.1%
213613.884984794 1
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct2860
Distinct (%)81.4%
Missing404
Missing (%)10.3%
Infinite0
Infinite (%)0.0%
Mean449281.51
Minimum436991.45
Maximum465094.19
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size34.6 KiB
2024-05-18T12:31:33.803054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum436991.45
5-th percentile441899.4
Q1444866.39
median448686.88
Q3452607.95
95-th percentile459625.4
Maximum465094.19
Range28102.742
Interquartile range (IQR)7741.5666

Descriptive statistics

Standard deviation5442.3876
Coefficient of variation (CV)0.012113536
Kurtosis-0.363818
Mean449281.51
Median Absolute Deviation (MAD)3845.8156
Skewness0.49384963
Sum1.5792245 × 109
Variance29619583
MonotonicityNot monotonic
2024-05-18T12:31:34.414697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
445455.90405262 7
 
0.2%
448243.817170275 6
 
0.2%
456473.886142136 5
 
0.1%
448711.725750126 5
 
0.1%
455068.381757311 5
 
0.1%
446705.197148871 5
 
0.1%
452608.062544497 5
 
0.1%
443834.310545284 5
 
0.1%
446783.967552696 5
 
0.1%
455664.635302013 4
 
0.1%
Other values (2850) 3463
88.4%
(Missing) 404
 
10.3%
ValueCountFrequency (%)
436991.446935421 1
< 0.1%
437401.591082059 1
< 0.1%
437571.204954672 1
< 0.1%
437880.321300564 1
< 0.1%
437914.06299827 1
< 0.1%
437915.621690013 1
< 0.1%
438068.094636291 1
< 0.1%
438436.109390506 2
0.1%
438486.034499121 1
< 0.1%
438520.182013694 1
< 0.1%
ValueCountFrequency (%)
465094.18915856 1
 
< 0.1%
464731.761130542 1
 
< 0.1%
464404.895005692 1
 
< 0.1%
464385.587785162 1
 
< 0.1%
464174.850719823 3
0.1%
464069.834711115 1
 
< 0.1%
464003.405075075 2
0.1%
463898.141439795 1
 
< 0.1%
463765.987531795 1
 
< 0.1%
463763.240794805 1
 
< 0.1%

위생업태명
Categorical

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size30.7 KiB
공동탕업
2976 
<NA>
367 
공동탕업+찜질시설서비스영업
 
242
한증막업
 
150
목욕장업 기타
 
108

Length

Max length14
Median length4
Mean length4.7971421
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공동탕업 2976
75.9%
<NA> 367
 
9.4%
공동탕업+찜질시설서비스영업 242
 
6.2%
한증막업 150
 
3.8%
목욕장업 기타 108
 
2.8%
찜질시설서비스영업 76
 
1.9%

Length

2024-05-18T12:31:35.143291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T12:31:35.498589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 2976
73.9%
na 367
 
9.1%
공동탕업+찜질시설서비스영업 242
 
6.0%
한증막업 150
 
3.7%
목욕장업 108
 
2.7%
기타 108
 
2.7%
찜질시설서비스영업 76
 
1.9%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct29
Distinct (%)1.1%
Missing1310
Missing (%)33.4%
Infinite0
Infinite (%)0.0%
Mean1.9808356
Minimum0
Maximum40
Zeros1674
Zeros (%)42.7%
Negative0
Negative (%)0.0%
Memory size34.6 KiB
2024-05-18T12:31:36.000778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile9
Maximum40
Range40
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.7325793
Coefficient of variation (CV)1.8843458
Kurtosis16.673868
Mean1.9808356
Median Absolute Deviation (MAD)0
Skewness3.305319
Sum5168
Variance13.932148
MonotonicityNot monotonic
2024-05-18T12:31:36.492991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0 1674
42.7%
3 217
 
5.5%
4 189
 
4.8%
5 129
 
3.3%
2 93
 
2.4%
6 71
 
1.8%
7 50
 
1.3%
8 29
 
0.7%
10 24
 
0.6%
1 24
 
0.6%
Other values (19) 109
 
2.8%
(Missing) 1310
33.4%
ValueCountFrequency (%)
0 1674
42.7%
1 24
 
0.6%
2 93
 
2.4%
3 217
 
5.5%
4 189
 
4.8%
5 129
 
3.3%
6 71
 
1.8%
7 50
 
1.3%
8 29
 
0.7%
9 19
 
0.5%
ValueCountFrequency (%)
40 1
 
< 0.1%
37 1
 
< 0.1%
35 1
 
< 0.1%
26 1
 
< 0.1%
25 3
0.1%
24 2
0.1%
22 3
0.1%
21 1
 
< 0.1%
20 4
0.1%
19 2
0.1%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)0.4%
Missing1448
Missing (%)36.9%
Infinite0
Infinite (%)0.0%
Mean0.51517604
Minimum0
Maximum9
Zeros1714
Zeros (%)43.7%
Negative0
Negative (%)0.0%
Memory size34.6 KiB
2024-05-18T12:31:37.111021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.024632
Coefficient of variation (CV)1.9888969
Kurtosis12.070655
Mean0.51517604
Median Absolute Deviation (MAD)0
Skewness3.0190541
Sum1273
Variance1.0498708
MonotonicityNot monotonic
2024-05-18T12:31:37.607215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 1714
43.7%
1 493
 
12.6%
2 132
 
3.4%
3 67
 
1.7%
4 38
 
1.0%
5 11
 
0.3%
6 8
 
0.2%
7 5
 
0.1%
8 2
 
0.1%
9 1
 
< 0.1%
(Missing) 1448
36.9%
ValueCountFrequency (%)
0 1714
43.7%
1 493
 
12.6%
2 132
 
3.4%
3 67
 
1.7%
4 38
 
1.0%
5 11
 
0.3%
6 8
 
0.2%
7 5
 
0.1%
8 2
 
0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
9 1
 
< 0.1%
8 2
 
0.1%
7 5
 
0.1%
6 8
 
0.2%
5 11
 
0.3%
4 38
 
1.0%
3 67
 
1.7%
2 132
 
3.4%
1 493
 
12.6%
0 1714
43.7%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct16
Distinct (%)0.7%
Missing1696
Missing (%)43.3%
Infinite0
Infinite (%)0.0%
Mean0.63697706
Minimum0
Maximum16
Zeros1537
Zeros (%)39.2%
Negative0
Negative (%)0.0%
Memory size34.6 KiB
2024-05-18T12:31:37.974126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3
Maximum16
Range16
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.4706918
Coefficient of variation (CV)2.3088616
Kurtosis35.499654
Mean0.63697706
Median Absolute Deviation (MAD)0
Skewness4.9504709
Sum1416
Variance2.1629345
MonotonicityNot monotonic
2024-05-18T12:31:38.533091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 1537
39.2%
1 363
 
9.3%
2 183
 
4.7%
3 59
 
1.5%
4 32
 
0.8%
5 19
 
0.5%
7 7
 
0.2%
6 7
 
0.2%
13 4
 
0.1%
15 3
 
0.1%
Other values (6) 9
 
0.2%
(Missing) 1696
43.3%
ValueCountFrequency (%)
0 1537
39.2%
1 363
 
9.3%
2 183
 
4.7%
3 59
 
1.5%
4 32
 
0.8%
5 19
 
0.5%
6 7
 
0.2%
7 7
 
0.2%
8 2
 
0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
16 1
 
< 0.1%
15 3
0.1%
14 1
 
< 0.1%
13 4
0.1%
12 2
 
0.1%
10 2
 
0.1%
9 1
 
< 0.1%
8 2
 
0.1%
7 7
0.2%
6 7
0.2%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct18
Distinct (%)1.6%
Missing2788
Missing (%)71.1%
Infinite0
Infinite (%)0.0%
Mean1.694076
Minimum0
Maximum17
Zeros398
Zeros (%)10.2%
Negative0
Negative (%)0.0%
Memory size34.6 KiB
2024-05-18T12:31:38.967312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile5
Maximum17
Range17
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.9902751
Coefficient of variation (CV)1.174844
Kurtosis12.046953
Mean1.694076
Median Absolute Deviation (MAD)1
Skewness2.5742071
Sum1916
Variance3.961195
MonotonicityNot monotonic
2024-05-18T12:31:39.518870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 398
 
10.2%
2 257
 
6.6%
1 186
 
4.7%
3 163
 
4.2%
4 50
 
1.3%
5 34
 
0.9%
6 17
 
0.4%
7 12
 
0.3%
13 3
 
0.1%
12 2
 
0.1%
Other values (8) 9
 
0.2%
(Missing) 2788
71.1%
ValueCountFrequency (%)
0 398
10.2%
1 186
4.7%
2 257
6.6%
3 163
4.2%
4 50
 
1.3%
5 34
 
0.9%
6 17
 
0.4%
7 12
 
0.3%
8 2
 
0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
17 1
 
< 0.1%
16 1
 
< 0.1%
15 1
 
< 0.1%
14 1
 
< 0.1%
13 3
0.1%
12 2
0.1%
11 1
 
< 0.1%
10 1
 
< 0.1%
9 1
 
< 0.1%
8 2
0.1%

사용시작지하층
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.3%
Missing1768
Missing (%)45.1%
Infinite0
Infinite (%)0.0%
Mean0.35518364
Minimum0
Maximum8
Zeros1511
Zeros (%)38.6%
Negative0
Negative (%)0.0%
Memory size34.6 KiB
2024-05-18T12:31:40.127920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile1
Maximum8
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.61403723
Coefficient of variation (CV)1.7287881
Kurtosis13.307593
Mean0.35518364
Median Absolute Deviation (MAD)0
Skewness2.3925982
Sum764
Variance0.37704172
MonotonicityNot monotonic
2024-05-18T12:31:40.665444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 1511
38.6%
1 534
 
13.6%
2 95
 
2.4%
3 8
 
0.2%
4 2
 
0.1%
8 1
 
< 0.1%
(Missing) 1768
45.1%
ValueCountFrequency (%)
0 1511
38.6%
1 534
 
13.6%
2 95
 
2.4%
3 8
 
0.2%
4 2
 
0.1%
8 1
 
< 0.1%
ValueCountFrequency (%)
8 1
 
< 0.1%
4 2
 
0.1%
3 8
 
0.2%
2 95
 
2.4%
1 534
 
13.6%
0 1511
38.6%

사용끝지하층
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct7
Distinct (%)0.7%
Missing2889
Missing (%)73.7%
Infinite0
Infinite (%)0.0%
Mean1.0019417
Minimum0
Maximum101
Zeros351
Zeros (%)9.0%
Negative0
Negative (%)0.0%
Memory size34.6 KiB
2024-05-18T12:31:41.176389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile2
Maximum101
Range101
Interquartile range (IQR)1

Descriptive statistics

Standard deviation3.2267703
Coefficient of variation (CV)3.2205169
Kurtosis898.61781
Mean1.0019417
Median Absolute Deviation (MAD)1
Skewness28.993444
Sum1032
Variance10.412047
MonotonicityNot monotonic
2024-05-18T12:31:41.643845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 461
 
11.8%
0 351
 
9.0%
2 190
 
4.8%
3 22
 
0.6%
4 4
 
0.1%
8 1
 
< 0.1%
101 1
 
< 0.1%
(Missing) 2889
73.7%
ValueCountFrequency (%)
0 351
9.0%
1 461
11.8%
2 190
4.8%
3 22
 
0.6%
4 4
 
0.1%
8 1
 
< 0.1%
101 1
 
< 0.1%
ValueCountFrequency (%)
101 1
 
< 0.1%
8 1
 
< 0.1%
4 4
 
0.1%
3 22
 
0.6%
2 190
4.8%
1 461
11.8%
0 351
9.0%

한실수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.7 KiB
0
2036 
<NA>
1883 

Length

Max length4
Median length1
Mean length2.4414391
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 (%)
0 2036
52.0%
<NA> 1883
48.0%

Length

2024-05-18T12:31:42.194822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T12:31:42.553911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2036
52.0%
na 1883
48.0%

양실수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.7 KiB
0
2036 
<NA>
1883 

Length

Max length4
Median length1
Mean length2.4414391
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 (%)
0 2036
52.0%
<NA> 1883
48.0%

Length

2024-05-18T12:31:43.021271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T12:31:43.398692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2036
52.0%
na 1883
48.0%

욕실수
Real number (ℝ)

MISSING  ZEROS 

Distinct15
Distinct (%)0.6%
Missing1497
Missing (%)38.2%
Infinite0
Infinite (%)0.0%
Mean0.90627581
Minimum0
Maximum16
Zeros1582
Zeros (%)40.4%
Negative0
Negative (%)0.0%
Memory size34.6 KiB
2024-05-18T12:31:43.811390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile4
Maximum16
Range16
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.7252079
Coefficient of variation (CV)1.9036235
Kurtosis16.087202
Mean0.90627581
Median Absolute Deviation (MAD)0
Skewness3.3442305
Sum2195
Variance2.9763423
MonotonicityNot monotonic
2024-05-18T12:31:44.296875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 1582
40.4%
2 538
 
13.7%
1 131
 
3.3%
4 37
 
0.9%
6 33
 
0.8%
3 33
 
0.8%
8 22
 
0.6%
5 19
 
0.5%
7 8
 
0.2%
10 5
 
0.1%
Other values (5) 14
 
0.4%
(Missing) 1497
38.2%
ValueCountFrequency (%)
0 1582
40.4%
1 131
 
3.3%
2 538
 
13.7%
3 33
 
0.8%
4 37
 
0.9%
5 19
 
0.5%
6 33
 
0.8%
7 8
 
0.2%
8 22
 
0.6%
9 4
 
0.1%
ValueCountFrequency (%)
16 3
 
0.1%
14 1
 
< 0.1%
12 2
 
0.1%
11 4
 
0.1%
10 5
 
0.1%
9 4
 
0.1%
8 22
0.6%
7 8
 
0.2%
6 33
0.8%
5 19
0.5%

발한실여부
Boolean

MISSING 

Distinct2
Distinct (%)0.1%
Missing368
Missing (%)9.4%
Memory size7.8 KiB
False
2946 
True
605 
(Missing)
368 
ValueCountFrequency (%)
False 2946
75.2%
True 605
 
15.4%
(Missing) 368
 
9.4%
2024-05-18T12:31:44.821576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.7 KiB
0
2028 
<NA>
1887 
5
 
2
6
 
1
7
 
1

Length

Max length4
Median length1
Mean length2.4445011
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 (%)
0 2028
51.7%
<NA> 1887
48.2%
5 2
 
0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%

Length

2024-05-18T12:31:45.245311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T12:31:45.593669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2028
51.7%
na 1887
48.2%
5 2
 
0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
Distinct3
Distinct (%)100.0%
Missing3916
Missing (%)99.9%
Memory size30.7 KiB
2024-05-18T12:31:46.108826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length88
Median length69
Mean length55
Min length8

Characters and Unicode

Total characters165
Distinct characters69
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row이 영업신고의 효력은 건축물 임시사용승인기간 2012.4.30까지이며 건축물 사용승인 연장 또는 준공 완료시 재신청 해야 함
2nd row영업신고 수리는 임시사용승인기간(2005.2.28 ~ 2006.2.27)으로 하고 기간해제(사용검사 필)나 기간연장시는 자동으로 해제 또는 연장된것으로 본다.
3rd row지위승계신청보류
ValueCountFrequency (%)
건축물 2
 
6.7%
또는 2
 
6.7%
1
 
3.3%
수리는 1
 
3.3%
본다 1
 
3.3%
연장된것으로 1
 
3.3%
해제 1
 
3.3%
자동으로 1
 
3.3%
기간연장시는 1
 
3.3%
필)나 1
 
3.3%
Other values (18) 18
60.0%
2024-05-18T12:31:47.122314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
27
 
16.4%
2 8
 
4.8%
. 7
 
4.2%
0 6
 
3.6%
5
 
3.0%
4
 
2.4%
4
 
2.4%
4
 
2.4%
4
 
2.4%
4
 
2.4%
Other values (59) 92
55.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 105
63.6%
Space Separator 27
 
16.4%
Decimal Number 21
 
12.7%
Other Punctuation 7
 
4.2%
Close Punctuation 2
 
1.2%
Open Punctuation 2
 
1.2%
Math Symbol 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5
 
4.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
3
 
2.9%
3
 
2.9%
Other values (45) 66
62.9%
Decimal Number
ValueCountFrequency (%)
2 8
38.1%
0 6
28.6%
7 1
 
4.8%
6 1
 
4.8%
8 1
 
4.8%
5 1
 
4.8%
1 1
 
4.8%
4 1
 
4.8%
3 1
 
4.8%
Space Separator
ValueCountFrequency (%)
27
100.0%
Other Punctuation
ValueCountFrequency (%)
. 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 105
63.6%
Common 60
36.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5
 
4.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
3
 
2.9%
3
 
2.9%
Other values (45) 66
62.9%
Common
ValueCountFrequency (%)
27
45.0%
2 8
 
13.3%
. 7
 
11.7%
0 6
 
10.0%
) 2
 
3.3%
( 2
 
3.3%
7 1
 
1.7%
~ 1
 
1.7%
6 1
 
1.7%
8 1
 
1.7%
Other values (4) 4
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 105
63.6%
ASCII 60
36.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
27
45.0%
2 8
 
13.3%
. 7
 
11.7%
0 6
 
10.0%
) 2
 
3.3%
( 2
 
3.3%
7 1
 
1.7%
~ 1
 
1.7%
6 1
 
1.7%
8 1
 
1.7%
Other values (4) 4
 
6.7%
Hangul
ValueCountFrequency (%)
5
 
4.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
3
 
2.9%
3
 
2.9%
Other values (45) 66
62.9%

조건부허가시작일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.7 KiB
<NA>
3917 
20120301
 
1
20050304
 
1

Length

Max length8
Median length4
Mean length4.0020413
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> 3917
99.9%
20120301 1
 
< 0.1%
20050304 1
 
< 0.1%

Length

2024-05-18T12:31:47.787555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T12:31:48.267473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3917
99.9%
20120301 1
 
< 0.1%
20050304 1
 
< 0.1%

조건부허가종료일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.7 KiB
<NA>
3917 
20120430
 
1
20060227
 
1

Length

Max length8
Median length4
Mean length4.0020413
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> 3917
99.9%
20120430 1
 
< 0.1%
20060227 1
 
< 0.1%

Length

2024-05-18T12:31:48.837590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T12:31:49.306306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3917
99.9%
20120430 1
 
< 0.1%
20060227 1
 
< 0.1%
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.7 KiB
<NA>
3255 
임대
429 
자가
 
235

Length

Max length4
Median length4
Mean length3.661138
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> 3255
83.1%
임대 429
 
10.9%
자가 235
 
6.0%

Length

2024-05-18T12:31:49.869971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T12:31:50.355499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3255
83.1%
임대 429
 
10.9%
자가 235
 
6.0%

세탁기수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.7 KiB
<NA>
3148 
0
771 

Length

Max length4
Median length4
Mean length3.4097984
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> 3148
80.3%
0 771
 
19.7%

Length

2024-05-18T12:31:50.879182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T12:31:51.214551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3148
80.3%
0 771
 
19.7%

여성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size30.7 KiB
<NA>
3706 
0
 
205
2
 
3
20
 
2
4
 
2

Length

Max length4
Median length4
Mean length3.8374585
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> 3706
94.6%
0 205
 
5.2%
2 3
 
0.1%
20 2
 
0.1%
4 2
 
0.1%
1 1
 
< 0.1%

Length

2024-05-18T12:31:51.664213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T12:31:52.140355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3706
94.6%
0 205
 
5.2%
2 3
 
0.1%
20 2
 
0.1%
4 2
 
0.1%
1 1
 
< 0.1%

남성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size30.7 KiB
<NA>
3706 
0
 
202
1
 
4
2
 
3
20
 
2

Length

Max length4
Median length4
Mean length3.8374585
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> 3706
94.6%
0 202
 
5.2%
1 4
 
0.1%
2 3
 
0.1%
20 2
 
0.1%
3 2
 
0.1%

Length

2024-05-18T12:31:52.640595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T12:31:53.148149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3706
94.6%
0 202
 
5.2%
1 4
 
0.1%
2 3
 
0.1%
20 2
 
0.1%
3 2
 
0.1%

회수건조수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.7 KiB
<NA>
3277 
0
642 

Length

Max length4
Median length4
Mean length3.5085481
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> 3277
83.6%
0 642
 
16.4%

Length

2024-05-18T12:31:53.754176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T12:31:54.214983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3277
83.6%
0 642
 
16.4%

침대수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.7 KiB
<NA>
3299 
0
620 

Length

Max length4
Median length4
Mean length3.5253891
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> 3299
84.2%
0 620
 
15.8%

Length

2024-05-18T12:31:54.661794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T12:31:55.010510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3299
84.2%
0 620
 
15.8%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.1%
Missing367
Missing (%)9.4%
Memory size7.8 KiB
False
3526 
True
 
26
(Missing)
367 
ValueCountFrequency (%)
False 3526
90.0%
True 26
 
0.7%
(Missing) 367
 
9.4%
2024-05-18T12:31:55.344357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
032000003200000-202-2021-000012021-05-26<NA>1영업/정상1영업<NA><NA><NA><NA>0260125234390.19151-830서울특별시 관악구 봉천동 702-49서울특별시 관악구 보라매로 13, B101호 (봉천동)8708샤워 인 더 하우스2023-03-08 13:55:08U2022-12-02 23:00:00.0공동탕업193481.099048443157.363464<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
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231800003180000-202-2002-000102002-12-26<NA>1영업/정상1영업<NA><NA><NA><NA>02 8315117640.00150-857서울특별시 영등포구 신길동 4936 푸른숲마을상가 지하서울특별시 영등포구 가마산로79길 46 (신길동,푸른숲마을상가 지하)7350푸른숲헬스사우나2023-03-10 09:51:14U2022-12-02 23:02:00.0공동탕업192702.306288445115.514647<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
331500003150000-202-2000-000322000-07-29<NA>1영업/정상1영업<NA><NA><NA><NA>0226912240381.90157-884서울특별시 강서구 화곡동 370-39서울특별시 강서구 월정로30길 55 (화곡동)7765태영탕2023-03-15 13:58:24U2022-12-02 23:07:00.0공동탕업185699.207165448088.463635<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
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731300003130000-202-1999-001611999-02-27<NA>1영업/정상1영업<NA><NA><NA><NA>02 701 3370532.76121-876서울특별시 마포구 용강동 122-16 지하1층 일부서울특별시 마포구 토정로32길 4, 지하1층 (용강동)4163토정24시사우나찜질방2023-03-23 14:38:37U2022-12-02 22:05:00.0공동탕업194742.383948448757.883381<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
832200003220000-202-1997-002401997-02-25<NA>3폐업2폐업2023-03-28<NA><NA><NA>0234636100198.55135-270서울특별시 강남구 도곡동 902-124 ,125서울특별시 강남구 남부순환로365길 39 (도곡동,,125)6269장수사우나2023-03-28 12:06:36U2022-12-02 21:00:00.0공동탕업203448.153783442872.045848<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
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개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
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