Overview

Dataset statistics

Number of variables44
Number of observations488
Missing cells4890
Missing cells (%)22.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory179.8 KiB
Average record size in memory377.3 B

Variable types

Categorical20
Text6
DateTime4
Unsupported8
Numeric5
Boolean1

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,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author강동구
URLhttps://data.seoul.go.kr/dataList/OA-18551/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
위생업태명 is highly imbalanced (58.4%)Imbalance
여성종사자수 is highly imbalanced (53.6%)Imbalance
급수시설구분명 is highly imbalanced (59.3%)Imbalance
총인원 is highly imbalanced (89.2%)Imbalance
본사종업원수 is highly imbalanced (89.2%)Imbalance
공장사무직종업원수 is highly imbalanced (89.2%)Imbalance
공장판매직종업원수 is highly imbalanced (89.2%)Imbalance
공장생산직종업원수 is highly imbalanced (89.2%)Imbalance
보증액 is highly imbalanced (89.2%)Imbalance
월세액 is highly imbalanced (89.2%)Imbalance
인허가취소일자 has 488 (100.0%) missing valuesMissing
폐업일자 has 82 (16.8%) missing valuesMissing
휴업시작일자 has 488 (100.0%) missing valuesMissing
휴업종료일자 has 488 (100.0%) missing valuesMissing
재개업일자 has 488 (100.0%) missing valuesMissing
전화번호 has 40 (8.2%) missing valuesMissing
도로명주소 has 364 (74.6%) missing valuesMissing
도로명우편번호 has 366 (75.0%) missing valuesMissing
좌표정보(X) has 26 (5.3%) missing valuesMissing
좌표정보(Y) has 26 (5.3%) missing valuesMissing
건물소유구분명 has 488 (100.0%) missing valuesMissing
다중이용업소여부 has 41 (8.4%) missing valuesMissing
시설총규모 has 41 (8.4%) missing valuesMissing
전통업소지정번호 has 488 (100.0%) missing valuesMissing
전통업소주된음식 has 488 (100.0%) missing valuesMissing
홈페이지 has 488 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물소유구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-29 19:45:43.468791
Analysis finished2024-04-29 19:45:44.333241
Duration0.86 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
3240000
488 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3240000
2nd row3240000
3rd row3240000
4th row3240000
5th row3240000

Common Values

ValueCountFrequency (%)
3240000 488
100.0%

Length

2024-04-30T04:45:44.394220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:45:44.482110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3240000 488
100.0%

관리번호
Text

UNIQUE 

Distinct488
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2024-04-30T04:45:44.639205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters10736
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

Unique488 ?
Unique (%)100.0%

Sample

1st row3240000-103-1993-05372
2nd row3240000-103-1993-05373
3rd row3240000-103-1993-05374
4th row3240000-103-1993-05375
5th row3240000-103-1993-05376
ValueCountFrequency (%)
3240000-103-1993-05372 1
 
0.2%
3240000-103-1996-05214 1
 
0.2%
3240000-103-1996-05212 1
 
0.2%
3240000-103-1996-05211 1
 
0.2%
3240000-103-1996-05210 1
 
0.2%
3240000-103-1996-05209 1
 
0.2%
3240000-103-1996-05208 1
 
0.2%
3240000-103-1996-05207 1
 
0.2%
3240000-103-1996-05206 1
 
0.2%
3240000-103-1996-05205 1
 
0.2%
Other values (478) 478
98.0%
2024-04-30T04:45:44.914014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3273
30.5%
- 1464
13.6%
3 1303
 
12.1%
1 1178
 
11.0%
9 974
 
9.1%
4 763
 
7.1%
2 761
 
7.1%
5 603
 
5.6%
6 155
 
1.4%
7 147
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9272
86.4%
Dash Punctuation 1464
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3273
35.3%
3 1303
 
14.1%
1 1178
 
12.7%
9 974
 
10.5%
4 763
 
8.2%
2 761
 
8.2%
5 603
 
6.5%
6 155
 
1.7%
7 147
 
1.6%
8 115
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 1464
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10736
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3273
30.5%
- 1464
13.6%
3 1303
 
12.1%
1 1178
 
11.0%
9 974
 
9.1%
4 763
 
7.1%
2 761
 
7.1%
5 603
 
5.6%
6 155
 
1.4%
7 147
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10736
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3273
30.5%
- 1464
13.6%
3 1303
 
12.1%
1 1178
 
11.0%
9 974
 
9.1%
4 763
 
7.1%
2 761
 
7.1%
5 603
 
5.6%
6 155
 
1.4%
7 147
 
1.4%

인허가일자
Date

Distinct392
Distinct (%)80.3%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
Minimum1993-01-04 00:00:00
Maximum2022-10-14 00:00:00
2024-04-30T04:45:45.063624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:45:45.203076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing488
Missing (%)100.0%
Memory size4.4 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
3
406 
1
82 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 406
83.2%
1 82
 
16.8%

Length

2024-04-30T04:45:45.320843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:45:45.425684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 406
83.2%
1 82
 
16.8%

영업상태명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
폐업
406 
영업/정상
82 

Length

Max length5
Median length2
Mean length2.5040984
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 406
83.2%
영업/정상 82
 
16.8%

Length

2024-04-30T04:45:45.513279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:45:45.599415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 406
83.2%
영업/정상 82
 
16.8%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2
406 
1
82 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 406
83.2%
1 82
 
16.8%

Length

2024-04-30T04:45:45.702260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:45:45.781345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 406
83.2%
1 82
 
16.8%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
폐업
406 
영업
82 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 406
83.2%
영업 82
 
16.8%

Length

2024-04-30T04:45:45.860796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:45:45.950880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 406
83.2%
영업 82
 
16.8%

폐업일자
Date

MISSING 

Distinct346
Distinct (%)85.2%
Missing82
Missing (%)16.8%
Memory size3.9 KiB
Minimum1993-10-26 00:00:00
Maximum2024-02-13 00:00:00
2024-04-30T04:45:46.042868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:45:46.149837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing488
Missing (%)100.0%
Memory size4.4 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing488
Missing (%)100.0%
Memory size4.4 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing488
Missing (%)100.0%
Memory size4.4 KiB

전화번호
Text

MISSING 

Distinct341
Distinct (%)76.1%
Missing40
Missing (%)8.2%
Memory size3.9 KiB
2024-04-30T04:45:46.403418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.0200893
Min length2

Characters and Unicode

Total characters4041
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

Unique327 ?
Unique (%)73.0%

Sample

1st row02 4854123
2nd row0204748891
3rd row02 4750051
4th row02 4887070
5th row0204839560
ValueCountFrequency (%)
02 343
45.0%
0200000000 22
 
2.9%
00000 11
 
1.4%
0 7
 
0.9%
486 4
 
0.5%
487 4
 
0.5%
484 3
 
0.4%
477 3
 
0.4%
4429656 2
 
0.3%
483 2
 
0.3%
Other values (350) 362
47.4%
2024-04-30T04:45:46.786395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 951
23.5%
2 660
16.3%
4 531
13.1%
390
9.7%
7 350
 
8.7%
8 321
 
7.9%
3 187
 
4.6%
5 178
 
4.4%
6 167
 
4.1%
9 158
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3651
90.3%
Space Separator 390
 
9.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 951
26.0%
2 660
18.1%
4 531
14.5%
7 350
 
9.6%
8 321
 
8.8%
3 187
 
5.1%
5 178
 
4.9%
6 167
 
4.6%
9 158
 
4.3%
1 148
 
4.1%
Space Separator
ValueCountFrequency (%)
390
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4041
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 951
23.5%
2 660
16.3%
4 531
13.1%
390
9.7%
7 350
 
8.7%
8 321
 
7.9%
3 187
 
4.6%
5 178
 
4.4%
6 167
 
4.1%
9 158
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4041
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 951
23.5%
2 660
16.3%
4 531
13.1%
390
9.7%
7 350
 
8.7%
8 321
 
7.9%
3 187
 
4.6%
5 178
 
4.4%
6 167
 
4.1%
9 158
 
3.9%

소재지면적
Real number (ℝ)

Distinct465
Distinct (%)95.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean107.55852
Minimum31.74
Maximum394.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-04-30T04:45:46.910968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum31.74
5-th percentile50.053
Q181.255
median105.325
Q3134.88
95-th percentile150.2685
Maximum394.6
Range362.86
Interquartile range (IQR)53.625

Descriptive statistics

Standard deviation37.614609
Coefficient of variation (CV)0.34971295
Kurtosis7.1792664
Mean107.55852
Median Absolute Deviation (MAD)26.92
Skewness1.296643
Sum52488.56
Variance1414.8588
MonotonicityNot monotonic
2024-04-30T04:45:47.030451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
142.0 3
 
0.6%
75.85 3
 
0.6%
83.66 2
 
0.4%
148.0 2
 
0.4%
97.1 2
 
0.4%
143.48 2
 
0.4%
115.52 2
 
0.4%
74.0 2
 
0.4%
143.4 2
 
0.4%
148.1 2
 
0.4%
Other values (455) 466
95.5%
ValueCountFrequency (%)
31.74 1
0.2%
33.06 1
0.2%
36.07 1
0.2%
39.38 1
0.2%
40.03 1
0.2%
40.17 1
0.2%
40.65 1
0.2%
41.61 1
0.2%
41.8 1
0.2%
43.4 2
0.4%
ValueCountFrequency (%)
394.6 1
0.2%
256.68 1
0.2%
254.7 1
0.2%
246.4 1
0.2%
227.56 1
0.2%
204.75 1
0.2%
204.68 1
0.2%
198.0 1
0.2%
192.0 1
0.2%
191.76 1
0.2%

소재지우편번호
Text

Distinct67
Distinct (%)13.7%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2024-04-30T04:45:47.222472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0512295
Min length6

Characters and Unicode

Total characters2953
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

Unique19 ?
Unique (%)3.9%

Sample

1st row134871
2nd row134871
3rd row134814
4th row134861
5th row134-851
ValueCountFrequency (%)
134814 87
17.8%
134874 32
 
6.6%
134877 22
 
4.5%
134859 22
 
4.5%
134871 21
 
4.3%
134867 21
 
4.3%
134830 21
 
4.3%
134872 19
 
3.9%
134864 16
 
3.3%
134880 15
 
3.1%
Other values (57) 212
43.4%
2024-04-30T04:45:47.533828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 694
23.5%
1 676
22.9%
3 544
18.4%
8 513
17.4%
7 165
 
5.6%
6 89
 
3.0%
0 80
 
2.7%
5 66
 
2.2%
2 62
 
2.1%
9 39
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2928
99.2%
Dash Punctuation 25
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 694
23.7%
1 676
23.1%
3 544
18.6%
8 513
17.5%
7 165
 
5.6%
6 89
 
3.0%
0 80
 
2.7%
5 66
 
2.3%
2 62
 
2.1%
9 39
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2953
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 694
23.5%
1 676
22.9%
3 544
18.4%
8 513
17.4%
7 165
 
5.6%
6 89
 
3.0%
0 80
 
2.7%
5 66
 
2.2%
2 62
 
2.1%
9 39
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2953
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 694
23.5%
1 676
22.9%
3 544
18.4%
8 513
17.4%
7 165
 
5.6%
6 89
 
3.0%
0 80
 
2.7%
5 66
 
2.2%
2 62
 
2.1%
9 39
 
1.3%

지번주소
Text

Distinct408
Distinct (%)83.6%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2024-04-30T04:45:47.825027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length32
Mean length22.215164
Min length14

Characters and Unicode

Total characters10841
Distinct characters68
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

Unique341 ?
Unique (%)69.9%

Sample

1st row서울특별시 강동구 천호동 397-45번지
2nd row서울특별시 강동구 천호동 397-233번지
3rd row서울특별시 강동구 길동 414-9번지
4th row서울특별시 강동구 천호동 34-21번지
5th row서울특별시 강동구 성내동 553-12
ValueCountFrequency (%)
서울특별시 488
24.3%
강동구 488
24.3%
천호동 161
 
8.0%
길동 132
 
6.6%
성내동 87
 
4.3%
암사동 53
 
2.6%
명일동 38
 
1.9%
둔촌동 15
 
0.7%
지하 6
 
0.3%
413-1번지 5
 
0.2%
Other values (426) 536
26.7%
2024-04-30T04:45:48.201121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1966
18.1%
동 978
 
9.0%
강 489
 
4.5%
서 488
 
4.5%
특 488
 
4.5%
별 488
 
4.5%
시 488
 
4.5%
구 488
 
4.5%
울 488
 
4.5%
- 477
 
4.4%
Other values (58) 4003
36.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6195
57.1%
Decimal Number 2187
 
20.2%
Space Separator 1966
 
18.1%
Dash Punctuation 477
 
4.4%
Other Punctuation 12
 
0.1%
Close Punctuation 2
 
< 0.1%
Open Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 978
15.8%
강 489
7.9%
서 488
7.9%
특 488
7.9%
별 488
7.9%
시 488
7.9%
구 488
7.9%
울 488
7.9%
지 442
7.1%
번 422
6.8%
Other values (43) 936
15.1%
Decimal Number
ValueCountFrequency (%)
4 434
19.8%
1 383
17.5%
3 280
12.8%
5 269
12.3%
2 240
11.0%
0 133
 
6.1%
9 120
 
5.5%
8 116
 
5.3%
7 115
 
5.3%
6 97
 
4.4%
Space Separator
ValueCountFrequency (%)
1966
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 477
100.0%
Other Punctuation
ValueCountFrequency (%)
, 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6195
57.1%
Common 4646
42.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 978
15.8%
강 489
7.9%
서 488
7.9%
특 488
7.9%
별 488
7.9%
시 488
7.9%
구 488
7.9%
울 488
7.9%
지 442
7.1%
번 422
6.8%
Other values (43) 936
15.1%
Common
ValueCountFrequency (%)
1966
42.3%
- 477
 
10.3%
4 434
 
9.3%
1 383
 
8.2%
3 280
 
6.0%
5 269
 
5.8%
2 240
 
5.2%
0 133
 
2.9%
9 120
 
2.6%
8 116
 
2.5%
Other values (5) 228
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6195
57.1%
ASCII 4646
42.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1966
42.3%
- 477
 
10.3%
4 434
 
9.3%
1 383
 
8.2%
3 280
 
6.0%
5 269
 
5.8%
2 240
 
5.2%
0 133
 
2.9%
9 120
 
2.6%
8 116
 
2.5%
Other values (5) 228
 
4.9%
Hangul
ValueCountFrequency (%)
동 978
15.8%
강 489
7.9%
서 488
7.9%
특 488
7.9%
별 488
7.9%
시 488
7.9%
구 488
7.9%
울 488
7.9%
지 442
7.1%
번 422
6.8%
Other values (43) 936
15.1%

도로명주소
Text

MISSING 

Distinct122
Distinct (%)98.4%
Missing364
Missing (%)74.6%
Memory size3.9 KiB
2024-04-30T04:45:48.429414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length36
Mean length26.403226
Min length21

Characters and Unicode

Total characters3274
Distinct characters75
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique120 ?
Unique (%)96.8%

Sample

1st row서울특별시 강동구 상암로 175 (천호동)
2nd row서울특별시 강동구 성내로 8-8 (성내동)
3rd row서울특별시 강동구 풍성로57길 16 (성내동)
4th row서울특별시 강동구 상암로 169 (천호동)
5th row서울특별시 강동구 천중로 228 (길동)
ValueCountFrequency (%)
서울특별시 124
18.8%
강동구 124
18.8%
천호동 31
 
4.7%
길동 27
 
4.1%
성내동 20
 
3.0%
양재대로 18
 
2.7%
명일동 18
 
2.7%
구천면로 14
 
2.1%
지1층 10
 
1.5%
천중로 9
 
1.4%
Other values (168) 263
40.0%
2024-04-30T04:45:48.753950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
534
 
16.3%
동 251
 
7.7%
1 158
 
4.8%
구 139
 
4.2%
( 126
 
3.8%
) 126
 
3.8%
강 125
 
3.8%
서 124
 
3.8%
특 124
 
3.8%
별 124
 
3.8%
Other values (65) 1443
44.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1926
58.8%
Space Separator 534
 
16.3%
Decimal Number 500
 
15.3%
Open Punctuation 126
 
3.8%
Close Punctuation 126
 
3.8%
Other Punctuation 49
 
1.5%
Dash Punctuation 12
 
0.4%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 251
13.0%
구 139
 
7.2%
강 125
 
6.5%
서 124
 
6.4%
특 124
 
6.4%
별 124
 
6.4%
시 124
 
6.4%
울 124
 
6.4%
로 122
 
6.3%
천 81
 
4.2%
Other values (49) 588
30.5%
Decimal Number
ValueCountFrequency (%)
1 158
31.6%
2 54
 
10.8%
4 51
 
10.2%
5 44
 
8.8%
3 42
 
8.4%
7 42
 
8.4%
8 29
 
5.8%
9 29
 
5.8%
6 28
 
5.6%
0 23
 
4.6%
Space Separator
ValueCountFrequency (%)
534
100.0%
Open Punctuation
ValueCountFrequency (%)
( 126
100.0%
Close Punctuation
ValueCountFrequency (%)
) 126
100.0%
Other Punctuation
ValueCountFrequency (%)
, 49
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1926
58.8%
Common 1347
41.1%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 251
13.0%
구 139
 
7.2%
강 125
 
6.5%
서 124
 
6.4%
특 124
 
6.4%
별 124
 
6.4%
시 124
 
6.4%
울 124
 
6.4%
로 122
 
6.3%
천 81
 
4.2%
Other values (49) 588
30.5%
Common
ValueCountFrequency (%)
534
39.6%
1 158
 
11.7%
( 126
 
9.4%
) 126
 
9.4%
2 54
 
4.0%
4 51
 
3.8%
, 49
 
3.6%
5 44
 
3.3%
3 42
 
3.1%
7 42
 
3.1%
Other values (5) 121
 
9.0%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1926
58.8%
ASCII 1348
41.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
534
39.6%
1 158
 
11.7%
( 126
 
9.3%
) 126
 
9.3%
2 54
 
4.0%
4 51
 
3.8%
, 49
 
3.6%
5 44
 
3.3%
3 42
 
3.1%
7 42
 
3.1%
Other values (6) 122
 
9.1%
Hangul
ValueCountFrequency (%)
동 251
13.0%
구 139
 
7.2%
강 125
 
6.5%
서 124
 
6.4%
특 124
 
6.4%
별 124
 
6.4%
시 124
 
6.4%
울 124
 
6.4%
로 122
 
6.3%
천 81
 
4.2%
Other values (49) 588
30.5%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct62
Distinct (%)50.8%
Missing366
Missing (%)75.0%
Infinite0
Infinite (%)0.0%
Mean5331.1148
Minimum5241
Maximum5408
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-04-30T04:45:48.878263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5241
5-th percentile5257
Q15302.25
median5335
Q35355
95-th percentile5402.95
Maximum5408
Range167
Interquartile range (IQR)52.75

Descriptive statistics

Standard deviation44.681462
Coefficient of variation (CV)0.0083812605
Kurtosis-0.72552427
Mean5331.1148
Median Absolute Deviation (MAD)27.5
Skewness-0.23690119
Sum650396
Variance1996.433
MonotonicityNot monotonic
2024-04-30T04:45:48.998346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5353 11
 
2.3%
5355 10
 
2.0%
5335 7
 
1.4%
5334 5
 
1.0%
5257 5
 
1.0%
5373 4
 
0.8%
5292 4
 
0.8%
5398 4
 
0.8%
5303 3
 
0.6%
5259 3
 
0.6%
Other values (52) 66
 
13.5%
(Missing) 366
75.0%
ValueCountFrequency (%)
5241 1
 
0.2%
5242 1
 
0.2%
5244 1
 
0.2%
5248 1
 
0.2%
5257 5
1.0%
5259 3
0.6%
5262 1
 
0.2%
5264 1
 
0.2%
5265 2
 
0.4%
5266 1
 
0.2%
ValueCountFrequency (%)
5408 2
0.4%
5407 1
 
0.2%
5405 2
0.4%
5404 1
 
0.2%
5403 1
 
0.2%
5402 1
 
0.2%
5398 4
0.8%
5396 2
0.4%
5392 1
 
0.2%
5390 1
 
0.2%

사업장명
Text

Distinct441
Distinct (%)90.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2024-04-30T04:45:49.243142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length3.9118852
Min length1

Characters and Unicode

Total characters1909
Distinct characters389
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique401 ?
Unique (%)82.2%

Sample

1st row아방궁
2nd row품바
3rd row뉴프로포즈
4th row짱1노래주점
5th row주화단란주점
ValueCountFrequency (%)
라이브 6
 
1.2%
밀라노 3
 
0.6%
파라다이스 3
 
0.6%
만남 3
 
0.6%
스타 3
 
0.6%
연예인 3
 
0.6%
에버그린 3
 
0.6%
만남단란주점 3
 
0.6%
콘서트 3
 
0.6%
큐 2
 
0.4%
Other values (438) 472
93.7%
2024-04-30T04:45:49.624462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 73
 
3.8%
이 69
 
3.6%
점 68
 
3.6%
스 57
 
3.0%
단 45
 
2.4%
란 45
 
2.4%
라 44
 
2.3%
노 30
 
1.6%
가 29
 
1.5%
리 29
 
1.5%
Other values (379) 1420
74.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1779
93.2%
Decimal Number 58
 
3.0%
Uppercase Letter 34
 
1.8%
Space Separator 16
 
0.8%
Open Punctuation 6
 
0.3%
Close Punctuation 6
 
0.3%
Letter Number 4
 
0.2%
Lowercase Letter 4
 
0.2%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 73
 
4.1%
이 69
 
3.9%
점 68
 
3.8%
스 57
 
3.2%
단 45
 
2.5%
란 45
 
2.5%
라 44
 
2.5%
노 30
 
1.7%
가 29
 
1.6%
리 29
 
1.6%
Other values (353) 1290
72.5%
Uppercase Letter
ValueCountFrequency (%)
B 7
20.6%
M 6
17.6%
P 3
8.8%
C 3
8.8%
A 3
8.8%
I 3
8.8%
O 2
 
5.9%
S 2
 
5.9%
W 2
 
5.9%
V 2
 
5.9%
Decimal Number
ValueCountFrequency (%)
0 25
43.1%
2 10
 
17.2%
8 8
 
13.8%
7 8
 
13.8%
1 3
 
5.2%
4 2
 
3.4%
5 2
 
3.4%
Lowercase Letter
ValueCountFrequency (%)
a 2
50.0%
o 1
25.0%
i 1
25.0%
Space Separator
ValueCountFrequency (%)
16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 4
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1779
93.2%
Common 88
 
4.6%
Latin 42
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 73
 
4.1%
이 69
 
3.9%
점 68
 
3.8%
스 57
 
3.2%
단 45
 
2.5%
란 45
 
2.5%
라 44
 
2.5%
노 30
 
1.7%
가 29
 
1.6%
리 29
 
1.6%
Other values (353) 1290
72.5%
Latin
ValueCountFrequency (%)
B 7
16.7%
M 6
14.3%
Ⅱ 4
9.5%
P 3
7.1%
C 3
7.1%
A 3
7.1%
I 3
7.1%
O 2
 
4.8%
S 2
 
4.8%
a 2
 
4.8%
Other values (5) 7
16.7%
Common
ValueCountFrequency (%)
0 25
28.4%
16
18.2%
2 10
 
11.4%
8 8
 
9.1%
7 8
 
9.1%
( 6
 
6.8%
) 6
 
6.8%
1 3
 
3.4%
. 2
 
2.3%
4 2
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1779
93.2%
ASCII 126
 
6.6%
Number Forms 4
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 73
 
4.1%
이 69
 
3.9%
점 68
 
3.8%
스 57
 
3.2%
단 45
 
2.5%
란 45
 
2.5%
라 44
 
2.5%
노 30
 
1.7%
가 29
 
1.6%
리 29
 
1.6%
Other values (353) 1290
72.5%
ASCII
ValueCountFrequency (%)
0 25
19.8%
16
12.7%
2 10
 
7.9%
8 8
 
6.3%
7 8
 
6.3%
B 7
 
5.6%
( 6
 
4.8%
M 6
 
4.8%
) 6
 
4.8%
P 3
 
2.4%
Other values (15) 31
24.6%
Number Forms
ValueCountFrequency (%)
Ⅱ 4
100.0%

최종수정일자
Date

Distinct273
Distinct (%)55.9%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
Minimum1999-03-13 00:00:00
Maximum2024-04-11 09:29:05
2024-04-30T04:45:49.755779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:45:50.063900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
I
411 
U
77 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 411
84.2%
U 77
 
15.8%

Length

2024-04-30T04:45:50.183463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:45:50.270152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 411
84.2%
u 77
 
15.8%

데이터갱신일자
Date

Distinct73
Distinct (%)15.0%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 23:05:00
2024-04-30T04:45:50.358580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:45:50.498163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
단란주점
488 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
단란주점 488
100.0%

Length

2024-04-30T04:45:50.607551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:45:50.691538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
단란주점 488
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct352
Distinct (%)76.2%
Missing26
Missing (%)5.3%
Infinite0
Infinite (%)0.0%
Mean211761.94
Minimum210655.81
Maximum214980.83
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-04-30T04:45:50.776782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum210655.81
5-th percentile210830.59
Q1211187.14
median211796.89
Q3212154.72
95-th percentile212712.83
Maximum214980.83
Range4325.0202
Interquartile range (IQR)967.58625

Descriptive statistics

Standard deviation665.99591
Coefficient of variation (CV)0.0031450217
Kurtosis0.86201708
Mean211761.94
Median Absolute Deviation (MAD)528.16468
Skewness0.6677279
Sum97834017
Variance443550.55
MonotonicityNot monotonic
2024-04-30T04:45:50.888301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
211185.18354777 5
 
1.0%
212102.520890186 4
 
0.8%
212205.324163557 4
 
0.8%
212025.713738228 4
 
0.8%
210970.75707265 4
 
0.8%
212241.599163626 4
 
0.8%
211963.787409013 3
 
0.6%
211122.336085013 3
 
0.6%
212004.614055512 3
 
0.6%
212664.391769031 3
 
0.6%
Other values (342) 425
87.1%
(Missing) 26
 
5.3%
ValueCountFrequency (%)
210655.813512179 1
0.2%
210660.022685902 1
0.2%
210664.882366319 1
0.2%
210690.953426374 1
0.2%
210691.700571744 1
0.2%
210710.526860304 1
0.2%
210710.614638389 1
0.2%
210721.262679123 1
0.2%
210733.801352578 1
0.2%
210735.821288617 1
0.2%
ValueCountFrequency (%)
214980.833756622 1
0.2%
213751.225969745 1
0.2%
213680.993194221 1
0.2%
213676.319090609 1
0.2%
213674.493379728 1
0.2%
213672.65981884 2
0.4%
213671.045593053 1
0.2%
213640.278266791 1
0.2%
213632.141350282 1
0.2%
213620.683279907 1
0.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct352
Distinct (%)76.2%
Missing26
Missing (%)5.3%
Infinite0
Infinite (%)0.0%
Mean448648.21
Minimum446748.49
Maximum450991.03
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-04-30T04:45:51.004291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum446748.49
5-th percentile447304.52
Q1448126.21
median448560.87
Q3449336.36
95-th percentile450049.91
Maximum450991.03
Range4242.5383
Interquartile range (IQR)1210.155

Descriptive statistics

Standard deviation834.08251
Coefficient of variation (CV)0.0018591014
Kurtosis-0.51113486
Mean448648.21
Median Absolute Deviation (MAD)469.24189
Skewness0.17988873
Sum2.0727547 × 108
Variance695693.63
MonotonicityNot monotonic
2024-04-30T04:45:51.123371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
448606.609911561 5
 
1.0%
448099.228692808 4
 
0.8%
448170.096215943 4
 
0.8%
448227.378064025 4
 
0.8%
448713.31669728 4
 
0.8%
448298.45939367 4
 
0.8%
448212.012860784 3
 
0.6%
448641.392175021 3
 
0.6%
448123.892547255 3
 
0.6%
449780.919173405 3
 
0.6%
Other values (342) 425
87.1%
(Missing) 26
 
5.3%
ValueCountFrequency (%)
446748.493341691 1
0.2%
446800.369554447 1
0.2%
446824.955578969 1
0.2%
446844.00511621 1
0.2%
446872.29983338 1
0.2%
446894.680049364 1
0.2%
446907.632018709 1
0.2%
446959.93759108 1
0.2%
446968.119700507 1
0.2%
446975.489394196 1
0.2%
ValueCountFrequency (%)
450991.031680959 1
0.2%
450311.965425595 1
0.2%
450309.175253834 2
0.4%
450307.054379144 2
0.4%
450306.570278603 2
0.4%
450264.713132142 1
0.2%
450264.368517397 1
0.2%
450219.030003409 1
0.2%
450194.855705321 1
0.2%
450160.936702182 1
0.2%

위생업태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
단란주점
447 
<NA>
 
41

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
단란주점 447
91.6%
<NA> 41
 
8.4%

Length

2024-04-30T04:45:51.253971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:45:51.338850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
단란주점 447
91.6%
na 41
 
8.4%

남성종사자수
Categorical

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
0
351 
<NA>
114 
1
 
19
2
 
4

Length

Max length4
Median length1
Mean length1.7008197
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 351
71.9%
<NA> 114
 
23.4%
1 19
 
3.9%
2 4
 
0.8%

Length

2024-04-30T04:45:51.440209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:45:51.532448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 351
71.9%
na 114
 
23.4%
1 19
 
3.9%
2 4
 
0.8%

여성종사자수
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
0
352 
<NA>
114 
1
 
16
2
 
5
3
 
1

Length

Max length4
Median length1
Mean length1.7008197
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
0 352
72.1%
<NA> 114
 
23.4%
1 16
 
3.3%
2 5
 
1.0%
3 1
 
0.2%

Length

2024-04-30T04:45:51.641286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:45:51.724705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 352
72.1%
na 114
 
23.4%
1 16
 
3.3%
2 5
 
1.0%
3 1
 
0.2%

영업장주변구분명
Categorical

Distinct7
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
주택가주변
186 
유흥업소밀집지역
145 
기타
83 
<NA>
71 
결혼예식장주변
 
1
Other values (2)
 
2

Length

Max length8
Median length7
Mean length5.2459016
Min length2

Unique

Unique3 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
주택가주변 186
38.1%
유흥업소밀집지역 145
29.7%
기타 83
17.0%
<NA> 71
 
14.5%
결혼예식장주변 1
 
0.2%
아파트지역 1
 
0.2%
학교정화(상대) 1
 
0.2%

Length

2024-04-30T04:45:51.828104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:45:51.921960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주택가주변 186
38.1%
유흥업소밀집지역 145
29.7%
기타 83
17.0%
na 71
 
14.5%
결혼예식장주변 1
 
0.2%
아파트지역 1
 
0.2%
학교정화(상대 1
 
0.2%

등급구분명
Categorical

Distinct8
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
자율
198 
기타
174 
<NA>
95 
을
 
8
관리
 
5
Other values (3)
 
8

Length

Max length4
Median length2
Mean length2.3688525
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
자율 198
40.6%
기타 174
35.7%
<NA> 95
19.5%
을 8
 
1.6%
관리 5
 
1.0%
우수 3
 
0.6%
지도 3
 
0.6%
갑 2
 
0.4%

Length

2024-04-30T04:45:52.036718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:45:52.146198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자율 198
40.6%
기타 174
35.7%
na 95
19.5%
을 8
 
1.6%
관리 5
 
1.0%
우수 3
 
0.6%
지도 3
 
0.6%
갑 2
 
0.4%

급수시설구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
상수도전용
411 
<NA>
76 
간이상수도
 
1

Length

Max length5
Median length5
Mean length4.8442623
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
상수도전용 411
84.2%
<NA> 76
 
15.6%
간이상수도 1
 
0.2%

Length

2024-04-30T04:45:52.246254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:45:52.324725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 411
84.2%
na 76
 
15.6%
간이상수도 1
 
0.2%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
481 
0
 
7

Length

Max length4
Median length4
Mean length3.9569672
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> 481
98.6%
0 7
 
1.4%

Length

2024-04-30T04:45:52.422418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:45:52.504905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 481
98.6%
0 7
 
1.4%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
481 
0
 
7

Length

Max length4
Median length4
Mean length3.9569672
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> 481
98.6%
0 7
 
1.4%

Length

2024-04-30T04:45:52.597892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:45:52.681077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 481
98.6%
0 7
 
1.4%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
481 
0
 
7

Length

Max length4
Median length4
Mean length3.9569672
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> 481
98.6%
0 7
 
1.4%

Length

2024-04-30T04:45:52.766559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:45:52.849605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 481
98.6%
0 7
 
1.4%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
481 
0
 
7

Length

Max length4
Median length4
Mean length3.9569672
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> 481
98.6%
0 7
 
1.4%

Length

2024-04-30T04:45:52.929598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:45:53.019248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 481
98.6%
0 7
 
1.4%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
481 
0
 
7

Length

Max length4
Median length4
Mean length3.9569672
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> 481
98.6%
0 7
 
1.4%

Length

2024-04-30T04:45:53.119560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:45:53.217118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 481
98.6%
0 7
 
1.4%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing488
Missing (%)100.0%
Memory size4.4 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
481 
0
 
7

Length

Max length4
Median length4
Mean length3.9569672
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> 481
98.6%
0 7
 
1.4%

Length

2024-04-30T04:45:53.305512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:45:53.388893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 481
98.6%
0 7
 
1.4%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
481 
0
 
7

Length

Max length4
Median length4
Mean length3.9569672
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> 481
98.6%
0 7
 
1.4%

Length

2024-04-30T04:45:53.479426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:45:53.583810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 481
98.6%
0 7
 
1.4%

다중이용업소여부
Boolean

MISSING 

Distinct2
Distinct (%)0.4%
Missing41
Missing (%)8.4%
Memory size1.1 KiB
False
385 
True
62 
(Missing)
41 
ValueCountFrequency (%)
False 385
78.9%
True 62
 
12.7%
(Missing) 41
 
8.4%
2024-04-30T04:45:53.672076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING 

Distinct426
Distinct (%)95.3%
Missing41
Missing (%)8.4%
Infinite0
Infinite (%)0.0%
Mean108.13119
Minimum31.74
Maximum394.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-04-30T04:45:53.764430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum31.74
5-th percentile49.586
Q180.12
median106.13
Q3135.63
95-th percentile152.344
Maximum394.6
Range362.86
Interquartile range (IQR)55.51

Descriptive statistics

Standard deviation38.424506
Coefficient of variation (CV)0.35535083
Kurtosis7.075679
Mean108.13119
Median Absolute Deviation (MAD)27.19
Skewness1.3066101
Sum48334.64
Variance1476.4427
MonotonicityNot monotonic
2024-04-30T04:45:53.903258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
75.85 3
 
0.6%
142.0 3
 
0.6%
50.3 2
 
0.4%
115.52 2
 
0.4%
74.0 2
 
0.4%
139.7 2
 
0.4%
123.66 2
 
0.4%
148.0 2
 
0.4%
143.48 2
 
0.4%
143.4 2
 
0.4%
Other values (416) 425
87.1%
(Missing) 41
 
8.4%
ValueCountFrequency (%)
31.74 1
0.2%
33.06 1
0.2%
36.07 1
0.2%
39.38 1
0.2%
40.03 1
0.2%
40.17 1
0.2%
40.65 1
0.2%
41.61 1
0.2%
41.8 1
0.2%
43.4 1
0.2%
ValueCountFrequency (%)
394.6 1
0.2%
256.68 1
0.2%
254.7 1
0.2%
246.4 1
0.2%
227.56 1
0.2%
204.75 1
0.2%
204.68 1
0.2%
198.0 1
0.2%
192.0 1
0.2%
191.76 1
0.2%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing488
Missing (%)100.0%
Memory size4.4 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing488
Missing (%)100.0%
Memory size4.4 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing488
Missing (%)100.0%
Memory size4.4 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
032400003240000-103-1993-0537219931217<NA>3폐업2폐업20121228<NA><NA><NA>02 485412382.11134871서울특별시 강동구 천호동 397-45번지<NA><NA>아방궁2008-01-21 18:16:44I2018-08-31 23:59:59.0단란주점<NA><NA>단란주점00유흥업소밀집지역자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N82.11<NA><NA><NA>
132400003240000-103-1993-0537319931220<NA>3폐업2폐업19970722<NA><NA><NA>020474889198.83134871서울특별시 강동구 천호동 397-233번지<NA><NA>품바2002-06-05 00:00:00I2018-08-31 23:59:59.0단란주점<NA><NA>단란주점00유흥업소밀집지역자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N98.83<NA><NA><NA>
232400003240000-103-1993-0537419931220<NA>3폐업2폐업20010827<NA><NA><NA>02 4750051133.2134814서울특별시 강동구 길동 414-9번지<NA><NA>뉴프로포즈2002-06-05 00:00:00I2018-08-31 23:59:59.0단란주점212112.777294448266.564306단란주점00유흥업소밀집지역자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N133.2<NA><NA><NA>
332400003240000-103-1993-0537519931221<NA>1영업/정상1영업<NA><NA><NA><NA>02 4887070107.91134861서울특별시 강동구 천호동 34-21번지서울특별시 강동구 상암로 175 (천호동)5307짱1노래주점2017-12-07 10:04:06I2018-08-31 23:59:59.0단란주점212467.891746449347.740613단란주점00주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>Y107.91<NA><NA><NA>
432400003240000-103-1993-053761993-12-23<NA>3폐업2폐업2023-08-07<NA><NA><NA>020483956058.68134-851서울특별시 강동구 성내동 553-12서울특별시 강동구 성내로 8-8 (성내동)5398주화단란주점2023-08-07 09:22:41U2022-12-08 00:09:00.0단란주점210664.882366447547.014887<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
532400003240000-103-1993-0537719931224<NA>3폐업2폐업20110322<NA><NA><NA>02 441866846.8134867서울특별시 강동구 천호동 311-3번지<NA><NA>보리밭노래주점2010-05-04 13:22:20I2018-08-31 23:59:59.0단란주점211268.715189449474.992362단란주점00주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N46.8<NA><NA><NA>
632400003240000-103-1993-0537819931224<NA>3폐업2폐업20161123<NA><NA><NA>02 488536758.21134844서울특별시 강동구 성내동 415-5번지서울특별시 강동구 풍성로57길 16 (성내동)5376라이브2016-11-23 14:27:41I2018-08-31 23:59:59.0단란주점211974.499114447505.647406단란주점00주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N58.21<NA><NA><NA>
732400003240000-103-1993-0537919931224<NA>3폐업2폐업20010314<NA><NA><NA>023426040176.87134830서울특별시 강동구 명일동 312-78번지<NA><NA>코러스2001-03-14 00:00:00I2018-08-31 23:59:59.0단란주점212581.128737449918.981418단란주점00주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N76.87<NA><NA><NA>
832400003240000-103-1993-0538919931130<NA>3폐업2폐업20070423<NA><NA><NA>02 4785916142.0134812서울특별시 강동구 길동 367-1번지<NA><NA>길단란주점2002-06-05 00:00:00I2018-08-31 23:59:59.0단란주점212324.156328448603.376101단란주점00기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N142.0<NA><NA><NA>
932400003240000-103-1993-0539019931130<NA>3폐업2폐업20010911<NA><NA><NA>0204754448136.56134814서울특별시 강동구 길동 446-2번지<NA><NA>비엠더블유2002-06-05 00:00:00I2018-08-31 23:59:59.0단란주점211963.787409448212.012861단란주점00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N136.56<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
47832400003240000-103-2017-0000120170328<NA>3폐업2폐업20220628<NA><NA><NA><NA>79.15134871서울특별시 강동구 천호동 556서울특별시 강동구 진황도로 17 (천호동)5334여러분2022-06-28 13:43:47U2021-12-05 21:00:00.0단란주점211376.012702448604.82121<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
47932400003240000-103-2017-0000220170615<NA>1영업/정상1영업<NA><NA><NA><NA><NA>143.75134880서울특별시 강동구 길동 389-1번지서울특별시 강동구 양재대로113길 7, 2층 (길동)5353행복2018-07-04 15:54:40I2018-08-31 23:59:59.0단란주점212255.440997448416.842894단란주점<NA><NA>기타<NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>Y143.75<NA><NA><NA>
48032400003240000-103-2017-0000320170707<NA>3폐업2폐업20181112<NA><NA><NA><NA>121.89134814서울특별시 강동구 길동 414-5번지서울특별시 강동구 양재대로111길 29 (길동)5353가랑비Ⅱ2018-11-12 14:15:31U2018-11-14 02:36:38.0단란주점212126.200127448339.048387단란주점<NA><NA>유흥업소밀집지역<NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>Y121.89<NA><NA><NA>
48132400003240000-103-2018-0000120180405<NA>3폐업2폐업20210503<NA><NA><NA><NA>149.34134871서울특별시 강동구 천호동 550-5서울특별시 강동구 구천면로 212, 지층 (천호동)5334쉘부르 라이브 카페2021-05-03 14:06:43U2021-05-05 02:40:00.0단란주점211259.158202448691.17648단란주점<NA><NA>유흥업소밀집지역<NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>Y149.34<NA><NA><NA>
48232400003240000-103-2019-0000120190719<NA>1영업/정상1영업<NA><NA><NA><NA><NA>138.25134864서울특별시 강동구 천호동 453-7번지서울특별시 강동구 천호대로159길 25, 지층 (천호동)5335로데오포차70802020-03-30 14:34:47U2020-04-01 02:40:00.0단란주점211220.108222448503.534642단란주점<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>Y138.25<NA><NA><NA>
48332400003240000-103-2019-0000220191113<NA>1영업/정상1영업<NA><NA><NA><NA><NA>132.9134843서울특별시 강동구 성내동 244-14번지서울특별시 강동구 천호대로176길 10, 지층 (성내동)5373별이 빛나는 밤에2019-11-13 14:00:13I2019-11-15 00:23:15.0단란주점211960.925532447983.906817단란주점1<NA>기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>Y132.9<NA><NA><NA>
48432400003240000-103-2020-0000120200320<NA>1영업/정상1영업<NA><NA><NA><NA>02 485798273.35134843서울특별시 강동구 성내동 379번지서울특별시 강동구 천호대로 1134, 지하1층 (성내동)5373마당라이브주점2020-03-20 11:12:26I2020-03-22 00:23:22.0단란주점212058.101636447981.734199단란주점<NA><NA>기타<NA>간이상수도<NA><NA><NA><NA><NA><NA><NA><NA>Y73.35<NA><NA><NA>
48532400003240000-103-2022-0000120220511<NA>1영업/정상1영업<NA><NA><NA><NA>02 4742102111.88134814서울특별시 강동구 길동 414-5 골드클래스서울특별시 강동구 양재대로111길 27, B01호 (길동, 골드클래스)5353가랑비Ⅱ2022-08-11 14:19:49U2021-12-07 23:03:00.0단란주점212126.200127448339.048387<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
48632400003240000-103-2022-0000220220810<NA>1영업/정상1영업<NA><NA><NA><NA><NA>126.31134814서울특별시 강동구 길동 415-13 강동 큐브 2차서울특별시 강동구 진황도로 85, 지층 1,2호 (길동, 강동 큐브 2차)5354철부지2022-08-23 11:11:31U2021-12-07 22:05:00.0단란주점211963.942242448273.205059<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
48732400003240000-103-2022-0000320221014<NA>1영업/정상1영업<NA><NA><NA><NA><NA>123.2134864서울특별시 강동구 천호동 452 산경2 빌딩서울특별시 강동구 천호대로 1045, 산경2 빌딩 지층 (천호동)5335뭉스밸리(라이프앤라이브바)2022-10-27 13:54:40U2021-10-30 22:09:00.0단란주점211279.672086448363.39064<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>