Overview

Dataset statistics

Number of variables44
Number of observations383
Missing cells3467
Missing cells (%)20.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory140.4 KiB
Average record size in memory375.3 B

Variable types

Categorical21
Text7
DateTime4
Unsupported7
Numeric4
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
Author양천구
URLhttps://data.seoul.go.kr/dataList/OA-18016/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
남성종사자수 is highly imbalanced (71.5%)Imbalance
여성종사자수 is highly imbalanced (80.2%)Imbalance
영업장주변구분명 is highly imbalanced (79.6%)Imbalance
등급구분명 is highly imbalanced (65.2%)Imbalance
총인원 is highly imbalanced (78.6%)Imbalance
공장사무직종업원수 is highly imbalanced (78.6%)Imbalance
공장판매직종업원수 is highly imbalanced (78.6%)Imbalance
공장생산직종업원수 is highly imbalanced (78.6%)Imbalance
건물소유구분명 is highly imbalanced (87.3%)Imbalance
인허가취소일자 has 383 (100.0%) missing valuesMissing
폐업일자 has 225 (58.7%) missing valuesMissing
휴업시작일자 has 383 (100.0%) missing valuesMissing
휴업종료일자 has 383 (100.0%) missing valuesMissing
재개업일자 has 383 (100.0%) missing valuesMissing
전화번호 has 62 (16.2%) missing valuesMissing
소재지면적 has 32 (8.4%) missing valuesMissing
도로명주소 has 29 (7.6%) missing valuesMissing
도로명우편번호 has 34 (8.9%) missing valuesMissing
좌표정보(X) has 4 (1.0%) missing valuesMissing
좌표정보(Y) has 4 (1.0%) missing valuesMissing
다중이용업소여부 has 198 (51.7%) missing valuesMissing
시설총규모 has 198 (51.7%) missing valuesMissing
전통업소지정번호 has 383 (100.0%) missing valuesMissing
전통업소주된음식 has 383 (100.0%) missing valuesMissing
홈페이지 has 383 (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
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
시설총규모 has 35 (9.1%) zerosZeros

Reproduction

Analysis started2024-04-29 19:33:28.520864
Analysis finished2024-04-29 19:33:29.468833
Duration0.95 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
3140000
383 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3140000
2nd row3140000
3rd row3140000
4th row3140000
5th row3140000

Common Values

ValueCountFrequency (%)
3140000 383
100.0%

Length

2024-04-30T04:33:29.530099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:33:29.601955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3140000 383
100.0%

관리번호
Text

UNIQUE 

Distinct383
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2024-04-30T04:33:29.753667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters8426
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

Unique383 ?
Unique (%)100.0%

Sample

1st row3140000-105-1977-00067
2nd row3140000-105-1981-00020
3rd row3140000-105-1985-00001
4th row3140000-105-1985-00002
5th row3140000-105-1986-00003
ValueCountFrequency (%)
3140000-105-1977-00067 1
 
0.3%
3140000-105-2013-00021 1
 
0.3%
3140000-105-2013-00018 1
 
0.3%
3140000-105-2013-00017 1
 
0.3%
3140000-105-2013-00016 1
 
0.3%
3140000-105-2013-00015 1
 
0.3%
3140000-105-2013-00014 1
 
0.3%
3140000-105-2013-00013 1
 
0.3%
3140000-105-2013-00012 1
 
0.3%
3140000-105-2013-00011 1
 
0.3%
Other values (373) 373
97.4%
2024-04-30T04:33:30.040256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3780
44.9%
- 1149
 
13.6%
1 1123
 
13.3%
5 528
 
6.3%
3 490
 
5.8%
4 459
 
5.4%
2 450
 
5.3%
9 218
 
2.6%
7 79
 
0.9%
6 77
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7277
86.4%
Dash Punctuation 1149
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3780
51.9%
1 1123
 
15.4%
5 528
 
7.3%
3 490
 
6.7%
4 459
 
6.3%
2 450
 
6.2%
9 218
 
3.0%
7 79
 
1.1%
6 77
 
1.1%
8 73
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 1149
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8426
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3780
44.9%
- 1149
 
13.6%
1 1123
 
13.3%
5 528
 
6.3%
3 490
 
5.8%
4 459
 
5.4%
2 450
 
5.3%
9 218
 
2.6%
7 79
 
0.9%
6 77
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8426
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3780
44.9%
- 1149
 
13.6%
1 1123
 
13.3%
5 528
 
6.3%
3 490
 
5.8%
4 459
 
5.4%
2 450
 
5.3%
9 218
 
2.6%
7 79
 
0.9%
6 77
 
0.9%
Distinct330
Distinct (%)86.2%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
Minimum1977-10-01 00:00:00
Maximum2024-04-08 00:00:00
2024-04-30T04:33:30.170233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:33:30.300522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing383
Missing (%)100.0%
Memory size3.5 KiB
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
1
225 
3
158 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 225
58.7%
3 158
41.3%

Length

2024-04-30T04:33:30.415962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:33:30.495693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 225
58.7%
3 158
41.3%

영업상태명
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
영업/정상
225 
폐업
158 

Length

Max length5
Median length5
Mean length3.7624021
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 225
58.7%
폐업 158
41.3%

Length

2024-04-30T04:33:30.581745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:33:30.682980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 225
58.7%
폐업 158
41.3%
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
1
225 
2
158 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 225
58.7%
2 158
41.3%

Length

2024-04-30T04:33:30.774732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:33:30.851208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 225
58.7%
2 158
41.3%
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
영업
225 
폐업
158 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 225
58.7%
폐업 158
41.3%

Length

2024-04-30T04:33:30.939026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:33:31.022441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 225
58.7%
폐업 158
41.3%

폐업일자
Date

MISSING 

Distinct149
Distinct (%)94.3%
Missing225
Missing (%)58.7%
Memory size3.1 KiB
Minimum1994-06-28 00:00:00
Maximum2024-03-29 00:00:00
2024-04-30T04:33:31.130103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:33:31.253598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing383
Missing (%)100.0%
Memory size3.5 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing383
Missing (%)100.0%
Memory size3.5 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing383
Missing (%)100.0%
Memory size3.5 KiB

전화번호
Text

MISSING 

Distinct304
Distinct (%)94.7%
Missing62
Missing (%)16.2%
Memory size3.1 KiB
2024-04-30T04:33:31.440121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.168224
Min length8

Characters and Unicode

Total characters3264
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

Unique291 ?
Unique (%)90.7%

Sample

1st row0226917779
2nd row0226023122
3rd row02 6852313
4th row0226977251
5th row0226965601
ValueCountFrequency (%)
02 37
 
10.3%
0226965601 5
 
1.4%
0226517355 3
 
0.8%
0226531007 2
 
0.6%
26461816 2
 
0.6%
0226080262 2
 
0.6%
0226999014 2
 
0.6%
0226468909 2
 
0.6%
0226947567 2
 
0.6%
0226920253 2
 
0.6%
Other values (295) 300
83.6%
2024-04-30T04:33:31.764786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 765
23.4%
0 636
19.5%
6 448
13.7%
5 221
 
6.8%
4 219
 
6.7%
1 214
 
6.6%
9 206
 
6.3%
7 190
 
5.8%
3 175
 
5.4%
8 127
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3201
98.1%
Space Separator 63
 
1.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 765
23.9%
0 636
19.9%
6 448
14.0%
5 221
 
6.9%
4 219
 
6.8%
1 214
 
6.7%
9 206
 
6.4%
7 190
 
5.9%
3 175
 
5.5%
8 127
 
4.0%
Space Separator
ValueCountFrequency (%)
63
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3264
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 765
23.4%
0 636
19.5%
6 448
13.7%
5 221
 
6.8%
4 219
 
6.7%
1 214
 
6.6%
9 206
 
6.3%
7 190
 
5.8%
3 175
 
5.4%
8 127
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3264
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 765
23.4%
0 636
19.5%
6 448
13.7%
5 221
 
6.8%
4 219
 
6.7%
1 214
 
6.6%
9 206
 
6.3%
7 190
 
5.8%
3 175
 
5.4%
8 127
 
3.9%

소재지면적
Text

MISSING 

Distinct252
Distinct (%)71.8%
Missing32
Missing (%)8.4%
Memory size3.1 KiB
2024-04-30T04:33:32.070102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length5.1794872
Min length3

Characters and Unicode

Total characters1818
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

Unique217 ?
Unique (%)61.8%

Sample

1st row31.68
2nd row51.51
3rd row33.82
4th row35.24
5th row14.76
ValueCountFrequency (%)
00 17
 
4.8%
33.00 9
 
2.6%
16.50 9
 
2.6%
13.20 8
 
2.3%
18.00 8
 
2.3%
9.90 6
 
1.7%
30.00 5
 
1.4%
21.00 5
 
1.4%
12.00 5
 
1.4%
0.00 5
 
1.4%
Other values (242) 274
78.1%
2024-04-30T04:33:32.577648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 432
23.8%
. 351
19.3%
1 226
12.4%
2 148
 
8.1%
3 145
 
8.0%
5 108
 
5.9%
6 95
 
5.2%
8 90
 
5.0%
9 76
 
4.2%
4 75
 
4.1%
Other values (2) 72
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1465
80.6%
Other Punctuation 353
 
19.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 432
29.5%
1 226
15.4%
2 148
 
10.1%
3 145
 
9.9%
5 108
 
7.4%
6 95
 
6.5%
8 90
 
6.1%
9 76
 
5.2%
4 75
 
5.1%
7 70
 
4.8%
Other Punctuation
ValueCountFrequency (%)
. 351
99.4%
, 2
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
Common 1818
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 432
23.8%
. 351
19.3%
1 226
12.4%
2 148
 
8.1%
3 145
 
8.0%
5 108
 
5.9%
6 95
 
5.2%
8 90
 
5.0%
9 76
 
4.2%
4 75
 
4.1%
Other values (2) 72
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1818
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 432
23.8%
. 351
19.3%
1 226
12.4%
2 148
 
8.1%
3 145
 
8.0%
5 108
 
5.9%
6 95
 
5.2%
8 90
 
5.0%
9 76
 
4.2%
4 75
 
4.1%
Other values (2) 72
 
4.0%
Distinct128
Distinct (%)33.4%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2024-04-30T04:33:32.853917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.4151436
Min length6

Characters and Unicode

Total characters2457
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

Unique47 ?
Unique (%)12.3%

Sample

1st row158-090
2nd row158831
3rd row158855
4th row158070
5th row158840
ValueCountFrequency (%)
158070 33
 
8.6%
158-070 19
 
5.0%
158806 14
 
3.7%
158-050 14
 
3.7%
158050 13
 
3.4%
158885 8
 
2.1%
158829 7
 
1.8%
158-822 7
 
1.8%
158-823 6
 
1.6%
158860 6
 
1.6%
Other values (118) 256
66.8%
2024-04-30T04:33:33.240723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 719
29.3%
5 474
19.3%
1 443
18.0%
0 230
 
9.4%
- 159
 
6.5%
7 121
 
4.9%
2 78
 
3.2%
6 66
 
2.7%
4 66
 
2.7%
3 56
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2298
93.5%
Dash Punctuation 159
 
6.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 719
31.3%
5 474
20.6%
1 443
19.3%
0 230
 
10.0%
7 121
 
5.3%
2 78
 
3.4%
6 66
 
2.9%
4 66
 
2.9%
3 56
 
2.4%
9 45
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
- 159
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2457
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 719
29.3%
5 474
19.3%
1 443
18.0%
0 230
 
9.4%
- 159
 
6.5%
7 121
 
4.9%
2 78
 
3.2%
6 66
 
2.7%
4 66
 
2.7%
3 56
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2457
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 719
29.3%
5 474
19.3%
1 443
18.0%
0 230
 
9.4%
- 159
 
6.5%
7 121
 
4.9%
2 78
 
3.2%
6 66
 
2.7%
4 66
 
2.7%
3 56
 
2.3%
Distinct374
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2024-04-30T04:33:33.471737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length37
Mean length24.407311
Min length16

Characters and Unicode

Total characters9348
Distinct characters196
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique365 ?
Unique (%)95.3%

Sample

1st row서울특별시 양천구 신월동 338 중부운수 지하 1층
2nd row서울특별시 양천구 신월동 228-2
3rd row서울특별시 양천구 신정동 737-6번지
4th row서울특별시 양천구 신정동 1312번지
5th row서울특별시 양천구 신월동 546-27
ValueCountFrequency (%)
서울특별시 383
21.1%
양천구 383
21.1%
신정동 140
 
7.7%
목동 125
 
6.9%
신월동 121
 
6.7%
1층 24
 
1.3%
지하1층 22
 
1.2%
지상1층 14
 
0.8%
지하 7
 
0.4%
2층 7
 
0.4%
Other values (495) 589
32.5%
2024-04-30T04:33:33.821675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1616
 
17.3%
429
 
4.6%
1 426
 
4.6%
409
 
4.4%
394
 
4.2%
394
 
4.2%
394
 
4.2%
393
 
4.2%
389
 
4.2%
384
 
4.1%
Other values (186) 4120
44.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5587
59.8%
Decimal Number 1812
 
19.4%
Space Separator 1616
 
17.3%
Dash Punctuation 312
 
3.3%
Math Symbol 5
 
0.1%
Uppercase Letter 5
 
0.1%
Close Punctuation 4
 
< 0.1%
Open Punctuation 4
 
< 0.1%
Other Punctuation 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
429
 
7.7%
409
 
7.3%
394
 
7.1%
394
 
7.1%
394
 
7.1%
393
 
7.0%
389
 
7.0%
384
 
6.9%
384
 
6.9%
288
 
5.2%
Other values (166) 1729
30.9%
Decimal Number
ValueCountFrequency (%)
1 426
23.5%
2 252
13.9%
3 209
11.5%
9 178
9.8%
4 162
 
8.9%
0 134
 
7.4%
7 127
 
7.0%
5 124
 
6.8%
6 111
 
6.1%
8 89
 
4.9%
Uppercase Letter
ValueCountFrequency (%)
S 2
40.0%
B 1
20.0%
A 1
20.0%
O 1
20.0%
Space Separator
ValueCountFrequency (%)
1616
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 312
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5587
59.8%
Common 3756
40.2%
Latin 5
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
429
 
7.7%
409
 
7.3%
394
 
7.1%
394
 
7.1%
394
 
7.1%
393
 
7.0%
389
 
7.0%
384
 
6.9%
384
 
6.9%
288
 
5.2%
Other values (166) 1729
30.9%
Common
ValueCountFrequency (%)
1616
43.0%
1 426
 
11.3%
- 312
 
8.3%
2 252
 
6.7%
3 209
 
5.6%
9 178
 
4.7%
4 162
 
4.3%
0 134
 
3.6%
7 127
 
3.4%
5 124
 
3.3%
Other values (6) 216
 
5.8%
Latin
ValueCountFrequency (%)
S 2
40.0%
B 1
20.0%
A 1
20.0%
O 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5587
59.8%
ASCII 3761
40.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1616
43.0%
1 426
 
11.3%
- 312
 
8.3%
2 252
 
6.7%
3 209
 
5.6%
9 178
 
4.7%
4 162
 
4.3%
0 134
 
3.6%
7 127
 
3.4%
5 124
 
3.3%
Other values (10) 221
 
5.9%
Hangul
ValueCountFrequency (%)
429
 
7.7%
409
 
7.3%
394
 
7.1%
394
 
7.1%
394
 
7.1%
393
 
7.0%
389
 
7.0%
384
 
6.9%
384
 
6.9%
288
 
5.2%
Other values (166) 1729
30.9%

도로명주소
Text

MISSING 

Distinct341
Distinct (%)96.3%
Missing29
Missing (%)7.6%
Memory size3.1 KiB
2024-04-30T04:33:34.092146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length70
Median length45
Mean length30.135593
Min length21

Characters and Unicode

Total characters10668
Distinct characters203
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique331 ?
Unique (%)93.5%

Sample

1st row서울특별시 양천구 지양로 106, 중부운수 지하 1층 (신월동)
2nd row서울특별시 양천구 월정로 117 (신월동)
3rd row서울특별시 양천구 신정로7길 17 (신정동)
4th row서울특별시 양천구 신월로 151 (신월동)
5th row서울특별시 양천구 목동동로 105 (신정동)
ValueCountFrequency (%)
서울특별시 354
 
17.0%
양천구 354
 
17.0%
신정동 131
 
6.3%
신월동 114
 
5.5%
목동 113
 
5.4%
1층 35
 
1.7%
목동동로 27
 
1.3%
목동서로 25
 
1.2%
지하1층 23
 
1.1%
신월로 18
 
0.9%
Other values (465) 890
42.7%
2024-04-30T04:33:34.594893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1730
 
16.2%
585
 
5.5%
410
 
3.8%
382
 
3.6%
367
 
3.4%
1 367
 
3.4%
365
 
3.4%
365
 
3.4%
365
 
3.4%
359
 
3.4%
Other values (193) 5373
50.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6583
61.7%
Space Separator 1730
 
16.2%
Decimal Number 1382
 
13.0%
Close Punctuation 354
 
3.3%
Open Punctuation 354
 
3.3%
Other Punctuation 216
 
2.0%
Dash Punctuation 36
 
0.3%
Math Symbol 7
 
0.1%
Uppercase Letter 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
585
 
8.9%
410
 
6.2%
382
 
5.8%
367
 
5.6%
365
 
5.5%
365
 
5.5%
365
 
5.5%
359
 
5.5%
356
 
5.4%
355
 
5.4%
Other values (173) 2674
40.6%
Decimal Number
ValueCountFrequency (%)
1 367
26.6%
2 195
14.1%
3 167
12.1%
0 120
 
8.7%
5 111
 
8.0%
4 106
 
7.7%
7 97
 
7.0%
6 81
 
5.9%
8 73
 
5.3%
9 65
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
A 2
33.3%
S 2
33.3%
O 1
16.7%
B 1
16.7%
Space Separator
ValueCountFrequency (%)
1730
100.0%
Close Punctuation
ValueCountFrequency (%)
) 354
100.0%
Open Punctuation
ValueCountFrequency (%)
( 354
100.0%
Other Punctuation
ValueCountFrequency (%)
, 216
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 36
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6583
61.7%
Common 4079
38.2%
Latin 6
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
585
 
8.9%
410
 
6.2%
382
 
5.8%
367
 
5.6%
365
 
5.5%
365
 
5.5%
365
 
5.5%
359
 
5.5%
356
 
5.4%
355
 
5.4%
Other values (173) 2674
40.6%
Common
ValueCountFrequency (%)
1730
42.4%
1 367
 
9.0%
) 354
 
8.7%
( 354
 
8.7%
, 216
 
5.3%
2 195
 
4.8%
3 167
 
4.1%
0 120
 
2.9%
5 111
 
2.7%
4 106
 
2.6%
Other values (6) 359
 
8.8%
Latin
ValueCountFrequency (%)
A 2
33.3%
S 2
33.3%
O 1
16.7%
B 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6583
61.7%
ASCII 4085
38.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1730
42.4%
1 367
 
9.0%
) 354
 
8.7%
( 354
 
8.7%
, 216
 
5.3%
2 195
 
4.8%
3 167
 
4.1%
0 120
 
2.9%
5 111
 
2.7%
4 106
 
2.6%
Other values (10) 365
 
8.9%
Hangul
ValueCountFrequency (%)
585
 
8.9%
410
 
6.2%
382
 
5.8%
367
 
5.6%
365
 
5.5%
365
 
5.5%
365
 
5.5%
359
 
5.5%
356
 
5.4%
355
 
5.4%
Other values (173) 2674
40.6%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct150
Distinct (%)43.0%
Missing34
Missing (%)8.9%
Infinite0
Infinite (%)0.0%
Mean8003.6504
Minimum7900
Maximum8111
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2024-04-30T04:33:34.731900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7900
5-th percentile7909
Q17957
median8003
Q38049
95-th percentile8102.8
Maximum8111
Range211
Interquartile range (IQR)92

Descriptive statistics

Standard deviation60.958375
Coefficient of variation (CV)0.0076163215
Kurtosis-1.04558
Mean8003.6504
Median Absolute Deviation (MAD)46
Skewness0.043274591
Sum2793274
Variance3715.9234
MonotonicityNot monotonic
2024-04-30T04:33:34.875264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7909 10
 
2.6%
7902 7
 
1.8%
8100 6
 
1.6%
7925 6
 
1.6%
8021 6
 
1.6%
8080 6
 
1.6%
7984 6
 
1.6%
8107 6
 
1.6%
8032 6
 
1.6%
7929 5
 
1.3%
Other values (140) 285
74.4%
(Missing) 34
 
8.9%
ValueCountFrequency (%)
7900 1
 
0.3%
7901 1
 
0.3%
7902 7
1.8%
7903 1
 
0.3%
7905 1
 
0.3%
7906 1
 
0.3%
7907 1
 
0.3%
7908 1
 
0.3%
7909 10
2.6%
7910 1
 
0.3%
ValueCountFrequency (%)
8111 1
 
0.3%
8110 1
 
0.3%
8108 1
 
0.3%
8107 6
1.6%
8106 4
1.0%
8104 5
1.3%
8101 2
 
0.5%
8100 6
1.6%
8099 2
 
0.5%
8098 2
 
0.5%
Distinct346
Distinct (%)90.3%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2024-04-30T04:33:35.071924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length18
Mean length8.2036554
Min length4

Characters and Unicode

Total characters3142
Distinct characters302
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique314 ?
Unique (%)82.0%

Sample

1st row중부운수주식회사
2nd row신길운수(주)구내식당
3rd row상마운수구내식당
4th row풍양운수(주)
5th row세정병원
ValueCountFrequency (%)
어린이집 8
 
1.9%
구립해바라기어린이집 4
 
1.0%
구립 4
 
1.0%
구립갈산어린이집 3
 
0.7%
횃불자연어린이집 3
 
0.7%
구내식당 3
 
0.7%
명지어린이집 3
 
0.7%
혜원유아학교 3
 
0.7%
해맞이경로식당 2
 
0.5%
서울sos어린이마을 2
 
0.5%
Other values (355) 385
91.7%
2024-04-30T04:33:35.403826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
185
 
5.9%
178
 
5.7%
160
 
5.1%
157
 
5.0%
106
 
3.4%
87
 
2.8%
84
 
2.7%
80
 
2.5%
77
 
2.5%
70
 
2.2%
Other values (292) 1958
62.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2990
95.2%
Space Separator 37
 
1.2%
Close Punctuation 34
 
1.1%
Open Punctuation 34
 
1.1%
Uppercase Letter 30
 
1.0%
Decimal Number 16
 
0.5%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
185
 
6.2%
178
 
6.0%
160
 
5.4%
157
 
5.3%
106
 
3.5%
87
 
2.9%
84
 
2.8%
80
 
2.7%
77
 
2.6%
70
 
2.3%
Other values (275) 1806
60.4%
Uppercase Letter
ValueCountFrequency (%)
S 18
60.0%
O 5
 
16.7%
G 2
 
6.7%
W 1
 
3.3%
B 1
 
3.3%
P 1
 
3.3%
L 1
 
3.3%
H 1
 
3.3%
Decimal Number
ValueCountFrequency (%)
3 7
43.8%
2 4
25.0%
4 2
 
12.5%
5 2
 
12.5%
1 1
 
6.2%
Space Separator
ValueCountFrequency (%)
37
100.0%
Close Punctuation
ValueCountFrequency (%)
) 34
100.0%
Open Punctuation
ValueCountFrequency (%)
( 34
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2990
95.2%
Common 122
 
3.9%
Latin 30
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
185
 
6.2%
178
 
6.0%
160
 
5.4%
157
 
5.3%
106
 
3.5%
87
 
2.9%
84
 
2.8%
80
 
2.7%
77
 
2.6%
70
 
2.3%
Other values (275) 1806
60.4%
Common
ValueCountFrequency (%)
37
30.3%
) 34
27.9%
( 34
27.9%
3 7
 
5.7%
2 4
 
3.3%
4 2
 
1.6%
5 2
 
1.6%
- 1
 
0.8%
1 1
 
0.8%
Latin
ValueCountFrequency (%)
S 18
60.0%
O 5
 
16.7%
G 2
 
6.7%
W 1
 
3.3%
B 1
 
3.3%
P 1
 
3.3%
L 1
 
3.3%
H 1
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2990
95.2%
ASCII 152
 
4.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
185
 
6.2%
178
 
6.0%
160
 
5.4%
157
 
5.3%
106
 
3.5%
87
 
2.9%
84
 
2.8%
80
 
2.7%
77
 
2.6%
70
 
2.3%
Other values (275) 1806
60.4%
ASCII
ValueCountFrequency (%)
37
24.3%
) 34
22.4%
( 34
22.4%
S 18
11.8%
3 7
 
4.6%
O 5
 
3.3%
2 4
 
2.6%
4 2
 
1.3%
5 2
 
1.3%
G 2
 
1.3%
Other values (7) 7
 
4.6%
Distinct379
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
Minimum1999-03-22 00:00:00
Maximum2024-04-22 15:17:12
2024-04-30T04:33:35.556411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:33:35.843832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
U
260 
I
123 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 260
67.9%
I 123
32.1%

Length

2024-04-30T04:33:35.956765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:33:36.034693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 260
67.9%
i 123
32.1%
Distinct149
Distinct (%)38.9%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 23:07:00
2024-04-30T04:33:36.137720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:33:36.257700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct8
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
어린이집
176 
학교
62 
집단급식소
48 
산업체
28 
병원
24 
Other values (3)
45 

Length

Max length8
Median length6
Mean length3.7963446
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row산업체
2nd row산업체
3rd row집단급식소
4th row집단급식소
5th row병원

Common Values

ValueCountFrequency (%)
어린이집 176
46.0%
학교 62
 
16.2%
집단급식소 48
 
12.5%
산업체 28
 
7.3%
병원 24
 
6.3%
사회복지시설 23
 
6.0%
공공기관 15
 
3.9%
기타 집단급식소 7
 
1.8%

Length

2024-04-30T04:33:36.364722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:33:36.470117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
어린이집 176
45.1%
학교 62
 
15.9%
집단급식소 55
 
14.1%
산업체 28
 
7.2%
병원 24
 
6.2%
사회복지시설 23
 
5.9%
공공기관 15
 
3.8%
기타 7
 
1.8%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct285
Distinct (%)75.2%
Missing4
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean187123.58
Minimum184303.31
Maximum189954.81
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2024-04-30T04:33:36.583159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum184303.31
5-th percentile184605.36
Q1185642.57
median187480.1
Q3188463.45
95-th percentile189397.58
Maximum189954.81
Range5651.498
Interquartile range (IQR)2820.8799

Descriptive statistics

Standard deviation1574.8421
Coefficient of variation (CV)0.0084160535
Kurtosis-1.2961254
Mean187123.58
Median Absolute Deviation (MAD)1279.5359
Skewness-0.21972157
Sum70919838
Variance2480127.6
MonotonicityNot monotonic
2024-04-30T04:33:36.710227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
185827.975624821 6
 
1.6%
188012.804745161 4
 
1.0%
187249.317873069 4
 
1.0%
186736.062689359 4
 
1.0%
185154.943534009 3
 
0.8%
185474.91252016 3
 
0.8%
184454.72857146 3
 
0.8%
186212.077225528 3
 
0.8%
184383.822944091 3
 
0.8%
188248.45432693 3
 
0.8%
Other values (275) 343
89.6%
(Missing) 4
 
1.0%
ValueCountFrequency (%)
184303.313102325 1
 
0.3%
184328.485185892 1
 
0.3%
184383.822944091 3
0.8%
184399.621995774 1
 
0.3%
184448.272783027 1
 
0.3%
184448.497335143 1
 
0.3%
184454.72857146 3
0.8%
184487.550160698 1
 
0.3%
184495.17209953 1
 
0.3%
184521.933999559 1
 
0.3%
ValueCountFrequency (%)
189954.811054416 1
 
0.3%
189887.346500162 1
 
0.3%
189878.40729119 1
 
0.3%
189755.541308355 1
 
0.3%
189749.776358917 1
 
0.3%
189668.460949388 1
 
0.3%
189659.125277836 3
0.8%
189606.474101545 1
 
0.3%
189591.500240064 1
 
0.3%
189529.814073561 1
 
0.3%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct285
Distinct (%)75.2%
Missing4
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean447071.2
Minimum444868.74
Maximum449629.96
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2024-04-30T04:33:36.821255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum444868.74
5-th percentile445395.94
Q1446176.18
median446938.51
Q3448047.16
95-th percentile449137.01
Maximum449629.96
Range4761.2207
Interquartile range (IQR)1870.9757

Descriptive statistics

Standard deviation1152.1928
Coefficient of variation (CV)0.002577202
Kurtosis-0.87737066
Mean447071.2
Median Absolute Deviation (MAD)885.95101
Skewness0.21664116
Sum1.6943999 × 108
Variance1327548.3
MonotonicityNot monotonic
2024-04-30T04:33:36.959054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
446176.194065655 6
 
1.6%
445428.447103333 4
 
1.0%
446114.410048234 4
 
1.0%
445459.440713374 4
 
1.0%
448178.682163138 3
 
0.8%
445064.011138948 3
 
0.8%
447667.536679893 3
 
0.8%
445395.940461092 3
 
0.8%
448400.817278971 3
 
0.8%
447406.301288366 3
 
0.8%
Other values (275) 343
89.6%
(Missing) 4
 
1.0%
ValueCountFrequency (%)
444868.742452 1
 
0.3%
444892.582335434 1
 
0.3%
444905.824632031 1
 
0.3%
444911.609710795 2
0.5%
445064.011138948 3
0.8%
445113.109971419 1
 
0.3%
445182.294506346 1
 
0.3%
445195.138133503 3
0.8%
445209.687205241 1
 
0.3%
445314.902028856 1
 
0.3%
ValueCountFrequency (%)
449629.963135049 1
0.3%
449514.720303239 1
0.3%
449396.806374349 1
0.3%
449394.906116227 1
0.3%
449385.138579775 1
0.3%
449356.035158698 1
0.3%
449355.938021288 1
0.3%
449321.244359901 1
0.3%
449259.449227257 1
0.3%
449236.333206296 2
0.5%

위생업태명
Categorical

Distinct9
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
<NA>
198 
어린이집
90 
집단급식소
48 
병원
 
15
산업체
 
10
Other values (4)
22 

Length

Max length8
Median length4
Mean length4.0626632
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 198
51.7%
어린이집 90
23.5%
집단급식소 48
 
12.5%
병원 15
 
3.9%
산업체 10
 
2.6%
사회복지시설 8
 
2.1%
학교 6
 
1.6%
공공기관 5
 
1.3%
기타 집단급식소 3
 
0.8%

Length

2024-04-30T04:33:37.103826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:33:37.208979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 198
51.3%
어린이집 90
23.3%
집단급식소 51
 
13.2%
병원 15
 
3.9%
산업체 10
 
2.6%
사회복지시설 8
 
2.1%
학교 6
 
1.6%
공공기관 5
 
1.3%
기타 3
 
0.8%

남성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
<NA>
350 
0
 
31
1
 
2

Length

Max length4
Median length4
Mean length3.7415144
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 350
91.4%
0 31
 
8.1%
1 2
 
0.5%

Length

2024-04-30T04:33:37.324091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:33:37.430149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 350
91.4%
0 31
 
8.1%
1 2
 
0.5%

여성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
<NA>
350 
0
 
27
4
 
2
6
 
2
3
 
1

Length

Max length4
Median length4
Mean length3.7415144
Min length1

Unique

Unique2 ?
Unique (%)0.5%

Sample

1st row<NA>
2nd row0
3rd row0
4th row4
5th row4

Common Values

ValueCountFrequency (%)
<NA> 350
91.4%
0 27
 
7.0%
4 2
 
0.5%
6 2
 
0.5%
3 1
 
0.3%
7 1
 
0.3%

Length

2024-04-30T04:33:37.525671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:33:37.623212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 350
91.4%
0 27
 
7.0%
4 2
 
0.5%
6 2
 
0.5%
3 1
 
0.3%
7 1
 
0.3%

영업장주변구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
<NA>
358 
기타
 
20
주택가주변
 
3
학교정화(절대)
 
2

Length

Max length8
Median length4
Mean length3.924282
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 358
93.5%
기타 20
 
5.2%
주택가주변 3
 
0.8%
학교정화(절대) 2
 
0.5%

Length

2024-04-30T04:33:37.747057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:33:37.859607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 358
93.5%
기타 20
 
5.2%
주택가주변 3
 
0.8%
학교정화(절대 2
 
0.5%

등급구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
<NA>
358 
기타
 
25

Length

Max length4
Median length4
Mean length3.8694517
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 358
93.5%
기타 25
 
6.5%

Length

2024-04-30T04:33:37.966071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:33:38.067720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 358
93.5%
기타 25
 
6.5%
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
<NA>
236 
상수도전용
147 

Length

Max length5
Median length4
Mean length4.383812
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 236
61.6%
상수도전용 147
38.4%

Length

2024-04-30T04:33:38.146221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:33:38.235998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 236
61.6%
상수도전용 147
38.4%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
<NA>
370 
0
 
13

Length

Max length4
Median length4
Mean length3.8981723
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 370
96.6%
0 13
 
3.4%

Length

2024-04-30T04:33:38.345036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:33:38.429087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 370
96.6%
0 13
 
3.4%
Distinct4
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
<NA>
236 
0
145 
3
 
1
13
 
1

Length

Max length4
Median length4
Mean length2.8511749
Min length1

Unique

Unique2 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 236
61.6%
0 145
37.9%
3 1
 
0.3%
13 1
 
0.3%

Length

2024-04-30T04:33:38.523815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:33:38.614644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 236
61.6%
0 145
37.9%
3 1
 
0.3%
13 1
 
0.3%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
<NA>
370 
0
 
13

Length

Max length4
Median length4
Mean length3.8981723
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 370
96.6%
0 13
 
3.4%

Length

2024-04-30T04:33:38.720658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:33:38.831239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 370
96.6%
0 13
 
3.4%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
<NA>
370 
0
 
13

Length

Max length4
Median length4
Mean length3.8981723
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 370
96.6%
0 13
 
3.4%

Length

2024-04-30T04:33:38.919150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:33:39.011284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 370
96.6%
0 13
 
3.4%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
<NA>
370 
0
 
13

Length

Max length4
Median length4
Mean length3.8981723
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 370
96.6%
0 13
 
3.4%

Length

2024-04-30T04:33:39.097473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:33:39.180984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 370
96.6%
0 13
 
3.4%

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
<NA>
372 
자가
 
10
임대
 
1

Length

Max length4
Median length4
Mean length3.9425587
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 372
97.1%
자가 10
 
2.6%
임대 1
 
0.3%

Length

2024-04-30T04:33:39.271386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:33:39.373739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 372
97.1%
자가 10
 
2.6%
임대 1
 
0.3%

보증액
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
<NA>
275 
0
108 

Length

Max length4
Median length4
Mean length3.154047
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 275
71.8%
0 108
 
28.2%

Length

2024-04-30T04:33:39.502116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:33:39.587479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 275
71.8%
0 108
 
28.2%

월세액
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
<NA>
275 
0
108 

Length

Max length4
Median length4
Mean length3.154047
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 275
71.8%
0 108
 
28.2%

Length

2024-04-30T04:33:39.675383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:33:39.768172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 275
71.8%
0 108
 
28.2%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.5%
Missing198
Missing (%)51.7%
Memory size898.0 B
False
185 
(Missing)
198 
ValueCountFrequency (%)
False 185
48.3%
(Missing) 198
51.7%
2024-04-30T04:33:39.841394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct115
Distinct (%)62.2%
Missing198
Missing (%)51.7%
Infinite0
Infinite (%)0.0%
Mean66.822432
Minimum0
Maximum1335.84
Zeros35
Zeros (%)9.1%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2024-04-30T04:33:39.937157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q19.04
median16.5
Q343.44
95-th percentile324.12
Maximum1335.84
Range1335.84
Interquartile range (IQR)34.4

Descriptive statistics

Standard deviation145.30589
Coefficient of variation (CV)2.1745076
Kurtosis34.629721
Mean66.822432
Median Absolute Deviation (MAD)12.54
Skewness5.0008922
Sum12362.15
Variance21113.801
MonotonicityNot monotonic
2024-04-30T04:33:40.067535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 35
 
9.1%
18.0 6
 
1.6%
13.2 5
 
1.3%
15.0 5
 
1.3%
9.9 4
 
1.0%
10.0 4
 
1.0%
16.5 4
 
1.0%
20.0 4
 
1.0%
9.0 3
 
0.8%
21.0 3
 
0.8%
Other values (105) 112
29.2%
(Missing) 198
51.7%
ValueCountFrequency (%)
0.0 35
9.1%
5.0 1
 
0.3%
6.1 1
 
0.3%
6.6 2
 
0.5%
7.1 1
 
0.3%
7.5 1
 
0.3%
8.1 1
 
0.3%
9.0 3
 
0.8%
9.01 1
 
0.3%
9.04 1
 
0.3%
ValueCountFrequency (%)
1335.84 1
0.3%
777.07 1
0.3%
511.38 1
0.3%
462.0 1
0.3%
442.0 1
0.3%
414.86 1
0.3%
392.33 1
0.3%
380.0 1
0.3%
364.21 1
0.3%
325.7 1
0.3%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing383
Missing (%)100.0%
Memory size3.5 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing383
Missing (%)100.0%
Memory size3.5 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing383
Missing (%)100.0%
Memory size3.5 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031400003140000-105-1977-000671977-10-01<NA>1영업/정상1영업<NA><NA><NA><NA>022691777931.68158-090서울특별시 양천구 신월동 338 중부운수 지하 1층서울특별시 양천구 지양로 106, 중부운수 지하 1층 (신월동)8033중부운수주식회사2023-04-03 11:16:17U2022-12-04 00:05:00.0산업체184981.248966446925.40176<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
131400003140000-105-1981-0002019811001<NA>3폐업2폐업20211231<NA><NA><NA>022602312251.51158831서울특별시 양천구 신월동 228-2서울특별시 양천구 월정로 117 (신월동)7925신길운수(주)구내식당2021-12-31 13:54:16U2022-01-02 02:40:00.0산업체185642.568764447475.465043산업체00기타기타상수도전용00000<NA>00N89.76<NA><NA><NA>
231400003140000-105-1985-0000119851101<NA>3폐업2폐업19950528<NA><NA><NA>02 685231333.82158855서울특별시 양천구 신정동 737-6번지<NA><NA>상마운수구내식당2002-01-07 00:00:00I2018-08-31 23:59:59.0집단급식소<NA><NA>집단급식소00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N202.81<NA><NA><NA>
331400003140000-105-1985-0000219851201<NA>3폐업2폐업20100413<NA><NA><NA>022697725135.24158070서울특별시 양천구 신정동 1312번지서울특별시 양천구 신정로7길 17 (신정동)8056풍양운수(주)2012-09-21 11:06:16I2018-08-31 23:59:59.0집단급식소185474.91252445064.011139집단급식소04기타기타<NA><NA>0<NA><NA><NA><NA><NA><NA>N73.65<NA><NA><NA>
431400003140000-105-1986-0000319861201<NA>3폐업2폐업20040930<NA><NA><NA>022696560114.76158840서울특별시 양천구 신월동 546-27서울특별시 양천구 신월로 151 (신월동)8032세정병원2021-11-23 20:02:41U2021-11-25 02:40:00.0병원185827.975625446176.194066병원04주택가주변기타상수도전용00000<NA>00N37.97<NA><NA><NA>
531400003140000-105-1988-0000519880501<NA>1영업/정상1영업<NA><NA><NA><NA>0226203802558.00158885서울특별시 양천구 신정동 321-4번지서울특별시 양천구 목동동로 105 (신정동)8095양천구청구내식당2016-10-17 17:48:44I2018-08-31 23:59:59.0공공기관188126.018239446099.600366공공기관00기타기타상수도전용<NA>0<NA><NA><NA><NA><NA><NA>N511.38<NA><NA><NA>
631400003140000-105-1990-0000419900703<NA>3폐업2폐업20060405<NA><NA><NA>02 600800146.80158822서울특별시 양천구 신월동 6-2번지<NA><NA>삼성제2생활관2003-04-03 00:00:00I2018-08-31 23:59:59.0집단급식소<NA><NA>집단급식소00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N325.7<NA><NA><NA>
731400003140000-105-1991-000211991-03-13<NA>1영업/정상1영업<NA><NA><NA><NA>0226460941256.00158-876서울특별시 양천구 목동 905-16서울특별시 양천구 목동서로 117 (목동)7988서울양천우체국2023-07-11 16:27:04U2022-12-06 23:03:00.0공공기관188973.702515447842.027536<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
831400003140000-105-1992-0000619920507<NA>3폐업2폐업19970123<NA><NA><NA>02 693555239.14158857서울특별시 양천구 신정동 899-1번지<NA><NA>홍익병원구내식당2001-09-28 00:00:00I2018-08-31 23:59:59.0집단급식소187879.054915447370.031968집단급식소00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N112.1<NA><NA><NA>
931400003140000-105-1992-0000719920516<NA>3폐업2폐업20130208<NA><NA><NA>022644131356.27158819서울특별시 양천구 목동 793-3번지서울특별시 양천구 등촌로 22 (목동)7966제성병원2013-02-13 16:32:42I2018-08-31 23:59:59.0집단급식소187918.421583447753.887261집단급식소00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N121.95<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
37331400003140000-105-2022-000032022-03-04<NA>1영업/정상1영업<NA><NA><NA><NA>022691050956.32158-070서울특별시 양천구 신정동 1268 복합메디컬타운 2층 217호서울특별시 양천구 중앙로 181, 복합메디컬타운 2층 217호 (신정동)8106피에스에이목동어학학원2024-04-15 13:56:09U2023-12-03 23:07:00.0기타 집단급식소187181.284838445624.366466<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
37431400003140000-105-2022-000042022-03-21<NA>1영업/정상1영업<NA><NA><NA><NA><NA>6.60158-826서울특별시 양천구 신월동 92-19 명지어린이집서울특별시 양천구 곰달래로9길 72, 명지어린이집 1층 (신월동)7917명지어린이집2023-03-29 18:16:19U2022-12-04 00:01:00.0어린이집185154.943534448178.682163<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
37531400003140000-105-2022-000052022-05-30<NA>1영업/정상1영업<NA><NA><NA><NA>02260592379.90158-831서울특별시 양천구 신월동 218-31 베다니어린이집서울특별시 양천구 남부순환로65길 16-1, 베다니어린이집 (신월동)7927서울베다니어린이집2023-03-29 18:10:14U2022-12-04 00:01:00.0어린이집185405.104294447292.369515<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
37631400003140000-105-2022-0000620220608<NA>1영업/정상1영업<NA><NA><NA><NA><NA>9.90158070서울특별시 양천구 신정동 1277 신트리4단지아파트서울특별시 양천구 신정로 260, 보육원동 1층 (신정동, 신트리4단지아파트)8107혜원유아학교 어린이집2022-06-08 16:06:41I2021-12-05 23:00:00.0어린이집186736.062689445459.440713<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
37731400003140000-105-2023-000012023-02-08<NA>3폐업2폐업2023-11-30<NA><NA><NA><NA>332.68158-822서울특별시 양천구 신월동 17-1 강서양천교육지원청 4층서울특별시 양천구 월정로 269, 강서양천교육지원청 4층 (신월동)7902서울특별시강서양천교육지원청2023-11-30 18:16:17U2022-11-02 00:02:00.0공공기관184858.473385448809.049681<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
37831400003140000-105-2023-000022023-02-28<NA>1영업/정상1영업<NA><NA><NA><NA>022602290226.32158-822서울특별시 양천구 신월동 1-35 이글나래어린이집 1층서울특별시 양천구 화곡로3길 27-8, 이글나래어린이집 1층 (신월동)7900이글나래 어린이집2023-03-30 09:01:50U2022-12-04 00:01:00.0어린이집184599.242641448862.812457<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
37931400003140000-105-2023-000032023-03-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA>339.00158-070서울특별시 양천구 신정동 1322-14서울특별시 양천구 신정이펜2로 56 (신정동)8045사단법인 열방아카데미2023-07-14 13:46:19U2022-12-06 23:06:00.0기타 집단급식소185055.397162445947.200505<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
38031400003140000-105-2023-000042023-06-16<NA>1영업/정상1영업<NA><NA><NA><NA>02 556 2373337.02158-806서울특별시 양천구 목동 408-116서울특별시 양천구 오목로 284, 1층 (목동)8003시대인재 목동 W관 식당2024-04-12 10:54:37U2023-12-03 23:04:00.0기타 집단급식소188344.714957446998.82255<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
38131400003140000-105-2023-000052023-10-26<NA>1영업/정상1영업<NA><NA><NA><NA><NA>166.74158-050서울특별시 양천구 목동 923-14 드림타워서울특별시 양천구 목동동로 233-1, 드림타워 지하124~127호 (목동)7995시대인재 목동식당2024-04-22 13:34:22U2023-12-03 22:04:00.0기타 집단급식소188584.345447447255.070457<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
38231400003140000-105-2024-000012024-04-08<NA>1영업/정상1영업<NA><NA><NA><NA>0226405171467.55158-872서울특별시 양천구 목동 900서울특별시 양천구 목동서로 20, 1층 (목동)7978서울에너지공사 구내식당2024-04-08 14:09:05I2023-12-03 23:00:00.0산업체189659.125278448616.907018<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>