Overview

Dataset statistics

Number of variables44
Number of observations293
Missing cells2909
Missing cells (%)22.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory108.0 KiB
Average record size in memory377.5 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
Author강북구
URLhttps://data.seoul.go.kr/dataList/OA-18410/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
영업장주변구분명 is highly imbalanced (57.7%)Imbalance
등급구분명 is highly imbalanced (56.1%)Imbalance
총인원 is highly imbalanced (75.3%)Imbalance
본사종업원수 is highly imbalanced (75.3%)Imbalance
공장사무직종업원수 is highly imbalanced (75.3%)Imbalance
공장판매직종업원수 is highly imbalanced (75.3%)Imbalance
공장생산직종업원수 is highly imbalanced (75.3%)Imbalance
보증액 is highly imbalanced (75.3%)Imbalance
월세액 is highly imbalanced (75.3%)Imbalance
다중이용업소여부 is highly imbalanced (96.1%)Imbalance
인허가취소일자 has 293 (100.0%) missing valuesMissing
폐업일자 has 82 (28.0%) missing valuesMissing
휴업시작일자 has 293 (100.0%) missing valuesMissing
휴업종료일자 has 293 (100.0%) missing valuesMissing
재개업일자 has 293 (100.0%) missing valuesMissing
전화번호 has 151 (51.5%) missing valuesMissing
소재지면적 has 35 (11.9%) missing valuesMissing
도로명주소 has 94 (32.1%) missing valuesMissing
도로명우편번호 has 95 (32.4%) missing valuesMissing
좌표정보(X) has 4 (1.4%) missing valuesMissing
좌표정보(Y) has 4 (1.4%) missing valuesMissing
건물소유구분명 has 293 (100.0%) missing valuesMissing
다중이용업소여부 has 50 (17.1%) missing valuesMissing
시설총규모 has 50 (17.1%) missing valuesMissing
전통업소지정번호 has 293 (100.0%) missing valuesMissing
전통업소주된음식 has 293 (100.0%) missing valuesMissing
홈페이지 has 293 (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
소재지면적 has 6 (2.0%) zerosZeros
시설총규모 has 35 (11.9%) zerosZeros

Reproduction

Analysis started2024-05-11 03:58:35.109435
Analysis finished2024-05-11 03:58:37.435594
Duration2.33 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
3080000
293 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3080000
2nd row3080000
3rd row3080000
4th row3080000
5th row3080000

Common Values

ValueCountFrequency (%)
3080000 293
100.0%

Length

2024-05-11T03:58:37.763310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:58:38.166537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3080000 293
100.0%

관리번호
Text

UNIQUE 

Distinct293
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2024-05-11T03:58:38.700432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters6446
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

Unique293 ?
Unique (%)100.0%

Sample

1st row3080000-121-1969-01952
2nd row3080000-121-1971-01960
3rd row3080000-121-1978-01949
4th row3080000-121-1979-01932
5th row3080000-121-1981-01939
ValueCountFrequency (%)
3080000-121-1969-01952 1
 
0.3%
3080000-121-2009-00009 1
 
0.3%
3080000-121-2014-00001 1
 
0.3%
3080000-121-2013-00008 1
 
0.3%
3080000-121-2013-00007 1
 
0.3%
3080000-121-2013-00006 1
 
0.3%
3080000-121-2013-00005 1
 
0.3%
3080000-121-2013-00004 1
 
0.3%
3080000-121-2013-00003 1
 
0.3%
3080000-121-2013-00002 1
 
0.3%
Other values (283) 283
96.6%
2024-05-11T03:58:40.110174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2826
43.8%
1 895
 
13.9%
- 879
 
13.6%
2 686
 
10.6%
3 387
 
6.0%
8 380
 
5.9%
9 150
 
2.3%
7 62
 
1.0%
5 61
 
0.9%
4 61
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5567
86.4%
Dash Punctuation 879
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2826
50.8%
1 895
 
16.1%
2 686
 
12.3%
3 387
 
7.0%
8 380
 
6.8%
9 150
 
2.7%
7 62
 
1.1%
5 61
 
1.1%
4 61
 
1.1%
6 59
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 879
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6446
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2826
43.8%
1 895
 
13.9%
- 879
 
13.6%
2 686
 
10.6%
3 387
 
6.0%
8 380
 
5.9%
9 150
 
2.3%
7 62
 
1.0%
5 61
 
0.9%
4 61
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6446
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2826
43.8%
1 895
 
13.9%
- 879
 
13.6%
2 686
 
10.6%
3 387
 
6.0%
8 380
 
5.9%
9 150
 
2.3%
7 62
 
1.0%
5 61
 
0.9%
4 61
 
0.9%

인허가일자
Date

Distinct282
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
Minimum1969-12-12 00:00:00
Maximum2024-04-12 00:00:00
2024-05-11T03:58:40.646051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:58:41.280211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing293
Missing (%)100.0%
Memory size2.7 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
3
211 
1
82 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 211
72.0%
1 82
 
28.0%

Length

2024-05-11T03:58:42.130801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:58:42.732798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 211
72.0%
1 82
 
28.0%

영업상태명
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
폐업
211 
영업/정상
82 

Length

Max length5
Median length2
Mean length2.8395904
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 211
72.0%
영업/정상 82
 
28.0%

Length

2024-05-11T03:58:43.171475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:58:43.639239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 211
72.0%
영업/정상 82
 
28.0%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2
211 
1
82 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 211
72.0%
1 82
 
28.0%

Length

2024-05-11T03:58:43.967994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:58:44.343076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 211
72.0%
1 82
 
28.0%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
폐업
211 
영업
82 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 211
72.0%
영업 82
 
28.0%

Length

2024-05-11T03:58:44.736593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:58:45.057826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 211
72.0%
영업 82
 
28.0%

폐업일자
Date

MISSING 

Distinct190
Distinct (%)90.0%
Missing82
Missing (%)28.0%
Memory size2.4 KiB
Minimum2005-10-20 00:00:00
Maximum2024-03-18 00:00:00
2024-05-11T03:58:45.414289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:58:45.844937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing293
Missing (%)100.0%
Memory size2.7 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing293
Missing (%)100.0%
Memory size2.7 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing293
Missing (%)100.0%
Memory size2.7 KiB

전화번호
Text

MISSING 

Distinct140
Distinct (%)98.6%
Missing151
Missing (%)51.5%
Memory size2.4 KiB
2024-05-11T03:58:46.561012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.478873
Min length2

Characters and Unicode

Total characters1488
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

Unique138 ?
Unique (%)97.2%

Sample

1st row0209942207
2nd row0209893003
3rd row02 9930519
4th row02 9936170
5th row0209022710
ValueCountFrequency (%)
02 122
40.1%
987 4
 
1.3%
902 3
 
1.0%
989 3
 
1.0%
986 2
 
0.7%
998 2
 
0.7%
997 2
 
0.7%
0008 2
 
0.7%
980 2
 
0.7%
991 2
 
0.7%
Other values (158) 160
52.6%
2024-05-11T03:58:47.599349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 284
19.1%
2 226
15.2%
9 223
15.0%
207
13.9%
8 132
8.9%
4 85
 
5.7%
7 74
 
5.0%
5 73
 
4.9%
1 65
 
4.4%
3 64
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1281
86.1%
Space Separator 207
 
13.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 284
22.2%
2 226
17.6%
9 223
17.4%
8 132
10.3%
4 85
 
6.6%
7 74
 
5.8%
5 73
 
5.7%
1 65
 
5.1%
3 64
 
5.0%
6 55
 
4.3%
Space Separator
ValueCountFrequency (%)
207
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1488
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 284
19.1%
2 226
15.2%
9 223
15.0%
207
13.9%
8 132
8.9%
4 85
 
5.7%
7 74
 
5.0%
5 73
 
4.9%
1 65
 
4.4%
3 64
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1488
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 284
19.1%
2 226
15.2%
9 223
15.0%
207
13.9%
8 132
8.9%
4 85
 
5.7%
7 74
 
5.0%
5 73
 
4.9%
1 65
 
4.4%
3 64
 
4.3%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct188
Distinct (%)72.9%
Missing35
Missing (%)11.9%
Infinite0
Infinite (%)0.0%
Mean42.056008
Minimum0
Maximum263.75
Zeros6
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-05-11T03:58:48.055119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile11.36
Q123.215
median31.57
Q349.875
95-th percentile105.09
Maximum263.75
Range263.75
Interquartile range (IQR)26.66

Descriptive statistics

Standard deviation33.825915
Coefficient of variation (CV)0.80430638
Kurtosis10.256512
Mean42.056008
Median Absolute Deviation (MAD)10.57
Skewness2.6630875
Sum10850.45
Variance1144.1925
MonotonicityNot monotonic
2024-05-11T03:58:48.567295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
32.0 8
 
2.7%
26.4 6
 
2.0%
0.0 6
 
2.0%
24.0 6
 
2.0%
30.0 5
 
1.7%
20.0 4
 
1.4%
26.0 4
 
1.4%
21.0 4
 
1.4%
27.0 4
 
1.4%
17.0 4
 
1.4%
Other values (178) 207
70.6%
(Missing) 35
 
11.9%
ValueCountFrequency (%)
0.0 6
2.0%
1.0 1
 
0.3%
3.3 1
 
0.3%
6.6 1
 
0.3%
7.0 1
 
0.3%
9.2 1
 
0.3%
9.79 1
 
0.3%
10.0 1
 
0.3%
11.6 1
 
0.3%
13.0 1
 
0.3%
ValueCountFrequency (%)
263.75 1
0.3%
184.72 1
0.3%
184.41 1
0.3%
175.22 1
0.3%
152.82 1
0.3%
150.3 1
0.3%
150.0 1
0.3%
138.66 1
0.3%
132.0 1
0.3%
119.63 1
0.3%

소재지우편번호
Text

Distinct70
Distinct (%)23.9%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2024-05-11T03:58:49.127161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.116041
Min length6

Characters and Unicode

Total characters1792
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 (%)6.5%

Sample

1st row142868
2nd row142809
3rd row142864
4th row142-070
5th row142872
ValueCountFrequency (%)
142804 22
 
7.5%
142100 19
 
6.5%
142805 19
 
6.5%
142872 16
 
5.5%
142070 13
 
4.4%
142821 11
 
3.8%
142877 10
 
3.4%
142874 9
 
3.1%
142876 9
 
3.1%
142812 8
 
2.7%
Other values (60) 157
53.6%
2024-05-11T03:58:50.098697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 375
20.9%
2 349
19.5%
4 340
19.0%
8 286
16.0%
0 167
9.3%
7 125
 
7.0%
6 57
 
3.2%
- 34
 
1.9%
5 27
 
1.5%
9 18
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1758
98.1%
Dash Punctuation 34
 
1.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 375
21.3%
2 349
19.9%
4 340
19.3%
8 286
16.3%
0 167
9.5%
7 125
 
7.1%
6 57
 
3.2%
5 27
 
1.5%
9 18
 
1.0%
3 14
 
0.8%
Dash Punctuation
ValueCountFrequency (%)
- 34
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1792
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 375
20.9%
2 349
19.5%
4 340
19.0%
8 286
16.0%
0 167
9.3%
7 125
 
7.0%
6 57
 
3.2%
- 34
 
1.9%
5 27
 
1.5%
9 18
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1792
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 375
20.9%
2 349
19.5%
4 340
19.0%
8 286
16.0%
0 167
9.3%
7 125
 
7.0%
6 57
 
3.2%
- 34
 
1.9%
5 27
 
1.5%
9 18
 
1.0%

지번주소
Text

Distinct283
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2024-05-11T03:58:50.774537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length43
Mean length26.327645
Min length18

Characters and Unicode

Total characters7714
Distinct characters186
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique274 ?
Unique (%)93.5%

Sample

1st row서울특별시 강북구 번동 463-40 지상1층
2nd row서울특별시 강북구 미아동 134-39번지
3rd row서울특별시 강북구 번동 415-7번지
4th row서울특별시 강북구 수유동 287 삼원빌딩
5th row서울특별시 강북구 수유동 30-25번지
ValueCountFrequency (%)
서울특별시 293
20.4%
강북구 293
20.4%
미아동 143
 
10.0%
수유동 113
 
7.9%
번동 36
 
2.5%
1층 29
 
2.0%
지상1층 16
 
1.1%
지하2층 8
 
0.6%
70-6 7
 
0.5%
롯데백화점 6
 
0.4%
Other values (418) 490
34.2%
2024-05-11T03:58:51.922328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1371
 
17.8%
1 339
 
4.4%
동 311
 
4.0%
시 304
 
3.9%
북 302
 
3.9%
강 296
 
3.8%
구 296
 
3.8%
서 294
 
3.8%
특 293
 
3.8%
별 293
 
3.8%
Other values (176) 3615
46.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4386
56.9%
Decimal Number 1567
 
20.3%
Space Separator 1371
 
17.8%
Dash Punctuation 277
 
3.6%
Close Punctuation 45
 
0.6%
Open Punctuation 45
 
0.6%
Other Punctuation 10
 
0.1%
Uppercase Letter 9
 
0.1%
Math Symbol 2
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 311
 
7.1%
시 304
 
6.9%
북 302
 
6.9%
강 296
 
6.7%
구 296
 
6.7%
서 294
 
6.7%
특 293
 
6.7%
별 293
 
6.7%
울 293
 
6.7%
번 229
 
5.2%
Other values (151) 1475
33.6%
Decimal Number
ValueCountFrequency (%)
1 339
21.6%
2 200
12.8%
3 179
11.4%
4 169
10.8%
5 135
 
8.6%
6 134
 
8.6%
0 122
 
7.8%
7 112
 
7.1%
8 98
 
6.3%
9 79
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
B 4
44.4%
S 2
22.2%
K 2
22.2%
A 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
, 7
70.0%
. 2
 
20.0%
@ 1
 
10.0%
Math Symbol
ValueCountFrequency (%)
~ 1
50.0%
> 1
50.0%
Lowercase Letter
ValueCountFrequency (%)
k 1
50.0%
s 1
50.0%
Space Separator
ValueCountFrequency (%)
1371
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 277
100.0%
Close Punctuation
ValueCountFrequency (%)
) 45
100.0%
Open Punctuation
ValueCountFrequency (%)
( 45
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4386
56.9%
Common 3317
43.0%
Latin 11
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 311
 
7.1%
시 304
 
6.9%
북 302
 
6.9%
강 296
 
6.7%
구 296
 
6.7%
서 294
 
6.7%
특 293
 
6.7%
별 293
 
6.7%
울 293
 
6.7%
번 229
 
5.2%
Other values (151) 1475
33.6%
Common
ValueCountFrequency (%)
1371
41.3%
1 339
 
10.2%
- 277
 
8.4%
2 200
 
6.0%
3 179
 
5.4%
4 169
 
5.1%
5 135
 
4.1%
6 134
 
4.0%
0 122
 
3.7%
7 112
 
3.4%
Other values (9) 279
 
8.4%
Latin
ValueCountFrequency (%)
B 4
36.4%
S 2
18.2%
K 2
18.2%
k 1
 
9.1%
s 1
 
9.1%
A 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4386
56.9%
ASCII 3328
43.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1371
41.2%
1 339
 
10.2%
- 277
 
8.3%
2 200
 
6.0%
3 179
 
5.4%
4 169
 
5.1%
5 135
 
4.1%
6 134
 
4.0%
0 122
 
3.7%
7 112
 
3.4%
Other values (15) 290
 
8.7%
Hangul
ValueCountFrequency (%)
동 311
 
7.1%
시 304
 
6.9%
북 302
 
6.9%
강 296
 
6.7%
구 296
 
6.7%
서 294
 
6.7%
특 293
 
6.7%
별 293
 
6.7%
울 293
 
6.7%
번 229
 
5.2%
Other values (151) 1475
33.6%

도로명주소
Text

MISSING 

Distinct193
Distinct (%)97.0%
Missing94
Missing (%)32.1%
Memory size2.4 KiB
2024-05-11T03:58:52.855614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length46
Mean length31.492462
Min length22

Characters and Unicode

Total characters6267
Distinct characters170
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

Unique189 ?
Unique (%)95.0%

Sample

1st row서울특별시 강북구 도봉로 382 (번동,지상1층)
2nd row서울특별시 강북구 오패산로 412 (번동)
3rd row서울특별시 강북구 삼양로123길 1, 삼원빌딩 1층 (수유동)
4th row서울특별시 강북구 노해로 55, 1층 (수유동)
5th row서울특별시 강북구 삼양로 621 (우이동)
ValueCountFrequency (%)
서울특별시 199
 
16.2%
강북구 199
 
16.2%
1층 73
 
5.9%
미아동 69
 
5.6%
수유동 65
 
5.3%
도봉로 38
 
3.1%
번동 21
 
1.7%
삼양로 15
 
1.2%
솔샘로 14
 
1.1%
62 11
 
0.9%
Other values (323) 523
42.6%
2024-05-11T03:58:54.394021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1028
 
16.4%
1 306
 
4.9%
) 216
 
3.4%
( 216
 
3.4%
동 214
 
3.4%
로 209
 
3.3%
북 206
 
3.3%
시 203
 
3.2%
강 202
 
3.2%
구 202
 
3.2%
Other values (160) 3265
52.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3599
57.4%
Space Separator 1028
 
16.4%
Decimal Number 997
 
15.9%
Close Punctuation 216
 
3.4%
Open Punctuation 216
 
3.4%
Other Punctuation 181
 
2.9%
Dash Punctuation 22
 
0.4%
Uppercase Letter 7
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 214
 
5.9%
로 209
 
5.8%
북 206
 
5.7%
시 203
 
5.6%
강 202
 
5.6%
구 202
 
5.6%
서 200
 
5.6%
울 199
 
5.5%
특 199
 
5.5%
별 199
 
5.5%
Other values (139) 1566
43.5%
Decimal Number
ValueCountFrequency (%)
1 306
30.7%
2 141
14.1%
3 106
 
10.6%
4 78
 
7.8%
0 76
 
7.6%
7 74
 
7.4%
6 62
 
6.2%
8 56
 
5.6%
5 49
 
4.9%
9 49
 
4.9%
Uppercase Letter
ValueCountFrequency (%)
B 4
57.1%
P 1
 
14.3%
K 1
 
14.3%
S 1
 
14.3%
Other Punctuation
ValueCountFrequency (%)
, 177
97.8%
. 4
 
2.2%
Space Separator
ValueCountFrequency (%)
1028
100.0%
Close Punctuation
ValueCountFrequency (%)
) 216
100.0%
Open Punctuation
ValueCountFrequency (%)
( 216
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%
Math Symbol
ValueCountFrequency (%)
> 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3599
57.4%
Common 2661
42.5%
Latin 7
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 214
 
5.9%
로 209
 
5.8%
북 206
 
5.7%
시 203
 
5.6%
강 202
 
5.6%
구 202
 
5.6%
서 200
 
5.6%
울 199
 
5.5%
특 199
 
5.5%
별 199
 
5.5%
Other values (139) 1566
43.5%
Common
ValueCountFrequency (%)
1028
38.6%
1 306
 
11.5%
) 216
 
8.1%
( 216
 
8.1%
, 177
 
6.7%
2 141
 
5.3%
3 106
 
4.0%
4 78
 
2.9%
0 76
 
2.9%
7 74
 
2.8%
Other values (7) 243
 
9.1%
Latin
ValueCountFrequency (%)
B 4
57.1%
P 1
 
14.3%
K 1
 
14.3%
S 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3599
57.4%
ASCII 2668
42.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1028
38.5%
1 306
 
11.5%
) 216
 
8.1%
( 216
 
8.1%
, 177
 
6.6%
2 141
 
5.3%
3 106
 
4.0%
4 78
 
2.9%
0 76
 
2.8%
7 74
 
2.8%
Other values (11) 250
 
9.4%
Hangul
ValueCountFrequency (%)
동 214
 
5.9%
로 209
 
5.8%
북 206
 
5.7%
시 203
 
5.6%
강 202
 
5.6%
구 202
 
5.6%
서 200
 
5.6%
울 199
 
5.5%
특 199
 
5.5%
별 199
 
5.5%
Other values (139) 1566
43.5%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct90
Distinct (%)45.5%
Missing95
Missing (%)32.4%
Infinite0
Infinite (%)0.0%
Mean1126.1768
Minimum1002
Maximum1234
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-05-11T03:58:55.019382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1002
5-th percentile1030
Q11065.25
median1118
Q31194
95-th percentile1224
Maximum1234
Range232
Interquartile range (IQR)128.75

Descriptive statistics

Standard deviation68.76351
Coefficient of variation (CV)0.061059251
Kurtosis-1.4407409
Mean1126.1768
Median Absolute Deviation (MAD)64
Skewness0.047873217
Sum222983
Variance4728.4204
MonotonicityNot monotonic
2024-05-11T03:58:55.565408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1215 12
 
4.1%
1062 6
 
2.0%
1170 6
 
2.0%
1077 5
 
1.7%
1211 5
 
1.7%
1071 5
 
1.7%
1194 5
 
1.7%
1076 4
 
1.4%
1135 4
 
1.4%
1078 4
 
1.4%
Other values (80) 142
48.5%
(Missing) 95
32.4%
ValueCountFrequency (%)
1002 1
 
0.3%
1005 1
 
0.3%
1011 3
1.0%
1014 1
 
0.3%
1015 1
 
0.3%
1026 2
0.7%
1030 3
1.0%
1031 2
0.7%
1034 1
 
0.3%
1035 1
 
0.3%
ValueCountFrequency (%)
1234 2
 
0.7%
1233 3
 
1.0%
1230 2
 
0.7%
1229 1
 
0.3%
1226 1
 
0.3%
1224 2
 
0.7%
1222 2
 
0.7%
1219 3
 
1.0%
1215 12
4.1%
1213 1
 
0.3%

사업장명
Text

Distinct261
Distinct (%)89.1%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2024-05-11T03:58:56.491131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length20
Mean length6.996587
Min length2

Characters and Unicode

Total characters2050
Distinct characters334
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

Unique238 ?
Unique (%)81.2%

Sample

1st row파리바게트번동점
2nd row쉐휘가로 과자점
3rd row뚜레쥬르(강북경찰서점)
4th row에덴 베이커리
5th row베이커리브로뜨
ValueCountFrequency (%)
뚜레쥬르 10
 
2.7%
파리바게뜨 9
 
2.5%
베이커리 6
 
1.6%
크라운베이커리 6
 
1.6%
빵굽는마을 6
 
1.6%
파리바게트 4
 
1.1%
빵집 3
 
0.8%
핫브레드 3
 
0.8%
카페 3
 
0.8%
브레드칸 3
 
0.8%
Other values (285) 314
85.6%
2024-05-11T03:58:58.054817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 116
 
5.7%
이 100
 
4.9%
점 76
 
3.7%
74
 
3.6%
베 62
 
3.0%
빵 61
 
3.0%
커 57
 
2.8%
레 37
 
1.8%
미 33
 
1.6%
스 32
 
1.6%
Other values (324) 1402
68.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1792
87.4%
Space Separator 74
 
3.6%
Uppercase Letter 65
 
3.2%
Lowercase Letter 48
 
2.3%
Open Punctuation 21
 
1.0%
Close Punctuation 21
 
1.0%
Decimal Number 19
 
0.9%
Other Punctuation 10
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 116
 
6.5%
이 100
 
5.6%
점 76
 
4.2%
베 62
 
3.5%
빵 61
 
3.4%
커 57
 
3.2%
레 37
 
2.1%
미 33
 
1.8%
스 32
 
1.8%
아 31
 
1.7%
Other values (275) 1187
66.2%
Uppercase Letter
ValueCountFrequency (%)
K 8
12.3%
A 7
10.8%
S 7
10.8%
B 7
10.8%
R 6
9.2%
N 5
 
7.7%
E 3
 
4.6%
L 3
 
4.6%
C 3
 
4.6%
O 2
 
3.1%
Other values (10) 14
21.5%
Lowercase Letter
ValueCountFrequency (%)
e 9
18.8%
o 7
14.6%
l 4
8.3%
n 4
8.3%
a 3
 
6.2%
i 3
 
6.2%
t 3
 
6.2%
r 3
 
6.2%
s 3
 
6.2%
g 2
 
4.2%
Other values (6) 7
14.6%
Decimal Number
ValueCountFrequency (%)
2 7
36.8%
1 5
26.3%
9 2
 
10.5%
4 2
 
10.5%
5 1
 
5.3%
6 1
 
5.3%
3 1
 
5.3%
Other Punctuation
ValueCountFrequency (%)
? 6
60.0%
. 2
 
20.0%
' 2
 
20.0%
Space Separator
ValueCountFrequency (%)
74
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1792
87.4%
Common 145
 
7.1%
Latin 113
 
5.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 116
 
6.5%
이 100
 
5.6%
점 76
 
4.2%
베 62
 
3.5%
빵 61
 
3.4%
커 57
 
3.2%
레 37
 
2.1%
미 33
 
1.8%
스 32
 
1.8%
아 31
 
1.7%
Other values (275) 1187
66.2%
Latin
ValueCountFrequency (%)
e 9
 
8.0%
K 8
 
7.1%
o 7
 
6.2%
A 7
 
6.2%
S 7
 
6.2%
B 7
 
6.2%
R 6
 
5.3%
N 5
 
4.4%
l 4
 
3.5%
n 4
 
3.5%
Other values (26) 49
43.4%
Common
ValueCountFrequency (%)
74
51.0%
( 21
 
14.5%
) 21
 
14.5%
2 7
 
4.8%
? 6
 
4.1%
1 5
 
3.4%
9 2
 
1.4%
. 2
 
1.4%
4 2
 
1.4%
' 2
 
1.4%
Other values (3) 3
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1792
87.4%
ASCII 258
 
12.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 116
 
6.5%
이 100
 
5.6%
점 76
 
4.2%
베 62
 
3.5%
빵 61
 
3.4%
커 57
 
3.2%
레 37
 
2.1%
미 33
 
1.8%
스 32
 
1.8%
아 31
 
1.7%
Other values (275) 1187
66.2%
ASCII
ValueCountFrequency (%)
74
28.7%
( 21
 
8.1%
) 21
 
8.1%
e 9
 
3.5%
K 8
 
3.1%
2 7
 
2.7%
o 7
 
2.7%
A 7
 
2.7%
S 7
 
2.7%
B 7
 
2.7%
Other values (39) 90
34.9%

최종수정일자
Date

Distinct275
Distinct (%)93.9%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
Minimum2000-02-23 00:00:00
Maximum2024-04-25 17:00:26
2024-05-11T03:58:58.491870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:58:59.194456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
I
191 
U
102 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 191
65.2%
U 102
34.8%

Length

2024-05-11T03:58:59.864474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:59:00.154693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 191
65.2%
u 102
34.8%

데이터갱신일자
Date

Distinct102
Distinct (%)34.8%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 23:04:00
2024-05-11T03:59:00.510812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:59:01.021398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
제과점영업
293 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제과점영업 293
100.0%

Length

2024-05-11T03:59:01.495389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:59:01.955376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제과점영업 293
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct231
Distinct (%)79.9%
Missing4
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean202049.68
Minimum200626.32
Maximum204083.18
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-05-11T03:59:02.346205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum200626.32
5-th percentile201059.87
Q1201602.58
median202066.88
Q3202475.5
95-th percentile202988.04
Maximum204083.18
Range3456.8563
Interquartile range (IQR)872.91783

Descriptive statistics

Standard deviation618.39059
Coefficient of variation (CV)0.0030605868
Kurtosis0.48021843
Mean202049.68
Median Absolute Deviation (MAD)441.24341
Skewness0.39347123
Sum58392357
Variance382406.92
MonotonicityNot monotonic
2024-05-11T03:59:02.972326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
202625.646264572 13
 
4.4%
201045.611312321 4
 
1.4%
202066.875485264 4
 
1.4%
201589.777957863 4
 
1.4%
201853.408864503 4
 
1.4%
201812.904685238 3
 
1.0%
201956.180985499 3
 
1.0%
201059.873232343 3
 
1.0%
202178.772315814 3
 
1.0%
201566.145877343 2
 
0.7%
Other values (221) 246
84.0%
(Missing) 4
 
1.4%
ValueCountFrequency (%)
200626.320844864 1
 
0.3%
200804.005134656 1
 
0.3%
200862.154522935 1
 
0.3%
200867.659414886 1
 
0.3%
200876.152543999 1
 
0.3%
200880.479051084 1
 
0.3%
200902.161113986 2
0.7%
200986.860505615 1
 
0.3%
201045.611312321 4
1.4%
201046.377443927 1
 
0.3%
ValueCountFrequency (%)
204083.177112537 2
0.7%
203932.991517795 1
0.3%
203784.358132827 2
0.7%
203589.199617419 1
0.3%
203510.105578062 1
0.3%
203480.440498484 1
0.3%
203452.54250506 1
0.3%
203350.316168209 1
0.3%
203311.703852798 1
0.3%
203083.468974539 2
0.7%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct231
Distinct (%)79.9%
Missing4
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean458569.17
Minimum456579.08
Maximum462238.04
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-05-11T03:59:03.422886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum456579.08
5-th percentile456714.98
Q1457441.24
median458590.91
Q3459736.04
95-th percentile460391.95
Maximum462238.04
Range5658.9544
Interquartile range (IQR)2294.7968

Descriptive statistics

Standard deviation1266.4662
Coefficient of variation (CV)0.0027617779
Kurtosis-1.1435414
Mean458569.17
Median Absolute Deviation (MAD)1149.6637
Skewness0.070509457
Sum1.3252649 × 108
Variance1603936.6
MonotonicityNot monotonic
2024-05-11T03:59:03.912475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
456875.973976242 13
 
4.4%
457292.961457264 4
 
1.4%
459769.643758386 4
 
1.4%
457545.100871485 4
 
1.4%
459819.8227051 4
 
1.4%
459775.992830125 3
 
1.0%
458714.365820521 3
 
1.0%
457514.212737818 3
 
1.0%
459687.04992284 3
 
1.0%
458078.684280775 2
 
0.7%
Other values (221) 246
84.0%
(Missing) 4
 
1.4%
ValueCountFrequency (%)
456579.082459363 1
0.3%
456633.896077108 1
0.3%
456666.40708658 1
0.3%
456677.29708398 1
0.3%
456682.757626174 1
0.3%
456683.469621481 2
0.7%
456688.044422115 1
0.3%
456688.179891088 1
0.3%
456692.207136967 1
0.3%
456700.896298569 1
0.3%
ValueCountFrequency (%)
462238.036827392 1
0.3%
461763.87068998 1
0.3%
460853.681103507 1
0.3%
460677.658068686 1
0.3%
460664.417890535 1
0.3%
460606.446134024 1
0.3%
460576.260101332 1
0.3%
460532.414582678 1
0.3%
460529.271915193 1
0.3%
460516.57829091 1
0.3%

위생업태명
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
제과점영업
243 
<NA>
50 

Length

Max length5
Median length5
Mean length4.8293515
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제과점영업 243
82.9%
<NA> 50
 
17.1%

Length

2024-05-11T03:59:04.369816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:59:04.740657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제과점영업 243
82.9%
na 50
 
17.1%

남성종사자수
Categorical

Distinct5
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
185 
0
83 
1
 
18
2
 
6
4
 
1

Length

Max length4
Median length4
Mean length2.894198
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st row2
2nd row2
3rd row1
4th row<NA>
5th row1

Common Values

ValueCountFrequency (%)
<NA> 185
63.1%
0 83
28.3%
1 18
 
6.1%
2 6
 
2.0%
4 1
 
0.3%

Length

2024-05-11T03:59:05.497596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:59:05.943602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 185
63.1%
0 83
28.3%
1 18
 
6.1%
2 6
 
2.0%
4 1
 
0.3%

여성종사자수
Categorical

Distinct4
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
185 
0
81 
1
19 
2
 
8

Length

Max length4
Median length4
Mean length2.894198
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row1
4th row<NA>
5th row1

Common Values

ValueCountFrequency (%)
<NA> 185
63.1%
0 81
27.6%
1 19
 
6.5%
2 8
 
2.7%

Length

2024-05-11T03:59:06.474557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:59:06.952656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 185
63.1%
0 81
27.6%
1 19
 
6.5%
2 8
 
2.7%

영업장주변구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
225 
주택가주변
47 
기타
 
13
아파트지역
 
5
유흥업소밀집지역
 
2

Length

Max length8
Median length4
Mean length4.1262799
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 225
76.8%
주택가주변 47
 
16.0%
기타 13
 
4.4%
아파트지역 5
 
1.7%
유흥업소밀집지역 2
 
0.7%
결혼예식장주변 1
 
0.3%

Length

2024-05-11T03:59:07.362690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:59:07.773499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 225
76.8%
주택가주변 47
 
16.0%
기타 13
 
4.4%
아파트지역 5
 
1.7%
유흥업소밀집지역 2
 
0.7%
결혼예식장주변 1
 
0.3%

등급구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
234 
자율
30 
기타
 
22
지도
 
6
갑
 
1

Length

Max length4
Median length4
Mean length3.5938567
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 234
79.9%
자율 30
 
10.2%
기타 22
 
7.5%
지도 6
 
2.0%
갑 1
 
0.3%

Length

2024-05-11T03:59:08.235092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:59:08.575245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 234
79.9%
자율 30
 
10.2%
기타 22
 
7.5%
지도 6
 
2.0%
갑 1
 
0.3%

급수시설구분명
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
215 
상수도전용
78 

Length

Max length5
Median length4
Mean length4.2662116
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 215
73.4%
상수도전용 78
 
26.6%

Length

2024-05-11T03:59:09.213914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:59:09.868616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 215
73.4%
상수도전용 78
 
26.6%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
281 
0
 
12

Length

Max length4
Median length4
Mean length3.8771331
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> 281
95.9%
0 12
 
4.1%

Length

2024-05-11T03:59:10.211193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:59:10.531368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 281
95.9%
0 12
 
4.1%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
281 
0
 
12

Length

Max length4
Median length4
Mean length3.8771331
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> 281
95.9%
0 12
 
4.1%

Length

2024-05-11T03:59:10.856708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:59:11.250921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 281
95.9%
0 12
 
4.1%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
281 
0
 
12

Length

Max length4
Median length4
Mean length3.8771331
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> 281
95.9%
0 12
 
4.1%

Length

2024-05-11T03:59:11.898454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:59:12.487654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 281
95.9%
0 12
 
4.1%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
281 
0
 
12

Length

Max length4
Median length4
Mean length3.8771331
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> 281
95.9%
0 12
 
4.1%

Length

2024-05-11T03:59:12.809587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:59:13.107458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 281
95.9%
0 12
 
4.1%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
281 
0
 
12

Length

Max length4
Median length4
Mean length3.8771331
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> 281
95.9%
0 12
 
4.1%

Length

2024-05-11T03:59:13.427212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:59:13.780616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 281
95.9%
0 12
 
4.1%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing293
Missing (%)100.0%
Memory size2.7 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
281 
0
 
12

Length

Max length4
Median length4
Mean length3.8771331
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> 281
95.9%
0 12
 
4.1%

Length

2024-05-11T03:59:14.424721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:59:15.051694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 281
95.9%
0 12
 
4.1%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
281 
0
 
12

Length

Max length4
Median length4
Mean length3.8771331
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> 281
95.9%
0 12
 
4.1%

Length

2024-05-11T03:59:15.982219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:59:16.819800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 281
95.9%
0 12
 
4.1%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.8%
Missing50
Missing (%)17.1%
Memory size718.0 B
False
242 
True
 
1
(Missing)
50 
ValueCountFrequency (%)
False 242
82.6%
True 1
 
0.3%
(Missing) 50
 
17.1%
2024-05-11T03:59:17.366463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct162
Distinct (%)66.7%
Missing50
Missing (%)17.1%
Infinite0
Infinite (%)0.0%
Mean36.924733
Minimum0
Maximum184.72
Zeros35
Zeros (%)11.9%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-05-11T03:59:18.001542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q119.875
median29.7
Q347.25
95-th percentile96.099
Maximum184.72
Range184.72
Interquartile range (IQR)27.375

Descriptive statistics

Standard deviation32.839574
Coefficient of variation (CV)0.88936525
Kurtosis5.203211
Mean36.924733
Median Absolute Deviation (MAD)12.7
Skewness1.9343794
Sum8972.71
Variance1078.4376
MonotonicityNot monotonic
2024-05-11T03:59:18.575049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 35
 
11.9%
32.0 7
 
2.4%
26.4 5
 
1.7%
30.0 5
 
1.7%
20.0 4
 
1.4%
27.0 4
 
1.4%
23.1 3
 
1.0%
24.0 3
 
1.0%
31.0 3
 
1.0%
66.0 3
 
1.0%
Other values (152) 171
58.4%
(Missing) 50
 
17.1%
ValueCountFrequency (%)
0.0 35
11.9%
1.0 1
 
0.3%
3.3 1
 
0.3%
6.6 1
 
0.3%
7.0 1
 
0.3%
9.2 1
 
0.3%
9.79 1
 
0.3%
11.6 1
 
0.3%
13.2 1
 
0.3%
14.0 2
 
0.7%
ValueCountFrequency (%)
184.72 1
0.3%
184.41 1
0.3%
175.22 1
0.3%
152.82 1
0.3%
150.3 1
0.3%
150.0 1
0.3%
138.66 1
0.3%
132.0 1
0.3%
105.6 2
0.7%
105.0 1
0.3%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing293
Missing (%)100.0%
Memory size2.7 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing293
Missing (%)100.0%
Memory size2.7 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing293
Missing (%)100.0%
Memory size2.7 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030800003080000-121-1969-0195219691212<NA>1영업/정상1영업<NA><NA><NA><NA>020994220774.55142868서울특별시 강북구 번동 463-40 지상1층서울특별시 강북구 도봉로 382 (번동,지상1층)1056파리바게트번동점2021-04-08 15:57:34U2021-04-10 02:40:00.0제과점영업202486.96005459824.448656제과점영업22주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N74.55<NA><NA><NA>
130800003080000-121-1971-0196019711111<NA>3폐업2폐업20070713<NA><NA><NA>0209893003<NA>142809서울특별시 강북구 미아동 134-39번지<NA><NA>쉐휘가로 과자점2003-03-22 00:00:00I2018-08-31 23:59:59.0제과점영업202469.796754457569.49783제과점영업22주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
230800003080000-121-1978-0194919780214<NA>3폐업2폐업20130423<NA><NA><NA>02 993051921.81142864서울특별시 강북구 번동 415-7번지서울특별시 강북구 오패산로 412 (번동)1064뚜레쥬르(강북경찰서점)2009-01-19 16:49:25I2018-08-31 23:59:59.0제과점영업202279.559016459459.587902제과점영업11주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N21.81<NA><NA><NA>
330800003080000-121-1979-019321979-06-12<NA>1영업/정상1영업<NA><NA><NA><NA>02 993617048.61142-070서울특별시 강북구 수유동 287 삼원빌딩서울특별시 강북구 삼양로123길 1, 삼원빌딩 1층 (수유동)1030에덴 베이커리2024-03-28 13:23:23U2023-12-02 21:00:00.0제과점영업201293.24097460263.699624<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
430800003080000-121-1981-0193919810326<NA>3폐업2폐업20180426<NA><NA><NA>020902271026.4142872서울특별시 강북구 수유동 30-25번지서울특별시 강북구 노해로 55, 1층 (수유동)1077베이커리브로뜨2018-04-26 10:33:38I2018-08-31 23:59:59.0제과점영업201898.852413459799.37584제과점영업11주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N26.4<NA><NA><NA>
530800003080000-121-1982-0198719820727<NA>3폐업2폐업20111017<NA><NA><NA>02985108747.0142805서울특별시 강북구 미아동 62-9번지<NA><NA>케?하우스몽마2010-07-22 14:52:57I2018-08-31 23:59:59.0제과점영업202554.757267456920.088016제과점영업11주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N47.0<NA><NA><NA>
630800003080000-121-1983-0049119830210<NA>3폐업2폐업20100519<NA><NA><NA>02 9045280<NA>142879서울특별시 강북구 수유동 253-1번지<NA><NA>샤모니빵2001-10-19 00:00:00I2018-08-31 23:59:59.0제과점영업<NA><NA>제과점영업11주택가주변지도<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
730800003080000-121-1983-0188719831227<NA>3폐업2폐업20110831<NA><NA><NA>02 980466624.0142810서울특별시 강북구 미아동 217-106번지<NA><NA>빵굽는 세상2005-12-06 00:00:00I2018-08-31 23:59:59.0제과점영업201941.61582458657.557598제과점영업11주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N24.0<NA><NA><NA>
830800003080000-121-1983-0192519830513<NA>3폐업2폐업20100830<NA><NA><NA>02 981289229.37142874서울특별시 강북구 수유동 57-81번지<NA><NA>케?하우스브랑제리2002-12-10 00:00:00I2018-08-31 23:59:59.0제과점영업201520.517541458692.382759제과점영업11주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N29.37<NA><NA><NA>
930800003080000-121-1985-0785519850703<NA>1영업/정상1영업<NA><NA><NA><NA>02 902 863048.0142892서울특별시 강북구 우이동 44-22서울특별시 강북구 삼양로 621 (우이동)1005뚜레쥬르(우이점)2021-05-11 11:23:26U2021-05-13 02:40:00.0제과점영업201125.285461763.87069제과점영업11주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N48.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
28330800003080000-121-2023-000052023-09-04<NA>3폐업2폐업2023-09-09<NA><NA><NA><NA>0.0142-070서울특별시 강북구 수유동 741 수유동 741(백년시장) 및 수유동 647-2(우이천 쌍한교) 일대<NA><NA>이경수베이커리2023-09-10 04:15:11U2022-12-08 23:02:00.0제과점영업202178.038036459981.690838<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
28430800003080000-121-2023-000062023-09-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>36.0142-864서울특별시 강북구 번동 412-13서울특별시 강북구 한천로123길 14, 1층 (번동)1066현이네빵집2023-09-07 13:39:54I2022-12-09 00:09:00.0제과점영업202680.208852459318.080782<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
28530800003080000-121-2023-000072023-10-06<NA>1영업/정상1영업<NA><NA><NA><NA><NA>27.92142-100서울특별시 강북구 미아동 813 삼성래미안트리베라1차아파트서울특별시 강북구 삼양로19길 25, 108동 지하1층 3호 (미아동, 삼성래미안트리베라1차아파트)1200렌토2023-10-06 11:42:56I2022-10-31 00:08:00.0제과점영업201760.433753456845.37383<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
28630800003080000-121-2023-000082023-10-11<NA>3폐업2폐업2023-10-14<NA><NA><NA><NA><NA>142-876서울특별시 강북구 수유동 166-30 앞 쌍한교~수유교 사이 배드민턴장서울특별시 강북구 도봉로101길 71 (수유동)1052이경수과자점2023-10-15 04:15:12U2022-10-30 23:07:00.0제과점영업202336.408198460255.770461<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
28730800003080000-121-2023-000092023-12-01<NA>1영업/정상1영업<NA><NA><NA><NA><NA>13.0142-805서울특별시 강북구 미아동 450-64 대암빌딩서울특별시 강북구 도봉로13길 58, 대암빌딩 지하1층 (미아동)1206케쿠케쿠2023-12-01 14:45:51I2022-11-02 00:03:00.0제과점영업202316.219092456978.341462<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
28830800003080000-121-2023-000102023-12-19<NA>3폐업2폐업2023-12-25<NA><NA><NA><NA>0.0142-701서울특별시 강북구 수유동 192-59 강북구청서울특별시 강북구 도봉로89길 13, 강북구청 및 한천로139길 일대 (수유동)1071까미노빵집2023-12-26 04:15:09U2022-11-01 22:08:00.0제과점영업202178.772316459687.049923<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
28930800003080000-121-2023-000112023-12-19<NA>3폐업2폐업2023-12-25<NA><NA><NA><NA>0.0142-701서울특별시 강북구 수유동 192-59 강북구청서울특별시 강북구 도봉로89길 13, 강북구청 및 한천로139길 일대 (수유동)1071봄날과자점2023-12-26 04:15:09U2022-11-01 22:08:00.0제과점영업202178.772316459687.049923<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
29030800003080000-121-2023-000122023-12-20<NA>3폐업2폐업2023-12-25<NA><NA><NA><NA>0.0142-701서울특별시 강북구 수유동 192-59 강북구청서울특별시 강북구 도봉로89길 13, 강북구청 및 한천로139길 일대 (수유동)1071카페 풀고르2023-12-26 04:15:09U2022-11-01 22:08:00.0제과점영업202178.772316459687.049923<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
29130800003080000-121-2024-000012024-03-18<NA>1영업/정상1영업<NA><NA><NA><NA><NA>24.0142-804서울특별시 강북구 미아동 75-44서울특별시 강북구 오현로6길 58, 1층 우측호 (미아동)1219케이크랩(CAKE LAB)2024-03-18 14:14:13I2023-12-02 22:00:00.0제과점영업202810.420422456841.590123<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
29230800003080000-121-2024-000022024-04-12<NA>1영업/정상1영업<NA><NA><NA><NA><NA>21.0142-879서울특별시 강북구 수유동 254-5 무너미서울특별시 강북구 노해로21길 58, 무너미 1층 좌측호 (수유동)1047민설기2024-04-12 16:39:33I2023-12-03 23:04:00.0제과점영업201706.070909460338.272783<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>