Overview

Dataset statistics

Number of variables44
Number of observations232
Missing cells2059
Missing cells (%)20.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory85.1 KiB
Average record size in memory375.6 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
Author중랑구
URLhttps://data.seoul.go.kr/dataList/OA-18383/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
남성종사자수 is highly imbalanced (71.3%)Imbalance
여성종사자수 is highly imbalanced (68.0%)Imbalance
영업장주변구분명 is highly imbalanced (75.7%)Imbalance
등급구분명 is highly imbalanced (76.0%)Imbalance
급수시설구분명 is highly imbalanced (54.8%)Imbalance
총인원 is highly imbalanced (63.8%)Imbalance
공장판매직종업원수 is highly imbalanced (57.4%)Imbalance
보증액 is highly imbalanced (67.9%)Imbalance
월세액 is highly imbalanced (69.0%)Imbalance
인허가취소일자 has 232 (100.0%) missing valuesMissing
폐업일자 has 83 (35.8%) missing valuesMissing
휴업시작일자 has 232 (100.0%) missing valuesMissing
휴업종료일자 has 232 (100.0%) missing valuesMissing
재개업일자 has 232 (100.0%) missing valuesMissing
전화번호 has 107 (46.1%) missing valuesMissing
소재지면적 has 18 (7.8%) missing valuesMissing
도로명주소 has 33 (14.2%) missing valuesMissing
도로명우편번호 has 40 (17.2%) missing valuesMissing
다중이용업소여부 has 75 (32.3%) missing valuesMissing
시설총규모 has 75 (32.3%) missing valuesMissing
전통업소지정번호 has 232 (100.0%) missing valuesMissing
전통업소주된음식 has 232 (100.0%) missing valuesMissing
홈페이지 has 232 (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 137 (59.1%) zerosZeros

Reproduction

Analysis started2024-05-18 00:57:51.594258
Analysis finished2024-05-18 00:57:53.269947
Duration1.68 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
3060000
232 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3060000
2nd row3060000
3rd row3060000
4th row3060000
5th row3060000

Common Values

ValueCountFrequency (%)
3060000 232
100.0%

Length

2024-05-18T09:57:53.457303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:57:53.708359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3060000 232
100.0%

관리번호
Text

UNIQUE 

Distinct232
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-05-18T09:57:54.101502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters5104
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

Unique232 ?
Unique (%)100.0%

Sample

1st row3060000-113-1997-00252
2nd row3060000-113-1997-00253
3rd row3060000-113-1998-00254
4th row3060000-113-1998-00255
5th row3060000-113-1998-00256
ValueCountFrequency (%)
3060000-113-1997-00252 1
 
0.4%
3060000-113-2020-00002 1
 
0.4%
3060000-113-2021-00006 1
 
0.4%
3060000-113-2019-00008 1
 
0.4%
3060000-113-2019-00009 1
 
0.4%
3060000-113-2019-00010 1
 
0.4%
3060000-113-2019-00011 1
 
0.4%
3060000-113-2019-00012 1
 
0.4%
3060000-113-2019-00013 1
 
0.4%
3060000-113-2019-00014 1
 
0.4%
Other values (222) 222
95.7%
2024-05-18T09:57:54.941732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2293
44.9%
1 703
 
13.8%
- 696
 
13.6%
3 543
 
10.6%
2 361
 
7.1%
6 270
 
5.3%
9 58
 
1.1%
5 57
 
1.1%
4 53
 
1.0%
8 39
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4408
86.4%
Dash Punctuation 696
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2293
52.0%
1 703
 
15.9%
3 543
 
12.3%
2 361
 
8.2%
6 270
 
6.1%
9 58
 
1.3%
5 57
 
1.3%
4 53
 
1.2%
8 39
 
0.9%
7 31
 
0.7%
Dash Punctuation
ValueCountFrequency (%)
- 696
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5104
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2293
44.9%
1 703
 
13.8%
- 696
 
13.6%
3 543
 
10.6%
2 361
 
7.1%
6 270
 
5.3%
9 58
 
1.1%
5 57
 
1.1%
4 53
 
1.0%
8 39
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5104
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2293
44.9%
1 703
 
13.8%
- 696
 
13.6%
3 543
 
10.6%
2 361
 
7.1%
6 270
 
5.3%
9 58
 
1.1%
5 57
 
1.1%
4 53
 
1.0%
8 39
 
0.8%
Distinct226
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
Minimum1997-07-04 00:00:00
Maximum2024-04-19 00:00:00
2024-05-18T09:57:55.369727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:57:55.761275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing232
Missing (%)100.0%
Memory size2.2 KiB
Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
3
149 
1
83 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 149
64.2%
1 83
35.8%

Length

2024-05-18T09:57:56.151279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:57:56.432095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 149
64.2%
1 83
35.8%

영업상태명
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
폐업
149 
영업/정상
83 

Length

Max length5
Median length2
Mean length3.0732759
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 149
64.2%
영업/정상 83
35.8%

Length

2024-05-18T09:57:56.813222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:57:57.160973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 149
64.2%
영업/정상 83
35.8%
Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2
149 
1
83 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 149
64.2%
1 83
35.8%

Length

2024-05-18T09:57:57.533043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:57:57.913976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 149
64.2%
1 83
35.8%
Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
폐업
149 
영업
83 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 149
64.2%
영업 83
35.8%

Length

2024-05-18T09:57:58.298786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:57:58.687515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 149
64.2%
영업 83
35.8%

폐업일자
Date

MISSING 

Distinct135
Distinct (%)90.6%
Missing83
Missing (%)35.8%
Memory size1.9 KiB
Minimum1997-10-15 00:00:00
Maximum2024-04-22 00:00:00
2024-05-18T09:57:59.065223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:57:59.517566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing232
Missing (%)100.0%
Memory size2.2 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing232
Missing (%)100.0%
Memory size2.2 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing232
Missing (%)100.0%
Memory size2.2 KiB

전화번호
Text

MISSING 

Distinct123
Distinct (%)98.4%
Missing107
Missing (%)46.1%
Memory size1.9 KiB
2024-05-18T09:58:00.236601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.672
Min length8

Characters and Unicode

Total characters1334
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

Unique121 ?
Unique (%)96.8%

Sample

1st row02 4326207
2nd row02 4377171
3rd row0234219677
4th row02 4348932
5th row02 2082000
ValueCountFrequency (%)
02 71
30.6%
070 6
 
2.6%
0222090588 2
 
0.9%
438 2
 
0.9%
16006568 2
 
0.9%
491 2
 
0.9%
432 2
 
0.9%
436 2
 
0.9%
433 2
 
0.9%
4364237 1
 
0.4%
Other values (140) 140
60.3%
2024-05-18T09:58:01.544224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 234
17.5%
2 225
16.9%
150
11.2%
4 119
8.9%
3 107
8.0%
9 96
7.2%
7 90
 
6.7%
6 84
 
6.3%
1 80
 
6.0%
8 77
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1184
88.8%
Space Separator 150
 
11.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 234
19.8%
2 225
19.0%
4 119
10.1%
3 107
9.0%
9 96
8.1%
7 90
 
7.6%
6 84
 
7.1%
1 80
 
6.8%
8 77
 
6.5%
5 72
 
6.1%
Space Separator
ValueCountFrequency (%)
150
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1334
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 234
17.5%
2 225
16.9%
150
11.2%
4 119
8.9%
3 107
8.0%
9 96
7.2%
7 90
 
6.7%
6 84
 
6.3%
1 80
 
6.0%
8 77
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1334
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 234
17.5%
2 225
16.9%
150
11.2%
4 119
8.9%
3 107
8.0%
9 96
7.2%
7 90
 
6.7%
6 84
 
6.3%
1 80
 
6.0%
8 77
 
5.8%

소재지면적
Text

MISSING 

Distinct150
Distinct (%)70.1%
Missing18
Missing (%)7.8%
Memory size1.9 KiB
2024-05-18T09:58:02.365545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.9953271
Min length3

Characters and Unicode

Total characters1069
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

Unique125 ?
Unique (%)58.4%

Sample

1st row.00
2nd row337.89
3rd row.00
4th row.00
5th row198.22
ValueCountFrequency (%)
3.30 9
 
4.2%
10.00 6
 
2.8%
33.00 6
 
2.8%
30.00 6
 
2.8%
99.00 5
 
2.3%
00 5
 
2.3%
60.00 5
 
2.3%
49.50 4
 
1.9%
0.00 4
 
1.9%
20.00 4
 
1.9%
Other values (140) 160
74.8%
2024-05-18T09:58:03.751922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 299
28.0%
. 214
20.0%
3 100
 
9.4%
1 85
 
8.0%
5 74
 
6.9%
6 64
 
6.0%
9 58
 
5.4%
2 53
 
5.0%
4 43
 
4.0%
8 40
 
3.7%
Other values (2) 39
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 854
79.9%
Other Punctuation 215
 
20.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 299
35.0%
3 100
 
11.7%
1 85
 
10.0%
5 74
 
8.7%
6 64
 
7.5%
9 58
 
6.8%
2 53
 
6.2%
4 43
 
5.0%
8 40
 
4.7%
7 38
 
4.4%
Other Punctuation
ValueCountFrequency (%)
. 214
99.5%
, 1
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Common 1069
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 299
28.0%
. 214
20.0%
3 100
 
9.4%
1 85
 
8.0%
5 74
 
6.9%
6 64
 
6.0%
9 58
 
5.4%
2 53
 
5.0%
4 43
 
4.0%
8 40
 
3.7%
Other values (2) 39
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1069
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 299
28.0%
. 214
20.0%
3 100
 
9.4%
1 85
 
8.0%
5 74
 
6.9%
6 64
 
6.0%
9 58
 
5.4%
2 53
 
5.0%
4 43
 
4.0%
8 40
 
3.7%
Other values (2) 39
 
3.6%
Distinct85
Distinct (%)36.6%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-05-18T09:58:04.436314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.2241379
Min length6

Characters and Unicode

Total characters1444
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

Unique32 ?
Unique (%)13.8%

Sample

1st row131802
2nd row131857
3rd row131830
4th row131802
5th row131877
ValueCountFrequency (%)
131802 10
 
4.3%
131859 9
 
3.9%
131-865 8
 
3.4%
131852 8
 
3.4%
131881 7
 
3.0%
131-859 6
 
2.6%
131853 6
 
2.6%
131877 6
 
2.6%
131861 6
 
2.6%
131809 6
 
2.6%
Other values (75) 160
69.0%
2024-05-18T09:58:05.548597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 525
36.4%
3 268
18.6%
8 261
18.1%
5 69
 
4.8%
2 61
 
4.2%
0 60
 
4.2%
7 54
 
3.7%
- 52
 
3.6%
6 52
 
3.6%
9 28
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1392
96.4%
Dash Punctuation 52
 
3.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 525
37.7%
3 268
19.3%
8 261
18.8%
5 69
 
5.0%
2 61
 
4.4%
0 60
 
4.3%
7 54
 
3.9%
6 52
 
3.7%
9 28
 
2.0%
4 14
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 52
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1444
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 525
36.4%
3 268
18.6%
8 261
18.1%
5 69
 
4.8%
2 61
 
4.2%
0 60
 
4.2%
7 54
 
3.7%
- 52
 
3.6%
6 52
 
3.6%
9 28
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1444
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 525
36.4%
3 268
18.6%
8 261
18.1%
5 69
 
4.8%
2 61
 
4.2%
0 60
 
4.2%
7 54
 
3.7%
- 52
 
3.6%
6 52
 
3.6%
9 28
 
1.9%
Distinct220
Distinct (%)94.8%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-05-18T09:58:06.289516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length35
Mean length23.844828
Min length15

Characters and Unicode

Total characters5532
Distinct characters166
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

Unique209 ?
Unique (%)90.1%

Sample

1st row서울특별시 중랑구 망우동 134-3
2nd row서울특별시 중랑구 상봉동 116-20
3rd row서울특별시 중랑구 면목동 376-6
4th row서울특별시 중랑구 망우동 134-22
5th row서울특별시 중랑구 중화동 295-21
ValueCountFrequency (%)
서울특별시 232
20.9%
중랑구 232
20.9%
면목동 63
 
5.7%
중화동 39
 
3.5%
상봉동 35
 
3.1%
망우동 34
 
3.1%
신내동 32
 
2.9%
묵동 29
 
2.6%
2층 13
 
1.2%
3층 8
 
0.7%
Other values (308) 395
35.5%
2024-05-18T09:58:07.992279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1025
18.5%
273
 
4.9%
1 246
 
4.4%
244
 
4.4%
239
 
4.3%
234
 
4.2%
233
 
4.2%
233
 
4.2%
232
 
4.2%
232
 
4.2%
Other values (156) 2341
42.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3041
55.0%
Decimal Number 1183
 
21.4%
Space Separator 1025
 
18.5%
Dash Punctuation 208
 
3.8%
Uppercase Letter 42
 
0.8%
Lowercase Letter 18
 
0.3%
Close Punctuation 7
 
0.1%
Open Punctuation 7
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
273
 
9.0%
244
 
8.0%
239
 
7.9%
234
 
7.7%
233
 
7.7%
233
 
7.7%
232
 
7.6%
232
 
7.6%
232
 
7.6%
63
 
2.1%
Other values (121) 826
27.2%
Uppercase Letter
ValueCountFrequency (%)
S 6
14.3%
E 4
9.5%
G 4
9.5%
R 4
9.5%
O 3
7.1%
T 3
7.1%
W 3
7.1%
V 3
7.1%
K 3
7.1%
B 2
 
4.8%
Other values (5) 7
16.7%
Decimal Number
ValueCountFrequency (%)
1 246
20.8%
2 176
14.9%
3 128
10.8%
0 117
9.9%
5 110
9.3%
4 109
9.2%
6 100
8.5%
7 78
 
6.6%
8 62
 
5.2%
9 57
 
4.8%
Lowercase Letter
ValueCountFrequency (%)
e 6
33.3%
r 3
16.7%
t 3
16.7%
c 3
16.7%
n 3
16.7%
Space Separator
ValueCountFrequency (%)
1025
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 208
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3041
55.0%
Common 2431
43.9%
Latin 60
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
273
 
9.0%
244
 
8.0%
239
 
7.9%
234
 
7.7%
233
 
7.7%
233
 
7.7%
232
 
7.6%
232
 
7.6%
232
 
7.6%
63
 
2.1%
Other values (121) 826
27.2%
Latin
ValueCountFrequency (%)
e 6
 
10.0%
S 6
 
10.0%
E 4
 
6.7%
G 4
 
6.7%
R 4
 
6.7%
r 3
 
5.0%
O 3
 
5.0%
T 3
 
5.0%
t 3
 
5.0%
c 3
 
5.0%
Other values (10) 21
35.0%
Common
ValueCountFrequency (%)
1025
42.2%
1 246
 
10.1%
- 208
 
8.6%
2 176
 
7.2%
3 128
 
5.3%
0 117
 
4.8%
5 110
 
4.5%
4 109
 
4.5%
6 100
 
4.1%
7 78
 
3.2%
Other values (5) 134
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3041
55.0%
ASCII 2491
45.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1025
41.1%
1 246
 
9.9%
- 208
 
8.4%
2 176
 
7.1%
3 128
 
5.1%
0 117
 
4.7%
5 110
 
4.4%
4 109
 
4.4%
6 100
 
4.0%
7 78
 
3.1%
Other values (25) 194
 
7.8%
Hangul
ValueCountFrequency (%)
273
 
9.0%
244
 
8.0%
239
 
7.9%
234
 
7.7%
233
 
7.7%
233
 
7.7%
232
 
7.6%
232
 
7.6%
232
 
7.6%
63
 
2.1%
Other values (121) 826
27.2%

도로명주소
Text

MISSING 

Distinct195
Distinct (%)98.0%
Missing33
Missing (%)14.2%
Memory size1.9 KiB
2024-05-18T09:58:09.221786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length44
Mean length33.60804
Min length22

Characters and Unicode

Total characters6688
Distinct characters192
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

Unique191 ?
Unique (%)96.0%

Sample

1st row서울특별시 중랑구 동일로140길 19-6 (중화동)
2nd row서울특별시 중랑구 봉화산로 123 (상봉동,신내테크노타운 2층)
3rd row서울특별시 중랑구 동일로 608 (면목동)
4th row서울특별시 중랑구 신내역로 111, 신내 SK V1 center 1층 127호 (신내동)
5th row서울특별시 중랑구 겸재로28길 22 (면목동)
ValueCountFrequency (%)
서울특별시 199
 
15.2%
중랑구 199
 
15.2%
면목동 55
 
4.2%
중화동 32
 
2.4%
1층 30
 
2.3%
상봉동 30
 
2.3%
망우동 28
 
2.1%
신내동 26
 
2.0%
3층 23
 
1.8%
동일로 21
 
1.6%
Other values (385) 668
51.0%
2024-05-18T09:58:10.654993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1112
 
16.6%
1 290
 
4.3%
262
 
3.9%
251
 
3.8%
, 218
 
3.3%
214
 
3.2%
205
 
3.1%
201
 
3.0%
201
 
3.0%
200
 
3.0%
Other values (182) 3534
52.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3715
55.5%
Decimal Number 1142
 
17.1%
Space Separator 1112
 
16.6%
Other Punctuation 218
 
3.3%
Close Punctuation 200
 
3.0%
Open Punctuation 200
 
3.0%
Uppercase Letter 49
 
0.7%
Dash Punctuation 34
 
0.5%
Lowercase Letter 18
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
262
 
7.1%
251
 
6.8%
214
 
5.8%
205
 
5.5%
201
 
5.4%
201
 
5.4%
200
 
5.4%
200
 
5.4%
199
 
5.4%
199
 
5.4%
Other values (147) 1583
42.6%
Uppercase Letter
ValueCountFrequency (%)
A 6
12.2%
S 6
12.2%
B 5
10.2%
G 4
8.2%
R 4
8.2%
E 4
8.2%
T 3
 
6.1%
O 3
 
6.1%
W 3
 
6.1%
K 3
 
6.1%
Other values (5) 8
16.3%
Decimal Number
ValueCountFrequency (%)
1 290
25.4%
2 155
13.6%
3 128
11.2%
0 116
 
10.2%
4 101
 
8.8%
5 86
 
7.5%
6 84
 
7.4%
7 80
 
7.0%
9 65
 
5.7%
8 37
 
3.2%
Lowercase Letter
ValueCountFrequency (%)
e 6
33.3%
n 3
16.7%
r 3
16.7%
t 3
16.7%
c 3
16.7%
Space Separator
ValueCountFrequency (%)
1112
100.0%
Other Punctuation
ValueCountFrequency (%)
, 218
100.0%
Close Punctuation
ValueCountFrequency (%)
) 200
100.0%
Open Punctuation
ValueCountFrequency (%)
( 200
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 34
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3715
55.5%
Common 2906
43.5%
Latin 67
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
262
 
7.1%
251
 
6.8%
214
 
5.8%
205
 
5.5%
201
 
5.4%
201
 
5.4%
200
 
5.4%
200
 
5.4%
199
 
5.4%
199
 
5.4%
Other values (147) 1583
42.6%
Latin
ValueCountFrequency (%)
e 6
 
9.0%
A 6
 
9.0%
S 6
 
9.0%
B 5
 
7.5%
G 4
 
6.0%
R 4
 
6.0%
E 4
 
6.0%
T 3
 
4.5%
O 3
 
4.5%
W 3
 
4.5%
Other values (10) 23
34.3%
Common
ValueCountFrequency (%)
1112
38.3%
1 290
 
10.0%
, 218
 
7.5%
) 200
 
6.9%
( 200
 
6.9%
2 155
 
5.3%
3 128
 
4.4%
0 116
 
4.0%
4 101
 
3.5%
5 86
 
3.0%
Other values (5) 300
 
10.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3715
55.5%
ASCII 2973
44.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1112
37.4%
1 290
 
9.8%
, 218
 
7.3%
) 200
 
6.7%
( 200
 
6.7%
2 155
 
5.2%
3 128
 
4.3%
0 116
 
3.9%
4 101
 
3.4%
5 86
 
2.9%
Other values (25) 367
 
12.3%
Hangul
ValueCountFrequency (%)
262
 
7.1%
251
 
6.8%
214
 
5.8%
205
 
5.5%
201
 
5.4%
201
 
5.4%
200
 
5.4%
200
 
5.4%
199
 
5.4%
199
 
5.4%
Other values (147) 1583
42.6%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct113
Distinct (%)58.9%
Missing40
Missing (%)17.2%
Infinite0
Infinite (%)0.0%
Mean2122.0521
Minimum2002
Maximum2262
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-18T09:58:11.175910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2002
5-th percentile2011
Q12055
median2122.5
Q32179
95-th percentile2245
Maximum2262
Range260
Interquartile range (IQR)124

Descriptive statistics

Standard deviation75.649421
Coefficient of variation (CV)0.035649182
Kurtosis-1.133736
Mean2122.0521
Median Absolute Deviation (MAD)64
Skewness0.06823597
Sum407434
Variance5722.835
MonotonicityNot monotonic
2024-05-18T09:58:11.681730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2154 7
 
3.0%
2176 5
 
2.2%
2013 5
 
2.2%
2071 4
 
1.7%
2057 4
 
1.7%
2122 4
 
1.7%
2076 3
 
1.3%
2103 3
 
1.3%
2010 3
 
1.3%
2153 3
 
1.3%
Other values (103) 151
65.1%
(Missing) 40
 
17.2%
ValueCountFrequency (%)
2002 1
 
0.4%
2006 2
 
0.9%
2007 3
1.3%
2010 3
1.3%
2011 2
 
0.9%
2013 5
2.2%
2014 3
1.3%
2015 3
1.3%
2017 3
1.3%
2019 1
 
0.4%
ValueCountFrequency (%)
2262 3
1.3%
2260 1
 
0.4%
2259 1
 
0.4%
2258 1
 
0.4%
2252 1
 
0.4%
2249 1
 
0.4%
2248 1
 
0.4%
2245 2
0.9%
2244 1
 
0.4%
2243 1
 
0.4%
Distinct230
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-05-18T09:58:12.386594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length16
Mean length7.1206897
Min length2

Characters and Unicode

Total characters1652
Distinct characters362
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

Unique228 ?
Unique (%)98.3%

Sample

1st row삼정종합식품
2nd row(주)고제
3rd row미조식품
4th row국일스위트
5th row보성케어프리
ValueCountFrequency (%)
주식회사 28
 
10.0%
열혈셰프 2
 
0.7%
대상(주 2
 
0.7%
대상라이프사이언스(주 2
 
0.7%
에타프 1
 
0.4%
coffee 1
 
0.4%
봉평메밀가 1
 
0.4%
주)하임자연건강 1
 
0.4%
chm 1
 
0.4%
삼정종합식품 1
 
0.4%
Other values (240) 240
85.7%
2024-05-18T09:58:14.165989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
97
 
5.9%
( 82
 
5.0%
) 82
 
5.0%
48
 
2.9%
44
 
2.7%
44
 
2.7%
43
 
2.6%
41
 
2.5%
31
 
1.9%
30
 
1.8%
Other values (352) 1110
67.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1321
80.0%
Open Punctuation 82
 
5.0%
Close Punctuation 82
 
5.0%
Uppercase Letter 71
 
4.3%
Space Separator 48
 
2.9%
Lowercase Letter 34
 
2.1%
Decimal Number 11
 
0.7%
Other Punctuation 2
 
0.1%
Connector Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
97
 
7.3%
44
 
3.3%
44
 
3.3%
43
 
3.3%
41
 
3.1%
31
 
2.3%
30
 
2.3%
24
 
1.8%
24
 
1.8%
20
 
1.5%
Other values (305) 923
69.9%
Uppercase Letter
ValueCountFrequency (%)
A 9
12.7%
F 8
11.3%
B 8
11.3%
C 6
 
8.5%
L 5
 
7.0%
U 4
 
5.6%
M 4
 
5.6%
N 4
 
5.6%
E 4
 
5.6%
P 3
 
4.2%
Other values (11) 16
22.5%
Lowercase Letter
ValueCountFrequency (%)
i 5
14.7%
e 5
14.7%
o 4
11.8%
a 3
8.8%
n 3
8.8%
r 3
8.8%
g 2
 
5.9%
v 2
 
5.9%
s 2
 
5.9%
w 1
 
2.9%
Other values (4) 4
11.8%
Decimal Number
ValueCountFrequency (%)
0 3
27.3%
5 2
18.2%
1 2
18.2%
2 1
 
9.1%
4 1
 
9.1%
6 1
 
9.1%
3 1
 
9.1%
Open Punctuation
ValueCountFrequency (%)
( 82
100.0%
Close Punctuation
ValueCountFrequency (%)
) 82
100.0%
Space Separator
ValueCountFrequency (%)
48
100.0%
Other Punctuation
ValueCountFrequency (%)
& 2
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1321
80.0%
Common 226
 
13.7%
Latin 105
 
6.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
97
 
7.3%
44
 
3.3%
44
 
3.3%
43
 
3.3%
41
 
3.1%
31
 
2.3%
30
 
2.3%
24
 
1.8%
24
 
1.8%
20
 
1.5%
Other values (305) 923
69.9%
Latin
ValueCountFrequency (%)
A 9
 
8.6%
F 8
 
7.6%
B 8
 
7.6%
C 6
 
5.7%
i 5
 
4.8%
L 5
 
4.8%
e 5
 
4.8%
U 4
 
3.8%
M 4
 
3.8%
o 4
 
3.8%
Other values (25) 47
44.8%
Common
ValueCountFrequency (%)
( 82
36.3%
) 82
36.3%
48
21.2%
0 3
 
1.3%
5 2
 
0.9%
& 2
 
0.9%
1 2
 
0.9%
_ 1
 
0.4%
2 1
 
0.4%
4 1
 
0.4%
Other values (2) 2
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1321
80.0%
ASCII 331
 
20.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
97
 
7.3%
44
 
3.3%
44
 
3.3%
43
 
3.3%
41
 
3.1%
31
 
2.3%
30
 
2.3%
24
 
1.8%
24
 
1.8%
20
 
1.5%
Other values (305) 923
69.9%
ASCII
ValueCountFrequency (%)
( 82
24.8%
) 82
24.8%
48
14.5%
A 9
 
2.7%
F 8
 
2.4%
B 8
 
2.4%
C 6
 
1.8%
i 5
 
1.5%
L 5
 
1.5%
e 5
 
1.5%
Other values (37) 73
22.1%
Distinct228
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
Minimum1999-11-23 00:00:00
Maximum2024-05-13 10:59:36
2024-05-18T09:58:14.664943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:58:15.161963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
I
154 
U
78 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 154
66.4%
U 78
33.6%

Length

2024-05-18T09:58:15.714830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:58:16.005782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 154
66.4%
u 78
33.6%
Distinct115
Distinct (%)49.6%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 23:05:00
2024-05-18T09:58:16.334143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:58:16.782752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
유통전문판매업
232 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
유통전문판매업 232
100.0%

Length

2024-05-18T09:58:17.169709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:58:17.411754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유통전문판매업 232
100.0%

좌표정보(X)
Real number (ℝ)

Distinct191
Distinct (%)83.0%
Missing2
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean207644.49
Minimum206264.85
Maximum209856.12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-18T09:58:17.710951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum206264.85
5-th percentile206509.28
Q1206953.86
median207563.62
Q3208292.21
95-th percentile209259.36
Maximum209856.12
Range3591.2642
Interquartile range (IQR)1338.3522

Descriptive statistics

Standard deviation869.01699
Coefficient of variation (CV)0.0041851193
Kurtosis-0.66725054
Mean207644.49
Median Absolute Deviation (MAD)698.22095
Skewness0.51049325
Sum47758234
Variance755190.53
MonotonicityNot monotonic
2024-05-18T09:58:18.150382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
207590.031147049 6
 
2.6%
208842.713556665 4
 
1.7%
208295.099818379 3
 
1.3%
206804.57585151 3
 
1.3%
208481.612667873 3
 
1.3%
206780.792913125 3
 
1.3%
206974.095837709 3
 
1.3%
208363.251684625 3
 
1.3%
206490.785290292 3
 
1.3%
208478.949850502 3
 
1.3%
Other values (181) 196
84.5%
ValueCountFrequency (%)
206264.85197789 1
 
0.4%
206270.96670005 1
 
0.4%
206310.371215011 1
 
0.4%
206346.045098344 1
 
0.4%
206390.408395132 1
 
0.4%
206414.354398066 1
 
0.4%
206463.443740034 2
0.9%
206490.785290292 3
1.3%
206507.070733448 1
 
0.4%
206511.982404412 1
 
0.4%
ValueCountFrequency (%)
209856.1161416 2
0.9%
209646.142554388 1
0.4%
209640.285276983 1
0.4%
209579.542671166 1
0.4%
209475.230649494 1
0.4%
209411.804210246 1
0.4%
209405.131185412 1
0.4%
209323.738296463 1
0.4%
209313.095099176 1
0.4%
209274.893741346 2
0.9%

좌표정보(Y)
Real number (ℝ)

Distinct191
Distinct (%)83.0%
Missing2
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean455050.43
Minimum452208.73
Maximum457494.21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-18T09:58:18.589357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum452208.73
5-th percentile453014.81
Q1454251.89
median455093.57
Q3455900.77
95-th percentile456995.78
Maximum457494.21
Range5285.48
Interquartile range (IQR)1648.887

Descriptive statistics

Standard deviation1164.6956
Coefficient of variation (CV)0.0025594868
Kurtosis-0.44580346
Mean455050.43
Median Absolute Deviation (MAD)814.9188
Skewness-0.086765628
Sum1.046616 × 108
Variance1356515.7
MonotonicityNot monotonic
2024-05-18T09:58:19.067598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
454599.632823069 6
 
2.6%
455205.504339797 4
 
1.7%
456014.999180519 3
 
1.3%
455570.897293619 3
 
1.3%
455496.980508789 3
 
1.3%
455900.774375242 3
 
1.3%
454601.381554597 3
 
1.3%
454187.778670298 3
 
1.3%
456373.540744485 3
 
1.3%
456167.614560351 3
 
1.3%
Other values (181) 196
84.5%
ValueCountFrequency (%)
452208.729385467 1
0.4%
452366.702644539 1
0.4%
452385.227806435 1
0.4%
452484.719722857 1
0.4%
452571.21470028 1
0.4%
452666.306495265 1
0.4%
452702.005658153 1
0.4%
452855.640657346 1
0.4%
452877.825893738 1
0.4%
452919.351420943 1
0.4%
ValueCountFrequency (%)
457494.209355194 1
0.4%
457462.766652935 1
0.4%
457315.078254949 1
0.4%
457283.215342184 2
0.9%
457183.637796144 1
0.4%
457177.021921581 1
0.4%
457113.638411288 1
0.4%
457093.793867508 1
0.4%
457086.477069066 1
0.4%
457049.254148268 1
0.4%

위생업태명
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
유통전문판매업
157 
<NA>
75 

Length

Max length7
Median length7
Mean length6.0301724
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
유통전문판매업 157
67.7%
<NA> 75
32.3%

Length

2024-05-18T09:58:19.666773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:58:20.187965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유통전문판매업 157
67.7%
na 75
32.3%

남성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
203 
0
 
18
2
 
5
1
 
4
8
 
1

Length

Max length4
Median length4
Mean length3.625
Min length1

Unique

Unique2 ?
Unique (%)0.9%

Sample

1st row2
2nd row8
3rd row2
4th row2
5th row3

Common Values

ValueCountFrequency (%)
<NA> 203
87.5%
0 18
 
7.8%
2 5
 
2.2%
1 4
 
1.7%
8 1
 
0.4%
3 1
 
0.4%

Length

2024-05-18T09:58:20.651268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:58:21.136642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 203
87.5%
0 18
 
7.8%
2 5
 
2.2%
1 4
 
1.7%
8 1
 
0.4%
3 1
 
0.4%

여성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
205 
0
 
20
1
 
5
2
 
2

Length

Max length4
Median length4
Mean length3.6508621
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row2
3rd row0
4th row1
5th row1

Common Values

ValueCountFrequency (%)
<NA> 205
88.4%
0 20
 
8.6%
1 5
 
2.2%
2 2
 
0.9%

Length

2024-05-18T09:58:21.793164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:58:22.416127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 205
88.4%
0 20
 
8.6%
1 5
 
2.2%
2 2
 
0.9%

영업장주변구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
218 
주택가주변
 
9
기타
 
5

Length

Max length5
Median length4
Mean length3.9956897
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 218
94.0%
주택가주변 9
 
3.9%
기타 5
 
2.2%

Length

2024-05-18T09:58:22.837854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:58:23.289528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 218
94.0%
주택가주변 9
 
3.9%
기타 5
 
2.2%

등급구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
218 
기타
 
10
자율
 
4

Length

Max length4
Median length4
Mean length3.8793103
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 218
94.0%
기타 10
 
4.3%
자율 4
 
1.7%

Length

2024-05-18T09:58:24.001759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:58:24.401679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 218
94.0%
기타 10
 
4.3%
자율 4
 
1.7%

급수시설구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
210 
상수도전용
22 

Length

Max length5
Median length4
Mean length4.0948276
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 210
90.5%
상수도전용 22
 
9.5%

Length

2024-05-18T09:58:24.911888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:58:25.491638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 210
90.5%
상수도전용 22
 
9.5%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
216 
0
 
16

Length

Max length4
Median length4
Mean length3.7931034
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> 216
93.1%
0 16
 
6.9%

Length

2024-05-18T09:58:25.936580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:58:26.353685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 216
93.1%
0 16
 
6.9%
Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
178 
0
54 

Length

Max length4
Median length4
Mean length3.3017241
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> 178
76.7%
0 54
 
23.3%

Length

2024-05-18T09:58:26.756360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:58:27.125598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 178
76.7%
0 54
 
23.3%
Distinct3
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
177 
0
53 
1
 
2

Length

Max length4
Median length4
Mean length3.2887931
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> 177
76.3%
0 53
 
22.8%
1 2
 
0.9%

Length

2024-05-18T09:58:27.523720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:58:27.950334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 177
76.3%
0 53
 
22.8%
1 2
 
0.9%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
177 
0
53 
2
 
1
1
 
1

Length

Max length4
Median length4
Mean length3.2887931
Min length1

Unique

Unique2 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 177
76.3%
0 53
 
22.8%
2 1
 
0.4%
1 1
 
0.4%

Length

2024-05-18T09:58:28.315745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:58:28.608056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 177
76.3%
0 53
 
22.8%
2 1
 
0.4%
1 1
 
0.4%
Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
178 
0
54 

Length

Max length4
Median length4
Mean length3.3017241
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> 178
76.7%
0 54
 
23.3%

Length

2024-05-18T09:58:29.004707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:58:29.345316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 178
76.7%
0 54
 
23.3%
Distinct3
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
105 
임대
65 
자가
62 

Length

Max length4
Median length2
Mean length2.9051724
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 105
45.3%
임대 65
28.0%
자가 62
26.7%

Length

2024-05-18T09:58:29.721302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:58:30.095926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 105
45.3%
임대 65
28.0%
자가 62
26.7%

보증액
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
209 
0
21 
5000000
 
2

Length

Max length7
Median length4
Mean length3.7543103
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> 209
90.1%
0 21
 
9.1%
5000000 2
 
0.9%

Length

2024-05-18T09:58:30.506040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:58:30.855521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 209
90.1%
0 21
 
9.1%
5000000 2
 
0.9%

월세액
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
209 
0
22 
300000
 
1

Length

Max length6
Median length4
Mean length3.7241379
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 209
90.1%
0 22
 
9.5%
300000 1
 
0.4%

Length

2024-05-18T09:58:31.198660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:58:31.510783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 209
90.1%
0 22
 
9.5%
300000 1
 
0.4%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.6%
Missing75
Missing (%)32.3%
Memory size596.0 B
False
157 
(Missing)
75 
ValueCountFrequency (%)
False 157
67.7%
(Missing) 75
32.3%
2024-05-18T09:58:31.783613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct21
Distinct (%)13.4%
Missing75
Missing (%)32.3%
Infinite0
Infinite (%)0.0%
Mean5.586051
Minimum0
Maximum95.5
Zeros137
Zeros (%)59.1%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-18T09:58:32.218384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile49.958
Maximum95.5
Range95.5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation17.477052
Coefficient of variation (CV)3.1286955
Kurtosis11.24382
Mean5.586051
Median Absolute Deviation (MAD)0
Skewness3.4140109
Sum877.01
Variance305.44735
MonotonicityNot monotonic
2024-05-18T09:58:32.677291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0.0 137
59.1%
54.6 1
 
0.4%
75.56 1
 
0.4%
95.5 1
 
0.4%
5.0 1
 
0.4%
10.0 1
 
0.4%
41.34 1
 
0.4%
23.0 1
 
0.4%
30.0 1
 
0.4%
27.23 1
 
0.4%
Other values (11) 11
 
4.7%
(Missing) 75
32.3%
ValueCountFrequency (%)
0.0 137
59.1%
4.0 1
 
0.4%
5.0 1
 
0.4%
10.0 1
 
0.4%
16.3 1
 
0.4%
23.0 1
 
0.4%
27.23 1
 
0.4%
29.16 1
 
0.4%
30.0 1
 
0.4%
33.0 1
 
0.4%
ValueCountFrequency (%)
95.5 1
0.4%
81.0 1
0.4%
76.11 1
0.4%
75.56 1
0.4%
74.54 1
0.4%
66.0 1
0.4%
54.6 1
0.4%
51.79 1
0.4%
49.5 1
0.4%
41.34 1
0.4%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing232
Missing (%)100.0%
Memory size2.2 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing232
Missing (%)100.0%
Memory size2.2 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing232
Missing (%)100.0%
Memory size2.2 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030600003060000-113-1997-0025219970704<NA>3폐업2폐업19971015<NA><NA><NA>02 4326207.00131802서울특별시 중랑구 망우동 134-3<NA><NA>삼정종합식품2001-10-04 00:00:00I2018-08-31 23:59:59.0유통전문판매업209411.80421455408.951348유통전문판매업2<NA>주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
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230600003060000-113-1998-0025419980522<NA>3폐업2폐업19990419<NA><NA><NA>0234219677.00131830서울특별시 중랑구 면목동 376-6<NA><NA>미조식품2001-10-04 00:00:00I2018-08-31 23:59:59.0유통전문판매업207078.289179452571.2147유통전문판매업20주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
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430600003060000-113-1998-0025619980722<NA>3폐업2폐업20091026<NA><NA><NA>02 2082000198.22131877서울특별시 중랑구 중화동 295-21<NA><NA>보성케어프리2005-08-01 00:00:00I2018-08-31 23:59:59.0유통전문판매업207030.026043455105.680618유통전문판매업31주택가주변기타상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
530600003060000-113-1998-0025719980804<NA>3폐업2폐업19990831<NA><NA><NA>02 2090588.00131857서울특별시 중랑구 상봉동 74-28<NA><NA>세농물산2001-10-04 00:00:00I2018-08-31 23:59:59.0유통전문판매업208301.50456455210.286867유통전문판매업11주택가주변기타상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
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830600003060000-113-1999-0036119990703<NA>3폐업2폐업20030422<NA><NA><NA>02 436423739.47131861서울특별시 중랑구 상봉동 130-157<NA><NA>산타모니카2001-06-14 00:00:00I2018-08-31 23:59:59.0유통전문판매업206657.247125454460.52017유통전문판매업21기타자율<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
930600003060000-113-1999-0039119990921<NA>3폐업2폐업20041119<NA><NA><NA>022209382527.72131834서울특별시 중랑구 면목동 527-52<NA><NA>강원식품1999-11-26 00:00:00I2018-08-31 23:59:59.0유통전문판매업208161.856579452995.183011유통전문판매업11주택가주변자율상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
22230600003060000-113-2024-000012024-01-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>30.00131-859서울특별시 중랑구 상봉동 105-45 경원리더스 홈서울특별시 중랑구 봉우재로37가길 16, 603호 (상봉동, 경원리더스 홈)2153케어플랜2024-01-02 14:45:10I2023-12-01 00:04:00.0유통전문판매업207785.051404454621.293984<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
22330600003060000-113-2024-000022024-01-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>1.00131-865서울특별시 중랑구 신내동 666 신아타운서울특별시 중랑구 봉화산로 194, 신아타운 3층 369-253호 (신내동)2076웰페이커2024-01-02 16:06:55I2023-12-01 00:04:00.0유통전문판매업208295.099818456014.999181<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
22430600003060000-113-2024-000032024-01-12<NA>1영업/정상1영업<NA><NA><NA><NA><NA>20.00131-865서울특별시 중랑구 신내동 821-2 신내 SK V1 center서울특별시 중랑구 신내역로 111, 신내 SK V1 center 616-10호 (신내동)2262백번랩(100BURN LAB)2024-01-12 16:32:54I2023-11-30 23:04:00.0유통전문판매업209856.116142456761.92113<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
22530600003060000-113-2024-000042024-02-20<NA>1영업/정상1영업<NA><NA><NA><NA><NA>54.00131-859서울특별시 중랑구 상봉동 101-19 상봉베스트원아파트서울특별시 중랑구 망우로 304, 1층 107호 (상봉동, 상봉베스트원아파트)2148주식회사 혜당인터내셔널2024-02-20 11:30:39I2023-12-01 22:02:00.0유통전문판매업207566.976888454857.881211<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
22630600003060000-113-2024-000052024-02-21<NA>1영업/정상1영업<NA><NA><NA><NA><NA>16.50131-830서울특별시 중랑구 면목동 384-19서울특별시 중랑구 답십리로77가길 6 (면목동)2245에타프2024-02-21 14:41:56I2023-12-01 22:03:00.0유통전문판매업207169.356702452385.227806<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
22730600003060000-113-2024-000062024-03-04<NA>1영업/정상1영업<NA><NA><NA><NA><NA>8.00131-873서울특별시 중랑구 신내동 661 신내대명아파트서울특별시 중랑구 봉화산로 193, 1106-805호 (신내동)2043굳드림2024-03-04 17:12:41I2023-12-03 00:06:00.0유통전문판매업208231.356512456138.417215<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
22830600003060000-113-2024-000072024-03-12<NA>1영업/정상1영업<NA><NA><NA><NA><NA>80.76131-859서울특별시 중랑구 상봉동 105-22서울특별시 중랑구 봉우재로33길 38, 4층 (상봉동)2153돼봉삼겹살2024-03-12 14:44:29I2023-12-02 23:04:00.0유통전문판매업207710.601703454639.957115<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
22930600003060000-113-2024-000082024-03-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA>20.00131-872서울특별시 중랑구 신내동 650 신내6단지신내아파트서울특별시 중랑구 신내로19길 42, 601동 504호 (신내동, 신내6단지신내아파트)2028비아012024-03-29 15:02:58I2023-12-02 21:01:00.0유통전문판매업207966.14019456995.44171<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23030600003060000-113-2024-000092024-04-16<NA>1영업/정상1영업<NA><NA><NA><NA>0704524037442.00131-880서울특별시 중랑구 중화동 316-1 가현월디움(5차)서울특별시 중랑구 중랑역로 47, 101동 303호 (중화동, 가현월디움(5차))2106바이오큐2024-04-16 15:27:58I2023-12-03 23:08:00.0유통전문판매업206699.849664455093.039902<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23130600003060000-113-2024-000102024-04-19<NA>1영업/정상1영업<NA><NA><NA><NA><NA>20.00131-865서울특별시 중랑구 신내동 817 신내 데시앙포레서울특별시 중랑구 신내역로 165, 221동 902호 (신내동, 신내 데시앙포레)2055비타민멘토2024-04-22 14:29:25U2023-12-03 22:04:00.0유통전문판매업209646.142554456996.056603<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>