Overview

Dataset statistics

Number of variables44
Number of observations343
Missing cells3387
Missing cells (%)22.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory126.4 KiB
Average record size in memory377.4 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
Author중랑구
URLhttps://data.seoul.go.kr/dataList/OA-18408/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
영업장주변구분명 is highly imbalanced (50.3%)Imbalance
등급구분명 is highly imbalanced (53.7%)Imbalance
총인원 is highly imbalanced (69.1%)Imbalance
본사종업원수 is highly imbalanced (67.9%)Imbalance
공장사무직종업원수 is highly imbalanced (67.9%)Imbalance
공장판매직종업원수 is highly imbalanced (67.9%)Imbalance
공장생산직종업원수 is highly imbalanced (67.9%)Imbalance
보증액 is highly imbalanced (67.9%)Imbalance
월세액 is highly imbalanced (67.9%)Imbalance
인허가취소일자 has 343 (100.0%) missing valuesMissing
폐업일자 has 111 (32.4%) missing valuesMissing
휴업시작일자 has 343 (100.0%) missing valuesMissing
휴업종료일자 has 343 (100.0%) missing valuesMissing
재개업일자 has 343 (100.0%) missing valuesMissing
전화번호 has 160 (46.6%) missing valuesMissing
도로명주소 has 109 (31.8%) missing valuesMissing
도로명우편번호 has 109 (31.8%) missing valuesMissing
좌표정보(X) has 10 (2.9%) missing valuesMissing
좌표정보(Y) has 10 (2.9%) missing valuesMissing
건물소유구분명 has 343 (100.0%) missing valuesMissing
다중이용업소여부 has 67 (19.5%) missing valuesMissing
시설총규모 has 67 (19.5%) missing valuesMissing
전통업소지정번호 has 343 (100.0%) missing valuesMissing
전통업소주된음식 has 343 (100.0%) missing valuesMissing
홈페이지 has 343 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물소유구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-11 08:02:20.709141
Analysis finished2024-05-11 08:02:22.899039
Duration2.19 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
3060000
343 

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 343
100.0%

Length

2024-05-11T08:02:23.194118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:02:23.556561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3060000 343
100.0%

관리번호
Text

UNIQUE 

Distinct343
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2024-05-11T08:02:24.035373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters7546
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

Unique343 ?
Unique (%)100.0%

Sample

1st row3060000-121-1972-07077
2nd row3060000-121-1978-07087
3rd row3060000-121-1979-07096
4th row3060000-121-1979-07107
5th row3060000-121-1980-06992
ValueCountFrequency (%)
3060000-121-1972-07077 1
 
0.3%
3060000-121-2013-00002 1
 
0.3%
3060000-121-2014-00003 1
 
0.3%
3060000-121-2014-00002 1
 
0.3%
3060000-121-2014-00001 1
 
0.3%
3060000-121-2013-00017 1
 
0.3%
3060000-121-2013-00016 1
 
0.3%
3060000-121-2013-00015 1
 
0.3%
3060000-121-2013-00014 1
 
0.3%
3060000-121-2013-00013 1
 
0.3%
Other values (333) 333
97.1%
2024-05-11T08:02:25.281499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3227
42.8%
1 1049
 
13.9%
- 1029
 
13.6%
2 779
 
10.3%
3 431
 
5.7%
6 424
 
5.6%
9 206
 
2.7%
8 124
 
1.6%
7 120
 
1.6%
4 93
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6517
86.4%
Dash Punctuation 1029
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3227
49.5%
1 1049
 
16.1%
2 779
 
12.0%
3 431
 
6.6%
6 424
 
6.5%
9 206
 
3.2%
8 124
 
1.9%
7 120
 
1.8%
4 93
 
1.4%
5 64
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 1029
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7546
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3227
42.8%
1 1049
 
13.9%
- 1029
 
13.6%
2 779
 
10.3%
3 431
 
5.7%
6 424
 
5.6%
9 206
 
2.7%
8 124
 
1.6%
7 120
 
1.6%
4 93
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7546
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3227
42.8%
1 1049
 
13.9%
- 1029
 
13.6%
2 779
 
10.3%
3 431
 
5.7%
6 424
 
5.6%
9 206
 
2.7%
8 124
 
1.6%
7 120
 
1.6%
4 93
 
1.2%

인허가일자
Date

Distinct332
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
Minimum1972-05-11 00:00:00
Maximum2024-04-30 00:00:00
2024-05-11T08:02:25.780019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:02:26.615963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing343
Missing (%)100.0%
Memory size3.1 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
3
232 
1
111 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 232
67.6%
1 111
32.4%

Length

2024-05-11T08:02:27.180205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:02:27.586783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 232
67.6%
1 111
32.4%

영업상태명
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
폐업
232 
영업/정상
111 

Length

Max length5
Median length2
Mean length2.9708455
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 232
67.6%
영업/정상 111
32.4%

Length

2024-05-11T08:02:27.999057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:02:28.345784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 232
67.6%
영업/정상 111
32.4%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2
232 
1
111 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 232
67.6%
1 111
32.4%

Length

2024-05-11T08:02:28.695956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:02:29.032415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 232
67.6%
1 111
32.4%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
폐업
232 
영업
111 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 232
67.6%
영업 111
32.4%

Length

2024-05-11T08:02:29.451328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:02:29.897246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 232
67.6%
영업 111
32.4%

폐업일자
Date

MISSING 

Distinct217
Distinct (%)93.5%
Missing111
Missing (%)32.4%
Memory size2.8 KiB
Minimum1999-05-20 00:00:00
Maximum2024-04-12 00:00:00
2024-05-11T08:02:30.328433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:02:30.825462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing343
Missing (%)100.0%
Memory size3.1 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing343
Missing (%)100.0%
Memory size3.1 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing343
Missing (%)100.0%
Memory size3.1 KiB

전화번호
Text

MISSING 

Distinct176
Distinct (%)96.2%
Missing160
Missing (%)46.6%
Memory size2.8 KiB
2024-05-11T08:02:31.806979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.568306
Min length8

Characters and Unicode

Total characters1934
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

Unique173 ?
Unique (%)94.5%

Sample

1st row02 4917252
2nd row02 4332661
3rd row02 4331783
4th row02 4350111
5th row02 4337037
ValueCountFrequency (%)
02 141
38.4%
070 8
 
2.2%
948 5
 
1.4%
71237600 5
 
1.4%
491 4
 
1.1%
493 4
 
1.1%
1074 3
 
0.8%
439 3
 
0.8%
02435 2
 
0.5%
979 2
 
0.5%
Other values (186) 190
51.8%
2024-05-11T08:02:33.302897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 340
17.6%
2 308
15.9%
226
11.7%
4 220
11.4%
3 206
10.7%
9 140
7.2%
7 117
 
6.0%
1 111
 
5.7%
8 94
 
4.9%
5 92
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1708
88.3%
Space Separator 226
 
11.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 340
19.9%
2 308
18.0%
4 220
12.9%
3 206
12.1%
9 140
8.2%
7 117
 
6.9%
1 111
 
6.5%
8 94
 
5.5%
5 92
 
5.4%
6 80
 
4.7%
Space Separator
ValueCountFrequency (%)
226
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1934
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 340
17.6%
2 308
15.9%
226
11.7%
4 220
11.4%
3 206
10.7%
9 140
7.2%
7 117
 
6.0%
1 111
 
5.7%
8 94
 
4.9%
5 92
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1934
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 340
17.6%
2 308
15.9%
226
11.7%
4 220
11.4%
3 206
10.7%
9 140
7.2%
7 117
 
6.0%
1 111
 
5.7%
8 94
 
4.9%
5 92
 
4.8%

소재지면적
Real number (ℝ)

Distinct285
Distinct (%)83.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43.735364
Minimum0.5
Maximum373
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-05-11T08:02:33.970297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.5
5-th percentile9.055
Q124.5
median33.63
Q353.96
95-th percentile102.74
Maximum373
Range372.5
Interquartile range (IQR)29.46

Descriptive statistics

Standard deviation35.821078
Coefficient of variation (CV)0.81904149
Kurtosis25.121624
Mean43.735364
Median Absolute Deviation (MAD)13.38
Skewness3.7768104
Sum15001.23
Variance1283.1496
MonotonicityNot monotonic
2024-05-11T08:02:34.622098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.0 9
 
2.6%
30.0 8
 
2.3%
19.8 4
 
1.2%
3.0 3
 
0.9%
50.0 3
 
0.9%
26.4 3
 
0.9%
29.08 3
 
0.9%
39.6 3
 
0.9%
6.6 3
 
0.9%
29.0 3
 
0.9%
Other values (275) 301
87.8%
ValueCountFrequency (%)
0.5 1
 
0.3%
0.77 1
 
0.3%
1.0 2
0.6%
1.4 1
 
0.3%
2.0 1
 
0.3%
3.0 3
0.9%
3.3 1
 
0.3%
4.0 1
 
0.3%
4.95 1
 
0.3%
6.6 3
0.9%
ValueCountFrequency (%)
373.0 1
0.3%
251.9 1
0.3%
219.52 1
0.3%
149.76 1
0.3%
143.5 1
0.3%
143.16 1
0.3%
141.72 1
0.3%
132.23 1
0.3%
128.21 1
0.3%
127.6 1
0.3%

소재지우편번호
Text

Distinct95
Distinct (%)27.7%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2024-05-11T08:02:35.652997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1457726
Min length6

Characters and Unicode

Total characters2108
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

Unique29 ?
Unique (%)8.5%

Sample

1st row131808
2nd row131818
3rd row131810
4th row131826
5th row131811
ValueCountFrequency (%)
131816 21
 
6.1%
131848 15
 
4.4%
131828 14
 
4.1%
131813 12
 
3.5%
131802 10
 
2.9%
131809 10
 
2.9%
131881 9
 
2.6%
131807 7
 
2.0%
131872 7
 
2.0%
131820 7
 
2.0%
Other values (85) 231
67.3%
2024-05-11T08:02:37.125612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 792
37.6%
3 391
18.5%
8 388
18.4%
2 117
 
5.6%
0 104
 
4.9%
7 76
 
3.6%
6 72
 
3.4%
5 56
 
2.7%
- 50
 
2.4%
4 37
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2058
97.6%
Dash Punctuation 50
 
2.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 792
38.5%
3 391
19.0%
8 388
18.9%
2 117
 
5.7%
0 104
 
5.1%
7 76
 
3.7%
6 72
 
3.5%
5 56
 
2.7%
4 37
 
1.8%
9 25
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 50
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2108
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 792
37.6%
3 391
18.5%
8 388
18.4%
2 117
 
5.6%
0 104
 
4.9%
7 76
 
3.6%
6 72
 
3.4%
5 56
 
2.7%
- 50
 
2.4%
4 37
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2108
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 792
37.6%
3 391
18.5%
8 388
18.4%
2 117
 
5.6%
0 104
 
4.9%
7 76
 
3.6%
6 72
 
3.4%
5 56
 
2.7%
- 50
 
2.4%
4 37
 
1.8%

지번주소
Text

Distinct316
Distinct (%)92.1%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2024-05-11T08:02:37.987645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length42
Mean length24.087464
Min length16

Characters and Unicode

Total characters8262
Distinct characters156
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

Unique294 ?
Unique (%)85.7%

Sample

1st row서울특별시 중랑구 망우동 458-1번지
2nd row서울특별시 중랑구 면목동 502-7번지
3rd row서울특별시 중랑구 망우동 563-0번지
4th row서울특별시 중랑구 면목동 371-125번지
5th row서울특별시 중랑구 면목동 17-34번지
ValueCountFrequency (%)
서울특별시 343
21.9%
중랑구 343
21.9%
면목동 131
 
8.4%
망우동 55
 
3.5%
묵동 44
 
2.8%
상봉동 39
 
2.5%
신내동 37
 
2.4%
중화동 37
 
2.4%
1층 19
 
1.2%
지상1층 12
 
0.8%
Other values (413) 505
32.3%
2024-05-11T08:02:39.425492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1482
17.9%
1 387
 
4.7%
중 382
 
4.6%
동 372
 
4.5%
시 347
 
4.2%
서 345
 
4.2%
울 345
 
4.2%
랑 345
 
4.2%
구 343
 
4.2%
별 343
 
4.2%
Other values (146) 3571
43.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4792
58.0%
Decimal Number 1656
 
20.0%
Space Separator 1482
 
17.9%
Dash Punctuation 295
 
3.6%
Uppercase Letter 20
 
0.2%
Other Punctuation 10
 
0.1%
Open Punctuation 3
 
< 0.1%
Close Punctuation 3
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
중 382
 
8.0%
동 372
 
7.8%
시 347
 
7.2%
서 345
 
7.2%
울 345
 
7.2%
랑 345
 
7.2%
구 343
 
7.2%
별 343
 
7.2%
특 343
 
7.2%
지 266
 
5.6%
Other values (122) 1361
28.4%
Decimal Number
ValueCountFrequency (%)
1 387
23.4%
2 194
11.7%
4 185
11.2%
0 180
10.9%
3 159
9.6%
6 136
 
8.2%
5 128
 
7.7%
7 124
 
7.5%
8 88
 
5.3%
9 75
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
B 6
30.0%
S 5
25.0%
C 3
15.0%
D 2
 
10.0%
A 2
 
10.0%
E 1
 
5.0%
K 1
 
5.0%
Other Punctuation
ValueCountFrequency (%)
, 9
90.0%
& 1
 
10.0%
Space Separator
ValueCountFrequency (%)
1482
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 295
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4792
58.0%
Common 3449
41.7%
Latin 21
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
중 382
 
8.0%
동 372
 
7.8%
시 347
 
7.2%
서 345
 
7.2%
울 345
 
7.2%
랑 345
 
7.2%
구 343
 
7.2%
별 343
 
7.2%
특 343
 
7.2%
지 266
 
5.6%
Other values (122) 1361
28.4%
Common
ValueCountFrequency (%)
1482
43.0%
1 387
 
11.2%
- 295
 
8.6%
2 194
 
5.6%
4 185
 
5.4%
0 180
 
5.2%
3 159
 
4.6%
6 136
 
3.9%
5 128
 
3.7%
7 124
 
3.6%
Other values (6) 179
 
5.2%
Latin
ValueCountFrequency (%)
B 6
28.6%
S 5
23.8%
C 3
14.3%
D 2
 
9.5%
A 2
 
9.5%
E 1
 
4.8%
K 1
 
4.8%
e 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4792
58.0%
ASCII 3470
42.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1482
42.7%
1 387
 
11.2%
- 295
 
8.5%
2 194
 
5.6%
4 185
 
5.3%
0 180
 
5.2%
3 159
 
4.6%
6 136
 
3.9%
5 128
 
3.7%
7 124
 
3.6%
Other values (14) 200
 
5.8%
Hangul
ValueCountFrequency (%)
중 382
 
8.0%
동 372
 
7.8%
시 347
 
7.2%
서 345
 
7.2%
울 345
 
7.2%
랑 345
 
7.2%
구 343
 
7.2%
별 343
 
7.2%
특 343
 
7.2%
지 266
 
5.6%
Other values (122) 1361
28.4%

도로명주소
Text

MISSING 

Distinct226
Distinct (%)96.6%
Missing109
Missing (%)31.8%
Memory size2.8 KiB
2024-05-11T08:02:40.633071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length49
Mean length30.858974
Min length21

Characters and Unicode

Total characters7221
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

Unique219 ?
Unique (%)93.6%

Sample

1st row서울특별시 중랑구 면목로 365 (면목동)
2nd row서울특별시 중랑구 망우로 388 (망우동)
3rd row서울특별시 중랑구 면목로 480 (상봉동)
4th row서울특별시 중랑구 봉우재로 40 (면목동)
5th row서울특별시 중랑구 양원역로 19 (망우동)
ValueCountFrequency (%)
서울특별시 234
 
16.1%
중랑구 234
 
16.1%
1층 101
 
7.0%
면목동 78
 
5.4%
망우동 38
 
2.6%
망우로 30
 
2.1%
묵동 29
 
2.0%
상봉동 28
 
1.9%
신내동 23
 
1.6%
중화동 21
 
1.4%
Other values (349) 637
43.8%
2024-05-11T08:02:42.673211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1219
 
16.9%
1 370
 
5.1%
동 287
 
4.0%
중 274
 
3.8%
랑 247
 
3.4%
시 239
 
3.3%
울 236
 
3.3%
) 236
 
3.3%
( 236
 
3.3%
서 236
 
3.3%
Other values (176) 3641
50.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4148
57.4%
Space Separator 1219
 
16.9%
Decimal Number 1125
 
15.6%
Close Punctuation 236
 
3.3%
Open Punctuation 236
 
3.3%
Other Punctuation 218
 
3.0%
Uppercase Letter 21
 
0.3%
Dash Punctuation 14
 
0.2%
Lowercase Letter 3
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 287
 
6.9%
중 274
 
6.6%
랑 247
 
6.0%
시 239
 
5.8%
울 236
 
5.7%
서 236
 
5.7%
별 234
 
5.6%
구 234
 
5.6%
특 234
 
5.6%
로 233
 
5.6%
Other values (148) 1694
40.8%
Decimal Number
ValueCountFrequency (%)
1 370
32.9%
2 129
 
11.5%
3 128
 
11.4%
0 91
 
8.1%
5 79
 
7.0%
4 78
 
6.9%
6 69
 
6.1%
8 63
 
5.6%
7 59
 
5.2%
9 59
 
5.2%
Uppercase Letter
ValueCountFrequency (%)
B 8
38.1%
S 5
23.8%
C 3
 
14.3%
D 2
 
9.5%
A 1
 
4.8%
K 1
 
4.8%
E 1
 
4.8%
Other Punctuation
ValueCountFrequency (%)
, 216
99.1%
. 1
 
0.5%
& 1
 
0.5%
Lowercase Letter
ValueCountFrequency (%)
k 1
33.3%
s 1
33.3%
e 1
33.3%
Space Separator
ValueCountFrequency (%)
1219
100.0%
Close Punctuation
ValueCountFrequency (%)
) 236
100.0%
Open Punctuation
ValueCountFrequency (%)
( 236
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4148
57.4%
Common 3049
42.2%
Latin 24
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 287
 
6.9%
중 274
 
6.6%
랑 247
 
6.0%
시 239
 
5.8%
울 236
 
5.7%
서 236
 
5.7%
별 234
 
5.6%
구 234
 
5.6%
특 234
 
5.6%
로 233
 
5.6%
Other values (148) 1694
40.8%
Common
ValueCountFrequency (%)
1219
40.0%
1 370
 
12.1%
) 236
 
7.7%
( 236
 
7.7%
, 216
 
7.1%
2 129
 
4.2%
3 128
 
4.2%
0 91
 
3.0%
5 79
 
2.6%
4 78
 
2.6%
Other values (8) 267
 
8.8%
Latin
ValueCountFrequency (%)
B 8
33.3%
S 5
20.8%
C 3
 
12.5%
D 2
 
8.3%
k 1
 
4.2%
A 1
 
4.2%
s 1
 
4.2%
K 1
 
4.2%
E 1
 
4.2%
e 1
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4148
57.4%
ASCII 3073
42.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1219
39.7%
1 370
 
12.0%
) 236
 
7.7%
( 236
 
7.7%
, 216
 
7.0%
2 129
 
4.2%
3 128
 
4.2%
0 91
 
3.0%
5 79
 
2.6%
4 78
 
2.5%
Other values (18) 291
 
9.5%
Hangul
ValueCountFrequency (%)
동 287
 
6.9%
중 274
 
6.6%
랑 247
 
6.0%
시 239
 
5.8%
울 236
 
5.7%
서 236
 
5.7%
별 234
 
5.6%
구 234
 
5.6%
특 234
 
5.6%
로 233
 
5.6%
Other values (148) 1694
40.8%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct115
Distinct (%)49.1%
Missing109
Missing (%)31.8%
Infinite0
Infinite (%)0.0%
Mean2127.7735
Minimum2001
Maximum2259
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-05-11T08:02:43.259203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2001
5-th percentile2017
Q12066
median2134
Q32188.75
95-th percentile2243.35
Maximum2259
Range258
Interquartile range (IQR)122.75

Descriptive statistics

Standard deviation74.526459
Coefficient of variation (CV)0.03502556
Kurtosis-1.2310767
Mean2127.7735
Median Absolute Deviation (MAD)65.5
Skewness0.0082202565
Sum497899
Variance5554.1931
MonotonicityNot monotonic
2024-05-11T08:02:43.781836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2033 8
 
2.3%
2087 7
 
2.0%
2024 7
 
2.0%
2169 6
 
1.7%
2162 6
 
1.7%
2150 5
 
1.5%
2213 5
 
1.5%
2163 5
 
1.5%
2085 4
 
1.2%
2249 4
 
1.2%
Other values (105) 177
51.6%
(Missing) 109
31.8%
ValueCountFrequency (%)
2001 1
 
0.3%
2005 2
0.6%
2006 1
 
0.3%
2007 1
 
0.3%
2009 3
0.9%
2010 1
 
0.3%
2012 2
0.6%
2017 4
1.2%
2019 2
0.6%
2021 1
 
0.3%
ValueCountFrequency (%)
2259 1
 
0.3%
2254 2
0.6%
2250 1
 
0.3%
2249 4
1.2%
2246 1
 
0.3%
2245 1
 
0.3%
2244 2
0.6%
2243 2
0.6%
2242 1
 
0.3%
2240 2
0.6%

사업장명
Text

Distinct305
Distinct (%)88.9%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2024-05-11T08:02:44.512750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length19
Mean length7.483965
Min length2

Characters and Unicode

Total characters2567
Distinct characters367
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

Unique279 ?
Unique (%)81.3%

Sample

1st row크라운베이커리
2nd row뚜레쥬르 면목점
3rd row동부고려제과
4th row브레드메카
5th row봉베이커리
ValueCountFrequency (%)
파리바게뜨 19
 
4.2%
뚜레쥬르 11
 
2.4%
면목점 10
 
2.2%
몽블랑제 8
 
1.8%
상봉점 8
 
1.8%
크라운베이커리 4
 
0.9%
코스트코홀세일베이커리 4
 
0.9%
이지바이 4
 
0.9%
주)신세계푸드 4
 
0.9%
파리바게트 4
 
0.9%
Other values (326) 376
83.2%
2024-05-11T08:02:45.996848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 116
 
4.5%
이 115
 
4.5%
점 109
 
4.2%
109
 
4.2%
스 66
 
2.6%
베 64
 
2.5%
커 60
 
2.3%
빵 51
 
2.0%
( 44
 
1.7%
) 44
 
1.7%
Other values (357) 1789
69.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2250
87.7%
Space Separator 109
 
4.2%
Lowercase Letter 52
 
2.0%
Uppercase Letter 47
 
1.8%
Open Punctuation 44
 
1.7%
Close Punctuation 44
 
1.7%
Other Punctuation 12
 
0.5%
Decimal Number 9
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 116
 
5.2%
이 115
 
5.1%
점 109
 
4.8%
스 66
 
2.9%
베 64
 
2.8%
커 60
 
2.7%
빵 51
 
2.3%
바 42
 
1.9%
레 41
 
1.8%
드 39
 
1.7%
Other values (311) 1547
68.8%
Lowercase Letter
ValueCountFrequency (%)
e 10
19.2%
a 7
13.5%
o 5
9.6%
r 4
 
7.7%
n 3
 
5.8%
c 3
 
5.8%
t 3
 
5.8%
y 2
 
3.8%
k 2
 
3.8%
f 2
 
3.8%
Other values (8) 11
21.2%
Uppercase Letter
ValueCountFrequency (%)
A 5
10.6%
E 5
10.6%
D 4
 
8.5%
S 4
 
8.5%
B 4
 
8.5%
R 3
 
6.4%
M 3
 
6.4%
I 3
 
6.4%
W 2
 
4.3%
F 2
 
4.3%
Other values (8) 12
25.5%
Decimal Number
ValueCountFrequency (%)
2 5
55.6%
0 2
 
22.2%
5 1
 
11.1%
8 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
? 7
58.3%
& 3
25.0%
' 2
 
16.7%
Space Separator
ValueCountFrequency (%)
109
100.0%
Open Punctuation
ValueCountFrequency (%)
( 44
100.0%
Close Punctuation
ValueCountFrequency (%)
) 44
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2250
87.7%
Common 218
 
8.5%
Latin 99
 
3.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 116
 
5.2%
이 115
 
5.1%
점 109
 
4.8%
스 66
 
2.9%
베 64
 
2.8%
커 60
 
2.7%
빵 51
 
2.3%
바 42
 
1.9%
레 41
 
1.8%
드 39
 
1.7%
Other values (311) 1547
68.8%
Latin
ValueCountFrequency (%)
e 10
 
10.1%
a 7
 
7.1%
A 5
 
5.1%
E 5
 
5.1%
o 5
 
5.1%
D 4
 
4.0%
r 4
 
4.0%
S 4
 
4.0%
B 4
 
4.0%
R 3
 
3.0%
Other values (26) 48
48.5%
Common
ValueCountFrequency (%)
109
50.0%
( 44
20.2%
) 44
20.2%
? 7
 
3.2%
2 5
 
2.3%
& 3
 
1.4%
0 2
 
0.9%
' 2
 
0.9%
5 1
 
0.5%
8 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2250
87.7%
ASCII 317
 
12.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 116
 
5.2%
이 115
 
5.1%
점 109
 
4.8%
스 66
 
2.9%
베 64
 
2.8%
커 60
 
2.7%
빵 51
 
2.3%
바 42
 
1.9%
레 41
 
1.8%
드 39
 
1.7%
Other values (311) 1547
68.8%
ASCII
ValueCountFrequency (%)
109
34.4%
( 44
13.9%
) 44
13.9%
e 10
 
3.2%
a 7
 
2.2%
? 7
 
2.2%
2 5
 
1.6%
A 5
 
1.6%
E 5
 
1.6%
o 5
 
1.6%
Other values (36) 76
24.0%

최종수정일자
Date

Distinct310
Distinct (%)90.4%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
Minimum1999-01-20 00:00:00
Maximum2024-05-07 15:09:48
2024-05-11T08:02:46.463089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:02:47.227286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
I
246 
U
97 

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 246
71.7%
U 97
 
28.3%

Length

2024-05-11T08:02:47.778968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:02:48.246408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 246
71.7%
u 97
 
28.3%

데이터갱신일자
Date

Distinct117
Distinct (%)34.1%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T08:02:48.963180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:02:49.556283image/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 size2.8 KiB
제과점영업
343 

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 343
100.0%

Length

2024-05-11T08:02:50.148140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:02:50.517754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제과점영업 343
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct261
Distinct (%)78.4%
Missing10
Missing (%)2.9%
Infinite0
Infinite (%)0.0%
Mean207706.02
Minimum206445.05
Maximum209797.76
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-05-11T08:02:50.924299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum206445.05
5-th percentile206653.48
Q1207029.01
median207733.92
Q3208208.79
95-th percentile208947.07
Maximum209797.76
Range3352.7108
Interquartile range (IQR)1179.7806

Descriptive statistics

Standard deviation729.17294
Coefficient of variation (CV)0.0035106009
Kurtosis-0.79097398
Mean207706.02
Median Absolute Deviation (MAD)623.40035
Skewness0.19635564
Sum69166105
Variance531693.18
MonotonicityNot monotonic
2024-05-11T08:02:51.554877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
207923.745922676 7
 
2.0%
208183.558935157 6
 
1.7%
208112.860200669 6
 
1.7%
206777.731391054 6
 
1.7%
207553.170404939 5
 
1.5%
207897.260402153 4
 
1.2%
208185.587866215 4
 
1.2%
208361.517012411 3
 
0.9%
208208.786684767 3
 
0.9%
206643.557292629 3
 
0.9%
Other values (251) 286
83.4%
(Missing) 10
 
2.9%
ValueCountFrequency (%)
206445.049396642 1
 
0.3%
206494.386747812 1
 
0.3%
206520.286462085 1
 
0.3%
206544.310283401 1
 
0.3%
206547.302261118 1
 
0.3%
206556.148986381 3
0.9%
206562.028696525 1
 
0.3%
206595.707775401 1
 
0.3%
206599.170939143 1
 
0.3%
206601.772671113 1
 
0.3%
ValueCountFrequency (%)
209797.760188391 1
0.3%
209479.161719823 1
0.3%
209455.150864288 1
0.3%
209399.93927584 1
0.3%
209200.036845418 2
0.6%
209113.869071049 2
0.6%
209089.3160463 2
0.6%
209083.646196172 1
0.3%
209072.09180353 2
0.6%
209042.228269528 1
0.3%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct261
Distinct (%)78.4%
Missing10
Missing (%)2.9%
Infinite0
Infinite (%)0.0%
Mean454840.93
Minimum452208.89
Maximum457702.63
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-05-11T08:02:52.362405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum452208.89
5-th percentile452951.78
Q1454045.53
median454911.25
Q3455633.71
95-th percentile457042.49
Maximum457702.63
Range5493.7446
Interquartile range (IQR)1588.1759

Descriptive statistics

Standard deviation1257.4586
Coefficient of variation (CV)0.0027646117
Kurtosis-0.73207984
Mean454840.93
Median Absolute Deviation (MAD)818.15332
Skewness0.083533845
Sum1.5146203 × 108
Variance1581202.1
MonotonicityNot monotonic
2024-05-11T08:02:53.006979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
455090.718335439 7
 
2.0%
454911.24852306 6
 
1.7%
457113.638411288 6
 
1.7%
456837.219624564 6
 
1.7%
453031.11581883 5
 
1.5%
454953.363448013 4
 
1.2%
455005.951408018 4
 
1.2%
455654.154748002 3
 
0.9%
457054.793655589 3
 
0.9%
455871.400781785 3
 
0.9%
Other values (251) 286
83.4%
(Missing) 10
 
2.9%
ValueCountFrequency (%)
452208.886545884 1
0.3%
452419.12647681 2
0.6%
452461.815582664 2
0.6%
452517.896471138 2
0.6%
452547.055071015 1
0.3%
452580.012274859 1
0.3%
452613.554399115 2
0.6%
452691.626557446 1
0.3%
452715.123717789 1
0.3%
452797.777343792 2
0.6%
ValueCountFrequency (%)
457702.631123 1
 
0.3%
457462.766652935 1
 
0.3%
457315.078254949 1
 
0.3%
457300.590845829 1
 
0.3%
457229.891781643 1
 
0.3%
457150.22870364 1
 
0.3%
457122.700436003 1
 
0.3%
457113.638411288 6
1.7%
457098.850403445 1
 
0.3%
457054.793655589 3
0.9%

위생업태명
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
제과점영업
276 
<NA>
67 

Length

Max length5
Median length5
Mean length4.8046647
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제과점영업 276
80.5%
<NA> 67
 
19.5%

Length

2024-05-11T08:02:53.977361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:02:54.418592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제과점영업 276
80.5%
na 67
 
19.5%

남성종사자수
Categorical

Distinct6
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
<NA>
202 
0
83 
1
38 
2
 
15
3
 
4

Length

Max length4
Median length4
Mean length2.7667638
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st row0
2nd row2
3rd row2
4th row2
5th row1

Common Values

ValueCountFrequency (%)
<NA> 202
58.9%
0 83
24.2%
1 38
 
11.1%
2 15
 
4.4%
3 4
 
1.2%
6 1
 
0.3%

Length

2024-05-11T08:02:54.972246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:02:55.446745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 202
58.9%
0 83
24.2%
1 38
 
11.1%
2 15
 
4.4%
3 4
 
1.2%
6 1
 
0.3%

여성종사자수
Categorical

Distinct6
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
<NA>
202 
0
92 
1
43 
2
 
4
4
 
1

Length

Max length4
Median length4
Mean length2.7667638
Min length1

Unique

Unique2 ?
Unique (%)0.6%

Sample

1st row0
2nd row1
3rd row2
4th row1
5th row1

Common Values

ValueCountFrequency (%)
<NA> 202
58.9%
0 92
26.8%
1 43
 
12.5%
2 4
 
1.2%
4 1
 
0.3%
5 1
 
0.3%

Length

2024-05-11T08:02:56.165331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:02:56.635628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 202
58.9%
0 92
26.8%
1 43
 
12.5%
2 4
 
1.2%
4 1
 
0.3%
5 1
 
0.3%

영업장주변구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
<NA>
254 
주택가주변
60 
기타
 
19
아파트지역
 
9
학교정화(상대)
 
1

Length

Max length8
Median length4
Mean length4.1020408
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 254
74.1%
주택가주변 60
 
17.5%
기타 19
 
5.5%
아파트지역 9
 
2.6%
학교정화(상대) 1
 
0.3%

Length

2024-05-11T08:02:57.230997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:02:57.617544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 254
74.1%
주택가주변 60
 
17.5%
기타 19
 
5.5%
아파트지역 9
 
2.6%
학교정화(상대 1
 
0.3%

등급구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
<NA>
265 
기타
39 
갑
 
16
자율
 
14
지도
 
7

Length

Max length4
Median length4
Mean length3.4927114
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row갑
2nd row갑
3rd row갑
4th row지도
5th row갑

Common Values

ValueCountFrequency (%)
<NA> 265
77.3%
기타 39
 
11.4%
갑 16
 
4.7%
자율 14
 
4.1%
지도 7
 
2.0%
을 2
 
0.6%

Length

2024-05-11T08:02:58.079694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:02:58.522341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 265
77.3%
기타 39
 
11.4%
갑 16
 
4.7%
자율 14
 
4.1%
지도 7
 
2.0%
을 2
 
0.6%

급수시설구분명
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
상수도전용
181 
<NA>
162 

Length

Max length5
Median length5
Mean length4.5276968
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
상수도전용 181
52.8%
<NA> 162
47.2%

Length

2024-05-11T08:02:58.891458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:02:59.183066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 181
52.8%
na 162
47.2%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
<NA>
324 
0
 
19

Length

Max length4
Median length4
Mean length3.8338192
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> 324
94.5%
0 19
 
5.5%

Length

2024-05-11T08:02:59.524800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:02:59.896505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 324
94.5%
0 19
 
5.5%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
<NA>
323 
0
 
20

Length

Max length4
Median length4
Mean length3.8250729
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> 323
94.2%
0 20
 
5.8%

Length

2024-05-11T08:03:00.242498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:03:00.574214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 323
94.2%
0 20
 
5.8%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
<NA>
323 
0
 
20

Length

Max length4
Median length4
Mean length3.8250729
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> 323
94.2%
0 20
 
5.8%

Length

2024-05-11T08:03:00.932222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:03:01.267568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 323
94.2%
0 20
 
5.8%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
<NA>
323 
0
 
20

Length

Max length4
Median length4
Mean length3.8250729
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> 323
94.2%
0 20
 
5.8%

Length

2024-05-11T08:03:01.663402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:03:02.107120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 323
94.2%
0 20
 
5.8%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
<NA>
323 
0
 
20

Length

Max length4
Median length4
Mean length3.8250729
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> 323
94.2%
0 20
 
5.8%

Length

2024-05-11T08:03:02.471192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:03:02.819783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 323
94.2%
0 20
 
5.8%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing343
Missing (%)100.0%
Memory size3.1 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
<NA>
323 
0
 
20

Length

Max length4
Median length4
Mean length3.8250729
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> 323
94.2%
0 20
 
5.8%

Length

2024-05-11T08:03:03.170222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:03:03.511212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 323
94.2%
0 20
 
5.8%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
<NA>
323 
0
 
20

Length

Max length4
Median length4
Mean length3.8250729
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> 323
94.2%
0 20
 
5.8%

Length

2024-05-11T08:03:03.811468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:03:04.071333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 323
94.2%
0 20
 
5.8%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.4%
Missing67
Missing (%)19.5%
Memory size818.0 B
False
276 
(Missing)
67 
ValueCountFrequency (%)
False 276
80.5%
(Missing) 67
 
19.5%
2024-05-11T08:03:04.333727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING 

Distinct238
Distinct (%)86.2%
Missing67
Missing (%)19.5%
Infinite0
Infinite (%)0.0%
Mean42.405217
Minimum0.5
Maximum251.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-05-11T08:03:04.689133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.5
5-th percentile11.125
Q124.5
median34.125
Q353.13
95-th percentile93.26
Maximum251.9
Range251.4
Interquartile range (IQR)28.63

Descriptive statistics

Standard deviation30.18682
Coefficient of variation (CV)0.71186571
Kurtosis12.935687
Mean42.405217
Median Absolute Deviation (MAD)12.715
Skewness2.8080816
Sum11703.84
Variance911.24411
MonotonicityNot monotonic
2024-05-11T08:03:05.182240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30.0 6
 
1.7%
33.0 5
 
1.5%
19.8 4
 
1.2%
29.08 3
 
0.9%
32.0 3
 
0.9%
53.52 3
 
0.9%
6.6 3
 
0.9%
26.4 3
 
0.9%
27.0 2
 
0.6%
32.7 2
 
0.6%
Other values (228) 242
70.6%
(Missing) 67
 
19.5%
ValueCountFrequency (%)
0.5 1
 
0.3%
3.3 1
 
0.3%
4.0 1
 
0.3%
4.95 1
 
0.3%
6.6 3
0.9%
9.0 2
0.6%
9.05 1
 
0.3%
9.1 1
 
0.3%
9.9 2
0.6%
10.0 1
 
0.3%
ValueCountFrequency (%)
251.9 1
0.3%
219.52 1
0.3%
143.5 1
0.3%
143.16 1
0.3%
132.23 1
0.3%
128.21 1
0.3%
127.6 1
0.3%
126.74 1
0.3%
124.82 1
0.3%
117.78 1
0.3%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing343
Missing (%)100.0%
Memory size3.1 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing343
Missing (%)100.0%
Memory size3.1 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing343
Missing (%)100.0%
Memory size3.1 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030600003060000-121-1972-0707719720511<NA>3폐업2폐업20060412<NA><NA><NA>02 491725256.18131808서울특별시 중랑구 망우동 458-1번지<NA><NA>크라운베이커리2002-07-09 00:00:00I2018-08-31 23:59:59.0제과점영업208736.900269454786.28674제과점영업00주택가주변갑상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N56.18<NA><NA><NA>
130600003060000-121-1978-0708719781208<NA>3폐업2폐업20120918<NA><NA><NA>02 433266132.37131818서울특별시 중랑구 면목동 502-7번지서울특별시 중랑구 면목로 365 (면목동)2220뚜레쥬르 면목점2011-11-29 13:12:46I2018-08-31 23:59:59.0제과점영업207719.355685453613.027419제과점영업21주택가주변갑상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N32.37<NA><NA><NA>
230600003060000-121-1979-0709619790425<NA>1영업/정상1영업<NA><NA><NA><NA>02 433178336.16131810서울특별시 중랑구 망우동 563-0번지서울특별시 중랑구 망우로 388 (망우동)2163동부고려제과2011-11-29 13:13:41I2018-08-31 23:59:59.0제과점영업208330.92727455135.629709제과점영업22주택가주변갑상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N36.16<NA><NA><NA>
330600003060000-121-1979-0710719791227<NA>3폐업2폐업20080129<NA><NA><NA>02 435011135.3131826서울특별시 중랑구 면목동 371-125번지<NA><NA>브레드메카2002-07-10 00:00:00I2018-08-31 23:59:59.0제과점영업207522.246023452613.554399제과점영업21주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N35.3<NA><NA><NA>
430600003060000-121-1980-0699219800828<NA>3폐업2폐업20070827<NA><NA><NA>02 433703735.4131811서울특별시 중랑구 면목동 17-34번지<NA><NA>봉베이커리2002-07-09 00:00:00I2018-08-31 23:59:59.0제과점영업208508.026892454127.818164제과점영업11주택가주변갑상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N35.4<NA><NA><NA>
530600003060000-121-1980-0712319800821<NA>1영업/정상1영업<NA><NA><NA><NA>02 434160651.65131859서울특별시 중랑구 상봉동 102-73번지서울특별시 중랑구 면목로 480 (상봉동)2148파리바게뜨상봉역점2017-09-05 16:03:40I2018-08-31 23:59:59.0제과점영업207543.224207454729.811288제과점영업11주택가주변갑상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N51.65<NA><NA><NA>
630600003060000-121-1981-0704519811031<NA>3폐업2폐업20200506<NA><NA><NA>02435 875416.16131823서울특별시 중랑구 면목동 181-1번지서울특별시 중랑구 봉우재로 40 (면목동)2131파리바게뜨 면목동부점2020-05-06 09:49:34U2020-05-08 02:40:00.0제과점영업206795.009538454234.233947제과점영업32주택가주변갑상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N16.16<NA><NA><NA>
730600003060000-121-1981-0710019810225<NA>3폐업2폐업20070302<NA><NA><NA>02 432002351.8131817서울특별시 중랑구 면목동 226-10번지<NA><NA>오늘은 빵굽는날2004-01-31 00:00:00I2018-08-31 23:59:59.0제과점영업207606.57147454383.20403제과점영업11주택가주변갑상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N51.8<NA><NA><NA>
830600003060000-121-1981-0844019811221<NA>3폐업2폐업20100405<NA><NA><NA>02 434109143.64131822서울특별시 중랑구 면목동 172-1번지<NA><NA>신라베이커리2002-07-09 00:00:00I2018-08-31 23:59:59.0제과점영업206954.727827453603.234835제과점영업21주택가주변갑상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N43.64<NA><NA><NA>
930600003060000-121-1982-0698319821014<NA>1영업/정상1영업<NA><NA><NA><NA>02 434420255.11131802서울특별시 중랑구 망우동 182-63서울특별시 중랑구 양원역로 19 (망우동)2064빵굼터2021-04-07 10:48:01U2021-04-09 02:40:00.0제과점영업209455.150864455552.131201제과점영업11주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N55.11<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
33330600003060000-121-2024-000012024-01-18<NA>1영업/정상1영업<NA><NA><NA><NA>070 8064508763.06131-851서울특별시 중랑구 묵동 233-27 1층서울특별시 중랑구 중랑역로47길 12, 1층 (묵동)2001카페 무미2024-01-18 14:02:49I2023-11-30 22:00:00.0제과점영업206520.286462456978.268385<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
33430600003060000-121-2024-000022024-01-31<NA>1영업/정상1영업<NA><NA><NA><NA><NA>89.76131-230서울특별시 중랑구 망우동 584 신내역 프라디움 더 테라스 C동 CB101호서울특별시 중랑구 용마산로 670, C동 CB101호 (망우동, 신내역 프라디움 더 테라스)2057파리바게뜨 신내역점2024-01-31 13:01:55I2023-12-02 00:02:00.0제과점영업208947.072331456501.73508<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
33530600003060000-121-2024-000042024-02-06<NA>1영업/정상1영업<NA><NA><NA><NA><NA>39.4131-858서울특별시 중랑구 상봉동 91-4 상봉역 유보라 퍼스트리브&포스퀘어 제B119호서울특별시 중랑구 망우로 322, 제지1층 제B119호 (상봉동, 상봉역 유보라 퍼스트리브&포스퀘어)2149쿨캣2024-02-06 16:14:31I2023-12-02 00:08:00.0제과점영업207734.217753454934.006785<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
33630600003060000-121-2024-000052024-02-27<NA>1영업/정상1영업<NA><NA><NA><NA><NA>66.11131-802서울특별시 중랑구 망우동 209-27 1층서울특별시 중랑구 망우로 467, 1층 (망우동)2066파리바게트 망우금란점2024-02-27 11:53:05I2023-12-01 22:09:00.0제과점영업209113.869071455385.874615<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
33730600003060000-121-2024-000062024-03-04<NA>1영업/정상1영업<NA><NA><NA><NA><NA>56.0131-230서울특별시 중랑구 망우동 584 신내역 프라디움 더 테라스 D동 DB호서울특별시 중랑구 용마산로 670, D동 DB111호 (망우동, 신내역 프라디움 더 테라스)2057화이트리에 신내역점2024-03-04 10:32:59I2023-12-03 00:06:00.0제과점영업208947.072331456501.73508<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
33830600003060000-121-2024-000072024-03-21<NA>1영업/정상1영업<NA><NA><NA><NA><NA>72.0131-872서울특별시 중랑구 신내동 646 금강리빙스텔 147, 148호서울특별시 중랑구 신내로 211, 금강리빙스텔 147, 148호 (신내동)2024파리바게뜨 봉화산역점2024-03-21 11:13:10I2023-12-02 22:03:00.0제과점영업208112.860201457113.638411<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
33930600003060000-121-2024-000082024-04-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>46.8131-857서울특별시 중랑구 상봉동 100-9 상봉역서울특별시 중랑구 망우로 297, 상봉역 1층 (상봉동)2098삼송빵집 상봉역점2024-04-02 14:25:14I2023-12-04 00:04:00.0제과점영업207527.877317454942.176383<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
34030600003060000-121-2024-000092024-04-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA>33.0131-857서울특별시 중랑구 상봉동 49-11서울특별시 중랑구 송림길 5, 1층 102호 (상봉동)2086필릿(Feel eat)2024-04-08 10:50:09I2023-12-03 23:00:00.0제과점영업208335.490182455234.627072<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
34130600003060000-121-2024-000102024-04-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA>35.0131-811서울특별시 중랑구 면목동 5-33서울특별시 중랑구 용마산로94길 24, 1층 (면목동)2191케이크봉봉2024-04-30 13:16:55I2023-12-05 00:02:00.0제과점영업208594.550085454057.348854<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
34230600003060000-121-2024-000112024-04-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA>141.72131-859서울특별시 중랑구 상봉동 101-11 지층, 1층서울특별시 중랑구 망우로 302-1, 지층, 1층 (상봉동)2148비지티(BGT)호두단팥빵 상봉점2024-04-30 15:43:40I2023-12-05 00:02:00.0제과점영업207536.387866454888.517257<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>