Overview

Dataset statistics

Number of variables44
Number of observations133
Missing cells1239
Missing cells (%)21.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory49.0 KiB
Average record size in memory377.0 B

Variable types

Categorical22
Text6
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
Author종로구
URLhttps://data.seoul.go.kr/dataList/OA-18177/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
남성종사자수 is highly imbalanced (61.0%)Imbalance
영업장주변구분명 is highly imbalanced (70.1%)Imbalance
등급구분명 is highly imbalanced (70.1%)Imbalance
급수시설구분명 is highly imbalanced (56.3%)Imbalance
총인원 is highly imbalanced (73.5%)Imbalance
본사종업원수 is highly imbalanced (59.0%)Imbalance
보증액 is highly imbalanced (51.5%)Imbalance
월세액 is highly imbalanced (51.5%)Imbalance
시설총규모 is highly imbalanced (56.1%)Imbalance
인허가취소일자 has 133 (100.0%) missing valuesMissing
폐업일자 has 45 (33.8%) missing valuesMissing
휴업시작일자 has 133 (100.0%) missing valuesMissing
휴업종료일자 has 133 (100.0%) missing valuesMissing
재개업일자 has 133 (100.0%) missing valuesMissing
전화번호 has 59 (44.4%) missing valuesMissing
소재지면적 has 76 (57.1%) missing valuesMissing
도로명주소 has 44 (33.1%) missing valuesMissing
도로명우편번호 has 45 (33.8%) missing valuesMissing
좌표정보(X) has 5 (3.8%) missing valuesMissing
좌표정보(Y) has 5 (3.8%) missing valuesMissing
다중이용업소여부 has 29 (21.8%) missing valuesMissing
전통업소지정번호 has 133 (100.0%) missing valuesMissing
전통업소주된음식 has 133 (100.0%) missing valuesMissing
홈페이지 has 133 (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

Reproduction

Analysis started2024-05-11 06:23:10.719033
Analysis finished2024-05-11 06:23:11.805205
Duration1.09 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
3000000
133 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3000000
2nd row3000000
3rd row3000000
4th row3000000
5th row3000000

Common Values

ValueCountFrequency (%)
3000000 133
100.0%

Length

2024-05-11T15:23:11.932010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:12.063853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3000000 133
100.0%

관리번호
Text

UNIQUE 

Distinct133
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-05-11T15:23:12.270302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters2926
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

Unique133 ?
Unique (%)100.0%

Sample

1st row3000000-109-1998-00068
2nd row3000000-109-1998-00169
3rd row3000000-109-1999-00108
4th row3000000-109-1999-00149
5th row3000000-109-1999-00210
ValueCountFrequency (%)
3000000-109-1998-00068 1
 
0.8%
3000000-109-2014-00002 1
 
0.8%
3000000-109-2019-00002 1
 
0.8%
3000000-109-2019-00001 1
 
0.8%
3000000-109-2018-00011 1
 
0.8%
3000000-109-2018-00010 1
 
0.8%
3000000-109-2018-00009 1
 
0.8%
3000000-109-2018-00008 1
 
0.8%
3000000-109-2018-00007 1
 
0.8%
3000000-109-2018-00006 1
 
0.8%
Other values (123) 123
92.5%
2024-05-11T15:23:12.740072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1631
55.7%
- 399
 
13.6%
1 239
 
8.2%
2 195
 
6.7%
9 169
 
5.8%
3 163
 
5.6%
4 37
 
1.3%
5 33
 
1.1%
8 24
 
0.8%
6 24
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2527
86.4%
Dash Punctuation 399
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1631
64.5%
1 239
 
9.5%
2 195
 
7.7%
9 169
 
6.7%
3 163
 
6.5%
4 37
 
1.5%
5 33
 
1.3%
8 24
 
0.9%
6 24
 
0.9%
7 12
 
0.5%
Dash Punctuation
ValueCountFrequency (%)
- 399
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2926
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1631
55.7%
- 399
 
13.6%
1 239
 
8.2%
2 195
 
6.7%
9 169
 
5.8%
3 163
 
5.6%
4 37
 
1.3%
5 33
 
1.1%
8 24
 
0.8%
6 24
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2926
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1631
55.7%
- 399
 
13.6%
1 239
 
8.2%
2 195
 
6.7%
9 169
 
5.8%
3 163
 
5.6%
4 37
 
1.3%
5 33
 
1.1%
8 24
 
0.8%
6 24
 
0.8%

인허가일자
Date

Distinct130
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum1998-08-03 00:00:00
Maximum2024-04-18 00:00:00
2024-05-11T15:23:12.977134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:23:13.171112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing133
Missing (%)100.0%
Memory size1.3 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
3
88 
1
45 

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 88
66.2%
1 45
33.8%

Length

2024-05-11T15:23:13.434314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:13.624981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 88
66.2%
1 45
33.8%

영업상태명
Categorical

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
폐업
88 
영업/정상
45 

Length

Max length5
Median length2
Mean length3.0150376
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 88
66.2%
영업/정상 45
33.8%

Length

2024-05-11T15:23:13.834835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:14.051935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 88
66.2%
영업/정상 45
33.8%

상세영업상태코드
Categorical

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2
88 
1
45 

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 88
66.2%
1 45
33.8%

Length

2024-05-11T15:23:14.241361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:14.403978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 88
66.2%
1 45
33.8%

상세영업상태명
Categorical

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
폐업
88 
영업
45 

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 88
66.2%
영업 45
33.8%

Length

2024-05-11T15:23:14.599157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:14.779595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 88
66.2%
영업 45
33.8%

폐업일자
Date

MISSING 

Distinct77
Distinct (%)87.5%
Missing45
Missing (%)33.8%
Memory size1.2 KiB
Minimum2001-02-02 00:00:00
Maximum2024-03-26 00:00:00
2024-05-11T15:23:14.994049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:23:15.279654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing133
Missing (%)100.0%
Memory size1.3 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing133
Missing (%)100.0%
Memory size1.3 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing133
Missing (%)100.0%
Memory size1.3 KiB

전화번호
Text

MISSING 

Distinct71
Distinct (%)95.9%
Missing59
Missing (%)44.4%
Memory size1.2 KiB
2024-05-11T15:23:15.790466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.743243
Min length7

Characters and Unicode

Total characters795
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

Unique68 ?
Unique (%)91.9%

Sample

1st row02 7370558
2nd row02 3131957
3rd row02 3738877
4th row02 2488464
5th row02 7368140
ValueCountFrequency (%)
02 56
37.1%
070 3
 
2.0%
0236769244 2
 
1.3%
730 2
 
1.3%
6789 2
 
1.3%
7326373 2
 
1.3%
22233502 1
 
0.7%
7412015 1
 
0.7%
9999 1
 
0.7%
949 1
 
0.7%
Other values (80) 80
53.0%
2024-05-11T15:23:16.583462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 134
16.9%
0 116
14.6%
107
13.5%
7 91
11.4%
3 74
9.3%
6 69
8.7%
4 51
 
6.4%
5 45
 
5.7%
9 39
 
4.9%
1 35
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 688
86.5%
Space Separator 107
 
13.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 134
19.5%
0 116
16.9%
7 91
13.2%
3 74
10.8%
6 69
10.0%
4 51
 
7.4%
5 45
 
6.5%
9 39
 
5.7%
1 35
 
5.1%
8 34
 
4.9%
Space Separator
ValueCountFrequency (%)
107
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 795
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 134
16.9%
0 116
14.6%
107
13.5%
7 91
11.4%
3 74
9.3%
6 69
8.7%
4 51
 
6.4%
5 45
 
5.7%
9 39
 
4.9%
1 35
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 795
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 134
16.9%
0 116
14.6%
107
13.5%
7 91
11.4%
3 74
9.3%
6 69
8.7%
4 51
 
6.4%
5 45
 
5.7%
9 39
 
4.9%
1 35
 
4.4%

소재지면적
Real number (ℝ)

MISSING 

Distinct46
Distinct (%)80.7%
Missing76
Missing (%)57.1%
Infinite0
Infinite (%)0.0%
Mean36.992982
Minimum3.3
Maximum390
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-11T15:23:16.893528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.3
5-th percentile5.66
Q110
median16.5
Q346.21
95-th percentile113.576
Maximum390
Range386.7
Interquartile range (IQR)36.21

Descriptive statistics

Standard deviation58.40573
Coefficient of variation (CV)1.5788327
Kurtosis24.231268
Mean36.992982
Median Absolute Deviation (MAD)8.5
Skewness4.4281763
Sum2108.6
Variance3411.2293
MonotonicityNot monotonic
2024-05-11T15:23:17.191416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
10.0 7
 
5.3%
50.0 3
 
2.3%
9.9 2
 
1.5%
9.0 2
 
1.5%
3.3 2
 
1.5%
59.5 1
 
0.8%
20.0 1
 
0.8%
6.0 1
 
0.8%
49.5 1
 
0.8%
12.4 1
 
0.8%
Other values (36) 36
27.1%
(Missing) 76
57.1%
ValueCountFrequency (%)
3.3 2
1.5%
4.3 1
0.8%
6.0 1
0.8%
6.01 1
0.8%
6.45 1
0.8%
8.02 1
0.8%
8.5 1
0.8%
9.0 2
1.5%
9.3 1
0.8%
9.9 2
1.5%
ValueCountFrequency (%)
390.0 1
0.8%
170.75 1
0.8%
143.88 1
0.8%
106.0 1
0.8%
99.72 1
0.8%
78.57 1
0.8%
66.0 1
0.8%
61.0 1
0.8%
59.5 1
0.8%
52.63 1
0.8%

소재지우편번호
Text

Distinct89
Distinct (%)66.9%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-05-11T15:23:17.718968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1729323
Min length6

Characters and Unicode

Total characters821
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

Unique59 ?
Unique (%)44.4%

Sample

1st row110100
2nd row110848
3rd row110102
4th row110862
5th row110043
ValueCountFrequency (%)
110847 5
 
3.8%
110170 4
 
3.0%
110054 4
 
3.0%
110045 3
 
2.3%
110522 3
 
2.3%
110837 3
 
2.3%
110043 3
 
2.3%
110817 3
 
2.3%
110801 3
 
2.3%
110260 3
 
2.3%
Other values (79) 99
74.4%
2024-05-11T15:23:18.537348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 301
36.7%
0 235
28.6%
2 51
 
6.2%
8 49
 
6.0%
4 49
 
6.0%
3 37
 
4.5%
5 32
 
3.9%
7 25
 
3.0%
- 23
 
2.8%
6 11
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 798
97.2%
Dash Punctuation 23
 
2.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 301
37.7%
0 235
29.4%
2 51
 
6.4%
8 49
 
6.1%
4 49
 
6.1%
3 37
 
4.6%
5 32
 
4.0%
7 25
 
3.1%
6 11
 
1.4%
9 8
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 821
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 301
36.7%
0 235
28.6%
2 51
 
6.2%
8 49
 
6.0%
4 49
 
6.0%
3 37
 
4.5%
5 32
 
3.9%
7 25
 
3.0%
- 23
 
2.8%
6 11
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 821
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 301
36.7%
0 235
28.6%
2 51
 
6.2%
8 49
 
6.0%
4 49
 
6.0%
3 37
 
4.5%
5 32
 
3.9%
7 25
 
3.0%
- 23
 
2.8%
6 11
 
1.3%

지번주소
Text

Distinct131
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-05-11T15:23:19.098283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length38
Mean length23.781955
Min length16

Characters and Unicode

Total characters3163
Distinct characters177
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

Unique129 ?
Unique (%)97.0%

Sample

1st row서울특별시 종로구 교남동 61-2
2nd row서울특별시 종로구 평창동 471-9
3rd row서울특별시 종로구 평동 219-0 평동박영빌딩201호
4th row서울특별시 종로구 숭인동 65-11 명경빌딩3층 (핸드폰016)
5th row서울특별시 종로구 통인동 5-9
ValueCountFrequency (%)
서울특별시 133
20.4%
종로구 132
20.2%
1층 15
 
2.3%
창신동 11
 
1.7%
평창동 8
 
1.2%
2층 8
 
1.2%
지하1층 8
 
1.2%
숭인동 5
 
0.8%
명륜2가 5
 
0.8%
계동 5
 
0.8%
Other values (248) 322
49.4%
2024-05-11T15:23:19.910748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
618
19.5%
1 186
 
5.9%
종 145
 
4.6%
로 144
 
4.6%
서 138
 
4.4%
구 134
 
4.2%
시 134
 
4.2%
울 133
 
4.2%
별 133
 
4.2%
특 133
 
4.2%
Other values (167) 1265
40.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1840
58.2%
Space Separator 618
 
19.5%
Decimal Number 598
 
18.9%
Dash Punctuation 85
 
2.7%
Close Punctuation 6
 
0.2%
Open Punctuation 6
 
0.2%
Other Punctuation 5
 
0.2%
Uppercase Letter 5
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
종 145
 
7.9%
로 144
 
7.8%
서 138
 
7.5%
구 134
 
7.3%
시 134
 
7.3%
울 133
 
7.2%
별 133
 
7.2%
특 133
 
7.2%
동 124
 
6.7%
층 48
 
2.6%
Other values (147) 574
31.2%
Decimal Number
ValueCountFrequency (%)
1 186
31.1%
2 92
15.4%
3 57
 
9.5%
0 49
 
8.2%
5 48
 
8.0%
4 47
 
7.9%
8 34
 
5.7%
6 31
 
5.2%
9 29
 
4.8%
7 25
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
B 2
40.0%
D 1
20.0%
A 1
20.0%
M 1
20.0%
Other Punctuation
ValueCountFrequency (%)
, 4
80.0%
@ 1
 
20.0%
Space Separator
ValueCountFrequency (%)
618
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 85
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1840
58.2%
Common 1318
41.7%
Latin 5
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
종 145
 
7.9%
로 144
 
7.8%
서 138
 
7.5%
구 134
 
7.3%
시 134
 
7.3%
울 133
 
7.2%
별 133
 
7.2%
특 133
 
7.2%
동 124
 
6.7%
층 48
 
2.6%
Other values (147) 574
31.2%
Common
ValueCountFrequency (%)
618
46.9%
1 186
 
14.1%
2 92
 
7.0%
- 85
 
6.4%
3 57
 
4.3%
0 49
 
3.7%
5 48
 
3.6%
4 47
 
3.6%
8 34
 
2.6%
6 31
 
2.4%
Other values (6) 71
 
5.4%
Latin
ValueCountFrequency (%)
B 2
40.0%
D 1
20.0%
A 1
20.0%
M 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1840
58.2%
ASCII 1323
41.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
618
46.7%
1 186
 
14.1%
2 92
 
7.0%
- 85
 
6.4%
3 57
 
4.3%
0 49
 
3.7%
5 48
 
3.6%
4 47
 
3.6%
8 34
 
2.6%
6 31
 
2.3%
Other values (10) 76
 
5.7%
Hangul
ValueCountFrequency (%)
종 145
 
7.9%
로 144
 
7.8%
서 138
 
7.5%
구 134
 
7.3%
시 134
 
7.3%
울 133
 
7.2%
별 133
 
7.2%
특 133
 
7.2%
동 124
 
6.7%
층 48
 
2.6%
Other values (147) 574
31.2%

도로명주소
Text

MISSING 

Distinct89
Distinct (%)100.0%
Missing44
Missing (%)33.1%
Memory size1.2 KiB
2024-05-11T15:23:20.603473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length42
Mean length31.314607
Min length20

Characters and Unicode

Total characters2787
Distinct characters176
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

Unique89 ?
Unique (%)100.0%

Sample

1st row서울특별시 종로구 계동길 5 (계동)
2nd row서울특별시 종로구 종로 1 (종로1가)
3rd row서울특별시 종로구 종로 310 (창신동)
4th row서울특별시 종로구 지봉로 87 (창신동,이수아파트상가1층)
5th row서울특별시 종로구 사직로8길 5 (필운동, 제이앤제이빌딩)
ValueCountFrequency (%)
서울특별시 89
 
15.7%
종로구 88
 
15.5%
1층 23
 
4.1%
지하1층 7
 
1.2%
2층 7
 
1.2%
종로 6
 
1.1%
창신동 6
 
1.1%
4 5
 
0.9%
자하문로 4
 
0.7%
계동 4
 
0.7%
Other values (241) 327
57.8%
2024-05-11T15:23:21.494329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
477
 
17.1%
로 168
 
6.0%
1 130
 
4.7%
종 110
 
3.9%
동 94
 
3.4%
서 92
 
3.3%
시 90
 
3.2%
울 89
 
3.2%
) 89
 
3.2%
( 89
 
3.2%
Other values (166) 1359
48.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1613
57.9%
Space Separator 477
 
17.1%
Decimal Number 409
 
14.7%
Close Punctuation 89
 
3.2%
Open Punctuation 89
 
3.2%
Other Punctuation 84
 
3.0%
Dash Punctuation 19
 
0.7%
Uppercase Letter 6
 
0.2%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 168
 
10.4%
종 110
 
6.8%
동 94
 
5.8%
서 92
 
5.7%
시 90
 
5.6%
울 89
 
5.5%
구 89
 
5.5%
별 89
 
5.5%
특 89
 
5.5%
층 60
 
3.7%
Other values (146) 643
39.9%
Decimal Number
ValueCountFrequency (%)
1 130
31.8%
2 69
16.9%
5 38
 
9.3%
3 37
 
9.0%
4 32
 
7.8%
9 25
 
6.1%
0 25
 
6.1%
8 24
 
5.9%
6 15
 
3.7%
7 14
 
3.4%
Uppercase Letter
ValueCountFrequency (%)
B 3
50.0%
D 1
 
16.7%
A 1
 
16.7%
F 1
 
16.7%
Space Separator
ValueCountFrequency (%)
477
100.0%
Close Punctuation
ValueCountFrequency (%)
) 89
100.0%
Open Punctuation
ValueCountFrequency (%)
( 89
100.0%
Other Punctuation
ValueCountFrequency (%)
, 84
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1613
57.9%
Common 1168
41.9%
Latin 6
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 168
 
10.4%
종 110
 
6.8%
동 94
 
5.8%
서 92
 
5.7%
시 90
 
5.6%
울 89
 
5.5%
구 89
 
5.5%
별 89
 
5.5%
특 89
 
5.5%
층 60
 
3.7%
Other values (146) 643
39.9%
Common
ValueCountFrequency (%)
477
40.8%
1 130
 
11.1%
) 89
 
7.6%
( 89
 
7.6%
, 84
 
7.2%
2 69
 
5.9%
5 38
 
3.3%
3 37
 
3.2%
4 32
 
2.7%
9 25
 
2.1%
Other values (6) 98
 
8.4%
Latin
ValueCountFrequency (%)
B 3
50.0%
D 1
 
16.7%
A 1
 
16.7%
F 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1613
57.9%
ASCII 1174
42.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
477
40.6%
1 130
 
11.1%
) 89
 
7.6%
( 89
 
7.6%
, 84
 
7.2%
2 69
 
5.9%
5 38
 
3.2%
3 37
 
3.2%
4 32
 
2.7%
9 25
 
2.1%
Other values (10) 104
 
8.9%
Hangul
ValueCountFrequency (%)
로 168
 
10.4%
종 110
 
6.8%
동 94
 
5.8%
서 92
 
5.7%
시 90
 
5.6%
울 89
 
5.5%
구 89
 
5.5%
별 89
 
5.5%
특 89
 
5.5%
층 60
 
3.7%
Other values (146) 643
39.9%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct67
Distinct (%)76.1%
Missing45
Missing (%)33.8%
Infinite0
Infinite (%)0.0%
Mean3131.25
Minimum3007
Maximum6064
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-11T15:23:21.766454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3007
5-th percentile3012.05
Q13043.75
median3097.5
Q33147.5
95-th percentile3191.65
Maximum6064
Range3057
Interquartile range (IQR)103.75

Descriptive statistics

Standard deviation321.52558
Coefficient of variation (CV)0.10268282
Kurtosis82.143795
Mean3131.25
Median Absolute Deviation (MAD)52
Skewness8.9147866
Sum275550
Variance103378.7
MonotonicityNot monotonic
2024-05-11T15:23:22.061934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3055 4
 
3.0%
3040 4
 
3.0%
3020 2
 
1.5%
3145 2
 
1.5%
3168 2
 
1.5%
3133 2
 
1.5%
3054 2
 
1.5%
3043 2
 
1.5%
3123 2
 
1.5%
3197 2
 
1.5%
Other values (57) 64
48.1%
(Missing) 45
33.8%
ValueCountFrequency (%)
3007 1
0.8%
3008 2
1.5%
3009 1
0.8%
3011 1
0.8%
3014 1
0.8%
3017 1
0.8%
3020 2
1.5%
3022 1
0.8%
3023 1
0.8%
3034 2
1.5%
ValueCountFrequency (%)
6064 1
0.8%
3197 2
1.5%
3195 1
0.8%
3192 1
0.8%
3191 1
0.8%
3190 1
0.8%
3188 2
1.5%
3186 1
0.8%
3180 1
0.8%
3173 1
0.8%

사업장명
Text

Distinct131
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-05-11T15:23:22.579985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length15
Mean length6.7518797
Min length2

Characters and Unicode

Total characters898
Distinct characters274
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

Unique129 ?
Unique (%)97.0%

Sample

1st row이조유통
2nd row한국유통
3rd row신성애드컴
4th row비엠택
5th row제일수퍼
ValueCountFrequency (%)
주식회사 5
 
2.9%
퀸할인매장 2
 
1.2%
금일농수산유통 2
 
1.2%
위니비니 2
 
1.2%
명과 2
 
1.2%
주)명신바이오텍 1
 
0.6%
풍기인삼 1
 
0.6%
협동조합 1
 
0.6%
서울사무소 1
 
0.6%
라플란드 1
 
0.6%
Other values (155) 155
89.6%
2024-05-11T15:23:23.294488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
40
 
4.5%
주 35
 
3.9%
) 34
 
3.8%
( 31
 
3.5%
이 25
 
2.8%
스 24
 
2.7%
리 14
 
1.6%
아 13
 
1.4%
사 13
 
1.4%
마 12
 
1.3%
Other values (264) 657
73.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 744
82.9%
Space Separator 40
 
4.5%
Close Punctuation 34
 
3.8%
Open Punctuation 31
 
3.5%
Lowercase Letter 27
 
3.0%
Uppercase Letter 14
 
1.6%
Decimal Number 7
 
0.8%
Modifier Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 35
 
4.7%
이 25
 
3.4%
스 24
 
3.2%
리 14
 
1.9%
아 13
 
1.7%
사 13
 
1.7%
마 12
 
1.6%
제 11
 
1.5%
점 11
 
1.5%
로 11
 
1.5%
Other values (233) 575
77.3%
Lowercase Letter
ValueCountFrequency (%)
e 4
14.8%
t 3
11.1%
l 3
11.1%
p 3
11.1%
s 2
7.4%
i 2
7.4%
a 2
7.4%
o 2
7.4%
m 1
 
3.7%
r 1
 
3.7%
Other values (4) 4
14.8%
Uppercase Letter
ValueCountFrequency (%)
E 3
21.4%
S 2
14.3%
T 2
14.3%
A 1
 
7.1%
K 1
 
7.1%
C 1
 
7.1%
R 1
 
7.1%
F 1
 
7.1%
O 1
 
7.1%
G 1
 
7.1%
Decimal Number
ValueCountFrequency (%)
1 3
42.9%
0 2
28.6%
5 2
28.6%
Space Separator
ValueCountFrequency (%)
40
100.0%
Close Punctuation
ValueCountFrequency (%)
) 34
100.0%
Open Punctuation
ValueCountFrequency (%)
( 31
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 744
82.9%
Common 113
 
12.6%
Latin 41
 
4.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 35
 
4.7%
이 25
 
3.4%
스 24
 
3.2%
리 14
 
1.9%
아 13
 
1.7%
사 13
 
1.7%
마 12
 
1.6%
제 11
 
1.5%
점 11
 
1.5%
로 11
 
1.5%
Other values (233) 575
77.3%
Latin
ValueCountFrequency (%)
e 4
 
9.8%
t 3
 
7.3%
E 3
 
7.3%
l 3
 
7.3%
p 3
 
7.3%
s 2
 
4.9%
i 2
 
4.9%
S 2
 
4.9%
T 2
 
4.9%
a 2
 
4.9%
Other values (14) 15
36.6%
Common
ValueCountFrequency (%)
40
35.4%
) 34
30.1%
( 31
27.4%
1 3
 
2.7%
0 2
 
1.8%
5 2
 
1.8%
` 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 744
82.9%
ASCII 154
 
17.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
40
26.0%
) 34
22.1%
( 31
20.1%
e 4
 
2.6%
1 3
 
1.9%
t 3
 
1.9%
E 3
 
1.9%
l 3
 
1.9%
p 3
 
1.9%
s 2
 
1.3%
Other values (21) 28
18.2%
Hangul
ValueCountFrequency (%)
주 35
 
4.7%
이 25
 
3.4%
스 24
 
3.2%
리 14
 
1.9%
아 13
 
1.7%
사 13
 
1.7%
마 12
 
1.6%
제 11
 
1.5%
점 11
 
1.5%
로 11
 
1.5%
Other values (233) 575
77.3%

최종수정일자
Date

Distinct131
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum1998-12-23 00:00:00
Maximum2024-04-18 10:34:38
2024-05-11T15:23:23.615402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:23:23.871914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
I
91 
U
42 

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 91
68.4%
U 42
31.6%

Length

2024-05-11T15:23:24.180682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:24.387302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 91
68.4%
u 42
31.6%

데이터갱신일자
Date

Distinct58
Distinct (%)43.6%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 22:00:00
2024-05-11T15:23:24.622596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:23:25.337808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
식품소분업
133 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품소분업 133
100.0%

Length

2024-05-11T15:23:25.612382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:25.810542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 133
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct119
Distinct (%)93.0%
Missing5
Missing (%)3.8%
Infinite0
Infinite (%)0.0%
Mean198711.75
Minimum196188.68
Maximum203799.46
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-11T15:23:26.048188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum196188.68
5-th percentile196632.26
Q1197376.97
median198577.52
Q3199912.94
95-th percentile201268.35
Maximum203799.46
Range7610.7805
Interquartile range (IQR)2535.9692

Descriptive statistics

Standard deviation1548.0463
Coefficient of variation (CV)0.0077904114
Kurtosis-0.24902417
Mean198711.75
Median Absolute Deviation (MAD)1301.1459
Skewness0.56655846
Sum25435104
Variance2396447.3
MonotonicityNot monotonic
2024-05-11T15:23:26.348238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
199878.668537625 3
 
2.3%
198742.659391924 2
 
1.5%
197416.92841556 2
 
1.5%
197181.393301659 2
 
1.5%
196925.848272668 2
 
1.5%
197980.401689693 2
 
1.5%
201228.579823795 2
 
1.5%
198351.818737482 2
 
1.5%
200312.390703196 1
 
0.8%
197618.459740824 1
 
0.8%
Other values (109) 109
82.0%
(Missing) 5
 
3.8%
ValueCountFrequency (%)
196188.676804345 1
0.8%
196362.38246525 1
0.8%
196424.837917374 1
0.8%
196467.975088253 1
0.8%
196475.522160107 1
0.8%
196532.869792779 1
0.8%
196569.797128129 1
0.8%
196748.269536892 1
0.8%
196790.337498006 1
0.8%
196865.157323592 1
0.8%
ValueCountFrequency (%)
203799.457293732 1
0.8%
201946.768574808 1
0.8%
201890.636280279 1
0.8%
201767.682997978 1
0.8%
201702.974433451 1
0.8%
201330.533467614 1
0.8%
201273.887781838 1
0.8%
201258.062657124 1
0.8%
201228.579823795 2
1.5%
201168.350187013 1
0.8%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct119
Distinct (%)93.0%
Missing5
Missing (%)3.8%
Infinite0
Infinite (%)0.0%
Mean452987.54
Minimum446738.76
Maximum457029.35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-11T15:23:26.654751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum446738.76
5-th percentile451925.37
Q1452293.82
median452735.73
Q3453263.01
95-th percentile455997.93
Maximum457029.35
Range10290.597
Interquartile range (IQR)969.19641

Descriptive statistics

Standard deviation1273.7304
Coefficient of variation (CV)0.0028118441
Kurtosis5.4587239
Mean452987.54
Median Absolute Deviation (MAD)466.20803
Skewness0.38971978
Sum57982405
Variance1622389
MonotonicityNot monotonic
2024-05-11T15:23:26.931307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
453693.071412414 3
 
2.3%
452814.32796848 2
 
1.5%
452855.09250407 2
 
1.5%
452458.826651573 2
 
1.5%
454483.196631026 2
 
1.5%
452403.295775364 2
 
1.5%
452855.249637866 2
 
1.5%
451921.60302604 2
 
1.5%
452425.038952122 1
 
0.8%
452311.285166273 1
 
0.8%
Other values (109) 109
82.0%
(Missing) 5
 
3.8%
ValueCountFrequency (%)
446738.75698971 1
0.8%
451580.195594285 1
0.8%
451813.489945391 1
0.8%
451864.495054695 1
0.8%
451875.944604705 1
0.8%
451921.60302604 2
1.5%
451932.36673738 1
0.8%
451939.677286976 1
0.8%
451943.192566668 1
0.8%
451962.63614134 1
0.8%
ValueCountFrequency (%)
457029.354438962 1
0.8%
456211.92274867 1
0.8%
456142.715416274 1
0.8%
456055.205802855 1
0.8%
456048.716300069 1
0.8%
456038.650926234 1
0.8%
456018.751573648 1
0.8%
455959.269196762 1
0.8%
455893.228194817 1
0.8%
455775.301893958 1
0.8%

위생업태명
Categorical

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
식품소분업
104 
<NA>
29 

Length

Max length5
Median length5
Mean length4.7819549
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품소분업 104
78.2%
<NA> 29
 
21.8%

Length

2024-05-11T15:23:27.185864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:27.410962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 104
78.2%
na 29
 
21.8%

남성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
116 
0
15 
2
 
2

Length

Max length4
Median length4
Mean length3.6165414
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 116
87.2%
0 15
 
11.3%
2 2
 
1.5%

Length

2024-05-11T15:23:27.718144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:27.973881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 116
87.2%
0 15
 
11.3%
2 2
 
1.5%

여성종사자수
Categorical

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
116 
0
17 

Length

Max length4
Median length4
Mean length3.6165414
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 116
87.2%
0 17
 
12.8%

Length

2024-05-11T15:23:28.230456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:28.458781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 116
87.2%
0 17
 
12.8%

영업장주변구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
121 
기타
 
11
아파트지역
 
1

Length

Max length5
Median length4
Mean length3.8421053
Min length2

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 121
91.0%
기타 11
 
8.3%
아파트지역 1
 
0.8%

Length

2024-05-11T15:23:28.683272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:28.868482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 121
91.0%
기타 11
 
8.3%
아파트지역 1
 
0.8%

등급구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
121 
기타
 
11
자율
 
1

Length

Max length4
Median length4
Mean length3.8195489
Min length2

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 121
91.0%
기타 11
 
8.3%
자율 1
 
0.8%

Length

2024-05-11T15:23:29.117704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:29.328877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 121
91.0%
기타 11
 
8.3%
자율 1
 
0.8%

급수시설구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
121 
상수도전용
 
12

Length

Max length5
Median length4
Mean length4.0902256
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 121
91.0%
상수도전용 12
 
9.0%

Length

2024-05-11T15:23:29.545661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:29.755413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 121
91.0%
상수도전용 12
 
9.0%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
127 
0
 
6

Length

Max length4
Median length4
Mean length3.8646617
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> 127
95.5%
0 6
 
4.5%

Length

2024-05-11T15:23:29.951461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:30.164181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 127
95.5%
0 6
 
4.5%

본사종업원수
Categorical

IMBALANCE 

Distinct4
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
106 
0
25 
5
 
1
2
 
1

Length

Max length4
Median length4
Mean length3.3909774
Min length1

Unique

Unique2 ?
Unique (%)1.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 106
79.7%
0 25
 
18.8%
5 1
 
0.8%
2 1
 
0.8%

Length

2024-05-11T15:23:30.402668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:30.732131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 106
79.7%
0 25
 
18.8%
5 1
 
0.8%
2 1
 
0.8%

공장사무직종업원수
Categorical

Distinct3
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
106 
0
25 
1
 
2

Length

Max length4
Median length4
Mean length3.3909774
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> 106
79.7%
0 25
 
18.8%
1 2
 
1.5%

Length

2024-05-11T15:23:30.967026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:31.201329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 106
79.7%
0 25
 
18.8%
1 2
 
1.5%

공장판매직종업원수
Categorical

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
108 
0
25 

Length

Max length4
Median length4
Mean length3.4360902
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> 108
81.2%
0 25
 
18.8%

Length

2024-05-11T15:23:31.420747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:31.592294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 108
81.2%
0 25
 
18.8%

공장생산직종업원수
Categorical

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
108 
0
25 

Length

Max length4
Median length4
Mean length3.4360902
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> 108
81.2%
0 25
 
18.8%

Length

2024-05-11T15:23:31.780864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:32.010735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 108
81.2%
0 25
 
18.8%

건물소유구분명
Categorical

Distinct3
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
73 
자가
36 
임대
24 

Length

Max length4
Median length4
Mean length3.0977444
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> 73
54.9%
자가 36
27.1%
임대 24
 
18.0%

Length

2024-05-11T15:23:32.240679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:32.454245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 73
54.9%
자가 36
27.1%
임대 24
 
18.0%

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
119 
0
14 

Length

Max length4
Median length4
Mean length3.6842105
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> 119
89.5%
0 14
 
10.5%

Length

2024-05-11T15:23:32.664747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:32.842725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 119
89.5%
0 14
 
10.5%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
119 
0
14 

Length

Max length4
Median length4
Mean length3.6842105
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> 119
89.5%
0 14
 
10.5%

Length

2024-05-11T15:23:33.067223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:33.255380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 119
89.5%
0 14
 
10.5%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)1.0%
Missing29
Missing (%)21.8%
Memory size398.0 B
False
104 
(Missing)
29 
ValueCountFrequency (%)
False 104
78.2%
(Missing) 29
 
21.8%
2024-05-11T15:23:33.389127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Categorical

IMBALANCE 

Distinct4
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
0.0
102 
<NA>
29 
6.6
 
1
186.0
 
1

Length

Max length5
Median length3
Mean length3.2330827
Min length3

Unique

Unique2 ?
Unique (%)1.5%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 102
76.7%
<NA> 29
 
21.8%
6.6 1
 
0.8%
186.0 1
 
0.8%

Length

2024-05-11T15:23:33.548112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:33.740864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 102
76.7%
na 29
 
21.8%
6.6 1
 
0.8%
186.0 1
 
0.8%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing133
Missing (%)100.0%
Memory size1.3 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing133
Missing (%)100.0%
Memory size1.3 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing133
Missing (%)100.0%
Memory size1.3 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030000003000000-109-1998-0006819980803<NA>3폐업2폐업20030502<NA><NA><NA>02 7370558<NA>110100서울특별시 종로구 교남동 61-2<NA><NA>이조유통2003-05-03 00:00:00I2018-08-31 23:59:59.0식품소분업196748.269537451864.495055식품소분업<NA><NA>기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
130000003000000-109-1998-0016919981223<NA>3폐업2폐업20020108<NA><NA><NA>02 3131957<NA>110848서울특별시 종로구 평창동 471-9<NA><NA>한국유통1998-12-23 00:00:00I2018-08-31 23:59:59.0식품소분업197671.447893457029.354439식품소분업20기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
230000003000000-109-1999-0010819991125<NA>3폐업2폐업20030502<NA><NA><NA>02 3738877<NA>110102서울특별시 종로구 평동 219-0 평동박영빌딩201호<NA><NA>신성애드컴2003-05-03 00:00:00I2018-08-31 23:59:59.0식품소분업196973.061991451580.195594식품소분업00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
330000003000000-109-1999-0014919990903<NA>3폐업2폐업20010202<NA><NA><NA>02 2488464<NA>110862서울특별시 종로구 숭인동 65-11 명경빌딩3층 (핸드폰016)<NA><NA>비엠택2001-02-02 00:00:00I2018-08-31 23:59:59.0식품소분업201330.533468452594.737187식품소분업20기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
430000003000000-109-1999-0021019990518<NA>3폐업2폐업20040804<NA><NA><NA>02 7368140<NA>110043서울특별시 종로구 통인동 5-9<NA><NA>제일수퍼1999-05-18 00:00:00I2018-08-31 23:59:59.0식품소분업197347.974686453196.437979식품소분업00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
530000003000000-109-1999-0021419990531<NA>3폐업2폐업20060719<NA><NA><NA>02 7206625<NA>110054서울특별시 종로구 사직동 54-0<NA><NA>서울상사1999-05-31 00:00:00I2018-08-31 23:59:59.0식품소분업<NA><NA>식품소분업00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
630000003000000-109-1999-0021519990205<NA>3폐업2폐업20050429<NA><NA><NA>0236750628<NA>110522서울특별시 종로구 명륜2가 4 아남아파트상가 지층<NA><NA>스카이마트2005-06-18 00:00:00I2018-08-31 23:59:59.0식품소분업199878.668538453693.071412식품소분업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
730000003000000-109-2000-0007920000217<NA>1영업/정상1영업<NA><NA><NA><NA>02 7392360<NA>110080서울특별시 종로구 무악동 82 무악현대아파트상가 지하1층(지하101호)<NA><NA>현대후레쉬마트2007-02-06 00:00:00I2018-08-31 23:59:59.0식품소분업196467.975088452566.13403식품소분업00아파트지역자율<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
830000003000000-109-2000-0008120000223<NA>3폐업2폐업20100414<NA><NA><NA>02 3967182<NA>110803서울특별시 종로구 구기동 85-9<NA><NA>플러스마트2006-11-20 00:00:00I2018-08-31 23:59:59.0식품소분업196188.676804456211.922749식품소분업00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
930000003000000-109-2000-0023220000412<NA>3폐업2폐업20030502<NA><NA><NA>02 7326373<NA>110300서울특별시 종로구 관훈동 198-1<NA><NA>페어익스체인지2003-05-03 00:00:00I2018-08-31 23:59:59.0식품소분업198594.308615452255.899868식품소분업00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
12330000003000000-109-2023-000022023-03-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA>14.92110-300서울특별시 종로구 관훈동 155-2서울특별시 종로구 인사동길 49, 1층 (관훈동)3145티로아2023-03-30 13:24:40I2022-12-04 00:01:00.0식품소분업198498.918633452473.40375<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
12430000003000000-109-2023-000032023-04-05<NA>1영업/정상1영업<NA><NA><NA><NA><NA>13.24110-524서울특별시 종로구 명륜4가 12-3 4층서울특별시 종로구 대명길 17, 4층 (명륜4가)3078바른 식품2023-04-05 12:18:09I2022-12-04 00:07:00.0식품소분업199984.706065453441.791586<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
12530000003000000-109-2023-000042023-05-10<NA>1영업/정상1영업<NA><NA><NA><NA><NA>39.68110-836서울특별시 종로구 종로5가 280-6 1층서울특별시 종로구 종로40가길 8, 1층 (종로5가)3197맛보는날2023-08-01 14:08:14U2022-12-08 00:03:00.0식품소분업200483.256323452010.993764<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
12630000003000000-109-2023-000052023-08-24<NA>1영업/정상1영업<NA><NA><NA><NA>070 4266531899.72110-044서울특별시 종로구 필운동 163 지하1층서울특별시 종로구 필운대로 12, 지하1층 (필운동)3041(주)케이엠아이2023-08-24 15:07:04I2022-12-07 22:06:00.0식품소분업197231.292852452764.457296<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
12730000003000000-109-2023-000062023-10-24<NA>1영업/정상1영업<NA><NA><NA><NA>02 6964763310.0110-420서울특별시 종로구 관수동 20 국일관드림펠리스 6층서울특별시 종로구 수표로 96, 국일관드림펠리스 6층 (관수동)3192당봄한의원 종로점2023-10-24 14:33:24I2022-10-30 22:06:00.0식품소분업199045.043603451939.677287<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
12830000003000000-109-2024-000012024-01-04<NA>1영업/정상1영업<NA><NA><NA><NA><NA>23.1110-827서울특별시 종로구 숭인동 1086 은진장여관서울특별시 종로구 숭인동길 46, 은진장여관 1층 5호 (숭인동)3111호호박스숭인점2024-01-04 11:45:37I2023-12-01 00:06:00.0식품소분업201890.63628452750.276177<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
12930000003000000-109-2024-000022024-02-01<NA>1영업/정상1영업<NA><NA><NA><NA><NA>143.88110-806서울특별시 종로구 누하동 218서울특별시 종로구 자하문로7길 43, 제지1층 비101,102호 (누하동)3040티피카 주식회사2024-02-01 11:02:28I2023-12-02 00:03:00.0식품소분업197248.014261453000.202393<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
13030000003000000-109-2024-000032024-02-06<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3110-522서울특별시 종로구 명륜2가 21-28 선남빌딩서울특별시 종로구 창경궁로 256, 선남빌딩 4층 F-61호 (명륜2가)3077샤샤샵2024-02-06 11:07:19I2023-12-02 00:08:00.0식품소분업199947.810512453528.912708<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
13130000003000000-109-2024-000042024-03-11<NA>1영업/정상1영업<NA><NA><NA><NA><NA>10.0110-020서울특별시 종로구 홍지동 94-14서울특별시 종로구 세검정로6길 8, 1층 (홍지동)3017테이크파이브(TAKE5)2024-03-11 13:52:27I2023-12-02 23:03:00.0식품소분업196362.382465455364.542277<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
13230000003000000-109-2024-000052024-04-18<NA>1영업/정상1영업<NA><NA><NA><NA><NA>6.45110-320서울특별시 종로구 낙원동 120-1서울특별시 종로구 돈화문로11길 34-6, 1층 (낙원동)3133아진당 떡상점2024-04-18 10:34:38I2023-12-03 22:00:00.0식품소분업199013.050524452284.428699<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>