Overview

Dataset statistics

Number of variables44
Number of observations10000
Missing cells120229
Missing cells (%)27.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 MiB
Average record size in memory385.0 B

Variable types

Numeric8
Text6
DateTime4
Unsupported7
Categorical18
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
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-16095/S/1/datasetView.do

Alerts

위생업태명 is highly imbalanced (63.2%)Imbalance
영업장주변구분명 is highly imbalanced (82.9%)Imbalance
등급구분명 is highly imbalanced (81.8%)Imbalance
급수시설구분명 is highly imbalanced (75.9%)Imbalance
총인원 is highly imbalanced (86.6%)Imbalance
본사종업원수 is highly imbalanced (86.4%)Imbalance
공장사무직종업원수 is highly imbalanced (86.4%)Imbalance
공장판매직종업원수 is highly imbalanced (86.4%)Imbalance
공장생산직종업원수 is highly imbalanced (86.4%)Imbalance
보증액 is highly imbalanced (86.4%)Imbalance
월세액 is highly imbalanced (86.4%)Imbalance
다중이용업소여부 is highly imbalanced (90.9%)Imbalance
전통업소지정번호 is highly imbalanced (99.9%)Imbalance
인허가취소일자 has 10000 (100.0%) missing valuesMissing
폐업일자 has 5517 (55.2%) missing valuesMissing
휴업시작일자 has 10000 (100.0%) missing valuesMissing
휴업종료일자 has 10000 (100.0%) missing valuesMissing
재개업일자 has 10000 (100.0%) missing valuesMissing
전화번호 has 7307 (73.1%) missing valuesMissing
소재지면적 has 1870 (18.7%) missing valuesMissing
도로명주소 has 985 (9.8%) missing valuesMissing
도로명우편번호 has 1018 (10.2%) missing valuesMissing
좌표정보(X) has 343 (3.4%) missing valuesMissing
좌표정보(Y) has 343 (3.4%) missing valuesMissing
남성종사자수 has 8913 (89.1%) missing valuesMissing
여성종사자수 has 8909 (89.1%) missing valuesMissing
건물소유구분명 has 10000 (100.0%) missing valuesMissing
다중이용업소여부 has 7505 (75.0%) missing valuesMissing
시설총규모 has 7505 (75.0%) missing valuesMissing
전통업소주된음식 has 10000 (100.0%) missing valuesMissing
홈페이지 has 10000 (100.0%) missing valuesMissing
남성종사자수 is highly skewed (γ1 = 26.895358)Skewed
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
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 has 171 (1.7%) zerosZeros
남성종사자수 has 968 (9.7%) zerosZeros
여성종사자수 has 672 (6.7%) zerosZeros

Reproduction

Analysis started2024-05-11 05:46:28.846208
Analysis finished2024-05-11 05:46:32.692260
Duration3.85 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Real number (ℝ)

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3112868
Minimum3000000
Maximum3240000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T14:46:32.780541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3000000
Q13010000
median3120000
Q33210000
95-th percentile3240000
Maximum3240000
Range240000
Interquartile range (IQR)200000

Descriptive statistics

Standard deviation88536.989
Coefficient of variation (CV)0.028442256
Kurtosis-1.5337891
Mean3112868
Median Absolute Deviation (MAD)90000
Skewness0.0098970589
Sum3.112868 × 1010
Variance7.8387985 × 109
MonotonicityNot monotonic
2024-05-11T14:46:32.980260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
3000000 1953
19.5%
3220000 869
 
8.7%
3240000 708
 
7.1%
3010000 708
 
7.1%
3230000 506
 
5.1%
3210000 428
 
4.3%
3130000 428
 
4.3%
3180000 425
 
4.2%
3150000 405
 
4.0%
3140000 302
 
3.0%
Other values (15) 3268
32.7%
ValueCountFrequency (%)
3000000 1953
19.5%
3010000 708
 
7.1%
3020000 239
 
2.4%
3030000 204
 
2.0%
3040000 249
 
2.5%
3050000 237
 
2.4%
3060000 186
 
1.9%
3070000 260
 
2.6%
3080000 153
 
1.5%
3090000 138
 
1.4%
ValueCountFrequency (%)
3240000 708
7.1%
3230000 506
5.1%
3220000 869
8.7%
3210000 428
4.3%
3200000 225
 
2.2%
3190000 156
 
1.6%
3180000 425
4.2%
3170000 170
 
1.7%
3160000 262
 
2.6%
3150000 405
4.0%

관리번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T14:46:33.269890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters220000
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

Unique10000 ?
Unique (%)100.0%

Sample

1st row3130000-104-2021-00361
2nd row3000000-104-1999-10805
3rd row3000000-104-2013-00127
4th row3030000-104-1986-00605
5th row3000000-104-2019-00102
ValueCountFrequency (%)
3130000-104-2021-00361 1
 
< 0.1%
3010000-104-2021-00181 1
 
< 0.1%
3220000-104-2022-00363 1
 
< 0.1%
3100000-104-2018-00169 1
 
< 0.1%
3070000-104-2023-00127 1
 
< 0.1%
3220000-104-2022-00247 1
 
< 0.1%
3000000-104-2005-00074 1
 
< 0.1%
3180000-104-2023-00042 1
 
< 0.1%
3000000-104-2012-00018 1
 
< 0.1%
3020000-104-2023-00172 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-05-11T14:46:33.735415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 93171
42.4%
- 30000
 
13.6%
2 24526
 
11.1%
1 23949
 
10.9%
3 16642
 
7.6%
4 14820
 
6.7%
9 4161
 
1.9%
8 3399
 
1.5%
5 3162
 
1.4%
7 3087
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 190000
86.4%
Dash Punctuation 30000
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 93171
49.0%
2 24526
 
12.9%
1 23949
 
12.6%
3 16642
 
8.8%
4 14820
 
7.8%
9 4161
 
2.2%
8 3399
 
1.8%
5 3162
 
1.7%
7 3087
 
1.6%
6 3083
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 30000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 93171
42.4%
- 30000
 
13.6%
2 24526
 
11.1%
1 23949
 
10.9%
3 16642
 
7.6%
4 14820
 
6.7%
9 4161
 
1.9%
8 3399
 
1.5%
5 3162
 
1.4%
7 3087
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 93171
42.4%
- 30000
 
13.6%
2 24526
 
11.1%
1 23949
 
10.9%
3 16642
 
7.6%
4 14820
 
6.7%
9 4161
 
1.9%
8 3399
 
1.5%
5 3162
 
1.4%
7 3087
 
1.4%
Distinct3806
Distinct (%)38.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1965-12-23 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T14:46:33.948158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:46:34.217270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
5517 
3
4483 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 5517
55.2%
3 4483
44.8%

Length

2024-05-11T14:46:34.476499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:46:34.628474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 5517
55.2%
3 4483
44.8%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
영업/정상
5517 
폐업
4483 

Length

Max length5
Median length5
Mean length3.6551
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 5517
55.2%
폐업 4483
44.8%

Length

2024-05-11T14:46:34.801702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:46:34.956885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 5517
55.2%
폐업 4483
44.8%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
5517 
2
4483 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 5517
55.2%
2 4483
44.8%

Length

2024-05-11T14:46:35.124564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:46:35.278786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 5517
55.2%
2 4483
44.8%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
영업
5517 
폐업
4483 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 5517
55.2%
폐업 4483
44.8%

Length

2024-05-11T14:46:35.433297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:46:35.592288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 5517
55.2%
폐업 4483
44.8%

폐업일자
Date

MISSING 

Distinct1949
Distinct (%)43.5%
Missing5517
Missing (%)55.2%
Memory size156.2 KiB
Minimum1983-04-02 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T14:46:35.766916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:46:35.966520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

전화번호
Text

MISSING 

Distinct2418
Distinct (%)89.8%
Missing7307
Missing (%)73.1%
Memory size156.2 KiB
2024-05-11T14:46:36.473971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.604159
Min length1

Characters and Unicode

Total characters28557
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

Unique2312 ?
Unique (%)85.9%

Sample

1st row02 5531811
2nd row02 737 8799
3rd row000207333264
4th row02 3024464
5th row02 8729417
ValueCountFrequency (%)
02 1461
30.2%
070 77
 
1.6%
031 37
 
0.8%
053 24
 
0.5%
758 22
 
0.5%
30151180 20
 
0.4%
0200000000 19
 
0.4%
710 16
 
0.3%
5108 16
 
0.3%
32848112 13
 
0.3%
Other values (2655) 3136
64.8%
2024-05-11T14:46:37.275805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5338
18.7%
2 4761
16.7%
2972
10.4%
7 2607
9.1%
3 2313
8.1%
1 1970
 
6.9%
4 1810
 
6.3%
5 1801
 
6.3%
6 1782
 
6.2%
8 1721
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 25585
89.6%
Space Separator 2972
 
10.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5338
20.9%
2 4761
18.6%
7 2607
10.2%
3 2313
9.0%
1 1970
 
7.7%
4 1810
 
7.1%
5 1801
 
7.0%
6 1782
 
7.0%
8 1721
 
6.7%
9 1482
 
5.8%
Space Separator
ValueCountFrequency (%)
2972
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 28557
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5338
18.7%
2 4761
16.7%
2972
10.4%
7 2607
9.1%
3 2313
8.1%
1 1970
 
6.9%
4 1810
 
6.3%
5 1801
 
6.3%
6 1782
 
6.2%
8 1721
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 28557
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5338
18.7%
2 4761
16.7%
2972
10.4%
7 2607
9.1%
3 2313
8.1%
1 1970
 
6.9%
4 1810
 
6.3%
5 1801
 
6.3%
6 1782
 
6.2%
8 1721
 
6.0%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct3395
Distinct (%)41.8%
Missing1870
Missing (%)18.7%
Infinite0
Infinite (%)0.0%
Mean49.638622
Minimum0
Maximum1124.36
Zeros171
Zeros (%)1.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T14:46:37.537973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.3
Q110
median27.6
Q353.975
95-th percentile198.897
Maximum1124.36
Range1124.36
Interquartile range (IQR)43.975

Descriptive statistics

Standard deviation72.706272
Coefficient of variation (CV)1.4647117
Kurtosis22.507802
Mean49.638622
Median Absolute Deviation (MAD)19.6
Skewness3.8375051
Sum403562
Variance5286.202
MonotonicityNot monotonic
2024-05-11T14:46:37.768770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.3 732
 
7.3%
6.6 275
 
2.8%
10.0 175
 
1.8%
0.0 171
 
1.7%
33.0 126
 
1.3%
20.0 119
 
1.2%
30.0 112
 
1.1%
9.9 92
 
0.9%
15.0 73
 
0.7%
6.0 66
 
0.7%
Other values (3385) 6189
61.9%
(Missing) 1870
 
18.7%
ValueCountFrequency (%)
0.0 171
1.7%
0.1 1
 
< 0.1%
0.5 1
 
< 0.1%
0.9 2
 
< 0.1%
1.0 8
 
0.1%
1.02 1
 
< 0.1%
1.14 1
 
< 0.1%
1.15 2
 
< 0.1%
1.2 1
 
< 0.1%
1.3 1
 
< 0.1%
ValueCountFrequency (%)
1124.36 1
< 0.1%
836.82 1
< 0.1%
810.95 1
< 0.1%
767.5 1
< 0.1%
733.97 1
< 0.1%
684.11 1
< 0.1%
680.0 1
< 0.1%
673.58 1
< 0.1%
619.81 1
< 0.1%
592.13 1
< 0.1%
Distinct3061
Distinct (%)30.6%
Missing7
Missing (%)0.1%
Memory size156.2 KiB
2024-05-11T14:46:38.266472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.5851096
Min length6

Characters and Unicode

Total characters65805
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

Unique1363 ?
Unique (%)13.6%

Sample

1st row121-835
2nd row110530
3rd row110030
4th row133827
5th row110122
ValueCountFrequency (%)
157-210 82
 
0.8%
110111 69
 
0.7%
158-724 68
 
0.7%
110809 62
 
0.6%
110522 59
 
0.6%
135-731 55
 
0.6%
100011 55
 
0.6%
137-713 55
 
0.6%
134-779 54
 
0.5%
120-706 52
 
0.5%
Other values (3051) 9382
93.9%
2024-05-11T14:46:39.063587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15931
24.2%
0 9381
14.3%
8 7567
11.5%
3 6580
10.0%
- 5847
 
8.9%
5 4695
 
7.1%
2 4344
 
6.6%
4 3500
 
5.3%
7 3449
 
5.2%
9 2398
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59958
91.1%
Dash Punctuation 5847
 
8.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15931
26.6%
0 9381
15.6%
8 7567
12.6%
3 6580
11.0%
5 4695
 
7.8%
2 4344
 
7.2%
4 3500
 
5.8%
7 3449
 
5.8%
9 2398
 
4.0%
6 2113
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 5847
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 65805
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 15931
24.2%
0 9381
14.3%
8 7567
11.5%
3 6580
10.0%
- 5847
 
8.9%
5 4695
 
7.1%
2 4344
 
6.6%
4 3500
 
5.3%
7 3449
 
5.2%
9 2398
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 65805
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 15931
24.2%
0 9381
14.3%
8 7567
11.5%
3 6580
10.0%
- 5847
 
8.9%
5 4695
 
7.1%
2 4344
 
6.6%
4 3500
 
5.3%
7 3449
 
5.2%
9 2398
 
3.6%
Distinct8187
Distinct (%)81.9%
Missing7
Missing (%)0.1%
Memory size156.2 KiB
2024-05-11T14:46:39.662542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length54
Mean length24.525668
Min length14

Characters and Unicode

Total characters245085
Distinct characters665
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7666 ?
Unique (%)76.7%

Sample

1st row서울특별시 마포구 상암동 1597 사보이시티디엠씨
2nd row서울특별시 종로구 혜화동 185-0번지 중원빌딩102호
3rd row서울특별시 종로구 청운동 59-5번지
4th row서울특별시 성동구 성수동2가 321-85번지
5th row서울특별시 종로구 종로2가 40번지 육의전빌딩
ValueCountFrequency (%)
서울특별시 9992
 
20.4%
종로구 1950
 
4.0%
1층 973
 
2.0%
강남구 869
 
1.8%
강동구 708
 
1.4%
중구 708
 
1.4%
송파구 506
 
1.0%
서초구 428
 
0.9%
마포구 427
 
0.9%
영등포구 424
 
0.9%
Other values (10179) 31929
65.3%
2024-05-11T14:46:40.540041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
41356
 
16.9%
11593
 
4.7%
1 11188
 
4.6%
11091
 
4.5%
10556
 
4.3%
10370
 
4.2%
10131
 
4.1%
10000
 
4.1%
9996
 
4.1%
- 7572
 
3.1%
Other values (655) 111232
45.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 148734
60.7%
Decimal Number 45109
 
18.4%
Space Separator 41356
 
16.9%
Dash Punctuation 7572
 
3.1%
Uppercase Letter 975
 
0.4%
Other Punctuation 374
 
0.2%
Open Punctuation 366
 
0.1%
Close Punctuation 365
 
0.1%
Lowercase Letter 145
 
0.1%
Math Symbol 69
 
< 0.1%
Other values (3) 20
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
11593
 
7.8%
11091
 
7.5%
10556
 
7.1%
10370
 
7.0%
10131
 
6.8%
10000
 
6.7%
9996
 
6.7%
3488
 
2.3%
3154
 
2.1%
2467
 
1.7%
Other values (583) 65888
44.3%
Uppercase Letter
ValueCountFrequency (%)
B 116
11.9%
C 85
 
8.7%
E 84
 
8.6%
S 83
 
8.5%
T 81
 
8.3%
A 69
 
7.1%
D 65
 
6.7%
K 38
 
3.9%
M 38
 
3.9%
N 37
 
3.8%
Other values (16) 279
28.6%
Lowercase Letter
ValueCountFrequency (%)
e 32
22.1%
r 15
10.3%
a 11
 
7.6%
t 10
 
6.9%
n 10
 
6.9%
i 10
 
6.9%
l 9
 
6.2%
o 8
 
5.5%
w 8
 
5.5%
c 7
 
4.8%
Other values (9) 25
17.2%
Decimal Number
ValueCountFrequency (%)
1 11188
24.8%
2 6011
13.3%
3 4607
10.2%
4 4035
 
8.9%
5 3920
 
8.7%
0 3663
 
8.1%
6 3291
 
7.3%
9 3046
 
6.8%
7 2843
 
6.3%
8 2505
 
5.6%
Other Punctuation
ValueCountFrequency (%)
, 346
92.5%
. 13
 
3.5%
& 5
 
1.3%
? 4
 
1.1%
/ 4
 
1.1%
' 1
 
0.3%
: 1
 
0.3%
Letter Number
ValueCountFrequency (%)
10
55.6%
6
33.3%
2
 
11.1%
Space Separator
ValueCountFrequency (%)
41356
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7572
100.0%
Open Punctuation
ValueCountFrequency (%)
( 366
100.0%
Close Punctuation
ValueCountFrequency (%)
) 365
100.0%
Math Symbol
ValueCountFrequency (%)
~ 69
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 148734
60.7%
Common 95212
38.8%
Latin 1138
 
0.5%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
11593
 
7.8%
11091
 
7.5%
10556
 
7.1%
10370
 
7.0%
10131
 
6.8%
10000
 
6.7%
9996
 
6.7%
3488
 
2.3%
3154
 
2.1%
2467
 
1.7%
Other values (583) 65888
44.3%
Latin
ValueCountFrequency (%)
B 116
 
10.2%
C 85
 
7.5%
E 84
 
7.4%
S 83
 
7.3%
T 81
 
7.1%
A 69
 
6.1%
D 65
 
5.7%
K 38
 
3.3%
M 38
 
3.3%
N 37
 
3.3%
Other values (38) 442
38.8%
Common
ValueCountFrequency (%)
41356
43.4%
1 11188
 
11.8%
- 7572
 
8.0%
2 6011
 
6.3%
3 4607
 
4.8%
4 4035
 
4.2%
5 3920
 
4.1%
0 3663
 
3.8%
6 3291
 
3.5%
9 3046
 
3.2%
Other values (13) 6523
 
6.9%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 148733
60.7%
ASCII 96332
39.3%
Number Forms 18
 
< 0.1%
None 1
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
41356
42.9%
1 11188
 
11.6%
- 7572
 
7.9%
2 6011
 
6.2%
3 4607
 
4.8%
4 4035
 
4.2%
5 3920
 
4.1%
0 3663
 
3.8%
6 3291
 
3.4%
9 3046
 
3.2%
Other values (58) 7643
 
7.9%
Hangul
ValueCountFrequency (%)
11593
 
7.8%
11091
 
7.5%
10556
 
7.1%
10370
 
7.0%
10131
 
6.8%
10000
 
6.7%
9996
 
6.7%
3488
 
2.3%
3154
 
2.1%
2467
 
1.7%
Other values (582) 65887
44.3%
Number Forms
ValueCountFrequency (%)
10
55.6%
6
33.3%
2
 
11.1%
None
ValueCountFrequency (%)
1
100.0%
CJK
ValueCountFrequency (%)
1
100.0%

도로명주소
Text

MISSING 

Distinct7941
Distinct (%)88.1%
Missing985
Missing (%)9.8%
Memory size156.2 KiB
2024-05-11T14:46:41.123234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length68
Median length60
Mean length35.56772
Min length20

Characters and Unicode

Total characters320643
Distinct characters707
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7661 ?
Unique (%)85.0%

Sample

1st row서울특별시 마포구 월드컵북로54길 17, 사보이시티디엠씨 2층 222호 (상암동)
2nd row서울특별시 종로구 자하문로33길 10, 1층 (청운동)
3rd row서울특별시 성동구 성수일로4길 52 (성수동2가)
4th row서울특별시 종로구 수표로 105, 육의전빌딩 지하2층 (종로2가)
5th row서울특별시 서대문구 수색로 56, 성공타워1 122,123호 (북가좌동)
ValueCountFrequency (%)
서울특별시 9014
 
14.3%
1층 4116
 
6.5%
지하1층 1285
 
2.0%
종로구 1229
 
2.0%
강남구 860
 
1.4%
강동구 703
 
1.1%
중구 573
 
0.9%
지상1층 521
 
0.8%
송파구 502
 
0.8%
101호 454
 
0.7%
Other values (9154) 43671
69.4%
2024-05-11T14:46:41.898284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
53945
 
16.8%
1 17495
 
5.5%
11839
 
3.7%
10936
 
3.4%
10771
 
3.4%
, 10603
 
3.3%
9757
 
3.0%
9476
 
3.0%
) 9241
 
2.9%
( 9240
 
2.9%
Other values (697) 167340
52.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 185353
57.8%
Space Separator 53945
 
16.8%
Decimal Number 49193
 
15.3%
Other Punctuation 10644
 
3.3%
Close Punctuation 9242
 
2.9%
Open Punctuation 9241
 
2.9%
Uppercase Letter 1530
 
0.5%
Dash Punctuation 1165
 
0.4%
Lowercase Letter 183
 
0.1%
Math Symbol 127
 
< 0.1%
Other values (2) 20
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
11839
 
6.4%
10936
 
5.9%
10771
 
5.8%
9757
 
5.3%
9476
 
5.1%
9230
 
5.0%
9023
 
4.9%
9018
 
4.9%
7942
 
4.3%
4120
 
2.2%
Other values (623) 93241
50.3%
Uppercase Letter
ValueCountFrequency (%)
B 351
22.9%
A 171
11.2%
C 125
 
8.2%
S 117
 
7.6%
E 99
 
6.5%
D 98
 
6.4%
T 88
 
5.8%
M 45
 
2.9%
G 41
 
2.7%
N 41
 
2.7%
Other values (16) 354
23.1%
Lowercase Letter
ValueCountFrequency (%)
e 35
19.1%
b 21
11.5%
r 17
9.3%
a 14
 
7.7%
t 13
 
7.1%
l 11
 
6.0%
o 10
 
5.5%
w 9
 
4.9%
n 8
 
4.4%
s 8
 
4.4%
Other values (10) 37
20.2%
Decimal Number
ValueCountFrequency (%)
1 17495
35.6%
2 6538
 
13.3%
3 4708
 
9.6%
0 4701
 
9.6%
4 3362
 
6.8%
5 3189
 
6.5%
6 2845
 
5.8%
7 2441
 
5.0%
8 2136
 
4.3%
9 1778
 
3.6%
Other Punctuation
ValueCountFrequency (%)
, 10603
99.6%
. 21
 
0.2%
& 8
 
0.1%
/ 5
 
< 0.1%
? 5
 
< 0.1%
! 1
 
< 0.1%
* 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
10
52.6%
7
36.8%
2
 
10.5%
Close Punctuation
ValueCountFrequency (%)
) 9241
> 99.9%
] 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 9240
> 99.9%
[ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
53945
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1165
100.0%
Math Symbol
ValueCountFrequency (%)
~ 127
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 185353
57.8%
Common 133557
41.7%
Latin 1732
 
0.5%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
11839
 
6.4%
10936
 
5.9%
10771
 
5.8%
9757
 
5.3%
9476
 
5.1%
9230
 
5.0%
9023
 
4.9%
9018
 
4.9%
7942
 
4.3%
4120
 
2.2%
Other values (623) 93241
50.3%
Latin
ValueCountFrequency (%)
B 351
20.3%
A 171
 
9.9%
C 125
 
7.2%
S 117
 
6.8%
E 99
 
5.7%
D 98
 
5.7%
T 88
 
5.1%
M 45
 
2.6%
G 41
 
2.4%
N 41
 
2.4%
Other values (39) 556
32.1%
Common
ValueCountFrequency (%)
53945
40.4%
1 17495
 
13.1%
, 10603
 
7.9%
) 9241
 
6.9%
( 9240
 
6.9%
2 6538
 
4.9%
3 4708
 
3.5%
0 4701
 
3.5%
4 3362
 
2.5%
5 3189
 
2.4%
Other values (14) 10535
 
7.9%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 185351
57.8%
ASCII 135270
42.2%
Number Forms 19
 
< 0.1%
CJK 1
 
< 0.1%
Compat Jamo 1
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
53945
39.9%
1 17495
 
12.9%
, 10603
 
7.8%
) 9241
 
6.8%
( 9240
 
6.8%
2 6538
 
4.8%
3 4708
 
3.5%
0 4701
 
3.5%
4 3362
 
2.5%
5 3189
 
2.4%
Other values (60) 12248
 
9.1%
Hangul
ValueCountFrequency (%)
11839
 
6.4%
10936
 
5.9%
10771
 
5.8%
9757
 
5.3%
9476
 
5.1%
9230
 
5.0%
9023
 
4.9%
9018
 
4.9%
7942
 
4.3%
4120
 
2.2%
Other values (621) 93239
50.3%
Number Forms
ValueCountFrequency (%)
10
52.6%
7
36.8%
2
 
10.5%
CJK
ValueCountFrequency (%)
1
100.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%
None
ValueCountFrequency (%)
1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct3055
Distinct (%)34.0%
Missing1018
Missing (%)10.2%
Infinite0
Infinite (%)0.0%
Mean5033.4163
Minimum1000
Maximum21349
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T14:46:42.438381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1000
5-th percentile1791.05
Q13180
median5039
Q36546
95-th percentile8340.65
Maximum21349
Range20349
Interquartile range (IQR)3366

Descriptive statistics

Standard deviation2005.6096
Coefficient of variation (CV)0.39845891
Kurtosis-0.47651483
Mean5033.4163
Median Absolute Deviation (MAD)1695
Skewness0.13374792
Sum45210145
Variance4022469.8
MonotonicityNot monotonic
2024-05-11T14:46:42.690592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6164 142
 
1.4%
4530 139
 
1.4%
6546 126
 
1.3%
5328 89
 
0.9%
7998 84
 
0.8%
4533 76
 
0.8%
3789 69
 
0.7%
8209 63
 
0.6%
5554 54
 
0.5%
7305 51
 
0.5%
Other values (3045) 8089
80.9%
(Missing) 1018
 
10.2%
ValueCountFrequency (%)
1000 2
< 0.1%
1002 1
< 0.1%
1004 1
< 0.1%
1005 1
< 0.1%
1006 2
< 0.1%
1009 1
< 0.1%
1010 1
< 0.1%
1014 1
< 0.1%
1022 1
< 0.1%
1025 1
< 0.1%
ValueCountFrequency (%)
21349 1
 
< 0.1%
8864 3
< 0.1%
8861 1
 
< 0.1%
8860 3
< 0.1%
8859 2
< 0.1%
8857 1
 
< 0.1%
8854 3
< 0.1%
8852 1
 
< 0.1%
8851 1
 
< 0.1%
8850 1
 
< 0.1%
Distinct9120
Distinct (%)91.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T14:46:43.193916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length32
Mean length8.8445
Min length1

Characters and Unicode

Total characters88445
Distinct characters1084
Distinct categories15 ?
Distinct scripts4 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8762 ?
Unique (%)87.6%

Sample

1st row요거넛 넘버나인(NO.9)
2nd row미스터피자
3rd row바오밥나무
4th row유정커피숍
5th row피앤티스퀘어
ValueCountFrequency (%)
세븐일레븐 245
 
1.5%
카페 225
 
1.4%
씨유 219
 
1.4%
스타벅스 186
 
1.2%
gs25 110
 
0.7%
메가엠지씨커피 104
 
0.7%
coffee 99
 
0.6%
지에스25 95
 
0.6%
주식회사 89
 
0.6%
리은푸드 83
 
0.5%
Other values (10283) 14450
90.9%
2024-05-11T14:46:43.967921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5917
 
6.7%
3722
 
4.2%
2707
 
3.1%
) 1958
 
2.2%
( 1951
 
2.2%
1823
 
2.1%
1367
 
1.5%
1283
 
1.5%
1176
 
1.3%
953
 
1.1%
Other values (1074) 65588
74.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 66168
74.8%
Space Separator 5917
 
6.7%
Lowercase Letter 5259
 
5.9%
Uppercase Letter 4908
 
5.5%
Close Punctuation 1958
 
2.2%
Open Punctuation 1951
 
2.2%
Decimal Number 1907
 
2.2%
Other Punctuation 315
 
0.4%
Dash Punctuation 37
 
< 0.1%
Connector Punctuation 13
 
< 0.1%
Other values (5) 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3722
 
5.6%
2707
 
4.1%
1823
 
2.8%
1367
 
2.1%
1283
 
1.9%
1176
 
1.8%
953
 
1.4%
887
 
1.3%
775
 
1.2%
768
 
1.2%
Other values (989) 50707
76.6%
Lowercase Letter
ValueCountFrequency (%)
e 879
16.7%
o 520
 
9.9%
a 496
 
9.4%
f 350
 
6.7%
n 304
 
5.8%
r 289
 
5.5%
c 288
 
5.5%
i 263
 
5.0%
s 257
 
4.9%
t 244
 
4.6%
Other values (16) 1369
26.0%
Uppercase Letter
ValueCountFrequency (%)
C 497
 
10.1%
S 492
 
10.0%
E 426
 
8.7%
A 368
 
7.5%
G 364
 
7.4%
O 296
 
6.0%
F 228
 
4.6%
R 206
 
4.2%
T 205
 
4.2%
P 203
 
4.1%
Other values (16) 1623
33.1%
Other Punctuation
ValueCountFrequency (%)
& 83
26.3%
. 55
17.5%
? 51
16.2%
' 40
12.7%
, 40
12.7%
/ 13
 
4.1%
: 12
 
3.8%
! 10
 
3.2%
# 7
 
2.2%
% 3
 
1.0%
Decimal Number
ValueCountFrequency (%)
2 637
33.4%
5 450
23.6%
1 205
 
10.7%
4 157
 
8.2%
3 138
 
7.2%
9 76
 
4.0%
0 76
 
4.0%
7 71
 
3.7%
8 50
 
2.6%
6 47
 
2.5%
Letter Number
ValueCountFrequency (%)
3
75.0%
1
 
25.0%
Other Symbol
ValueCountFrequency (%)
2
66.7%
1
33.3%
Space Separator
ValueCountFrequency (%)
5917
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1958
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1951
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 37
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 13
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 2
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%
Other Number
ValueCountFrequency (%)
² 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 66154
74.8%
Common 12104
 
13.7%
Latin 10171
 
11.5%
Han 16
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3722
 
5.6%
2707
 
4.1%
1823
 
2.8%
1367
 
2.1%
1283
 
1.9%
1176
 
1.8%
953
 
1.4%
887
 
1.3%
775
 
1.2%
768
 
1.2%
Other values (974) 50693
76.6%
Latin
ValueCountFrequency (%)
e 879
 
8.6%
o 520
 
5.1%
C 497
 
4.9%
a 496
 
4.9%
S 492
 
4.8%
E 426
 
4.2%
A 368
 
3.6%
G 364
 
3.6%
f 350
 
3.4%
n 304
 
3.0%
Other values (44) 5475
53.8%
Common
ValueCountFrequency (%)
5917
48.9%
) 1958
 
16.2%
( 1951
 
16.1%
2 637
 
5.3%
5 450
 
3.7%
1 205
 
1.7%
4 157
 
1.3%
3 138
 
1.1%
& 83
 
0.7%
9 76
 
0.6%
Other values (20) 532
 
4.4%
Han
ValueCountFrequency (%)
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
Other values (6) 6
37.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 66145
74.8%
ASCII 22269
 
25.2%
CJK 13
 
< 0.1%
Compat Jamo 7
 
< 0.1%
Number Forms 4
 
< 0.1%
None 3
 
< 0.1%
CJK Compat Ideographs 3
 
< 0.1%
Letterlike Symbols 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5917
26.6%
) 1958
 
8.8%
( 1951
 
8.8%
e 879
 
3.9%
2 637
 
2.9%
o 520
 
2.3%
C 497
 
2.2%
a 496
 
2.2%
S 492
 
2.2%
5 450
 
2.0%
Other values (70) 8472
38.0%
Hangul
ValueCountFrequency (%)
3722
 
5.6%
2707
 
4.1%
1823
 
2.8%
1367
 
2.1%
1283
 
1.9%
1176
 
1.8%
953
 
1.4%
887
 
1.3%
775
 
1.2%
768
 
1.2%
Other values (968) 50684
76.6%
Number Forms
ValueCountFrequency (%)
3
75.0%
1
 
25.0%
Compat Jamo
ValueCountFrequency (%)
3
42.9%
1
 
14.3%
1
 
14.3%
1
 
14.3%
1
 
14.3%
None
ValueCountFrequency (%)
2
66.7%
² 1
33.3%
CJK
ValueCountFrequency (%)
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
Other values (3) 3
23.1%
CJK Compat Ideographs
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Letterlike Symbols
ValueCountFrequency (%)
1
100.0%
Distinct9042
Distinct (%)90.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1999-01-07 00:00:00
Maximum2024-05-09 17:08:02
2024-05-11T14:46:44.180113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:46:44.397208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
U
5424 
I
4574 
D
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 5424
54.2%
I 4574
45.7%
D 2
 
< 0.1%

Length

2024-05-11T14:46:44.636786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:46:44.820511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 5424
54.2%
i 4574
45.7%
d 2
 
< 0.1%
Distinct1196
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T14:46:45.036323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:46:45.269979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct18
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
커피숍
3837 
기타 휴게음식점
2221 
편의점
1006 
일반조리판매
988 
다방
630 
Other values (13)
1318 

Length

Max length8
Median length3
Mean length4.4604
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row기타 휴게음식점
2nd row패스트푸드
3rd row커피숍
4th row다방
5th row커피숍

Common Values

ValueCountFrequency (%)
커피숍 3837
38.4%
기타 휴게음식점 2221
22.2%
편의점 1006
 
10.1%
일반조리판매 988
 
9.9%
다방 630
 
6.3%
백화점 429
 
4.3%
패스트푸드 364
 
3.6%
과자점 152
 
1.5%
푸드트럭 112
 
1.1%
아이스크림 95
 
0.9%
Other values (8) 166
 
1.7%

Length

2024-05-11T14:46:45.502306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
커피숍 3837
31.4%
기타 2221
18.2%
휴게음식점 2221
18.2%
편의점 1006
 
8.2%
일반조리판매 988
 
8.1%
다방 630
 
5.2%
백화점 429
 
3.5%
패스트푸드 364
 
3.0%
과자점 152
 
1.2%
푸드트럭 112
 
0.9%
Other values (9) 261
 
2.1%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct6899
Distinct (%)71.4%
Missing343
Missing (%)3.4%
Infinite0
Infinite (%)0.0%
Mean199647.58
Minimum176792.47
Maximum215927.69
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T14:46:45.723475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum176792.47
5-th percentile187441.25
Q1194408.14
median199752.61
Q3204538.14
95-th percentile211542.88
Maximum215927.69
Range39135.221
Interquartile range (IQR)10130.004

Descriptive statistics

Standard deviation7014.1898
Coefficient of variation (CV)0.035132857
Kurtosis-0.48949689
Mean199647.58
Median Absolute Deviation (MAD)4959.6684
Skewness-0.087378737
Sum1.9279967 × 109
Variance49198859
MonotonicityNot monotonic
2024-05-11T14:46:46.011105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
198263.90839194 139
 
1.4%
200250.447804795 126
 
1.3%
205130.591678902 86
 
0.9%
188884.075622342 84
 
0.8%
198259.65357739 83
 
0.8%
210929.919693661 72
 
0.7%
194265.067639805 63
 
0.6%
190107.045415333 62
 
0.6%
208589.363343145 55
 
0.5%
205210.358779172 53
 
0.5%
Other values (6889) 8834
88.3%
(Missing) 343
 
3.4%
ValueCountFrequency (%)
176792.467792121 1
 
< 0.1%
182086.388313239 1
 
< 0.1%
182524.823835629 13
0.1%
182797.996662976 1
 
< 0.1%
182849.273281599 1
 
< 0.1%
182876.367858149 1
 
< 0.1%
182899.542076002 1
 
< 0.1%
182974.850127567 1
 
< 0.1%
183007.220061564 1
 
< 0.1%
183013.939535662 1
 
< 0.1%
ValueCountFrequency (%)
215927.688523964 1
< 0.1%
215898.113091143 1
< 0.1%
215728.497758 1
< 0.1%
215661.222623 1
< 0.1%
215527.721278 1
< 0.1%
215502.593610945 2
< 0.1%
215487.94428281 1
< 0.1%
215426.028109 1
< 0.1%
215423.76462869 2
< 0.1%
215422.746119624 1
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct6899
Distinct (%)71.4%
Missing343
Missing (%)3.4%
Infinite0
Infinite (%)0.0%
Mean449760.53
Minimum436893.31
Maximum465175.42
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T14:46:46.253311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum436893.31
5-th percentile442250.02
Q1445970.31
median450314.27
Q3452451.56
95-th percentile458114.84
Maximum465175.42
Range28282.108
Interquartile range (IQR)6481.2551

Descriptive statistics

Standard deviation4757.2241
Coefficient of variation (CV)0.010577238
Kurtosis0.0031144015
Mean449760.53
Median Absolute Deviation (MAD)3009.1832
Skewness0.25059461
Sum4.3433375 × 109
Variance22631181
MonotonicityNot monotonic
2024-05-11T14:46:46.481303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
450960.762964932 139
 
1.4%
444683.220506107 126
 
1.3%
445590.096837802 86
 
0.9%
447186.888604306 84
 
0.8%
451392.198218657 83
 
0.8%
448537.406728283 72
 
0.7%
450433.691021245 63
 
0.6%
445157.626366229 62
 
0.6%
445455.90405262 55
 
0.5%
445154.42225208 53
 
0.5%
Other values (6889) 8834
88.3%
(Missing) 343
 
3.4%
ValueCountFrequency (%)
436893.312157815 1
< 0.1%
437299.637939286 1
< 0.1%
437560.573323753 1
< 0.1%
437653.308606196 1
< 0.1%
437773.047519431 1
< 0.1%
437898.766330059 1
< 0.1%
437959.961132488 1
< 0.1%
438012.1279662 1
< 0.1%
438046.941961006 1
< 0.1%
438299.627768186 1
< 0.1%
ValueCountFrequency (%)
465175.420371013 1
< 0.1%
465029.008416693 1
< 0.1%
465025.246646886 1
< 0.1%
465014.07337341 1
< 0.1%
464942.358410473 1
< 0.1%
464866.74995962 1
< 0.1%
464814.717432497 1
< 0.1%
464714.276766904 1
< 0.1%
464664.845668554 1
< 0.1%
464591.516973411 1
< 0.1%

위생업태명
Categorical

IMBALANCE 

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7505 
커피숍
 
713
다방
 
587
기타 휴게음식점
 
389
일반조리판매
 
242
Other values (12)
 
564

Length

Max length8
Median length4
Mean length3.995
Min length2

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7505
75.0%
커피숍 713
 
7.1%
다방 587
 
5.9%
기타 휴게음식점 389
 
3.9%
일반조리판매 242
 
2.4%
편의점 183
 
1.8%
패스트푸드 141
 
1.4%
과자점 138
 
1.4%
전통찻집 41
 
0.4%
백화점 26
 
0.3%
Other values (7) 35
 
0.4%

Length

2024-05-11T14:46:46.707381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 7505
72.2%
커피숍 713
 
6.9%
다방 587
 
5.7%
기타 389
 
3.7%
휴게음식점 389
 
3.7%
일반조리판매 242
 
2.3%
편의점 183
 
1.8%
패스트푸드 141
 
1.4%
과자점 138
 
1.3%
전통찻집 41
 
0.4%
Other values (8) 61
 
0.6%

남성종사자수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct8
Distinct (%)0.7%
Missing8913
Missing (%)89.1%
Infinite0
Infinite (%)0.0%
Mean0.19871205
Minimum0
Maximum46
Zeros968
Zeros (%)9.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T14:46:46.888104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum46
Range46
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.4924852
Coefficient of variation (CV)7.5107937
Kurtosis818.80546
Mean0.19871205
Median Absolute Deviation (MAD)0
Skewness26.895358
Sum216
Variance2.2275122
MonotonicityNot monotonic
2024-05-11T14:46:47.055163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 968
 
9.7%
1 87
 
0.9%
2 20
 
0.2%
3 5
 
0.1%
4 3
 
< 0.1%
5 2
 
< 0.1%
46 1
 
< 0.1%
6 1
 
< 0.1%
(Missing) 8913
89.1%
ValueCountFrequency (%)
0 968
9.7%
1 87
 
0.9%
2 20
 
0.2%
3 5
 
0.1%
4 3
 
< 0.1%
5 2
 
< 0.1%
6 1
 
< 0.1%
46 1
 
< 0.1%
ValueCountFrequency (%)
46 1
 
< 0.1%
6 1
 
< 0.1%
5 2
 
< 0.1%
4 3
 
< 0.1%
3 5
 
0.1%
2 20
 
0.2%
1 87
 
0.9%
0 968
9.7%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)0.9%
Missing8909
Missing (%)89.1%
Infinite0
Infinite (%)0.0%
Mean0.86434464
Minimum0
Maximum12
Zeros672
Zeros (%)6.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T14:46:47.200764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile3
Maximum12
Range12
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.2971115
Coefficient of variation (CV)1.5006878
Kurtosis7.1891055
Mean0.86434464
Median Absolute Deviation (MAD)0
Skewness1.9006859
Sum943
Variance1.6824982
MonotonicityNot monotonic
2024-05-11T14:46:47.354704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 672
 
6.7%
2 172
 
1.7%
3 119
 
1.2%
1 98
 
1.0%
4 22
 
0.2%
5 3
 
< 0.1%
6 2
 
< 0.1%
12 1
 
< 0.1%
10 1
 
< 0.1%
7 1
 
< 0.1%
(Missing) 8909
89.1%
ValueCountFrequency (%)
0 672
6.7%
1 98
 
1.0%
2 172
 
1.7%
3 119
 
1.2%
4 22
 
0.2%
5 3
 
< 0.1%
6 2
 
< 0.1%
7 1
 
< 0.1%
10 1
 
< 0.1%
12 1
 
< 0.1%
ValueCountFrequency (%)
12 1
 
< 0.1%
10 1
 
< 0.1%
7 1
 
< 0.1%
6 2
 
< 0.1%
5 3
 
< 0.1%
4 22
 
0.2%
3 119
 
1.2%
2 172
 
1.7%
1 98
 
1.0%
0 672
6.7%

영업장주변구분명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9153 
기타
 
675
유흥업소밀집지역
 
75
주택가주변
 
64
학교정화(상대)
 
16
Other values (3)
 
17

Length

Max length8
Median length4
Mean length3.911
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9153
91.5%
기타 675
 
6.8%
유흥업소밀집지역 75
 
0.8%
주택가주변 64
 
0.6%
학교정화(상대) 16
 
0.2%
아파트지역 11
 
0.1%
결혼예식장주변 3
 
< 0.1%
학교정화(절대) 3
 
< 0.1%

Length

2024-05-11T14:46:47.537456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:46:47.695315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9153
91.5%
기타 675
 
6.8%
유흥업소밀집지역 75
 
0.8%
주택가주변 64
 
0.6%
학교정화(상대 16
 
0.2%
아파트지역 11
 
0.1%
결혼예식장주변 3
 
< 0.1%
학교정화(절대 3
 
< 0.1%

등급구분명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9231 
기타
 
324
 
240
자율
 
98
지도
 
63
Other values (3)
 
44

Length

Max length4
Median length4
Mean length3.8193
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9231
92.3%
기타 324
 
3.2%
240
 
2.4%
자율 98
 
1.0%
지도 63
 
0.6%
29
 
0.3%
우수 10
 
0.1%
관리 5
 
0.1%

Length

2024-05-11T14:46:47.938445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:46:48.149274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9231
92.3%
기타 324
 
3.2%
240
 
2.4%
자율 98
 
1.0%
지도 63
 
0.6%
29
 
0.3%
우수 10
 
0.1%
관리 5
 
< 0.1%

급수시설구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8972 
상수도전용
1023 
상수도(음용)지하수(주방용)겸용
 
4
간이상수도
 
1

Length

Max length17
Median length4
Mean length4.1076
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8972
89.7%
상수도전용 1023
 
10.2%
상수도(음용)지하수(주방용)겸용 4
 
< 0.1%
간이상수도 1
 
< 0.1%

Length

2024-05-11T14:46:48.391420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:46:48.565212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8972
89.7%
상수도전용 1023
 
10.2%
상수도(음용)지하수(주방용)겸용 4
 
< 0.1%
간이상수도 1
 
< 0.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9814 
0
 
186

Length

Max length4
Median length4
Mean length3.9442
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> 9814
98.1%
0 186
 
1.9%

Length

2024-05-11T14:46:48.780659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:46:48.946904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9814
98.1%
0 186
 
1.9%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9809 
0
 
191

Length

Max length4
Median length4
Mean length3.9427
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> 9809
98.1%
0 191
 
1.9%

Length

2024-05-11T14:46:49.107988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:46:49.266475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9809
98.1%
0 191
 
1.9%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9809 
0
 
191

Length

Max length4
Median length4
Mean length3.9427
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> 9809
98.1%
0 191
 
1.9%

Length

2024-05-11T14:46:49.448089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:46:49.626643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9809
98.1%
0 191
 
1.9%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9809 
0
 
191

Length

Max length4
Median length4
Mean length3.9427
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> 9809
98.1%
0 191
 
1.9%

Length

2024-05-11T14:46:49.789298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:46:49.966743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9809
98.1%
0 191
 
1.9%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9809 
0
 
191

Length

Max length4
Median length4
Mean length3.9427
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> 9809
98.1%
0 191
 
1.9%

Length

2024-05-11T14:46:50.165305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:46:50.355552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9809
98.1%
0 191
 
1.9%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9809 
0
 
191

Length

Max length4
Median length4
Mean length3.9427
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> 9809
98.1%
0 191
 
1.9%

Length

2024-05-11T14:46:50.656132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:46:50.835474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9809
98.1%
0 191
 
1.9%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9809 
0
 
191

Length

Max length4
Median length4
Mean length3.9427
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> 9809
98.1%
0 191
 
1.9%

Length

2024-05-11T14:46:51.010215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:46:51.187015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9809
98.1%
0 191
 
1.9%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.1%
Missing7505
Missing (%)75.0%
Memory size97.7 KiB
False
2466 
True
 
29
(Missing)
7505 
ValueCountFrequency (%)
False 2466
 
24.7%
True 29
 
0.3%
(Missing) 7505
75.0%
2024-05-11T14:46:51.296535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING 

Distinct1513
Distinct (%)60.6%
Missing7505
Missing (%)75.0%
Infinite0
Infinite (%)0.0%
Mean53.105042
Minimum0
Maximum1096.62
Zeros91
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T14:46:51.881226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q112
median33
Q370.11
95-th percentile165.587
Maximum1096.62
Range1096.62
Interquartile range (IQR)58.11

Descriptive statistics

Standard deviation67.484743
Coefficient of variation (CV)1.2707784
Kurtosis41.382133
Mean53.105042
Median Absolute Deviation (MAD)24.75
Skewness4.5350455
Sum132497.08
Variance4554.1905
MonotonicityNot monotonic
2024-05-11T14:46:52.096539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.3 128
 
1.3%
0.0 91
 
0.9%
6.6 53
 
0.5%
10.0 49
 
0.5%
9.9 30
 
0.3%
33.0 25
 
0.2%
9.0 24
 
0.2%
16.5 22
 
0.2%
13.2 21
 
0.2%
6.0 18
 
0.2%
Other values (1503) 2034
 
20.3%
(Missing) 7505
75.0%
ValueCountFrequency (%)
0.0 91
0.9%
1.3 1
 
< 0.1%
1.5 2
 
< 0.1%
1.65 1
 
< 0.1%
2.0 7
 
0.1%
2.24 1
 
< 0.1%
2.36 1
 
< 0.1%
2.4 1
 
< 0.1%
2.45 1
 
< 0.1%
2.5 1
 
< 0.1%
ValueCountFrequency (%)
1096.62 1
< 0.1%
881.81 1
< 0.1%
695.47 1
< 0.1%
530.68 1
< 0.1%
514.86 1
< 0.1%
439.68 1
< 0.1%
422.3 1
< 0.1%
417.99 1
< 0.1%
414.25 1
< 0.1%
403.26 1
< 0.1%

전통업소지정번호
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9999 
0
 
1

Length

Max length4
Median length4
Mean length3.9997
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9999
> 99.9%
0 1
 
< 0.1%

Length

2024-05-11T14:46:52.309947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:46:52.465576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9999
> 99.9%
0 1
 
< 0.1%

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
679531300003130000-104-2021-003612021-11-18<NA>3폐업2폐업2023-07-05<NA><NA><NA><NA>37.36121-835서울특별시 마포구 상암동 1597 사보이시티디엠씨서울특별시 마포구 월드컵북로54길 17, 사보이시티디엠씨 2층 222호 (상암동)3924요거넛 넘버나인(NO.9)2023-07-05 11:14:45U2022-12-07 00:07:00.0기타 휴게음식점190086.625449453231.427685<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2324030000003000000-104-1999-1080519991004<NA>3폐업2폐업19991118<NA><NA><NA>02 5531811<NA>110530서울특별시 종로구 혜화동 185-0번지 중원빌딩102호<NA><NA>미스터피자2000-01-31 00:00:00I2018-08-31 23:59:59.0패스트푸드200121.81372453518.007319패스트푸드00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N310.82<NA><NA><NA>
2393630000003000000-104-2013-0012720130925<NA>3폐업2폐업20171018<NA><NA><NA>02 737 8799<NA>110030서울특별시 종로구 청운동 59-5번지서울특별시 종로구 자하문로33길 10, 1층 (청운동)3031바오밥나무2017-10-18 11:42:56I2018-08-31 23:59:59.0커피숍197223.986198453768.406867커피숍<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N13.2<NA><NA><NA>
1600330300003030000-104-1986-0060519861230<NA>3폐업2폐업20131128<NA><NA><NA><NA>58.59133827서울특별시 성동구 성수동2가 321-85번지서울특별시 성동구 성수일로4길 52 (성수동2가)4781유정커피숍2011-08-01 10:54:27I2018-08-31 23:59:59.0다방204728.390413448916.843513다방00기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N58.59<NA><NA><NA>
2004330000003000000-104-2019-0010220190514<NA>1영업/정상1영업<NA><NA><NA><NA>00020733326418.0110122서울특별시 종로구 종로2가 40번지 육의전빌딩서울특별시 종로구 수표로 105, 육의전빌딩 지하2층 (종로2가)3140피앤티스퀘어2019-05-14 11:25:29I2019-05-16 02:20:47.0커피숍198966.805968452027.574754커피숍<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N18.0<NA><NA><NA>
1862131200003120000-104-2015-0016020151103<NA>1영업/정상1영업<NA><NA><NA><NA>02 302446479.95120130서울특별시 서대문구 북가좌동 487 성공타워1서울특별시 서대문구 수색로 56, 성공타워1 122,123호 (북가좌동)3791크리스피크림 가좌역점2022-09-05 13:37:10U2021-12-09 00:07:00.0기타 휴게음식점192209.323633452067.03943<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2119630000003000000-104-2017-0004520170228<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>110160서울특별시 종로구 공평동 144번지 104호서울특별시 종로구 삼봉로 94, 1층 104호 (공평동)3158GS25시94빌딩점2017-02-28 11:44:12I2018-08-31 23:59:59.0편의점198360.548239452168.842961편의점<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N5.0<NA><NA><NA>
39030600003060000-104-2022-000892022-06-13<NA>3폐업2폐업2023-03-02<NA><NA><NA><NA>19.0131-868서울특별시 중랑구 신내동 413-3서울특별시 중랑구 봉화산로56길 30, 1층 (신내동)2067우주요거트 아이스크림2023-03-02 11:11:04U2022-12-03 00:04:00.0아이스크림208673.09282456099.907231<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
145132000003200000-104-1995-091751995-12-15<NA>1영업/정상1영업<NA><NA><NA><NA>02 872941782.13151-930서울특별시 관악구 신림동 1637-2서울특별시 관악구 신림로 311 (신림동)8776배스킨라빈스 신림점2023-10-31 15:19:45U2022-11-01 00:02:00.0기타 휴게음식점193708.789974442219.282949<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2079930000003000000-104-2015-0010020150615<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>110847서울특별시 종로구 평창동 182-11번지서울특별시 종로구 평창12길 3, 1층 (평창동)3009배스킨라빈스2016-12-30 17:51:48I2018-08-31 23:59:59.0아이스크림197025.849892455981.012781아이스크림<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N42.24<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
2186230000003000000-104-1993-0904319931210<NA>3폐업2폐업19940526<NA><NA><NA>0207322511<NA>110052서울특별시 종로구 적선동 122-1번지<NA><NA>카자로18호2001-09-29 00:00:00I2018-08-31 23:59:59.0다방197583.394691452513.612018다방00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N45.5<NA><NA><NA>
2380730000003000000-104-2014-0013220140716<NA>3폐업2폐업20170116<NA><NA><NA><NA><NA>110122서울특별시 종로구 종로2가 84-2번지 지상1~4층서울특별시 종로구 종로 72-2, 지상1~4층 (종로2가)3189마노핀 종로점2014-07-16 18:13:05I2018-08-31 23:59:59.0커피숍198652.145786451962.651382커피숍<NA><NA>기타<NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N152.42<NA><NA><NA>
471531500003150000-104-2011-001512011-09-28<NA>1영업/정상1영업<NA><NA><NA><NA>022667982555.0157-930서울특별시 강서구 등촌동 689-0 외 2필지 강서NC백화점 (지하 1층)서울특별시 강서구 강서로56길 17, 지하 1층 (등촌동, 3동 강서NC백화점)7584롯데리아NC강서점2023-05-18 16:38:47U2022-12-04 22:00:00.0패스트푸드185824.428509450866.252126<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1765431300003130000-104-2022-0020420220711<NA>1영업/정상1영업<NA><NA><NA><NA><NA>99.79121865서울특별시 마포구 연남동 246-20서울특별시 마포구 성미산로23길 24, 1층 (연남동)3979발트 2호점2022-07-11 11:38:43I2021-12-06 23:03:00.0커피숍192971.577871451354.915424<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1085330100003010000-104-2024-001312024-05-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>6.6100-747서울특별시 중구 충무로1가 52-5 신세계백화점건물서울특별시 중구 소공로 63, 신세계백화점건물 지1층 (충무로1가)4530엘리스파이2024-05-02 13:16:45I2023-12-05 00:04:00.0기타 휴게음식점198263.908392450960.762965<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2446530100003010000-104-2021-0000720210107<NA>3폐업2폐업20210114<NA><NA><NA><NA>6.6100747서울특별시 중구 충무로1가 52-5 신세계백화점서울특별시 중구 소공로 63, 신세계백화점 지하1층 (충무로1가)4530서울호떡2021-01-15 04:15:08U2021-01-17 02:40:00.0기타 휴게음식점198263.908392450960.762965기타 휴게음식점<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N6.6<NA><NA><NA>
641930500003050000-104-2012-001332012-12-11<NA>3폐업2폐업2023-09-20<NA><NA><NA><NA>62.0130-850서울특별시 동대문구 전농동 90 서울시립대학교 미래관 지하1층서울특별시 동대문구 서울시립대로 163, 지하1층 (전농동, 서울시립대학교 미래관)2504카페드림(서울시립대점)2023-09-20 10:21:37U2022-12-08 22:02:00.0커피숍205232.466601453459.55417<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1618531800003180000-104-2008-0013120081009<NA>1영업/정상1영업<NA><NA><NA><NA><NA>101.22150835서울특별시 영등포구 문래동3가 55-5 로데오왁 141호서울특별시 영등포구 당산로 34 (문래동3가,로데오왁 141호)7297카페 오가닉2023-01-30 16:21:01U2022-12-02 00:01:00.0커피숍190777.430587446138.269919<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1780032100003210000-104-2021-0009420210401<NA>3폐업2폐업20220415<NA><NA><NA><NA>18.0137808서울특별시 서초구 반포동 701-21 B102호서울특별시 서초구 주흥길 81, B102호 (반포동)6533멜로웨이브(Mellowave)2022-04-15 14:52:24U2021-12-03 23:07:00.0기타 휴게음식점201537.423687445254.709842<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
337532300003230000-104-2023-001992023-05-16<NA>1영업/정상1영업<NA><NA><NA><NA><NA>27.63138-864서울특별시 송파구 잠실동 233-16서울특별시 송파구 백제고분로17길 1, 102호 (잠실동)5568그린도트2023-05-16 11:40:06I2022-12-04 23:08:00.0커피숍207444.81745444849.797734<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>