Overview

Dataset statistics

Number of variables44
Number of observations315
Missing cells3759
Missing cells (%)27.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory116.1 KiB
Average record size in memory377.4 B

Variable types

Categorical18
Text8
DateTime4
Unsupported9
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
Author중구
URLhttps://data.seoul.go.kr/dataList/OA-17978/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
인허가취소일자 has 315 (100.0%) missing valuesMissing
폐업일자 has 91 (28.9%) missing valuesMissing
휴업시작일자 has 315 (100.0%) missing valuesMissing
휴업종료일자 has 315 (100.0%) missing valuesMissing
재개업일자 has 315 (100.0%) missing valuesMissing
전화번호 has 82 (26.0%) missing valuesMissing
소재지면적 has 51 (16.2%) missing valuesMissing
도로명주소 has 91 (28.9%) missing valuesMissing
도로명우편번호 has 96 (30.5%) missing valuesMissing
좌표정보(X) has 19 (6.0%) missing valuesMissing
좌표정보(Y) has 19 (6.0%) missing valuesMissing
영업장주변구분명 has 313 (99.4%) missing valuesMissing
등급구분명 has 315 (100.0%) missing valuesMissing
건물소유구분명 has 315 (100.0%) missing valuesMissing
다중이용업소여부 has 81 (25.7%) missing valuesMissing
시설총규모 has 81 (25.7%) missing valuesMissing
전통업소지정번호 has 315 (100.0%) missing valuesMissing
전통업소주된음식 has 315 (100.0%) missing valuesMissing
홈페이지 has 315 (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
등급구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물소유구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
시설총규모 has 52 (16.5%) zerosZeros

Reproduction

Analysis started2024-05-11 06:43:46.780352
Analysis finished2024-05-11 06:43:47.875785
Duration1.1 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
3010000
315 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3010000
2nd row3010000
3rd row3010000
4th row3010000
5th row3010000

Common Values

ValueCountFrequency (%)
3010000 315
100.0%

Length

2024-05-11T15:43:47.959993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:43:48.092316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3010000 315
100.0%

관리번호
Text

UNIQUE 

Distinct315
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2024-05-11T15:43:48.332784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters6930
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

Unique315 ?
Unique (%)100.0%

Sample

1st row3010000-120-2003-00001
2nd row3010000-120-2003-00002
3rd row3010000-120-2003-00003
4th row3010000-120-2003-00004
5th row3010000-120-2003-00005
ValueCountFrequency (%)
3010000-120-2003-00001 1
 
0.3%
3010000-120-2016-00002 1
 
0.3%
3010000-120-2016-00009 1
 
0.3%
3010000-120-2016-00008 1
 
0.3%
3010000-120-2016-00007 1
 
0.3%
3010000-120-2016-00006 1
 
0.3%
3010000-120-2016-00005 1
 
0.3%
3010000-120-2016-00004 1
 
0.3%
3010000-120-2017-00001 1
 
0.3%
3010000-120-2016-00001 1
 
0.3%
Other values (305) 305
96.8%
2024-05-11T15:43:48.810679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3530
50.9%
- 945
 
13.6%
1 874
 
12.6%
2 764
 
11.0%
3 462
 
6.7%
4 74
 
1.1%
5 67
 
1.0%
6 67
 
1.0%
7 61
 
0.9%
8 48
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5985
86.4%
Dash Punctuation 945
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3530
59.0%
1 874
 
14.6%
2 764
 
12.8%
3 462
 
7.7%
4 74
 
1.2%
5 67
 
1.1%
6 67
 
1.1%
7 61
 
1.0%
8 48
 
0.8%
9 38
 
0.6%
Dash Punctuation
ValueCountFrequency (%)
- 945
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6930
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3530
50.9%
- 945
 
13.6%
1 874
 
12.6%
2 764
 
11.0%
3 462
 
6.7%
4 74
 
1.1%
5 67
 
1.0%
6 67
 
1.0%
7 61
 
0.9%
8 48
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6930
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3530
50.9%
- 945
 
13.6%
1 874
 
12.6%
2 764
 
11.0%
3 462
 
6.7%
4 74
 
1.1%
5 67
 
1.0%
6 67
 
1.0%
7 61
 
0.9%
8 48
 
0.7%
Distinct263
Distinct (%)83.5%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
Minimum2003-05-29 00:00:00
Maximum2024-03-13 00:00:00
2024-05-11T15:43:49.056894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:43:49.277176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing315
Missing (%)100.0%
Memory size2.9 KiB
Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
3
224 
1
91 

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 (%)
3 224
71.1%
1 91
28.9%

Length

2024-05-11T15:43:49.467229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:43:49.593040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 224
71.1%
1 91
28.9%

영업상태명
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
폐업
224 
영업/정상
91 

Length

Max length5
Median length2
Mean length2.8666667
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 224
71.1%
영업/정상 91
28.9%

Length

2024-05-11T15:43:49.760420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:43:49.913481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 224
71.1%
영업/정상 91
28.9%
Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2
224 
1
91 

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 (%)
2 224
71.1%
1 91
28.9%

Length

2024-05-11T15:43:50.047273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:43:50.185929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 224
71.1%
1 91
28.9%
Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
폐업
224 
영업
91 

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 224
71.1%
영업 91
28.9%

Length

2024-05-11T15:43:50.333208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:43:50.459669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 224
71.1%
영업 91
28.9%

폐업일자
Date

MISSING 

Distinct205
Distinct (%)91.5%
Missing91
Missing (%)28.9%
Memory size2.6 KiB
Minimum2003-07-31 00:00:00
Maximum2024-02-29 00:00:00
2024-05-11T15:43:50.614973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:43:50.810266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing315
Missing (%)100.0%
Memory size2.9 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing315
Missing (%)100.0%
Memory size2.9 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing315
Missing (%)100.0%
Memory size2.9 KiB

전화번호
Text

MISSING 

Distinct214
Distinct (%)91.8%
Missing82
Missing (%)26.0%
Memory size2.6 KiB
2024-05-11T15:43:51.102677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.502146
Min length8

Characters and Unicode

Total characters2447
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

Unique202 ?
Unique (%)86.7%

Sample

1st row02 3169113
2nd row02 3120933
3rd row02 7571199
4th row0221124114
5th row02 7587178
ValueCountFrequency (%)
02 107
27.8%
0233976000 5
 
1.3%
33920455 4
 
1.0%
027532955 4
 
1.0%
729 3
 
0.8%
0237015741 2
 
0.5%
7329 2
 
0.5%
312 2
 
0.5%
070 2
 
0.5%
02310 2
 
0.5%
Other values (242) 252
65.5%
2024-05-11T15:43:51.610706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 460
18.8%
2 454
18.6%
3 220
9.0%
210
8.6%
7 196
8.0%
5 194
7.9%
1 191
7.8%
4 141
 
5.8%
8 137
 
5.6%
9 128
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2237
91.4%
Space Separator 210
 
8.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 460
20.6%
2 454
20.3%
3 220
9.8%
7 196
8.8%
5 194
8.7%
1 191
8.5%
4 141
 
6.3%
8 137
 
6.1%
9 128
 
5.7%
6 116
 
5.2%
Space Separator
ValueCountFrequency (%)
210
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2447
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 460
18.8%
2 454
18.6%
3 220
9.0%
210
8.6%
7 196
8.0%
5 194
7.9%
1 191
7.8%
4 141
 
5.8%
8 137
 
5.6%
9 128
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2447
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 460
18.8%
2 454
18.6%
3 220
9.0%
210
8.6%
7 196
8.0%
5 194
7.9%
1 191
7.8%
4 141
 
5.8%
8 137
 
5.6%
9 128
 
5.2%

소재지면적
Text

MISSING 

Distinct204
Distinct (%)77.3%
Missing51
Missing (%)16.2%
Memory size2.6 KiB
2024-05-11T15:43:52.035524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length6.0378788
Min length3

Characters and Unicode

Total characters1594
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique159 ?
Unique (%)60.2%

Sample

1st row176.30
2nd row1,273.00
3rd row716.10
4th row1,317.00
5th row1,199.00
ValueCountFrequency (%)
103.50 4
 
1.5%
297.93 3
 
1.1%
100.93 3
 
1.1%
86.00 3
 
1.1%
780.00 3
 
1.1%
321.88 3
 
1.1%
189.00 3
 
1.1%
208.00 3
 
1.1%
241.76 3
 
1.1%
50.09 3
 
1.1%
Other values (194) 233
88.3%
2024-05-11T15:43:52.684718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 327
20.5%
. 264
16.6%
1 149
9.3%
2 128
 
8.0%
3 118
 
7.4%
4 108
 
6.8%
5 103
 
6.5%
7 100
 
6.3%
8 94
 
5.9%
6 94
 
5.9%
Other values (2) 109
 
6.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1309
82.1%
Other Punctuation 285
 
17.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 327
25.0%
1 149
11.4%
2 128
 
9.8%
3 118
 
9.0%
4 108
 
8.3%
5 103
 
7.9%
7 100
 
7.6%
8 94
 
7.2%
6 94
 
7.2%
9 88
 
6.7%
Other Punctuation
ValueCountFrequency (%)
. 264
92.6%
, 21
 
7.4%

Most occurring scripts

ValueCountFrequency (%)
Common 1594
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 327
20.5%
. 264
16.6%
1 149
9.3%
2 128
 
8.0%
3 118
 
7.4%
4 108
 
6.8%
5 103
 
6.5%
7 100
 
6.3%
8 94
 
5.9%
6 94
 
5.9%
Other values (2) 109
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1594
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 327
20.5%
. 264
16.6%
1 149
9.3%
2 128
 
8.0%
3 118
 
7.4%
4 108
 
6.8%
5 103
 
6.5%
7 100
 
6.3%
8 94
 
5.9%
6 94
 
5.9%
Other values (2) 109
 
6.8%
Distinct113
Distinct (%)35.9%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2024-05-11T15:43:53.098792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1714286
Min length6

Characters and Unicode

Total characters1944
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

Unique48 ?
Unique (%)15.2%

Sample

1st row100874
2nd row100859
3rd row100070
4th row100802
5th row100843
ValueCountFrequency (%)
100250 14
 
4.4%
100802 13
 
4.1%
100180 12
 
3.8%
100120 10
 
3.2%
100878 8
 
2.5%
100856 8
 
2.5%
100162 7
 
2.2%
100845 7
 
2.2%
100130 7
 
2.2%
100843 7
 
2.2%
Other values (103) 222
70.5%
2024-05-11T15:43:53.826320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 792
40.7%
1 455
23.4%
8 172
 
8.8%
2 100
 
5.1%
5 87
 
4.5%
7 66
 
3.4%
3 61
 
3.1%
9 60
 
3.1%
4 59
 
3.0%
- 54
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1890
97.2%
Dash Punctuation 54
 
2.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 792
41.9%
1 455
24.1%
8 172
 
9.1%
2 100
 
5.3%
5 87
 
4.6%
7 66
 
3.5%
3 61
 
3.2%
9 60
 
3.2%
4 59
 
3.1%
6 38
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
- 54
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1944
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 792
40.7%
1 455
23.4%
8 172
 
8.8%
2 100
 
5.1%
5 87
 
4.5%
7 66
 
3.4%
3 61
 
3.1%
9 60
 
3.1%
4 59
 
3.0%
- 54
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1944
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 792
40.7%
1 455
23.4%
8 172
 
8.8%
2 100
 
5.1%
5 87
 
4.5%
7 66
 
3.4%
3 61
 
3.1%
9 60
 
3.1%
4 59
 
3.0%
- 54
 
2.8%
Distinct291
Distinct (%)92.4%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2024-05-11T15:43:54.232600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length36
Mean length25.390476
Min length14

Characters and Unicode

Total characters7998
Distinct characters236
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique271 ?
Unique (%)86.0%

Sample

1st row서울특별시 중구 회현동1가 194-5번지
2nd row서울특별시 중구 중림동 363-0번지
3rd row서울특별시 중구 소공동 87-10번지
4th row서울특별시 중구 남대문로5가 537-0번지 (LG역전빌딩)
5th row서울특별시 중구 을지로1가 87-0번지 (삼성화재)
ValueCountFrequency (%)
서울특별시 315
20.3%
중구 315
20.3%
지하1층 34
 
2.2%
신당동 22
 
1.4%
을지로2가 21
 
1.4%
남대문로5가 19
 
1.2%
장충동2가 18
 
1.2%
예장동 17
 
1.1%
지하2층 14
 
0.9%
다동 14
 
0.9%
Other values (402) 760
49.1%
2024-05-11T15:43:54.847506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1469
18.4%
1 393
 
4.9%
332
 
4.2%
328
 
4.1%
327
 
4.1%
324
 
4.1%
323
 
4.0%
319
 
4.0%
318
 
4.0%
316
 
4.0%
Other values (226) 3549
44.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4800
60.0%
Space Separator 1469
 
18.4%
Decimal Number 1334
 
16.7%
Dash Punctuation 209
 
2.6%
Close Punctuation 60
 
0.8%
Open Punctuation 60
 
0.8%
Uppercase Letter 48
 
0.6%
Other Punctuation 9
 
0.1%
Lowercase Letter 8
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
332
 
6.9%
328
 
6.8%
327
 
6.8%
324
 
6.8%
323
 
6.7%
319
 
6.6%
318
 
6.6%
316
 
6.6%
249
 
5.2%
191
 
4.0%
Other values (184) 1773
36.9%
Uppercase Letter
ValueCountFrequency (%)
K 7
14.6%
L 5
10.4%
S 5
10.4%
T 5
10.4%
E 3
 
6.2%
I 3
 
6.2%
A 3
 
6.2%
B 3
 
6.2%
D 2
 
4.2%
X 1
 
2.1%
Other values (11) 11
22.9%
Decimal Number
ValueCountFrequency (%)
1 393
29.5%
2 237
17.8%
5 145
 
10.9%
3 132
 
9.9%
0 110
 
8.2%
4 71
 
5.3%
8 71
 
5.3%
6 70
 
5.2%
7 58
 
4.3%
9 47
 
3.5%
Lowercase Letter
ValueCountFrequency (%)
o 2
25.0%
w 2
25.0%
e 2
25.0%
r 2
25.0%
Other Punctuation
ValueCountFrequency (%)
, 7
77.8%
/ 2
 
22.2%
Space Separator
ValueCountFrequency (%)
1469
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 209
100.0%
Close Punctuation
ValueCountFrequency (%)
) 60
100.0%
Open Punctuation
ValueCountFrequency (%)
( 60
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4800
60.0%
Common 3142
39.3%
Latin 56
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
332
 
6.9%
328
 
6.8%
327
 
6.8%
324
 
6.8%
323
 
6.7%
319
 
6.6%
318
 
6.6%
316
 
6.6%
249
 
5.2%
191
 
4.0%
Other values (184) 1773
36.9%
Latin
ValueCountFrequency (%)
K 7
 
12.5%
L 5
 
8.9%
S 5
 
8.9%
T 5
 
8.9%
E 3
 
5.4%
I 3
 
5.4%
A 3
 
5.4%
B 3
 
5.4%
D 2
 
3.6%
o 2
 
3.6%
Other values (15) 18
32.1%
Common
ValueCountFrequency (%)
1469
46.8%
1 393
 
12.5%
2 237
 
7.5%
- 209
 
6.7%
5 145
 
4.6%
3 132
 
4.2%
0 110
 
3.5%
4 71
 
2.3%
8 71
 
2.3%
6 70
 
2.2%
Other values (7) 235
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4800
60.0%
ASCII 3198
40.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1469
45.9%
1 393
 
12.3%
2 237
 
7.4%
- 209
 
6.5%
5 145
 
4.5%
3 132
 
4.1%
0 110
 
3.4%
4 71
 
2.2%
8 71
 
2.2%
6 70
 
2.2%
Other values (32) 291
 
9.1%
Hangul
ValueCountFrequency (%)
332
 
6.9%
328
 
6.8%
327
 
6.8%
324
 
6.8%
323
 
6.7%
319
 
6.6%
318
 
6.6%
316
 
6.6%
249
 
5.2%
191
 
4.0%
Other values (184) 1773
36.9%

도로명주소
Text

MISSING 

Distinct204
Distinct (%)91.1%
Missing91
Missing (%)28.9%
Memory size2.6 KiB
2024-05-11T15:43:55.220327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length40
Mean length31.308036
Min length20

Characters and Unicode

Total characters7013
Distinct characters241
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique186 ?
Unique (%)83.0%

Sample

1st row서울특별시 중구 퇴계로 10 (남대문로5가,(LG역전빌딩))
2nd row서울특별시 중구 수표로 34 (저동2가,(쌍용B/D 18층))
3rd row서울특별시 중구 소공로 106 (소공동)
4th row서울특별시 중구 동호로15길 93 (신당동)
5th row서울특별시 중구 새문안로 22 (충정로1가)
ValueCountFrequency (%)
서울특별시 224
 
16.2%
중구 224
 
16.2%
지하1층 37
 
2.7%
을지로 31
 
2.2%
지하2층 27
 
2.0%
퇴계로 25
 
1.8%
남대문로 21
 
1.5%
을지로2가 16
 
1.2%
30 14
 
1.0%
3층 13
 
0.9%
Other values (332) 752
54.3%
2024-05-11T15:43:55.916410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1161
 
16.6%
300
 
4.3%
) 249
 
3.6%
( 249
 
3.6%
240
 
3.4%
234
 
3.3%
233
 
3.3%
232
 
3.3%
229
 
3.3%
228
 
3.3%
Other values (231) 3658
52.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4171
59.5%
Space Separator 1161
 
16.6%
Decimal Number 925
 
13.2%
Close Punctuation 249
 
3.6%
Open Punctuation 249
 
3.6%
Other Punctuation 204
 
2.9%
Uppercase Letter 42
 
0.6%
Lowercase Letter 8
 
0.1%
Math Symbol 2
 
< 0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
300
 
7.2%
240
 
5.8%
234
 
5.6%
233
 
5.6%
232
 
5.6%
229
 
5.5%
228
 
5.5%
225
 
5.4%
206
 
4.9%
174
 
4.2%
Other values (190) 1870
44.8%
Uppercase Letter
ValueCountFrequency (%)
K 5
11.9%
T 5
11.9%
L 5
11.9%
A 4
 
9.5%
E 3
 
7.1%
I 3
 
7.1%
S 3
 
7.1%
B 2
 
4.8%
U 1
 
2.4%
D 1
 
2.4%
Other values (10) 10
23.8%
Decimal Number
ValueCountFrequency (%)
2 199
21.5%
1 195
21.1%
3 99
10.7%
5 82
8.9%
0 76
 
8.2%
6 58
 
6.3%
4 56
 
6.1%
7 55
 
5.9%
9 54
 
5.8%
8 51
 
5.5%
Lowercase Letter
ValueCountFrequency (%)
r 2
25.0%
e 2
25.0%
w 2
25.0%
o 2
25.0%
Other Punctuation
ValueCountFrequency (%)
, 203
99.5%
/ 1
 
0.5%
Space Separator
ValueCountFrequency (%)
1161
100.0%
Close Punctuation
ValueCountFrequency (%)
) 249
100.0%
Open Punctuation
ValueCountFrequency (%)
( 249
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4171
59.5%
Common 2792
39.8%
Latin 50
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
300
 
7.2%
240
 
5.8%
234
 
5.6%
233
 
5.6%
232
 
5.6%
229
 
5.5%
228
 
5.5%
225
 
5.4%
206
 
4.9%
174
 
4.2%
Other values (190) 1870
44.8%
Latin
ValueCountFrequency (%)
K 5
 
10.0%
T 5
 
10.0%
L 5
 
10.0%
A 4
 
8.0%
E 3
 
6.0%
I 3
 
6.0%
S 3
 
6.0%
r 2
 
4.0%
e 2
 
4.0%
w 2
 
4.0%
Other values (14) 16
32.0%
Common
ValueCountFrequency (%)
1161
41.6%
) 249
 
8.9%
( 249
 
8.9%
, 203
 
7.3%
2 199
 
7.1%
1 195
 
7.0%
3 99
 
3.5%
5 82
 
2.9%
0 76
 
2.7%
6 58
 
2.1%
Other values (7) 221
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4171
59.5%
ASCII 2842
40.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1161
40.9%
) 249
 
8.8%
( 249
 
8.8%
, 203
 
7.1%
2 199
 
7.0%
1 195
 
6.9%
3 99
 
3.5%
5 82
 
2.9%
0 76
 
2.7%
6 58
 
2.0%
Other values (31) 271
 
9.5%
Hangul
ValueCountFrequency (%)
300
 
7.2%
240
 
5.8%
234
 
5.6%
233
 
5.6%
232
 
5.6%
229
 
5.5%
228
 
5.5%
225
 
5.4%
206
 
4.9%
174
 
4.2%
Other values (190) 1870
44.8%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct65
Distinct (%)29.7%
Missing96
Missing (%)30.5%
Infinite0
Infinite (%)0.0%
Mean4563.1461
Minimum4500
Maximum4637
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-05-11T15:43:56.140287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4500
5-th percentile4510.9
Q14525
median4548
Q34608.5
95-th percentile4636.1
Maximum4637
Range137
Interquartile range (IQR)83.5

Descriptive statistics

Standard deviation44.295988
Coefficient of variation (CV)0.0097073349
Kurtosis-1.2640205
Mean4563.1461
Median Absolute Deviation (MAD)27
Skewness0.50433834
Sum999329
Variance1962.1345
MonotonicityNot monotonic
2024-05-11T15:43:56.406708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4637 11
 
3.5%
4516 10
 
3.2%
4566 10
 
3.2%
4628 10
 
3.2%
4521 9
 
2.9%
4571 8
 
2.5%
4605 8
 
2.5%
4538 7
 
2.2%
4533 6
 
1.9%
4523 6
 
1.9%
Other values (55) 134
42.5%
(Missing) 96
30.5%
ValueCountFrequency (%)
4500 1
 
0.3%
4502 1
 
0.3%
4505 1
 
0.3%
4509 5
1.6%
4510 3
 
1.0%
4511 2
 
0.6%
4512 1
 
0.3%
4513 3
 
1.0%
4515 2
 
0.6%
4516 10
3.2%
ValueCountFrequency (%)
4637 11
3.5%
4636 3
 
1.0%
4635 1
 
0.3%
4634 3
 
1.0%
4632 1
 
0.3%
4631 4
 
1.3%
4629 5
1.6%
4628 10
3.2%
4627 3
 
1.0%
4626 2
 
0.6%
Distinct304
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2024-05-11T15:43:56.849455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length20
Mean length13.914286
Min length3

Characters and Unicode

Total characters4383
Distinct characters299
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

Unique295 ?
Unique (%)93.7%

Sample

1st row신세계푸드 대한전선본사
2nd row동원홈푸드(종로강북)
3rd row신세계푸드 신세계본사
4th row(주)아워홈 역전점
5th row삼성화재
ValueCountFrequency (%)
주)아워홈 23
 
4.1%
씨제이프레시웨이(주 14
 
2.5%
주)신세계푸드 12
 
2.1%
신세계푸드 10
 
1.8%
삼성웰스토리(주 9
 
1.6%
주)엘에스씨푸드 8
 
1.4%
명동점 7
 
1.2%
본우리집밥 7
 
1.2%
주)현대그린푸드 7
 
1.2%
주식회사 6
 
1.1%
Other values (370) 457
81.6%
2024-05-11T15:43:57.347281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
245
 
5.6%
224
 
5.1%
) 219
 
5.0%
( 219
 
5.0%
160
 
3.7%
125
 
2.9%
96
 
2.2%
89
 
2.0%
77
 
1.8%
65
 
1.5%
Other values (289) 2864
65.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3615
82.5%
Space Separator 245
 
5.6%
Close Punctuation 219
 
5.0%
Open Punctuation 219
 
5.0%
Uppercase Letter 66
 
1.5%
Dash Punctuation 10
 
0.2%
Decimal Number 7
 
0.2%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
224
 
6.2%
160
 
4.4%
125
 
3.5%
96
 
2.7%
89
 
2.5%
77
 
2.1%
65
 
1.8%
58
 
1.6%
54
 
1.5%
52
 
1.4%
Other values (266) 2615
72.3%
Uppercase Letter
ValueCountFrequency (%)
K 13
19.7%
S 11
16.7%
L 8
12.1%
J 6
9.1%
G 5
 
7.6%
C 5
 
7.6%
F 4
 
6.1%
T 4
 
6.1%
D 3
 
4.5%
I 2
 
3.0%
Other values (5) 5
 
7.6%
Decimal Number
ValueCountFrequency (%)
2 3
42.9%
7 3
42.9%
1 1
 
14.3%
Space Separator
ValueCountFrequency (%)
245
100.0%
Close Punctuation
ValueCountFrequency (%)
) 219
100.0%
Open Punctuation
ValueCountFrequency (%)
( 219
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3615
82.5%
Common 702
 
16.0%
Latin 66
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
224
 
6.2%
160
 
4.4%
125
 
3.5%
96
 
2.7%
89
 
2.5%
77
 
2.1%
65
 
1.8%
58
 
1.6%
54
 
1.5%
52
 
1.4%
Other values (266) 2615
72.3%
Latin
ValueCountFrequency (%)
K 13
19.7%
S 11
16.7%
L 8
12.1%
J 6
9.1%
G 5
 
7.6%
C 5
 
7.6%
F 4
 
6.1%
T 4
 
6.1%
D 3
 
4.5%
I 2
 
3.0%
Other values (5) 5
 
7.6%
Common
ValueCountFrequency (%)
245
34.9%
) 219
31.2%
( 219
31.2%
- 10
 
1.4%
2 3
 
0.4%
7 3
 
0.4%
. 2
 
0.3%
1 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3615
82.5%
ASCII 768
 
17.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
245
31.9%
) 219
28.5%
( 219
28.5%
K 13
 
1.7%
S 11
 
1.4%
- 10
 
1.3%
L 8
 
1.0%
J 6
 
0.8%
G 5
 
0.7%
C 5
 
0.7%
Other values (13) 27
 
3.5%
Hangul
ValueCountFrequency (%)
224
 
6.2%
160
 
4.4%
125
 
3.5%
96
 
2.7%
89
 
2.5%
77
 
2.1%
65
 
1.8%
58
 
1.6%
54
 
1.5%
52
 
1.4%
Other values (266) 2615
72.3%
Distinct308
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
Minimum2003-06-05 00:00:00
Maximum2024-04-18 17:37:12
2024-05-11T15:43:57.540080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:43:57.738066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
I
207 
U
108 

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 207
65.7%
U 108
34.3%

Length

2024-05-11T15:43:57.954333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:43:58.156434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 207
65.7%
u 108
34.3%
Distinct107
Distinct (%)34.0%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 22:00:00
2024-05-11T15:43:58.329035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:43:58.574435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
위탁급식영업
315 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
위탁급식영업 315
100.0%

Length

2024-05-11T15:43:58.770262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:43:58.898960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
위탁급식영업 315
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct139
Distinct (%)47.0%
Missing19
Missing (%)6.0%
Infinite0
Infinite (%)0.0%
Mean198898.9
Minimum196757.68
Maximum202128.14
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-05-11T15:43:59.042080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum196757.68
5-th percentile197230.09
Q1197885.46
median198611.24
Q3199803.37
95-th percentile201428.15
Maximum202128.14
Range5370.4538
Interquartile range (IQR)1917.9101

Descriptive statistics

Standard deviation1309.85
Coefficient of variation (CV)0.0065855065
Kurtosis-0.51833794
Mean198898.9
Median Absolute Deviation (MAD)848.73843
Skewness0.68846431
Sum58874073
Variance1715707
MonotonicityNot monotonic
2024-05-11T15:43:59.254565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
201428.149730846 11
 
3.5%
201083.133966078 6
 
1.9%
198229.951228532 6
 
1.9%
197762.501510022 6
 
1.9%
199803.37296067 5
 
1.6%
197396.958791381 5
 
1.6%
197243.215346366 5
 
1.6%
200314.646974736 5
 
1.6%
198817.114277587 5
 
1.6%
200461.421710224 5
 
1.6%
Other values (129) 237
75.2%
(Missing) 19
 
6.0%
ValueCountFrequency (%)
196757.683195655 1
 
0.3%
196948.933328771 1
 
0.3%
196981.426086312 1
 
0.3%
197032.923485936 1
 
0.3%
197155.202941326 4
1.3%
197164.226466038 3
1.0%
197214.205778633 3
1.0%
197229.761422932 1
 
0.3%
197230.206089772 2
 
0.6%
197243.215346366 5
1.6%
ValueCountFrequency (%)
202128.136971071 1
 
0.3%
201945.852349721 3
 
1.0%
201944.611391747 1
 
0.3%
201823.908977364 2
 
0.6%
201709.339736009 1
 
0.3%
201438.911214839 1
 
0.3%
201428.149730846 11
3.5%
201400.824438273 2
 
0.6%
201362.695573425 1
 
0.3%
201263.092335622 2
 
0.6%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct139
Distinct (%)47.0%
Missing19
Missing (%)6.0%
Infinite0
Infinite (%)0.0%
Mean451136.97
Minimum449777.52
Maximum452076.82
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-05-11T15:43:59.791446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum449777.52
5-th percentile450234.79
Q1450779.09
median451271.33
Q3451554.07
95-th percentile451840.33
Maximum452076.82
Range2299.3028
Interquartile range (IQR)774.97442

Descriptive statistics

Standard deviation507.52285
Coefficient of variation (CV)0.0011249862
Kurtosis-0.61223491
Mean451136.97
Median Absolute Deviation (MAD)369.85405
Skewness-0.45483444
Sum1.3353654 × 108
Variance257579.44
MonotonicityNot monotonic
2024-05-11T15:44:00.039347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
451851.925540893 11
 
3.5%
451485.056385084 6
 
1.9%
451804.346043518 6
 
1.9%
450337.580626313 6
 
1.9%
450779.092503874 5
 
1.6%
451509.63614311 5
 
1.6%
450655.104239931 5
 
1.6%
451554.066925226 5
 
1.6%
450514.417668384 5
 
1.6%
451682.120811509 5
 
1.6%
Other values (129) 237
75.2%
(Missing) 19
 
6.0%
ValueCountFrequency (%)
449777.515840267 1
 
0.3%
449809.744684888 3
1.0%
450066.837234924 1
 
0.3%
450075.941386762 3
1.0%
450122.648712336 1
 
0.3%
450124.408847071 1
 
0.3%
450126.859257667 1
 
0.3%
450173.966697254 1
 
0.3%
450180.019066426 1
 
0.3%
450234.792371602 3
1.0%
ValueCountFrequency (%)
452076.818664092 2
 
0.6%
451995.163058 2
 
0.6%
451851.925540893 11
3.5%
451836.458256618 1
 
0.3%
451808.098341971 2
 
0.6%
451808.048376715 3
 
1.0%
451804.346043518 6
1.9%
451781.184065635 1
 
0.3%
451779.880897566 2
 
0.6%
451775.169253151 1
 
0.3%

위생업태명
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
위탁급식영업
234 
<NA>
81 

Length

Max length6
Median length6
Mean length5.4857143
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
위탁급식영업 234
74.3%
<NA> 81
 
25.7%

Length

2024-05-11T15:44:00.345116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:44:00.530490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
위탁급식영업 234
74.3%
na 81
 
25.7%
Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
0
234 
<NA>
81 

Length

Max length4
Median length1
Mean length1.7714286
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 234
74.3%
<NA> 81
 
25.7%

Length

2024-05-11T15:44:00.747081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:44:00.933267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 234
74.3%
na 81
 
25.7%
Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
0
234 
<NA>
81 

Length

Max length4
Median length1
Mean length1.7714286
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 234
74.3%
<NA> 81
 
25.7%

Length

2024-05-11T15:44:01.132333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:44:01.319268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 234
74.3%
na 81
 
25.7%
Distinct2
Distinct (%)100.0%
Missing313
Missing (%)99.4%
Memory size2.6 KiB
2024-05-11T15:44:01.517987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters16
Distinct characters9
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row학교정화(상대)
2nd row학교정화(절대)
ValueCountFrequency (%)
학교정화(상대 1
50.0%
학교정화(절대 1
50.0%
2024-05-11T15:44:01.923891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2
12.5%
2
12.5%
2
12.5%
2
12.5%
( 2
12.5%
2
12.5%
) 2
12.5%
1
6.2%
1
6.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12
75.0%
Open Punctuation 2
 
12.5%
Close Punctuation 2
 
12.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2
16.7%
2
16.7%
2
16.7%
2
16.7%
2
16.7%
1
8.3%
1
8.3%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12
75.0%
Common 4
 
25.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2
16.7%
2
16.7%
2
16.7%
2
16.7%
2
16.7%
1
8.3%
1
8.3%
Common
ValueCountFrequency (%)
( 2
50.0%
) 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12
75.0%
ASCII 4
 
25.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2
16.7%
2
16.7%
2
16.7%
2
16.7%
2
16.7%
1
8.3%
1
8.3%
ASCII
ValueCountFrequency (%)
( 2
50.0%
) 2
50.0%

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing315
Missing (%)100.0%
Memory size2.9 KiB
Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
<NA>
272 
상수도전용
43 

Length

Max length5
Median length4
Mean length4.1365079
Min length4

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> 272
86.3%
상수도전용 43
 
13.7%

Length

2024-05-11T15:44:02.153118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:44:02.307085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 272
86.3%
상수도전용 43
 
13.7%

총인원
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
0
234 
<NA>
81 

Length

Max length4
Median length1
Mean length1.7714286
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 234
74.3%
<NA> 81
 
25.7%

Length

2024-05-11T15:44:02.538768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:44:02.744266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 234
74.3%
na 81
 
25.7%
Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
0
234 
<NA>
81 

Length

Max length4
Median length1
Mean length1.7714286
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 234
74.3%
<NA> 81
 
25.7%

Length

2024-05-11T15:44:02.899787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:44:03.089955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 234
74.3%
na 81
 
25.7%
Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
0
234 
<NA>
81 

Length

Max length4
Median length1
Mean length1.7714286
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 234
74.3%
<NA> 81
 
25.7%

Length

2024-05-11T15:44:03.288356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:44:03.489698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 234
74.3%
na 81
 
25.7%
Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
0
234 
<NA>
81 

Length

Max length4
Median length1
Mean length1.7714286
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 234
74.3%
<NA> 81
 
25.7%

Length

2024-05-11T15:44:03.685982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:44:03.856360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 234
74.3%
na 81
 
25.7%
Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
0
234 
<NA>
81 

Length

Max length4
Median length1
Mean length1.7714286
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 234
74.3%
<NA> 81
 
25.7%

Length

2024-05-11T15:44:04.059524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:44:04.257308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 234
74.3%
na 81
 
25.7%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing315
Missing (%)100.0%
Memory size2.9 KiB

보증액
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
0
234 
<NA>
81 

Length

Max length4
Median length1
Mean length1.7714286
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 234
74.3%
<NA> 81
 
25.7%

Length

2024-05-11T15:44:04.452467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:44:04.603579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 234
74.3%
na 81
 
25.7%

월세액
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
0
234 
<NA>
81 

Length

Max length4
Median length1
Mean length1.7714286
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 234
74.3%
<NA> 81
 
25.7%

Length

2024-05-11T15:44:04.801973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:44:05.000097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 234
74.3%
na 81
 
25.7%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.4%
Missing81
Missing (%)25.7%
Memory size762.0 B
False
234 
(Missing)
81 
ValueCountFrequency (%)
False 234
74.3%
(Missing) 81
 
25.7%
2024-05-11T15:44:05.121724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct150
Distinct (%)64.1%
Missing81
Missing (%)25.7%
Infinite0
Infinite (%)0.0%
Mean356.56107
Minimum0
Maximum3946.8
Zeros52
Zeros (%)16.5%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-05-11T15:44:05.289061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q150.13
median208.645
Q3463.725
95-th percentile1207.225
Maximum3946.8
Range3946.8
Interquartile range (IQR)413.595

Descriptive statistics

Standard deviation516.41317
Coefficient of variation (CV)1.4483162
Kurtosis18.743336
Mean356.56107
Median Absolute Deviation (MAD)200.555
Skewness3.6765905
Sum83435.29
Variance266682.56
MonotonicityNot monotonic
2024-05-11T15:44:05.521024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 52
 
16.5%
50.09 3
 
1.0%
65.36 3
 
1.0%
241.76 3
 
1.0%
297.93 3
 
1.0%
189.0 3
 
1.0%
300.23 3
 
1.0%
321.88 3
 
1.0%
924.0 2
 
0.6%
85.25 2
 
0.6%
Other values (140) 157
49.8%
(Missing) 81
25.7%
ValueCountFrequency (%)
0.0 52
16.5%
21.3 1
 
0.3%
23.54 1
 
0.3%
42.23 1
 
0.3%
47.56 1
 
0.3%
50.09 3
 
1.0%
50.25 1
 
0.3%
64.5 1
 
0.3%
65.36 3
 
1.0%
66.78 2
 
0.6%
ValueCountFrequency (%)
3946.8 1
0.3%
3453.7 1
0.3%
3180.0 1
0.3%
2369.28 1
0.3%
1561.54 1
0.3%
1530.0 1
0.3%
1452.0 1
0.3%
1443.76 1
0.3%
1299.6 1
0.3%
1273.0 1
0.3%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing315
Missing (%)100.0%
Memory size2.9 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing315
Missing (%)100.0%
Memory size2.9 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing315
Missing (%)100.0%
Memory size2.9 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030100003010000-120-2003-0000120030529<NA>3폐업2폐업20080114<NA><NA><NA>02 3169113<NA>100874서울특별시 중구 회현동1가 194-5번지<NA><NA>신세계푸드 대한전선본사2006-03-31 00:00:00I2018-08-31 23:59:59.0위탁급식영업198021.294450645.904333위탁급식영업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
130100003010000-120-2003-0000220030603<NA>3폐업2폐업20101228<NA><NA><NA>02 3120933<NA>100859서울특별시 중구 중림동 363-0번지<NA><NA>동원홈푸드(종로강북)2006-08-04 00:00:00I2018-08-31 23:59:59.0위탁급식영업197155.202941450860.41193위탁급식영업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
230100003010000-120-2003-0000320030604<NA>3폐업2폐업20051027<NA><NA><NA>02 7571199<NA>100070서울특별시 중구 소공동 87-10번지<NA><NA>신세계푸드 신세계본사2005-03-24 00:00:00I2018-08-31 23:59:59.0위탁급식영업198103.149079451392.93799위탁급식영업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
330100003010000-120-2003-0000420030604<NA>3폐업2폐업20140103<NA><NA><NA>0221124114<NA>100802서울특별시 중구 남대문로5가 537-0번지 (LG역전빌딩)서울특별시 중구 퇴계로 10 (남대문로5가,(LG역전빌딩))4637(주)아워홈 역전점2010-09-28 17:33:55I2018-08-31 23:59:59.0위탁급식영업197675.397522450448.564322위탁급식영업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
430100003010000-120-2003-0000520030605<NA>3폐업2폐업20050921<NA><NA><NA>02 7587178<NA>100843서울특별시 중구 을지로1가 87-0번지 (삼성화재)<NA><NA>삼성화재2003-06-05 00:00:00I2018-08-31 23:59:59.0위탁급식영업198256.131666451576.096658위탁급식영업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
530100003010000-120-2003-0000620030605<NA>3폐업2폐업20091201<NA><NA><NA>02 3654133<NA>100371서울특별시 중구 만리동1가 171-0번지<NA><NA>신세계푸드 영원무역2006-03-31 00:00:00I2018-08-31 23:59:59.0위탁급식영업<NA><NA>위탁급식영업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
630100003010000-120-2003-0000720030605<NA>3폐업2폐업20041231<NA><NA><NA>0234066100<NA>100180서울특별시 중구 다동 140-0번지<NA><NA>신세계푸드 대우조선본사2003-06-05 00:00:00I2018-08-31 23:59:59.0위탁급식영업198264.174398451644.992566위탁급식영업00<NA><NA>상수도전용00000<NA>00N0.0<NA><NA><NA>
730100003010000-120-2003-0000820030610<NA>3폐업2폐업20090427<NA><NA><NA>02 7762715<NA>100810서울특별시 중구 명동2가 51-14번지<NA><NA>(주)아워홈 에스콰이어 명동점2004-09-17 00:00:00I2018-08-31 23:59:59.0위탁급식영업198539.246462451217.150102위탁급식영업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
830100003010000-120-2003-0000920030610<NA>3폐업2폐업20061229<NA><NA><NA>0222636118<NA>100013서울특별시 중구 충무로3가 60-1번지<NA><NA>(주)아워홈 극동건설점2004-09-14 00:00:00I2018-08-31 23:59:59.0위탁급식영업199145.324201451040.432662위탁급식영업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
930100003010000-120-2003-0001020030610<NA>3폐업2폐업20040731<NA><NA><NA>0237089497<NA>100751서울특별시 중구 예장동 8-3번지 (숭의여자대학학생식당1층)<NA><NA>숭의여대점2003-06-10 00:00:00I2018-08-31 23:59:59.0위탁급식영업198817.114278450514.417668위탁급식영업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
30530100003010000-120-2024-000012024-02-15<NA>1영업/정상1영업<NA><NA><NA><NA>15448272333.18100-715서울특별시 중구 필동3가 26-1 동국대학교서울특별시 중구 필동로1길 30, 남산학사 지1층 (필동3가)4620삼성웰스토리(주) 동국대남산기숙사2024-02-15 10:59:48I2023-12-01 23:07:00.0위탁급식영업199803.372961450779.092504<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
30630100003010000-120-2024-000022024-02-29<NA>1영업/정상1영업<NA><NA><NA><NA>02 21761992604.00100-130서울특별시 중구 순화동 1-1 이화여자외국어고등학교서울특별시 중구 통일로4길 30, 이화여자외국어고등학교 (순화동)4516세종에프앤에스(주)-이화외고2024-02-29 09:56:12I2023-12-03 00:02:00.0위탁급식영업197269.78529451400.213265<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
30730100003010000-120-2024-000032024-02-29<NA>1영업/정상1영업<NA><NA><NA><NA>02 752 3353131.76100-120서울특별시 중구 정동 32-1 이화여자고등학교서울특별시 중구 정동길 26, 이화여자고등학교 (정동)4516세종에프앤에스(주)-이화여고2024-02-29 10:02:11I2023-12-03 00:02:00.0위탁급식영업197396.958791451509.636143<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
30830100003010000-120-2024-000042024-02-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA>103.50100-878서울특별시 중구 흥인동 1-1 성동공업고등학교서울특별시 중구 다산로 290, 성동공업고등학교 (흥인동)4571성동공업고등학교2024-02-29 13:26:55I2023-12-03 00:02:00.0위탁급식영업201428.149731451851.925541<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
30930100003010000-120-2024-000052024-02-29<NA>1영업/정상1영업<NA><NA><NA><NA>02 15770001303.00100-070서울특별시 중구 소공동 1 롯데백화점 본점서울특별시 중구 남대문로 81, 롯데백화점 본점 15층 (소공동)4533푸디스트 주식회사 롯데백화점 본점점2024-03-11 15:04:32U2023-12-02 23:03:00.0위탁급식영업198259.653577451392.198219<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
31030100003010000-120-2024-000062024-02-29<NA>1영업/정상1영업<NA><NA><NA><NA>02 21496619408.47100-192서울특별시 중구 을지로2가 205 신한L Tower서울특별시 중구 삼일대로 358, 신한L Tower 지하2층 (을지로2가)4542씨제이프레시웨이(주) 신한라이프점2024-02-29 16:15:29I2023-12-03 00:02:00.0위탁급식영업198877.134151451578.377237<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
31130100003010000-120-2024-000072024-02-29<NA>1영업/정상1영업<NA><NA><NA><NA>0234092971760.00100-701서울특별시 중구 예관동 120-1 중구청서울특별시 중구 창경궁로 17, 중구청 지1층 (예관동)4558(주)호박패밀리 중구청점2024-02-29 17:32:41I2023-12-03 00:02:00.0위탁급식영업199732.248739451272.806325<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
31230100003010000-120-2024-000082024-03-04<NA>1영업/정상1영업<NA><NA><NA><NA><NA>878.90100-821서울특별시 중구 신당동 161 성동고등학교서울특별시 중구 퇴계로90길 17, 성동고등학교 (신당동)4579성동고등학교2024-03-04 14:27:00I2023-12-03 00:06:00.0위탁급식영업201945.85235451316.61274<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
31330100003010000-120-2024-000092024-03-04<NA>1영업/정상1영업<NA><NA><NA><NA>025738215780.00100-889서울특별시 중구 신당동 250-3 성동글로벌경영고등학교서울특별시 중구 퇴계로 375, 성동글로벌경영고등학교 (신당동)4566성동글로벌경영고등학교2024-03-04 14:32:25I2023-12-03 00:06:00.0위탁급식영업201083.133966451485.056385<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
31430100003010000-120-2024-000102024-03-13<NA>1영업/정상1영업<NA><NA><NA><NA><NA>1157.68100-192서울특별시 중구 을지로2가 203 파인에비뉴서울특별시 중구 을지로 100, 파인에비뉴 A동 25층 (을지로2가)4551(주)아워홈 신한카드중구점2024-03-13 13:29:58I2023-12-02 23:06:00.0위탁급식영업198921.241301451495.985361<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>