Overview

Dataset statistics

Number of variables30
Number of observations1581
Missing cells13206
Missing cells (%)27.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory390.7 KiB
Average record size in memory253.1 B

Variable types

Categorical8
Numeric5
DateTime5
Unsupported5
Text7

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),업소구분명,소재지,지정일자,신청일자,항목값1
Author동대문구
URLhttps://data.seoul.go.kr/dataList/OA-19457/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
상세영업상태코드 is highly imbalanced (53.0%)Imbalance
상세영업상태명 is highly imbalanced (53.0%)Imbalance
데이터갱신구분 is highly imbalanced (77.9%)Imbalance
업소구분명 is highly imbalanced (64.5%)Imbalance
항목값1 is highly imbalanced (60.6%)Imbalance
인허가취소일자 has 1581 (100.0%) missing valuesMissing
폐업일자 has 801 (50.7%) missing valuesMissing
휴업시작일자 has 795 (50.3%) missing valuesMissing
휴업종료일자 has 1581 (100.0%) missing valuesMissing
재개업일자 has 1581 (100.0%) missing valuesMissing
전화번호 has 442 (28.0%) missing valuesMissing
소재지면적 has 1581 (100.0%) missing valuesMissing
소재지우편번호 has 301 (19.0%) missing valuesMissing
도로명주소 has 209 (13.2%) missing valuesMissing
도로명우편번호 has 1029 (65.1%) missing valuesMissing
업태구분명 has 1581 (100.0%) missing valuesMissing
좌표정보(X) has 162 (10.2%) missing valuesMissing
좌표정보(Y) has 162 (10.2%) missing valuesMissing
소재지 has 136 (8.6%) missing valuesMissing
지정일자 has 1130 (71.5%) missing valuesMissing
신청일자 has 125 (7.9%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 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
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-29 19:56:23.572461
Analysis finished2024-04-29 19:56:24.694724
Duration1.12 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size12.5 KiB
3050000
1581 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3050000
2nd row3050000
3rd row3050000
4th row3050000
5th row3050000

Common Values

ValueCountFrequency (%)
3050000 1581
100.0%

Length

2024-04-30T04:56:24.760288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:56:24.838997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3050000 1581
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct1581
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0500001 × 1017
Minimum3.0500001 × 1017
Maximum3.0500001 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.0 KiB
2024-04-30T04:56:24.945325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.0500001 × 1017
5-th percentile3.0500001 × 1017
Q13.0500001 × 1017
median3.0500001 × 1017
Q33.0500001 × 1017
95-th percentile3.0500001 × 1017
Maximum3.0500001 × 1017
Range3000018
Interquartile range (IQR)1299968

Descriptive statistics

Standard deviation809347
Coefficient of variation (CV)2.6535966 × 10-12
Kurtosis-0.98461705
Mean3.0500001 × 1017
Median Absolute Deviation (MAD)600000
Skewness-0.037552004
Sum2.5896765 × 1018
Variance6.5504256 × 1011
MonotonicityStrictly increasing
2024-04-30T04:56:25.069021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
305000014199400001 1
 
0.1%
305000014201200244 1
 
0.1%
305000014201200242 1
 
0.1%
305000014201200241 1
 
0.1%
305000014201200240 1
 
0.1%
305000014201200239 1
 
0.1%
305000014201200238 1
 
0.1%
305000014201200237 1
 
0.1%
305000014201200236 1
 
0.1%
305000014201200235 1
 
0.1%
Other values (1571) 1571
99.4%
ValueCountFrequency (%)
305000014199400001 1
0.1%
305000014199400002 1
0.1%
305000014199400003 1
0.1%
305000014199400022 1
0.1%
305000014199400023 1
0.1%
305000014199400024 1
0.1%
305000014199400025 1
0.1%
305000014199400026 1
0.1%
305000014199400027 1
0.1%
305000014199400028 1
0.1%
ValueCountFrequency (%)
305000014202400019 1
0.1%
305000014202400018 1
0.1%
305000014202400017 1
0.1%
305000014202400016 1
0.1%
305000014202400015 1
0.1%
305000014202400014 1
0.1%
305000014202400013 1
0.1%
305000014202400012 1
0.1%
305000014202400011 1
0.1%
305000014202400010 1
0.1%

인허가일자
Date

Distinct605
Distinct (%)38.3%
Missing0
Missing (%)0.0%
Memory size12.5 KiB
Minimum1994-03-02 00:00:00
Maximum2024-04-23 00:00:00
2024-04-30T04:56:25.185456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:56:25.296895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1581
Missing (%)100.0%
Memory size14.0 KiB

영업상태코드
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size12.5 KiB
1
800 
3
780 
5
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
1 800
50.6%
3 780
49.3%
5 1
 
0.1%

Length

2024-04-30T04:56:25.394805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:56:25.477681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 800
50.6%
3 780
49.3%
5 1
 
0.1%

영업상태명
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size12.5 KiB
영업/정상
800 
폐업
780 
제외/삭제/전출
 
1

Length

Max length8
Median length5
Mean length3.5218216
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 800
50.6%
폐업 780
49.3%
제외/삭제/전출 1
 
0.1%

Length

2024-04-30T04:56:25.576682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:56:25.668954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 800
50.6%
폐업 780
49.3%
제외/삭제/전출 1
 
0.1%

상세영업상태코드
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size12.5 KiB
11
783 
2
780 
3
 
13
0
 
4
5
 
1

Length

Max length2
Median length1
Mean length1.4952562
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
11 783
49.5%
2 780
49.3%
3 13
 
0.8%
0 4
 
0.3%
5 1
 
0.1%

Length

2024-04-30T04:56:25.762185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:56:25.862959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11 783
49.5%
2 780
49.3%
3 13
 
0.8%
0 4
 
0.3%
5 1
 
0.1%

상세영업상태명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size12.5 KiB
영업
783 
폐업
780 
재개업
 
13
<NA>
 
4
제외사항
 
1

Length

Max length4
Median length2
Mean length2.0145478
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
영업 783
49.5%
폐업 780
49.3%
재개업 13
 
0.8%
<NA> 4
 
0.3%
제외사항 1
 
0.1%

Length

2024-04-30T04:56:25.979122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:56:26.097148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 783
49.5%
폐업 780
49.3%
재개업 13
 
0.8%
na 4
 
0.3%
제외사항 1
 
0.1%

폐업일자
Date

MISSING 

Distinct120
Distinct (%)15.4%
Missing801
Missing (%)50.7%
Memory size12.5 KiB
Minimum2006-01-01 00:00:00
Maximum2023-04-28 00:00:00
2024-04-30T04:56:26.209363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:56:26.317790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Date

MISSING 

Distinct113
Distinct (%)14.4%
Missing795
Missing (%)50.3%
Memory size12.5 KiB
Minimum2012-07-25 00:00:00
Maximum2018-02-21 00:00:00
2024-04-30T04:56:26.421188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:56:26.545039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1581
Missing (%)100.0%
Memory size14.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1581
Missing (%)100.0%
Memory size14.0 KiB

전화번호
Text

MISSING 

Distinct1106
Distinct (%)97.1%
Missing442
Missing (%)28.0%
Memory size12.5 KiB
2024-04-30T04:56:26.822619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10
Mean length9.9552239
Min length7

Characters and Unicode

Total characters11339
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1075 ?
Unique (%)94.4%

Sample

1st row0222436275
2nd row0222174116
3rd row0222156544
4th row0222493384
5th row0222468879
ValueCountFrequency (%)
02 359
 
23.4%
964 4
 
0.3%
070-7092-7315 3
 
0.2%
969 3
 
0.2%
1577-0711 3
 
0.2%
963 3
 
0.2%
959 3
 
0.2%
957 3
 
0.2%
2215-0178 2
 
0.1%
0222124749 2
 
0.1%
Other values (1118) 1148
74.9%
2024-04-30T04:56:27.158880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2771
24.4%
0 1514
13.4%
9 1049
 
9.3%
4 922
 
8.1%
6 906
 
8.0%
1 746
 
6.6%
3 705
 
6.2%
5 695
 
6.1%
7 675
 
6.0%
8 520
 
4.6%
Other values (2) 836
 
7.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10503
92.6%
Space Separator 472
 
4.2%
Dash Punctuation 364
 
3.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 2771
26.4%
0 1514
14.4%
9 1049
 
10.0%
4 922
 
8.8%
6 906
 
8.6%
1 746
 
7.1%
3 705
 
6.7%
5 695
 
6.6%
7 675
 
6.4%
8 520
 
5.0%
Space Separator
ValueCountFrequency (%)
472
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 364
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11339
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 2771
24.4%
0 1514
13.4%
9 1049
 
9.3%
4 922
 
8.1%
6 906
 
8.0%
1 746
 
6.6%
3 705
 
6.2%
5 695
 
6.1%
7 675
 
6.0%
8 520
 
4.6%
Other values (2) 836
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11339
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 2771
24.4%
0 1514
13.4%
9 1049
 
9.3%
4 922
 
8.1%
6 906
 
8.0%
1 746
 
6.6%
3 705
 
6.2%
5 695
 
6.1%
7 675
 
6.0%
8 520
 
4.6%
Other values (2) 836
 
7.4%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1581
Missing (%)100.0%
Memory size14.0 KiB

소재지우편번호
Text

MISSING 

Distinct120
Distinct (%)9.4%
Missing301
Missing (%)19.0%
Memory size12.5 KiB
2024-04-30T04:56:27.400956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0085938
Min length6

Characters and Unicode

Total characters7691
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

Unique31 ?
Unique (%)2.4%

Sample

1st row130032
2nd row130032
3rd row130032
4th row130092
5th row130092
ValueCountFrequency (%)
130101 85
 
6.6%
130081 52
 
4.1%
130021 51
 
4.0%
130070 47
 
3.7%
130102 44
 
3.4%
130050 44
 
3.4%
130092 42
 
3.3%
130031 38
 
3.0%
130082 36
 
2.8%
130060 36
 
2.8%
Other values (110) 805
62.9%
2024-04-30T04:56:27.712309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2504
32.6%
1 1987
25.8%
3 1537
20.0%
8 444
 
5.8%
2 443
 
5.8%
7 188
 
2.4%
4 181
 
2.4%
6 171
 
2.2%
5 127
 
1.7%
9 98
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7680
99.9%
Dash Punctuation 11
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2504
32.6%
1 1987
25.9%
3 1537
20.0%
8 444
 
5.8%
2 443
 
5.8%
7 188
 
2.4%
4 181
 
2.4%
6 171
 
2.2%
5 127
 
1.7%
9 98
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7691
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2504
32.6%
1 1987
25.8%
3 1537
20.0%
8 444
 
5.8%
2 443
 
5.8%
7 188
 
2.4%
4 181
 
2.4%
6 171
 
2.2%
5 127
 
1.7%
9 98
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7691
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2504
32.6%
1 1987
25.8%
3 1537
20.0%
8 444
 
5.8%
2 443
 
5.8%
7 188
 
2.4%
4 181
 
2.4%
6 171
 
2.2%
5 127
 
1.7%
9 98
 
1.3%

지번주소
Text

Distinct1315
Distinct (%)83.7%
Missing9
Missing (%)0.6%
Memory size12.5 KiB
2024-04-30T04:56:27.923274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length43
Mean length24.220102
Min length15

Characters and Unicode

Total characters38074
Distinct characters194
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1101 ?
Unique (%)70.0%

Sample

1st row서울특별시 동대문구 답십리동 58-16번지
2nd row서울특별시 동대문구 답십리동 53-42번지
3rd row서울특별시 동대문구 답십리동 40-53번지
4th row서울특별시 동대문구 휘경동 312-203번지
5th row서울특별시 동대문구 휘경동 293-96번지
ValueCountFrequency (%)
서울특별시 1572
23.8%
동대문구 1572
23.8%
답십리동 376
 
5.7%
장안동 371
 
5.6%
이문동 174
 
2.6%
제기동 152
 
2.3%
용두동 146
 
2.2%
휘경동 129
 
2.0%
청량리동 85
 
1.3%
번지 77
 
1.2%
Other values (1408) 1947
29.5%
2024-04-30T04:56:28.253440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6565
17.2%
동 3168
 
8.3%
문 1748
 
4.6%
대 1589
 
4.2%
시 1574
 
4.1%
서 1572
 
4.1%
특 1572
 
4.1%
별 1572
 
4.1%
구 1572
 
4.1%
울 1572
 
4.1%
Other values (184) 15570
40.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 23028
60.5%
Decimal Number 7020
 
18.4%
Space Separator 6565
 
17.2%
Dash Punctuation 1402
 
3.7%
Uppercase Letter 31
 
0.1%
Other Punctuation 18
 
< 0.1%
Close Punctuation 3
 
< 0.1%
Open Punctuation 3
 
< 0.1%
Lowercase Letter 2
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 3168
13.8%
문 1748
 
7.6%
대 1589
 
6.9%
시 1574
 
6.8%
서 1572
 
6.8%
특 1572
 
6.8%
별 1572
 
6.8%
구 1572
 
6.8%
울 1572
 
6.8%
지 1461
 
6.3%
Other values (155) 5628
24.4%
Decimal Number
ValueCountFrequency (%)
1 1341
19.1%
2 944
13.4%
3 943
13.4%
4 716
10.2%
5 609
8.7%
0 533
 
7.6%
9 517
 
7.4%
6 499
 
7.1%
8 492
 
7.0%
7 426
 
6.1%
Uppercase Letter
ValueCountFrequency (%)
S 9
29.0%
A 8
25.8%
K 8
25.8%
L 2
 
6.5%
P 1
 
3.2%
T 1
 
3.2%
Y 1
 
3.2%
B 1
 
3.2%
Other Punctuation
ValueCountFrequency (%)
, 9
50.0%
@ 5
27.8%
. 4
22.2%
Lowercase Letter
ValueCountFrequency (%)
s 1
50.0%
k 1
50.0%
Space Separator
ValueCountFrequency (%)
6565
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1402
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Other Symbol
ValueCountFrequency (%)
ⓐ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 23028
60.5%
Common 15013
39.4%
Latin 33
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 3168
13.8%
문 1748
 
7.6%
대 1589
 
6.9%
시 1574
 
6.8%
서 1572
 
6.8%
특 1572
 
6.8%
별 1572
 
6.8%
구 1572
 
6.8%
울 1572
 
6.8%
지 1461
 
6.3%
Other values (155) 5628
24.4%
Common
ValueCountFrequency (%)
6565
43.7%
- 1402
 
9.3%
1 1341
 
8.9%
2 944
 
6.3%
3 943
 
6.3%
4 716
 
4.8%
5 609
 
4.1%
0 533
 
3.6%
9 517
 
3.4%
6 499
 
3.3%
Other values (9) 944
 
6.3%
Latin
ValueCountFrequency (%)
S 9
27.3%
A 8
24.2%
K 8
24.2%
L 2
 
6.1%
P 1
 
3.0%
T 1
 
3.0%
Y 1
 
3.0%
s 1
 
3.0%
k 1
 
3.0%
B 1
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 23028
60.5%
ASCII 15045
39.5%
Enclosed Alphanum 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6565
43.6%
- 1402
 
9.3%
1 1341
 
8.9%
2 944
 
6.3%
3 943
 
6.3%
4 716
 
4.8%
5 609
 
4.0%
0 533
 
3.5%
9 517
 
3.4%
6 499
 
3.3%
Other values (18) 976
 
6.5%
Hangul
ValueCountFrequency (%)
동 3168
13.8%
문 1748
 
7.6%
대 1589
 
6.9%
시 1574
 
6.8%
서 1572
 
6.8%
특 1572
 
6.8%
별 1572
 
6.8%
구 1572
 
6.8%
울 1572
 
6.8%
지 1461
 
6.3%
Other values (155) 5628
24.4%
Enclosed Alphanum
ValueCountFrequency (%)
ⓐ 1
100.0%

도로명주소
Text

MISSING 

Distinct1246
Distinct (%)90.8%
Missing209
Missing (%)13.2%
Memory size12.5 KiB
2024-04-30T04:56:28.517962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length54
Mean length28.311224
Min length22

Characters and Unicode

Total characters38843
Distinct characters246
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1130 ?
Unique (%)82.4%

Sample

1st row서울특별시 동대문구 답십리로52길 13-2 (답십리동)
2nd row서울특별시 동대문구 답십리로50길 7 (답십리동)
3rd row서울특별시 동대문구 답십리로56길 71 (답십리동)
4th row서울특별시 동대문구 서울시립대로29가길 30 (휘경동)
5th row서울특별시 동대문구 망우로18가길 76 (휘경동)
ValueCountFrequency (%)
서울특별시 1372
18.8%
동대문구 1372
18.8%
장안동 329
 
4.5%
답십리동 159
 
2.2%
전농동 149
 
2.0%
이문동 148
 
2.0%
1층 128
 
1.8%
용두동 126
 
1.7%
제기동 122
 
1.7%
휘경동 106
 
1.5%
Other values (955) 3287
45.0%
2024-04-30T04:56:28.889115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6490
 
16.7%
동 2828
 
7.3%
문 1630
 
4.2%
대 1606
 
4.1%
시 1453
 
3.7%
서 1410
 
3.6%
울 1406
 
3.6%
( 1378
 
3.5%
) 1378
 
3.5%
특 1372
 
3.5%
Other values (236) 17892
46.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 23815
61.3%
Space Separator 6490
 
16.7%
Decimal Number 5195
 
13.4%
Open Punctuation 1378
 
3.5%
Close Punctuation 1378
 
3.5%
Other Punctuation 350
 
0.9%
Dash Punctuation 185
 
0.5%
Uppercase Letter 48
 
0.1%
Lowercase Letter 2
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 2828
 
11.9%
문 1630
 
6.8%
대 1606
 
6.7%
시 1453
 
6.1%
서 1410
 
5.9%
울 1406
 
5.9%
특 1372
 
5.8%
별 1372
 
5.8%
구 1372
 
5.8%
로 1370
 
5.8%
Other values (202) 7996
33.6%
Uppercase Letter
ValueCountFrequency (%)
A 10
20.8%
S 9
18.8%
K 8
16.7%
M 5
10.4%
B 4
 
8.3%
L 2
 
4.2%
I 2
 
4.2%
U 2
 
4.2%
Y 1
 
2.1%
E 1
 
2.1%
Other values (4) 4
 
8.3%
Decimal Number
ValueCountFrequency (%)
1 1270
24.4%
2 788
15.2%
3 554
10.7%
4 477
 
9.2%
0 394
 
7.6%
6 376
 
7.2%
5 374
 
7.2%
7 359
 
6.9%
8 335
 
6.4%
9 268
 
5.2%
Other Punctuation
ValueCountFrequency (%)
, 342
97.7%
@ 6
 
1.7%
. 2
 
0.6%
Space Separator
ValueCountFrequency (%)
6490
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1378
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1378
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 185
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Other Symbol
ValueCountFrequency (%)
ⓐ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 23815
61.3%
Common 14978
38.6%
Latin 50
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 2828
 
11.9%
문 1630
 
6.8%
대 1606
 
6.7%
시 1453
 
6.1%
서 1410
 
5.9%
울 1406
 
5.9%
특 1372
 
5.8%
별 1372
 
5.8%
구 1372
 
5.8%
로 1370
 
5.8%
Other values (202) 7996
33.6%
Common
ValueCountFrequency (%)
6490
43.3%
( 1378
 
9.2%
) 1378
 
9.2%
1 1270
 
8.5%
2 788
 
5.3%
3 554
 
3.7%
4 477
 
3.2%
0 394
 
2.6%
6 376
 
2.5%
5 374
 
2.5%
Other values (9) 1499
 
10.0%
Latin
ValueCountFrequency (%)
A 10
20.0%
S 9
18.0%
K 8
16.0%
M 5
10.0%
B 4
 
8.0%
e 2
 
4.0%
L 2
 
4.0%
I 2
 
4.0%
U 2
 
4.0%
Y 1
 
2.0%
Other values (5) 5
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 23815
61.3%
ASCII 15027
38.7%
Enclosed Alphanum 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6490
43.2%
( 1378
 
9.2%
) 1378
 
9.2%
1 1270
 
8.5%
2 788
 
5.2%
3 554
 
3.7%
4 477
 
3.2%
0 394
 
2.6%
6 376
 
2.5%
5 374
 
2.5%
Other values (23) 1548
 
10.3%
Hangul
ValueCountFrequency (%)
동 2828
 
11.9%
문 1630
 
6.8%
대 1606
 
6.7%
시 1453
 
6.1%
서 1410
 
5.9%
울 1406
 
5.9%
특 1372
 
5.8%
별 1372
 
5.8%
구 1372
 
5.8%
로 1370
 
5.8%
Other values (202) 7996
33.6%
Enclosed Alphanum
ValueCountFrequency (%)
ⓐ 1
100.0%

도로명우편번호
Text

MISSING 

Distinct219
Distinct (%)39.7%
Missing1029
Missing (%)65.1%
Memory size12.5 KiB
2024-04-30T04:56:29.176132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.4836957
Min length5

Characters and Unicode

Total characters3027
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

Unique82 ?
Unique (%)14.9%

Sample

1st row130844
2nd row02626
3rd row130812
4th row130829
5th row02568
ValueCountFrequency (%)
130101 25
 
4.5%
130031 15
 
2.7%
130840 13
 
2.4%
130081 10
 
1.8%
130070 10
 
1.8%
130864 7
 
1.3%
130876 7
 
1.3%
02637 6
 
1.1%
130060 6
 
1.1%
02636 6
 
1.1%
Other values (209) 447
81.0%
2024-04-30T04:56:29.573644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 779
25.7%
1 441
14.6%
2 404
13.3%
3 364
12.0%
5 231
 
7.6%
8 226
 
7.5%
4 205
 
6.8%
6 187
 
6.2%
7 100
 
3.3%
9 85
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3022
99.8%
Dash Punctuation 5
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 779
25.8%
1 441
14.6%
2 404
13.4%
3 364
12.0%
5 231
 
7.6%
8 226
 
7.5%
4 205
 
6.8%
6 187
 
6.2%
7 100
 
3.3%
9 85
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3027
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 779
25.7%
1 441
14.6%
2 404
13.3%
3 364
12.0%
5 231
 
7.6%
8 226
 
7.5%
4 205
 
6.8%
6 187
 
6.2%
7 100
 
3.3%
9 85
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3027
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 779
25.7%
1 441
14.6%
2 404
13.3%
3 364
12.0%
5 231
 
7.6%
8 226
 
7.5%
4 205
 
6.8%
6 187
 
6.2%
7 100
 
3.3%
9 85
 
2.8%

사업장명
Text

Distinct1335
Distinct (%)84.4%
Missing0
Missing (%)0.0%
Memory size12.5 KiB
2024-04-30T04:56:29.801585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length24
Mean length6.773561
Min length2

Characters and Unicode

Total characters10709
Distinct characters459
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

Unique1179 ?
Unique (%)74.6%

Sample

1st row성일유통
2nd row윤영슈퍼
3rd row한아름슈퍼
4th row동네슈퍼
5th row여주쌀상회
ValueCountFrequency (%)
씨유 100
 
4.8%
gs25 95
 
4.5%
세븐일레븐 70
 
3.4%
cu 28
 
1.3%
지에스25 13
 
0.6%
위드미 12
 
0.6%
미니스톱 12
 
0.6%
현대슈퍼 11
 
0.5%
이마트24 10
 
0.5%
주)코리아세븐 10
 
0.5%
Other values (1317) 1727
82.7%
2024-04-30T04:56:30.302852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
510
 
4.8%
점 502
 
4.7%
마 393
 
3.7%
트 377
 
3.5%
퍼 355
 
3.3%
슈 341
 
3.2%
리 215
 
2.0%
2 207
 
1.9%
븐 194
 
1.8%
장 191
 
1.8%
Other values (449) 7424
69.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9050
84.5%
Space Separator 510
 
4.8%
Uppercase Letter 472
 
4.4%
Decimal Number 455
 
4.2%
Close Punctuation 96
 
0.9%
Open Punctuation 96
 
0.9%
Lowercase Letter 16
 
0.1%
Other Punctuation 11
 
0.1%
Modifier Symbol 2
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 502
 
5.5%
마 393
 
4.3%
트 377
 
4.2%
퍼 355
 
3.9%
슈 341
 
3.8%
리 215
 
2.4%
븐 194
 
2.1%
장 191
 
2.1%
대 184
 
2.0%
안 174
 
1.9%
Other values (400) 6124
67.7%
Uppercase Letter
ValueCountFrequency (%)
S 159
33.7%
G 155
32.8%
C 49
 
10.4%
U 45
 
9.5%
K 10
 
2.1%
A 9
 
1.9%
L 9
 
1.9%
M 5
 
1.1%
I 4
 
0.8%
D 4
 
0.8%
Other values (10) 23
 
4.9%
Lowercase Letter
ValueCountFrequency (%)
e 5
31.2%
n 3
18.8%
u 1
 
6.2%
s 1
 
6.2%
o 1
 
6.2%
z 1
 
6.2%
t 1
 
6.2%
k 1
 
6.2%
r 1
 
6.2%
a 1
 
6.2%
Decimal Number
ValueCountFrequency (%)
2 207
45.5%
5 179
39.3%
4 28
 
6.2%
1 13
 
2.9%
3 12
 
2.6%
9 7
 
1.5%
6 6
 
1.3%
0 3
 
0.7%
Other Punctuation
ValueCountFrequency (%)
/ 4
36.4%
. 3
27.3%
? 1
 
9.1%
@ 1
 
9.1%
! 1
 
9.1%
& 1
 
9.1%
Space Separator
ValueCountFrequency (%)
510
100.0%
Close Punctuation
ValueCountFrequency (%)
) 96
100.0%
Open Punctuation
ValueCountFrequency (%)
( 96
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9050
84.5%
Common 1171
 
10.9%
Latin 488
 
4.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 502
 
5.5%
마 393
 
4.3%
트 377
 
4.2%
퍼 355
 
3.9%
슈 341
 
3.8%
리 215
 
2.4%
븐 194
 
2.1%
장 191
 
2.1%
대 184
 
2.0%
안 174
 
1.9%
Other values (400) 6124
67.7%
Latin
ValueCountFrequency (%)
S 159
32.6%
G 155
31.8%
C 49
 
10.0%
U 45
 
9.2%
K 10
 
2.0%
A 9
 
1.8%
L 9
 
1.8%
M 5
 
1.0%
e 5
 
1.0%
I 4
 
0.8%
Other values (20) 38
 
7.8%
Common
ValueCountFrequency (%)
510
43.6%
2 207
17.7%
5 179
 
15.3%
) 96
 
8.2%
( 96
 
8.2%
4 28
 
2.4%
1 13
 
1.1%
3 12
 
1.0%
9 7
 
0.6%
6 6
 
0.5%
Other values (9) 17
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9050
84.5%
ASCII 1659
 
15.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
510
30.7%
2 207
12.5%
5 179
 
10.8%
S 159
 
9.6%
G 155
 
9.3%
) 96
 
5.8%
( 96
 
5.8%
C 49
 
3.0%
U 45
 
2.7%
4 28
 
1.7%
Other values (39) 135
 
8.1%
Hangul
ValueCountFrequency (%)
점 502
 
5.5%
마 393
 
4.3%
트 377
 
4.2%
퍼 355
 
3.9%
슈 341
 
3.8%
리 215
 
2.4%
븐 194
 
2.1%
장 191
 
2.1%
대 184
 
2.0%
안 174
 
1.9%
Other values (400) 6124
67.7%

최종수정일자
Date

Distinct1526
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Memory size12.5 KiB
Minimum2007-07-21 10:44:03
Maximum2024-04-23 11:03:44
2024-04-30T04:56:30.425000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:56:30.535244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size12.5 KiB
I
1525 
U
 
56

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 1525
96.5%
U 56
 
3.5%

Length

2024-04-30T04:56:30.632019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:56:30.710557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 1525
96.5%
u 56
 
3.5%

데이터갱신일자
Date

Distinct75
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size12.5 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:06:00
2024-04-30T04:56:30.802551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:56:30.930712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1581
Missing (%)100.0%
Memory size14.0 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1078
Distinct (%)76.0%
Missing162
Missing (%)10.2%
Infinite0
Infinite (%)0.0%
Mean204755.01
Minimum202032.94
Maximum206618.08
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.0 KiB
2024-04-30T04:56:31.056640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum202032.94
5-th percentile202534.66
Q1203821.95
median205011.35
Q3205746.04
95-th percentile206311.05
Maximum206618.08
Range4585.1467
Interquartile range (IQR)1924.0893

Descriptive statistics

Standard deviation1189.5034
Coefficient of variation (CV)0.0058093982
Kurtosis-0.74751024
Mean204755.01
Median Absolute Deviation (MAD)829.49199
Skewness-0.55167184
Sum2.9054735 × 108
Variance1414918.3
MonotonicityNot monotonic
2024-04-30T04:56:31.163203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
205208.167449959 8
 
0.5%
205381.986112403 7
 
0.4%
204718.0 5
 
0.3%
206120.983279154 5
 
0.3%
206455.357834541 5
 
0.3%
206170.308088921 4
 
0.3%
203009.188734992 4
 
0.3%
203900.727367772 4
 
0.3%
204698.776644614 4
 
0.3%
206521.405320134 4
 
0.3%
Other values (1068) 1369
86.6%
(Missing) 162
 
10.2%
ValueCountFrequency (%)
202032.935534754 1
0.1%
202034.733564967 1
0.1%
202036.453390905 1
0.1%
202042.817335648 2
0.1%
202042.827600608 1
0.1%
202052.556195859 1
0.1%
202061.169089769 1
0.1%
202090.987353843 1
0.1%
202091.896824059 2
0.1%
202096.000930557 1
0.1%
ValueCountFrequency (%)
206618.082278385 1
 
0.1%
206592.423303981 3
0.2%
206590.046202018 3
0.2%
206586.572428103 1
 
0.1%
206560.736934242 1
 
0.1%
206543.156690365 2
0.1%
206538.84863498 1
 
0.1%
206522.763968502 1
 
0.1%
206521.405320134 4
0.3%
206488.078041774 2
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct1078
Distinct (%)76.0%
Missing162
Missing (%)10.2%
Infinite0
Infinite (%)0.0%
Mean453060.72
Minimum451011.19
Maximum455917.55
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.0 KiB
2024-04-30T04:56:31.308558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum451011.19
5-th percentile451400.3
Q1452171.16
median452875.45
Q3453884.06
95-th percentile455210.09
Maximum455917.55
Range4906.3583
Interquartile range (IQR)1712.8989

Descriptive statistics

Standard deviation1154.8067
Coefficient of variation (CV)0.0025489006
Kurtosis-0.61189252
Mean453060.72
Median Absolute Deviation (MAD)858.77382
Skewness0.4338096
Sum6.4289316 × 108
Variance1333578.6
MonotonicityNot monotonic
2024-04-30T04:56:31.449821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
452466.868525878 8
 
0.5%
451896.756025119 7
 
0.4%
452269.0 5
 
0.3%
452775.947650727 5
 
0.3%
452077.137056886 5
 
0.3%
451470.889060822 4
 
0.3%
453776.829188234 4
 
0.3%
453480.356785847 4
 
0.3%
453786.184389292 4
 
0.3%
451940.119059947 4
 
0.3%
Other values (1068) 1369
86.6%
(Missing) 162
 
10.2%
ValueCountFrequency (%)
451011.194201757 1
0.1%
451025.902075739 1
0.1%
451042.369315593 1
0.1%
451082.41626322 1
0.1%
451088.609204795 1
0.1%
451098.299986522 2
0.1%
451104.428484125 1
0.1%
451106.632184873 2
0.1%
451110.245309908 2
0.1%
451118.479199016 2
0.1%
ValueCountFrequency (%)
455917.552544887 3
0.2%
455899.982370316 2
0.1%
455876.231869346 1
 
0.1%
455813.713540339 1
 
0.1%
455801.638525525 1
 
0.1%
455790.631069022 2
0.1%
455753.744478701 1
 
0.1%
455750.85927464 1
 
0.1%
455746.103581101 1
 
0.1%
455714.48034047 1
 
0.1%

업소구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size12.5 KiB
지정
1417 
<NA>
 
125
종료
 
39

Length

Max length4
Median length2
Mean length2.1581278
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지정 1417
89.6%
<NA> 125
 
7.9%
종료 39
 
2.5%

Length

2024-04-30T04:56:31.575439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:56:31.684886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지정 1417
89.6%
na 125
 
7.9%
종료 39
 
2.5%

소재지
Text

MISSING 

Distinct1366
Distinct (%)94.5%
Missing136
Missing (%)8.6%
Memory size12.5 KiB
2024-04-30T04:56:31.927456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length39
Mean length22.691349
Min length9

Characters and Unicode

Total characters32789
Distinct characters155
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

Unique1294 ?
Unique (%)89.6%

Sample

1st row서울특별시 동대문구 답십리동 58-16
2nd row서울특별시 동대문구 답십리동 36-19
3rd row서울특별시 동대문구 답십리동 40-53
4th row서울특별시 동대문구 휘경동 312-203
5th row서울특별시 동대문구 휘경동 293-96
ValueCountFrequency (%)
동대문구 1429
21.9%
서울특별시 1366
20.9%
장안동 335
 
5.1%
답십리동 186
 
2.8%
전농동 171
 
2.6%
이문동 164
 
2.5%
호 154
 
2.4%
제기동 141
 
2.2%
용두동 128
 
2.0%
휘경동 115
 
1.8%
Other values (1372) 2343
35.9%
2024-04-30T04:56:32.324130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5485
16.7%
동 2891
 
8.8%
문 1594
 
4.9%
대 1445
 
4.4%
구 1429
 
4.4%
서 1378
 
4.2%
울 1378
 
4.2%
시 1367
 
4.2%
별 1367
 
4.2%
특 1367
 
4.2%
Other values (145) 13088
39.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 20026
61.1%
Decimal Number 6466
 
19.7%
Space Separator 5485
 
16.7%
Dash Punctuation 773
 
2.4%
Other Punctuation 20
 
0.1%
Uppercase Letter 12
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%
Lowercase Letter 2
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 2891
14.4%
문 1594
 
8.0%
대 1445
 
7.2%
구 1429
 
7.1%
서 1378
 
6.9%
울 1378
 
6.9%
시 1367
 
6.8%
별 1367
 
6.8%
특 1367
 
6.8%
지 906
 
4.5%
Other values (119) 4904
24.5%
Decimal Number
ValueCountFrequency (%)
1 1246
19.3%
2 893
13.8%
3 869
13.4%
4 657
10.2%
5 551
8.5%
9 476
 
7.4%
0 468
 
7.2%
6 464
 
7.2%
8 445
 
6.9%
7 397
 
6.1%
Uppercase Letter
ValueCountFrequency (%)
A 7
58.3%
K 1
 
8.3%
S 1
 
8.3%
P 1
 
8.3%
T 1
 
8.3%
B 1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
, 10
50.0%
@ 6
30.0%
. 4
 
20.0%
Lowercase Letter
ValueCountFrequency (%)
s 1
50.0%
k 1
50.0%
Space Separator
ValueCountFrequency (%)
5485
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 773
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 20026
61.1%
Common 12749
38.9%
Latin 14
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 2891
14.4%
문 1594
 
8.0%
대 1445
 
7.2%
구 1429
 
7.1%
서 1378
 
6.9%
울 1378
 
6.9%
시 1367
 
6.8%
별 1367
 
6.8%
특 1367
 
6.8%
지 906
 
4.5%
Other values (119) 4904
24.5%
Common
ValueCountFrequency (%)
5485
43.0%
1 1246
 
9.8%
2 893
 
7.0%
3 869
 
6.8%
- 773
 
6.1%
4 657
 
5.2%
5 551
 
4.3%
9 476
 
3.7%
0 468
 
3.7%
6 464
 
3.6%
Other values (8) 867
 
6.8%
Latin
ValueCountFrequency (%)
A 7
50.0%
K 1
 
7.1%
S 1
 
7.1%
P 1
 
7.1%
T 1
 
7.1%
s 1
 
7.1%
k 1
 
7.1%
B 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 20026
61.1%
ASCII 12763
38.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5485
43.0%
1 1246
 
9.8%
2 893
 
7.0%
3 869
 
6.8%
- 773
 
6.1%
4 657
 
5.1%
5 551
 
4.3%
9 476
 
3.7%
0 468
 
3.7%
6 464
 
3.6%
Other values (16) 881
 
6.9%
Hangul
ValueCountFrequency (%)
동 2891
14.4%
문 1594
 
8.0%
대 1445
 
7.2%
구 1429
 
7.1%
서 1378
 
6.9%
울 1378
 
6.9%
시 1367
 
6.8%
별 1367
 
6.8%
특 1367
 
6.8%
지 906
 
4.5%
Other values (119) 4904
24.5%

지정일자
Real number (ℝ)

MISSING 

Distinct346
Distinct (%)76.7%
Missing1130
Missing (%)71.5%
Infinite0
Infinite (%)0.0%
Mean20141378
Minimum20040521
Maximum20200916
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.0 KiB
2024-04-30T04:56:32.438868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20040521
5-th percentile20080906
Q120130522
median20150318
Q320160528
95-th percentile20170966
Maximum20200916
Range160395
Interquartile range (IQR)30006.5

Descriptive statistics

Standard deviation27557.753
Coefficient of variation (CV)0.0013682159
Kurtosis2.7880624
Mean20141378
Median Absolute Deviation (MAD)10609
Skewness-1.4979105
Sum9.0837614 × 109
Variance7.5942977 × 108
MonotonicityNot monotonic
2024-04-30T04:56:32.558903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20141029 7
 
0.4%
20180221 5
 
0.3%
20170210 4
 
0.3%
20150326 4
 
0.3%
20151229 3
 
0.2%
20140128 3
 
0.2%
20140626 3
 
0.2%
20160920 3
 
0.2%
20160921 3
 
0.2%
20080104 3
 
0.2%
Other values (336) 413
 
26.1%
(Missing) 1130
71.5%
ValueCountFrequency (%)
20040521 1
 
0.1%
20040524 1
 
0.1%
20040603 3
0.2%
20040604 1
 
0.1%
20040607 1
 
0.1%
20040805 1
 
0.1%
20050101 1
 
0.1%
20050811 1
 
0.1%
20061229 1
 
0.1%
20070614 1
 
0.1%
ValueCountFrequency (%)
20200916 1
 
0.1%
20180328 1
 
0.1%
20180309 1
 
0.1%
20180305 1
 
0.1%
20180221 5
0.3%
20180129 1
 
0.1%
20180126 2
 
0.1%
20180108 1
 
0.1%
20180104 2
 
0.1%
20171220 1
 
0.1%

신청일자
Real number (ℝ)

MISSING 

Distinct410
Distinct (%)28.2%
Missing125
Missing (%)7.9%
Infinite0
Infinite (%)0.0%
Mean20084617
Minimum19941210
Maximum20200916
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.0 KiB
2024-04-30T04:56:32.679281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19941210
5-th percentile20040521
Q120040604
median20051227
Q320121030
95-th percentile20161020
Maximum20200916
Range259706
Interquartile range (IQR)80426

Descriptive statistics

Standard deviation50625.343
Coefficient of variation (CV)0.0025206029
Kurtosis-0.99142992
Mean20084617
Median Absolute Deviation (MAD)19193
Skewness0.10846497
Sum2.9243202 × 1010
Variance2.5629253 × 109
MonotonicityNot monotonic
2024-04-30T04:56:32.794897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20050101 124
 
7.8%
20040604 76
 
4.8%
20040603 74
 
4.7%
20040607 65
 
4.1%
20040521 51
 
3.2%
20120806 47
 
3.0%
20040524 46
 
2.9%
20120802 43
 
2.7%
20120809 39
 
2.5%
20120808 37
 
2.3%
Other values (400) 854
54.0%
(Missing) 125
 
7.9%
ValueCountFrequency (%)
19941210 15
0.9%
19981117 1
 
0.1%
19990812 1
 
0.1%
19991103 2
 
0.1%
19991108 1
 
0.1%
19991111 1
 
0.1%
20000112 4
 
0.3%
20000610 1
 
0.1%
20000814 1
 
0.1%
20001219 9
0.6%
ValueCountFrequency (%)
20200916 1
0.1%
20180328 1
0.1%
20180309 1
0.1%
20180305 1
0.1%
20180221 1
0.1%
20180126 1
0.1%
20180104 2
0.1%
20171220 1
0.1%
20171218 1
0.1%
20171130 1
0.1%

항목값1
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size12.5 KiB
관급봉투
1458 
<NA>
 
123

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
관급봉투 1458
92.2%
<NA> 123
 
7.8%

Length

2024-04-30T04:56:32.902858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:56:32.978599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
관급봉투 1458
92.2%
na 123
 
7.8%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)업소구분명소재지지정일자신청일자항목값1
0305000030500001419940000119941210<NA>3폐업2폐업2012072520120725<NA><NA>0222436275<NA>130032서울특별시 동대문구 답십리동 58-16번지서울특별시 동대문구 답십리로52길 13-2 (답십리동)<NA>성일유통2012-07-25 14:39:32I2018-08-31 23:59:59.0<NA>205111.176277452203.040396지정서울특별시 동대문구 답십리동 58-16<NA>20050101관급봉투
1305000030500001419940000219941210<NA>3폐업2폐업2012072520120725<NA><NA>0222174116<NA>130032서울특별시 동대문구 답십리동 53-42번지서울특별시 동대문구 답십리로50길 7 (답십리동)<NA>윤영슈퍼2012-07-25 14:36:51I2018-08-31 23:59:59.0<NA>205082.379688452238.231509지정서울특별시 동대문구 답십리동 36-19<NA>20050101관급봉투
2305000030500001419940000319941210<NA>3폐업2폐업2012072520120725<NA><NA>0222156544<NA>130032서울특별시 동대문구 답십리동 40-53번지서울특별시 동대문구 답십리로56길 71 (답십리동)<NA>한아름슈퍼2012-07-25 13:18:53I2018-08-31 23:59:59.0<NA>205150.949078451941.744427지정서울특별시 동대문구 답십리동 40-53<NA>20050101관급봉투
3305000030500001419940002219941210<NA>3폐업2폐업2015062520150625<NA><NA>0222493384<NA>130092서울특별시 동대문구 휘경동 312-203번지서울특별시 동대문구 서울시립대로29가길 30 (휘경동)<NA>동네슈퍼2015-07-23 10:46:13I2018-08-31 23:59:59.0<NA>204819.789602453674.788169지정서울특별시 동대문구 휘경동 312-203<NA>20040521관급봉투
4305000030500001419940002319941210<NA>3폐업2폐업2012072520120725<NA><NA>0222468879<NA>130092서울특별시 동대문구 휘경동 293-96번지서울특별시 동대문구 망우로18가길 76 (휘경동)<NA>여주쌀상회2012-07-25 09:49:05I2018-08-31 23:59:59.0<NA>205243.737434453856.172583지정서울특별시 동대문구 휘경동 293-96<NA>20040521관급봉투
5305000030500001419940002419941210<NA>1영업/정상3재개업<NA>20120801<NA><NA>0222453351<NA>130092서울특별시 동대문구 휘경동 267-110번지서울특별시 동대문구 망우로16길 20 (휘경동)<NA>서흥하이퍼마켓2012-08-28 14:35:46I2018-08-31 23:59:59.0<NA>205319.294449454114.949325지정서울특별시 동대문구 휘경동 267-110<NA>20040521관급봉투
6305000030500001419940002519941210<NA>3폐업2폐업2012072520120725<NA><NA>0222434977<NA>130092서울특별시 동대문구 휘경동 34-49번지서울특별시 동대문구 망우로 118 (휘경동)<NA>백암문구2012-07-25 09:57:46I2018-08-31 23:59:59.0<NA>205785.838196454305.171471지정서울특별시 동대문구 휘경동 34-49<NA>20040521관급봉투
7305000030500001419940002619941210<NA>1영업/정상3재개업<NA>20120801<NA><NA><NA><NA>130092서울특별시 동대문구 휘경동 43-184번지서울특별시 동대문구 한천로 279 (휘경동)<NA>동성슈퍼2012-08-28 14:36:04I2018-08-31 23:59:59.0<NA>205868.4959453723.126591지정서울특별시 동대문구 휘경동 43-184<NA>20040521관급봉투
8305000030500001419940002719941210<NA>3폐업2폐업2012072520120725<NA><NA>0222174426<NA>130092서울특별시 동대문구 휘경동 43-210번지서울특별시 동대문구 한천로51길 38-2 (휘경동)<NA>배봉슈퍼2012-07-25 10:01:06I2018-08-31 23:59:59.0<NA>205736.672822453662.897688지정서울특별시 동대문구 휘경동 43-210<NA>20040521관급봉투
9305000030500001419940002819941210<NA>1영업/정상3재개업<NA>20120801<NA><NA>0222457336<NA>130092서울특별시 동대문구 휘경동 293-180번지서울특별시 동대문구 망우로14가길 73 (휘경동)<NA>마을슈퍼2012-08-28 14:36:28I2018-08-31 23:59:59.0<NA>205185.425893453742.191642지정서울특별시 동대문구 휘경동 293-180<NA>20040521관급봉투
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)업소구분명소재지지정일자신청일자항목값1
157130500003050000142024000102024-02-23<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 동대문구 장안동 391-1서울특별시 동대문구 한천로26길 58, 1동 101호 (장안동)02624세븐일레븐 장안금빛점2024-02-23 14:31:42I2023-12-01 22:05:00.0<NA>206008.689699452066.002481<NA><NA><NA><NA><NA>
157230500003050000142024000112024-03-07<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 동대문구 장안동 93-43서울특별시 동대문구 사가정로25길 34, 1층 101호 (장안동)02515지에스(GS)25 장안주공2024-03-07 16:42:56I2023-12-03 00:09:00.0<NA>206190.228695453109.711082<NA><NA><NA><NA><NA>
157330500003050000142024000122024-03-07<NA>1영업/정상11영업<NA><NA><NA><NA>070-7760-0702<NA><NA>서울특별시 동대문구 제기동 289-6서울특별시 동대문구 제기로 68, 1-4호 (제기동)02480둘레2024-03-07 16:46:07I2023-12-03 00:09:00.0<NA>203511.265992453797.186822<NA><NA><NA><NA><NA>
157430500003050000142024000132024-03-25<NA>1영업/정상11영업<NA><NA><NA><NA>959-8545<NA><NA>서울특별시 동대문구 회기동 33-1서울특별시 동대문구 경희대로 20 (회기동)02453홈플러스 익스프레스 회기점2024-03-25 15:17:05I2023-12-02 22:07:00.0<NA>204599.373004454552.779663<NA><NA><NA><NA><NA>
157530500003050000142024000142024-03-28<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 동대문구 이문동 264-445서울특별시 동대문구 천장산로 47, 1층 나12,13호 (이문동)02448씨유(CU) 이문삼성2024-03-28 21:06:55I2023-12-02 21:00:00.0<NA>204991.594355455332.294542<NA><NA><NA><NA><NA>
157630500003050000142024000152024-04-02<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 동대문구 장안동 309-4서울특별시 동대문구 장한로28가길 1 (장안동)02523지에스25 장안장평점2024-04-02 10:31:45I2023-12-04 00:04:00.0<NA>206329.469799452312.085255<NA><NA><NA><NA><NA>
157730500003050000142024000162024-04-04<NA>1영업/정상11영업<NA><NA><NA><NA>1577-0711<NA><NA>서울특별시 동대문구 장안동 535서울특별시 동대문구 한천로 146, 1층 우측전부호 (장안동)02529(주)코리아세븐 장안센트럴점2024-04-04 14:37:12I2023-12-04 00:06:00.0<NA>205867.033392452405.471472<NA><NA><NA><NA><NA>
157830500003050000142024000172024-04-17<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 동대문구 답십리동 955-21서울특별시 동대문구 황물로15길 34-10, 1층 (답십리동)02619씨유 답십리대림점2024-04-17 13:57:38I2023-12-03 22:02:00.0<NA>205138.337479451501.62969<NA><NA><NA><NA><NA>
157930500003050000142024000182024-04-18<NA>1영업/정상11영업<NA><NA><NA><NA>02-3295-4785<NA><NA>서울특별시 동대문구 제기동 1019 경동시장서울특별시 동대문구 고산자로36길 3, 경동시장 2층 일부층 (제기동)02571노브랜드 서울경동시장점2024-04-18 11:03:44I2023-12-03 22:02:00.0<NA>203403.019535452985.72542<NA><NA><NA><NA><NA>
158030500003050000142024000192024-04-23<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 동대문구 장안동 424-7서울특별시 동대문구 장한로5길 16, 1층 (장안동)02629씨유(CU) 장안지우점2024-04-23 11:03:44I2023-12-03 22:05:00.0<NA>205722.737527451359.751072<NA><NA><NA><NA><NA>