Overview

Dataset statistics

Number of variables30
Number of observations4122
Missing cells39831
Missing cells (%)32.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1014.5 KiB
Average record size in memory252.0 B

Variable types

Numeric6
DateTime5
Unsupported5
Categorical7
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
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-16126/S/1/datasetView.do

Alerts

영업상태코드 is highly imbalanced (63.7%)Imbalance
영업상태명 is highly imbalanced (63.7%)Imbalance
상세영업상태코드 is highly imbalanced (70.1%)Imbalance
상세영업상태명 is highly imbalanced (68.5%)Imbalance
인허가취소일자 has 4122 (100.0%) missing valuesMissing
폐업일자 has 3077 (74.6%) missing valuesMissing
휴업시작일자 has 3270 (79.3%) missing valuesMissing
휴업종료일자 has 4122 (100.0%) missing valuesMissing
재개업일자 has 4122 (100.0%) missing valuesMissing
전화번호 has 1228 (29.8%) missing valuesMissing
소재지면적 has 4122 (100.0%) missing valuesMissing
소재지우편번호 has 1379 (33.5%) missing valuesMissing
지번주소 has 265 (6.4%) missing valuesMissing
도로명주소 has 1014 (24.6%) missing valuesMissing
도로명우편번호 has 2073 (50.3%) missing valuesMissing
업태구분명 has 4122 (100.0%) missing valuesMissing
좌표정보(X) has 875 (21.2%) missing valuesMissing
좌표정보(Y) has 875 (21.2%) missing valuesMissing
소재지 has 1318 (32.0%) missing valuesMissing
지정일자 has 2824 (68.5%) missing valuesMissing
신청일자 has 1023 (24.8%) missing valuesMissing
지정일자 is highly skewed (γ1 = 20.77224675)Skewed
신청일자 is highly skewed (γ1 = -39.13764923)Skewed
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 started2024-05-11 05:22:23.788481
Analysis finished2024-05-11 05:22:26.273865
Duration2.49 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Real number (ℝ)

Distinct13
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3074536.6
Minimum3000000
Maximum3220000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.4 KiB
2024-05-11T14:22:26.331879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3000000
Q13050000
median3050000
Q33130000
95-th percentile3210000
Maximum3220000
Range220000
Interquartile range (IQR)80000

Descriptive statistics

Standard deviation58131.057
Coefficient of variation (CV)0.018907258
Kurtosis0.049110552
Mean3074536.6
Median Absolute Deviation (MAD)20000
Skewness0.81610571
Sum1.267324 × 1010
Variance3.3792198 × 109
MonotonicityNot monotonic
2024-05-11T14:22:26.448917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
3050000 1582
38.4%
3130000 805
19.5%
3000000 711
17.2%
3070000 411
 
10.0%
3210000 288
 
7.0%
3100000 87
 
2.1%
3040000 86
 
2.1%
3110000 69
 
1.7%
3170000 45
 
1.1%
3220000 27
 
0.7%
Other values (3) 11
 
0.3%
ValueCountFrequency (%)
3000000 711
17.2%
3020000 1
 
< 0.1%
3040000 86
 
2.1%
3050000 1582
38.4%
3060000 7
 
0.2%
3070000 411
 
10.0%
3100000 87
 
2.1%
3110000 69
 
1.7%
3130000 805
19.5%
3160000 3
 
0.1%
ValueCountFrequency (%)
3220000 27
 
0.7%
3210000 288
 
7.0%
3170000 45
 
1.1%
3160000 3
 
0.1%
3130000 805
19.5%
3110000 69
 
1.7%
3100000 87
 
2.1%
3070000 411
 
10.0%
3060000 7
 
0.2%
3050000 1582
38.4%

관리번호
Real number (ℝ)

UNIQUE 

Distinct4122
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0745372 × 1017
Minimum3.0000001 × 1017
Maximum3.2200001 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.4 KiB
2024-05-11T14:22:26.583020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.0000001 × 1017
5-th percentile3.0000001 × 1017
Q13.0500001 × 1017
median3.0500001 × 1017
Q33.1300001 × 1017
95-th percentile3.2100001 × 1017
Maximum3.2200001 × 1017
Range2.2 × 1016
Interquartile range (IQR)8 × 1015

Descriptive statistics

Standard deviation5.8131028 × 1015
Coefficient of variation (CV)0.018907245
Kurtosis0.049095398
Mean3.0745372 × 1017
Median Absolute Deviation (MAD)2 × 1015
Skewness0.81608752
Sum-5.5011265 × 1018
Variance3.3792164 × 1031
MonotonicityNot monotonic
2024-05-11T14:22:26.736776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
313000014202200034 1
 
< 0.1%
307000014200000210 1
 
< 0.1%
307000014200000076 1
 
< 0.1%
307000014200000077 1
 
< 0.1%
307000014200000078 1
 
< 0.1%
307000014200000079 1
 
< 0.1%
307000014200000080 1
 
< 0.1%
307000014200000081 1
 
< 0.1%
307000014200000082 1
 
< 0.1%
307000014200000083 1
 
< 0.1%
Other values (4112) 4112
99.8%
ValueCountFrequency (%)
300000014201300001 1
< 0.1%
300000014201300003 1
< 0.1%
300000014201300004 1
< 0.1%
300000014201300005 1
< 0.1%
300000014201300006 1
< 0.1%
300000014201300007 1
< 0.1%
300000014201300008 1
< 0.1%
300000014201300009 1
< 0.1%
300000014201300010 1
< 0.1%
300000014201300011 1
< 0.1%
ValueCountFrequency (%)
322000014200100091 1
< 0.1%
322000014200100090 1
< 0.1%
322000014200100089 1
< 0.1%
322000014200100088 1
< 0.1%
322000014200100087 1
< 0.1%
322000014200100086 1
< 0.1%
322000014200100085 1
< 0.1%
322000014200100084 1
< 0.1%
322000014200100083 1
< 0.1%
322000014200100082 1
< 0.1%
Distinct1200
Distinct (%)29.1%
Missing0
Missing (%)0.0%
Memory size32.3 KiB
Minimum1994-03-02 00:00:00
Maximum2024-05-03 00:00:00
2024-05-11T14:22:26.879542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:22:27.015086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4122
Missing (%)100.0%
Memory size36.4 KiB

영업상태코드
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size32.3 KiB
1
3071 
3
1041 
4
 
4
5
 
4
2
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 3071
74.5%
3 1041
 
25.3%
4 4
 
0.1%
5 4
 
0.1%
2 2
 
< 0.1%

Length

2024-05-11T14:22:27.156956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:22:27.306402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 3071
74.5%
3 1041
 
25.3%
4 4
 
0.1%
5 4
 
0.1%
2 2
 
< 0.1%

영업상태명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size32.3 KiB
영업/정상
3071 
폐업
1041 
취소/말소/만료/정지/중지
 
4
제외/삭제/전출
 
4
휴업
 
2

Length

Max length14
Median length5
Mean length4.2525473
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 3071
74.5%
폐업 1041
 
25.3%
취소/말소/만료/정지/중지 4
 
0.1%
제외/삭제/전출 4
 
0.1%
휴업 2
 
< 0.1%

Length

2024-05-11T14:22:27.465442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:22:27.593552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 3071
74.5%
폐업 1041
 
25.3%
취소/말소/만료/정지/중지 4
 
0.1%
제외/삭제/전출 4
 
0.1%
휴업 2
 
< 0.1%

상세영업상태코드
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size32.3 KiB
11
3048 
2
1041 
3
 
13
0
 
5
BBBB
 
5
Other values (3)
 
10

Length

Max length4
Median length2
Mean length1.7430859
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row11
3rd row2
4th row11
5th row11

Common Values

ValueCountFrequency (%)
11 3048
73.9%
2 1041
 
25.3%
3 13
 
0.3%
0 5
 
0.1%
BBBB 5
 
0.1%
4 4
 
0.1%
5 4
 
0.1%
1 2
 
< 0.1%

Length

2024-05-11T14:22:27.740024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:22:27.858807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11 3048
73.9%
2 1041
 
25.3%
3 13
 
0.3%
0 5
 
0.1%
bbbb 5
 
0.1%
4 4
 
0.1%
5 4
 
0.1%
1 2
 
< 0.1%

상세영업상태명
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size32.3 KiB
영업
3053 
폐업
1041 
재개업
 
13
<NA>
 
5
폐쇄
 
4
Other values (2)
 
6

Length

Max length4
Median length2
Mean length2.0075206
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 3053
74.1%
폐업 1041
 
25.3%
재개업 13
 
0.3%
<NA> 5
 
0.1%
폐쇄 4
 
0.1%
제외사항 4
 
0.1%
휴업 2
 
< 0.1%

Length

2024-05-11T14:22:27.998382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:22:28.171632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 3053
74.1%
폐업 1041
 
25.3%
재개업 13
 
0.3%
na 5
 
0.1%
폐쇄 4
 
0.1%
제외사항 4
 
0.1%
휴업 2
 
< 0.1%

폐업일자
Date

MISSING 

Distinct238
Distinct (%)22.8%
Missing3077
Missing (%)74.6%
Memory size32.3 KiB
Minimum1997-10-05 00:00:00
Maximum2024-04-11 00:00:00
2024-05-11T14:22:28.333748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:22:28.466158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Date

MISSING 

Distinct155
Distinct (%)18.2%
Missing3270
Missing (%)79.3%
Memory size32.3 KiB
Minimum2012-07-25 00:00:00
Maximum2021-10-14 00:00:00
2024-05-11T14:22:28.589011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:22:28.706898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4122
Missing (%)100.0%
Memory size36.4 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4122
Missing (%)100.0%
Memory size36.4 KiB

전화번호
Text

MISSING 

Distinct2776
Distinct (%)95.9%
Missing1228
Missing (%)29.8%
Memory size32.3 KiB
2024-05-11T14:22:29.010694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length10.590187
Min length2

Characters and Unicode

Total characters30648
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

Unique2674 ?
Unique (%)92.4%

Sample

1st row02-6949-5919
2nd row02-725-9120
3rd row02-2103-9500
4th row070-7760-0702
5th row02-395-7437
ValueCountFrequency (%)
02 942
 
21.5%
0002 50
 
1.1%
912 40
 
0.9%
914 32
 
0.7%
915 30
 
0.7%
917 26
 
0.6%
918 24
 
0.5%
913 20
 
0.5%
916 15
 
0.3%
919 15
 
0.3%
Other values (2849) 3190
72.8%
2024-05-11T14:22:29.556107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 5766
18.8%
0 4288
14.0%
3 2447
8.0%
9 2356
7.7%
7 2261
 
7.4%
- 2242
 
7.3%
4 2057
 
6.7%
1 2056
 
6.7%
6 1934
 
6.3%
1915
 
6.2%
Other values (2) 3326
10.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 26491
86.4%
Dash Punctuation 2242
 
7.3%
Space Separator 1915
 
6.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 5766
21.8%
0 4288
16.2%
3 2447
9.2%
9 2356
8.9%
7 2261
 
8.5%
4 2057
 
7.8%
1 2056
 
7.8%
6 1934
 
7.3%
5 1873
 
7.1%
8 1453
 
5.5%
Dash Punctuation
ValueCountFrequency (%)
- 2242
100.0%
Space Separator
ValueCountFrequency (%)
1915
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 30648
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 5766
18.8%
0 4288
14.0%
3 2447
8.0%
9 2356
7.7%
7 2261
 
7.4%
- 2242
 
7.3%
4 2057
 
6.7%
1 2056
 
6.7%
6 1934
 
6.3%
1915
 
6.2%
Other values (2) 3326
10.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30648
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 5766
18.8%
0 4288
14.0%
3 2447
8.0%
9 2356
7.7%
7 2261
 
7.4%
- 2242
 
7.3%
4 2057
 
6.7%
1 2056
 
6.7%
6 1934
 
6.3%
1915
 
6.2%
Other values (2) 3326
10.9%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4122
Missing (%)100.0%
Memory size36.4 KiB

소재지우편번호
Text

MISSING 

Distinct394
Distinct (%)14.4%
Missing1379
Missing (%)33.5%
Memory size32.3 KiB
2024-05-11T14:22:29.964610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0116661
Min length6

Characters and Unicode

Total characters16490
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

Unique132 ?
Unique (%)4.8%

Sample

1st row110-122
2nd row110-011
3rd row121-811
4th row110-320
5th row121-849
ValueCountFrequency (%)
130101 85
 
3.1%
130081 52
 
1.9%
130021 51
 
1.9%
130070 47
 
1.7%
130102 44
 
1.6%
130050 44
 
1.6%
130092 42
 
1.5%
137132 41
 
1.5%
137071 39
 
1.4%
130031 38
 
1.4%
Other values (384) 2260
82.4%
2024-05-11T14:22:30.526459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 4926
29.9%
0 3744
22.7%
3 2913
17.7%
2 1361
 
8.3%
4 769
 
4.7%
6 718
 
4.4%
8 692
 
4.2%
7 645
 
3.9%
5 419
 
2.5%
9 271
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16458
99.8%
Dash Punctuation 32
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4926
29.9%
0 3744
22.7%
3 2913
17.7%
2 1361
 
8.3%
4 769
 
4.7%
6 718
 
4.4%
8 692
 
4.2%
7 645
 
3.9%
5 419
 
2.5%
9 271
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 16490
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 4926
29.9%
0 3744
22.7%
3 2913
17.7%
2 1361
 
8.3%
4 769
 
4.7%
6 718
 
4.4%
8 692
 
4.2%
7 645
 
3.9%
5 419
 
2.5%
9 271
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16490
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 4926
29.9%
0 3744
22.7%
3 2913
17.7%
2 1361
 
8.3%
4 769
 
4.7%
6 718
 
4.4%
8 692
 
4.2%
7 645
 
3.9%
5 419
 
2.5%
9 271
 
1.6%

지번주소
Text

MISSING 

Distinct3469
Distinct (%)89.9%
Missing265
Missing (%)6.4%
Memory size32.3 KiB
2024-05-11T14:22:30.980416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length45
Mean length23.535131
Min length14

Characters and Unicode

Total characters90775
Distinct characters395
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3129 ?
Unique (%)81.1%

Sample

1st row서울특별시 마포구 창전동 6-172
2nd row서울특별시 종로구 수송동 135
3rd row서울특별시 종로구 종로2가 40 101호
4th row서울특별시 동대문구 제기동 289-6
5th row서울특별시 동대문구 장안동 93-43
ValueCountFrequency (%)
서울특별시 3856
23.2%
동대문구 1573
 
9.4%
종로구 638
 
3.8%
마포구 617
 
3.7%
성북구 411
 
2.5%
답십리동 376
 
2.3%
장안동 372
 
2.2%
번지 300
 
1.8%
서초구 288
 
1.7%
이문동 175
 
1.1%
Other values (3960) 8045
48.3%
2024-05-11T14:22:31.614809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16723
18.4%
5466
 
6.0%
4378
 
4.8%
3905
 
4.3%
3875
 
4.3%
3860
 
4.3%
3856
 
4.2%
3856
 
4.2%
1 3423
 
3.8%
- 3177
 
3.5%
Other values (385) 38256
42.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 53899
59.4%
Decimal Number 16751
 
18.5%
Space Separator 16723
 
18.4%
Dash Punctuation 3177
 
3.5%
Uppercase Letter 132
 
0.1%
Other Punctuation 40
 
< 0.1%
Lowercase Letter 28
 
< 0.1%
Open Punctuation 10
 
< 0.1%
Close Punctuation 10
 
< 0.1%
Math Symbol 3
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5466
 
10.1%
4378
 
8.1%
3905
 
7.2%
3875
 
7.2%
3860
 
7.2%
3856
 
7.2%
3856
 
7.2%
3038
 
5.6%
2914
 
5.4%
1796
 
3.3%
Other values (330) 16955
31.5%
Uppercase Letter
ValueCountFrequency (%)
S 16
12.1%
K 14
10.6%
A 13
9.8%
D 11
 
8.3%
M 10
 
7.6%
C 10
 
7.6%
B 9
 
6.8%
T 8
 
6.1%
G 6
 
4.5%
L 6
 
4.5%
Other values (11) 29
22.0%
Lowercase Letter
ValueCountFrequency (%)
o 4
14.3%
i 3
10.7%
e 3
10.7%
r 3
10.7%
c 3
10.7%
y 2
7.1%
t 2
7.1%
w 2
7.1%
n 2
7.1%
d 1
 
3.6%
Other values (3) 3
10.7%
Decimal Number
ValueCountFrequency (%)
1 3423
20.4%
2 2249
13.4%
3 2099
12.5%
4 1674
10.0%
5 1483
8.9%
6 1263
 
7.5%
0 1216
 
7.3%
8 1143
 
6.8%
7 1113
 
6.6%
9 1088
 
6.5%
Other Punctuation
ValueCountFrequency (%)
, 27
67.5%
. 7
 
17.5%
@ 5
 
12.5%
/ 1
 
2.5%
Space Separator
ValueCountFrequency (%)
16723
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3177
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 53899
59.4%
Common 36715
40.4%
Latin 161
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5466
 
10.1%
4378
 
8.1%
3905
 
7.2%
3875
 
7.2%
3860
 
7.2%
3856
 
7.2%
3856
 
7.2%
3038
 
5.6%
2914
 
5.4%
1796
 
3.3%
Other values (330) 16955
31.5%
Latin
ValueCountFrequency (%)
S 16
 
9.9%
K 14
 
8.7%
A 13
 
8.1%
D 11
 
6.8%
M 10
 
6.2%
C 10
 
6.2%
B 9
 
5.6%
T 8
 
5.0%
G 6
 
3.7%
L 6
 
3.7%
Other values (25) 58
36.0%
Common
ValueCountFrequency (%)
16723
45.5%
1 3423
 
9.3%
- 3177
 
8.7%
2 2249
 
6.1%
3 2099
 
5.7%
4 1674
 
4.6%
5 1483
 
4.0%
6 1263
 
3.4%
0 1216
 
3.3%
8 1143
 
3.1%
Other values (10) 2265
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 53899
59.4%
ASCII 36874
40.6%
Number Forms 1
 
< 0.1%
Enclosed Alphanum 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16723
45.4%
1 3423
 
9.3%
- 3177
 
8.6%
2 2249
 
6.1%
3 2099
 
5.7%
4 1674
 
4.5%
5 1483
 
4.0%
6 1263
 
3.4%
0 1216
 
3.3%
8 1143
 
3.1%
Other values (43) 2424
 
6.6%
Hangul
ValueCountFrequency (%)
5466
 
10.1%
4378
 
8.1%
3905
 
7.2%
3875
 
7.2%
3860
 
7.2%
3856
 
7.2%
3856
 
7.2%
3038
 
5.6%
2914
 
5.4%
1796
 
3.3%
Other values (330) 16955
31.5%
Number Forms
ValueCountFrequency (%)
1
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
1
100.0%

도로명주소
Text

MISSING 

Distinct2859
Distinct (%)92.0%
Missing1014
Missing (%)24.6%
Memory size32.3 KiB
2024-05-11T14:22:32.030864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length55
Mean length28.754183
Min length20

Characters and Unicode

Total characters89368
Distinct characters436
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2628 ?
Unique (%)84.6%

Sample

1st row서울특별시 마포구 와우산로 114 (창전동)
2nd row서울특별시 종로구 종로1길 42-1, 1층 (수송동)
3rd row서울특별시 종로구 수표로 105, 101호 (종로2가)
4th row서울특별시 동대문구 제기로 68, 1-4호 (제기동)
5th row서울특별시 동대문구 사가정로25길 34, 1층 101호 (장안동)
ValueCountFrequency (%)
서울특별시 3108
 
17.8%
동대문구 1373
 
7.8%
마포구 793
 
4.5%
종로구 701
 
4.0%
1층 582
 
3.3%
장안동 330
 
1.9%
서초구 223
 
1.3%
답십리동 159
 
0.9%
이문동 149
 
0.9%
전농동 149
 
0.9%
Other values (2474) 9935
56.8%
2024-05-11T14:22:32.640717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15196
 
17.0%
4702
 
5.3%
3679
 
4.1%
3654
 
4.1%
1 3436
 
3.8%
3224
 
3.6%
3167
 
3.5%
3128
 
3.5%
( 3119
 
3.5%
) 3119
 
3.5%
Other values (426) 42944
48.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 53728
60.1%
Space Separator 15196
 
17.0%
Decimal Number 12145
 
13.6%
Open Punctuation 3119
 
3.5%
Close Punctuation 3119
 
3.5%
Other Punctuation 1416
 
1.6%
Dash Punctuation 410
 
0.5%
Uppercase Letter 193
 
0.2%
Lowercase Letter 34
 
< 0.1%
Math Symbol 5
 
< 0.1%
Other values (2) 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4702
 
8.8%
3679
 
6.8%
3654
 
6.8%
3224
 
6.0%
3167
 
5.9%
3128
 
5.8%
3108
 
5.8%
3108
 
5.8%
1889
 
3.5%
1778
 
3.3%
Other values (371) 22291
41.5%
Uppercase Letter
ValueCountFrequency (%)
B 33
17.1%
C 17
 
8.8%
M 17
 
8.8%
S 16
 
8.3%
A 16
 
8.3%
K 15
 
7.8%
D 15
 
7.8%
T 8
 
4.1%
L 7
 
3.6%
E 6
 
3.1%
Other values (12) 43
22.3%
Lowercase Letter
ValueCountFrequency (%)
b 5
14.7%
e 5
14.7%
o 4
11.8%
i 3
8.8%
c 3
8.8%
r 3
8.8%
y 2
 
5.9%
t 2
 
5.9%
w 2
 
5.9%
n 2
 
5.9%
Other values (2) 3
8.8%
Decimal Number
ValueCountFrequency (%)
1 3436
28.3%
2 1717
14.1%
3 1291
 
10.6%
4 1029
 
8.5%
0 949
 
7.8%
5 887
 
7.3%
6 812
 
6.7%
7 725
 
6.0%
8 698
 
5.7%
9 601
 
4.9%
Other Punctuation
ValueCountFrequency (%)
, 1401
98.9%
. 8
 
0.6%
@ 6
 
0.4%
/ 1
 
0.1%
Space Separator
ValueCountFrequency (%)
15196
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3119
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3119
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 410
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%
Letter Number
ValueCountFrequency (%)
2
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 53728
60.1%
Common 35411
39.6%
Latin 229
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4702
 
8.8%
3679
 
6.8%
3654
 
6.8%
3224
 
6.0%
3167
 
5.9%
3128
 
5.8%
3108
 
5.8%
3108
 
5.8%
1889
 
3.5%
1778
 
3.3%
Other values (371) 22291
41.5%
Latin
ValueCountFrequency (%)
B 33
14.4%
C 17
 
7.4%
M 17
 
7.4%
S 16
 
7.0%
A 16
 
7.0%
K 15
 
6.6%
D 15
 
6.6%
T 8
 
3.5%
L 7
 
3.1%
E 6
 
2.6%
Other values (25) 79
34.5%
Common
ValueCountFrequency (%)
15196
42.9%
1 3436
 
9.7%
( 3119
 
8.8%
) 3119
 
8.8%
2 1717
 
4.8%
, 1401
 
4.0%
3 1291
 
3.6%
4 1029
 
2.9%
0 949
 
2.7%
5 887
 
2.5%
Other values (10) 3267
 
9.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 53728
60.1%
ASCII 35637
39.9%
Number Forms 2
 
< 0.1%
Enclosed Alphanum 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15196
42.6%
1 3436
 
9.6%
( 3119
 
8.8%
) 3119
 
8.8%
2 1717
 
4.8%
, 1401
 
3.9%
3 1291
 
3.6%
4 1029
 
2.9%
0 949
 
2.7%
5 887
 
2.5%
Other values (43) 3493
 
9.8%
Hangul
ValueCountFrequency (%)
4702
 
8.8%
3679
 
6.8%
3654
 
6.8%
3224
 
6.0%
3167
 
5.9%
3128
 
5.8%
3108
 
5.8%
3108
 
5.8%
1889
 
3.5%
1778
 
3.3%
Other values (371) 22291
41.5%
Number Forms
ValueCountFrequency (%)
2
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
1
100.0%

도로명우편번호
Text

MISSING 

Distinct791
Distinct (%)38.6%
Missing2073
Missing (%)50.3%
Memory size32.3 KiB
2024-05-11T14:22:33.072779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.36408
Min length5

Characters and Unicode

Total characters10991
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

Unique279 ?
Unique (%)13.6%

Sample

1st row04059
2nd row03152
3rd row110-122
4th row02480
5th row02515
ValueCountFrequency (%)
130101 25
 
1.2%
130031 15
 
0.7%
130840 13
 
0.6%
03938 11
 
0.5%
110111 11
 
0.5%
130081 10
 
0.5%
130070 10
 
0.5%
110862 10
 
0.5%
04002 10
 
0.5%
03964 9
 
0.4%
Other values (781) 1925
93.9%
2024-05-11T14:22:33.645273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3087
28.1%
1 2127
19.4%
3 1252
11.4%
4 1045
 
9.5%
2 850
 
7.7%
8 668
 
6.1%
9 576
 
5.2%
5 544
 
4.9%
6 437
 
4.0%
7 380
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10966
99.8%
Dash Punctuation 25
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3087
28.2%
1 2127
19.4%
3 1252
11.4%
4 1045
 
9.5%
2 850
 
7.8%
8 668
 
6.1%
9 576
 
5.3%
5 544
 
5.0%
6 437
 
4.0%
7 380
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10991
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3087
28.1%
1 2127
19.4%
3 1252
11.4%
4 1045
 
9.5%
2 850
 
7.7%
8 668
 
6.1%
9 576
 
5.2%
5 544
 
4.9%
6 437
 
4.0%
7 380
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10991
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3087
28.1%
1 2127
19.4%
3 1252
11.4%
4 1045
 
9.5%
2 850
 
7.7%
8 668
 
6.1%
9 576
 
5.2%
5 544
 
4.9%
6 437
 
4.0%
7 380
 
3.5%
Distinct3409
Distinct (%)82.7%
Missing0
Missing (%)0.0%
Memory size32.3 KiB
2024-05-11T14:22:34.022907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length27
Mean length7.0247453
Min length1

Characters and Unicode

Total characters28956
Distinct characters594
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

Unique3040 ?
Unique (%)73.8%

Sample

1st row블루25 행복한 와우점
2nd row세븐일레븐 세종로점
3rd row롯데씨브이에스711(주) 종로육의전점
4th row둘레
5th row지에스(GS)25 장안주공
ValueCountFrequency (%)
씨유 289
 
5.3%
세븐일레븐 228
 
4.2%
gs25 220
 
4.0%
이마트24 64
 
1.2%
지에스25 60
 
1.1%
주)코리아세븐 49
 
0.9%
cu 46
 
0.8%
미니스톱 27
 
0.5%
지에스(gs)25 24
 
0.4%
현대슈퍼 23
 
0.4%
Other values (3351) 4462
81.2%
2024-05-11T14:22:34.553504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1434
 
5.0%
1375
 
4.7%
1002
 
3.5%
964
 
3.3%
848
 
2.9%
787
 
2.7%
636
 
2.2%
2 601
 
2.1%
5 495
 
1.7%
469
 
1.6%
Other values (584) 20345
70.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 24324
84.0%
Space Separator 1375
 
4.7%
Decimal Number 1343
 
4.6%
Uppercase Letter 1107
 
3.8%
Close Punctuation 332
 
1.1%
Open Punctuation 331
 
1.1%
Lowercase Letter 98
 
0.3%
Other Punctuation 21
 
0.1%
Dash Punctuation 15
 
0.1%
Other Symbol 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1434
 
5.9%
1002
 
4.1%
964
 
4.0%
848
 
3.5%
787
 
3.2%
636
 
2.6%
469
 
1.9%
457
 
1.9%
456
 
1.9%
451
 
1.9%
Other values (524) 16820
69.1%
Uppercase Letter
ValueCountFrequency (%)
S 370
33.4%
G 369
33.3%
C 108
 
9.8%
U 92
 
8.3%
L 29
 
2.6%
M 22
 
2.0%
K 17
 
1.5%
A 14
 
1.3%
T 10
 
0.9%
R 9
 
0.8%
Other values (13) 67
 
6.1%
Lowercase Letter
ValueCountFrequency (%)
s 26
26.5%
g 21
21.4%
c 8
 
8.2%
e 8
 
8.2%
u 7
 
7.1%
k 7
 
7.1%
r 4
 
4.1%
a 3
 
3.1%
t 3
 
3.1%
n 3
 
3.1%
Other values (5) 8
 
8.2%
Decimal Number
ValueCountFrequency (%)
2 601
44.8%
5 495
36.9%
4 95
 
7.1%
1 53
 
3.9%
3 39
 
2.9%
6 22
 
1.6%
7 16
 
1.2%
9 12
 
0.9%
0 5
 
0.4%
8 5
 
0.4%
Other Punctuation
ValueCountFrequency (%)
. 7
33.3%
& 5
23.8%
/ 4
19.0%
? 3
14.3%
@ 1
 
4.8%
! 1
 
4.8%
Space Separator
ValueCountFrequency (%)
1375
100.0%
Close Punctuation
ValueCountFrequency (%)
) 332
100.0%
Open Punctuation
ValueCountFrequency (%)
( 331
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%
Other Symbol
ValueCountFrequency (%)
8
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 24332
84.0%
Common 3419
 
11.8%
Latin 1205
 
4.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1434
 
5.9%
1002
 
4.1%
964
 
4.0%
848
 
3.5%
787
 
3.2%
636
 
2.6%
469
 
1.9%
457
 
1.9%
456
 
1.9%
451
 
1.9%
Other values (525) 16828
69.2%
Latin
ValueCountFrequency (%)
S 370
30.7%
G 369
30.6%
C 108
 
9.0%
U 92
 
7.6%
L 29
 
2.4%
s 26
 
2.2%
M 22
 
1.8%
g 21
 
1.7%
K 17
 
1.4%
A 14
 
1.2%
Other values (28) 137
 
11.4%
Common
ValueCountFrequency (%)
1375
40.2%
2 601
17.6%
5 495
 
14.5%
) 332
 
9.7%
( 331
 
9.7%
4 95
 
2.8%
1 53
 
1.6%
3 39
 
1.1%
6 22
 
0.6%
7 16
 
0.5%
Other values (11) 60
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 24324
84.0%
ASCII 4624
 
16.0%
None 8
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1434
 
5.9%
1002
 
4.1%
964
 
4.0%
848
 
3.5%
787
 
3.2%
636
 
2.6%
469
 
1.9%
457
 
1.9%
456
 
1.9%
451
 
1.9%
Other values (524) 16820
69.1%
ASCII
ValueCountFrequency (%)
1375
29.7%
2 601
13.0%
5 495
 
10.7%
S 370
 
8.0%
G 369
 
8.0%
) 332
 
7.2%
( 331
 
7.2%
C 108
 
2.3%
4 95
 
2.1%
U 92
 
2.0%
Other values (49) 456
 
9.9%
None
ValueCountFrequency (%)
8
100.0%
Distinct3221
Distinct (%)78.1%
Missing0
Missing (%)0.0%
Memory size32.3 KiB
Minimum2007-06-30 09:57:25
Maximum2024-05-07 16:07:17
2024-05-11T14:22:34.976540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:22:35.128103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.3 KiB
I
3462 
U
660 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 3462
84.0%
U 660
 
16.0%

Length

2024-05-11T14:22:35.283574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:22:35.419922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 3462
84.0%
u 660
 
16.0%
Distinct465
Distinct (%)11.3%
Missing0
Missing (%)0.0%
Memory size32.3 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T14:22:35.721876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:22:36.288925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4122
Missing (%)100.0%
Memory size36.4 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct2641
Distinct (%)81.3%
Missing875
Missing (%)21.2%
Infinite0
Infinite (%)0.0%
Mean200465.57
Minimum185001.24
Maximum212211.01
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.4 KiB
2024-05-11T14:22:36.566450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum185001.24
5-th percentile191782.73
Q1196510.02
median201703.8
Q3204839.61
95-th percentile206119.74
Maximum212211.01
Range27209.771
Interquartile range (IQR)8329.5863

Descriptive statistics

Standard deviation4846.2147
Coefficient of variation (CV)0.024174798
Kurtosis-0.94025688
Mean200465.57
Median Absolute Deviation (MAD)3500.2385
Skewness-0.55862484
Sum6.5091171 × 108
Variance23485797
MonotonicityNot monotonic
2024-05-11T14:22:36.878424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
205208.167449959 8
 
0.2%
205381.986112403 7
 
0.2%
192311.642580307 7
 
0.2%
206120.983279154 5
 
0.1%
206455.357834541 5
 
0.1%
204718.0 5
 
0.1%
204507.409771246 4
 
0.1%
205243.737434464 4
 
0.1%
204698.776644614 4
 
0.1%
203009.188734992 4
 
0.1%
Other values (2631) 3194
77.5%
(Missing) 875
 
21.2%
ValueCountFrequency (%)
185001.241571665 1
< 0.1%
187348.717361766 1
< 0.1%
189212.737535822 1
< 0.1%
189315.310470024 1
< 0.1%
189337.0 1
< 0.1%
189378.0 1
< 0.1%
189392.975995366 1
< 0.1%
189461.587933606 1
< 0.1%
189520.410979113 1
< 0.1%
189520.465145926 1
< 0.1%
ValueCountFrequency (%)
212211.012072968 1
< 0.1%
209423.649311203 1
< 0.1%
209371.036034514 1
< 0.1%
208912.924448629 1
< 0.1%
208877.010707599 1
< 0.1%
208155.958194355 1
< 0.1%
207670.24509546 1
< 0.1%
207613.550996972 1
< 0.1%
207130.877304261 1
< 0.1%
207074.98665308 1
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct2641
Distinct (%)81.3%
Missing875
Missing (%)21.2%
Infinite0
Infinite (%)0.0%
Mean451544.29
Minimum439123.41
Maximum458148.39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.4 KiB
2024-05-11T14:22:37.134585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum439123.41
5-th percentile442940.18
Q1450545.12
median452267.74
Q3453216.41
95-th percentile455100.88
Maximum458148.39
Range19024.976
Interquartile range (IQR)2671.2903

Descriptive statistics

Standard deviation3094.1792
Coefficient of variation (CV)0.006852438
Kurtosis3.5402771
Mean451544.29
Median Absolute Deviation (MAD)1157.4962
Skewness-1.8144083
Sum1.4661643 × 109
Variance9573945.1
MonotonicityNot monotonic
2024-05-11T14:22:37.386755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
452466.868525878 8
 
0.2%
451896.756025119 7
 
0.2%
449855.643910445 7
 
0.2%
452775.947650727 5
 
0.1%
452077.137056886 5
 
0.1%
452269.0 5
 
0.1%
454145.156618096 4
 
0.1%
453856.172583423 4
 
0.1%
453786.184389292 4
 
0.1%
453776.829188234 4
 
0.1%
Other values (2631) 3194
77.5%
(Missing) 875
 
21.2%
ValueCountFrequency (%)
439123.409737111 1
< 0.1%
439524.792743725 1
< 0.1%
439583.348149956 1
< 0.1%
440125.988508969 1
< 0.1%
440182.898235134 1
< 0.1%
440208.558412381 1
< 0.1%
440281.405998565 1
< 0.1%
440425.82329747 1
< 0.1%
440471.199973164 1
< 0.1%
440627.71005447 2
< 0.1%
ValueCountFrequency (%)
458148.38566155 1
< 0.1%
457963.196810318 1
< 0.1%
457715.946602513 1
< 0.1%
457700.419829693 1
< 0.1%
457638.727453242 1
< 0.1%
457247.570869701 1
< 0.1%
457041.349875739 1
< 0.1%
456587.90777321 2
< 0.1%
456587.140422813 1
< 0.1%
456429.344666667 1
< 0.1%

업소구분명
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size32.3 KiB
지정
2918 
<NA>
1018 
종료
 
186

Length

Max length4
Median length2
Mean length2.493935
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지정 2918
70.8%
<NA> 1018
 
24.7%
종료 186
 
4.5%

Length

2024-05-11T14:22:37.637176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:22:37.813699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지정 2918
70.8%
na 1018
 
24.7%
종료 186
 
4.5%

소재지
Text

MISSING 

Distinct2673
Distinct (%)95.3%
Missing1318
Missing (%)32.0%
Memory size32.3 KiB
2024-05-11T14:22:38.312332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length43
Mean length22.866619
Min length4

Characters and Unicode

Total characters64118
Distinct characters343
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

Unique2553 ?
Unique (%)91.0%

Sample

1st row서울특별시 종로구 명륜2가 222번지
2nd row서울특별시 종로구 명륜3가 1번지 28호
3rd row서울특별시 종로구 부암동 220번지 1호 1층
4th row서울특별시 종로구 봉익동 115번지
5th row서울특별시 종로구 연건동 208번지
ValueCountFrequency (%)
서울특별시 2695
20.3%
동대문구 1427
 
10.7%
종로구 467
 
3.5%
443
 
3.3%
마포구 410
 
3.1%
장안동 335
 
2.5%
서초구 285
 
2.1%
답십리동 185
 
1.4%
전농동 171
 
1.3%
이문동 163
 
1.2%
Other values (2599) 6704
50.5%
2024-05-11T14:22:39.026894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11659
18.2%
4224
 
6.6%
3175
 
5.0%
2773
 
4.3%
2712
 
4.2%
2709
 
4.2%
2697
 
4.2%
2697
 
4.2%
1 2580
 
4.0%
1929
 
3.0%
Other values (333) 26963
42.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 38876
60.6%
Decimal Number 12282
 
19.2%
Space Separator 11659
 
18.2%
Dash Punctuation 1154
 
1.8%
Uppercase Letter 83
 
0.1%
Other Punctuation 32
 
< 0.1%
Lowercase Letter 15
 
< 0.1%
Open Punctuation 7
 
< 0.1%
Close Punctuation 7
 
< 0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4224
 
10.9%
3175
 
8.2%
2773
 
7.1%
2712
 
7.0%
2709
 
7.0%
2697
 
6.9%
2697
 
6.9%
1929
 
5.0%
1835
 
4.7%
1599
 
4.1%
Other values (283) 12526
32.2%
Uppercase Letter
ValueCountFrequency (%)
A 11
13.3%
D 7
 
8.4%
T 7
 
8.4%
M 7
 
8.4%
S 7
 
8.4%
B 7
 
8.4%
K 6
 
7.2%
C 6
 
7.2%
P 4
 
4.8%
N 3
 
3.6%
Other values (10) 18
21.7%
Decimal Number
ValueCountFrequency (%)
1 2580
21.0%
2 1672
13.6%
3 1562
12.7%
4 1237
10.1%
5 1075
8.8%
6 889
 
7.2%
0 860
 
7.0%
9 815
 
6.6%
7 798
 
6.5%
8 794
 
6.5%
Lowercase Letter
ValueCountFrequency (%)
e 3
20.0%
r 2
13.3%
w 2
13.3%
o 2
13.3%
y 1
 
6.7%
i 1
 
6.7%
c 1
 
6.7%
t 1
 
6.7%
k 1
 
6.7%
s 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
, 18
56.2%
@ 6
 
18.8%
. 5
 
15.6%
? 2
 
6.2%
/ 1
 
3.1%
Space Separator
ValueCountFrequency (%)
11659
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1154
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 38876
60.6%
Common 25144
39.2%
Latin 98
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4224
 
10.9%
3175
 
8.2%
2773
 
7.1%
2712
 
7.0%
2709
 
7.0%
2697
 
6.9%
2697
 
6.9%
1929
 
5.0%
1835
 
4.7%
1599
 
4.1%
Other values (283) 12526
32.2%
Latin
ValueCountFrequency (%)
A 11
 
11.2%
D 7
 
7.1%
T 7
 
7.1%
M 7
 
7.1%
S 7
 
7.1%
B 7
 
7.1%
K 6
 
6.1%
C 6
 
6.1%
P 4
 
4.1%
N 3
 
3.1%
Other values (20) 33
33.7%
Common
ValueCountFrequency (%)
11659
46.4%
1 2580
 
10.3%
2 1672
 
6.6%
3 1562
 
6.2%
4 1237
 
4.9%
- 1154
 
4.6%
5 1075
 
4.3%
6 889
 
3.5%
0 860
 
3.4%
9 815
 
3.2%
Other values (10) 1641
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 38876
60.6%
ASCII 25242
39.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11659
46.2%
1 2580
 
10.2%
2 1672
 
6.6%
3 1562
 
6.2%
4 1237
 
4.9%
- 1154
 
4.6%
5 1075
 
4.3%
6 889
 
3.5%
0 860
 
3.4%
9 815
 
3.2%
Other values (40) 1739
 
6.9%
Hangul
ValueCountFrequency (%)
4224
 
10.9%
3175
 
8.2%
2773
 
7.1%
2712
 
7.0%
2709
 
7.0%
2697
 
6.9%
2697
 
6.9%
1929
 
5.0%
1835
 
4.7%
1599
 
4.1%
Other values (283) 12526
32.2%

지정일자
Real number (ℝ)

MISSING  SKEWED 

Distinct734
Distinct (%)56.5%
Missing2824
Missing (%)68.5%
Infinite0
Infinite (%)0.0%
Mean20161174
Minimum20000101
Maximum22070709
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.4 KiB
2024-05-11T14:22:39.266694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20000101
5-th percentile20090792
Q120140917
median20160614
Q320180821
95-th percentile20210801
Maximum22070709
Range2070608
Interquartile range (IQR)39904.5

Descriptive statistics

Standard deviation63587.453
Coefficient of variation (CV)0.0031539558
Kurtosis627.3228
Mean20161174
Median Absolute Deviation (MAD)19811
Skewness20.772247
Sum2.6169204 × 1010
Variance4.0433642 × 109
MonotonicityNot monotonic
2024-05-11T14:22:39.455931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20210801 104
 
2.5%
20150110 12
 
0.3%
20151229 12
 
0.3%
20171121 12
 
0.3%
20190408 10
 
0.2%
20150714 9
 
0.2%
20141029 9
 
0.2%
20171226 8
 
0.2%
20150507 8
 
0.2%
20181023 8
 
0.2%
Other values (724) 1106
 
26.8%
(Missing) 2824
68.5%
ValueCountFrequency (%)
20000101 2
< 0.1%
20040521 1
 
< 0.1%
20040524 1
 
< 0.1%
20040603 3
0.1%
20040604 1
 
< 0.1%
20040607 1
 
< 0.1%
20040805 1
 
< 0.1%
20041214 1
 
< 0.1%
20050101 1
 
< 0.1%
20050811 1
 
< 0.1%
ValueCountFrequency (%)
22070709 1
 
< 0.1%
20220315 1
 
< 0.1%
20220311 3
0.1%
20220310 1
 
< 0.1%
20220307 1
 
< 0.1%
20220304 1
 
< 0.1%
20220124 1
 
< 0.1%
20220121 1
 
< 0.1%
20220111 2
< 0.1%
20220106 1
 
< 0.1%

신청일자
Real number (ℝ)

MISSING  SKEWED 

Distinct927
Distinct (%)29.9%
Missing1023
Missing (%)24.8%
Infinite0
Infinite (%)0.0%
Mean20082465
Minimum11941206
Maximum20220315
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.4 KiB
2024-05-11T14:22:39.621433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11941206
5-th percentile19991030
Q120000664
median20061002
Q320151029
95-th percentile20210426
Maximum20220315
Range8279109
Interquartile range (IQR)150364.5

Descriptive statistics

Standard deviation164496.76
Coefficient of variation (CV)0.0081910639
Kurtosis1937.4939
Mean20082465
Median Absolute Deviation (MAD)60901
Skewness-39.137649
Sum6.2235559 × 1010
Variance2.7059183 × 1010
MonotonicityNot monotonic
2024-05-11T14:22:39.776016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20000101 316
 
7.7%
19991030 248
 
6.0%
20050101 124
 
3.0%
20210801 105
 
2.5%
20040604 76
 
1.8%
20040603 74
 
1.8%
20040607 65
 
1.6%
20040521 51
 
1.2%
20120806 47
 
1.1%
20040524 46
 
1.1%
Other values (917) 1947
47.2%
(Missing) 1023
24.8%
ValueCountFrequency (%)
11941206 1
 
< 0.1%
19941203 3
 
0.1%
19941206 28
0.7%
19941210 15
0.4%
19970930 11
 
0.3%
19980925 1
 
< 0.1%
19981117 1
 
< 0.1%
19981204 1
 
< 0.1%
19981215 2
 
< 0.1%
19981231 8
 
0.2%
ValueCountFrequency (%)
20220315 1
 
< 0.1%
20220311 3
0.1%
20220310 1
 
< 0.1%
20220304 2
< 0.1%
20220124 1
 
< 0.1%
20220121 1
 
< 0.1%
20220111 2
< 0.1%
20220106 1
 
< 0.1%
20211224 1
 
< 0.1%
20211215 1
 
< 0.1%

항목값1
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.3 KiB
관급봉투
3641 
<NA>
481 

Length

Max length4
Median length4
Mean length4
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 (%)
관급봉투 3641
88.3%
<NA> 481
 
11.7%

Length

2024-05-11T14:22:39.901889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:22:40.016713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
관급봉투 3641
88.3%
na 481
 
11.7%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)업소구분명소재지지정일자신청일자항목값1
031300003130000142022000342022-07-19<NA>3폐업2폐업2023-02-28<NA><NA><NA>02-6949-5919<NA><NA>서울특별시 마포구 창전동 6-172서울특별시 마포구 와우산로 114 (창전동)04059블루25 행복한 와우점2023-03-02 18:15:12U2022-12-03 00:04:00.0<NA>193395.60654450095.767055<NA><NA><NA><NA><NA>
130000003000000142023000022023-03-07<NA>1영업/정상11영업<NA><NA><NA><NA>02-725-9120<NA><NA>서울특별시 종로구 수송동 135서울특별시 종로구 종로1길 42-1, 1층 (수송동)03152세븐일레븐 세종로점2023-03-07 10:51:53I2022-12-03 00:09:00.0<NA>198046.964111452437.652334<NA><NA><NA><NA><NA>
230000003000000142013002642013-12-26<NA>3폐업2폐업2023-02-28<NA><NA><NA>02-2103-9500<NA>110-122서울특별시 종로구 종로2가 40 101호서울특별시 종로구 수표로 105, 101호 (종로2가)110-122롯데씨브이에스711(주) 종로육의전점2023-03-07 10:58:39U2022-12-03 00:09:00.0<NA>198966.805968452027.574754<NA><NA><NA><NA><NA>
330500003050000142024000122024-03-07<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>
430500003050000142024000112024-03-07<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>
530000003000000142024000092024-03-13<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 종로구 종로5가 247-1서울특별시 종로구 종로 248-19 (종로5가)03197씨유 신진시장점2024-03-13 09:55:46I2023-12-02 23:06:00.0<NA>200401.358475452013.592207<NA><NA><NA><NA><NA>
630000003000000142014000222014-02-10<NA>1영업/정상11영업<NA><NA><NA><NA>02-395-7437<NA>110-011서울특별시 종로구 구기동 56-21 1층서울특별시 종로구 진흥로22길 17, 1층 (구기동)110-011CU(상명구기점)2023-03-23 19:43:24U2022-12-02 22:05:00.0<NA>196240.173808455997.737793<NA><NA><NA><NA><NA>
731300003130000142023000102023-03-13<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 도화동 565 서울대학교 총동창회 장학빌딩서울특별시 마포구 새창로 7, 서울대학교 총동창회 장학빌딩 1층 (도화동)04168세븐일레븐 마포센터점2023-03-10 18:33:50I2022-12-02 23:02:00.0<NA>195597.981544448915.134736<NA><NA><NA><NA><NA>
830500003050000142023000362023-07-11<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 동대문구 장안동 351-3서울특별시 동대문구 장한로18길 26-4, 1층 1호 (장안동)02640유진아울렛2023-07-11 10:50:01I2022-12-06 23:03:00.0<NA>206130.459084451692.754689<NA><NA><NA><NA><NA>
930000003000000142017000412017-08-28<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 종로구 화동 61 안송빌딩서울특별시 종로구 삼청로 68, 안송빌딩 (화동)03053이마트24 삼청동점2023-11-13 17:44:39U2022-10-31 23:05:00.0<NA>198286.187158453260.69137<NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)업소구분명소재지지정일자신청일자항목값1
4112313000031300001420160007620161202<NA>3폐업2폐업20221220<NA><NA><NA>02-322-3917<NA><NA>서울특별시 마포구 서교동 490 메세나폴리스서울특별시 마포구 양화로 45, 지하1층 199호 (서교동, 메세나폴리스)04036세븐일레븐 메세나폴리스점2022-12-26 10:35:59U2021-11-01 22:09:00.0<NA>192311.64258449855.64391<NA><NA><NA><NA><NA>
4113313000031300001420150009620151229<NA>3폐업2폐업20210110<NA><NA><NA>02-324-8247<NA><NA>서울특별시 마포구 서교동 401-8 남주빌딩서울특별시 마포구 독막로7길 16, 남주빌딩 (서교동)04048세븐일레븐 서교2호점2022-12-26 10:56:49U2021-11-01 22:09:00.0<NA>192773.485248449597.533762<NA><NA><NA><NA><NA>
4114300000030000001420130012720131216<NA>3폐업2폐업20230110<NA><NA><NA>02-925-3569<NA>110827서울특별시 종로구 숭인동 681서울특별시 종로구 숭인동길 67 (숭인동)110827경제식품2023-01-10 09:46:59U2022-11-30 23:02:00.0<NA>201850.170132452850.746327<NA><NA><NA><NA><NA>
4115313000031300001420210003720210714<NA>3폐업2폐업20220920<NA><NA><NA><NA><NA><NA>서울특별시 마포구 성산동 446 성산시영아파트서울특별시 마포구 월드컵북로 233-1, 제1상가동동 126호 (성산동, 성산시영아파트)03936지에스25 성산시영점2023-01-11 15:29:53U2022-11-30 23:03:00.0<NA>191263.451931452207.500654<NA><NA><NA><NA><NA>
4116313000031300001420150007020151026<NA>1영업/정상11영업<NA><NA><NA><NA>02-704-9006<NA><NA><NA>서울특별시 마포구 백범로20길 26, 1층 (대흥동)04151지에스25 대흥백범점2023-01-11 11:14:21U2022-11-30 23:03:00.0<NA><NA><NA><NA><NA><NA><NA><NA>
4117313000031300001420220005020221028<NA>1영업/정상11영업<NA><NA><NA><NA>02-335-4554<NA><NA>서울특별시 마포구 합정동 432-7서울특별시 마포구 동교로 60-1, 1층 (합정동)04022또또네 주류마켓2023-01-12 09:36:23U2022-11-30 23:04:00.0<NA>191891.868261450112.162741<NA><NA><NA><NA><NA>
4118300000030000001420130009320131205<NA>1영업/정상11영업<NA><NA><NA><NA>02-736-3582<NA>110043서울특별시 종로구 통인동 134-1서울특별시 종로구 자하문로9길 17 (통인동)110043오거리마트2023-01-26 20:06:39U2022-11-30 22:08:00.0<NA>197292.177005453002.67615<NA><NA><NA><NA><NA>
411930000003000000142023000012023-01-06<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 종로구 예지동 2-1서울특별시 종로구 창경궁로 88, 260호 (예지동)03195씨유 광장시장점2023-03-07 09:53:03U2022-12-03 00:09:00.0<NA>199816.770135451999.53084<NA><NA><NA><NA><NA>
412031300003130000142022000612022-12-26<NA>5제외/삭제/전출5제외사항<NA><NA><NA><NA>02-3144-7887<NA><NA>서울특별시 마포구 서교동 487 서교동 대우미래사랑서울특별시 마포구 월드컵북로5나길 18, 1층 (서교동, 서교동 대우미래사랑)04002비엔씨리테일 주식회사2023-03-13 11:07:08U2022-12-02 23:05:00.0<NA>192577.990805450569.670546<NA><NA><NA><NA><NA>
412130000003000000142016000172016-04-28<NA>1영업/정상11영업<NA><NA><NA><NA>02-906-0005<NA><NA>서울특별시 종로구 창신동 23-426서울특별시 종로구 창신6가길 42, 1층 102호 (창신동)03095심창기업(주)2024-04-02 20:00:47U2023-12-04 00:04:00.0<NA>201065.428086452607.572685<NA><NA><NA><NA><NA>