Overview

Dataset statistics

Number of variables29
Number of observations140
Missing cells1009
Missing cells (%)24.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory33.6 KiB
Average record size in memory245.9 B

Variable types

Categorical11
Text7
DateTime2
Unsupported6
Numeric3

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),비상시설위치,시설구분명,시설명_건물명,해제일자
Author서대문구
URLhttps://data.seoul.go.kr/dataList/OA-20039/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 is highly imbalanced (65.0%)Imbalance
폐업일자 is highly imbalanced (65.0%)Imbalance
해제일자 is highly imbalanced (63.9%)Imbalance
휴업시작일자 has 140 (100.0%) missing valuesMissing
휴업종료일자 has 140 (100.0%) missing valuesMissing
재개업일자 has 140 (100.0%) missing valuesMissing
전화번호 has 140 (100.0%) missing valuesMissing
소재지우편번호 has 140 (100.0%) missing valuesMissing
도로명우편번호 has 9 (6.4%) missing valuesMissing
업태구분명 has 140 (100.0%) missing valuesMissing
좌표정보(X) has 10 (7.1%) missing valuesMissing
좌표정보(Y) has 10 (7.1%) missing valuesMissing
비상시설위치 has 70 (50.0%) missing valuesMissing
시설명_건물명 has 70 (50.0%) missing valuesMissing
관리번호 has unique valuesUnique
최종수정일자 has unique valuesUnique
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
전화번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지우편번호 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 02:47:06.059441
Analysis finished2024-05-11 02:47:07.681116
Duration1.62 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
3120000
140 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3120000
2nd row3120000
3rd row3120000
4th row3120000
5th row3120000

Common Values

ValueCountFrequency (%)
3120000 140
100.0%

Length

2024-05-11T02:47:08.016383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:47:08.448616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3120000 140
100.0%

관리번호
Text

UNIQUE 

Distinct140
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-05-11T02:47:09.087372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length18
Mean length18
Min length18

Characters and Unicode

Total characters2520
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique140 ?
Unique (%)100.0%

Sample

1st row3120000-S195000009
2nd row3120000-S201600013
3rd row3120000-S202300002
4th row3120000-S202300010
5th row3120000-S202300009
ValueCountFrequency (%)
3120000-s195000009 1
 
0.7%
3120000-s200100013 1
 
0.7%
3120000-s200100018 1
 
0.7%
3120000-s200100009 1
 
0.7%
3120000-s200100004 1
 
0.7%
3120000-s202100002 1
 
0.7%
3120000-s202100001 1
 
0.7%
3120000-s201300008 1
 
0.7%
3120000-s200900002 1
 
0.7%
3120000-s201400029 1
 
0.7%
Other values (130) 130
92.9%
2024-05-11T02:47:10.387413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1209
48.0%
2 315
 
12.5%
1 313
 
12.4%
3 194
 
7.7%
- 140
 
5.6%
S 140
 
5.6%
9 106
 
4.2%
4 27
 
1.1%
6 24
 
1.0%
5 21
 
0.8%
Other values (2) 31
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2240
88.9%
Dash Punctuation 140
 
5.6%
Uppercase Letter 140
 
5.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1209
54.0%
2 315
 
14.1%
1 313
 
14.0%
3 194
 
8.7%
9 106
 
4.7%
4 27
 
1.2%
6 24
 
1.1%
5 21
 
0.9%
8 16
 
0.7%
7 15
 
0.7%
Dash Punctuation
ValueCountFrequency (%)
- 140
100.0%
Uppercase Letter
ValueCountFrequency (%)
S 140
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2380
94.4%
Latin 140
 
5.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1209
50.8%
2 315
 
13.2%
1 313
 
13.2%
3 194
 
8.2%
- 140
 
5.9%
9 106
 
4.5%
4 27
 
1.1%
6 24
 
1.0%
5 21
 
0.9%
8 16
 
0.7%
Latin
ValueCountFrequency (%)
S 140
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2520
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1209
48.0%
2 315
 
12.5%
1 313
 
12.4%
3 194
 
7.7%
- 140
 
5.6%
S 140
 
5.6%
9 106
 
4.2%
4 27
 
1.1%
6 24
 
1.0%
5 21
 
0.8%
Other values (2) 31
 
1.2%

인허가일자
Date

Distinct58
Distinct (%)41.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum1979-12-24 00:00:00
Maximum2021-01-12 00:00:00
2024-05-11T02:47:10.990507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:47:11.568735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Categorical

IMBALANCE 

Distinct9
Distinct (%)6.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
115 
42730
 
10
42401
 
6
42612
 
3
41785
 
2
Other values (4)
 
4

Length

Max length10
Median length4
Mean length4.2857143
Min length4

Unique

Unique4 ?
Unique (%)2.9%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 115
82.1%
42730 10
 
7.1%
42401 6
 
4.3%
42612 3
 
2.1%
41785 2
 
1.4%
2023-11-02 1
 
0.7%
2023-07-31 1
 
0.7%
2023-09-21 1
 
0.7%
43871 1
 
0.7%

Length

2024-05-11T02:47:12.198797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:47:12.630988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 115
82.1%
42730 10
 
7.1%
42401 6
 
4.3%
42612 3
 
2.1%
41785 2
 
1.4%
2023-11-02 1
 
0.7%
2023-07-31 1
 
0.7%
2023-09-21 1
 
0.7%
43871 1
 
0.7%

영업상태코드
Categorical

Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
1
115 
4
25 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 115
82.1%
4 25
 
17.9%

Length

2024-05-11T02:47:13.106735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:47:13.562718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 115
82.1%
4 25
 
17.9%

영업상태명
Categorical

Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
영업/정상
115 
취소/말소/만료/정지/중지
25 

Length

Max length14
Median length5
Mean length6.6071429
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 115
82.1%
취소/말소/만료/정지/중지 25
 
17.9%

Length

2024-05-11T02:47:14.087978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:47:14.538661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 115
82.1%
취소/말소/만료/정지/중지 25
 
17.9%

상세영업상태코드
Categorical

Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
18
115 
19
25 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row18
2nd row18
3rd row18
4th row18
5th row18

Common Values

ValueCountFrequency (%)
18 115
82.1%
19 25
 
17.9%

Length

2024-05-11T02:47:14.929476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:47:15.257982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
18 115
82.1%
19 25
 
17.9%

상세영업상태명
Categorical

Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
사용중
115 
사용중지
25 

Length

Max length4
Median length3
Mean length3.1785714
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사용중 115
82.1%
사용중지 25
 
17.9%

Length

2024-05-11T02:47:15.646476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:47:16.146442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사용중 115
82.1%
사용중지 25
 
17.9%

폐업일자
Categorical

IMBALANCE 

Distinct9
Distinct (%)6.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
115 
42730
 
10
42401
 
6
42612
 
3
41785
 
2
Other values (4)
 
4

Length

Max length10
Median length4
Mean length4.2857143
Min length4

Unique

Unique4 ?
Unique (%)2.9%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 115
82.1%
42730 10
 
7.1%
42401 6
 
4.3%
42612 3
 
2.1%
41785 2
 
1.4%
2023-11-02 1
 
0.7%
2023-07-31 1
 
0.7%
2023-09-21 1
 
0.7%
43871 1
 
0.7%

Length

2024-05-11T02:47:16.706212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:47:17.216914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 115
82.1%
42730 10
 
7.1%
42401 6
 
4.3%
42612 3
 
2.1%
41785 2
 
1.4%
2023-11-02 1
 
0.7%
2023-07-31 1
 
0.7%
2023-09-21 1
 
0.7%
43871 1
 
0.7%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing140
Missing (%)100.0%
Memory size1.4 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing140
Missing (%)100.0%
Memory size1.4 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing140
Missing (%)100.0%
Memory size1.4 KiB

전화번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing140
Missing (%)100.0%
Memory size1.4 KiB

소재지면적
Real number (ℝ)

Distinct108
Distinct (%)77.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5943.0964
Minimum132
Maximum57803
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-05-11T02:47:17.831859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum132
5-th percentile560.8525
Q11500
median2592.5
Q36645.25
95-th percentile22649.8
Maximum57803
Range57671
Interquartile range (IQR)5145.25

Descriptive statistics

Standard deviation8926.218
Coefficient of variation (CV)1.5019474
Kurtosis13.140489
Mean5943.0964
Median Absolute Deviation (MAD)1469.27
Skewness3.3646493
Sum832033.5
Variance79677368
MonotonicityNot monotonic
2024-05-11T02:47:18.457796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2000.0 8
 
5.7%
4000.0 8
 
5.7%
2451.0 8
 
5.7%
2500.0 5
 
3.6%
3500.0 3
 
2.1%
1500.0 3
 
2.1%
5500.0 2
 
1.4%
4500.0 2
 
1.4%
3000.0 2
 
1.4%
38539.0 1
 
0.7%
Other values (98) 98
70.0%
ValueCountFrequency (%)
132.0 1
0.7%
250.0 1
0.7%
323.0 1
0.7%
373.0 1
0.7%
518.0 1
0.7%
521.0 1
0.7%
558.05 1
0.7%
561.0 1
0.7%
608.0 1
0.7%
620.0 1
0.7%
ValueCountFrequency (%)
57803.0 1
0.7%
46714.0 1
0.7%
41156.0 1
0.7%
38539.0 1
0.7%
32723.0 1
0.7%
25475.0 1
0.7%
25021.0 1
0.7%
22525.0 1
0.7%
21778.48 1
0.7%
18387.0 1
0.7%

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing140
Missing (%)100.0%
Memory size1.4 KiB

지번주소
Text

Distinct84
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-05-11T02:47:19.193959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length30
Mean length23.064286
Min length19

Characters and Unicode

Total characters3229
Distinct characters112
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

Unique66 ?
Unique (%)47.1%

Sample

1st row서울특별시 서대문구 북아현동 1009번지
2nd row서울특별시 서대문구 홍제동 462번지
3rd row서울특별시 서대문구 홍제동 453 무악청구아파트
4th row서울특별시 서대문구 홍제동 459 홍제원현대아파트
5th row서울특별시 서대문구 홍제동 459 홍제원현대아파트
ValueCountFrequency (%)
서울특별시 140
22.2%
서대문구 139
22.0%
홍제동 37
 
5.9%
남가좌동 22
 
3.5%
홍은동 16
 
2.5%
북가좌동 14
 
2.2%
379번지 10
 
1.6%
연희동 10
 
1.6%
대현동 8
 
1.3%
신촌동 7
 
1.1%
Other values (117) 228
36.1%
2024-05-11T02:47:20.824116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
491
 
15.2%
서 279
 
8.6%
대 159
 
4.9%
시 145
 
4.5%
구 145
 
4.5%
특 140
 
4.3%
별 140
 
4.3%
문 140
 
4.3%
울 140
 
4.3%
동 137
 
4.2%
Other values (102) 1313
40.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2231
69.1%
Space Separator 491
 
15.2%
Decimal Number 450
 
13.9%
Uppercase Letter 45
 
1.4%
Dash Punctuation 5
 
0.2%
Lowercase Letter 5
 
0.2%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 279
 
12.5%
대 159
 
7.1%
시 145
 
6.5%
구 145
 
6.5%
특 140
 
6.3%
별 140
 
6.3%
문 140
 
6.3%
울 140
 
6.3%
동 137
 
6.1%
지 102
 
4.6%
Other values (84) 704
31.6%
Decimal Number
ValueCountFrequency (%)
4 81
18.0%
1 67
14.9%
3 63
14.0%
5 43
9.6%
7 38
8.4%
2 36
8.0%
0 35
7.8%
6 32
 
7.1%
9 29
 
6.4%
8 26
 
5.8%
Uppercase Letter
ValueCountFrequency (%)
D 15
33.3%
M 15
33.3%
C 15
33.3%
Space Separator
ValueCountFrequency (%)
491
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2231
69.1%
Common 948
29.4%
Latin 50
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 279
 
12.5%
대 159
 
7.1%
시 145
 
6.5%
구 145
 
6.5%
특 140
 
6.3%
별 140
 
6.3%
문 140
 
6.3%
울 140
 
6.3%
동 137
 
6.1%
지 102
 
4.6%
Other values (84) 704
31.6%
Common
ValueCountFrequency (%)
491
51.8%
4 81
 
8.5%
1 67
 
7.1%
3 63
 
6.6%
5 43
 
4.5%
7 38
 
4.0%
2 36
 
3.8%
0 35
 
3.7%
6 32
 
3.4%
9 29
 
3.1%
Other values (4) 33
 
3.5%
Latin
ValueCountFrequency (%)
D 15
30.0%
M 15
30.0%
C 15
30.0%
e 5
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2231
69.1%
ASCII 998
30.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
491
49.2%
4 81
 
8.1%
1 67
 
6.7%
3 63
 
6.3%
5 43
 
4.3%
7 38
 
3.8%
2 36
 
3.6%
0 35
 
3.5%
6 32
 
3.2%
9 29
 
2.9%
Other values (8) 83
 
8.3%
Hangul
ValueCountFrequency (%)
서 279
 
12.5%
대 159
 
7.1%
시 145
 
6.5%
구 145
 
6.5%
특 140
 
6.3%
별 140
 
6.3%
문 140
 
6.3%
울 140
 
6.3%
동 137
 
6.1%
지 102
 
4.6%
Other values (84) 704
31.6%

도로명주소
Text

Distinct86
Distinct (%)61.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-05-11T02:47:21.378928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length38
Mean length33.878571
Min length24

Characters and Unicode

Total characters4743
Distinct characters190
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique67 ?
Unique (%)47.9%

Sample

1st row서울특별시 서대문구 이화여대8길 62 (북아현동, 두산아파트)
2nd row서울특별시 서대문구 통일로 332 (홍제동, 홍제청구3차아파트)
3rd row서울특별시 서대문구 통일로 348 (홍제동, 무악청구아파트)
4th row서울특별시 서대문구 통일로34길 43 (홍제동, 홍제원현대아파트)
5th row서울특별시 서대문구 통일로34길 43 (홍제동, 홍제원현대아파트)
ValueCountFrequency (%)
서울특별시 140
 
16.8%
서대문구 139
 
16.7%
홍제동 37
 
4.4%
남가좌동 22
 
2.6%
통일로 18
 
2.2%
43 17
 
2.0%
홍은동 16
 
1.9%
북가좌동 14
 
1.7%
수색로 11
 
1.3%
연희동 10
 
1.2%
Other values (199) 410
49.2%
2024-05-11T02:47:22.496062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
698
 
14.7%
서 287
 
6.1%
대 191
 
4.0%
문 163
 
3.4%
동 151
 
3.2%
구 148
 
3.1%
울 147
 
3.1%
시 146
 
3.1%
( 141
 
3.0%
특 141
 
3.0%
Other values (180) 2530
53.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3113
65.6%
Space Separator 698
 
14.7%
Decimal Number 452
 
9.5%
Open Punctuation 141
 
3.0%
Close Punctuation 141
 
3.0%
Other Punctuation 119
 
2.5%
Uppercase Letter 51
 
1.1%
Dash Punctuation 23
 
0.5%
Lowercase Letter 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 287
 
9.2%
대 191
 
6.1%
문 163
 
5.2%
동 151
 
4.9%
구 148
 
4.8%
울 147
 
4.7%
시 146
 
4.7%
특 141
 
4.5%
별 141
 
4.5%
로 129
 
4.1%
Other values (161) 1469
47.2%
Decimal Number
ValueCountFrequency (%)
3 95
21.0%
1 74
16.4%
4 65
14.4%
2 53
11.7%
0 44
9.7%
5 43
9.5%
8 23
 
5.1%
9 21
 
4.6%
6 21
 
4.6%
7 13
 
2.9%
Uppercase Letter
ValueCountFrequency (%)
M 17
33.3%
C 17
33.3%
D 17
33.3%
Space Separator
ValueCountFrequency (%)
698
100.0%
Open Punctuation
ValueCountFrequency (%)
( 141
100.0%
Close Punctuation
ValueCountFrequency (%)
) 141
100.0%
Other Punctuation
ValueCountFrequency (%)
, 119
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3113
65.6%
Common 1574
33.2%
Latin 56
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 287
 
9.2%
대 191
 
6.1%
문 163
 
5.2%
동 151
 
4.9%
구 148
 
4.8%
울 147
 
4.7%
시 146
 
4.7%
특 141
 
4.5%
별 141
 
4.5%
로 129
 
4.1%
Other values (161) 1469
47.2%
Common
ValueCountFrequency (%)
698
44.3%
( 141
 
9.0%
) 141
 
9.0%
, 119
 
7.6%
3 95
 
6.0%
1 74
 
4.7%
4 65
 
4.1%
2 53
 
3.4%
0 44
 
2.8%
5 43
 
2.7%
Other values (5) 101
 
6.4%
Latin
ValueCountFrequency (%)
M 17
30.4%
C 17
30.4%
D 17
30.4%
e 5
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3113
65.6%
ASCII 1630
34.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
698
42.8%
( 141
 
8.7%
) 141
 
8.7%
, 119
 
7.3%
3 95
 
5.8%
1 74
 
4.5%
4 65
 
4.0%
2 53
 
3.3%
0 44
 
2.7%
5 43
 
2.6%
Other values (9) 157
 
9.6%
Hangul
ValueCountFrequency (%)
서 287
 
9.2%
대 191
 
6.1%
문 163
 
5.2%
동 151
 
4.9%
구 148
 
4.8%
울 147
 
4.7%
시 146
 
4.7%
특 141
 
4.5%
별 141
 
4.5%
로 129
 
4.1%
Other values (161) 1469
47.2%

도로명우편번호
Text

MISSING 

Distinct67
Distinct (%)51.1%
Missing9
Missing (%)6.4%
Memory size1.2 KiB
2024-05-11T02:47:23.048651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length4.7480916
Min length4

Characters and Unicode

Total characters622
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

Unique41 ?
Unique (%)31.3%

Sample

1st row03769
2nd row03634
3rd row03635
4th row03631
5th row03631
ValueCountFrequency (%)
3709 10
 
7.6%
3730 8
 
6.1%
03631 7
 
5.3%
03635 6
 
4.6%
3764 6
 
4.6%
03686 5
 
3.8%
120-752 5
 
3.8%
3746 4
 
3.1%
03615 3
 
2.3%
03657 3
 
2.3%
Other values (57) 74
56.5%
2024-05-11T02:47:24.052063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 164
26.4%
0 121
19.5%
7 91
14.6%
6 73
11.7%
1 46
 
7.4%
2 31
 
5.0%
5 26
 
4.2%
9 22
 
3.5%
4 22
 
3.5%
8 16
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 612
98.4%
Dash Punctuation 10
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 164
26.8%
0 121
19.8%
7 91
14.9%
6 73
11.9%
1 46
 
7.5%
2 31
 
5.1%
5 26
 
4.2%
9 22
 
3.6%
4 22
 
3.6%
8 16
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 622
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 164
26.4%
0 121
19.5%
7 91
14.6%
6 73
11.7%
1 46
 
7.4%
2 31
 
5.0%
5 26
 
4.2%
9 22
 
3.5%
4 22
 
3.5%
8 16
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 622
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 164
26.4%
0 121
19.5%
7 91
14.6%
6 73
11.7%
1 46
 
7.4%
2 31
 
5.0%
5 26
 
4.2%
9 22
 
3.5%
4 22
 
3.5%
8 16
 
2.6%

사업장명
Text

Distinct136
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-05-11T02:47:24.590848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length26
Mean length19.792857
Min length7

Characters and Unicode

Total characters2771
Distinct characters178
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique134 ?
Unique (%)95.7%

Sample

1st row북아현두산아파트 지하1층
2nd row홍제청구3차아파트 지하주차장 지하1~5층
3rd row무악청구1차아파트 제2주차장 지하1~2층
4th row홍제원현대아파트 제5주차장 지하1~2층
5th row홍제원현대아파트 제4주차장 지하1층
ValueCountFrequency (%)
지하주차장 48
 
11.3%
지하1층 36
 
8.5%
지하1~2층 24
 
5.7%
지하1~3층 22
 
5.2%
전동 9
 
2.1%
전체 8
 
1.9%
동의 8
 
1.9%
홍제원현대아파트 7
 
1.7%
제2주차장 7
 
1.7%
제1주차장 7
 
1.7%
Other values (153) 248
58.5%
2024-05-11T02:47:25.533299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
284
 
10.2%
지 198
 
7.1%
하 181
 
6.5%
1 145
 
5.2%
층 129
 
4.7%
차 123
 
4.4%
주 105
 
3.8%
장 103
 
3.7%
트 98
 
3.5%
파 96
 
3.5%
Other values (168) 1309
47.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2015
72.7%
Decimal Number 321
 
11.6%
Space Separator 284
 
10.2%
Math Symbol 75
 
2.7%
Uppercase Letter 52
 
1.9%
Open Punctuation 9
 
0.3%
Close Punctuation 8
 
0.3%
Lowercase Letter 5
 
0.2%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 198
 
9.8%
하 181
 
9.0%
층 129
 
6.4%
차 123
 
6.1%
주 105
 
5.2%
장 103
 
5.1%
트 98
 
4.9%
파 96
 
4.8%
아 95
 
4.7%
동 58
 
2.9%
Other values (148) 829
41.1%
Decimal Number
ValueCountFrequency (%)
1 145
45.2%
2 68
21.2%
3 46
 
14.3%
0 17
 
5.3%
4 16
 
5.0%
5 15
 
4.7%
6 7
 
2.2%
7 4
 
1.2%
9 2
 
0.6%
8 1
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
C 17
32.7%
D 17
32.7%
M 17
32.7%
A 1
 
1.9%
Space Separator
ValueCountFrequency (%)
284
100.0%
Math Symbol
ValueCountFrequency (%)
~ 75
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 5
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2015
72.7%
Common 699
 
25.2%
Latin 57
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 198
 
9.8%
하 181
 
9.0%
층 129
 
6.4%
차 123
 
6.1%
주 105
 
5.2%
장 103
 
5.1%
트 98
 
4.9%
파 96
 
4.8%
아 95
 
4.7%
동 58
 
2.9%
Other values (148) 829
41.1%
Common
ValueCountFrequency (%)
284
40.6%
1 145
20.7%
~ 75
 
10.7%
2 68
 
9.7%
3 46
 
6.6%
0 17
 
2.4%
4 16
 
2.3%
5 15
 
2.1%
( 9
 
1.3%
) 8
 
1.1%
Other values (5) 16
 
2.3%
Latin
ValueCountFrequency (%)
C 17
29.8%
D 17
29.8%
M 17
29.8%
e 5
 
8.8%
A 1
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2015
72.7%
ASCII 756
 
27.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
284
37.6%
1 145
19.2%
~ 75
 
9.9%
2 68
 
9.0%
3 46
 
6.1%
C 17
 
2.2%
D 17
 
2.2%
M 17
 
2.2%
0 17
 
2.2%
4 16
 
2.1%
Other values (10) 54
 
7.1%
Hangul
ValueCountFrequency (%)
지 198
 
9.8%
하 181
 
9.0%
층 129
 
6.4%
차 123
 
6.1%
주 105
 
5.2%
장 103
 
5.1%
트 98
 
4.9%
파 96
 
4.8%
아 95
 
4.7%
동 58
 
2.9%
Other values (148) 829
41.1%

최종수정일자
Date

UNIQUE 

Distinct140
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum2014-05-27 07:56:59
Maximum2024-01-30 18:32:32
2024-05-11T02:47:26.001744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:47:27.015563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
U
119 
I
21 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 119
85.0%
I 21
 
15.0%

Length

2024-05-11T02:47:27.563670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:47:27.911419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 119
85.0%
i 21
 
15.0%

데이터갱신일자
Categorical

Distinct26
Distinct (%)18.6%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2018-08-31 23:59:59.0
21 
2023-06-03 02:40:00.0
17 
2022-11-01 00:01:00.0
14 
2023-12-02 00:01:00.0
11 
2023-07-14 02:40:00.0
10 
Other values (21)
67 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique9 ?
Unique (%)6.4%

Sample

1st row2023-12-01 00:08:00.0
2nd row2022-11-01 00:04:00.0
3rd row2022-11-01 00:01:00.0
4th row2022-11-01 00:01:00.0
5th row2022-11-01 00:01:00.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 21
15.0%
2023-06-03 02:40:00.0 17
12.1%
2022-11-01 00:01:00.0 14
10.0%
2023-12-02 00:01:00.0 11
 
7.9%
2023-07-14 02:40:00.0 10
 
7.1%
2022-12-06 22:09:00.0 9
 
6.4%
2023-06-18 02:40:00.0 9
 
6.4%
2023-11-30 21:01:00.0 8
 
5.7%
2022-11-01 00:03:00.0 6
 
4.3%
2023-04-01 02:40:00.0 5
 
3.6%
Other values (16) 30
21.4%

Length

2024-05-11T02:47:28.244184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
02:40:00.0 49
17.5%
2022-11-01 28
 
10.0%
00:01:00.0 25
 
8.9%
2018-08-31 21
 
7.5%
23:59:59.0 21
 
7.5%
2023-06-03 17
 
6.1%
2022-12-06 12
 
4.3%
2023-12-02 11
 
3.9%
2023-07-14 10
 
3.6%
2023-06-18 9
 
3.2%
Other values (24) 77
27.5%

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing140
Missing (%)100.0%
Memory size1.4 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct82
Distinct (%)63.1%
Missing10
Missing (%)7.1%
Infinite0
Infinite (%)0.0%
Mean194656.45
Minimum191380.88
Maximum197004.36
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-05-11T02:47:28.656992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum191380.88
5-th percentile192028.42
Q1194089.59
median195212.16
Q3195586.62
95-th percentile196574.71
Maximum197004.36
Range5623.4863
Interquartile range (IQR)1497.0303

Descriptive statistics

Standard deviation1414.1472
Coefficient of variation (CV)0.0072648362
Kurtosis-0.4295303
Mean194656.45
Median Absolute Deviation (MAD)627.19953
Skewness-0.74104181
Sum25305338
Variance1999812.3
MonotonicityNot monotonic
2024-05-11T02:47:29.211398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
195477.913016234 7
 
5.0%
194584.959249312 7
 
5.0%
195259.429272709 7
 
5.0%
195332.123380254 6
 
4.3%
195694.979414141 5
 
3.6%
192028.41586192 5
 
3.6%
192559.994725361 5
 
3.6%
196536.360487065 4
 
2.9%
192214.50843343 3
 
2.1%
194509.896829194 2
 
1.4%
Other values (72) 79
56.4%
(Missing) 10
 
7.1%
ValueCountFrequency (%)
191380.878019415 1
 
0.7%
191484.638855239 1
 
0.7%
191489.601546595 1
 
0.7%
191798.272173715 1
 
0.7%
191836.275479334 1
 
0.7%
192028.41586192 5
3.6%
192214.50843343 3
2.1%
192260.299912091 1
 
0.7%
192380.048458303 1
 
0.7%
192402.47991549 1
 
0.7%
ValueCountFrequency (%)
197004.364341776 1
 
0.7%
196851.907463121 1
 
0.7%
196694.508582738 1
 
0.7%
196688.913227565 1
 
0.7%
196680.837898287 1
 
0.7%
196662.335160742 1
 
0.7%
196606.081100709 1
 
0.7%
196536.360487065 4
2.9%
196397.574633596 1
 
0.7%
196259.607806599 1
 
0.7%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct82
Distinct (%)63.1%
Missing10
Missing (%)7.1%
Infinite0
Infinite (%)0.0%
Mean452651.13
Minimum450268.83
Maximum455710.43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-05-11T02:47:29.892977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum450268.83
5-th percentile450788.89
Q1451540.28
median452651.65
Q3453430.81
95-th percentile454916.66
Maximum455710.43
Range5441.5953
Interquartile range (IQR)1890.5285

Descriptive statistics

Standard deviation1280.1983
Coefficient of variation (CV)0.0028282229
Kurtosis-0.61276408
Mean452651.13
Median Absolute Deviation (MAD)984.78417
Skewness0.19094947
Sum58844647
Variance1638907.7
MonotonicityNot monotonic
2024-05-11T02:47:30.505977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
453929.325030582 7
 
5.0%
451381.585492051 7
 
5.0%
453430.811542203 7
 
5.0%
450806.05844472 6
 
4.3%
453291.683935348 5
 
3.6%
452265.952165442 5
 
3.6%
452852.020155302 5
 
3.6%
451540.283068404 4
 
2.9%
452192.485035958 3
 
2.1%
452651.895077515 2
 
1.4%
Other values (72) 79
56.4%
(Missing) 10
 
7.1%
ValueCountFrequency (%)
450268.8345718 1
 
0.7%
450433.691021245 2
 
1.4%
450629.432880156 1
 
0.7%
450768.295518175 2
 
1.4%
450774.846649942 1
 
0.7%
450806.05844472 6
4.3%
450862.36191038 1
 
0.7%
450882.103642965 2
 
1.4%
450947.071750286 1
 
0.7%
450999.900043141 1
 
0.7%
ValueCountFrequency (%)
455710.429910779 1
0.7%
455588.317096857 1
0.7%
455298.773326189 1
0.7%
455184.177953414 1
0.7%
455134.654298054 1
0.7%
455079.366770368 1
0.7%
455023.542409959 1
0.7%
454786.019433577 1
0.7%
454754.899472127 1
0.7%
454718.872954095 1
0.7%

비상시설위치
Text

MISSING 

Distinct35
Distinct (%)50.0%
Missing70
Missing (%)50.0%
Memory size1.2 KiB
2024-05-11T02:47:31.276741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length28
Mean length22.185714
Min length19

Characters and Unicode

Total characters1553
Distinct characters71
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)35.7%

Sample

1st row서울특별시 서대문구 북가좌동 453 DMC현대아파트
2nd row서울특별시 서대문구 홍제동 156번지
3rd row서울특별시 서대문구 홍제동 161번지 1호
4th row서울특별시 서대문구 홍제동 331번지
5th row서울특별시 서대문구 북아현동 215 북성초등학교
ValueCountFrequency (%)
서울특별시 70
22.9%
서대문구 70
22.9%
홍제동 15
 
4.9%
남가좌동 14
 
4.6%
북가좌동 14
 
4.6%
379번지 10
 
3.3%
82번지 7
 
2.3%
대현동 6
 
2.0%
144번지 6
 
2.0%
현저동 5
 
1.6%
Other values (46) 89
29.1%
2024-05-11T02:47:32.415793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
236
 
15.2%
서 140
 
9.0%
대 77
 
5.0%
동 72
 
4.6%
문 71
 
4.6%
특 70
 
4.5%
별 70
 
4.5%
시 70
 
4.5%
구 70
 
4.5%
울 70
 
4.5%
Other values (61) 607
39.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1076
69.3%
Space Separator 236
 
15.2%
Decimal Number 209
 
13.5%
Uppercase Letter 27
 
1.7%
Lowercase Letter 5
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 140
13.0%
대 77
 
7.2%
동 72
 
6.7%
문 71
 
6.6%
특 70
 
6.5%
별 70
 
6.5%
시 70
 
6.5%
구 70
 
6.5%
울 70
 
6.5%
지 58
 
5.4%
Other values (46) 308
28.6%
Decimal Number
ValueCountFrequency (%)
1 44
21.1%
4 38
18.2%
3 24
11.5%
0 18
8.6%
8 17
 
8.1%
2 17
 
8.1%
9 13
 
6.2%
5 13
 
6.2%
6 13
 
6.2%
7 12
 
5.7%
Uppercase Letter
ValueCountFrequency (%)
D 9
33.3%
M 9
33.3%
C 9
33.3%
Space Separator
ValueCountFrequency (%)
236
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1076
69.3%
Common 445
28.7%
Latin 32
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 140
13.0%
대 77
 
7.2%
동 72
 
6.7%
문 71
 
6.6%
특 70
 
6.5%
별 70
 
6.5%
시 70
 
6.5%
구 70
 
6.5%
울 70
 
6.5%
지 58
 
5.4%
Other values (46) 308
28.6%
Common
ValueCountFrequency (%)
236
53.0%
1 44
 
9.9%
4 38
 
8.5%
3 24
 
5.4%
0 18
 
4.0%
8 17
 
3.8%
2 17
 
3.8%
9 13
 
2.9%
5 13
 
2.9%
6 13
 
2.9%
Latin
ValueCountFrequency (%)
D 9
28.1%
M 9
28.1%
C 9
28.1%
e 5
15.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1076
69.3%
ASCII 477
30.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
236
49.5%
1 44
 
9.2%
4 38
 
8.0%
3 24
 
5.0%
0 18
 
3.8%
8 17
 
3.6%
2 17
 
3.6%
9 13
 
2.7%
5 13
 
2.7%
6 13
 
2.7%
Other values (5) 44
 
9.2%
Hangul
ValueCountFrequency (%)
서 140
13.0%
대 77
 
7.2%
동 72
 
6.7%
문 71
 
6.6%
특 70
 
6.5%
별 70
 
6.5%
시 70
 
6.5%
구 70
 
6.5%
울 70
 
6.5%
지 58
 
5.4%
Other values (46) 308
28.6%

시설구분명
Categorical

Distinct3
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
70 
공공용시설
48 
공공시설
22 

Length

Max length5
Median length4
Mean length4.3428571
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> 70
50.0%
공공용시설 48
34.3%
공공시설 22
 
15.7%

Length

2024-05-11T02:47:33.011318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:47:33.434284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 70
50.0%
공공용시설 48
34.3%
공공시설 22
 
15.7%

시설명_건물명
Text

MISSING 

Distinct66
Distinct (%)94.3%
Missing70
Missing (%)50.0%
Memory size1.2 KiB
2024-05-11T02:47:34.232166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length25
Mean length20.071429
Min length7

Characters and Unicode

Total characters1405
Distinct characters115
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

Unique64 ?
Unique (%)91.4%

Sample

1st rowDMC현대아파트 지하주차장 1~3층
2nd row홍제센트럴아이파크아파트 지하주차장 지하1층
3rd row지하철3호선 홍제역 지하1~3층
4th row홍제현대아파트주차장 전동 지하주차장 지하1층
5th row북성교육문화관 지하주차장 지하1층
ValueCountFrequency (%)
지하주차장 28
 
13.1%
지하1층 17
 
8.0%
지하1~3층 9
 
4.2%
지하1~2층 8
 
3.8%
홍제한양아파트 7
 
3.3%
럭키대현아파트 6
 
2.8%
남가좌동 6
 
2.8%
삼성아파트2차 6
 
2.8%
동의 5
 
2.3%
천연동 5
 
2.3%
Other values (82) 116
54.5%
2024-05-11T02:47:36.700308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
143
 
10.2%
지 94
 
6.7%
하 80
 
5.7%
1 66
 
4.7%
차 63
 
4.5%
트 60
 
4.3%
파 59
 
4.2%
주 56
 
4.0%
장 55
 
3.9%
아 54
 
3.8%
Other values (105) 675
48.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1021
72.7%
Decimal Number 156
 
11.1%
Space Separator 143
 
10.2%
Uppercase Letter 33
 
2.3%
Math Symbol 31
 
2.2%
Close Punctuation 8
 
0.6%
Open Punctuation 8
 
0.6%
Lowercase Letter 5
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 94
 
9.2%
하 80
 
7.8%
차 63
 
6.2%
트 60
 
5.9%
파 59
 
5.8%
주 56
 
5.5%
장 55
 
5.4%
아 54
 
5.3%
층 52
 
5.1%
동 34
 
3.3%
Other values (87) 414
40.5%
Decimal Number
ValueCountFrequency (%)
1 66
42.3%
2 32
20.5%
3 22
 
14.1%
0 12
 
7.7%
4 10
 
6.4%
5 6
 
3.8%
6 3
 
1.9%
9 2
 
1.3%
7 2
 
1.3%
8 1
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
D 11
33.3%
M 11
33.3%
C 11
33.3%
Space Separator
ValueCountFrequency (%)
143
100.0%
Math Symbol
ValueCountFrequency (%)
~ 31
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1021
72.7%
Common 346
 
24.6%
Latin 38
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 94
 
9.2%
하 80
 
7.8%
차 63
 
6.2%
트 60
 
5.9%
파 59
 
5.8%
주 56
 
5.5%
장 55
 
5.4%
아 54
 
5.3%
층 52
 
5.1%
동 34
 
3.3%
Other values (87) 414
40.5%
Common
ValueCountFrequency (%)
143
41.3%
1 66
19.1%
2 32
 
9.2%
~ 31
 
9.0%
3 22
 
6.4%
0 12
 
3.5%
4 10
 
2.9%
) 8
 
2.3%
( 8
 
2.3%
5 6
 
1.7%
Other values (4) 8
 
2.3%
Latin
ValueCountFrequency (%)
D 11
28.9%
M 11
28.9%
C 11
28.9%
e 5
13.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1021
72.7%
ASCII 384
 
27.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
143
37.2%
1 66
17.2%
2 32
 
8.3%
~ 31
 
8.1%
3 22
 
5.7%
0 12
 
3.1%
D 11
 
2.9%
M 11
 
2.9%
C 11
 
2.9%
4 10
 
2.6%
Other values (8) 35
 
9.1%
Hangul
ValueCountFrequency (%)
지 94
 
9.2%
하 80
 
7.8%
차 63
 
6.2%
트 60
 
5.9%
파 59
 
5.8%
주 56
 
5.5%
장 55
 
5.4%
아 54
 
5.3%
층 52
 
5.1%
동 34
 
3.3%
Other values (87) 414
40.5%

해제일자
Categorical

IMBALANCE 

Distinct6
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
118 
20161226
 
10
20160201
 
6
20160830
 
3
20140526
 
2

Length

Max length8
Median length4
Mean length4.6285714
Min length4

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 118
84.3%
20161226 10
 
7.1%
20160201 6
 
4.3%
20160830 3
 
2.1%
20140526 2
 
1.4%
20200210 1
 
0.7%

Length

2024-05-11T02:47:37.524812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:47:38.048433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 118
84.3%
20161226 10
 
7.1%
20160201 6
 
4.3%
20160830 3
 
2.1%
20140526 2
 
1.4%
20200210 1
 
0.7%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)비상시설위치시설구분명시설명_건물명해제일자
031200003120000-S1950000091993-03-11<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>5500.0<NA>서울특별시 서대문구 북아현동 1009번지서울특별시 서대문구 이화여대8길 62 (북아현동, 두산아파트)03769북아현두산아파트 지하1층2024-01-06 11:37:43U2023-12-01 00:08:00.0<NA>195522.18574450768.295518<NA><NA><NA><NA>
131200003120000-S2016000132016-02-01<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>2000.0<NA>서울특별시 서대문구 홍제동 462번지서울특별시 서대문구 통일로 332 (홍제동, 홍제청구3차아파트)03634홍제청구3차아파트 지하주차장 지하1~5층2023-11-02 13:34:08U2022-11-01 00:04:00.0<NA>195773.341632453129.479552<NA><NA><NA><NA>
231200003120000-S2023000022008-12-02<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>558.05<NA>서울특별시 서대문구 홍제동 453 무악청구아파트서울특별시 서대문구 통일로 348 (홍제동, 무악청구아파트)03635무악청구1차아파트 제2주차장 지하1~2층2023-10-30 22:20:46U2022-11-01 00:01:00.0<NA>195694.979414453291.683935<NA><NA><NA><NA>
331200003120000-S2023000102008-12-02<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>3245.3<NA>서울특별시 서대문구 홍제동 459 홍제원현대아파트서울특별시 서대문구 통일로34길 43 (홍제동, 홍제원현대아파트)03631홍제원현대아파트 제5주차장 지하1~2층2023-10-30 23:07:54U2022-11-01 00:01:00.0<NA>195477.913016453929.325031<NA><NA><NA><NA>
431200003120000-S2023000092008-12-02<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>1909.0<NA>서울특별시 서대문구 홍제동 459 홍제원현대아파트서울특별시 서대문구 통일로34길 43 (홍제동, 홍제원현대아파트)03631홍제원현대아파트 제4주차장 지하1층2023-10-30 23:06:38U2022-11-01 00:01:00.0<NA>195477.913016453929.325031<NA><NA><NA><NA>
531200003120000-S2023000042008-12-02<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>1309.26<NA>서울특별시 서대문구 홍제동 453 무악청구아파트서울특별시 서대문구 통일로 348 (홍제동, 무악청구아파트)03635무악청구1차아파트 제5주차장 지하1~2층2023-10-30 22:21:44U2022-11-01 00:01:00.0<NA>195694.979414453291.683935<NA><NA><NA><NA>
631200003120000-S2023000032008-12-02<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>1277.55<NA>서울특별시 서대문구 홍제동 453 무악청구아파트서울특별시 서대문구 통일로 348 (홍제동, 무악청구아파트)03635무악청구1차아파트 제3주차장 지하1~2층2023-10-30 22:19:40U2022-11-01 00:01:00.0<NA>195694.979414453291.683935<NA><NA><NA><NA>
731200003120000-S2012000232012-10-04<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>16627.0<NA>서울특별시 서대문구 충정로3가 470번지서울특별시 서대문구 충정로 23 (충정로3가, 풍산빌딩)03737풍산빌딩 지하2층~지하7층2024-01-30 18:32:32U2023-12-02 00:01:00.0<NA>196662.335161450999.900043<NA><NA><NA><NA>
831200003120000-S2023000082008-12-02<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>3361.5<NA>서울특별시 서대문구 홍제동 459 홍제원현대아파트서울특별시 서대문구 통일로34길 43 (홍제동, 홍제원현대아파트)03631홍제원현대아파트 제3주차장 지하1~2층2023-10-30 23:07:05U2022-11-01 00:01:00.0<NA>195477.913016453929.325031<NA><NA><NA><NA>
931200003120000-S2023000072008-12-02<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>1611.9<NA>서울특별시 서대문구 홍제동 459 홍제원현대아파트서울특별시 서대문구 통일로34길 43 (홍제동, 홍제원현대아파트)03631홍제원현대아파트 제2주차장 지하1층2023-10-30 23:00:08U2022-11-01 00:01:00.0<NA>195477.913016453929.325031<NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)비상시설위치시설구분명시설명_건물명해제일자
13031200003120000-S2014000052014-04-23427304취소/말소/만료/정지/중지19사용중지42730<NA><NA><NA><NA>8336.0<NA>서울특별시 서대문구 신촌동 134번지서울특별시 서대문구 연세로 50-1 (신촌동)120-752세브란스 암병동2016-12-26 17:45:38I2018-08-31 23:59:59.0<NA>194584.959249451381.585492서울특별시 서대문구 신촌동 134번지공공시설세브란스 암병동20161226
13131200003120000-S2014000062014-04-23427304취소/말소/만료/정지/중지19사용중지42730<NA><NA><NA><NA>7130.0<NA>서울특별시 서대문구 신촌동 134번지서울특별시 서대문구 연세로 50-1 (신촌동)120-752세브란스 암병동2016-12-26 17:45:27I2018-08-31 23:59:59.0<NA>194584.959249451381.585492서울특별시 서대문구 신촌동 134번지공공시설세브란스 암병동20161226
13231200003120000-S2002000032002-07-31<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>25475.0<NA>서울특별시 서대문구 연희동 739번지서울특별시 서대문구 연희로 38-20 (연희동, 연희대우아파트)03781연희대우아파트 전체동 지하1층~지하3층2023-07-27 16:31:09U2022-12-06 22:09:00.0<NA>193702.766235451029.366956<NA><NA><NA><NA>
13331200003120000-S1999000221999-05-19<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>620.0<NA>서울특별시 서대문구 연희동 74번지 14호서울특별시 서대문구 연희로26가길 33 (연희동, 동도아카데미하우스)03720동도아카데미하우스2차 지하1층2023-07-27 16:10:29U2022-12-06 22:09:00.0<NA>194347.045112452462.552184<NA><NA><NA><NA>
13431200003120000-S1993000121993-09-03<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>608.0<NA>서울특별시 서대문구 연희동 700번지서울특별시 서대문구 연희로32길 20 (연희동, 대림아파트)03719연희대림아파트 전체동 지하1층2023-07-27 16:10:05U2022-12-06 22:09:00.0<NA>194297.832937452570.312593<NA><NA><NA><NA>
13531200003120000-S2009000032009-07-08<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>11982.55<NA>서울특별시 서대문구 홍은동 460번지서울특별시 서대문구 홍은중앙로 149 (홍은동, 홍은동풍림아이원아파트)03600풍림아이원아파트 전동 지하주차장 지하1~5층2023-11-01 21:13:27U2022-11-01 00:03:00.0<NA>195360.542102455710.429911<NA><NA><NA><NA>
13631200003120000-S2003000042003-06-04<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>1098.0<NA>서울특별시 서대문구 홍은동 453-2 풍림2차아파트서울특별시 서대문구 세검정로1길 35 (홍은동, 풍림2차아파트)03615풍림2차아파트 지하주차장 지하1~2층2023-12-04 15:03:08U2022-11-02 00:06:00.0<NA>194914.495659454564.345813<NA><NA><NA><NA>
13731200003120000-S2003000032003-06-04<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>692.0<NA>서울특별시 서대문구 홍은동 440번지 3호서울특별시 서대문구 통일로48가길 37 (홍은동, 홍은풍림1차아파트)03615풍림1차아파트 지하주차장 지하1층2023-11-01 21:03:42U2022-11-01 00:03:00.0<NA>194810.728275454718.872954<NA><NA><NA><NA>
13831200003120000-S2001000212001-01-01<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>1045.0<NA>서울특별시 서대문구 홍은동 457번지서울특별시 서대문구 홍은중앙로 81 (홍은동, 동일아파트)03604홍은동일아파트 지하주차장 지하1층2023-11-01 20:52:12U2022-11-01 00:03:00.0<NA>195219.8026455134.654298<NA><NA><NA><NA>
13931200003120000-S2001000232001-01-01<NA>1영업/정상18사용중<NA><NA><NA><NA><NA>3240.29<NA>서울특별시 서대문구 홍은동 454번지서울특별시 서대문구 포방터10길 33 (홍은동, 극동아파트)03601홍은극동아파트 전동 지하주차장 지하1~4층2023-11-01 16:00:29U2022-11-01 00:03:00.0<NA>195591.551749455588.317097<NA><NA><NA><NA>