Overview

Dataset statistics

Number of variables17
Number of observations553
Missing cells940
Missing cells (%)10.0%
Duplicate rows45
Duplicate rows (%)8.1%
Total size in memory76.8 KiB
Average record size in memory142.2 B

Variable types

Categorical4
Numeric5
Text8

Dataset

Description시군구코드,처분일자,교부번호,업종명,업태명,업소명,소재지도로명,소재지지번,지도점검일자,행정처분상태,처분명,법적근거,위반일자,위반내용,처분내용,처분기간,영업장면적(㎡)
Author금천구
URLhttps://data.seoul.go.kr/dataList/OA-10143/S/1/datasetView.do

Alerts

시군구코드 has constant value ""Constant
행정처분상태 has constant value ""Constant
Dataset has 45 (8.1%) duplicate rowsDuplicates
처분일자 is highly overall correlated with 지도점검일자 and 1 other fieldsHigh correlation
지도점검일자 is highly overall correlated with 처분일자 and 1 other fieldsHigh correlation
위반일자 is highly overall correlated with 처분일자 and 1 other fieldsHigh correlation
업종명 is highly overall correlated with 업태명High correlation
업태명 is highly overall correlated with 업종명High correlation
교부번호 has 24 (4.3%) missing valuesMissing
소재지도로명 has 334 (60.4%) missing valuesMissing
처분기간 has 480 (86.8%) missing valuesMissing
영업장면적(㎡) has 102 (18.4%) missing valuesMissing
처분기간 has 31 (5.6%) zerosZeros
영업장면적(㎡) has 47 (8.5%) zerosZeros

Reproduction

Analysis started2024-05-11 05:57:40.093836
Analysis finished2024-05-11 05:57:48.022418
Duration7.93 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
3170000
553 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3170000
2nd row3170000
3rd row3170000
4th row3170000
5th row3170000

Common Values

ValueCountFrequency (%)
3170000 553
100.0%

Length

2024-05-11T14:57:48.473310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:57:48.636267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3170000 553
100.0%

처분일자
Real number (ℝ)

HIGH CORRELATION 

Distinct271
Distinct (%)49.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20118511
Minimum20020913
Maximum20240329
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.0 KiB
2024-05-11T14:57:48.842690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20020913
5-th percentile20040326
Q120080508
median20110429
Q320151022
95-th percentile20210104
Maximum20240329
Range219416
Interquartile range (IQR)70514

Descriptive statistics

Standard deviation51372.891
Coefficient of variation (CV)0.0025535136
Kurtosis-0.81205752
Mean20118511
Median Absolute Deviation (MAD)39821
Skewness0.2567331
Sum1.1125536 × 1010
Variance2.639174 × 109
MonotonicityNot monotonic
2024-05-11T14:57:49.116221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20150915 14
 
2.5%
20110201 12
 
2.2%
20150302 10
 
1.8%
20091231 10
 
1.8%
20140904 10
 
1.8%
20190430 9
 
1.6%
20181203 9
 
1.6%
20091030 8
 
1.4%
20220104 7
 
1.3%
20170516 7
 
1.3%
Other values (261) 457
82.6%
ValueCountFrequency (%)
20020913 1
0.2%
20021011 1
0.2%
20021213 1
0.2%
20030205 1
0.2%
20030311 1
0.2%
20030319 1
0.2%
20030430 2
0.4%
20030625 1
0.2%
20030704 1
0.2%
20030718 1
0.2%
ValueCountFrequency (%)
20240329 1
 
0.2%
20231204 2
 
0.4%
20230328 4
0.7%
20230314 1
 
0.2%
20230307 1
 
0.2%
20220405 4
0.7%
20220216 2
 
0.4%
20220104 7
1.3%
20211006 1
 
0.2%
20210803 1
 
0.2%

교부번호
Text

MISSING 

Distinct245
Distinct (%)46.3%
Missing24
Missing (%)4.3%
Memory size4.4 KiB
2024-05-11T14:57:49.745020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length4.3610586
Min length1

Characters and Unicode

Total characters2307
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique145 ?
Unique (%)27.4%

Sample

1st row20001
2nd row20001
3rd row20001
4th row20001
5th row20001
ValueCountFrequency (%)
62 17
 
3.2%
0007 17
 
3.2%
0060 13
 
2.5%
64 10
 
1.9%
199 8
 
1.5%
20084 7
 
1.3%
31 6
 
1.1%
67 6
 
1.1%
0154 6
 
1.1%
043 6
 
1.1%
Other values (235) 433
81.9%
2024-05-11T14:57:50.749980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 884
38.3%
2 285
 
12.4%
1 256
 
11.1%
3 152
 
6.6%
4 148
 
6.4%
6 117
 
5.1%
5 110
 
4.8%
7 94
 
4.1%
9 84
 
3.6%
8 73
 
3.2%
Other values (7) 104
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2203
95.5%
Dash Punctuation 60
 
2.6%
Other Letter 44
 
1.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 884
40.1%
2 285
 
12.9%
1 256
 
11.6%
3 152
 
6.9%
4 148
 
6.7%
6 117
 
5.3%
5 110
 
5.0%
7 94
 
4.3%
9 84
 
3.8%
8 73
 
3.3%
Other Letter
ValueCountFrequency (%)
미 11
25.0%
용 11
25.0%
피 9
20.5%
부 9
20.5%
일 2
 
4.5%
반 2
 
4.5%
Dash Punctuation
ValueCountFrequency (%)
- 60
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2263
98.1%
Hangul 44
 
1.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 884
39.1%
2 285
 
12.6%
1 256
 
11.3%
3 152
 
6.7%
4 148
 
6.5%
6 117
 
5.2%
5 110
 
4.9%
7 94
 
4.2%
9 84
 
3.7%
8 73
 
3.2%
Hangul
ValueCountFrequency (%)
미 11
25.0%
용 11
25.0%
피 9
20.5%
부 9
20.5%
일 2
 
4.5%
반 2
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2263
98.1%
Hangul 44
 
1.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 884
39.1%
2 285
 
12.6%
1 256
 
11.3%
3 152
 
6.7%
4 148
 
6.5%
6 117
 
5.2%
5 110
 
4.9%
7 94
 
4.2%
9 84
 
3.7%
8 73
 
3.2%
Hangul
ValueCountFrequency (%)
미 11
25.0%
용 11
25.0%
피 9
20.5%
부 9
20.5%
일 2
 
4.5%
반 2
 
4.5%

업종명
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
숙박업(일반)
153 
목욕장업
128 
이용업
99 
위생관리용역업
92 
세탁업
21 
Other values (11)
60 

Length

Max length23
Median length12
Mean length5.323689
Min length3

Unique

Unique5 ?
Unique (%)0.9%

Sample

1st row숙박업(일반)
2nd row숙박업(일반)
3rd row숙박업(일반)
4th row숙박업(일반)
5th row숙박업(일반)

Common Values

ValueCountFrequency (%)
숙박업(일반) 153
27.7%
목욕장업 128
23.1%
이용업 99
17.9%
위생관리용역업 92
16.6%
세탁업 21
 
3.8%
피부미용업 20
 
3.6%
미용업 19
 
3.4%
일반미용업 6
 
1.1%
피부미용업, 네일미용업 6
 
1.1%
네일미용업 2
 
0.4%
Other values (6) 7
 
1.3%

Length

2024-05-11T14:57:51.051771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
숙박업(일반 153
27.0%
목욕장업 128
22.6%
이용업 99
17.5%
위생관리용역업 92
16.2%
피부미용업 27
 
4.8%
미용업 22
 
3.9%
세탁업 21
 
3.7%
네일미용업 10
 
1.8%
일반미용업 9
 
1.6%
화장ㆍ분장 3
 
0.5%
Other values (3) 3
 
0.5%

업태명
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
여관업
110 
일반이용업
99 
위생관리용역업
92 
공동탕업+찜질시설서비스영업
64 
공동탕업
60 
Other values (11)
128 

Length

Max length14
Median length9
Mean length5.7992767
Min length3

Unique

Unique3 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
여관업 110
19.9%
일반이용업 99
17.9%
위생관리용역업 92
16.6%
공동탕업+찜질시설서비스영업 64
11.6%
공동탕업 60
10.8%
여인숙업 39
 
7.1%
일반미용업 25
 
4.5%
피부미용업 23
 
4.2%
일반세탁업 18
 
3.3%
네일아트업 9
 
1.6%
Other values (6) 14
 
2.5%

Length

2024-05-11T14:57:51.292520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
여관업 110
19.8%
일반이용업 99
17.8%
위생관리용역업 92
16.5%
공동탕업+찜질시설서비스영업 64
11.5%
공동탕업 60
10.8%
여인숙업 39
 
7.0%
일반미용업 25
 
4.5%
피부미용업 23
 
4.1%
일반세탁업 18
 
3.2%
네일아트업 9
 
1.6%
Other values (7) 17
 
3.1%

업소명
Text

Distinct258
Distinct (%)46.7%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
2024-05-11T14:57:51.715459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length4.9475588
Min length2

Characters and Unicode

Total characters2736
Distinct characters274
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique145 ?
Unique (%)26.2%

Sample

1st row서울여인숙
2nd row서울여인숙
3rd row서울여인숙
4th row서울여인숙
5th row서울여인숙
ValueCountFrequency (%)
약수탕 17
 
2.9%
천지랜드 12
 
2.0%
주식회사 11
 
1.9%
중앙사우나 10
 
1.7%
사우나 10
 
1.7%
대명 8
 
1.4%
카멜리아불한증막사우나 8
 
1.4%
카멜리아 8
 
1.4%
삼성 8
 
1.4%
동원장 7
 
1.2%
Other values (261) 492
83.2%
2024-05-11T14:57:52.472425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 85
 
3.1%
주 72
 
2.6%
나 69
 
2.5%
장 66
 
2.4%
( 64
 
2.3%
) 64
 
2.3%
우 64
 
2.3%
리 56
 
2.0%
성 49
 
1.8%
한 49
 
1.8%
Other values (264) 2098
76.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2532
92.5%
Open Punctuation 64
 
2.3%
Close Punctuation 64
 
2.3%
Space Separator 38
 
1.4%
Decimal Number 16
 
0.6%
Uppercase Letter 13
 
0.5%
Dash Punctuation 6
 
0.2%
Other Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 85
 
3.4%
주 72
 
2.8%
나 69
 
2.7%
장 66
 
2.6%
우 64
 
2.5%
리 56
 
2.2%
성 49
 
1.9%
한 49
 
1.9%
모 48
 
1.9%
수 48
 
1.9%
Other values (245) 1926
76.1%
Uppercase Letter
ValueCountFrequency (%)
I 3
23.1%
N 2
15.4%
M 2
15.4%
Q 1
 
7.7%
A 1
 
7.7%
L 1
 
7.7%
T 1
 
7.7%
H 1
 
7.7%
D 1
 
7.7%
Decimal Number
ValueCountFrequency (%)
2 7
43.8%
4 5
31.2%
7 2
 
12.5%
3 2
 
12.5%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
？ 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 64
100.0%
Close Punctuation
ValueCountFrequency (%)
) 64
100.0%
Space Separator
ValueCountFrequency (%)
38
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2532
92.5%
Common 191
 
7.0%
Latin 13
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 85
 
3.4%
주 72
 
2.8%
나 69
 
2.7%
장 66
 
2.6%
우 64
 
2.5%
리 56
 
2.2%
성 49
 
1.9%
한 49
 
1.9%
모 48
 
1.9%
수 48
 
1.9%
Other values (245) 1926
76.1%
Common
ValueCountFrequency (%)
( 64
33.5%
) 64
33.5%
38
19.9%
2 7
 
3.7%
- 6
 
3.1%
4 5
 
2.6%
7 2
 
1.0%
. 2
 
1.0%
3 2
 
1.0%
？ 1
 
0.5%
Latin
ValueCountFrequency (%)
I 3
23.1%
N 2
15.4%
M 2
15.4%
Q 1
 
7.7%
A 1
 
7.7%
L 1
 
7.7%
T 1
 
7.7%
H 1
 
7.7%
D 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2532
92.5%
ASCII 203
 
7.4%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 85
 
3.4%
주 72
 
2.8%
나 69
 
2.7%
장 66
 
2.6%
우 64
 
2.5%
리 56
 
2.2%
성 49
 
1.9%
한 49
 
1.9%
모 48
 
1.9%
수 48
 
1.9%
Other values (245) 1926
76.1%
ASCII
ValueCountFrequency (%)
( 64
31.5%
) 64
31.5%
38
18.7%
2 7
 
3.4%
- 6
 
3.0%
4 5
 
2.5%
I 3
 
1.5%
N 2
 
1.0%
M 2
 
1.0%
7 2
 
1.0%
Other values (8) 10
 
4.9%
None
ValueCountFrequency (%)
？ 1
100.0%

소재지도로명
Text

MISSING 

Distinct137
Distinct (%)62.6%
Missing334
Missing (%)60.4%
Memory size4.4 KiB
2024-05-11T14:57:52.926500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length43
Mean length31.643836
Min length23

Characters and Unicode

Total characters6930
Distinct characters162
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

Unique103 ?
Unique (%)47.0%

Sample

1st row서울특별시 금천구 시흥대로54길 43, (시흥동)
2nd row서울특별시 금천구 시흥대로54길 43, (시흥동)
3rd row서울특별시 금천구 시흥대로62길 18-4, (시흥동,[현대시장길 93-5])
4th row서울특별시 금천구 시흥대로62길 18-4, (시흥동,[현대시장길 93-5])
5th row서울특별시 금천구 남부순환로108길 6, (가산동,[백년길 6])
ValueCountFrequency (%)
서울특별시 219
 
16.8%
금천구 219
 
16.8%
독산동 78
 
6.0%
시흥동 61
 
4.7%
가산동 39
 
3.0%
시흥대로 35
 
2.7%
독산로 22
 
1.7%
97 18
 
1.4%
시흥대로50길 17
 
1.3%
12-5 17
 
1.3%
Other values (272) 579
44.4%
2024-05-11T14:57:53.542096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1085
 
15.7%
시 407
 
5.9%
, 304
 
4.4%
1 252
 
3.6%
동 247
 
3.6%
금 237
 
3.4%
서 223
 
3.2%
천 222
 
3.2%
구 221
 
3.2%
로 221
 
3.2%
Other values (152) 3511
50.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3912
56.5%
Space Separator 1085
 
15.7%
Decimal Number 1074
 
15.5%
Other Punctuation 304
 
4.4%
Close Punctuation 251
 
3.6%
Open Punctuation 251
 
3.6%
Dash Punctuation 37
 
0.5%
Uppercase Letter 16
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 407
 
10.4%
동 247
 
6.3%
금 237
 
6.1%
서 223
 
5.7%
천 222
 
5.7%
구 221
 
5.6%
로 221
 
5.6%
울 221
 
5.6%
특 219
 
5.6%
별 219
 
5.6%
Other values (126) 1475
37.7%
Decimal Number
ValueCountFrequency (%)
1 252
23.5%
2 166
15.5%
3 123
11.5%
5 108
10.1%
0 106
9.9%
9 83
 
7.7%
4 64
 
6.0%
7 59
 
5.5%
6 59
 
5.5%
8 54
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
B 5
31.2%
A 3
18.8%
T 2
 
12.5%
I 1
 
6.2%
Y 1
 
6.2%
K 1
 
6.2%
E 1
 
6.2%
X 1
 
6.2%
F 1
 
6.2%
Close Punctuation
ValueCountFrequency (%)
) 220
87.6%
] 31
 
12.4%
Open Punctuation
ValueCountFrequency (%)
( 220
87.6%
[ 31
 
12.4%
Space Separator
ValueCountFrequency (%)
1085
100.0%
Other Punctuation
ValueCountFrequency (%)
, 304
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 37
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3912
56.5%
Common 3002
43.3%
Latin 16
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 407
 
10.4%
동 247
 
6.3%
금 237
 
6.1%
서 223
 
5.7%
천 222
 
5.7%
구 221
 
5.6%
로 221
 
5.6%
울 221
 
5.6%
특 219
 
5.6%
별 219
 
5.6%
Other values (126) 1475
37.7%
Common
ValueCountFrequency (%)
1085
36.1%
, 304
 
10.1%
1 252
 
8.4%
) 220
 
7.3%
( 220
 
7.3%
2 166
 
5.5%
3 123
 
4.1%
5 108
 
3.6%
0 106
 
3.5%
9 83
 
2.8%
Other values (7) 335
 
11.2%
Latin
ValueCountFrequency (%)
B 5
31.2%
A 3
18.8%
T 2
 
12.5%
I 1
 
6.2%
Y 1
 
6.2%
K 1
 
6.2%
E 1
 
6.2%
X 1
 
6.2%
F 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3912
56.5%
ASCII 3018
43.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1085
36.0%
, 304
 
10.1%
1 252
 
8.3%
) 220
 
7.3%
( 220
 
7.3%
2 166
 
5.5%
3 123
 
4.1%
5 108
 
3.6%
0 106
 
3.5%
9 83
 
2.8%
Other values (16) 351
 
11.6%
Hangul
ValueCountFrequency (%)
시 407
 
10.4%
동 247
 
6.3%
금 237
 
6.1%
서 223
 
5.7%
천 222
 
5.7%
구 221
 
5.6%
로 221
 
5.6%
울 221
 
5.6%
특 219
 
5.6%
별 219
 
5.6%
Other values (126) 1475
37.7%

소재지지번
Text

Distinct292
Distinct (%)52.8%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
2024-05-11T14:57:53.982009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length46
Mean length31.965642
Min length22

Characters and Unicode

Total characters17677
Distinct characters181
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique180 ?
Unique (%)32.5%

Sample

1st row서울특별시 금천구 시흥동 883번지 2호 [시흥대로 455]
2nd row서울특별시 금천구 시흥동 883번지 2호 [시흥대로 455]
3rd row서울특별시 금천구 시흥동 883번지 2호 [시흥대로 455]
4th row서울특별시 금천구 시흥동 883번지 2호 [시흥대로 455]
5th row서울특별시 금천구 시흥동 883번지 2호 [시흥대로 455]
ValueCountFrequency (%)
금천구 556
 
16.4%
서울특별시 553
 
16.3%
시흥동 237
 
7.0%
독산동 212
 
6.3%
가산동 104
 
3.1%
시흥대로 52
 
1.5%
984번지 43
 
1.3%
1호 41
 
1.2%
독산동길 32
 
0.9%
901번지 26
 
0.8%
Other values (420) 1527
45.1%
2024-05-11T14:57:54.715633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4113
23.3%
시 894
 
5.1%
1 744
 
4.2%
동 601
 
3.4%
지 591
 
3.3%
금 567
 
3.2%
구 567
 
3.2%
천 566
 
3.2%
울 555
 
3.1%
서 554
 
3.1%
Other values (171) 7925
44.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9428
53.3%
Space Separator 4113
23.3%
Decimal Number 3514
 
19.9%
Close Punctuation 228
 
1.3%
Open Punctuation 228
 
1.3%
Dash Punctuation 103
 
0.6%
Other Punctuation 32
 
0.2%
Uppercase Letter 31
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 894
 
9.5%
동 601
 
6.4%
지 591
 
6.3%
금 567
 
6.0%
구 567
 
6.0%
천 566
 
6.0%
울 555
 
5.9%
서 554
 
5.9%
별 553
 
5.9%
특 553
 
5.9%
Other values (146) 3427
36.3%
Decimal Number
ValueCountFrequency (%)
1 744
21.2%
2 451
12.8%
3 422
12.0%
9 368
10.5%
0 365
10.4%
4 303
8.6%
5 276
 
7.9%
8 263
 
7.5%
6 176
 
5.0%
7 146
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
B 19
61.3%
A 3
 
9.7%
F 3
 
9.7%
T 3
 
9.7%
K 2
 
6.5%
I 1
 
3.2%
Close Punctuation
ValueCountFrequency (%)
] 201
88.2%
) 23
 
10.1%
］ 4
 
1.8%
Open Punctuation
ValueCountFrequency (%)
[ 201
88.2%
( 23
 
10.1%
［ 4
 
1.8%
Space Separator
ValueCountFrequency (%)
4113
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 103
100.0%
Other Punctuation
ValueCountFrequency (%)
, 32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9428
53.3%
Common 8218
46.5%
Latin 31
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 894
 
9.5%
동 601
 
6.4%
지 591
 
6.3%
금 567
 
6.0%
구 567
 
6.0%
천 566
 
6.0%
울 555
 
5.9%
서 554
 
5.9%
별 553
 
5.9%
특 553
 
5.9%
Other values (146) 3427
36.3%
Common
ValueCountFrequency (%)
4113
50.0%
1 744
 
9.1%
2 451
 
5.5%
3 422
 
5.1%
9 368
 
4.5%
0 365
 
4.4%
4 303
 
3.7%
5 276
 
3.4%
8 263
 
3.2%
] 201
 
2.4%
Other values (9) 712
 
8.7%
Latin
ValueCountFrequency (%)
B 19
61.3%
A 3
 
9.7%
F 3
 
9.7%
T 3
 
9.7%
K 2
 
6.5%
I 1
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9428
53.3%
ASCII 8241
46.6%
None 8
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4113
49.9%
1 744
 
9.0%
2 451
 
5.5%
3 422
 
5.1%
9 368
 
4.5%
0 365
 
4.4%
4 303
 
3.7%
5 276
 
3.3%
8 263
 
3.2%
] 201
 
2.4%
Other values (13) 735
 
8.9%
Hangul
ValueCountFrequency (%)
시 894
 
9.5%
동 601
 
6.4%
지 591
 
6.3%
금 567
 
6.0%
구 567
 
6.0%
천 566
 
6.0%
울 555
 
5.9%
서 554
 
5.9%
별 553
 
5.9%
특 553
 
5.9%
Other values (146) 3427
36.3%
None
ValueCountFrequency (%)
［ 4
50.0%
］ 4
50.0%

지도점검일자
Real number (ℝ)

HIGH CORRELATION 

Distinct276
Distinct (%)49.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20116545
Minimum20020616
Maximum20240222
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.0 KiB
2024-05-11T14:57:54.949637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20020616
5-th percentile20040225
Q120080311
median20110107
Q320150903
95-th percentile20201208
Maximum20240222
Range219606
Interquartile range (IQR)70592

Descriptive statistics

Standard deviation51164.526
Coefficient of variation (CV)0.0025434052
Kurtosis-0.83749518
Mean20116545
Median Absolute Deviation (MAD)39593
Skewness0.24807451
Sum1.1124449 × 1010
Variance2.6178087 × 109
MonotonicityNot monotonic
2024-05-11T14:57:55.207946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20150813 19
 
3.4%
20141015 16
 
2.9%
20140801 16
 
2.9%
20110107 12
 
2.2%
20170324 10
 
1.8%
20180307 10
 
1.8%
20091125 10
 
1.8%
20181028 9
 
1.6%
20090929 8
 
1.4%
20090604 7
 
1.3%
Other values (266) 436
78.8%
ValueCountFrequency (%)
20020616 1
0.2%
20020830 1
0.2%
20021117 1
0.2%
20021203 1
0.2%
20021205 1
0.2%
20030113 1
0.2%
20030320 1
0.2%
20030325 1
0.2%
20030413 2
0.4%
20030526 1
0.2%
ValueCountFrequency (%)
20240222 1
 
0.2%
20230803 2
0.4%
20230213 1
 
0.2%
20230113 1
 
0.2%
20221231 4
0.7%
20220303 1
 
0.2%
20220302 2
0.4%
20220228 1
 
0.2%
20220106 2
0.4%
20211215 3
0.5%

행정처분상태
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
처분확정
553 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
처분확정 553
100.0%

Length

2024-05-11T14:57:55.373329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:57:55.480609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
처분확정 553
100.0%

처분명
Text

Distinct130
Distinct (%)23.5%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
2024-05-11T14:57:55.709789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length40
Mean length9.0940325
Min length2

Characters and Unicode

Total characters5029
Distinct characters150
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)13.4%

Sample

1st row과징금부과(영업정지1월갈음)
2nd row영업정지를 갈음하여 과징금(900,000원)부과
3rd row불문처분
4th row영업소 폐쇄명령
5th row영업소폐쇄(청소년보호법(3차)위반 포함)
ValueCountFrequency (%)
개선명령 105
 
11.7%
경고 93
 
10.4%
과태료부과 78
 
8.7%
영업정지 65
 
7.2%
과징금부과 40
 
4.5%
갈음 37
 
4.1%
영업소폐쇄 30
 
3.3%
및 27
 
3.0%
부과 23
 
2.6%
과징금 22
 
2.4%
Other values (158) 378
42.1%
2024-05-11T14:57:56.190585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 504
 
10.0%
349
 
6.9%
0 339
 
6.7%
부 246
 
4.9%
료 167
 
3.3%
태 165
 
3.3%
업 154
 
3.1%
영 151
 
3.0%
2 138
 
2.7%
개 137
 
2.7%
Other values (140) 2679
53.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3489
69.4%
Decimal Number 757
 
15.1%
Space Separator 349
 
6.9%
Other Punctuation 151
 
3.0%
Close Punctuation 131
 
2.6%
Open Punctuation 131
 
2.6%
Math Symbol 19
 
0.4%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 504
 
14.4%
부 246
 
7.1%
료 167
 
4.8%
태 165
 
4.7%
업 154
 
4.4%
영 151
 
4.3%
개 137
 
3.9%
지 133
 
3.8%
선 129
 
3.7%
령 128
 
3.7%
Other values (119) 1575
45.1%
Decimal Number
ValueCountFrequency (%)
0 339
44.8%
2 138
18.2%
1 114
 
15.1%
5 33
 
4.4%
8 32
 
4.2%
6 28
 
3.7%
3 28
 
3.7%
7 17
 
2.2%
9 15
 
2.0%
4 13
 
1.7%
Other Punctuation
ValueCountFrequency (%)
, 105
69.5%
. 40
 
26.5%
: 5
 
3.3%
/ 1
 
0.7%
Math Symbol
ValueCountFrequency (%)
~ 9
47.4%
< 5
26.3%
> 5
26.3%
Space Separator
ValueCountFrequency (%)
349
100.0%
Close Punctuation
ValueCountFrequency (%)
) 131
100.0%
Open Punctuation
ValueCountFrequency (%)
( 131
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3489
69.4%
Common 1540
30.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 504
 
14.4%
부 246
 
7.1%
료 167
 
4.8%
태 165
 
4.7%
업 154
 
4.4%
영 151
 
4.3%
개 137
 
3.9%
지 133
 
3.8%
선 129
 
3.7%
령 128
 
3.7%
Other values (119) 1575
45.1%
Common
ValueCountFrequency (%)
349
22.7%
0 339
22.0%
2 138
 
9.0%
) 131
 
8.5%
( 131
 
8.5%
1 114
 
7.4%
, 105
 
6.8%
. 40
 
2.6%
5 33
 
2.1%
8 32
 
2.1%
Other values (11) 128
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3489
69.4%
ASCII 1540
30.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 504
 
14.4%
부 246
 
7.1%
료 167
 
4.8%
태 165
 
4.7%
업 154
 
4.4%
영 151
 
4.3%
개 137
 
3.9%
지 133
 
3.8%
선 129
 
3.7%
령 128
 
3.7%
Other values (119) 1575
45.1%
ASCII
ValueCountFrequency (%)
349
22.7%
0 339
22.0%
2 138
 
9.0%
) 131
 
8.5%
( 131
 
8.5%
1 114
 
7.4%
, 105
 
6.8%
. 40
 
2.6%
5 33
 
2.1%
8 32
 
2.1%
Other values (11) 128
 
8.3%

법적근거
Text

Distinct131
Distinct (%)23.7%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
2024-05-11T14:57:56.521227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length37
Mean length15.079566
Min length6

Characters and Unicode

Total characters8339
Distinct characters76
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique67 ?
Unique (%)12.1%

Sample

1st row공중위생관리법 제11조
2nd row공중위생관리법제11조및 같은법시행규칙제19조
3rd row공중위생관리법제11조및 같은법시행규칙제19조
4th row공중위생관리법제11조,공중위생관리법시행규칙제19조
5th row공중위생관리법제11조, 같은법시행규칙제19조
ValueCountFrequency (%)
공중위생관리법 297
21.3%
법 144
 
10.3%
제17조 92
 
6.6%
제11조 67
 
4.8%
및 66
 
4.7%
제11조제1항 59
 
4.2%
제19조 50
 
3.6%
제4조제2항 46
 
3.3%
시행규칙 33
 
2.4%
공중위생법 31
 
2.2%
Other values (99) 510
36.6%
2024-05-11T14:57:56.951745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
제 1067
12.8%
854
 
10.2%
1 798
 
9.6%
조 642
 
7.7%
법 626
 
7.5%
위 413
 
5.0%
공 398
 
4.8%
생 398
 
4.8%
중 398
 
4.8%
관 383
 
4.6%
Other values (66) 2362
28.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5870
70.4%
Decimal Number 1561
 
18.7%
Space Separator 854
 
10.2%
Other Punctuation 34
 
0.4%
Open Punctuation 10
 
0.1%
Close Punctuation 9
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 1067
18.2%
조 642
10.9%
법 626
10.7%
위 413
 
7.0%
공 398
 
6.8%
생 398
 
6.8%
중 398
 
6.8%
관 383
 
6.5%
항 377
 
6.4%
리 368
 
6.3%
Other values (46) 800
13.6%
Decimal Number
ValueCountFrequency (%)
1 798
51.1%
2 224
 
14.3%
7 162
 
10.4%
4 144
 
9.2%
3 104
 
6.7%
9 72
 
4.6%
6 23
 
1.5%
0 16
 
1.0%
5 11
 
0.7%
8 7
 
0.4%
Open Punctuation
ValueCountFrequency (%)
「 7
70.0%
[ 2
 
20.0%
( 1
 
10.0%
Close Punctuation
ValueCountFrequency (%)
」 7
77.8%
] 1
 
11.1%
) 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
, 33
97.1%
. 1
 
2.9%
Space Separator
ValueCountFrequency (%)
854
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5870
70.4%
Common 2469
29.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 1067
18.2%
조 642
10.9%
법 626
10.7%
위 413
 
7.0%
공 398
 
6.8%
생 398
 
6.8%
중 398
 
6.8%
관 383
 
6.5%
항 377
 
6.4%
리 368
 
6.3%
Other values (46) 800
13.6%
Common
ValueCountFrequency (%)
854
34.6%
1 798
32.3%
2 224
 
9.1%
7 162
 
6.6%
4 144
 
5.8%
3 104
 
4.2%
9 72
 
2.9%
, 33
 
1.3%
6 23
 
0.9%
0 16
 
0.6%
Other values (10) 39
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5870
70.4%
ASCII 2455
29.4%
None 14
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
제 1067
18.2%
조 642
10.9%
법 626
10.7%
위 413
 
7.0%
공 398
 
6.8%
생 398
 
6.8%
중 398
 
6.8%
관 383
 
6.5%
항 377
 
6.4%
리 368
 
6.3%
Other values (46) 800
13.6%
ASCII
ValueCountFrequency (%)
854
34.8%
1 798
32.5%
2 224
 
9.1%
7 162
 
6.6%
4 144
 
5.9%
3 104
 
4.2%
9 72
 
2.9%
, 33
 
1.3%
6 23
 
0.9%
0 16
 
0.7%
Other values (8) 25
 
1.0%
None
ValueCountFrequency (%)
「 7
50.0%
」 7
50.0%

위반일자
Real number (ℝ)

HIGH CORRELATION 

Distinct274
Distinct (%)49.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20116441
Minimum20020616
Maximum20240222
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.0 KiB
2024-05-11T14:57:57.112612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20020616
5-th percentile20040217
Q120080316
median20110107
Q320150824
95-th percentile20201213
Maximum20240222
Range219606
Interquartile range (IQR)70508

Descriptive statistics

Standard deviation51131.431
Coefficient of variation (CV)0.0025417733
Kurtosis-0.84602412
Mean20116441
Median Absolute Deviation (MAD)39582
Skewness0.24380762
Sum1.1124392 × 1010
Variance2.6144232 × 109
MonotonicityNot monotonic
2024-05-11T14:57:57.269461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20140811 20
 
3.6%
20150813 17
 
3.1%
20141222 12
 
2.2%
20091126 11
 
2.0%
20190305 10
 
1.8%
20181028 9
 
1.6%
20090604 9
 
1.6%
20170327 9
 
1.6%
20180307 9
 
1.6%
20090929 8
 
1.4%
Other values (264) 439
79.4%
ValueCountFrequency (%)
20020616 1
0.2%
20020830 1
0.2%
20021117 1
0.2%
20021205 1
0.2%
20021221 1
0.2%
20030113 1
0.2%
20030320 1
0.2%
20030325 1
0.2%
20030413 2
0.4%
20030526 1
0.2%
ValueCountFrequency (%)
20240222 1
 
0.2%
20230803 2
0.4%
20230220 1
 
0.2%
20230213 1
 
0.2%
20221231 4
0.7%
20220228 4
0.7%
20220104 2
0.4%
20211215 2
0.4%
20210730 2
0.4%
20210701 1
 
0.2%

위반내용
Text

Distinct305
Distinct (%)55.2%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
2024-05-11T14:57:57.528375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length184
Median length110
Mean length39.685353
Min length5

Characters and Unicode

Total characters21946
Distinct characters328
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

Unique209 ?
Unique (%)37.8%

Sample

1st row2009.02.27 02:00경부터 같은날 13:00경까지 청소년보호법을 위반한 사실이(청소년 이성혼숙 허용) 서울금천경찰서 형사과-1857(2009.03.06)호로 적발, 통보됨.
2nd row2009.12.13. 06:00경 청소년보호법을 위반한 사실이(청소년 이성혼숙 허용) 서울금천경찰서형사과-12453(09.12.31)호로 적발,통보됨
3rd row2010.03.04. 02:00경 청소년보호법을 위반하여 서울금천경찰서 수사과-1659(2010. 03.08)호로 적발,통보됨
4th row2010.04.21. 02:10경 청소년보호법을 위반한사실(청소년 이성혼숙의 장소를 제공)이 서울금천경찰서 수사과-3912(2010.05.27)호로 적발,통보됨
5th row2010.02월 초순경부터2010.06.20경까지 이곳을 찾아오는 불상의 손님들을 상대로 성매매를 하도록 장소를 제공 및 알선한 사실이 서울금천경찰서 생활안전과-6736(2010.08.23)호로 적발,통보됨.
ValueCountFrequency (%)
위생교육 118
 
3.2%
사실이 90
 
2.5%
미이수 66
 
1.8%
통보됨 60
 
1.6%
서울금천경찰서 59
 
1.6%
적발 50
 
1.4%
이성혼숙 49
 
1.3%
욕조수 46
 
1.3%
위반 43
 
1.2%
미수료 42
 
1.2%
Other values (965) 3020
82.9%
2024-05-11T14:57:57.953602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3158
 
14.4%
0 1179
 
5.4%
2 726
 
3.3%
. 669
 
3.0%
1 584
 
2.7%
위 565
 
2.6%
이 422
 
1.9%
생 330
 
1.5%
수 328
 
1.5%
) 324
 
1.5%
Other values (318) 13661
62.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13278
60.5%
Decimal Number 3695
 
16.8%
Space Separator 3158
 
14.4%
Other Punctuation 923
 
4.2%
Close Punctuation 332
 
1.5%
Open Punctuation 332
 
1.5%
Dash Punctuation 183
 
0.8%
Uppercase Letter 26
 
0.1%
Lowercase Letter 13
 
0.1%
Math Symbol 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
위 565
 
4.3%
이 422
 
3.2%
생 330
 
2.5%
수 328
 
2.5%
사 275
 
2.1%
소 251
 
1.9%
년 238
 
1.8%
미 224
 
1.7%
서 222
 
1.7%
업 218
 
1.6%
Other values (288) 10205
76.9%
Decimal Number
ValueCountFrequency (%)
0 1179
31.9%
2 726
19.6%
1 584
15.8%
9 223
 
6.0%
3 208
 
5.6%
7 184
 
5.0%
6 155
 
4.2%
5 149
 
4.0%
8 146
 
4.0%
4 141
 
3.8%
Other Punctuation
ValueCountFrequency (%)
. 669
72.5%
, 128
 
13.9%
: 116
 
12.6%
/ 8
 
0.9%
; 1
 
0.1%
% 1
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
O 10
38.5%
U 5
19.2%
N 5
19.2%
T 5
19.2%
L 1
 
3.8%
Close Punctuation
ValueCountFrequency (%)
) 324
97.6%
] 8
 
2.4%
Open Punctuation
ValueCountFrequency (%)
( 324
97.6%
[ 8
 
2.4%
Lowercase Letter
ValueCountFrequency (%)
o 12
92.3%
m 1
 
7.7%
Space Separator
ValueCountFrequency (%)
3158
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 183
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13278
60.5%
Common 8629
39.3%
Latin 39
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
위 565
 
4.3%
이 422
 
3.2%
생 330
 
2.5%
수 328
 
2.5%
사 275
 
2.1%
소 251
 
1.9%
년 238
 
1.8%
미 224
 
1.7%
서 222
 
1.7%
업 218
 
1.6%
Other values (288) 10205
76.9%
Common
ValueCountFrequency (%)
3158
36.6%
0 1179
 
13.7%
2 726
 
8.4%
. 669
 
7.8%
1 584
 
6.8%
) 324
 
3.8%
( 324
 
3.8%
9 223
 
2.6%
3 208
 
2.4%
7 184
 
2.1%
Other values (13) 1050
 
12.2%
Latin
ValueCountFrequency (%)
o 12
30.8%
O 10
25.6%
U 5
12.8%
N 5
12.8%
T 5
12.8%
m 1
 
2.6%
L 1
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13278
60.5%
ASCII 8668
39.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3158
36.4%
0 1179
 
13.6%
2 726
 
8.4%
. 669
 
7.7%
1 584
 
6.7%
) 324
 
3.7%
( 324
 
3.7%
9 223
 
2.6%
3 208
 
2.4%
7 184
 
2.1%
Other values (20) 1089
 
12.6%
Hangul
ValueCountFrequency (%)
위 565
 
4.3%
이 422
 
3.2%
생 330
 
2.5%
수 328
 
2.5%
사 275
 
2.1%
소 251
 
1.9%
년 238
 
1.8%
미 224
 
1.7%
서 222
 
1.7%
업 218
 
1.6%
Other values (288) 10205
76.9%

처분내용
Text

Distinct130
Distinct (%)23.5%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
2024-05-11T14:57:58.187540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length40
Mean length9.0940325
Min length2

Characters and Unicode

Total characters5029
Distinct characters150
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)13.4%

Sample

1st row과징금부과(영업정지1월갈음)
2nd row영업정지를 갈음하여 과징금(900,000원)부과
3rd row불문처분
4th row영업소 폐쇄명령
5th row영업소폐쇄(청소년보호법(3차)위반 포함)
ValueCountFrequency (%)
개선명령 105
 
11.7%
경고 93
 
10.4%
과태료부과 78
 
8.7%
영업정지 65
 
7.2%
과징금부과 40
 
4.5%
갈음 37
 
4.1%
영업소폐쇄 30
 
3.3%
및 27
 
3.0%
부과 23
 
2.6%
과징금 22
 
2.4%
Other values (158) 378
42.1%
2024-05-11T14:57:58.618562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 504
 
10.0%
349
 
6.9%
0 339
 
6.7%
부 246
 
4.9%
료 167
 
3.3%
태 165
 
3.3%
업 154
 
3.1%
영 151
 
3.0%
2 138
 
2.7%
개 137
 
2.7%
Other values (140) 2679
53.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3489
69.4%
Decimal Number 757
 
15.1%
Space Separator 349
 
6.9%
Other Punctuation 151
 
3.0%
Close Punctuation 131
 
2.6%
Open Punctuation 131
 
2.6%
Math Symbol 19
 
0.4%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 504
 
14.4%
부 246
 
7.1%
료 167
 
4.8%
태 165
 
4.7%
업 154
 
4.4%
영 151
 
4.3%
개 137
 
3.9%
지 133
 
3.8%
선 129
 
3.7%
령 128
 
3.7%
Other values (119) 1575
45.1%
Decimal Number
ValueCountFrequency (%)
0 339
44.8%
2 138
18.2%
1 114
 
15.1%
5 33
 
4.4%
8 32
 
4.2%
6 28
 
3.7%
3 28
 
3.7%
7 17
 
2.2%
9 15
 
2.0%
4 13
 
1.7%
Other Punctuation
ValueCountFrequency (%)
, 105
69.5%
. 40
 
26.5%
: 5
 
3.3%
/ 1
 
0.7%
Math Symbol
ValueCountFrequency (%)
~ 9
47.4%
< 5
26.3%
> 5
26.3%
Space Separator
ValueCountFrequency (%)
349
100.0%
Close Punctuation
ValueCountFrequency (%)
) 131
100.0%
Open Punctuation
ValueCountFrequency (%)
( 131
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3489
69.4%
Common 1540
30.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 504
 
14.4%
부 246
 
7.1%
료 167
 
4.8%
태 165
 
4.7%
업 154
 
4.4%
영 151
 
4.3%
개 137
 
3.9%
지 133
 
3.8%
선 129
 
3.7%
령 128
 
3.7%
Other values (119) 1575
45.1%
Common
ValueCountFrequency (%)
349
22.7%
0 339
22.0%
2 138
 
9.0%
) 131
 
8.5%
( 131
 
8.5%
1 114
 
7.4%
, 105
 
6.8%
. 40
 
2.6%
5 33
 
2.1%
8 32
 
2.1%
Other values (11) 128
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3489
69.4%
ASCII 1540
30.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 504
 
14.4%
부 246
 
7.1%
료 167
 
4.8%
태 165
 
4.7%
업 154
 
4.4%
영 151
 
4.3%
개 137
 
3.9%
지 133
 
3.8%
선 129
 
3.7%
령 128
 
3.7%
Other values (119) 1575
45.1%
ASCII
ValueCountFrequency (%)
349
22.7%
0 339
22.0%
2 138
 
9.0%
) 131
 
8.5%
( 131
 
8.5%
1 114
 
7.4%
, 105
 
6.8%
. 40
 
2.6%
5 33
 
2.1%
8 32
 
2.1%
Other values (11) 128
 
8.3%

처분기간
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)16.4%
Missing480
Missing (%)86.8%
Infinite0
Infinite (%)0.0%
Mean8.9452055
Minimum0
Maximum61
Zeros31
Zeros (%)5.6%
Negative0
Negative (%)0.0%
Memory size5.0 KiB
2024-05-11T14:57:58.776431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median9
Q315
95-th percentile32
Maximum61
Range61
Interquartile range (IQR)15

Descriptive statistics

Standard deviation11.079123
Coefficient of variation (CV)1.2385543
Kurtosis5.9231247
Mean8.9452055
Median Absolute Deviation (MAD)9
Skewness1.9806188
Sum653
Variance122.74696
MonotonicityNot monotonic
2024-05-11T14:57:58.942906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 31
 
5.6%
10 12
 
2.2%
15 10
 
1.8%
9 5
 
0.9%
32 4
 
0.7%
16 3
 
0.5%
5 3
 
0.5%
23 1
 
0.2%
25 1
 
0.2%
31 1
 
0.2%
Other values (2) 2
 
0.4%
(Missing) 480
86.8%
ValueCountFrequency (%)
0 31
5.6%
5 3
 
0.5%
7 1
 
0.2%
9 5
 
0.9%
10 12
 
2.2%
15 10
 
1.8%
16 3
 
0.5%
23 1
 
0.2%
25 1
 
0.2%
31 1
 
0.2%
ValueCountFrequency (%)
61 1
 
0.2%
32 4
 
0.7%
31 1
 
0.2%
25 1
 
0.2%
23 1
 
0.2%
16 3
 
0.5%
15 10
1.8%
10 12
2.2%
9 5
0.9%
7 1
 
0.2%

영업장면적(㎡)
Real number (ℝ)

MISSING  ZEROS 

Distinct157
Distinct (%)34.8%
Missing102
Missing (%)18.4%
Infinite0
Infinite (%)0.0%
Mean4792.8291
Minimum0
Maximum121198
Zeros47
Zeros (%)8.5%
Negative0
Negative (%)0.0%
Memory size5.0 KiB
2024-05-11T14:57:59.176837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q125.775
median72.76
Q3518.58
95-th percentile4946.03
Maximum121198
Range121198
Interquartile range (IQR)492.805

Descriptive statistics

Standard deviation22373.459
Coefficient of variation (CV)4.6681111
Kurtosis23.384592
Mean4792.8291
Median Absolute Deviation (MAD)72.76
Skewness5.0221246
Sum2161565.9
Variance5.0057165 × 108
MonotonicityNot monotonic
2024-05-11T14:57:59.342690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 47
 
8.5%
244.42 17
 
3.1%
121198.0 16
 
2.9%
4946.03 12
 
2.2%
1173.68 10
 
1.8%
72.76 8
 
1.4%
66.0 8
 
1.4%
2121.7 7
 
1.3%
72.0 7
 
1.3%
82.5 6
 
1.1%
Other values (147) 313
56.6%
(Missing) 102
 
18.4%
ValueCountFrequency (%)
0.0 47
8.5%
12.31 5
 
0.9%
14.0 2
 
0.4%
14.2 6
 
1.1%
14.57 2
 
0.4%
15.0 1
 
0.2%
15.86 1
 
0.2%
16.2 4
 
0.7%
16.52 1
 
0.2%
17.19 2
 
0.4%
ValueCountFrequency (%)
121198.0 16
2.9%
6202.74 1
 
0.2%
4946.03 12
2.2%
4335.26 1
 
0.2%
4044.27 1
 
0.2%
3324.49 6
 
1.1%
2903.26 1
 
0.2%
2813.76 2
 
0.4%
2623.0 1
 
0.2%
2121.7 7
1.3%

Interactions

2024-05-11T14:57:46.423191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:57:42.879201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:57:43.785405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:57:44.646619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
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2024-05-11T14:57:46.570191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
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2024-05-11T14:57:43.946898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
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2024-05-11T14:57:43.215575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
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2024-05-11T14:57:43.619007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:57:44.445087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:57:45.356734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:57:46.266958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T14:57:59.468723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분일자업종명업태명지도점검일자위반일자처분기간영업장면적(㎡)
처분일자1.0000.5770.6000.9980.9980.3120.312
업종명0.5771.0000.9910.5990.5930.2490.321
업태명0.6000.9911.0000.6110.6050.1910.559
지도점검일자0.9980.5990.6111.0001.0000.3120.250
위반일자0.9980.5930.6051.0001.0000.3290.251
처분기간0.3120.2490.1910.3120.3291.0000.215
영업장면적(㎡)0.3120.3210.5590.2500.2510.2151.000
2024-05-11T14:57:59.650463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명업태명
업종명1.0000.792
업태명0.7921.000
2024-05-11T14:58:00.106427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분일자지도점검일자위반일자처분기간영업장면적(㎡)업종명업태명
처분일자1.0000.9980.9980.124-0.0390.2680.283
지도점검일자0.9981.0001.0000.118-0.0390.2830.291
위반일자0.9981.0001.0000.115-0.0400.2790.287
처분기간0.1240.1180.1151.0000.2950.1560.095
영업장면적(㎡)-0.039-0.039-0.0400.2951.0000.2480.435
업종명0.2680.2830.2790.1560.2481.0000.792
업태명0.2830.2910.2870.0950.4350.7921.000

Missing values

2024-05-11T14:57:47.296635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T14:57:47.663858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-05-11T14:57:47.898569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

시군구코드처분일자교부번호업종명업태명업소명소재지도로명소재지지번지도점검일자행정처분상태처분명법적근거위반일자위반내용처분내용처분기간영업장면적(㎡)
031700002009073120001숙박업(일반)여관업서울여인숙<NA>서울특별시 금천구 시흥동 883번지 2호 [시흥대로 455]20090227처분확정과징금부과(영업정지1월갈음)공중위생관리법 제11조200902272009.02.27 02:00경부터 같은날 13:00경까지 청소년보호법을 위반한 사실이(청소년 이성혼숙 허용) 서울금천경찰서 형사과-1857(2009.03.06)호로 적발, 통보됨.과징금부과(영업정지1월갈음)<NA>105.83
131700002010022320001숙박업(일반)여관업서울여인숙<NA>서울특별시 금천구 시흥동 883번지 2호 [시흥대로 455]20091213처분확정영업정지를 갈음하여 과징금(900,000원)부과공중위생관리법제11조및 같은법시행규칙제19조200912132009.12.13. 06:00경 청소년보호법을 위반한 사실이(청소년 이성혼숙 허용) 서울금천경찰서형사과-12453(09.12.31)호로 적발,통보됨영업정지를 갈음하여 과징금(900,000원)부과<NA>105.83
231700002010042820001숙박업(일반)여관업서울여인숙<NA>서울특별시 금천구 시흥동 883번지 2호 [시흥대로 455]20100309처분확정불문처분공중위생관리법제11조및 같은법시행규칙제19조201003042010.03.04. 02:00경 청소년보호법을 위반하여 서울금천경찰서 수사과-1659(2010. 03.08)호로 적발,통보됨불문처분<NA>105.83
331700002011050420001숙박업(일반)여관업서울여인숙<NA>서울특별시 금천구 시흥동 883번지 2호 [시흥대로 455]20100421처분확정영업소 폐쇄명령공중위생관리법제11조,공중위생관리법시행규칙제19조201004212010.04.21. 02:10경 청소년보호법을 위반한사실(청소년 이성혼숙의 장소를 제공)이 서울금천경찰서 수사과-3912(2010.05.27)호로 적발,통보됨영업소 폐쇄명령<NA>105.83
431700002011050420001숙박업(일반)여관업서울여인숙<NA>서울특별시 금천구 시흥동 883번지 2호 [시흥대로 455]20100824처분확정영업소폐쇄(청소년보호법(3차)위반 포함)공중위생관리법제11조, 같은법시행규칙제19조201008242010.02월 초순경부터2010.06.20경까지 이곳을 찾아오는 불상의 손님들을 상대로 성매매를 하도록 장소를 제공 및 알선한 사실이 서울금천경찰서 생활안전과-6736(2010.08.23)호로 적발,통보됨.영업소폐쇄(청소년보호법(3차)위반 포함)<NA>105.83
531700002008120920002숙박업(일반)여관업산호장<NA>서울특별시 금천구 시흥동 995번지 55호 [금천로 227-1]20080815처분확정과징금부과(영업정지2월 갈음)공중위생관리법 제11조200808152008.08.15 23:30경 청소년보호법을 위반(청소년 이성혼숙 허용)한 사실이 서울금천경찰서 형사과-7631(2008.09.26)호로 적발, 통보됨.과징금부과(영업정지2월 갈음)<NA>255.96
631700002012041020003숙박업(일반)여관업가림장<NA>서울특별시 금천구 시흥동 888번지 17호 [대명시장2길 6]20110810처분확정과징금부과공중위생관리법제11조제1항20110810청소년이성혼숙과징금부과<NA>0.0
731700002019090320003숙박업(일반)여관업가림모텔서울특별시 금천구 시흥대로54길 43, (시흥동)서울특별시 금천구 시흥동 888번지 17호20190515처분확정과징금부과법 제11조제1항20190515청소년 이성혼숙 장소제공과징금부과<NA>0.0
831700002019090320003숙박업(일반)여관업가림모텔서울특별시 금천구 시흥대로54길 43, (시흥동)서울특별시 금천구 시흥동 888번지 17호20190515처분확정과징금부과법 제11조제1항20190515미성년자 이성혼숙 장소 제공(1차)과징금부과<NA>0.0
931700002007032320004숙박업(일반)여관업청명여관<NA>서울특별시 금천구 시흥동 891번지 20호 [광장3길 21]20070121처분확정영업정지1월(기소유예처분으로 1월감경)공중위생관리법 제11조20070124청소년 이성혼숙 허용(1차)영업정지1월(기소유예처분으로 1월감경)<NA>98.79
시군구코드처분일자교부번호업종명업태명업소명소재지도로명소재지지번지도점검일자행정처분상태처분명법적근거위반일자위반내용처분내용처분기간영업장면적(㎡)
5433170000201904302016-00052일반미용업, 피부미용업일반미용업Q사랑힐링？서울특별시 금천구 독산로 48, 1층 (시흥동)서울특별시 금천구 시흥동 908번지 15호 1층20190430처분확정영업소폐쇄법 제11조제3항제2호20190305영업장 폐업 미신고영업소폐쇄<NA>33.0
5443170000201510192015-00002피부미용업, 네일미용업피부미용업티티하우스서울특별시 금천구 디지털로 203, 303호 (가산동)서울특별시 금천구 가산동 139번지 17호 -30320150903처분확정개선명령법 제3조제1항20150903작업장소 출입문 1/3이상 불투명하게 설치개선명령<NA>99.0
5453170000201510192015-00002피부미용업, 네일미용업피부미용업티티하우스서울특별시 금천구 디지털로 203, 303호 (가산동)서울특별시 금천구 가산동 139번지 17호 -30320150903처분확정개선명령법 제4조제4항20150903소독기구 미비치개선명령<NA>99.0
5463170000201510192015-00002피부미용업, 네일미용업피부미용업티티하우스서울특별시 금천구 디지털로 203, 303호 (가산동)서울특별시 금천구 가산동 139번지 17호 -30320150903처분확정개선명령법 제3조제1항20150903작업 장소 출입문 1/3이상 불투명하게 설치, 소독기구 미비치개선명령<NA>99.0
5473170000201803152015-00006피부미용업, 네일미용업네일아트업네일잇(NAIL IT)서울특별시 금천구 가산디지털1로 168, A동 127호 (가산동)서울특별시 금천구 가산동 371번지 28호 A -12720180307처분확정과태료부과법 제17조201803072017 위생교육 미이수과태료부과<NA>65.37
5483170000201904302017-00002피부미용업, 네일미용업네일아트업다소다서울특별시 금천구 디지털로9길 32, 221-1호 (가산동, 갑을그레이트밸리)서울특별시 금천구 가산동 60번지 5호 갑을그레이트밸리-221-120190430처분확정영업소폐쇄법 제11조제3항제2호20190305영업장 폐업 미신고영업소폐쇄<NA>24.81
5493170000201803152017-00033피부미용업, 네일미용업네일아트업라헨느서울특별시 금천구 서부샛길 606, 224호 (가산동, 대성디폴리스)서울특별시 금천구 가산동 543번지 1호 B 대성디폴리스-22420180307처분확정과태료부과법 제17조201803072017 위생교육 미이수과태료부과<NA>49.5
5503170000202204052019-00014화장ㆍ분장 미용업메이크업업시선서울특별시 금천구 탑골로2길 8, 1층 103호 (시흥동)서울특별시 금천구 시흥동 249번지 3호 -10320220228처분확정과태료부과법 제22조제2항제6호202202282021년 위생교육 미이수과태료부과<NA>24.24
5513170000201804062015-00048일반미용업, 네일미용업, 화장ㆍ분장 미용업네일아트업바비서울특별시 금천구 은행나무로 51, (시흥동)서울특별시 금천구 시흥동 909번지 24호20180307처분확정과태료부과(20만원)법 제17조201803072017 위생교육 미이수과태료부과(20만원)<NA>14.0
5523170000201804062015-00048일반미용업, 네일미용업, 화장ㆍ분장 미용업네일아트업바비서울특별시 금천구 은행나무로 51, (시흥동)서울특별시 금천구 시흥동 909번지 24호20180307처분확정과태료부과(20만원)법 제17조201804062017년도 위생교육 미이수과태료부과(20만원)<NA>14.0

Duplicate rows

Most frequently occurring

시군구코드처분일자교부번호업종명업태명업소명소재지도로명소재지지번지도점검일자행정처분상태처분명법적근거위반일자위반내용처분내용처분기간영업장면적(㎡)# duplicates
23170000200407230113이용업일반이용업신화<NA>서울특별시 금천구 독산동 1009번지 74호20040217처분확정영업정지공중위생관리법 제11조제1항20040217무자격안마행위영업정지<NA>42.333
3031700002013011130015숙박업(일반)여인숙업광명장<NA>서울특별시 금천구 가산동 142번지 3호 [백년길 6]20110714처분확정영업정지 2월 및 과태료 1,000,000원공중위생관리법제11조20110714성매매알선영업정지 2월 및 과태료 1,000,000원<NA><NA>3
0317000020040226<NA>미용업일반미용업헤어뱅크<NA>서울특별시 금천구 독산동 985번지 5호20040226처분확정경고공중위생법 제17조20040201위생교육 미필 -2003.7.23자로 영업신고후 6개월이내 위생교육 미필경고012.312
1317000020040226<NA>미용업일반미용업헤어뱅크<NA>서울특별시 금천구 독산동 985번지 5호20040226처분확정과태료 300,000원공중위생법 제17조20040201위생교육 미필 -2003.7.23자로 영업신고후 6개월이내 위생교육 미필과태료 300,000원012.312
33170000200508224이용업일반이용업수연<NA>서울특별시 금천구 독산동 331번지 65호20050818처분확정고발공중위생법 제20조제1항,제3항20050818공중위생법 제3조제1항및동법제8조제1항고발016.22
43170000200508224이용업일반이용업수연<NA>서울특별시 금천구 독산동 331번지 65호20050818처분확정영업신고취소공중위생법 제20조제1항,제3항20050818공중위생법 제3조제1항및동법제8조제1항영업신고취소016.22
5317000020060303<NA>목욕장업공동탕업황궁<NA>서울특별시 금천구 시흥동 995번지 61호20060303처분확정경고공중위생관리법 제17조 제1항200602012005년도 위생교육 미필경고0518.582
6317000020060303<NA>목욕장업공동탕업황궁<NA>서울특별시 금천구 시흥동 995번지 61호20060303처분확정과태료 200,000원공중위생관리법 제17조 제1항200602012005년도 위생교육 미필과태료 200,000원0518.582
7317000020060704<NA>이용업일반이용업큰빛<NA>서울특별시 금천구 가산동 143번지 11호20060704처분확정개선명령(칸막이<커튼>제거)시설기준위반20060508의자와 의자사이를 구획하는 칸막이(커튼)설치개선명령(칸막이<커튼>제거)966.02
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