Overview

Dataset statistics

Number of variables17
Number of observations675
Missing cells424
Missing cells (%)3.7%
Duplicate rows62
Duplicate rows (%)9.2%
Total size in memory93.7 KiB
Average record size in memory142.2 B

Variable types

Categorical5
Numeric4
Text8

Dataset

Description시군구코드,처분일자,교부번호,업종명,업태명,업소명,소재지도로명,소재지지번,지도점검일자,행정처분상태,처분명,법적근거,위반일자,위반내용,처분내용,처분기간,영업장면적(㎡)
Author양천구
URLhttps://data.seoul.go.kr/dataList/OA-10836/S/1/datasetView.do

Alerts

시군구코드 has constant value ""Constant
행정처분상태 has constant value ""Constant
Dataset has 62 (9.2%) duplicate rowsDuplicates
처분일자 is highly overall correlated with 지도점검일자 and 2 other fieldsHigh correlation
지도점검일자 is highly overall correlated with 처분일자 and 2 other fieldsHigh correlation
위반일자 is highly overall correlated with 처분일자 and 2 other fieldsHigh correlation
업종명 is highly overall correlated with 업태명High correlation
업태명 is highly overall correlated with 업종명 and 1 other fieldsHigh correlation
처분기간 is highly overall correlated with 처분일자 and 3 other fieldsHigh correlation
처분기간 is highly imbalanced (87.8%)Imbalance
교부번호 has 12 (1.8%) missing valuesMissing
소재지도로명 has 381 (56.4%) missing valuesMissing
영업장면적(㎡) has 31 (4.6%) missing valuesMissing
영업장면적(㎡) has 14 (2.1%) zerosZeros

Reproduction

Analysis started2024-05-04 05:00:35.751244
Analysis finished2024-05-04 05:00:45.370931
Duration9.62 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
3140000
675 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3140000
2nd row3140000
3rd row3140000
4th row3140000
5th row3140000

Common Values

ValueCountFrequency (%)
3140000 675
100.0%

Length

2024-05-04T05:00:45.707559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T05:00:46.141960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3140000 675
100.0%

처분일자
Real number (ℝ)

HIGH CORRELATION 

Distinct240
Distinct (%)35.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20123410
Minimum20030516
Maximum20240327
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.1 KiB
2024-05-04T05:00:46.707346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20030516
5-th percentile20040779
Q120090163
median20120718
Q320161108
95-th percentile20210121
Maximum20240327
Range209811
Interquartile range (IQR)70945.5

Descriptive statistics

Standard deviation51314.669
Coefficient of variation (CV)0.0025499987
Kurtosis-0.7838761
Mean20123410
Median Absolute Deviation (MAD)40190
Skewness-0.035217992
Sum1.3583301 × 1010
Variance2.6331952 × 109
MonotonicityDecreasing
2024-05-04T05:00:47.444624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20040824 27
 
4.0%
20110923 18
 
2.7%
20210121 16
 
2.4%
20070126 15
 
2.2%
20111222 15
 
2.2%
20130809 14
 
2.1%
20120222 14
 
2.1%
20170426 14
 
2.1%
20111230 13
 
1.9%
20050628 12
 
1.8%
Other values (230) 517
76.6%
ValueCountFrequency (%)
20030516 1
 
0.1%
20030718 1
 
0.1%
20030902 1
 
0.1%
20030905 1
 
0.1%
20031009 1
 
0.1%
20031010 1
 
0.1%
20031118 1
 
0.1%
20031215 4
0.6%
20031230 2
0.3%
20040126 1
 
0.1%
ValueCountFrequency (%)
20240327 1
0.1%
20240220 2
0.3%
20231127 1
0.1%
20231024 2
0.3%
20230912 1
0.1%
20230613 1
0.1%
20230515 1
0.1%
20230502 1
0.1%
20230317 1
0.1%
20230208 1
0.1%

교부번호
Text

MISSING 

Distinct252
Distinct (%)38.0%
Missing12
Missing (%)1.8%
Memory size5.4 KiB
2024-05-04T05:00:48.350003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length3
Mean length4.8446456
Min length2

Characters and Unicode

Total characters3212
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

Unique116 ?
Unique (%)17.5%

Sample

1st row2013-486
2nd row268
3rd row2019-00098
4th row035
5th row199
ValueCountFrequency (%)
137 27
 
4.1%
064 17
 
2.6%
088 17
 
2.6%
015 13
 
2.0%
2014-29 12
 
1.8%
018 12
 
1.8%
69 11
 
1.7%
2017-00004 9
 
1.4%
063 9
 
1.4%
036 9
 
1.4%
Other values (242) 527
79.5%
2024-05-04T05:00:49.576169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1130
35.2%
1 460
14.3%
2 391
 
12.2%
- 219
 
6.8%
3 210
 
6.5%
6 169
 
5.3%
7 154
 
4.8%
4 144
 
4.5%
9 129
 
4.0%
5 106
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2993
93.2%
Dash Punctuation 219
 
6.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1130
37.8%
1 460
15.4%
2 391
 
13.1%
3 210
 
7.0%
6 169
 
5.6%
7 154
 
5.1%
4 144
 
4.8%
9 129
 
4.3%
5 106
 
3.5%
8 100
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 219
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3212
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1130
35.2%
1 460
14.3%
2 391
 
12.2%
- 219
 
6.8%
3 210
 
6.5%
6 169
 
5.3%
7 154
 
4.8%
4 144
 
4.5%
9 129
 
4.0%
5 106
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3212
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1130
35.2%
1 460
14.3%
2 391
 
12.2%
- 219
 
6.8%
3 210
 
6.5%
6 169
 
5.3%
7 154
 
4.8%
4 144
 
4.5%
9 129
 
4.0%
5 106
 
3.3%

업종명
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
목욕장업
186 
이용업
111 
숙박업(일반)
97 
피부미용업
93 
위생관리용역업
78 
Other values (12)
110 

Length

Max length23
Median length16
Mean length4.9792593
Min length3

Unique

Unique3 ?
Unique (%)0.4%

Sample

1st row일반미용업
2nd row세탁업
3rd row일반미용업
4th row목욕장업
5th row세탁업

Common Values

ValueCountFrequency (%)
목욕장업 186
27.6%
이용업 111
16.4%
숙박업(일반) 97
14.4%
피부미용업 93
13.8%
위생관리용역업 78
11.6%
일반미용업 25
 
3.7%
미용업 22
 
3.3%
종합미용업 17
 
2.5%
세탁업 17
 
2.5%
네일미용업 10
 
1.5%
Other values (7) 19
 
2.8%

Length

2024-05-04T05:00:49.965261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
목욕장업 186
26.8%
이용업 111
16.0%
피부미용업 103
14.8%
숙박업(일반 97
14.0%
위생관리용역업 78
11.2%
미용업 27
 
3.9%
일반미용업 26
 
3.7%
네일미용업 23
 
3.3%
종합미용업 17
 
2.4%
세탁업 17
 
2.4%
Other values (3) 9
 
1.3%

업태명
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
일반이용업
110 
피부미용업
97 
공동탕업
94 
공동탕업+찜질시설서비스영업
91 
여관업
89 
Other values (11)
194 

Length

Max length14
Median length9
Mean length6.0651852
Min length3

Unique

Unique3 ?
Unique (%)0.4%

Sample

1st row일반미용업
2nd row일반세탁업
3rd row일반미용업
4th row공동탕업
5th row일반세탁업

Common Values

ValueCountFrequency (%)
일반이용업 110
16.3%
피부미용업 97
14.4%
공동탕업 94
13.9%
공동탕업+찜질시설서비스영업 91
13.5%
여관업 89
13.2%
위생관리용역업 78
11.6%
일반미용업 49
7.3%
네일아트업 25
 
3.7%
일반세탁업 15
 
2.2%
메이크업업 11
 
1.6%
Other values (6) 16
 
2.4%

Length

2024-05-04T05:00:50.269234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반이용업 110
16.3%
피부미용업 97
14.3%
공동탕업 94
13.9%
공동탕업+찜질시설서비스영업 91
13.5%
여관업 89
13.2%
위생관리용역업 78
11.5%
일반미용업 49
7.2%
네일아트업 25
 
3.7%
일반세탁업 15
 
2.2%
메이크업업 11
 
1.6%
Other values (7) 17
 
2.5%

업소명
Text

Distinct308
Distinct (%)45.6%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
2024-05-04T05:00:50.832070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length15
Mean length5.8903704
Min length2

Characters and Unicode

Total characters3976
Distinct characters352
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

Unique169 ?
Unique (%)25.0%

Sample

1st row머리쟁이
2nd row현대세탁소
3rd row지아쌀롱
4th row금강대중목욕탕
5th row원광사세탁소
ValueCountFrequency (%)
엔젤 27
 
3.5%
목동불한증막사우나 16
 
2.1%
아카데미 15
 
2.0%
청기와 12
 
1.6%
여관 12
 
1.6%
다미에스떼 12
 
1.6%
월드파크 10
 
1.3%
주식회사 10
 
1.3%
beauty 9
 
1.2%
in 9
 
1.2%
Other values (325) 629
82.7%
2024-05-04T05:00:51.868796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 112
 
2.8%
스 104
 
2.6%
나 101
 
2.5%
우 95
 
2.4%
86
 
2.2%
) 86
 
2.2%
( 86
 
2.2%
이 86
 
2.2%
동 75
 
1.9%
주 67
 
1.7%
Other values (342) 3078
77.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3438
86.5%
Lowercase Letter 149
 
3.7%
Space Separator 86
 
2.2%
Close Punctuation 86
 
2.2%
Open Punctuation 86
 
2.2%
Uppercase Letter 86
 
2.2%
Decimal Number 41
 
1.0%
Connector Punctuation 2
 
0.1%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 112
 
3.3%
스 104
 
3.0%
나 101
 
2.9%
우 95
 
2.8%
이 86
 
2.5%
동 75
 
2.2%
주 67
 
1.9%
미 60
 
1.7%
관 59
 
1.7%
용 58
 
1.7%
Other values (303) 2621
76.2%
Lowercase Letter
ValueCountFrequency (%)
u 17
11.4%
a 16
10.7%
i 16
10.7%
n 15
10.1%
y 15
10.1%
e 14
9.4%
o 12
8.1%
b 10
6.7%
t 9
6.0%
s 6
 
4.0%
Other values (7) 19
12.8%
Uppercase Letter
ValueCountFrequency (%)
A 24
27.9%
H 16
18.6%
N 14
16.3%
Q 7
 
8.1%
S 6
 
7.0%
I 4
 
4.7%
B 4
 
4.7%
K 3
 
3.5%
R 2
 
2.3%
L 2
 
2.3%
Other values (4) 4
 
4.7%
Decimal Number
ValueCountFrequency (%)
4 18
43.9%
2 15
36.6%
1 8
19.5%
Space Separator
ValueCountFrequency (%)
86
100.0%
Close Punctuation
ValueCountFrequency (%)
) 86
100.0%
Open Punctuation
ValueCountFrequency (%)
( 86
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Other Punctuation
ValueCountFrequency (%)
' 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3438
86.5%
Common 303
 
7.6%
Latin 235
 
5.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 112
 
3.3%
스 104
 
3.0%
나 101
 
2.9%
우 95
 
2.8%
이 86
 
2.5%
동 75
 
2.2%
주 67
 
1.9%
미 60
 
1.7%
관 59
 
1.7%
용 58
 
1.7%
Other values (303) 2621
76.2%
Latin
ValueCountFrequency (%)
A 24
 
10.2%
u 17
 
7.2%
H 16
 
6.8%
a 16
 
6.8%
i 16
 
6.8%
n 15
 
6.4%
y 15
 
6.4%
e 14
 
6.0%
N 14
 
6.0%
o 12
 
5.1%
Other values (21) 76
32.3%
Common
ValueCountFrequency (%)
86
28.4%
) 86
28.4%
( 86
28.4%
4 18
 
5.9%
2 15
 
5.0%
1 8
 
2.6%
_ 2
 
0.7%
' 2
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3438
86.5%
ASCII 538
 
13.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 112
 
3.3%
스 104
 
3.0%
나 101
 
2.9%
우 95
 
2.8%
이 86
 
2.5%
동 75
 
2.2%
주 67
 
1.9%
미 60
 
1.7%
관 59
 
1.7%
용 58
 
1.7%
Other values (303) 2621
76.2%
ASCII
ValueCountFrequency (%)
86
16.0%
) 86
16.0%
( 86
16.0%
A 24
 
4.5%
4 18
 
3.3%
u 17
 
3.2%
H 16
 
3.0%
a 16
 
3.0%
i 16
 
3.0%
n 15
 
2.8%
Other values (29) 158
29.4%

소재지도로명
Text

MISSING 

Distinct177
Distinct (%)60.2%
Missing381
Missing (%)56.4%
Memory size5.4 KiB
2024-05-04T05:00:52.461794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length42
Mean length33.343537
Min length22

Characters and Unicode

Total characters9803
Distinct characters158
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

Unique125 ?
Unique (%)42.5%

Sample

1st row서울특별시 양천구 곰달래로5길 55, 1층 (신월동)
2nd row서울특별시 양천구 목동동로 130, (신정동,14단지 C상가 115호)
3rd row서울특별시 양천구 곰달래로 48, 가동 1층 1호 (신월동)
4th row서울특별시 양천구 남부순환로80길 20, 지하 1, 1~2층 (신월동)
5th row서울특별시 양천구 중앙로39길 32, (신정동)
ValueCountFrequency (%)
서울특별시 294
 
15.6%
양천구 294
 
15.6%
목동 107
 
5.7%
신정동 83
 
4.4%
신월동 75
 
4.0%
1층 45
 
2.4%
3층 31
 
1.6%
오목로 22
 
1.2%
공항대로 21
 
1.1%
목동동로 20
 
1.1%
Other values (339) 898
47.5%
2024-05-04T05:00:53.652138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1596
 
16.3%
, 489
 
5.0%
동 485
 
4.9%
1 380
 
3.9%
서 322
 
3.3%
목 315
 
3.2%
양 314
 
3.2%
로 306
 
3.1%
천 302
 
3.1%
( 301
 
3.1%
Other values (148) 4993
50.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5543
56.5%
Space Separator 1596
 
16.3%
Decimal Number 1513
 
15.4%
Other Punctuation 489
 
5.0%
Open Punctuation 302
 
3.1%
Close Punctuation 302
 
3.1%
Dash Punctuation 35
 
0.4%
Uppercase Letter 21
 
0.2%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 485
 
8.7%
서 322
 
5.8%
목 315
 
5.7%
양 314
 
5.7%
로 306
 
5.5%
천 302
 
5.4%
시 300
 
5.4%
구 295
 
5.3%
특 294
 
5.3%
울 294
 
5.3%
Other values (127) 2316
41.8%
Decimal Number
ValueCountFrequency (%)
1 380
25.1%
2 269
17.8%
3 206
13.6%
0 197
13.0%
5 113
 
7.5%
4 99
 
6.5%
6 82
 
5.4%
9 62
 
4.1%
7 58
 
3.8%
8 47
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
B 16
76.2%
C 3
 
14.3%
S 2
 
9.5%
Open Punctuation
ValueCountFrequency (%)
( 301
99.7%
[ 1
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 301
99.7%
] 1
 
0.3%
Space Separator
ValueCountFrequency (%)
1596
100.0%
Other Punctuation
ValueCountFrequency (%)
, 489
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 35
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5543
56.5%
Common 4239
43.2%
Latin 21
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 485
 
8.7%
서 322
 
5.8%
목 315
 
5.7%
양 314
 
5.7%
로 306
 
5.5%
천 302
 
5.4%
시 300
 
5.4%
구 295
 
5.3%
특 294
 
5.3%
울 294
 
5.3%
Other values (127) 2316
41.8%
Common
ValueCountFrequency (%)
1596
37.7%
, 489
 
11.5%
1 380
 
9.0%
( 301
 
7.1%
) 301
 
7.1%
2 269
 
6.3%
3 206
 
4.9%
0 197
 
4.6%
5 113
 
2.7%
4 99
 
2.3%
Other values (8) 288
 
6.8%
Latin
ValueCountFrequency (%)
B 16
76.2%
C 3
 
14.3%
S 2
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5543
56.5%
ASCII 4260
43.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1596
37.5%
, 489
 
11.5%
1 380
 
8.9%
( 301
 
7.1%
) 301
 
7.1%
2 269
 
6.3%
3 206
 
4.8%
0 197
 
4.6%
5 113
 
2.7%
4 99
 
2.3%
Other values (11) 309
 
7.3%
Hangul
ValueCountFrequency (%)
동 485
 
8.7%
서 322
 
5.8%
목 315
 
5.7%
양 314
 
5.7%
로 306
 
5.5%
천 302
 
5.4%
시 300
 
5.4%
구 295
 
5.3%
특 294
 
5.3%
울 294
 
5.3%
Other values (127) 2316
41.8%

소재지지번
Text

Distinct320
Distinct (%)47.4%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
2024-05-04T05:00:54.316547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length46
Mean length29.642963
Min length21

Characters and Unicode

Total characters20009
Distinct characters168
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

Unique172 ?
Unique (%)25.5%

Sample

1st row서울특별시 양천구 신월동 143번지 8호
2nd row서울특별시 양천구 신정동 329번지 0호 14단지 C상가 115호
3rd row서울특별시 양천구 신월동 228번지 1호
4th row서울특별시 양천구 신월동 1002번지 8호 지하 1~2층
5th row서울특별시 양천구 신정동 1215번지 8호
ValueCountFrequency (%)
서울특별시 675
17.3%
양천구 675
17.3%
목동 255
 
6.5%
신정동 222
 
5.7%
신월동 199
 
5.1%
1호 107
 
2.7%
7호 51
 
1.3%
3층 44
 
1.1%
1층 41
 
1.0%
2호 41
 
1.0%
Other values (412) 1597
40.9%
2024-05-04T05:00:55.505085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4857
24.3%
1 953
 
4.8%
지 793
 
4.0%
동 746
 
3.7%
호 708
 
3.5%
시 685
 
3.4%
양 684
 
3.4%
천 684
 
3.4%
서 679
 
3.4%
번 676
 
3.4%
Other values (158) 8544
42.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10986
54.9%
Space Separator 4857
24.3%
Decimal Number 3863
 
19.3%
Dash Punctuation 91
 
0.5%
Other Punctuation 80
 
0.4%
Close Punctuation 47
 
0.2%
Open Punctuation 47
 
0.2%
Uppercase Letter 35
 
0.2%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 793
 
7.2%
동 746
 
6.8%
호 708
 
6.4%
시 685
 
6.2%
양 684
 
6.2%
천 684
 
6.2%
서 679
 
6.2%
번 676
 
6.2%
구 676
 
6.2%
특 675
 
6.1%
Other values (136) 3980
36.2%
Decimal Number
ValueCountFrequency (%)
1 953
24.7%
2 512
13.3%
0 473
12.2%
3 358
 
9.3%
9 338
 
8.7%
7 268
 
6.9%
5 250
 
6.5%
6 248
 
6.4%
4 244
 
6.3%
8 219
 
5.7%
Uppercase Letter
ValueCountFrequency (%)
B 27
77.1%
C 3
 
8.6%
A 3
 
8.6%
S 2
 
5.7%
Close Punctuation
ValueCountFrequency (%)
) 45
95.7%
] 2
 
4.3%
Open Punctuation
ValueCountFrequency (%)
( 45
95.7%
[ 2
 
4.3%
Space Separator
ValueCountFrequency (%)
4857
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 91
100.0%
Other Punctuation
ValueCountFrequency (%)
, 80
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10986
54.9%
Common 8988
44.9%
Latin 35
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 793
 
7.2%
동 746
 
6.8%
호 708
 
6.4%
시 685
 
6.2%
양 684
 
6.2%
천 684
 
6.2%
서 679
 
6.2%
번 676
 
6.2%
구 676
 
6.2%
특 675
 
6.1%
Other values (136) 3980
36.2%
Common
ValueCountFrequency (%)
4857
54.0%
1 953
 
10.6%
2 512
 
5.7%
0 473
 
5.3%
3 358
 
4.0%
9 338
 
3.8%
7 268
 
3.0%
5 250
 
2.8%
6 248
 
2.8%
4 244
 
2.7%
Other values (8) 487
 
5.4%
Latin
ValueCountFrequency (%)
B 27
77.1%
C 3
 
8.6%
A 3
 
8.6%
S 2
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10986
54.9%
ASCII 9023
45.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4857
53.8%
1 953
 
10.6%
2 512
 
5.7%
0 473
 
5.2%
3 358
 
4.0%
9 338
 
3.7%
7 268
 
3.0%
5 250
 
2.8%
6 248
 
2.7%
4 244
 
2.7%
Other values (12) 522
 
5.8%
Hangul
ValueCountFrequency (%)
지 793
 
7.2%
동 746
 
6.8%
호 708
 
6.4%
시 685
 
6.2%
양 684
 
6.2%
천 684
 
6.2%
서 679
 
6.2%
번 676
 
6.2%
구 676
 
6.2%
특 675
 
6.1%
Other values (136) 3980
36.2%

지도점검일자
Real number (ℝ)

HIGH CORRELATION 

Distinct242
Distinct (%)35.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20121807
Minimum20020819
Maximum20240122
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.1 KiB
2024-05-04T05:00:56.089145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20020819
5-th percentile20040711
Q120081116
median20120618
Q320161024
95-th percentile20201126
Maximum20240122
Range219303
Interquartile range (IQR)79908.5

Descriptive statistics

Standard deviation50455.965
Coefficient of variation (CV)0.0025075265
Kurtosis-0.78810909
Mean20121807
Median Absolute Deviation (MAD)40099
Skewness-0.046640009
Sum1.358222 × 1010
Variance2.5458044 × 109
MonotonicityNot monotonic
2024-05-04T05:00:56.718452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20110321 41
 
6.1%
20170327 28
 
4.1%
20040805 27
 
4.0%
20130109 19
 
2.8%
20110330 18
 
2.7%
20201126 16
 
2.4%
20070126 15
 
2.2%
20110822 12
 
1.8%
20120201 12
 
1.8%
20161024 12
 
1.8%
Other values (232) 475
70.4%
ValueCountFrequency (%)
20020819 1
 
0.1%
20030703 1
 
0.1%
20030829 1
 
0.1%
20030901 1
 
0.1%
20030918 1
 
0.1%
20031007 1
 
0.1%
20031019 1
 
0.1%
20031119 4
0.6%
20031204 2
0.3%
20031223 1
 
0.1%
ValueCountFrequency (%)
20240122 1
0.1%
20240109 1
0.1%
20231220 1
0.1%
20231108 1
0.1%
20230922 2
0.3%
20230814 1
0.1%
20230403 2
0.3%
20230228 1
0.1%
20221215 1
0.1%
20221120 1
0.1%

행정처분상태
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
처분확정
675 

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 675
100.0%

Length

2024-05-04T05:00:57.121741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T05:00:57.665376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
처분확정 675
100.0%

처분명
Text

Distinct120
Distinct (%)17.8%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
2024-05-04T05:00:58.252216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length53
Mean length9.7896296
Min length2

Characters and Unicode

Total characters6608
Distinct characters91
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

Unique68 ?
Unique (%)10.1%

Sample

1st row영업소폐쇄
2nd row직권말소
3rd row영업신고사항 직권말소
4th row개선명령
5th row직권말소
ValueCountFrequency (%)
개선명령 170
 
13.1%
경고 166
 
12.8%
과태료 67
 
5.2%
부과 67
 
5.2%
영업정지 46
 
3.5%
영업소폐쇄 44
 
3.4%
및 41
 
3.2%
내 39
 
3.0%
기한 39
 
3.0%
자진납부 29
 
2.2%
Other values (138) 589
45.4%
2024-05-04T05:00:59.693452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
623
 
9.4%
0 430
 
6.5%
과 418
 
6.3%
부 257
 
3.9%
원 242
 
3.7%
2 207
 
3.1%
개 195
 
3.0%
만 193
 
2.9%
고 193
 
2.9%
명 192
 
2.9%
Other values (81) 3658
55.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4404
66.6%
Decimal Number 1085
 
16.4%
Space Separator 623
 
9.4%
Other Punctuation 219
 
3.3%
Open Punctuation 141
 
2.1%
Close Punctuation 132
 
2.0%
Math Symbol 3
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 418
 
9.5%
부 257
 
5.8%
원 242
 
5.5%
개 195
 
4.4%
만 193
 
4.4%
고 193
 
4.4%
명 192
 
4.4%
령 192
 
4.4%
경 182
 
4.1%
선 181
 
4.1%
Other values (61) 2159
49.0%
Decimal Number
ValueCountFrequency (%)
0 430
39.6%
2 207
19.1%
1 133
 
12.3%
6 92
 
8.5%
5 68
 
6.3%
4 59
 
5.4%
8 38
 
3.5%
3 32
 
2.9%
9 17
 
1.6%
7 9
 
0.8%
Other Punctuation
ValueCountFrequency (%)
. 110
50.2%
, 86
39.3%
: 20
 
9.1%
% 2
 
0.9%
/ 1
 
0.5%
Space Separator
ValueCountFrequency (%)
623
100.0%
Open Punctuation
ValueCountFrequency (%)
( 141
100.0%
Close Punctuation
ValueCountFrequency (%)
) 132
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4404
66.6%
Common 2204
33.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 418
 
9.5%
부 257
 
5.8%
원 242
 
5.5%
개 195
 
4.4%
만 193
 
4.4%
고 193
 
4.4%
명 192
 
4.4%
령 192
 
4.4%
경 182
 
4.1%
선 181
 
4.1%
Other values (61) 2159
49.0%
Common
ValueCountFrequency (%)
623
28.3%
0 430
19.5%
2 207
 
9.4%
( 141
 
6.4%
1 133
 
6.0%
) 132
 
6.0%
. 110
 
5.0%
6 92
 
4.2%
, 86
 
3.9%
5 68
 
3.1%
Other values (10) 182
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4404
66.6%
ASCII 2204
33.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
623
28.3%
0 430
19.5%
2 207
 
9.4%
( 141
 
6.4%
1 133
 
6.0%
) 132
 
6.0%
. 110
 
5.0%
6 92
 
4.2%
, 86
 
3.9%
5 68
 
3.1%
Other values (10) 182
 
8.3%
Hangul
ValueCountFrequency (%)
과 418
 
9.5%
부 257
 
5.8%
원 242
 
5.5%
개 195
 
4.4%
만 193
 
4.4%
고 193
 
4.4%
명 192
 
4.4%
령 192
 
4.4%
경 182
 
4.1%
선 181
 
4.1%
Other values (61) 2159
49.0%

법적근거
Text

Distinct163
Distinct (%)24.1%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
2024-05-04T05:01:00.335274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length85
Median length63
Mean length22.442963
Min length6

Characters and Unicode

Total characters15149
Distinct characters82
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique83 ?
Unique (%)12.3%

Sample

1st row법 제11조제3항제1호
2nd row법 제3조3항
3rd row법 제3조3항
4th row법 제11조제1항제4호
5th row법 제3조3항
ValueCountFrequency (%)
공중위생관리법 368
 
13.9%
법 274
 
10.4%
및 185
 
7.0%
같은 144
 
5.5%
같은법 130
 
4.9%
시행규칙 106
 
4.0%
제11조 96
 
3.6%
제4조제7항 95
 
3.6%
시행령 86
 
3.3%
제19조 65
 
2.5%
Other values (153) 1092
41.3%
2024-05-04T05:01:01.670223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1983
 
13.1%
제 1829
 
12.1%
1 1102
 
7.3%
조 1089
 
7.2%
법 988
 
6.5%
항 628
 
4.1%
2 617
 
4.1%
위 554
 
3.7%
생 519
 
3.4%
공 514
 
3.4%
Other values (72) 5326
35.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10052
66.4%
Decimal Number 2712
 
17.9%
Space Separator 1983
 
13.1%
Other Punctuation 304
 
2.0%
Close Punctuation 49
 
0.3%
Open Punctuation 49
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 1829
18.2%
조 1089
10.8%
법 988
9.8%
항 628
 
6.2%
위 554
 
5.5%
생 519
 
5.2%
공 514
 
5.1%
중 514
 
5.1%
관 491
 
4.9%
리 474
 
4.7%
Other values (55) 2452
24.4%
Decimal Number
ValueCountFrequency (%)
1 1102
40.6%
2 617
22.8%
7 326
 
12.0%
4 277
 
10.2%
3 186
 
6.9%
9 90
 
3.3%
6 63
 
2.3%
0 46
 
1.7%
8 3
 
0.1%
5 2
 
0.1%
Other Punctuation
ValueCountFrequency (%)
, 265
87.2%
. 39
 
12.8%
Close Punctuation
ValueCountFrequency (%)
) 42
85.7%
] 7
 
14.3%
Open Punctuation
ValueCountFrequency (%)
( 42
85.7%
[ 7
 
14.3%
Space Separator
ValueCountFrequency (%)
1983
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10052
66.4%
Common 5097
33.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 1829
18.2%
조 1089
10.8%
법 988
9.8%
항 628
 
6.2%
위 554
 
5.5%
생 519
 
5.2%
공 514
 
5.1%
중 514
 
5.1%
관 491
 
4.9%
리 474
 
4.7%
Other values (55) 2452
24.4%
Common
ValueCountFrequency (%)
1983
38.9%
1 1102
21.6%
2 617
 
12.1%
7 326
 
6.4%
4 277
 
5.4%
, 265
 
5.2%
3 186
 
3.6%
9 90
 
1.8%
6 63
 
1.2%
0 46
 
0.9%
Other values (7) 142
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10052
66.4%
ASCII 5097
33.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1983
38.9%
1 1102
21.6%
2 617
 
12.1%
7 326
 
6.4%
4 277
 
5.4%
, 265
 
5.2%
3 186
 
3.6%
9 90
 
1.8%
6 63
 
1.2%
0 46
 
0.9%
Other values (7) 142
 
2.8%
Hangul
ValueCountFrequency (%)
제 1829
18.2%
조 1089
10.8%
법 988
9.8%
항 628
 
6.2%
위 554
 
5.5%
생 519
 
5.2%
공 514
 
5.1%
중 514
 
5.1%
관 491
 
4.9%
리 474
 
4.7%
Other values (55) 2452
24.4%

위반일자
Real number (ℝ)

HIGH CORRELATION 

Distinct252
Distinct (%)37.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20121016
Minimum20020726
Maximum20240122
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.1 KiB
2024-05-04T05:01:02.333915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20020726
5-th percentile20040618
Q120081127
median20120625
Q320161024
95-th percentile20201208
Maximum20240122
Range219396
Interquartile range (IQR)79897

Descriptive statistics

Standard deviation50636.648
Coefficient of variation (CV)0.002516605
Kurtosis-0.81463737
Mean20121016
Median Absolute Deviation (MAD)40105
Skewness-0.04091771
Sum1.3581686 × 1010
Variance2.5640701 × 109
MonotonicityNot monotonic
2024-05-04T05:01:03.006027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20110808 47
 
7.0%
20170327 28
 
4.1%
20130109 19
 
2.8%
20110330 18
 
2.7%
20201208 16
 
2.4%
20060628 15
 
2.2%
20161024 12
 
1.8%
20141231 12
 
1.8%
20111229 12
 
1.8%
20191231 11
 
1.6%
Other values (242) 485
71.9%
ValueCountFrequency (%)
20020726 1
 
0.1%
20030703 1
 
0.1%
20030829 1
 
0.1%
20030901 1
 
0.1%
20030916 1
 
0.1%
20030918 1
 
0.1%
20030930 1
 
0.1%
20031007 1
 
0.1%
20031010 4
0.6%
20031020 1
 
0.1%
ValueCountFrequency (%)
20240122 2
0.3%
20240109 1
0.1%
20231025 1
0.1%
20230831 1
0.1%
20230814 1
0.1%
20230428 1
0.1%
20230403 2
0.3%
20230228 1
0.1%
20221219 1
0.1%
20221120 1
0.1%

위반내용
Text

Distinct256
Distinct (%)37.9%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
2024-05-04T05:01:03.732435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length163
Median length75
Mean length25.771852
Min length4

Characters and Unicode

Total characters17396
Distinct characters282
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique163 ?
Unique (%)24.1%

Sample

1st row정당한 사유 없이 6개월 이상 계속 휴업
2nd row「공중위생관리법」제3조제2항 규정을 위반하여 폐업신고 의무를 이행하지 아니함
3rd row「공중위생관리법」제3조제2항 규정을 위반하여 폐업신고 의무를 이행하지 아니함
4th row욕수의 수질기준에 적합하게 욕수를 유지하지 않은 경우 1차(수질기준 부적합-대장균군 초과)
5th row부가가치세법에 따라 사업자등록말소,공중위생관리법 제3조 제2항을 이행하지 아니함(폐업신고)
ValueCountFrequency (%)
위생교육 142
 
4.0%
미이수 92
 
2.6%
미이행 90
 
2.5%
수질기준 81
 
2.3%
및 53
 
1.5%
1차 52
 
1.5%
경우 49
 
1.4%
초과 49
 
1.4%
이상 48
 
1.3%
준수사항 45
 
1.3%
Other values (563) 2868
80.4%
2024-05-04T05:01:05.341810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2922
 
16.8%
수 533
 
3.1%
위 454
 
2.6%
이 434
 
2.5%
업 377
 
2.2%
1 346
 
2.0%
미 334
 
1.9%
기 325
 
1.9%
생 300
 
1.7%
( 257
 
1.5%
Other values (272) 11114
63.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12459
71.6%
Space Separator 2922
 
16.8%
Decimal Number 1098
 
6.3%
Open Punctuation 310
 
1.8%
Close Punctuation 309
 
1.8%
Other Punctuation 226
 
1.3%
Dash Punctuation 29
 
0.2%
Lowercase Letter 24
 
0.1%
Uppercase Letter 18
 
0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 533
 
4.3%
위 454
 
3.6%
이 434
 
3.5%
업 377
 
3.0%
미 334
 
2.7%
기 325
 
2.6%
생 300
 
2.4%
하 251
 
2.0%
자 241
 
1.9%
년 239
 
1.9%
Other values (238) 8971
72.0%
Decimal Number
ValueCountFrequency (%)
1 346
31.5%
0 255
23.2%
2 254
23.1%
3 62
 
5.6%
6 56
 
5.1%
8 34
 
3.1%
5 27
 
2.5%
9 24
 
2.2%
7 23
 
2.1%
4 17
 
1.5%
Other Punctuation
ValueCountFrequency (%)
, 97
42.9%
. 76
33.6%
: 41
18.1%
/ 7
 
3.1%
？ 3
 
1.3%
※ 1
 
0.4%
; 1
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
L 10
55.6%
C 4
 
22.2%
V 2
 
11.1%
T 2
 
11.1%
Lowercase Letter
ValueCountFrequency (%)
u 10
41.7%
x 10
41.7%
m 2
 
8.3%
l 2
 
8.3%
Open Punctuation
ValueCountFrequency (%)
( 257
82.9%
[ 42
 
13.5%
「 11
 
3.5%
Close Punctuation
ValueCountFrequency (%)
) 257
83.2%
] 41
 
13.3%
」 11
 
3.6%
Space Separator
ValueCountFrequency (%)
2922
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%
Other Symbol
ValueCountFrequency (%)
○ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12459
71.6%
Common 4895
 
28.1%
Latin 42
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 533
 
4.3%
위 454
 
3.6%
이 434
 
3.5%
업 377
 
3.0%
미 334
 
2.7%
기 325
 
2.6%
생 300
 
2.4%
하 251
 
2.0%
자 241
 
1.9%
년 239
 
1.9%
Other values (238) 8971
72.0%
Common
ValueCountFrequency (%)
2922
59.7%
1 346
 
7.1%
( 257
 
5.3%
) 257
 
5.3%
0 255
 
5.2%
2 254
 
5.2%
, 97
 
2.0%
. 76
 
1.6%
3 62
 
1.3%
6 56
 
1.1%
Other values (16) 313
 
6.4%
Latin
ValueCountFrequency (%)
L 10
23.8%
u 10
23.8%
x 10
23.8%
C 4
 
9.5%
m 2
 
4.8%
l 2
 
4.8%
V 2
 
4.8%
T 2
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12459
71.6%
ASCII 4910
 
28.2%
None 25
 
0.1%
Punctuation 1
 
< 0.1%
Geometric Shapes 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2922
59.5%
1 346
 
7.0%
( 257
 
5.2%
) 257
 
5.2%
0 255
 
5.2%
2 254
 
5.2%
, 97
 
2.0%
. 76
 
1.5%
3 62
 
1.3%
6 56
 
1.1%
Other values (19) 328
 
6.7%
Hangul
ValueCountFrequency (%)
수 533
 
4.3%
위 454
 
3.6%
이 434
 
3.5%
업 377
 
3.0%
미 334
 
2.7%
기 325
 
2.6%
생 300
 
2.4%
하 251
 
2.0%
자 241
 
1.9%
년 239
 
1.9%
Other values (238) 8971
72.0%
None
ValueCountFrequency (%)
」 11
44.0%
「 11
44.0%
？ 3
 
12.0%
Punctuation
ValueCountFrequency (%)
※ 1
100.0%
Geometric Shapes
ValueCountFrequency (%)
○ 1
100.0%

처분내용
Text

Distinct120
Distinct (%)17.8%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
2024-05-04T05:01:05.973863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length53
Mean length9.7896296
Min length2

Characters and Unicode

Total characters6608
Distinct characters91
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

Unique68 ?
Unique (%)10.1%

Sample

1st row영업소폐쇄
2nd row직권말소
3rd row영업신고사항 직권말소
4th row개선명령
5th row직권말소
ValueCountFrequency (%)
개선명령 170
 
13.1%
경고 166
 
12.8%
과태료 67
 
5.2%
부과 67
 
5.2%
영업정지 46
 
3.5%
영업소폐쇄 44
 
3.4%
및 41
 
3.2%
내 39
 
3.0%
기한 39
 
3.0%
자진납부 29
 
2.2%
Other values (138) 589
45.4%
2024-05-04T05:01:07.042273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
623
 
9.4%
0 430
 
6.5%
과 418
 
6.3%
부 257
 
3.9%
원 242
 
3.7%
2 207
 
3.1%
개 195
 
3.0%
만 193
 
2.9%
고 193
 
2.9%
명 192
 
2.9%
Other values (81) 3658
55.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4404
66.6%
Decimal Number 1085
 
16.4%
Space Separator 623
 
9.4%
Other Punctuation 219
 
3.3%
Open Punctuation 141
 
2.1%
Close Punctuation 132
 
2.0%
Math Symbol 3
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 418
 
9.5%
부 257
 
5.8%
원 242
 
5.5%
개 195
 
4.4%
만 193
 
4.4%
고 193
 
4.4%
명 192
 
4.4%
령 192
 
4.4%
경 182
 
4.1%
선 181
 
4.1%
Other values (61) 2159
49.0%
Decimal Number
ValueCountFrequency (%)
0 430
39.6%
2 207
19.1%
1 133
 
12.3%
6 92
 
8.5%
5 68
 
6.3%
4 59
 
5.4%
8 38
 
3.5%
3 32
 
2.9%
9 17
 
1.6%
7 9
 
0.8%
Other Punctuation
ValueCountFrequency (%)
. 110
50.2%
, 86
39.3%
: 20
 
9.1%
% 2
 
0.9%
/ 1
 
0.5%
Space Separator
ValueCountFrequency (%)
623
100.0%
Open Punctuation
ValueCountFrequency (%)
( 141
100.0%
Close Punctuation
ValueCountFrequency (%)
) 132
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4404
66.6%
Common 2204
33.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 418
 
9.5%
부 257
 
5.8%
원 242
 
5.5%
개 195
 
4.4%
만 193
 
4.4%
고 193
 
4.4%
명 192
 
4.4%
령 192
 
4.4%
경 182
 
4.1%
선 181
 
4.1%
Other values (61) 2159
49.0%
Common
ValueCountFrequency (%)
623
28.3%
0 430
19.5%
2 207
 
9.4%
( 141
 
6.4%
1 133
 
6.0%
) 132
 
6.0%
. 110
 
5.0%
6 92
 
4.2%
, 86
 
3.9%
5 68
 
3.1%
Other values (10) 182
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4404
66.6%
ASCII 2204
33.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
623
28.3%
0 430
19.5%
2 207
 
9.4%
( 141
 
6.4%
1 133
 
6.0%
) 132
 
6.0%
. 110
 
5.0%
6 92
 
4.2%
, 86
 
3.9%
5 68
 
3.1%
Other values (10) 182
 
8.3%
Hangul
ValueCountFrequency (%)
과 418
 
9.5%
부 257
 
5.8%
원 242
 
5.5%
개 195
 
4.4%
만 193
 
4.4%
고 193
 
4.4%
명 192
 
4.4%
령 192
 
4.4%
경 182
 
4.1%
선 181
 
4.1%
Other values (61) 2159
49.0%

처분기간
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
<NA>
651 
15
 
9
5
 
8
18
 
6
10
 
1

Length

Max length4
Median length4
Mean length3.917037
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 651
96.4%
15 9
 
1.3%
5 8
 
1.2%
18 6
 
0.9%
10 1
 
0.1%

Length

2024-05-04T05:01:07.875835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T05:01:08.346125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 651
96.4%
15 9
 
1.3%
5 8
 
1.2%
18 6
 
0.9%
10 1
 
0.1%

영업장면적(㎡)
Real number (ℝ)

MISSING  ZEROS 

Distinct235
Distinct (%)36.5%
Missing31
Missing (%)4.6%
Infinite0
Infinite (%)0.0%
Mean368.40321
Minimum0
Maximum2753.89
Zeros14
Zeros (%)2.1%
Negative0
Negative (%)0.0%
Memory size6.1 KiB
2024-05-04T05:01:08.953640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile15.196
Q149.5
median128.15
Q3448.63
95-th percentile1452
Maximum2753.89
Range2753.89
Interquartile range (IQR)399.13

Descriptive statistics

Standard deviation530.40526
Coefficient of variation (CV)1.4397411
Kurtosis4.605678
Mean368.40321
Median Absolute Deviation (MAD)101.45
Skewness2.1479468
Sum237251.67
Variance281329.74
MonotonicityNot monotonic
2024-05-04T05:01:09.525993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
52.0 27
 
4.0%
1450.15 17
 
2.5%
160.0 17
 
2.5%
0.0 14
 
2.1%
597.69 12
 
1.8%
156.6 12
 
1.8%
448.63 9
 
1.3%
93.58 9
 
1.3%
1454.7 8
 
1.2%
180.0 8
 
1.2%
Other values (225) 511
75.7%
(Missing) 31
 
4.6%
ValueCountFrequency (%)
0.0 14
2.1%
7.0 2
 
0.3%
8.25 1
 
0.1%
9.9 2
 
0.3%
10.0 1
 
0.1%
11.6 1
 
0.1%
12.0 2
 
0.3%
12.6 1
 
0.1%
13.2 2
 
0.3%
13.4 2
 
0.3%
ValueCountFrequency (%)
2753.89 4
0.6%
2718.3 3
 
0.4%
2255.14 4
0.6%
1912.0 3
 
0.4%
1689.2 3
 
0.4%
1677.8 2
 
0.3%
1601.99 4
0.6%
1454.7 8
1.2%
1452.0 7
1.0%
1450.5 2
 
0.3%

Interactions

2024-05-04T05:00:40.619329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T05:00:37.809883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T05:00:38.504382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T05:00:39.366840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T05:00:41.024382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T05:00:37.980474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T05:00:38.671212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T05:00:39.584395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T05:00:41.660250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T05:00:38.174380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T05:00:38.852081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T05:00:39.830290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T05:00:42.327041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T05:00:38.339565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T05:00:39.095603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T05:00:40.119328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-04T05:01:09.905273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분일자업종명업태명지도점검일자위반일자처분기간영업장면적(㎡)
처분일자1.0000.6810.6800.9860.9830.7490.308
업종명0.6811.0000.9680.6740.6810.5810.591
업태명0.6800.9681.0000.6720.6840.7490.661
지도점검일자0.9860.6740.6721.0000.9980.7970.306
위반일자0.9830.6810.6840.9981.0000.7400.298
처분기간0.7490.5810.7490.7970.7401.0000.766
영업장면적(㎡)0.3080.5910.6610.3060.2980.7661.000
2024-05-04T05:01:10.324090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업태명업종명처분기간
업태명1.0000.7840.550
업종명0.7841.0000.489
처분기간0.5500.4891.000
2024-05-04T05:01:10.691722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분일자지도점검일자위반일자영업장면적(㎡)업종명업태명처분기간
처분일자1.0000.9940.998-0.0650.3430.3450.573
지도점검일자0.9941.0000.994-0.0860.3370.3370.607
위반일자0.9980.9941.000-0.0610.3420.3480.541
영업장면적(㎡)-0.065-0.086-0.0611.0000.2810.3430.394
업종명0.3430.3370.3420.2811.0000.7840.489
업태명0.3450.3370.3480.3430.7841.0000.550
처분기간0.5730.6070.5410.3940.4890.5501.000

Missing values

2024-05-04T05:00:43.379357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-04T05:00:44.499520image/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.
2024-05-04T05:00:45.024330image/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(㎡)
03140000202403272013-486일반미용업일반미용업머리쟁이서울특별시 양천구 곰달래로5길 55, 1층 (신월동)서울특별시 양천구 신월동 143번지 8호20231220처분확정영업소폐쇄법 제11조제3항제1호20240122정당한 사유 없이 6개월 이상 계속 휴업영업소폐쇄<NA>16.5
1314000020240220268세탁업일반세탁업현대세탁소서울특별시 양천구 목동동로 130, (신정동,14단지 C상가 115호)서울특별시 양천구 신정동 329번지 0호 14단지 C상가 115호20240109처분확정직권말소법 제3조3항20240109「공중위생관리법」제3조제2항 규정을 위반하여 폐업신고 의무를 이행하지 아니함직권말소<NA>17.64
23140000202402202019-00098일반미용업일반미용업지아쌀롱서울특별시 양천구 곰달래로 48, 가동 1층 1호 (신월동)서울특별시 양천구 신월동 228번지 1호20240122처분확정영업신고사항 직권말소법 제3조3항20240122「공중위생관리법」제3조제2항 규정을 위반하여 폐업신고 의무를 이행하지 아니함영업신고사항 직권말소<NA>49.01
3314000020231127035목욕장업공동탕업금강대중목욕탕서울특별시 양천구 남부순환로80길 20, 지하 1, 1~2층 (신월동)서울특별시 양천구 신월동 1002번지 8호 지하 1~2층20231108처분확정개선명령법 제11조제1항제4호20231025욕수의 수질기준에 적합하게 욕수를 유지하지 않은 경우 1차(수질기준 부적합-대장균군 초과)개선명령<NA>449.96
4314000020231024199세탁업일반세탁업원광사세탁소서울특별시 양천구 중앙로39길 32, (신정동)서울특별시 양천구 신정동 1215번지 8호20230922처분확정직권말소법 제3조3항20230831부가가치세법에 따라 사업자등록말소,공중위생관리법 제3조 제2항을 이행하지 아니함(폐업신고)직권말소<NA>20.46
5314000020231024233세탁업일반세탁업한일컴퓨터세탁서울특별시 양천구 곰달래로5길 43-1, (신월동)서울특별시 양천구 신월동 134번지 10호20230922처분확정직권말소법 제3조3항20230428부가가치세법에 따라 사업자 등록말소, 공중위생관리법 제3조 제2항을 이행하지 아니함(폐업신고)직권말소<NA>0.0
63140000202309122019-00066일반미용업일반미용업감동헤어(감동hair)서울특별시 양천구 신월로 150, 1층 (신월동)서울특별시 양천구 신월동 549번지 1호 1층20230814처분확정경고법 제4조제4항, 제10조, 제11조, 같은 법 시행규칙 제19조20230814면허증 미게시경고<NA>33.0
7314000020230613053목욕장업공동탕업태양서울특별시 양천구 곰달래로 33, 지하1층,지상1층 (신월동)서울특별시 양천구 신월동 121번지 19호 지하1층, 지상1층20221215처분확정개선명령법 제11조제1항제4호20221219목욕물의 수질기준에 적합하게 목욕물을 유지하지 않는 경우 1차[수질기준 부적합(대장균군 초과)]개선명령<NA>197.62
83140000202305152020-00003이용업이용업 기타동광서울특별시 양천구 목동중앙서로 12, 1층 (목동)서울특별시 양천구 목동 795번지 1호20230403처분확정직권말소법 제3조3항20230403사업자 등록 말소직권말소<NA>28.0
9314000020230502015이용업일반이용업영진이용원서울특별시 양천구 목동중앙북로 89, (목동)서울특별시 양천구 목동 513번지 19호20230403처분확정직권말소법 제3조3항20230403사업자 등록 말소직권말소<NA>66.0
시군구코드처분일자교부번호업종명업태명업소명소재지도로명소재지지번지도점검일자행정처분상태처분명법적근거위반일자위반내용처분내용처분기간영업장면적(㎡)
665314000020031215179이용업일반이용업현대이용원<NA>서울특별시 양천구 신정동 900번지 13호20031119처분확정개선명령공중위생법제11조20031010음란행위 알선및제공개선명령<NA>89.1
666314000020031215179이용업일반이용업현대이용원<NA>서울특별시 양천구 신정동 900번지 13호20031119처분확정영업정지공중위생법제11조20031010음란행위 알선및제공영업정지<NA>89.1
667314000020031215179이용업일반이용업현대이용원<NA>서울특별시 양천구 신정동 900번지 13호20031119처분확정영업정지공중위생법제11조20031010음란행위 알선및제공영업정지<NA>89.1
668314000020031118036숙박업(일반)여관업백조장<NA>서울특별시 양천구 신월동 145번지 7호20031019처분확정과징금부과(180만원)청소년보호법위반20030930청소년혼숙제공과징금부과(180만원)<NA>320.49
669314000020031010088이용업일반이용업남궁이용원<NA>서울특별시 양천구 목동 650번지 7호20030918처분확정개선명령공중위생관리법제3조20030918칸막이설치개선명령<NA>160.0
670314000020031009096이용업일반이용업배명이용원<NA>서울특별시 양천구 신정동 995번지 5호20031007처분확정개선명령공중위생관리법제3조20031007의자와 의자사이에 썬팅설치개선명령<NA>79.38
671314000020030905030숙박업(일반)여관업부곡장여관<NA>서울특별시 양천구 신정동 953번지 1호20030901처분확정영업정지청소년보호법위반20030901청소년남녀혼숙영업정지<NA>313.5
672314000020030902156이용업일반이용업21세기이용원<NA>서울특별시 양천구 신월동 234번지 21호 (지층)20030829처분확정개선명령공중위생관리법 제3조20030829칸막이설치개선명령<NA>92.0
673314000020030718191이용업일반이용업월드컵<NA>서울특별시 양천구 신정동 1027번지 10호20030703처분확정영업정지공중위생관리법 제11조20030703영업소내 별실설치영업정지<NA>132.8
674314000020030516014숙박업(일반)여관업갤러리모텔<NA>서울특별시 양천구 목동 793번지 6호20020819처분확정법원의조정권고로 영업정지1개월과 과징금1000만원공중위생관리법 제11조20020726청소년보호법 위반법원의조정권고로 영업정지1개월과 과징금1000만원<NA>340.6

Duplicate rows

Most frequently occurring

시군구코드처분일자교부번호업종명업태명업소명소재지도로명소재지지번지도점검일자행정처분상태처분명법적근거위반일자위반내용처분내용처분기간영업장면적(㎡)# duplicates
44314000020131127051목욕장업공동탕업신성탕서울특별시 양천구 목동남로 58-4, 지상3,4층 (신정동)서울특별시 양천구 신정동 210번지 16호 지상3,4층20131118처분확정개선명령공중위생관리법 제4조 제2항 및 같은법 시행규칙 제19조20131118욕조수 수질기준 부적합(대장균군)개선명령<NA>438.584
59314000020190307036숙박업(일반)여관업큐(Q)모텔서울특별시 양천구 곰달래로1길 67, (신월동)서울특별시 양천구 신월동 145번지 7호20190212처분확정경고 및 과태료 50만원 부과(의견제출 기한 내 자진납부 시 40만원)법제4조제7항, 제11조제1항, 제22조제1항제2호, 같은 법 시행령 제11조 및 같은 법 시행규칙 제19조20190212객실 및 침구 등의 청결을 유지하지 아니한 때 1차 [객실 접객용 정수기(냉온수기) 필터 교체 1년 이상 안함]경고 및 과태료 50만원 부과(의견제출 기한 내 자진납부 시 40만원)<NA>320.494
10314000020040824137이용업일반이용업엔젤<NA>서울특별시 양천구 신월동 961번지 3호20040805처분확정개선명령(지위승계신고공중위생관리법제11조20040717지위승계미신고개선명령(지위승계신고<NA>52.03
11314000020040824137이용업일반이용업엔젤<NA>서울특별시 양천구 신월동 961번지 3호20040805처분확정개선명령(지위승계신고공중위생관리법제11조20040805칸막이설치개선명령(지위승계신고<NA>52.03
12314000020040824137이용업일반이용업엔젤<NA>서울특별시 양천구 신월동 961번지 3호20040805처분확정개선명령(지위승계신고풍속영업의규제에관한법률20040719윤락행위개선명령(지위승계신고<NA>52.03
13314000020040824137이용업일반이용업엔젤<NA>서울특별시 양천구 신월동 961번지 3호20040805처분확정시설개수명령공중위생관리법제11조20040717지위승계미신고시설개수명령<NA>52.03
14314000020040824137이용업일반이용업엔젤<NA>서울특별시 양천구 신월동 961번지 3호20040805처분확정시설개수명령공중위생관리법제11조20040805칸막이설치시설개수명령<NA>52.03
15314000020040824137이용업일반이용업엔젤<NA>서울특별시 양천구 신월동 961번지 3호20040805처분확정시설개수명령풍속영업의규제에관한법률20040719윤락행위시설개수명령<NA>52.03
16314000020040824137이용업일반이용업엔젤<NA>서울특별시 양천구 신월동 961번지 3호20040805처분확정영업정지공중위생관리법제11조20040717지위승계미신고영업정지<NA>52.03
17314000020040824137이용업일반이용업엔젤<NA>서울특별시 양천구 신월동 961번지 3호20040805처분확정영업정지공중위생관리법제11조20040805칸막이설치영업정지<NA>52.03