Overview

Dataset statistics

Number of variables17
Number of observations886
Missing cells973
Missing cells (%)6.5%
Duplicate rows71
Duplicate rows (%)8.0%
Total size in memory123.0 KiB
Average record size in memory142.1 B

Variable types

Categorical4
Numeric5
Text8

Dataset

Description시군구코드,처분일자,교부번호,업종명,업태명,업소명,소재지도로명,소재지지번,지도점검일자,행정처분상태,처분명,법적근거,위반일자,위반내용,처분내용,처분기간,영업장면적(㎡)
Author구로구
URLhttps://data.seoul.go.kr/dataList/OA-2297/S/1/datasetView.do

Alerts

시군구코드 has constant value ""Constant
행정처분상태 has constant value ""Constant
Dataset has 71 (8.0%) 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
영업장면적(㎡) is highly overall correlated with 업종명 and 1 other fieldsHigh correlation
업종명 is highly overall correlated with 영업장면적(㎡) and 1 other fieldsHigh correlation
업태명 is highly overall correlated with 영업장면적(㎡) and 1 other fieldsHigh correlation
교부번호 has 41 (4.6%) missing valuesMissing
소재지도로명 has 58 (6.5%) missing valuesMissing
처분기간 has 815 (92.0%) missing valuesMissing
영업장면적(㎡) has 57 (6.4%) missing valuesMissing
처분기간 has 33 (3.7%) zerosZeros
영업장면적(㎡) has 19 (2.1%) zerosZeros

Reproduction

Analysis started2024-05-10 23:21:26.782552
Analysis finished2024-05-10 23:21:39.380389
Duration12.6 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
3160000
886 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3160000
2nd row3160000
3rd row3160000
4th row3160000
5th row3160000

Common Values

ValueCountFrequency (%)
3160000 886
100.0%

Length

2024-05-10T23:21:39.539345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:21:39.849767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3160000 886
100.0%

처분일자
Real number (ℝ)

HIGH CORRELATION 

Distinct350
Distinct (%)39.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20128135
Minimum20020722
Maximum20240227
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2024-05-10T23:21:40.159516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20020722
5-th percentile20040870
Q120090601
median20130107
Q320170718
95-th percentile20211178
Maximum20240227
Range219505
Interquartile range (IQR)80116.75

Descriptive statistics

Standard deviation53117.291
Coefficient of variation (CV)0.0026389573
Kurtosis-0.77663892
Mean20128135
Median Absolute Deviation (MAD)40011
Skewness0.077193608
Sum1.7833528 × 1010
Variance2.8214466 × 109
MonotonicityNot monotonic
2024-05-10T23:21:40.494528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20191022 48
 
5.4%
20130312 24
 
2.7%
20201013 22
 
2.5%
20120323 22
 
2.5%
20060309 17
 
1.9%
20140410 16
 
1.8%
20110208 16
 
1.8%
20120511 16
 
1.8%
20140312 16
 
1.8%
20080211 12
 
1.4%
Other values (340) 677
76.4%
ValueCountFrequency (%)
20020722 1
0.1%
20020823 1
0.1%
20020924 1
0.1%
20020930 1
0.1%
20021021 1
0.1%
20021023 2
0.2%
20021028 2
0.2%
20021029 1
0.1%
20021223 1
0.1%
20030123 1
0.1%
ValueCountFrequency (%)
20240227 1
 
0.1%
20240214 2
0.2%
20240205 3
0.3%
20240123 1
 
0.1%
20231221 1
 
0.1%
20231106 1
 
0.1%
20230614 1
 
0.1%
20230524 2
0.2%
20230414 3
0.3%
20230405 3
0.3%

교부번호
Text

MISSING 

Distinct374
Distinct (%)44.3%
Missing41
Missing (%)4.6%
Memory size7.1 KiB
2024-05-10T23:21:41.056294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length3
Mean length4.6662722
Min length1

Characters and Unicode

Total characters3943
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

Unique220 ?
Unique (%)26.0%

Sample

1st row002
2nd row25300410700013
3rd row010
4th row006
5th row005
ValueCountFrequency (%)
716 24
 
2.8%
165 14
 
1.7%
161 13
 
1.5%
026 11
 
1.3%
138 11
 
1.3%
284 11
 
1.3%
358 10
 
1.2%
1221 9
 
1.1%
159 9
 
1.1%
103 8
 
0.9%
Other values (364) 725
85.8%
2024-05-10T23:21:41.976219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1128
28.6%
1 733
18.6%
2 468
11.9%
6 264
 
6.7%
3 261
 
6.6%
5 217
 
5.5%
4 199
 
5.0%
7 196
 
5.0%
- 185
 
4.7%
8 162
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3758
95.3%
Dash Punctuation 185
 
4.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1128
30.0%
1 733
19.5%
2 468
12.5%
6 264
 
7.0%
3 261
 
6.9%
5 217
 
5.8%
4 199
 
5.3%
7 196
 
5.2%
8 162
 
4.3%
9 130
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 185
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3943
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1128
28.6%
1 733
18.6%
2 468
11.9%
6 264
 
6.7%
3 261
 
6.6%
5 217
 
5.5%
4 199
 
5.0%
7 196
 
5.0%
- 185
 
4.7%
8 162
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3943
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1128
28.6%
1 733
18.6%
2 468
11.9%
6 264
 
6.7%
3 261
 
6.6%
5 217
 
5.5%
4 199
 
5.0%
7 196
 
5.0%
- 185
 
4.7%
8 162
 
4.1%

업종명
Categorical

HIGH CORRELATION 

Distinct21
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
숙박업(일반)
189 
위생관리용역업
159 
이용업
125 
일반미용업
102 
피부미용업
95 
Other values (16)
216 

Length

Max length23
Median length16
Mean length5.4401806
Min length3

Unique

Unique5 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
숙박업(일반) 189
21.3%
위생관리용역업 159
17.9%
이용업 125
14.1%
일반미용업 102
11.5%
피부미용업 95
10.7%
목욕장업 86
9.7%
세탁업 44
 
5.0%
미용업 30
 
3.4%
종합미용업 17
 
1.9%
네일미용업 14
 
1.6%
Other values (11) 25
 
2.8%

Length

2024-05-10T23:21:42.435812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
숙박업(일반 189
20.7%
위생관리용역업 159
17.4%
이용업 125
13.7%
피부미용업 107
11.7%
일반미용업 105
11.5%
목욕장업 86
9.4%
세탁업 44
 
4.8%
미용업 40
 
4.4%
네일미용업 26
 
2.8%
종합미용업 17
 
1.9%
Other values (4) 17
 
1.9%

업태명
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
위생관리용역업
158 
일반미용업
141 
일반이용업
125 
여관업
125 
피부미용업
94 
Other values (14)
243 

Length

Max length14
Median length10
Mean length5
Min length2

Unique

Unique4 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
위생관리용역업 158
17.8%
일반미용업 141
15.9%
일반이용업 125
14.1%
여관업 125
14.1%
피부미용업 94
10.6%
공동탕업 74
8.4%
여인숙업 63
 
7.1%
일반세탁업 43
 
4.9%
네일아트업 23
 
2.6%
기타 11
 
1.2%
Other values (9) 29
 
3.3%

Length

2024-05-10T23:21:42.862163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
위생관리용역업 159
17.9%
일반미용업 141
15.8%
일반이용업 125
14.0%
여관업 125
14.0%
피부미용업 94
10.6%
공동탕업 74
8.3%
여인숙업 63
 
7.1%
일반세탁업 43
 
4.8%
네일아트업 23
 
2.6%
기타 15
 
1.7%
Other values (8) 28
 
3.1%

업소명
Text

Distinct437
Distinct (%)49.3%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
2024-05-10T23:21:43.555966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length15
Mean length5.5496614
Min length1

Characters and Unicode

Total characters4917
Distinct characters407
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique269 ?
Unique (%)30.4%

Sample

1st row원선
2nd row충남
3rd row나나
4th row삼화
5th row삼화
ValueCountFrequency (%)
헤어샵 25
 
2.3%
쌍둥이 24
 
2.2%
미용실 19
 
1.7%
주식회사 18
 
1.6%
주)모스퍼실리티 13
 
1.2%
휴게이용원 11
 
1.0%
더불어 11
 
1.0%
사는 11
 
1.0%
세상 11
 
1.0%
만남 10
 
0.9%
Other values (486) 955
86.2%
2024-05-10T23:21:44.587770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
222
 
4.5%
스 136
 
2.8%
주 133
 
2.7%
( 112
 
2.3%
) 112
 
2.3%
이 110
 
2.2%
어 107
 
2.2%
리 90
 
1.8%
사 84
 
1.7%
헤 81
 
1.6%
Other values (397) 3730
75.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4205
85.5%
Space Separator 222
 
4.5%
Lowercase Letter 115
 
2.3%
Open Punctuation 112
 
2.3%
Close Punctuation 112
 
2.3%
Uppercase Letter 103
 
2.1%
Other Punctuation 27
 
0.5%
Decimal Number 19
 
0.4%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 136
 
3.2%
주 133
 
3.2%
이 110
 
2.6%
어 107
 
2.5%
리 90
 
2.1%
사 84
 
2.0%
헤 81
 
1.9%
용 76
 
1.8%
원 72
 
1.7%
미 72
 
1.7%
Other values (342) 3244
77.1%
Uppercase Letter
ValueCountFrequency (%)
N 12
 
11.7%
A 11
 
10.7%
S 10
 
9.7%
O 7
 
6.8%
H 6
 
5.8%
I 6
 
5.8%
L 6
 
5.8%
T 5
 
4.9%
C 5
 
4.9%
R 4
 
3.9%
Other values (13) 31
30.1%
Lowercase Letter
ValueCountFrequency (%)
a 17
14.8%
e 15
13.0%
l 11
9.6%
o 9
7.8%
n 8
 
7.0%
i 8
 
7.0%
s 7
 
6.1%
m 7
 
6.1%
t 6
 
5.2%
h 5
 
4.3%
Other values (9) 22
19.1%
Other Punctuation
ValueCountFrequency (%)
？ 11
40.7%
& 8
29.6%
; 3
 
11.1%
' 2
 
7.4%
. 2
 
7.4%
, 1
 
3.7%
Decimal Number
ValueCountFrequency (%)
7 12
63.2%
2 5
26.3%
4 2
 
10.5%
Space Separator
ValueCountFrequency (%)
222
100.0%
Open Punctuation
ValueCountFrequency (%)
( 112
100.0%
Close Punctuation
ValueCountFrequency (%)
) 112
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4202
85.5%
Common 494
 
10.0%
Latin 218
 
4.4%
Han 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 136
 
3.2%
주 133
 
3.2%
이 110
 
2.6%
어 107
 
2.5%
리 90
 
2.1%
사 84
 
2.0%
헤 81
 
1.9%
용 76
 
1.8%
원 72
 
1.7%
미 72
 
1.7%
Other values (340) 3241
77.1%
Latin
ValueCountFrequency (%)
a 17
 
7.8%
e 15
 
6.9%
N 12
 
5.5%
A 11
 
5.0%
l 11
 
5.0%
S 10
 
4.6%
o 9
 
4.1%
n 8
 
3.7%
i 8
 
3.7%
s 7
 
3.2%
Other values (32) 110
50.5%
Common
ValueCountFrequency (%)
222
44.9%
( 112
22.7%
) 112
22.7%
7 12
 
2.4%
？ 11
 
2.2%
& 8
 
1.6%
2 5
 
1.0%
; 3
 
0.6%
' 2
 
0.4%
. 2
 
0.4%
Other values (3) 5
 
1.0%
Han
ValueCountFrequency (%)
美 2
66.7%
華 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4202
85.5%
ASCII 701
 
14.3%
None 11
 
0.2%
CJK 3
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
222
31.7%
( 112
16.0%
) 112
16.0%
a 17
 
2.4%
e 15
 
2.1%
7 12
 
1.7%
N 12
 
1.7%
A 11
 
1.6%
l 11
 
1.6%
S 10
 
1.4%
Other values (44) 167
23.8%
Hangul
ValueCountFrequency (%)
스 136
 
3.2%
주 133
 
3.2%
이 110
 
2.6%
어 107
 
2.5%
리 90
 
2.1%
사 84
 
2.0%
헤 81
 
1.9%
용 76
 
1.8%
원 72
 
1.7%
미 72
 
1.7%
Other values (340) 3241
77.1%
None
ValueCountFrequency (%)
？ 11
100.0%
CJK
ValueCountFrequency (%)
美 2
66.7%
華 1
33.3%

소재지도로명
Text

MISSING 

Distinct408
Distinct (%)49.3%
Missing58
Missing (%)6.5%
Memory size7.1 KiB
2024-05-10T23:21:45.171040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length49
Mean length31.836957
Min length23

Characters and Unicode

Total characters26361
Distinct characters241
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

Unique254 ?
Unique (%)30.7%

Sample

1st row서울특별시 구로구 구로동로22길 5-14, (구로동)
2nd row서울특별시 구로구 구로동로26길 55-8, (구로동)
3rd row서울특별시 구로구 경인로15길 8-6, (오류동)
4th row서울특별시 구로구 구로동로35길 13, (구로동)
5th row서울특별시 구로구 구로동로35길 13, (구로동)
ValueCountFrequency (%)
서울특별시 828
 
17.4%
구로구 828
 
17.4%
구로동 263
 
5.5%
개봉동 114
 
2.4%
오류동 72
 
1.5%
경인로 70
 
1.5%
가리봉동 47
 
1.0%
고척동 39
 
0.8%
구로중앙로 38
 
0.8%
36 34
 
0.7%
Other values (666) 2418
50.9%
2024-05-10T23:21:46.198075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3923
 
14.9%
구 2287
 
8.7%
로 2255
 
8.6%
, 1183
 
4.5%
동 1028
 
3.9%
( 906
 
3.4%
) 906
 
3.4%
1 864
 
3.3%
서 842
 
3.2%
시 834
 
3.2%
Other values (231) 11333
43.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15161
57.5%
Decimal Number 4036
 
15.3%
Space Separator 3923
 
14.9%
Other Punctuation 1185
 
4.5%
Open Punctuation 906
 
3.4%
Close Punctuation 906
 
3.4%
Dash Punctuation 145
 
0.6%
Uppercase Letter 97
 
0.4%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 2287
15.1%
로 2255
14.9%
동 1028
 
6.8%
서 842
 
5.6%
시 834
 
5.5%
울 830
 
5.5%
별 828
 
5.5%
특 828
 
5.5%
길 594
 
3.9%
봉 263
 
1.7%
Other values (200) 4572
30.2%
Uppercase Letter
ValueCountFrequency (%)
B 29
29.9%
A 16
16.5%
E 12
12.4%
I 8
 
8.2%
K 7
 
7.2%
L 4
 
4.1%
S 4
 
4.1%
V 4
 
4.1%
O 3
 
3.1%
U 3
 
3.1%
Other values (4) 7
 
7.2%
Decimal Number
ValueCountFrequency (%)
1 864
21.4%
2 619
15.3%
3 513
12.7%
5 377
9.3%
0 368
9.1%
6 295
 
7.3%
4 291
 
7.2%
7 264
 
6.5%
8 246
 
6.1%
9 199
 
4.9%
Other Punctuation
ValueCountFrequency (%)
, 1183
99.8%
. 2
 
0.2%
Space Separator
ValueCountFrequency (%)
3923
100.0%
Open Punctuation
ValueCountFrequency (%)
( 906
100.0%
Close Punctuation
ValueCountFrequency (%)
) 906
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 145
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15161
57.5%
Common 11101
42.1%
Latin 99
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 2287
15.1%
로 2255
14.9%
동 1028
 
6.8%
서 842
 
5.6%
시 834
 
5.5%
울 830
 
5.5%
별 828
 
5.5%
특 828
 
5.5%
길 594
 
3.9%
봉 263
 
1.7%
Other values (200) 4572
30.2%
Common
ValueCountFrequency (%)
3923
35.3%
, 1183
 
10.7%
( 906
 
8.2%
) 906
 
8.2%
1 864
 
7.8%
2 619
 
5.6%
3 513
 
4.6%
5 377
 
3.4%
0 368
 
3.3%
6 295
 
2.7%
Other values (6) 1147
 
10.3%
Latin
ValueCountFrequency (%)
B 29
29.3%
A 16
16.2%
E 12
12.1%
I 8
 
8.1%
K 7
 
7.1%
L 4
 
4.0%
S 4
 
4.0%
V 4
 
4.0%
O 3
 
3.0%
U 3
 
3.0%
Other values (5) 9
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15161
57.5%
ASCII 11200
42.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3923
35.0%
, 1183
 
10.6%
( 906
 
8.1%
) 906
 
8.1%
1 864
 
7.7%
2 619
 
5.5%
3 513
 
4.6%
5 377
 
3.4%
0 368
 
3.3%
6 295
 
2.6%
Other values (21) 1246
 
11.1%
Hangul
ValueCountFrequency (%)
구 2287
15.1%
로 2255
14.9%
동 1028
 
6.8%
서 842
 
5.6%
시 834
 
5.5%
울 830
 
5.5%
별 828
 
5.5%
특 828
 
5.5%
길 594
 
3.9%
봉 263
 
1.7%
Other values (200) 4572
30.2%

소재지지번
Text

Distinct425
Distinct (%)48.1%
Missing2
Missing (%)0.2%
Memory size7.1 KiB
2024-05-10T23:21:46.724252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length49
Mean length29.602941
Min length21

Characters and Unicode

Total characters26169
Distinct characters226
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

Unique258 ?
Unique (%)29.2%

Sample

1st row서울특별시 구로구 구로동 733번지 35호
2nd row서울특별시 구로구 구로동 730번지 29호
3rd row서울특별시 구로구 오류동 6번지 114호
4th row서울특별시 구로구 구로동 414번지 30호
5th row서울특별시 구로구 구로동 414번지 30호
ValueCountFrequency (%)
구로구 891
 
17.6%
서울특별시 884
 
17.5%
구로동 416
 
8.2%
개봉동 136
 
2.7%
오류동 134
 
2.7%
가리봉동 72
 
1.4%
고척동 68
 
1.3%
3층 57
 
1.1%
1호 55
 
1.1%
2호 38
 
0.8%
Other values (557) 2302
45.6%
2024-05-10T23:21:47.572742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6384
24.4%
구 2239
 
8.6%
로 1345
 
5.1%
1 1066
 
4.1%
지 959
 
3.7%
호 919
 
3.5%
동 911
 
3.5%
시 887
 
3.4%
울 886
 
3.4%
서 885
 
3.4%
Other values (216) 9688
37.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14452
55.2%
Space Separator 6384
24.4%
Decimal Number 4914
 
18.8%
Dash Punctuation 129
 
0.5%
Uppercase Letter 98
 
0.4%
Open Punctuation 81
 
0.3%
Close Punctuation 81
 
0.3%
Other Punctuation 28
 
0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 2239
15.5%
로 1345
 
9.3%
지 959
 
6.6%
호 919
 
6.4%
동 911
 
6.3%
시 887
 
6.1%
울 886
 
6.1%
서 885
 
6.1%
번 885
 
6.1%
별 884
 
6.1%
Other values (184) 3652
25.3%
Uppercase Letter
ValueCountFrequency (%)
B 29
29.6%
A 16
16.3%
E 12
12.2%
I 8
 
8.2%
K 7
 
7.1%
V 4
 
4.1%
L 4
 
4.1%
S 4
 
4.1%
U 3
 
3.1%
O 3
 
3.1%
Other values (5) 8
 
8.2%
Decimal Number
ValueCountFrequency (%)
1 1066
21.7%
3 625
12.7%
4 587
11.9%
2 558
11.4%
5 489
10.0%
0 444
9.0%
7 367
 
7.5%
6 345
 
7.0%
8 284
 
5.8%
9 149
 
3.0%
Other Punctuation
ValueCountFrequency (%)
, 26
92.9%
. 2
 
7.1%
Space Separator
ValueCountFrequency (%)
6384
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 129
100.0%
Open Punctuation
ValueCountFrequency (%)
( 81
100.0%
Close Punctuation
ValueCountFrequency (%)
) 81
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14452
55.2%
Common 11617
44.4%
Latin 100
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 2239
15.5%
로 1345
 
9.3%
지 959
 
6.6%
호 919
 
6.4%
동 911
 
6.3%
시 887
 
6.1%
울 886
 
6.1%
서 885
 
6.1%
번 885
 
6.1%
별 884
 
6.1%
Other values (184) 3652
25.3%
Common
ValueCountFrequency (%)
6384
55.0%
1 1066
 
9.2%
3 625
 
5.4%
4 587
 
5.1%
2 558
 
4.8%
5 489
 
4.2%
0 444
 
3.8%
7 367
 
3.2%
6 345
 
3.0%
8 284
 
2.4%
Other values (6) 468
 
4.0%
Latin
ValueCountFrequency (%)
B 29
29.0%
A 16
16.0%
E 12
12.0%
I 8
 
8.0%
K 7
 
7.0%
V 4
 
4.0%
L 4
 
4.0%
S 4
 
4.0%
U 3
 
3.0%
O 3
 
3.0%
Other values (6) 10
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14452
55.2%
ASCII 11717
44.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6384
54.5%
1 1066
 
9.1%
3 625
 
5.3%
4 587
 
5.0%
2 558
 
4.8%
5 489
 
4.2%
0 444
 
3.8%
7 367
 
3.1%
6 345
 
2.9%
8 284
 
2.4%
Other values (22) 568
 
4.8%
Hangul
ValueCountFrequency (%)
구 2239
15.5%
로 1345
 
9.3%
지 959
 
6.6%
호 919
 
6.4%
동 911
 
6.3%
시 887
 
6.1%
울 886
 
6.1%
서 885
 
6.1%
번 885
 
6.1%
별 884
 
6.1%
Other values (184) 3652
25.3%

지도점검일자
Real number (ℝ)

HIGH CORRELATION 

Distinct319
Distinct (%)36.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20126093
Minimum20020509
Maximum20240205
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2024-05-10T23:21:47.855563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20020509
5-th percentile20040618
Q120090215
median20121009
Q320170125
95-th percentile20211035
Maximum20240205
Range219696
Interquartile range (IQR)79910

Descriptive statistics

Standard deviation52780.097
Coefficient of variation (CV)0.0026224711
Kurtosis-0.79879913
Mean20126093
Median Absolute Deviation (MAD)40193
Skewness0.072197749
Sum1.7831718 × 1010
Variance2.7857386 × 109
MonotonicityNot monotonic
2024-05-10T23:21:48.137710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20190102 65
 
7.3%
20130205 28
 
3.2%
20120319 24
 
2.7%
20140127 24
 
2.7%
20110112 22
 
2.5%
20200807 21
 
2.4%
20121226 16
 
1.8%
20130308 16
 
1.8%
20181129 13
 
1.5%
20060309 12
 
1.4%
Other values (309) 645
72.8%
ValueCountFrequency (%)
20020509 1
0.1%
20020624 1
0.1%
20020716 1
0.1%
20020906 1
0.1%
20020919 2
0.2%
20020927 2
0.2%
20021011 1
0.1%
20021015 1
0.1%
20021130 1
0.1%
20021215 1
0.1%
ValueCountFrequency (%)
20240205 1
 
0.1%
20231202 1
 
0.1%
20231013 1
 
0.1%
20231009 1
 
0.1%
20230912 1
 
0.1%
20230714 4
 
0.5%
20230330 1
 
0.1%
20230221 12
1.4%
20230126 1
 
0.1%
20230119 1
 
0.1%

행정처분상태
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
처분확정
886 

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 886
100.0%

Length

2024-05-10T23:21:48.537797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:21:48.856400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
처분확정 886
100.0%

처분명
Text

Distinct142
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
2024-05-10T23:21:49.324425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length38
Mean length8.1557562
Min length2

Characters and Unicode

Total characters7226
Distinct characters132
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

Unique69 ?
Unique (%)7.8%

Sample

1st row영업정지 2월(2009.6.2~8.2)
2nd row영업정지
3rd row과징금부과
4th row영업정지
5th row영업정지 1월
ValueCountFrequency (%)
경고 140
 
10.0%
과태료부과 132
 
9.4%
부과 106
 
7.6%
과태료 105
 
7.5%
영업정지 87
 
6.2%
영업소폐쇄 77
 
5.5%
과징금부과 72
 
5.1%
개선명령 68
 
4.8%
20만원 43
 
3.1%
과징금 39
 
2.8%
Other values (149) 534
38.1%
2024-05-10T23:21:50.154965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 887
 
12.3%
518
 
7.2%
부 454
 
6.3%
0 393
 
5.4%
료 320
 
4.4%
태 314
 
4.3%
업 243
 
3.4%
영 238
 
3.3%
2 233
 
3.2%
원 231
 
3.2%
Other values (122) 3395
47.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5278
73.0%
Decimal Number 1012
 
14.0%
Space Separator 518
 
7.2%
Other Punctuation 143
 
2.0%
Open Punctuation 127
 
1.8%
Close Punctuation 125
 
1.7%
Math Symbol 14
 
0.2%
Dash Punctuation 9
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 887
16.8%
부 454
 
8.6%
료 320
 
6.1%
태 314
 
5.9%
업 243
 
4.6%
영 238
 
4.5%
원 231
 
4.4%
만 187
 
3.5%
정 177
 
3.4%
지 175
 
3.3%
Other values (102) 2052
38.9%
Decimal Number
ValueCountFrequency (%)
0 393
38.8%
2 233
23.0%
1 147
 
14.5%
6 73
 
7.2%
5 42
 
4.2%
4 35
 
3.5%
3 34
 
3.4%
8 29
 
2.9%
9 18
 
1.8%
7 8
 
0.8%
Other Punctuation
ValueCountFrequency (%)
, 85
59.4%
. 51
35.7%
* 6
 
4.2%
% 1
 
0.7%
Math Symbol
ValueCountFrequency (%)
~ 8
57.1%
= 6
42.9%
Space Separator
ValueCountFrequency (%)
518
100.0%
Open Punctuation
ValueCountFrequency (%)
( 127
100.0%
Close Punctuation
ValueCountFrequency (%)
) 125
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5278
73.0%
Common 1948
 
27.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 887
16.8%
부 454
 
8.6%
료 320
 
6.1%
태 314
 
5.9%
업 243
 
4.6%
영 238
 
4.5%
원 231
 
4.4%
만 187
 
3.5%
정 177
 
3.4%
지 175
 
3.3%
Other values (102) 2052
38.9%
Common
ValueCountFrequency (%)
518
26.6%
0 393
20.2%
2 233
12.0%
1 147
 
7.5%
( 127
 
6.5%
) 125
 
6.4%
, 85
 
4.4%
6 73
 
3.7%
. 51
 
2.6%
5 42
 
2.2%
Other values (10) 154
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5278
73.0%
ASCII 1948
 
27.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 887
16.8%
부 454
 
8.6%
료 320
 
6.1%
태 314
 
5.9%
업 243
 
4.6%
영 238
 
4.5%
원 231
 
4.4%
만 187
 
3.5%
정 177
 
3.4%
지 175
 
3.3%
Other values (102) 2052
38.9%
ASCII
ValueCountFrequency (%)
518
26.6%
0 393
20.2%
2 233
12.0%
1 147
 
7.5%
( 127
 
6.5%
) 125
 
6.4%
, 85
 
4.4%
6 73
 
3.7%
. 51
 
2.6%
5 42
 
2.2%
Other values (10) 154
 
7.9%

법적근거
Text

Distinct160
Distinct (%)18.1%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
2024-05-10T23:21:50.595595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length48
Mean length20.817156
Min length6

Characters and Unicode

Total characters18444
Distinct characters63
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

Unique67 ?
Unique (%)7.6%

Sample

1st row공중위생관리법제11조제1항
2nd row공중위생관리법11조1항
3rd row공중위생관리법 제11조제1항
4th row풍속영업의규제에관한법률
5th row공중위생관리법 제11조 1항
ValueCountFrequency (%)
공중위생관리법 619
19.0%
동법 268
 
8.2%
적용 246
 
7.5%
위반 246
 
7.5%
및 208
 
6.4%
제17조제1항 146
 
4.5%
제17조 132
 
4.0%
법 105
 
3.2%
제22조 101
 
3.1%
제2항 98
 
3.0%
Other values (122) 1095
33.5%
2024-05-10T23:21:51.542516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2390
13.0%
제 2143
11.6%
1 1640
 
8.9%
조 1289
 
7.0%
법 1205
 
6.5%
항 1041
 
5.6%
위 1033
 
5.6%
2 876
 
4.7%
중 780
 
4.2%
공 780
 
4.2%
Other values (53) 5267
28.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12342
66.9%
Decimal Number 3459
 
18.8%
Space Separator 2390
 
13.0%
Other Punctuation 245
 
1.3%
Open Punctuation 4
 
< 0.1%
Close Punctuation 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 2143
17.4%
조 1289
10.4%
법 1205
9.8%
항 1041
8.4%
위 1033
8.4%
중 780
 
6.3%
공 780
 
6.3%
생 780
 
6.3%
관 775
 
6.3%
리 769
 
6.2%
Other values (39) 1747
14.2%
Decimal Number
ValueCountFrequency (%)
1 1640
47.4%
2 876
25.3%
7 412
 
11.9%
3 283
 
8.2%
4 102
 
2.9%
6 57
 
1.6%
9 52
 
1.5%
8 16
 
0.5%
0 16
 
0.5%
5 5
 
0.1%
Space Separator
ValueCountFrequency (%)
2390
100.0%
Other Punctuation
ValueCountFrequency (%)
, 245
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12342
66.9%
Common 6102
33.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 2143
17.4%
조 1289
10.4%
법 1205
9.8%
항 1041
8.4%
위 1033
8.4%
중 780
 
6.3%
공 780
 
6.3%
생 780
 
6.3%
관 775
 
6.3%
리 769
 
6.2%
Other values (39) 1747
14.2%
Common
ValueCountFrequency (%)
2390
39.2%
1 1640
26.9%
2 876
 
14.4%
7 412
 
6.8%
3 283
 
4.6%
, 245
 
4.0%
4 102
 
1.7%
6 57
 
0.9%
9 52
 
0.9%
8 16
 
0.3%
Other values (4) 29
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12342
66.9%
ASCII 6102
33.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2390
39.2%
1 1640
26.9%
2 876
 
14.4%
7 412
 
6.8%
3 283
 
4.6%
, 245
 
4.0%
4 102
 
1.7%
6 57
 
0.9%
9 52
 
0.9%
8 16
 
0.3%
Other values (4) 29
 
0.5%
Hangul
ValueCountFrequency (%)
제 2143
17.4%
조 1289
10.4%
법 1205
9.8%
항 1041
8.4%
위 1033
8.4%
중 780
 
6.3%
공 780
 
6.3%
생 780
 
6.3%
관 775
 
6.3%
리 769
 
6.2%
Other values (39) 1747
14.2%

위반일자
Real number (ℝ)

HIGH CORRELATION 

Distinct321
Distinct (%)36.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20125647
Minimum20011001
Maximum20240205
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2024-05-10T23:21:51.830323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20011001
5-th percentile20040539
Q120090215
median20121013
Q320170125
95-th percentile20210984
Maximum20240205
Range229204
Interquartile range (IQR)79910

Descriptive statistics

Standard deviation53016.894
Coefficient of variation (CV)0.0026342952
Kurtosis-0.8070062
Mean20125647
Median Absolute Deviation (MAD)40189
Skewness0.069859382
Sum1.7831323 × 1010
Variance2.810791 × 109
MonotonicityNot monotonic
2024-05-10T23:21:52.294513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20190102 64
 
7.2%
20130205 28
 
3.2%
20140127 24
 
2.7%
20120224 24
 
2.7%
20200807 22
 
2.5%
20101231 20
 
2.3%
20130308 16
 
1.8%
20121226 14
 
1.6%
20181128 13
 
1.5%
20230221 12
 
1.4%
Other values (311) 649
73.3%
ValueCountFrequency (%)
20011001 1
0.1%
20020509 1
0.1%
20020624 1
0.1%
20020716 1
0.1%
20020906 1
0.1%
20020919 2
0.2%
20020927 2
0.2%
20021011 1
0.1%
20021015 1
0.1%
20021130 1
0.1%
ValueCountFrequency (%)
20240205 1
 
0.1%
20231202 1
 
0.1%
20231009 1
 
0.1%
20230912 1
 
0.1%
20230714 4
 
0.5%
20230330 1
 
0.1%
20230221 12
1.4%
20230126 1
 
0.1%
20230119 1
 
0.1%
20230117 5
0.6%

위반내용
Text

Distinct233
Distinct (%)26.3%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
2024-05-10T23:21:52.767808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length136
Median length64
Mean length15.339729
Min length4

Characters and Unicode

Total characters13591
Distinct characters262
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique117 ?
Unique (%)13.2%

Sample

1st row성매매알선등
2nd row 윤락행위알선
3rd row청소년 이성혼숙
4th row윤락행위알선제공
5th row윤락행위알선장소제공
ValueCountFrequency (%)
위생교육 349
 
12.2%
미이수 286
 
10.0%
및 96
 
3.4%
2012년 70
 
2.4%
2018년 65
 
2.3%
청소년 55
 
1.9%
청소년이성혼숙 41
 
1.4%
2011년 40
 
1.4%
이성혼숙 39
 
1.4%
미수료 38
 
1.3%
Other values (401) 1785
62.3%
2024-05-10T23:21:53.894287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2031
 
14.9%
위 592
 
4.4%
이 520
 
3.8%
2 498
 
3.7%
년 484
 
3.6%
0 456
 
3.4%
미 442
 
3.3%
생 434
 
3.2%
업 431
 
3.2%
수 400
 
2.9%
Other values (252) 7303
53.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9701
71.4%
Space Separator 2031
 
14.9%
Decimal Number 1553
 
11.4%
Close Punctuation 104
 
0.8%
Open Punctuation 104
 
0.8%
Other Punctuation 89
 
0.7%
Math Symbol 7
 
0.1%
Other Symbol 1
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
위 592
 
6.1%
이 520
 
5.4%
년 484
 
5.0%
미 442
 
4.6%
생 434
 
4.5%
업 431
 
4.4%
수 400
 
4.1%
육 378
 
3.9%
교 378
 
3.9%
소 238
 
2.5%
Other values (230) 5404
55.7%
Decimal Number
ValueCountFrequency (%)
2 498
32.1%
0 456
29.4%
1 371
23.9%
8 67
 
4.3%
3 55
 
3.5%
9 34
 
2.2%
5 27
 
1.7%
7 26
 
1.7%
4 14
 
0.9%
6 5
 
0.3%
Other Punctuation
ValueCountFrequency (%)
: 34
38.2%
. 27
30.3%
, 19
21.3%
/ 9
 
10.1%
Close Punctuation
ValueCountFrequency (%)
) 103
99.0%
] 1
 
1.0%
Open Punctuation
ValueCountFrequency (%)
( 103
99.0%
[ 1
 
1.0%
Space Separator
ValueCountFrequency (%)
2031
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%
Other Symbol
ValueCountFrequency (%)
○ 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9701
71.4%
Common 3890
28.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
위 592
 
6.1%
이 520
 
5.4%
년 484
 
5.0%
미 442
 
4.6%
생 434
 
4.5%
업 431
 
4.4%
수 400
 
4.1%
육 378
 
3.9%
교 378
 
3.9%
소 238
 
2.5%
Other values (230) 5404
55.7%
Common
ValueCountFrequency (%)
2031
52.2%
2 498
 
12.8%
0 456
 
11.7%
1 371
 
9.5%
) 103
 
2.6%
( 103
 
2.6%
8 67
 
1.7%
3 55
 
1.4%
9 34
 
0.9%
: 34
 
0.9%
Other values (12) 138
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9701
71.4%
ASCII 3889
28.6%
Geometric Shapes 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2031
52.2%
2 498
 
12.8%
0 456
 
11.7%
1 371
 
9.5%
) 103
 
2.6%
( 103
 
2.6%
8 67
 
1.7%
3 55
 
1.4%
9 34
 
0.9%
: 34
 
0.9%
Other values (11) 137
 
3.5%
Hangul
ValueCountFrequency (%)
위 592
 
6.1%
이 520
 
5.4%
년 484
 
5.0%
미 442
 
4.6%
생 434
 
4.5%
업 431
 
4.4%
수 400
 
4.1%
육 378
 
3.9%
교 378
 
3.9%
소 238
 
2.5%
Other values (230) 5404
55.7%
Geometric Shapes
ValueCountFrequency (%)
○ 1
100.0%

처분내용
Text

Distinct142
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
2024-05-10T23:21:54.378131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length38
Mean length8.1557562
Min length2

Characters and Unicode

Total characters7226
Distinct characters132
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

Unique69 ?
Unique (%)7.8%

Sample

1st row영업정지 2월(2009.6.2~8.2)
2nd row영업정지
3rd row과징금부과
4th row영업정지
5th row영업정지 1월
ValueCountFrequency (%)
경고 140
 
10.0%
과태료부과 132
 
9.4%
부과 106
 
7.6%
과태료 105
 
7.5%
영업정지 87
 
6.2%
영업소폐쇄 77
 
5.5%
과징금부과 72
 
5.1%
개선명령 68
 
4.8%
20만원 43
 
3.1%
과징금 39
 
2.8%
Other values (149) 534
38.1%
2024-05-10T23:21:55.357315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 887
 
12.3%
518
 
7.2%
부 454
 
6.3%
0 393
 
5.4%
료 320
 
4.4%
태 314
 
4.3%
업 243
 
3.4%
영 238
 
3.3%
2 233
 
3.2%
원 231
 
3.2%
Other values (122) 3395
47.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5278
73.0%
Decimal Number 1012
 
14.0%
Space Separator 518
 
7.2%
Other Punctuation 143
 
2.0%
Open Punctuation 127
 
1.8%
Close Punctuation 125
 
1.7%
Math Symbol 14
 
0.2%
Dash Punctuation 9
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 887
16.8%
부 454
 
8.6%
료 320
 
6.1%
태 314
 
5.9%
업 243
 
4.6%
영 238
 
4.5%
원 231
 
4.4%
만 187
 
3.5%
정 177
 
3.4%
지 175
 
3.3%
Other values (102) 2052
38.9%
Decimal Number
ValueCountFrequency (%)
0 393
38.8%
2 233
23.0%
1 147
 
14.5%
6 73
 
7.2%
5 42
 
4.2%
4 35
 
3.5%
3 34
 
3.4%
8 29
 
2.9%
9 18
 
1.8%
7 8
 
0.8%
Other Punctuation
ValueCountFrequency (%)
, 85
59.4%
. 51
35.7%
* 6
 
4.2%
% 1
 
0.7%
Math Symbol
ValueCountFrequency (%)
~ 8
57.1%
= 6
42.9%
Space Separator
ValueCountFrequency (%)
518
100.0%
Open Punctuation
ValueCountFrequency (%)
( 127
100.0%
Close Punctuation
ValueCountFrequency (%)
) 125
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5278
73.0%
Common 1948
 
27.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 887
16.8%
부 454
 
8.6%
료 320
 
6.1%
태 314
 
5.9%
업 243
 
4.6%
영 238
 
4.5%
원 231
 
4.4%
만 187
 
3.5%
정 177
 
3.4%
지 175
 
3.3%
Other values (102) 2052
38.9%
Common
ValueCountFrequency (%)
518
26.6%
0 393
20.2%
2 233
12.0%
1 147
 
7.5%
( 127
 
6.5%
) 125
 
6.4%
, 85
 
4.4%
6 73
 
3.7%
. 51
 
2.6%
5 42
 
2.2%
Other values (10) 154
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5278
73.0%
ASCII 1948
 
27.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 887
16.8%
부 454
 
8.6%
료 320
 
6.1%
태 314
 
5.9%
업 243
 
4.6%
영 238
 
4.5%
원 231
 
4.4%
만 187
 
3.5%
정 177
 
3.4%
지 175
 
3.3%
Other values (102) 2052
38.9%
ASCII
ValueCountFrequency (%)
518
26.6%
0 393
20.2%
2 233
12.0%
1 147
 
7.5%
( 127
 
6.5%
) 125
 
6.4%
, 85
 
4.4%
6 73
 
3.7%
. 51
 
2.6%
5 42
 
2.2%
Other values (10) 154
 
7.9%

처분기간
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)16.9%
Missing815
Missing (%)92.0%
Infinite0
Infinite (%)0.0%
Mean11.070423
Minimum0
Maximum61
Zeros33
Zeros (%)3.7%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2024-05-10T23:21:55.730099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q315
95-th percentile52.5
Maximum61
Range61
Interquartile range (IQR)15

Descriptive statistics

Standard deviation15.506979
Coefficient of variation (CV)1.4007576
Kurtosis3.7558159
Mean11.070423
Median Absolute Deviation (MAD)5
Skewness1.9417012
Sum786
Variance240.4664
MonotonicityNot monotonic
2024-05-10T23:21:56.133007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 33
 
3.7%
15 13
 
1.5%
22 6
 
0.7%
10 4
 
0.5%
5 4
 
0.5%
60 3
 
0.3%
30 2
 
0.2%
7 2
 
0.2%
61 1
 
0.1%
45 1
 
0.1%
Other values (2) 2
 
0.2%
(Missing) 815
92.0%
ValueCountFrequency (%)
0 33
3.7%
5 4
 
0.5%
7 2
 
0.2%
10 4
 
0.5%
15 13
 
1.5%
19 1
 
0.1%
20 1
 
0.1%
22 6
 
0.7%
30 2
 
0.2%
45 1
 
0.1%
ValueCountFrequency (%)
61 1
 
0.1%
60 3
 
0.3%
45 1
 
0.1%
30 2
 
0.2%
22 6
0.7%
20 1
 
0.1%
19 1
 
0.1%
15 13
1.5%
10 4
 
0.5%
7 2
 
0.2%

영업장면적(㎡)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct332
Distinct (%)40.0%
Missing57
Missing (%)6.4%
Infinite0
Infinite (%)0.0%
Mean275.23201
Minimum0
Maximum21131.68
Zeros19
Zeros (%)2.1%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2024-05-10T23:21:56.594863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile15
Q128
median70
Q3206
95-th percentile1023.188
Maximum21131.68
Range21131.68
Interquartile range (IQR)178

Descriptive statistics

Standard deviation886.69901
Coefficient of variation (CV)3.221642
Kurtosis374.03785
Mean275.23201
Median Absolute Deviation (MAD)50
Skewness16.734023
Sum228167.34
Variance786235.13
MonotonicityNot monotonic
2024-05-10T23:21:56.879375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20.0 35
 
4.0%
26.4 20
 
2.3%
0.0 19
 
2.1%
16.52 13
 
1.5%
136.0 11
 
1.2%
16.5 11
 
1.2%
97.53 11
 
1.2%
120.0 10
 
1.1%
117.0 9
 
1.0%
66.0 9
 
1.0%
Other values (322) 681
76.9%
(Missing) 57
 
6.4%
ValueCountFrequency (%)
0.0 19
2.1%
5.0 1
 
0.1%
6.0 1
 
0.1%
10.0 2
 
0.2%
10.09 1
 
0.1%
10.39 1
 
0.1%
10.78 1
 
0.1%
10.98 1
 
0.1%
12.1 5
 
0.6%
13.0 1
 
0.1%
ValueCountFrequency (%)
21131.68 1
 
0.1%
6240.24 1
 
0.1%
4225.19 1
 
0.1%
4198.0 1
 
0.1%
3995.0 2
0.2%
3072.42 1
 
0.1%
2858.88 1
 
0.1%
2268.0 4
0.5%
2108.7 3
0.3%
1728.45 1
 
0.1%

Interactions

2024-05-10T23:21:36.547812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:21:29.579189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:21:31.305511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:21:33.452420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:21:35.210324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:21:36.812307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:21:29.881567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:21:31.683280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:21:33.804449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:21:35.482590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:21:37.041949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:21:30.163436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:21:32.102830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:21:34.198636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:21:35.755655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:21:37.333815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:21:30.459202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:21:32.445892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:21:34.585853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:21:36.036791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:21:37.581623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:21:30.818392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:21:32.876804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:21:34.932322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:21:36.302260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-10T23:21:57.250585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분일자업종명업태명지도점검일자위반일자처분기간영업장면적(㎡)
처분일자1.0000.6150.6200.9980.9850.8530.214
업종명0.6151.0000.9720.6090.6240.5230.809
업태명0.6200.9721.0000.6190.6340.5990.943
지도점검일자0.9980.6090.6191.0000.9910.7100.184
위반일자0.9850.6240.6340.9911.0000.8920.216
처분기간0.8530.5230.5990.7100.8921.000NaN
영업장면적(㎡)0.2140.8090.9430.1840.216NaN1.000
2024-05-10T23:21:57.460861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명업태명
업종명1.0000.769
업태명0.7691.000
2024-05-10T23:21:57.618597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분일자지도점검일자위반일자처분기간영업장면적(㎡)업종명업태명
처분일자1.0000.9960.9950.184-0.3580.2770.285
지도점검일자0.9961.0001.0000.175-0.3690.2730.284
위반일자0.9951.0001.0000.158-0.3700.2840.295
처분기간0.1840.1750.1581.000-0.0780.2020.363
영업장면적(㎡)-0.358-0.369-0.370-0.0781.0000.5830.826
업종명0.2770.2730.2840.2020.5831.0000.769
업태명0.2850.2840.2950.3630.8260.7691.000

Missing values

2024-05-10T23:21:37.924331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-10T23:21:38.798080image/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.
2024-05-10T23:21:39.248824image/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(㎡)
0316000020090601002숙박업(일반)여인숙업원선서울특별시 구로구 구로동로22길 5-14, (구로동)서울특별시 구로구 구로동 733번지 35호20090305처분확정영업정지 2월(2009.6.2~8.2)공중위생관리법제11조제1항20090305성매매알선등영업정지 2월(2009.6.2~8.2)<NA>97.59
131600002003020325300410700013숙박업(일반)여인숙업충남서울특별시 구로구 구로동로26길 55-8, (구로동)서울특별시 구로구 구로동 730번지 29호20021215처분확정영업정지공중위생관리법11조1항20021215윤락행위알선영업정지<NA>47.93
2316000020140226010숙박업(일반)여인숙업나나서울특별시 구로구 경인로15길 8-6, (오류동)서울특별시 구로구 오류동 6번지 114호20120812처분확정과징금부과공중위생관리법 제11조제1항20120812청소년 이성혼숙과징금부과<NA>138.84
3316000020050325006숙박업(일반)여인숙업삼화서울특별시 구로구 구로동로35길 13, (구로동)서울특별시 구로구 구로동 414번지 30호20041001처분확정영업정지풍속영업의규제에관한법률20011001윤락행위알선제공영업정지<NA>189.42
4316000020050325<NA>숙박업(일반)여인숙업삼화서울특별시 구로구 구로동로35길 13, (구로동)서울특별시 구로구 구로동 414번지 30호20050325처분확정영업정지 1월공중위생관리법 제11조 1항20041101윤락행위알선장소제공영업정지 1월30189.42
5316000020070703005숙박업(일반)여인숙업산호서울특별시 구로구 구로동로25길 5-8, (구로동)서울특별시 구로구 구로동 728번지 12호20070526처분확정영업정지2월에 갈음하는 과징금 부과공중위생관리법제11조1항20070526청소년보호법위반(청소년이성혼숙)영업정지2월에 갈음하는 과징금 부과<NA>41.32
6316000020130122011숙박업(일반)여인숙업대교장서울특별시 구로구 구로동로17길 8-3, (구로동)서울특별시 구로구 구로동 722번지 26호20120912처분확정과징금부과공중위생관리법 제11조제1항20120912청소년 이성혼숙과징금부과<NA>167.27
7316000020040729014숙박업(일반)여인숙업수원서울특별시 구로구 구로동로25길 10-15, (구로동)서울특별시 구로구 구로동 705번지 9호20040618처분확정영업정지공중위생관리법제11조1항20040618윤락행위알선장소제공영업정지<NA>85.96
8316000020040729<NA>숙박업(일반)여인숙업수원여인숙서울특별시 구로구 구로동로25길 10-15, (구로동)서울특별시 구로구 구로동 705번지 9호20040618처분확정영업정지 2월공중위생관리법 제11조1항20040618윤락행위 알선 장소제공영업정지 2월6085.96
9316000020091124014숙박업(일반)여인숙업수원서울특별시 구로구 구로동로25길 10-15, (구로동)서울특별시 구로구 구로동 705번지 9호20090820처분확정영업정지 2월(2009.12.01~2010.01.31)공중위생관리법제11조20090820성매매 알선등 행위의 처벌에 관한 법률 위반영업정지 2월(2009.12.01~2010.01.31)<NA>85.96
시군구코드처분일자교부번호업종명업태명업소명소재지도로명소재지지번지도점검일자행정처분상태처분명법적근거위반일자위반내용처분내용처분기간영업장면적(㎡)
8763160000201910222017-00062화장ㆍ분장 미용업메이크업업속눈썹&프리마켓서울특별시 구로구 개봉로3가길 52, 1층 (개봉동)서울특별시 구로구 개봉동 368번지 10호20190102처분확정과태료 처분 제외공중위생관리법 제17조 위반 및 동법 제22조 제2항 적용201901022018년 위생교육 미이수과태료 처분 제외<NA>10.0
8773160000201912102019-00002화장ㆍ분장 미용업메이크업업엘렌서울특별시 구로구 고척로33길 14, 1층 (고척동)서울특별시 구로구 고척동 253번지 97호20191007처분확정과징금부과법 제4조제7항20191007반영구 문신 시술을 위한 의료기기(멸균침) 보유 및 사용과징금부과<NA>19.28
8783160000202010132018-00011일반미용업, 화장ㆍ분장 미용업일반미용업웨딩시티서울특별시 구로구 새말로 97, 신도림테크노마트 8층 77호 외 15구좌호 (구로동)서울특별시 구로구 구로동 3번지 25호 신도림테크노마트 8층-77호20200807처분확정과태료부과법 제22조제2항제6호202008072019년도 위생교육 미수료과태료부과<NA>181.5
8793160000201910222017-00105피부미용업, 화장ㆍ분장 미용업메이크업업러블리수서울특별시 구로구 개봉로20길 6, 상가1동 2층 214호 (개봉동, 현대아파트1단지)서울특별시 구로구 개봉동 481번지 상가1 현대아파트1단지-21420190102처분확정과태료 처분 제외공중위생관리법 제17조 위반 및 동법 제22조 제2항 적용201901022018년 위생교육 미이수과태료 처분 제외<NA>17.28
8803160000201912102018-00007피부미용업, 화장ㆍ분장 미용업메이크업업시크릿터치서울특별시 구로구 고척로33길 18, 1층 (고척동)서울특별시 구로구 고척동 253번지 78호20191007처분확정과징금부과법 제4조제7항20191007반영구 문신 시술을 위한 의료기기(멸균침) 보유 및 사용과징금부과<NA>28.0
8813160000202008312020-00003피부미용업, 화장ㆍ분장 미용업메이크업업터치앤래쉬서울특별시 구로구 남부순환로95길 8-5, 301호 (개봉동)서울특별시 구로구 개봉동 203번지 13호20200206처분확정과징금부과법 제11조제1항제4호20200206반영구 문신 불법 시술과징금부과<NA>40.0
8823160000201910222017-00070네일미용업, 화장ㆍ분장 미용업메이크업업해피라인서울특별시 구로구 디지털로32가길 9, 407호 (구로동, 대성빌딩)서울특별시 구로구 구로동 1127번지 26호 -40720190102처분확정과태료 처분 제외공중위생관리법 제17조 위반 및 동법 제22조 제2항 적용201901022018년 위생교육 미이수과태료 처분 제외<NA>24.0
8833160000202010192016-00084일반미용업, 네일미용업, 화장ㆍ분장 미용업일반미용업메이크업리베서울특별시 구로구 신도림로 7, 128호 (신도림동, 금강리빙스텔)서울특별시 구로구 신도림동 400번지 1호 -12820200908처분확정영업소폐쇄법 제3조3항20200908영업장 멸실 및 사업자등록 폐업영업소폐쇄<NA>37.88
8843160000201812202015-00009피부미용업, 네일미용업, 화장ㆍ분장 미용업피부미용업퓨어왁싱<NA>서울특별시 구로구 신도림동 337번지 신도림1차푸르지오20181129처분확정과태료20만원부과공중위생관리법 제17조 위반, 동법 제22조 제2항 적용201811282017년 위생교육 미이수과태료20만원부과<NA>56.78
8853160000201910222017-00034피부미용업, 네일미용업, 화장ㆍ분장 미용업메이크업업뷰티디자인서울특별시 구로구 경인로67길 23, 101동 1층 129호 (신도림동, 신도림2차푸르지오)서울특별시 구로구 신도림동 338번지 101 -12920190102처분확정과태료 부과(16만원)공중위생관리법 제17조 위반 및 동법 제22조 제2항 적용201901022018년 위생교육 미이수과태료 부과(16만원)<NA>28.83

Duplicate rows

Most frequently occurring

시군구코드처분일자교부번호업종명업태명업소명소재지도로명소재지지번지도점검일자행정처분상태처분명법적근거위반일자위반내용처분내용처분기간영업장면적(㎡)# duplicates
40316000020111201358이용업일반이용업만남서울특별시 구로구 구로동로 159, (구로동)서울특별시 구로구 구로동 413번지 80호20110601처분확정면허정지2월공중위생관리법 제11조제1항20110601성매매알선 등면허정지2월<NA><NA>4
41316000020111201358이용업일반이용업만남서울특별시 구로구 구로동로 159, (구로동)서울특별시 구로구 구로동 413번지 80호20110601처분확정영업정지2월공중위생관리법 제11조제1항20110601성매매알선 등영업정지2월<NA><NA>4
44316000020120904284이용업일반이용업휴게이용원서울특별시 구로구 경인로 216, (오류동,(3층))서울특별시 구로구 오류동 55번지 50호 (3층)20111104처분확정면허정지공중위생관리법 제11조제1항20111104성매매알선면허정지0136.04
45316000020120904284이용업일반이용업휴게이용원서울특별시 구로구 경인로 216, (오류동,(3층))서울특별시 구로구 오류동 55번지 50호 (3층)20111104처분확정영업정지공중위생관리법 제11조제1항20111104성매매알선영업정지15136.04
463160000201301282012-00262이용업일반이용업태양이용원서울특별시 구로구 경인로47다길 23, (고척동)서울특별시 구로구 고척동 57번지 56호20130114처분확정경고공중위생관리법 제17조제1항201301142012년 위생교육 미수료경고<NA>20.353
473160000201301292012-00262이용업일반이용업태양이용원서울특별시 구로구 경인로47다길 23, (고척동)서울특별시 구로구 고척동 57번지 56호20130114처분확정과태료부과공중위생관리법 제17조제1항201301142012년 위생교육 미수료과태료부과<NA>20.353
58316000020130524036목욕장업공동탕업삼원대중탕서울특별시 구로구 고척로27길 67, (개봉동)서울특별시 구로구 개봉동 115번지 2호20130409처분확정개선명령공중위생관리법 제4조제2항, 제7항20130409욕조수 수질기준 부적합개선명령<NA>441.523
59316000020130524036목욕장업공동탕업삼원대중탕서울특별시 구로구 고척로27길 67, (개봉동)서울특별시 구로구 개봉동 115번지 2호20130409처분확정과태료부과공중위생관리법 제4조제2항, 제7항20130409욕조수 수질기준 부적합과태료부과<NA>441.523
031600002002102825300410700097숙박업(일반)여인숙업충북서울특별시 구로구 신도림로11라길 13-8, (신도림동)서울특별시 구로구 신도림동 293번지 88호20020927처분확정윤락행위알선공중위생관리법11조1항20020927윤락행위알선윤락행위알선<NA>81.362
1316000020030612196숙박업(일반)여관업동방장서울특별시 구로구 경인로 236, (오류동)서울특별시 구로구 오류동 33번지 1호20030515처분확정영업정지공중위생관리법제11조1항20030515청소년이성혼숙영업정지<NA>653.42