Overview

Dataset statistics

Number of variables17
Number of observations709
Missing cells1052
Missing cells (%)8.7%
Duplicate rows69
Duplicate rows (%)9.7%
Total size in memory98.4 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(㎡)
Author성북구
URLhttps://data.seoul.go.kr/dataList/OA-11144/S/1/datasetView.do

Alerts

시군구코드 has constant value ""Constant
행정처분상태 has constant value ""Constant
Dataset has 69 (9.7%) 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
처분기간 is highly overall correlated with 업종명 and 1 other fieldsHigh correlation
업종명 is highly overall correlated with 처분기간 and 1 other fieldsHigh correlation
업태명 is highly overall correlated with 처분기간 and 1 other fieldsHigh correlation
소재지도로명 has 348 (49.1%) missing valuesMissing
처분기간 has 681 (96.1%) missing valuesMissing
영업장면적(㎡) has 22 (3.1%) missing valuesMissing

Reproduction

Analysis started2024-05-04 07:27:00.484130
Analysis finished2024-05-04 07:27:11.246454
Duration10.76 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
3070000
709 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3070000
2nd row3070000
3rd row3070000
4th row3070000
5th row3070000

Common Values

ValueCountFrequency (%)
3070000 709
100.0%

Length

2024-05-04T07:27:11.540917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T07:27:12.261241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3070000 709
100.0%

처분일자
Real number (ℝ)

HIGH CORRELATION 

Distinct279
Distinct (%)39.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20124529
Minimum20010116
Maximum20240222
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.4 KiB
2024-05-04T07:27:12.765342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20010116
5-th percentile20034765
Q120090227
median20130205
Q320160311
95-th percentile20230405
Maximum20240222
Range230106
Interquartile range (IQR)70084

Descriptive statistics

Standard deviation53793.556
Coefficient of variation (CV)0.0026730343
Kurtosis-0.46121528
Mean20124529
Median Absolute Deviation (MAD)39878
Skewness0.24813219
Sum1.4268291 × 1010
Variance2.8937466 × 109
MonotonicityDecreasing
2024-05-04T07:27:13.369656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20140318 44
 
6.2%
20130308 34
 
4.8%
20081205 27
 
3.8%
20170417 25
 
3.5%
20120227 19
 
2.7%
20230405 16
 
2.3%
20220124 16
 
2.3%
20140319 16
 
2.3%
20090327 14
 
2.0%
20130321 12
 
1.7%
Other values (269) 486
68.5%
ValueCountFrequency (%)
20010116 1
 
0.1%
20010209 1
 
0.1%
20010309 1
 
0.1%
20030103 1
 
0.1%
20030106 1
 
0.1%
20030121 2
0.3%
20030210 3
0.4%
20030211 1
 
0.1%
20030409 1
 
0.1%
20030414 4
0.6%
ValueCountFrequency (%)
20240222 1
 
0.1%
20240124 1
 
0.1%
20231226 1
 
0.1%
20231204 1
 
0.1%
20231113 2
 
0.3%
20230807 1
 
0.1%
20230724 1
 
0.1%
20230711 1
 
0.1%
20230626 1
 
0.1%
20230613 9
1.3%

교부번호
Text

Distinct388
Distinct (%)54.8%
Missing1
Missing (%)0.1%
Memory size5.7 KiB
2024-05-04T07:27:14.079310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length6
Mean length6.4011299
Min length3

Characters and Unicode

Total characters4532
Distinct characters28
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique245 ?
Unique (%)34.6%

Sample

1st row2016-00086
2nd row세탁0299
3rd row20200003
4th row미용0543
5th row2021-0021
ValueCountFrequency (%)
목욕0096 18
 
2.5%
세탁0276 11
 
1.5%
숙박0046 9
 
1.2%
미용1115 8
 
1.1%
미용 8
 
1.1%
목욕0080 7
 
1.0%
목욕0057 6
 
0.8%
미용1240 6
 
0.8%
목욕0109 6
 
0.8%
숙박191 6
 
0.8%
Other values (382) 636
88.2%
2024-05-04T07:27:15.446388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1115
24.6%
1 505
 
11.1%
용 260
 
5.7%
2 256
 
5.6%
4 198
 
4.4%
미 194
 
4.3%
6 192
 
4.2%
3 191
 
4.2%
9 178
 
3.9%
8 176
 
3.9%
Other values (18) 1267
28.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3102
68.4%
Other Letter 1362
30.1%
Dash Punctuation 54
 
1.2%
Space Separator 13
 
0.3%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
용 260
19.1%
미 194
14.2%
숙 149
10.9%
박 149
10.9%
목 113
8.3%
욕 113
8.3%
탁 70
 
5.1%
세 70
 
5.1%
이 66
 
4.8%
위 44
 
3.2%
Other values (5) 134
9.8%
Decimal Number
ValueCountFrequency (%)
0 1115
35.9%
1 505
16.3%
2 256
 
8.3%
4 198
 
6.4%
6 192
 
6.2%
3 191
 
6.2%
9 178
 
5.7%
8 176
 
5.7%
7 157
 
5.1%
5 134
 
4.3%
Dash Punctuation
ValueCountFrequency (%)
- 54
100.0%
Space Separator
ValueCountFrequency (%)
13
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3170
69.9%
Hangul 1362
30.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
용 260
19.1%
미 194
14.2%
숙 149
10.9%
박 149
10.9%
목 113
8.3%
욕 113
8.3%
탁 70
 
5.1%
세 70
 
5.1%
이 66
 
4.8%
위 44
 
3.2%
Other values (5) 134
9.8%
Common
ValueCountFrequency (%)
0 1115
35.2%
1 505
15.9%
2 256
 
8.1%
4 198
 
6.2%
6 192
 
6.1%
3 191
 
6.0%
9 178
 
5.6%
8 176
 
5.6%
7 157
 
5.0%
5 134
 
4.2%
Other values (3) 68
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3170
69.9%
Hangul 1362
30.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1115
35.2%
1 505
15.9%
2 256
 
8.1%
4 198
 
6.2%
6 192
 
6.1%
3 191
 
6.0%
9 178
 
5.6%
8 176
 
5.6%
7 157
 
5.0%
5 134
 
4.2%
Other values (3) 68
 
2.1%
Hangul
ValueCountFrequency (%)
용 260
19.1%
미 194
14.2%
숙 149
10.9%
박 149
10.9%
목 113
8.3%
욕 113
8.3%
탁 70
 
5.1%
세 70
 
5.1%
이 66
 
4.8%
위 44
 
3.2%
Other values (5) 134
9.8%

업종명
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
숙박업(일반)
149 
일반미용업
126 
목욕장업
118 
세탁업
76 
이용업
71 
Other values (9)
169 

Length

Max length16
Median length12
Mean length5.1565585
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
숙박업(일반) 149
21.0%
일반미용업 126
17.8%
목욕장업 118
16.6%
세탁업 76
10.7%
이용업 71
10.0%
피부미용업 59
 
8.3%
위생관리용역업 45
 
6.3%
종합미용업 33
 
4.7%
네일미용업 9
 
1.3%
미용업 6
 
0.8%
Other values (4) 17
 
2.4%

Length

2024-05-04T07:27:16.011695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
숙박업(일반 149
20.3%
일반미용업 131
17.9%
목욕장업 118
16.1%
세탁업 76
10.4%
이용업 71
9.7%
피부미용업 67
9.1%
위생관리용역업 45
 
6.1%
종합미용업 33
 
4.5%
네일미용업 23
 
3.1%
미용업 13
 
1.8%

업태명
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
일반미용업
151 
여관업
130 
일반세탁업
71 
일반이용업
71 
피부미용업
70 
Other values (13)
216 

Length

Max length14
Median length5
Mean length5.2722144
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반미용업 151
21.3%
여관업 130
18.3%
일반세탁업 71
10.0%
일반이용업 71
10.0%
피부미용업 70
9.9%
공동탕업 63
8.9%
공동탕업+찜질시설서비스영업 48
 
6.8%
위생관리용역업 45
 
6.3%
네일아트업 22
 
3.1%
여인숙업 11
 
1.6%
Other values (8) 27
 
3.8%

Length

2024-05-04T07:27:16.622279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반미용업 151
21.3%
여관업 130
18.3%
일반세탁업 71
10.0%
일반이용업 71
10.0%
피부미용업 70
9.9%
공동탕업 63
8.9%
공동탕업+찜질시설서비스영업 48
 
6.8%
위생관리용역업 45
 
6.3%
네일아트업 22
 
3.1%
여인숙업 11
 
1.6%
Other values (8) 27
 
3.8%

업소명
Text

Distinct395
Distinct (%)55.7%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
2024-05-04T07:27:17.420416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length20
Mean length5.2073343
Min length1

Characters and Unicode

Total characters3692
Distinct characters374
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

Unique255 ?
Unique (%)36.0%

Sample

1st row지나인헤어(G9hair)
2nd row덕영사
3rd row삼성세탁
4th row주노미용실
5th row현정미용실
ValueCountFrequency (%)
월곡건강랜드 18
 
2.3%
한신크리닝 11
 
1.4%
사운드바디 9
 
1.2%
헤어스토리 8
 
1.0%
대성 7
 
0.9%
삼선사우나 7
 
0.9%
한일 7
 
0.9%
민헤어 6
 
0.8%
세계산업 6
 
0.8%
파브모텔 6
 
0.8%
Other values (419) 690
89.0%
2024-05-04T07:27:18.970224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
어 103
 
2.8%
헤 99
 
2.7%
사 81
 
2.2%
리 81
 
2.2%
( 72
 
2.0%
) 72
 
2.0%
스 72
 
2.0%
이 69
 
1.9%
66
 
1.8%
아 58
 
1.6%
Other values (364) 2919
79.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3155
85.5%
Lowercase Letter 204
 
5.5%
Uppercase Letter 81
 
2.2%
Open Punctuation 72
 
2.0%
Close Punctuation 72
 
2.0%
Space Separator 66
 
1.8%
Decimal Number 22
 
0.6%
Other Punctuation 20
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
어 103
 
3.3%
헤 99
 
3.1%
사 81
 
2.6%
리 81
 
2.6%
스 72
 
2.3%
이 69
 
2.2%
아 58
 
1.8%
용 55
 
1.7%
성 55
 
1.7%
일 55
 
1.7%
Other values (314) 2427
76.9%
Lowercase Letter
ValueCountFrequency (%)
e 24
11.8%
i 19
9.3%
o 19
9.3%
y 17
 
8.3%
a 16
 
7.8%
n 16
 
7.8%
s 14
 
6.9%
l 14
 
6.9%
u 11
 
5.4%
h 10
 
4.9%
Other values (9) 44
21.6%
Uppercase Letter
ValueCountFrequency (%)
S 11
13.6%
O 9
11.1%
E 7
 
8.6%
J 7
 
8.6%
L 6
 
7.4%
N 6
 
7.4%
M 5
 
6.2%
W 4
 
4.9%
T 4
 
4.9%
R 4
 
4.9%
Other values (9) 18
22.2%
Decimal Number
ValueCountFrequency (%)
0 12
54.5%
2 5
22.7%
4 2
 
9.1%
3 2
 
9.1%
9 1
 
4.5%
Other Punctuation
ValueCountFrequency (%)
？ 9
45.0%
& 6
30.0%
, 3
 
15.0%
# 2
 
10.0%
Open Punctuation
ValueCountFrequency (%)
( 72
100.0%
Close Punctuation
ValueCountFrequency (%)
) 72
100.0%
Space Separator
ValueCountFrequency (%)
66
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3155
85.5%
Latin 285
 
7.7%
Common 252
 
6.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
어 103
 
3.3%
헤 99
 
3.1%
사 81
 
2.6%
리 81
 
2.6%
스 72
 
2.3%
이 69
 
2.2%
아 58
 
1.8%
용 55
 
1.7%
성 55
 
1.7%
일 55
 
1.7%
Other values (314) 2427
76.9%
Latin
ValueCountFrequency (%)
e 24
 
8.4%
i 19
 
6.7%
o 19
 
6.7%
y 17
 
6.0%
a 16
 
5.6%
n 16
 
5.6%
s 14
 
4.9%
l 14
 
4.9%
u 11
 
3.9%
S 11
 
3.9%
Other values (28) 124
43.5%
Common
ValueCountFrequency (%)
( 72
28.6%
) 72
28.6%
66
26.2%
0 12
 
4.8%
？ 9
 
3.6%
& 6
 
2.4%
2 5
 
2.0%
, 3
 
1.2%
4 2
 
0.8%
# 2
 
0.8%
Other values (2) 3
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3155
85.5%
ASCII 528
 
14.3%
None 9
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
어 103
 
3.3%
헤 99
 
3.1%
사 81
 
2.6%
리 81
 
2.6%
스 72
 
2.3%
이 69
 
2.2%
아 58
 
1.8%
용 55
 
1.7%
성 55
 
1.7%
일 55
 
1.7%
Other values (314) 2427
76.9%
ASCII
ValueCountFrequency (%)
( 72
 
13.6%
) 72
 
13.6%
66
 
12.5%
e 24
 
4.5%
i 19
 
3.6%
o 19
 
3.6%
y 17
 
3.2%
a 16
 
3.0%
n 16
 
3.0%
s 14
 
2.7%
Other values (39) 193
36.6%
None
ValueCountFrequency (%)
？ 9
100.0%

소재지도로명
Text

MISSING 

Distinct194
Distinct (%)53.7%
Missing348
Missing (%)49.1%
Memory size5.7 KiB
2024-05-04T07:27:19.788459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length48
Mean length31.426593
Min length23

Characters and Unicode

Total characters11345
Distinct characters164
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

Unique124 ?
Unique (%)34.3%

Sample

1st row서울특별시 성북구 동소문로20길 24, (동소문동5가)
2nd row서울특별시 성북구 장위로 80, (장위동)
3rd row서울특별시 성북구 화랑로30길 26, (석관동)
4th row서울특별시 성북구 보국문로11길 23, (정릉동,(2층))
5th row서울특별시 성북구 삼선교로14길 66, 1층 (삼선동2가)
ValueCountFrequency (%)
서울특별시 361
 
17.2%
성북구 361
 
17.2%
하월곡동 44
 
2.1%
1층 42
 
2.0%
장위동 41
 
2.0%
정릉동 30
 
1.4%
석관동 24
 
1.1%
동소문로 21
 
1.0%
장위로 20
 
1.0%
종암동 20
 
1.0%
Other values (374) 1133
54.0%
2024-05-04T07:27:20.923370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1736
 
15.3%
동 553
 
4.9%
, 506
 
4.5%
1 404
 
3.6%
( 403
 
3.6%
) 403
 
3.6%
서 380
 
3.3%
성 379
 
3.3%
북 374
 
3.3%
로 362
 
3.2%
Other values (154) 5845
51.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6485
57.2%
Space Separator 1736
 
15.3%
Decimal Number 1714
 
15.1%
Other Punctuation 507
 
4.5%
Open Punctuation 403
 
3.6%
Close Punctuation 403
 
3.6%
Dash Punctuation 79
 
0.7%
Uppercase Letter 11
 
0.1%
Lowercase Letter 6
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 553
 
8.5%
서 380
 
5.9%
성 379
 
5.8%
북 374
 
5.8%
로 362
 
5.6%
울 361
 
5.6%
시 361
 
5.6%
별 361
 
5.6%
특 361
 
5.6%
구 361
 
5.6%
Other values (125) 2632
40.6%
Decimal Number
ValueCountFrequency (%)
1 404
23.6%
2 340
19.8%
4 184
10.7%
3 161
 
9.4%
0 147
 
8.6%
6 121
 
7.1%
5 98
 
5.7%
7 93
 
5.4%
8 85
 
5.0%
9 81
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
B 6
54.5%
A 1
 
9.1%
P 1
 
9.1%
T 1
 
9.1%
R 1
 
9.1%
G 1
 
9.1%
Lowercase Letter
ValueCountFrequency (%)
x 1
16.7%
o 1
16.7%
b 1
16.7%
s 1
16.7%
k 1
16.7%
y 1
16.7%
Other Punctuation
ValueCountFrequency (%)
, 506
99.8%
. 1
 
0.2%
Space Separator
ValueCountFrequency (%)
1736
100.0%
Open Punctuation
ValueCountFrequency (%)
( 403
100.0%
Close Punctuation
ValueCountFrequency (%)
) 403
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 79
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6485
57.2%
Common 4843
42.7%
Latin 17
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 553
 
8.5%
서 380
 
5.9%
성 379
 
5.8%
북 374
 
5.8%
로 362
 
5.6%
울 361
 
5.6%
시 361
 
5.6%
별 361
 
5.6%
특 361
 
5.6%
구 361
 
5.6%
Other values (125) 2632
40.6%
Common
ValueCountFrequency (%)
1736
35.8%
, 506
 
10.4%
1 404
 
8.3%
( 403
 
8.3%
) 403
 
8.3%
2 340
 
7.0%
4 184
 
3.8%
3 161
 
3.3%
0 147
 
3.0%
6 121
 
2.5%
Other values (7) 438
 
9.0%
Latin
ValueCountFrequency (%)
B 6
35.3%
x 1
 
5.9%
A 1
 
5.9%
P 1
 
5.9%
T 1
 
5.9%
o 1
 
5.9%
R 1
 
5.9%
G 1
 
5.9%
b 1
 
5.9%
s 1
 
5.9%
Other values (2) 2
 
11.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6485
57.2%
ASCII 4860
42.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1736
35.7%
, 506
 
10.4%
1 404
 
8.3%
( 403
 
8.3%
) 403
 
8.3%
2 340
 
7.0%
4 184
 
3.8%
3 161
 
3.3%
0 147
 
3.0%
6 121
 
2.5%
Other values (19) 455
 
9.4%
Hangul
ValueCountFrequency (%)
동 553
 
8.5%
서 380
 
5.9%
성 379
 
5.8%
북 374
 
5.8%
로 362
 
5.6%
울 361
 
5.6%
시 361
 
5.6%
별 361
 
5.6%
특 361
 
5.6%
구 361
 
5.6%
Other values (125) 2632
40.6%

소재지지번
Text

Distinct385
Distinct (%)54.3%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
2024-05-04T07:27:21.975150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length47
Mean length28.351199
Min length22

Characters and Unicode

Total characters20101
Distinct characters173
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

Unique245 ?
Unique (%)34.6%

Sample

1st row서울특별시 성북구 동소문동5가 109번지
2nd row서울특별시 성북구 장위동 233번지 251호
3rd row서울특별시 성북구 석관동 338번지 156호
4th row서울특별시 성북구 정릉동 396번지 41호 (2층)
5th row서울특별시 성북구 삼선동2가 260번지
ValueCountFrequency (%)
서울특별시 709
 
18.5%
성북구 709
 
18.5%
정릉동 106
 
2.8%
하월곡동 97
 
2.5%
장위동 81
 
2.1%
석관동 68
 
1.8%
1호 64
 
1.7%
길음동 58
 
1.5%
종암동 51
 
1.3%
2호 45
 
1.2%
Other values (499) 1845
48.1%
2024-05-04T07:27:23.173306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4966
24.7%
동 874
 
4.3%
1 810
 
4.0%
지 766
 
3.8%
성 730
 
3.6%
북 722
 
3.6%
서 714
 
3.6%
시 712
 
3.5%
울 709
 
3.5%
번 709
 
3.5%
Other values (163) 8389
41.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11280
56.1%
Space Separator 4966
24.7%
Decimal Number 3610
 
18.0%
Open Punctuation 79
 
0.4%
Close Punctuation 79
 
0.4%
Dash Punctuation 41
 
0.2%
Other Punctuation 28
 
0.1%
Uppercase Letter 15
 
0.1%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 874
 
7.7%
지 766
 
6.8%
성 730
 
6.5%
북 722
 
6.4%
서 714
 
6.3%
시 712
 
6.3%
울 709
 
6.3%
번 709
 
6.3%
특 709
 
6.3%
구 709
 
6.3%
Other values (138) 3926
34.8%
Decimal Number
ValueCountFrequency (%)
1 810
22.4%
2 585
16.2%
3 422
11.7%
5 304
 
8.4%
0 290
 
8.0%
4 267
 
7.4%
6 259
 
7.2%
7 253
 
7.0%
8 219
 
6.1%
9 201
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
B 6
40.0%
A 3
20.0%
P 2
 
13.3%
T 2
 
13.3%
R 1
 
6.7%
G 1
 
6.7%
Lowercase Letter
ValueCountFrequency (%)
k 1
33.3%
s 1
33.3%
b 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 24
85.7%
. 4
 
14.3%
Space Separator
ValueCountFrequency (%)
4966
100.0%
Open Punctuation
ValueCountFrequency (%)
( 79
100.0%
Close Punctuation
ValueCountFrequency (%)
) 79
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 41
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11280
56.1%
Common 8803
43.8%
Latin 18
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 874
 
7.7%
지 766
 
6.8%
성 730
 
6.5%
북 722
 
6.4%
서 714
 
6.3%
시 712
 
6.3%
울 709
 
6.3%
번 709
 
6.3%
특 709
 
6.3%
구 709
 
6.3%
Other values (138) 3926
34.8%
Common
ValueCountFrequency (%)
4966
56.4%
1 810
 
9.2%
2 585
 
6.6%
3 422
 
4.8%
5 304
 
3.5%
0 290
 
3.3%
4 267
 
3.0%
6 259
 
2.9%
7 253
 
2.9%
8 219
 
2.5%
Other values (6) 428
 
4.9%
Latin
ValueCountFrequency (%)
B 6
33.3%
A 3
16.7%
P 2
 
11.1%
T 2
 
11.1%
R 1
 
5.6%
k 1
 
5.6%
s 1
 
5.6%
G 1
 
5.6%
b 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11280
56.1%
ASCII 8821
43.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4966
56.3%
1 810
 
9.2%
2 585
 
6.6%
3 422
 
4.8%
5 304
 
3.4%
0 290
 
3.3%
4 267
 
3.0%
6 259
 
2.9%
7 253
 
2.9%
8 219
 
2.5%
Other values (15) 446
 
5.1%
Hangul
ValueCountFrequency (%)
동 874
 
7.7%
지 766
 
6.8%
성 730
 
6.5%
북 722
 
6.4%
서 714
 
6.3%
시 712
 
6.3%
울 709
 
6.3%
번 709
 
6.3%
특 709
 
6.3%
구 709
 
6.3%
Other values (138) 3926
34.8%

지도점검일자
Real number (ℝ)

HIGH CORRELATION 

Distinct289
Distinct (%)40.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20122596
Minimum20001206
Maximum20240130
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.4 KiB
2024-05-04T07:27:23.733374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20001206
5-th percentile20031105
Q120081217
median20121210
Q320160222
95-th percentile20230315
Maximum20240130
Range238924
Interquartile range (IQR)79005

Descriptive statistics

Standard deviation53616.063
Coefficient of variation (CV)0.0026644705
Kurtosis-0.4692421
Mean20122596
Median Absolute Deviation (MAD)39294
Skewness0.21954307
Sum1.426692 × 1010
Variance2.8746822 × 109
MonotonicityNot monotonic
2024-05-04T07:27:24.203560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20140101 68
 
9.6%
20130101 29
 
4.1%
20130313 24
 
3.4%
20211230 24
 
3.4%
20120102 20
 
2.8%
20170411 19
 
2.7%
20230315 18
 
2.5%
20170116 12
 
1.7%
20101231 12
 
1.7%
20191210 10
 
1.4%
Other values (279) 473
66.7%
ValueCountFrequency (%)
20001206 1
0.1%
20010204 1
0.1%
20010210 1
0.1%
20021122 1
0.1%
20021128 1
0.1%
20021206 2
0.3%
20021218 1
0.1%
20030106 1
0.1%
20030110 1
0.1%
20030123 1
0.1%
ValueCountFrequency (%)
20240130 1
0.1%
20240112 1
0.1%
20231213 1
0.1%
20231120 1
0.1%
20231030 1
0.1%
20230919 1
0.1%
20230713 1
0.1%
20230706 1
0.1%
20230704 1
0.1%
20230605 1
0.1%

행정처분상태
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
처분확정
709 

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 709
100.0%

Length

2024-05-04T07:27:24.712873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T07:27:25.187624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
처분확정 709
100.0%

처분명
Text

Distinct110
Distinct (%)15.5%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
2024-05-04T07:27:25.610996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length31
Mean length7.9069111
Min length2

Characters and Unicode

Total characters5606
Distinct characters107
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique64 ?
Unique (%)9.0%

Sample

1st row경고
2nd row직권말소
3rd row직권말소
4th row직권말소
5th row직권말소
ValueCountFrequency (%)
과태료부과 194
17.0%
경고 150
 
13.2%
개선명령 114
 
10.0%
과징금부과 57
 
5.0%
영업정지 55
 
4.8%
과태료 44
 
3.9%
및 36
 
3.2%
부과 35
 
3.1%
납부시 33
 
2.9%
영업소폐쇄 28
 
2.5%
Other values (115) 392
34.4%
2024-05-04T07:27:26.663525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 705
 
12.6%
431
 
7.7%
부 379
 
6.8%
0 365
 
6.5%
료 284
 
5.1%
태 282
 
5.0%
원 211
 
3.8%
만 165
 
2.9%
고 164
 
2.9%
경 163
 
2.9%
Other values (97) 2457
43.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4137
73.8%
Decimal Number 774
 
13.8%
Space Separator 431
 
7.7%
Other Punctuation 93
 
1.7%
Close Punctuation 81
 
1.4%
Open Punctuation 81
 
1.4%
Math Symbol 7
 
0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 705
17.0%
부 379
 
9.2%
료 284
 
6.9%
태 282
 
6.8%
원 211
 
5.1%
만 165
 
4.0%
고 164
 
4.0%
경 163
 
3.9%
개 126
 
3.0%
령 121
 
2.9%
Other values (76) 1537
37.2%
Decimal Number
ValueCountFrequency (%)
0 365
47.2%
2 129
 
16.7%
4 60
 
7.8%
1 59
 
7.6%
6 45
 
5.8%
3 44
 
5.7%
8 31
 
4.0%
5 25
 
3.2%
9 10
 
1.3%
7 6
 
0.8%
Other Punctuation
ValueCountFrequency (%)
, 71
76.3%
. 18
 
19.4%
% 3
 
3.2%
/ 1
 
1.1%
Math Symbol
ValueCountFrequency (%)
× 5
71.4%
~ 1
 
14.3%
= 1
 
14.3%
Space Separator
ValueCountFrequency (%)
431
100.0%
Close Punctuation
ValueCountFrequency (%)
) 81
100.0%
Open Punctuation
ValueCountFrequency (%)
( 81
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4137
73.8%
Common 1469
 
26.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 705
17.0%
부 379
 
9.2%
료 284
 
6.9%
태 282
 
6.8%
원 211
 
5.1%
만 165
 
4.0%
고 164
 
4.0%
경 163
 
3.9%
개 126
 
3.0%
령 121
 
2.9%
Other values (76) 1537
37.2%
Common
ValueCountFrequency (%)
431
29.3%
0 365
24.8%
2 129
 
8.8%
) 81
 
5.5%
( 81
 
5.5%
, 71
 
4.8%
4 60
 
4.1%
1 59
 
4.0%
6 45
 
3.1%
3 44
 
3.0%
Other values (11) 103
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4137
73.8%
ASCII 1464
 
26.1%
None 5
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 705
17.0%
부 379
 
9.2%
료 284
 
6.9%
태 282
 
6.8%
원 211
 
5.1%
만 165
 
4.0%
고 164
 
4.0%
경 163
 
3.9%
개 126
 
3.0%
령 121
 
2.9%
Other values (76) 1537
37.2%
ASCII
ValueCountFrequency (%)
431
29.4%
0 365
24.9%
2 129
 
8.8%
) 81
 
5.5%
( 81
 
5.5%
, 71
 
4.8%
4 60
 
4.1%
1 59
 
4.0%
6 45
 
3.1%
3 44
 
3.0%
Other values (10) 98
 
6.7%
None
ValueCountFrequency (%)
× 5
100.0%

법적근거
Text

Distinct134
Distinct (%)18.9%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
2024-05-04T07:27:27.321808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length40
Mean length13.35543
Min length3

Characters and Unicode

Total characters9469
Distinct characters73
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

Unique64 ?
Unique (%)9.0%

Sample

1st row법 제11조제1항제4호
2nd row법 제11조제3항제2호
3rd row법 제11조제3항제2호
4th row법 제11조제3항제2호
5th row법 제11조제3항제2호
ValueCountFrequency (%)
공중위생관리법 357
21.1%
제17조 227
13.4%
법 197
 
11.6%
및 83
 
4.9%
1항 49
 
2.9%
제4조 49
 
2.9%
제22조제2항제6호 48
 
2.8%
제11조 42
 
2.5%
시행규칙 38
 
2.2%
제11조제1항 36
 
2.1%
Other values (123) 565
33.4%
2024-05-04T07:27:28.467441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
제 1069
11.3%
985
 
10.4%
1 832
 
8.8%
법 784
 
8.3%
조 774
 
8.2%
관 505
 
5.3%
위 504
 
5.3%
공 500
 
5.3%
생 500
 
5.3%
중 498
 
5.3%
Other values (63) 2518
26.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6664
70.4%
Decimal Number 1772
 
18.7%
Space Separator 985
 
10.4%
Other Punctuation 22
 
0.2%
Close Punctuation 13
 
0.1%
Open Punctuation 13
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 1069
16.0%
법 784
11.8%
조 774
11.6%
관 505
7.6%
위 504
7.6%
공 500
7.5%
생 500
7.5%
중 498
7.5%
리 495
7.4%
항 361
 
5.4%
Other values (47) 674
10.1%
Decimal Number
ValueCountFrequency (%)
1 832
47.0%
7 362
20.4%
2 265
 
15.0%
4 116
 
6.5%
3 102
 
5.8%
6 57
 
3.2%
9 26
 
1.5%
8 7
 
0.4%
0 5
 
0.3%
Other Punctuation
ValueCountFrequency (%)
, 17
77.3%
. 5
 
22.7%
Close Punctuation
ValueCountFrequency (%)
) 7
53.8%
] 6
46.2%
Open Punctuation
ValueCountFrequency (%)
( 7
53.8%
[ 6
46.2%
Space Separator
ValueCountFrequency (%)
985
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6664
70.4%
Common 2805
29.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 1069
16.0%
법 784
11.8%
조 774
11.6%
관 505
7.6%
위 504
7.6%
공 500
7.5%
생 500
7.5%
중 498
7.5%
리 495
7.4%
항 361
 
5.4%
Other values (47) 674
10.1%
Common
ValueCountFrequency (%)
985
35.1%
1 832
29.7%
7 362
 
12.9%
2 265
 
9.4%
4 116
 
4.1%
3 102
 
3.6%
6 57
 
2.0%
9 26
 
0.9%
, 17
 
0.6%
8 7
 
0.2%
Other values (6) 36
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6664
70.4%
ASCII 2805
29.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
제 1069
16.0%
법 784
11.8%
조 774
11.6%
관 505
7.6%
위 504
7.6%
공 500
7.5%
생 500
7.5%
중 498
7.5%
리 495
7.4%
항 361
 
5.4%
Other values (47) 674
10.1%
ASCII
ValueCountFrequency (%)
985
35.1%
1 832
29.7%
7 362
 
12.9%
2 265
 
9.4%
4 116
 
4.1%
3 102
 
3.6%
6 57
 
2.0%
9 26
 
0.9%
, 17
 
0.6%
8 7
 
0.2%
Other values (6) 36
 
1.3%

위반일자
Real number (ℝ)

HIGH CORRELATION 

Distinct293
Distinct (%)41.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20122411
Minimum20010210
Maximum20240130
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.4 KiB
2024-05-04T07:27:29.054913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20010210
5-th percentile20031107
Q120081204
median20121217
Q320160222
95-th percentile20230315
Maximum20240130
Range229920
Interquartile range (IQR)79018

Descriptive statistics

Standard deviation53359.367
Coefficient of variation (CV)0.0026517382
Kurtosis-0.4603277
Mean20122411
Median Absolute Deviation (MAD)39295
Skewness0.22259823
Sum1.426679 × 1010
Variance2.8472221 × 109
MonotonicityNot monotonic
2024-05-04T07:27:29.645720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20140101 68
 
9.6%
20130101 56
 
7.9%
20211230 24
 
3.4%
20120102 20
 
2.8%
20170411 18
 
2.5%
20230315 17
 
2.4%
20181231 11
 
1.6%
20170116 11
 
1.6%
20101231 11
 
1.6%
20160222 10
 
1.4%
Other values (283) 463
65.3%
ValueCountFrequency (%)
20010210 1
 
0.1%
20011016 2
0.3%
20021122 1
 
0.1%
20021128 1
 
0.1%
20021206 2
0.3%
20030106 1
 
0.1%
20030110 1
 
0.1%
20030123 1
 
0.1%
20030314 1
 
0.1%
20030316 4
0.6%
ValueCountFrequency (%)
20240130 1
0.1%
20240112 1
0.1%
20231213 1
0.1%
20231120 1
0.1%
20230919 1
0.1%
20230713 1
0.1%
20230706 1
0.1%
20230704 1
0.1%
20230518 1
0.1%
20230512 1
0.1%

위반내용
Text

Distinct279
Distinct (%)39.4%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
2024-05-04T07:27:30.228631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length304
Median length226
Mean length21.961918
Min length4

Characters and Unicode

Total characters15571
Distinct characters384
Distinct categories14 ?
Distinct scripts3 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique200 ?
Unique (%)28.2%

Sample

1st row공중위생관리법 시행규칙 제7조 별표4 제4호자목 개별미용서비스의 최종 지불가격 및 전체 미용서비스의 총액에 관한 내역서를 이용자에게 미리 제공하고 그 사본을 1개월 동안 보관하지 않음
2nd row사업자 등록 말소 후 영업신고 폐업을 하지 않음
3rd row사업자 등록 폐업 후 영업신고 폐업을 하지 않음
4th row사업자 등록 말소 후 영업 폐업신고를 하지 않음
5th row2023년 3월 31일 성북 세무서장에게 사업자 폐업 신고 후 공중위생영업 폐업 신고를 하지 않음
ValueCountFrequency (%)
위생교육 173
 
5.4%
미이수 153
 
4.8%
위생교육미이수 114
 
3.6%
청소년 52
 
1.6%
2012 42
 
1.3%
하지 40
 
1.3%
장소제공 38
 
1.2%
이성혼숙 37
 
1.2%
욕조수 33
 
1.0%
위반 33
 
1.0%
Other values (1037) 2461
77.5%
2024-05-04T07:27:31.420946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2525
 
16.2%
위 519
 
3.3%
0 499
 
3.2%
이 481
 
3.1%
2 432
 
2.8%
미 393
 
2.5%
수 393
 
2.5%
생 375
 
2.4%
육 330
 
2.1%
교 330
 
2.1%
Other values (374) 9294
59.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10651
68.4%
Space Separator 2525
 
16.2%
Decimal Number 1680
 
10.8%
Other Punctuation 384
 
2.5%
Close Punctuation 106
 
0.7%
Open Punctuation 106
 
0.7%
Dash Punctuation 33
 
0.2%
Lowercase Letter 18
 
0.1%
Uppercase Letter 18
 
0.1%
Final Punctuation 16
 
0.1%
Other values (4) 34
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
위 519
 
4.9%
이 481
 
4.5%
미 393
 
3.7%
수 393
 
3.7%
생 375
 
3.5%
육 330
 
3.1%
교 330
 
3.1%
업 286
 
2.7%
소 270
 
2.5%
하 220
 
2.1%
Other values (338) 7054
66.2%
Decimal Number
ValueCountFrequency (%)
0 499
29.7%
2 432
25.7%
1 315
18.8%
6 85
 
5.1%
7 83
 
4.9%
5 69
 
4.1%
4 66
 
3.9%
3 59
 
3.5%
8 48
 
2.9%
9 24
 
1.4%
Uppercase Letter
ValueCountFrequency (%)
C 6
33.3%
V 3
16.7%
T 3
16.7%
R 2
 
11.1%
G 2
 
11.1%
O 2
 
11.1%
Other Punctuation
ValueCountFrequency (%)
. 216
56.2%
: 73
 
19.0%
, 67
 
17.4%
* 20
 
5.2%
/ 8
 
2.1%
Close Punctuation
ValueCountFrequency (%)
) 105
99.1%
] 1
 
0.9%
Open Punctuation
ValueCountFrequency (%)
( 105
99.1%
[ 1
 
0.9%
Lowercase Letter
ValueCountFrequency (%)
l 9
50.0%
m 9
50.0%
Final Punctuation
ValueCountFrequency (%)
’ 8
50.0%
” 8
50.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 8
50.0%
“ 8
50.0%
Space Separator
ValueCountFrequency (%)
2525
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 33
100.0%
Math Symbol
ValueCountFrequency (%)
~ 13
100.0%
Other Symbol
ValueCountFrequency (%)
○ 4
100.0%
Other Number
ValueCountFrequency (%)
② 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10651
68.4%
Common 4884
31.4%
Latin 36
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
위 519
 
4.9%
이 481
 
4.5%
미 393
 
3.7%
수 393
 
3.7%
생 375
 
3.5%
육 330
 
3.1%
교 330
 
3.1%
업 286
 
2.7%
소 270
 
2.5%
하 220
 
2.1%
Other values (338) 7054
66.2%
Common
ValueCountFrequency (%)
2525
51.7%
0 499
 
10.2%
2 432
 
8.8%
1 315
 
6.4%
. 216
 
4.4%
) 105
 
2.1%
( 105
 
2.1%
6 85
 
1.7%
7 83
 
1.7%
: 73
 
1.5%
Other values (18) 446
 
9.1%
Latin
ValueCountFrequency (%)
l 9
25.0%
m 9
25.0%
C 6
16.7%
V 3
 
8.3%
T 3
 
8.3%
R 2
 
5.6%
G 2
 
5.6%
O 2
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10648
68.4%
ASCII 4883
31.4%
Punctuation 32
 
0.2%
Geometric Shapes 4
 
< 0.1%
Compat Jamo 3
 
< 0.1%
Enclosed Alphanum 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2525
51.7%
0 499
 
10.2%
2 432
 
8.8%
1 315
 
6.5%
. 216
 
4.4%
) 105
 
2.2%
( 105
 
2.2%
6 85
 
1.7%
7 83
 
1.7%
: 73
 
1.5%
Other values (20) 445
 
9.1%
Hangul
ValueCountFrequency (%)
위 519
 
4.9%
이 481
 
4.5%
미 393
 
3.7%
수 393
 
3.7%
생 375
 
3.5%
육 330
 
3.1%
교 330
 
3.1%
업 286
 
2.7%
소 270
 
2.5%
하 220
 
2.1%
Other values (337) 7051
66.2%
Punctuation
ValueCountFrequency (%)
’ 8
25.0%
” 8
25.0%
‘ 8
25.0%
“ 8
25.0%
Geometric Shapes
ValueCountFrequency (%)
○ 4
100.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 3
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
② 1
100.0%

처분내용
Text

Distinct110
Distinct (%)15.5%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
2024-05-04T07:27:32.164161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length31
Mean length7.9069111
Min length2

Characters and Unicode

Total characters5606
Distinct characters107
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique64 ?
Unique (%)9.0%

Sample

1st row경고
2nd row직권말소
3rd row직권말소
4th row직권말소
5th row직권말소
ValueCountFrequency (%)
과태료부과 194
17.0%
경고 150
 
13.2%
개선명령 114
 
10.0%
과징금부과 57
 
5.0%
영업정지 55
 
4.8%
과태료 44
 
3.9%
및 36
 
3.2%
부과 35
 
3.1%
납부시 33
 
2.9%
영업소폐쇄 28
 
2.5%
Other values (115) 392
34.4%
2024-05-04T07:27:33.413365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 705
 
12.6%
431
 
7.7%
부 379
 
6.8%
0 365
 
6.5%
료 284
 
5.1%
태 282
 
5.0%
원 211
 
3.8%
만 165
 
2.9%
고 164
 
2.9%
경 163
 
2.9%
Other values (97) 2457
43.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4137
73.8%
Decimal Number 774
 
13.8%
Space Separator 431
 
7.7%
Other Punctuation 93
 
1.7%
Close Punctuation 81
 
1.4%
Open Punctuation 81
 
1.4%
Math Symbol 7
 
0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 705
17.0%
부 379
 
9.2%
료 284
 
6.9%
태 282
 
6.8%
원 211
 
5.1%
만 165
 
4.0%
고 164
 
4.0%
경 163
 
3.9%
개 126
 
3.0%
령 121
 
2.9%
Other values (76) 1537
37.2%
Decimal Number
ValueCountFrequency (%)
0 365
47.2%
2 129
 
16.7%
4 60
 
7.8%
1 59
 
7.6%
6 45
 
5.8%
3 44
 
5.7%
8 31
 
4.0%
5 25
 
3.2%
9 10
 
1.3%
7 6
 
0.8%
Other Punctuation
ValueCountFrequency (%)
, 71
76.3%
. 18
 
19.4%
% 3
 
3.2%
/ 1
 
1.1%
Math Symbol
ValueCountFrequency (%)
× 5
71.4%
~ 1
 
14.3%
= 1
 
14.3%
Space Separator
ValueCountFrequency (%)
431
100.0%
Close Punctuation
ValueCountFrequency (%)
) 81
100.0%
Open Punctuation
ValueCountFrequency (%)
( 81
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4137
73.8%
Common 1469
 
26.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 705
17.0%
부 379
 
9.2%
료 284
 
6.9%
태 282
 
6.8%
원 211
 
5.1%
만 165
 
4.0%
고 164
 
4.0%
경 163
 
3.9%
개 126
 
3.0%
령 121
 
2.9%
Other values (76) 1537
37.2%
Common
ValueCountFrequency (%)
431
29.3%
0 365
24.8%
2 129
 
8.8%
) 81
 
5.5%
( 81
 
5.5%
, 71
 
4.8%
4 60
 
4.1%
1 59
 
4.0%
6 45
 
3.1%
3 44
 
3.0%
Other values (11) 103
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4137
73.8%
ASCII 1464
 
26.1%
None 5
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 705
17.0%
부 379
 
9.2%
료 284
 
6.9%
태 282
 
6.8%
원 211
 
5.1%
만 165
 
4.0%
고 164
 
4.0%
경 163
 
3.9%
개 126
 
3.0%
령 121
 
2.9%
Other values (76) 1537
37.2%
ASCII
ValueCountFrequency (%)
431
29.4%
0 365
24.9%
2 129
 
8.8%
) 81
 
5.5%
( 81
 
5.5%
, 71
 
4.8%
4 60
 
4.1%
1 59
 
4.0%
6 45
 
3.1%
3 44
 
3.0%
Other values (10) 98
 
6.7%
None
ValueCountFrequency (%)
× 5
100.0%

처분기간
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct7
Distinct (%)25.0%
Missing681
Missing (%)96.1%
Infinite0
Infinite (%)0.0%
Mean13.892857
Minimum4
Maximum25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.4 KiB
2024-05-04T07:27:33.957238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile7.7
Q113.75
median15
Q315
95-th percentile17.6
Maximum25
Range21
Interquartile range (IQR)1.25

Descriptive statistics

Standard deviation3.8618676
Coefficient of variation (CV)0.27797504
Kurtosis2.7210045
Mean13.892857
Median Absolute Deviation (MAD)0
Skewness-0.082778433
Sum389
Variance14.914021
MonotonicityNot monotonic
2024-05-04T07:27:34.336280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
15 19
 
2.7%
10 4
 
0.6%
25 1
 
0.1%
4 1
 
0.1%
9 1
 
0.1%
7 1
 
0.1%
19 1
 
0.1%
(Missing) 681
96.1%
ValueCountFrequency (%)
4 1
 
0.1%
7 1
 
0.1%
9 1
 
0.1%
10 4
 
0.6%
15 19
2.7%
19 1
 
0.1%
25 1
 
0.1%
ValueCountFrequency (%)
25 1
 
0.1%
19 1
 
0.1%
15 19
2.7%
10 4
 
0.6%
9 1
 
0.1%
7 1
 
0.1%
4 1
 
0.1%

영업장면적(㎡)
Real number (ℝ)

MISSING 

Distinct276
Distinct (%)40.2%
Missing22
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean379.13572
Minimum0
Maximum5213.41
Zeros5
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size6.4 KiB
2024-05-04T07:27:34.946396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile14.298
Q127.18
median71.76
Q3189
95-th percentile1604.514
Maximum5213.41
Range5213.41
Interquartile range (IQR)161.82

Descriptive statistics

Standard deviation991.15293
Coefficient of variation (CV)2.6142431
Kurtosis16.514569
Mean379.13572
Median Absolute Deviation (MAD)48.76
Skewness4.0979065
Sum260466.24
Variance982384.13
MonotonicityNot monotonic
2024-05-04T07:27:35.747746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
23.0 23
 
3.2%
33.0 20
 
2.8%
5213.41 18
 
2.5%
19.8 16
 
2.3%
66.0 14
 
2.0%
82.5 13
 
1.8%
26.4 12
 
1.7%
90.0 12
 
1.7%
20.0 11
 
1.6%
40.0 10
 
1.4%
Other values (266) 538
75.9%
(Missing) 22
 
3.1%
ValueCountFrequency (%)
0.0 5
0.7%
5.0 1
 
0.1%
5.69 1
 
0.1%
6.0 1
 
0.1%
7.0 5
0.7%
7.36 1
 
0.1%
9.9 1
 
0.1%
10.0 2
 
0.3%
10.9 1
 
0.1%
11.5 1
 
0.1%
ValueCountFrequency (%)
5213.41 18
2.5%
4978.0 6
 
0.8%
3300.0 3
 
0.4%
2251.29 2
 
0.3%
2062.08 1
 
0.1%
1980.0 2
 
0.3%
1822.39 1
 
0.1%
1621.92 2
 
0.3%
1563.9 1
 
0.1%
1479.65 2
 
0.3%

Interactions

2024-05-04T07:27:08.854264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
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2024-05-04T07:27:05.950813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
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2024-05-04T07:27:08.437135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:27:09.735187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:27:05.017615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:27:06.127971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:27:07.443271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:27:08.660155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-04T07:27:36.135050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분일자업종명업태명지도점검일자위반일자처분기간영업장면적(㎡)
처분일자1.0000.6530.6350.9760.9920.6040.201
업종명0.6531.0000.9540.6240.6360.7110.560
업태명0.6350.9541.0000.6290.6380.6900.783
지도점검일자0.9760.6240.6291.0000.9870.0000.137
위반일자0.9920.6360.6380.9871.0000.0000.214
처분기간0.6040.7110.6900.0000.0001.0000.980
영업장면적(㎡)0.2010.5600.7830.1370.2140.9801.000
2024-05-04T07:27:36.638471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명업태명
업종명1.0000.740
업태명0.7401.000
2024-05-04T07:27:36.982039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분일자지도점검일자위반일자처분기간영업장면적(㎡)업종명업태명
처분일자1.0000.9980.998-0.138-0.2270.3320.303
지도점검일자0.9981.0000.999-0.153-0.2250.3100.298
위반일자0.9980.9991.000-0.163-0.2270.3190.305
처분기간-0.138-0.153-0.1631.000-0.3380.5150.536
영업장면적(㎡)-0.227-0.225-0.227-0.3381.0000.2400.494
업종명0.3320.3100.3190.5150.2401.0000.740
업태명0.3030.2980.3050.5360.4940.7401.000

Missing values

2024-05-04T07:27:10.012960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-04T07:27:10.581717image/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.
2024-05-04T07:27:11.006788image/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(㎡)
03070000202402222016-00086일반미용업일반미용업지나인헤어(G9hair)서울특별시 성북구 동소문로20길 24, (동소문동5가)서울특별시 성북구 동소문동5가 109번지20240130처분확정경고법 제11조제1항제4호20240130공중위생관리법 시행규칙 제7조 별표4 제4호자목 개별미용서비스의 최종 지불가격 및 전체 미용서비스의 총액에 관한 내역서를 이용자에게 미리 제공하고 그 사본을 1개월 동안 보관하지 않음경고<NA>39.67
1307000020240124세탁0299세탁업일반세탁업덕영사서울특별시 성북구 장위로 80, (장위동)서울특별시 성북구 장위동 233번지 251호20240112처분확정직권말소법 제11조제3항제2호20240112사업자 등록 말소 후 영업신고 폐업을 하지 않음직권말소<NA>45.0
230700002023122620200003세탁업일반세탁업삼성세탁서울특별시 성북구 화랑로30길 26, (석관동)서울특별시 성북구 석관동 338번지 156호20231213처분확정직권말소법 제11조제3항제2호20231213사업자 등록 폐업 후 영업신고 폐업을 하지 않음직권말소<NA>26.4
3307000020231204미용0543종합미용업일반미용업주노미용실서울특별시 성북구 보국문로11길 23, (정릉동,(2층))서울특별시 성북구 정릉동 396번지 41호 (2층)20231120처분확정직권말소법 제11조제3항제2호20231120사업자 등록 말소 후 영업 폐업신고를 하지 않음직권말소<NA>59.4
43070000202311132021-0021일반미용업일반미용업현정미용실서울특별시 성북구 삼선교로14길 66, 1층 (삼선동2가)서울특별시 성북구 삼선동2가 260번지20231030처분확정직권말소법 제11조제3항제2호202303312023년 3월 31일 성북 세무서장에게 사업자 폐업 신고 후 공중위생영업 폐업 신고를 하지 않음직권말소<NA>25.46
53070000202311132019-00174일반미용업일반미용업헤어더뷰 성신여대점서울특별시 성북구 동소문로20나길 22, 2,3층 (동선동1가)서울특별시 성북구 동선동1가 85번지 80호 2,3층20230919처분확정경고법 제11조제1항제4호20230919미용기구 중 소독한 기구와 소독하지 아니한 기구를 동일 선반에 보관 (시행규칙 제7조위반)경고<NA>165.09
63070000202308072016-00088일반미용업일반미용업이브미용실서울특별시 성북구 장월로 119, (장위동)서울특별시 성북구 장위동 237번지 275호20230713처분확정직권말소법 제11조제3항제2호20230713사업자등록 폐업 후 영업신고 폐업을 하지 않음직권말소<NA>19.8
7307000020230724세탁480세탁업일반세탁업신라세탁서울특별시 성북구 삼선교로14길 14-5, 1층 (삼선동2가)서울특별시 성북구 삼선동2가 107번지 2호 1층20230706처분확정직권말소법 제11조제3항제2호20230706사업자등록 폐업 후 영업신고 폐업하지 않음직권말소<NA>43.2
8307000020230711숙박191숙박업(일반)여관업파브모텔서울특별시 성북구 동소문로20나길 5, (동선동1가)서울특별시 성북구 동선동1가 2번지 10호20230704처분확정과태료 부과법 제82조제2항, 시행령 제89조202307041.제76조의5(재난취약시설 보험ㆍ공제의 가입 등) ② 다음 각 호에 해당하는 시설 중 대통령령으로정하는 시설을 소유ㆍ관리 또는 점유하는 자는 해당 시설에서 발생하는 화재, 붕괴, 폭발 등으로인한 타인의 생명ㆍ신체나 재산상의 손해를 보상하기 위하여 보험 또는 공제에 가입하여야 한다. 2.보험미가입기간: 23.5.14.~23.5.15. (보험갱신일(시정): 23.5.16.)과태료 부과<NA>673.3
93070000202306262022-0002피부미용업, 화장ㆍ분장 미용업메이크업업오늘(oneul)서울특별시 성북구 장월로1마길 5, 승진빌딩 201호 (하월곡동)서울특별시 성북구 하월곡동 21번지 1호 승진빌딩20230605처분확정과징금부과법 제11조제1항제4호20230518미용업자의 의료행위(눈썹 문신)과징금부과<NA>179.78
시군구코드처분일자교부번호업종명업태명업소명소재지도로명소재지지번지도점검일자행정처분상태처분명법적근거위반일자위반내용처분내용처분기간영업장면적(㎡)
699307000020030210<NA>이용업일반이용업버킹검<NA>서울특별시 성북구 종암동 3번지 1237호20030110처분확정개선명령공중위생관리법제3조20030110시설 및 설비기준 위반개선명령<NA><NA>
700307000020030210숙박0022숙박업(일반)여관업한일장<NA>서울특별시 성북구 석관동 332번지 560호20030106처분확정영업정지공중위생관리법 제11조제1항20030106청소년 이성혼숙영업정지<NA>172.4
701307000020030210숙박0045숙박업(일반)여관업삼덕<NA>서울특별시 성북구 종암동 3번지 1259호20021218처분확정영업정지공중위생관리법 제11조제1항20031218윤락행위 알선영업정지<NA>75.9
702307000020030121이용0160이용업일반이용업동부<NA>서울특별시 성북구 하월곡동 37번지 15호20021128처분확정영업정지공중위생관리법제3조20021128시설 및 설비기준 위반영업정지1559.4
703307000020030121숙박0007숙박업(일반)여관업영빈장<NA>서울특별시 성북구 하월곡동 90번지 715호20021206처분확정영업정지공중위생관리법 제11조제1항20021206윤락행위 알선영업정지<NA>59.61
704307000020030106이용0186이용업일반이용업신세계<NA>서울특별시 성북구 길음동 25번지 7호20021206처분확정개선명령공중위생관리법제3조제1항20021206시설및설비기준 위반(의자사이 칸막이 설치)개선명령<NA>95.0
705307000020030103이용0207이용업일반이용업제일<NA>서울특별시 성북구 종암동 3번지 395호20021122처분확정개선명령공중위생관리법 제3조제1항20021122시설 및 시설기준위반(의자사이 칸막이 설치)개선명령<NA>132.0
70630700002001030902900430100343이용업일반이용업유진<NA>서울특별시 성북구 장위동 64번지 123호20010210처분확정영업장폐쇄,이용사면허취소공중위생관리법제11조1항20010210영업정지기간중영업영업장폐쇄,이용사면허취소<NA>76.34
70730700002001020902900430100316이용업일반이용업광명<NA>서울특별시 성북구 보문동5가 156번지 3호20010204처분확정개선명령공중위생관리법제11조2항20011016시설및설비기준위반개선명령<NA>73.74
70830700002001011602900430100387이용업일반이용업예진<NA>서울특별시 성북구 장위동 6번지 111호20001206처분확정영업정지15일공중위생관리법제11조2항20011016시설기준위반(밀실설치)영업정지15일15<NA>

Duplicate rows

Most frequently occurring

시군구코드처분일자교부번호업종명업태명업소명소재지도로명소재지지번지도점검일자행정처분상태처분명법적근거위반일자위반내용처분내용처분기간영업장면적(㎡)# duplicates
13307000020091217세탁0406세탁업일반세탁업크린토피아성북지사<NA>서울특별시 성북구 성북동 113번지 86호20091125처분확정경고공중위생관리법11조20091125출입기록부미비치경고<NA>292.04
0307000020030414이용0162이용업일반이용업카리브이용원<NA>서울특별시 성북구 장위동 65번지 171호20030316처분확정업무정지공중위생관리법제7조20030316윤락행위업무정지<NA>33.02
1307000020030414이용0162이용업일반이용업카리브이용원<NA>서울특별시 성북구 장위동 65번지 171호20030316처분확정영업정지공중위생관리법제7조20030316윤락행위영업정지<NA>33.02
2307000020030610숙박0171숙박업(일반)여관업삼미장<NA>서울특별시 성북구 정릉동 416번지 10호20030417처분확정영업정지공중위생관리법 제11조제1항20030417윤락행위 알선영업정지<NA>66.02
3307000020050303숙박0082숙박업(일반)여관업로즈힐모텔<NA>서울특별시 성북구 정릉동 397번지 41호20050217처분확정개선명령, 과태료50만원공중위생관리법 제4조7항20050217숙박업소 접객대에 요금표 미게시개선명령, 과태료50만원<NA>189.02
4307000020050303숙박0082숙박업(일반)여관업로즈힐모텔<NA>서울특별시 성북구 정릉동 397번지 41호20050217처분확정과태료부과 50만원공중위생관리법 제4조7항20050217숙박업소 접객대에 요금표 미게시과태료부과 50만원<NA>189.02
5307000020050316숙박0124숙박업(일반)여관업신도<NA>서울특별시 성북구 길음동 530번지 30호20050222처분확정개선명령, 과태료50만원공중위생관리법 제4조7항20050222숙박업소 접객대에 요금표 미 게시개선명령, 과태료50만원<NA>65.92
6307000020050316숙박0124숙박업(일반)여관업신도<NA>서울특별시 성북구 길음동 530번지 30호20050222처분확정과태료부과50만원공중위생관리법 제4조7항20050222숙박업소 접객대에 요금표 미 게시과태료부과50만원<NA>65.92
7307000020060206숙박0046숙박업(일반)여관업한일<NA>서울특별시 성북구 종암동 3번지 595호20051228처분확정경고및과태료부과공중위생관리법제17조200512282005년도 영업자위생교육 미필경고및과태료부과<NA>82.52
8307000020060206숙박0046숙박업(일반)여관업한일<NA>서울특별시 성북구 종암동 3번지 595호20051228처분확정과태료부과20만원공중위생관리법제17조200512282005년도 영업자위생교육 미필과태료부과20만원<NA>82.52