Overview

Dataset statistics

Number of variables7
Number of observations289
Missing cells36
Missing cells (%)1.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.2 KiB
Average record size in memory57.5 B

Variable types

Numeric1
Categorical3
Text3

Dataset

Description인천광역시 남동구 공중위생업소 서비스평가 결과에 대한 데이터로 연번, 평가구분, 업소명, 업종, 소재지, 전화번호, 데이터기준일자를 제공합니다.
Author인천광역시 남동구
URLhttps://www.data.go.kr/data/15090614/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 평가구분 and 1 other fieldsHigh correlation
평가구분 is highly overall correlated with 연번High correlation
업종 is highly overall correlated with 연번High correlation
전화번호 has 36 (12.5%) missing valuesMissing
연번 has unique valuesUnique
소재지(도로명) has unique valuesUnique

Reproduction

Analysis started2023-12-12 19:59:18.534330
Analysis finished2023-12-12 19:59:19.128867
Duration0.59 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct289
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean145
Minimum1
Maximum289
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2023-12-13T04:59:19.191488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile15.4
Q173
median145
Q3217
95-th percentile274.6
Maximum289
Range288
Interquartile range (IQR)144

Descriptive statistics

Standard deviation83.571327
Coefficient of variation (CV)0.57635398
Kurtosis-1.2
Mean145
Median Absolute Deviation (MAD)72
Skewness0
Sum41905
Variance6984.1667
MonotonicityStrictly increasing
2023-12-13T04:59:19.327851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
218 1
 
0.3%
198 1
 
0.3%
197 1
 
0.3%
196 1
 
0.3%
195 1
 
0.3%
194 1
 
0.3%
193 1
 
0.3%
192 1
 
0.3%
191 1
 
0.3%
Other values (279) 279
96.5%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
289 1
0.3%
288 1
0.3%
287 1
0.3%
286 1
0.3%
285 1
0.3%
284 1
0.3%
283 1
0.3%
282 1
0.3%
281 1
0.3%
280 1
0.3%

평가구분
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
녹색(최우수)
141 
황색(우수)
113 
백색(일반관리)
35 

Length

Max length8
Median length7
Mean length6.7301038
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row녹색(최우수)
2nd row녹색(최우수)
3rd row녹색(최우수)
4th row녹색(최우수)
5th row녹색(최우수)

Common Values

ValueCountFrequency (%)
녹색(최우수) 141
48.8%
황색(우수) 113
39.1%
백색(일반관리) 35
 
12.1%

Length

2023-12-13T04:59:19.451034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:59:19.544787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
녹색(최우수 141
48.8%
황색(우수 113
39.1%
백색(일반관리 35
 
12.1%

업소명
Text

Distinct273
Distinct (%)94.5%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2023-12-13T04:59:19.754026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length16
Mean length5.4636678
Min length2

Characters and Unicode

Total characters1579
Distinct characters293
Distinct categories8 ?
Distinct scripts5 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique262 ?
Unique (%)90.7%

Sample

1st rowcf 모텔
2nd rowHOTEL THE DESIGNERS INCHEON
3rd rowK(케이)
4th row골드코스트호텔인천
5th row골든호텔
ValueCountFrequency (%)
호텔 6
 
1.9%
주공세탁소 4
 
1.3%
현대세탁소 4
 
1.3%
백양세탁소 3
 
1.0%
모텔 3
 
1.0%
럭키세탁 2
 
0.6%
신일세탁소 2
 
0.6%
드라이119세탁 2
 
0.6%
엄마손운동화손세탁 2
 
0.6%
충남세탁소 2
 
0.6%
Other values (277) 281
90.4%
2023-12-13T04:59:20.324270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
세 143
 
9.1%
탁 142
 
9.0%
소 90
 
5.7%
텔 56
 
3.5%
사 41
 
2.6%
호 36
 
2.3%
모 29
 
1.8%
스 26
 
1.6%
크 23
 
1.5%
22
 
1.4%
Other values (283) 971
61.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1471
93.2%
Uppercase Letter 39
 
2.5%
Decimal Number 24
 
1.5%
Space Separator 22
 
1.4%
Open Punctuation 9
 
0.6%
Close Punctuation 9
 
0.6%
Lowercase Letter 4
 
0.3%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
세 143
 
9.7%
탁 142
 
9.7%
소 90
 
6.1%
텔 56
 
3.8%
사 41
 
2.8%
호 36
 
2.4%
모 29
 
2.0%
스 26
 
1.8%
크 23
 
1.6%
리 21
 
1.4%
Other values (252) 864
58.7%
Uppercase Letter
ValueCountFrequency (%)
E 6
15.4%
S 4
10.3%
O 4
10.3%
M 3
7.7%
T 3
7.7%
N 3
7.7%
H 3
7.7%
I 2
 
5.1%
R 2
 
5.1%
A 2
 
5.1%
Other values (6) 7
17.9%
Decimal Number
ValueCountFrequency (%)
1 7
29.2%
2 6
25.0%
4 4
16.7%
8 2
 
8.3%
5 2
 
8.3%
9 2
 
8.3%
0 1
 
4.2%
Lowercase Letter
ValueCountFrequency (%)
f 1
25.0%
c 1
25.0%
π 1
25.0%
e 1
25.0%
Space Separator
ValueCountFrequency (%)
22
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1470
93.1%
Common 65
 
4.1%
Latin 42
 
2.7%
Han 1
 
0.1%
Greek 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
세 143
 
9.7%
탁 142
 
9.7%
소 90
 
6.1%
텔 56
 
3.8%
사 41
 
2.8%
호 36
 
2.4%
모 29
 
2.0%
스 26
 
1.8%
크 23
 
1.6%
리 21
 
1.4%
Other values (251) 863
58.7%
Latin
ValueCountFrequency (%)
E 6
14.3%
S 4
 
9.5%
O 4
 
9.5%
M 3
 
7.1%
T 3
 
7.1%
N 3
 
7.1%
H 3
 
7.1%
I 2
 
4.8%
R 2
 
4.8%
A 2
 
4.8%
Other values (9) 10
23.8%
Common
ValueCountFrequency (%)
22
33.8%
( 9
13.8%
) 9
13.8%
1 7
 
10.8%
2 6
 
9.2%
4 4
 
6.2%
8 2
 
3.1%
5 2
 
3.1%
9 2
 
3.1%
0 1
 
1.5%
Han
ValueCountFrequency (%)
月 1
100.0%
Greek
ValueCountFrequency (%)
π 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1470
93.1%
ASCII 107
 
6.8%
CJK 1
 
0.1%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
세 143
 
9.7%
탁 142
 
9.7%
소 90
 
6.1%
텔 56
 
3.8%
사 41
 
2.8%
호 36
 
2.4%
모 29
 
2.0%
스 26
 
1.8%
크 23
 
1.6%
리 21
 
1.4%
Other values (251) 863
58.7%
ASCII
ValueCountFrequency (%)
22
20.6%
( 9
 
8.4%
) 9
 
8.4%
1 7
 
6.5%
E 6
 
5.6%
2 6
 
5.6%
S 4
 
3.7%
4 4
 
3.7%
O 4
 
3.7%
M 3
 
2.8%
Other values (20) 33
30.8%
CJK
ValueCountFrequency (%)
月 1
100.0%
None
ValueCountFrequency (%)
π 1
100.0%

업종
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
세탁업
184 
숙박업
76 
목욕장업
29 

Length

Max length4
Median length3
Mean length3.100346
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
세탁업 184
63.7%
숙박업 76
26.3%
목욕장업 29
 
10.0%

Length

2023-12-13T04:59:20.431876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:59:20.514363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
세탁업 184
63.7%
숙박업 76
26.3%
목욕장업 29
 
10.0%

소재지(도로명)
Text

UNIQUE 

Distinct289
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2023-12-13T04:59:20.748896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length50
Mean length34.83737
Min length21

Characters and Unicode

Total characters10068
Distinct characters236
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique289 ?
Unique (%)100.0%

Sample

1st row인천광역시 남동구 용천로153번길 50 (간석동)
2nd row인천광역시 남동구 남동대로765번길 8 (구월동, 3층~18층)
3rd row인천광역시 남동구 남동대로777번길 35 (구월동)
4th row인천광역시 남동구 논현로26번길 46, 1층 일부,6~15층 일부호 (논현동)
5th row인천광역시 남동구 석촌로 57, 1층 일부, 2~7층 (간석동)
ValueCountFrequency (%)
인천광역시 287
 
15.5%
남동구 287
 
15.5%
간석동 83
 
4.5%
1층 65
 
3.5%
구월동 54
 
2.9%
만수동 39
 
2.1%
논현동 38
 
2.1%
상가동 30
 
1.6%
2층 20
 
1.1%
남촌동 11
 
0.6%
Other values (563) 934
50.5%
2023-12-13T04:59:21.244381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1560
 
15.5%
동 670
 
6.7%
1 435
 
4.3%
구 394
 
3.9%
남 350
 
3.5%
인 322
 
3.2%
( 312
 
3.1%
) 312
 
3.1%
로 310
 
3.1%
천 299
 
3.0%
Other values (226) 5104
50.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5862
58.2%
Decimal Number 1694
 
16.8%
Space Separator 1560
 
15.5%
Open Punctuation 312
 
3.1%
Close Punctuation 312
 
3.1%
Other Punctuation 260
 
2.6%
Dash Punctuation 36
 
0.4%
Math Symbol 17
 
0.2%
Uppercase Letter 15
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 670
 
11.4%
구 394
 
6.7%
남 350
 
6.0%
인 322
 
5.5%
로 310
 
5.3%
천 299
 
5.1%
역 298
 
5.1%
시 293
 
5.0%
광 290
 
4.9%
길 204
 
3.5%
Other values (201) 2432
41.5%
Decimal Number
ValueCountFrequency (%)
1 435
25.7%
2 237
14.0%
6 160
 
9.4%
0 148
 
8.7%
4 148
 
8.7%
3 142
 
8.4%
5 134
 
7.9%
7 123
 
7.3%
9 84
 
5.0%
8 83
 
4.9%
Uppercase Letter
ValueCountFrequency (%)
A 4
26.7%
B 4
26.7%
L 3
20.0%
T 2
13.3%
P 1
 
6.7%
H 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
, 253
97.3%
/ 3
 
1.2%
@ 3
 
1.2%
. 1
 
0.4%
Space Separator
ValueCountFrequency (%)
1560
100.0%
Open Punctuation
ValueCountFrequency (%)
( 312
100.0%
Close Punctuation
ValueCountFrequency (%)
) 312
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 36
100.0%
Math Symbol
ValueCountFrequency (%)
~ 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5861
58.2%
Common 4191
41.6%
Latin 15
 
0.1%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 670
 
11.4%
구 394
 
6.7%
남 350
 
6.0%
인 322
 
5.5%
로 310
 
5.3%
천 299
 
5.1%
역 298
 
5.1%
시 293
 
5.0%
광 290
 
4.9%
길 204
 
3.5%
Other values (200) 2431
41.5%
Common
ValueCountFrequency (%)
1560
37.2%
1 435
 
10.4%
( 312
 
7.4%
) 312
 
7.4%
, 253
 
6.0%
2 237
 
5.7%
6 160
 
3.8%
0 148
 
3.5%
4 148
 
3.5%
3 142
 
3.4%
Other values (9) 484
 
11.5%
Latin
ValueCountFrequency (%)
A 4
26.7%
B 4
26.7%
L 3
20.0%
T 2
13.3%
P 1
 
6.7%
H 1
 
6.7%
Han
ValueCountFrequency (%)
內 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5861
58.2%
ASCII 4206
41.8%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1560
37.1%
1 435
 
10.3%
( 312
 
7.4%
) 312
 
7.4%
, 253
 
6.0%
2 237
 
5.6%
6 160
 
3.8%
0 148
 
3.5%
4 148
 
3.5%
3 142
 
3.4%
Other values (15) 499
 
11.9%
Hangul
ValueCountFrequency (%)
동 670
 
11.4%
구 394
 
6.7%
남 350
 
6.0%
인 322
 
5.5%
로 310
 
5.3%
천 299
 
5.1%
역 298
 
5.1%
시 293
 
5.0%
광 290
 
4.9%
길 204
 
3.5%
Other values (200) 2431
41.5%
CJK
ValueCountFrequency (%)
內 1
100.0%

전화번호
Text

MISSING 

Distinct253
Distinct (%)100.0%
Missing36
Missing (%)12.5%
Memory size2.4 KiB
2023-12-13T04:59:21.500781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.011858
Min length12

Characters and Unicode

Total characters3039
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

Unique253 ?
Unique (%)100.0%

Sample

1st row032-429-7478
2nd row032-431-3330
3rd row032-710-5230
4th row032-427-9000
5th row032-435-0113
ValueCountFrequency (%)
032-439-9005 1
 
0.4%
032-426-2737 1
 
0.4%
032-461-3567 1
 
0.4%
032-467-7233 1
 
0.4%
032-461-3547 1
 
0.4%
032-463-2115 1
 
0.4%
032-421-1281 1
 
0.4%
032-446-7600 1
 
0.4%
032-465-2681 1
 
0.4%
032-467-8107 1
 
0.4%
Other values (243) 243
96.0%
2023-12-13T04:59:21.973165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 506
16.7%
2 447
14.7%
0 436
14.3%
3 435
14.3%
4 360
11.8%
6 223
7.3%
7 155
 
5.1%
1 127
 
4.2%
5 124
 
4.1%
8 123
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2533
83.3%
Dash Punctuation 506
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 447
17.6%
0 436
17.2%
3 435
17.2%
4 360
14.2%
6 223
8.8%
7 155
 
6.1%
1 127
 
5.0%
5 124
 
4.9%
8 123
 
4.9%
9 103
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 506
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3039
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 506
16.7%
2 447
14.7%
0 436
14.3%
3 435
14.3%
4 360
11.8%
6 223
7.3%
7 155
 
5.1%
1 127
 
4.2%
5 124
 
4.1%
8 123
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3039
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 506
16.7%
2 447
14.7%
0 436
14.3%
3 435
14.3%
4 360
11.8%
6 223
7.3%
7 155
 
5.1%
1 127
 
4.2%
5 124
 
4.1%
8 123
 
4.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2023-09-16
289 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-09-16
2nd row2023-09-16
3rd row2023-09-16
4th row2023-09-16
5th row2023-09-16

Common Values

ValueCountFrequency (%)
2023-09-16 289
100.0%

Length

2023-12-13T04:59:22.213409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:59:22.366444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-09-16 289
100.0%

Interactions

2023-12-13T04:59:18.911276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T04:59:22.440557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번평가구분업종
연번1.0000.8530.888
평가구분0.8531.0000.388
업종0.8880.3881.000
2023-12-13T04:59:22.552174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
평가구분업종
평가구분1.0000.141
업종0.1411.000
2023-12-13T04:59:22.641467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번평가구분업종
연번1.0000.7630.821
평가구분0.7631.0000.141
업종0.8210.1411.000

Missing values

2023-12-13T04:59:19.004190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T04:59:19.092004image/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.

Sample

연번평가구분업소명업종소재지(도로명)전화번호데이터기준일자
01녹색(최우수)cf 모텔숙박업인천광역시 남동구 용천로153번길 50 (간석동)<NA>2023-09-16
12녹색(최우수)HOTEL THE DESIGNERS INCHEON숙박업인천광역시 남동구 남동대로765번길 8 (구월동, 3층~18층)032-429-74782023-09-16
23녹색(최우수)K(케이)숙박업인천광역시 남동구 남동대로777번길 35 (구월동)032-431-33302023-09-16
34녹색(최우수)골드코스트호텔인천숙박업인천광역시 남동구 논현로26번길 46, 1층 일부,6~15층 일부호 (논현동)032-710-52302023-09-16
45녹색(최우수)골든호텔숙박업인천광역시 남동구 석촌로 57, 1층 일부, 2~7층 (간석동)032-427-90002023-09-16
56녹색(최우수)광명장 여관숙박업인천광역시 남동구 호구포로889번길 16, 3층 (간석동)032-435-01132023-09-16
67녹색(최우수)구월호텔숙박업인천광역시 남동구 선수촌공원로23번길 1 (구월동, 구월호텔)032-465-92292023-09-16
78녹색(최우수)넘버25소래포구점숙박업인천광역시 남동구 소래역로46번길 28, 대영로데오 6,7층 601호,701호 (논현동)032-422-70062023-09-16
89녹색(최우수)노블레스 모텔숙박업인천광역시 남동구 경인로644번길 113 (간석동)032-431-11012023-09-16
910녹색(최우수)느낌호텔숙박업인천광역시 남동구 선수촌공원로23번길 10-11 (구월동)032-427-92222023-09-16
연번평가구분업소명업종소재지(도로명)전화번호데이터기준일자
279280백색(일반관리)우영세탁업인천광역시 남동구 백범로226번길 36 (만수동)032-472-35272023-09-16
280281백색(일반관리)일출세탁소세탁업인천광역시 남동구 백범로406번길 7 (간석동,(동암남6길 9))<NA>2023-09-16
281282백색(일반관리)제일세탁소세탁업인천광역시 남동구 석정로497번길 64 (간석동)032-428-76542023-09-16
282283백색(일반관리)조세탁소세탁업인천광역시 남동구 함박뫼로 437 (논현동,주공@2차상가 지하일부)032-446-30012023-09-16
283284백색(일반관리)주공세탁세탁업인천광역시 남동구 논고개로334번길 11, 상가동 2층 203호 (도림동, 도림주공그린빌1단지아파트)032-446-74722023-09-16
284285백색(일반관리)품질세탁소세탁업인천광역시 남동구 남촌동로26번길 9 (남촌동)032-469-75422023-09-16
285286백색(일반관리)풍림사세탁업인천광역시 남동구 호구포로535번길 16, 풍림아파트상가 상가동 2층 207호 (남촌동)032-469-38352023-09-16
286287백색(일반관리)행복세탁세탁업인천광역시 남동구 소래역남로 41 (논현동, 한화에코메트로 상가동(516동) 204호)032-424-09092023-09-16
287288백색(일반관리)현대세탁소세탁업인천광역시 남동구 간석로66번길 25 (간석동)032-425-32602023-09-16
288289백색(일반관리)흥균세탁세탁업인천광역시 남동구 용천로 190-11 (간석동)032-427-80952023-09-16