Overview

Dataset statistics

Number of variables9
Number of observations39
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.0 KiB
Average record size in memory79.4 B

Variable types

Categorical4
Numeric3
Text2

Dataset

Description서울특별시 양천구의 장애인 주차 단속 센서위치 (권역, 장소, 주소, 설치수량, 공영/사설 등)에 대한 정보를 제공합니다.
Author서울특별시 양천구
URLhttps://www.data.go.kr/data/15089777/fileData.do

Alerts

데이터기준일 has constant value ""Constant
위도값 is highly overall correlated with 권역High correlation
경도값 is highly overall correlated with 권역High correlation
권역 is highly overall correlated with 위도값 and 1 other fieldsHigh correlation
장소 has unique valuesUnique

Reproduction

Analysis started2023-12-12 12:03:27.778489
Analysis finished2023-12-12 12:03:29.951117
Duration2.17 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

설치일
Categorical

Distinct2
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size444.0 B
2020
23 
2019
16 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020
2nd row2020
3rd row2020
4th row2020
5th row2020

Common Values

ValueCountFrequency (%)
2020 23
59.0%
2019 16
41.0%

Length

2023-12-12T21:03:30.041941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:03:30.148672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 23
59.0%
2019 16
41.0%

위도값
Real number (ℝ)

HIGH CORRELATION 

Distinct37
Distinct (%)94.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.527921
Minimum37.511901
Maximum37.546094
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-12T21:03:30.276860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.511901
5-th percentile37.512997
Q137.518207
median37.528435
Q337.534695
95-th percentile37.542964
Maximum37.546094
Range0.0341932
Interquartile range (IQR)0.0164881

Descriptive statistics

Standard deviation0.0097762325
Coefficient of variation (CV)0.00026050557
Kurtosis-1.1013309
Mean37.527921
Median Absolute Deviation (MAD)0.0085094
Skewness0.039883336
Sum1463.5889
Variance9.5574721 × 10-5
MonotonicityNot monotonic
2023-12-12T21:03:30.415897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
37.5199255 2
 
5.1%
37.5333938 2
 
5.1%
37.5389361 1
 
2.6%
37.5370611 1
 
2.6%
37.524895 1
 
2.6%
37.5303204 1
 
2.6%
37.524935 1
 
2.6%
37.5331393 1
 
2.6%
37.5349925 1
 
2.6%
37.5185532 1
 
2.6%
Other values (27) 27
69.2%
ValueCountFrequency (%)
37.5119007 1
2.6%
37.51280601 1
2.6%
37.5130177 1
2.6%
37.5159478 1
2.6%
37.5161786 1
2.6%
37.5164386 1
2.6%
37.5167711 1
2.6%
37.5169164 1
2.6%
37.51764923 1
2.6%
37.5178605 1
2.6%
ValueCountFrequency (%)
37.5460939 1
2.6%
37.5447045 1
2.6%
37.5427705 1
2.6%
37.54208086 1
2.6%
37.53976578 1
2.6%
37.5389361 1
2.6%
37.5385259 1
2.6%
37.5370611 1
2.6%
37.5367453 1
2.6%
37.5349925 1
2.6%

경도값
Real number (ℝ)

HIGH CORRELATION 

Distinct37
Distinct (%)94.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.85226
Minimum126.82413
Maximum126.88062
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-12T21:03:30.552876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.82413
5-th percentile126.82671
Q1126.83394
median126.85429
Q3126.86558
95-th percentile126.87862
Maximum126.88062
Range0.056496
Interquartile range (IQR)0.0316437

Descriptive statistics

Standard deviation0.018385793
Coefficient of variation (CV)0.00014493863
Kurtosis-1.4254607
Mean126.85226
Median Absolute Deviation (MAD)0.0168135
Skewness-0.13271616
Sum4947.2383
Variance0.00033803739
MonotonicityNot monotonic
2023-12-12T21:03:30.684822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
126.8348562 2
 
5.1%
126.8765812 2
 
5.1%
126.865468 1
 
2.6%
126.8274714 1
 
2.6%
126.85473 1
 
2.6%
126.8711038 1
 
2.6%
126.8445573 1
 
2.6%
126.8245164 1
 
2.6%
126.8241287 1
 
2.6%
126.8542903 1
 
2.6%
Other values (27) 27
69.2%
ValueCountFrequency (%)
126.8241287 1
2.6%
126.8245164 1
2.6%
126.8269562 1
2.6%
126.8271645 1
2.6%
126.8274714 1
2.6%
126.8284999 1
2.6%
126.8285314 1
2.6%
126.8318536 1
2.6%
126.8321736 1
2.6%
126.8332994 1
2.6%
ValueCountFrequency (%)
126.8806247 1
2.6%
126.8797191 1
2.6%
126.8785006 1
2.6%
126.8765812 2
5.1%
126.8712232 1
2.6%
126.8711038 1
2.6%
126.8690841 1
2.6%
126.8664734 1
2.6%
126.8656996 1
2.6%
126.865468 1
2.6%

권역
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Memory size444.0 B
신월동
17 
목동
13 
신정동
7 
기타
2 

Length

Max length3
Median length3
Mean length2.6153846
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row목동
2nd row목동
3rd row신월동
4th row신월동
5th row신월동

Common Values

ValueCountFrequency (%)
신월동 17
43.6%
목동 13
33.3%
신정동 7
17.9%
기타 2
 
5.1%

Length

2023-12-12T21:03:30.852427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:03:30.977813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신월동 17
43.6%
목동 13
33.3%
신정동 7
17.9%
기타 2
 
5.1%

장소
Text

UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size444.0 B
2023-12-12T21:03:31.231662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length9
Mean length7.4871795
Min length3

Characters and Unicode

Total characters292
Distinct characters82
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

Unique39 ?
Unique (%)100.0%

Sample

1st row목사랑공영주차장
2nd row체비지주차장
3rd row신월3동주민센터
4th row신월5동주민센터
5th row해맞이역사도서관
ValueCountFrequency (%)
주민센터 3
 
6.5%
주차장 2
 
4.3%
계남체육관 1
 
2.2%
서남병원 1
 
2.2%
목1동 1
 
2.2%
신월2동 1
 
2.2%
능골공영주차장(주차건물 1
 
2.2%
여울공영주차장 1
 
2.2%
신정1동 1
 
2.2%
가로공원공영(지하 1
 
2.2%
Other values (33) 33
71.7%
2023-12-12T21:03:31.657677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 24
 
8.2%
차 18
 
6.2%
장 17
 
5.8%
공 15
 
5.1%
영 14
 
4.8%
동 10
 
3.4%
터 9
 
3.1%
서 9
 
3.1%
센 9
 
3.1%
민 7
 
2.4%
Other values (72) 160
54.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 271
92.8%
Decimal Number 8
 
2.7%
Space Separator 7
 
2.4%
Open Punctuation 3
 
1.0%
Close Punctuation 3
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 24
 
8.9%
차 18
 
6.6%
장 17
 
6.3%
공 15
 
5.5%
영 14
 
5.2%
동 10
 
3.7%
터 9
 
3.3%
서 9
 
3.3%
센 9
 
3.3%
민 7
 
2.6%
Other values (65) 139
51.3%
Decimal Number
ValueCountFrequency (%)
3 3
37.5%
1 2
25.0%
5 2
25.0%
2 1
 
12.5%
Space Separator
ValueCountFrequency (%)
7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 271
92.8%
Common 21
 
7.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 24
 
8.9%
차 18
 
6.6%
장 17
 
6.3%
공 15
 
5.5%
영 14
 
5.2%
동 10
 
3.7%
터 9
 
3.3%
서 9
 
3.3%
센 9
 
3.3%
민 7
 
2.6%
Other values (65) 139
51.3%
Common
ValueCountFrequency (%)
7
33.3%
( 3
14.3%
) 3
14.3%
3 3
14.3%
1 2
 
9.5%
5 2
 
9.5%
2 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 271
92.8%
ASCII 21
 
7.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 24
 
8.9%
차 18
 
6.6%
장 17
 
6.3%
공 15
 
5.5%
영 14
 
5.2%
동 10
 
3.7%
터 9
 
3.3%
서 9
 
3.3%
센 9
 
3.3%
민 7
 
2.6%
Other values (65) 139
51.3%
ASCII
ValueCountFrequency (%)
7
33.3%
( 3
14.3%
) 3
14.3%
3 3
14.3%
1 2
 
9.5%
5 2
 
9.5%
2 1
 
4.8%

주소
Text

Distinct38
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Memory size444.0 B
2023-12-12T21:03:31.967973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length22
Mean length19.025641
Min length16

Characters and Unicode

Total characters742
Distinct characters45
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

Unique37 ?
Unique (%)94.9%

Sample

1st row서울특별시 양천구 목동중앙남로 57-10
2nd row서울특별시 양천구 목동 908-26
3rd row서울특별시 양천구 남부순환로 54길
4th row서울특별시 양천구 화곡로4길 10
5th row서울특별시 양천구 지양로 37(신월동)
ValueCountFrequency (%)
서울특별시 39
25.0%
양천구 39
25.0%
신월동 9
 
5.8%
목동 7
 
4.5%
신정동 5
 
3.2%
905-32 2
 
1.3%
신정로 2
 
1.3%
81 1
 
0.6%
신정이펜1로 1
 
0.6%
263 1
 
0.6%
Other values (50) 50
32.1%
2023-12-12T21:03:32.414375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
119
16.0%
양 40
 
5.4%
서 39
 
5.3%
울 39
 
5.3%
천 39
 
5.3%
구 39
 
5.3%
시 39
 
5.3%
별 39
 
5.3%
특 39
 
5.3%
동 30
 
4.0%
Other values (35) 280
37.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 461
62.1%
Decimal Number 143
 
19.3%
Space Separator 119
 
16.0%
Dash Punctuation 17
 
2.3%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
양 40
8.7%
서 39
 
8.5%
울 39
 
8.5%
천 39
 
8.5%
구 39
 
8.5%
시 39
 
8.5%
별 39
 
8.5%
특 39
 
8.5%
동 30
 
6.5%
신 19
 
4.1%
Other values (21) 99
21.5%
Decimal Number
ValueCountFrequency (%)
1 27
18.9%
2 23
16.1%
5 17
11.9%
3 17
11.9%
9 15
10.5%
4 10
 
7.0%
8 9
 
6.3%
6 9
 
6.3%
0 9
 
6.3%
7 7
 
4.9%
Space Separator
ValueCountFrequency (%)
119
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 461
62.1%
Common 281
37.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
양 40
8.7%
서 39
 
8.5%
울 39
 
8.5%
천 39
 
8.5%
구 39
 
8.5%
시 39
 
8.5%
별 39
 
8.5%
특 39
 
8.5%
동 30
 
6.5%
신 19
 
4.1%
Other values (21) 99
21.5%
Common
ValueCountFrequency (%)
119
42.3%
1 27
 
9.6%
2 23
 
8.2%
5 17
 
6.0%
- 17
 
6.0%
3 17
 
6.0%
9 15
 
5.3%
4 10
 
3.6%
8 9
 
3.2%
6 9
 
3.2%
Other values (4) 18
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 461
62.1%
ASCII 281
37.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
119
42.3%
1 27
 
9.6%
2 23
 
8.2%
5 17
 
6.0%
- 17
 
6.0%
3 17
 
6.0%
9 15
 
5.3%
4 10
 
3.6%
8 9
 
3.2%
6 9
 
3.2%
Other values (4) 18
 
6.4%
Hangul
ValueCountFrequency (%)
양 40
8.7%
서 39
 
8.5%
울 39
 
8.5%
천 39
 
8.5%
구 39
 
8.5%
시 39
 
8.5%
별 39
 
8.5%
특 39
 
8.5%
동 30
 
6.5%
신 19
 
4.1%
Other values (21) 99
21.5%

설치수량
Real number (ℝ)

Distinct11
Distinct (%)28.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.1025641
Minimum1
Maximum20
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-12T21:03:32.552594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q34
95-th percentile13.5
Maximum20
Range19
Interquartile range (IQR)3

Descriptive statistics

Standard deviation4.7004752
Coefficient of variation (CV)1.1457408
Kurtosis4.0334011
Mean4.1025641
Median Absolute Deviation (MAD)1
Skewness2.1098926
Sum160
Variance22.094467
MonotonicityNot monotonic
2023-12-12T21:03:32.706714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1 12
30.8%
2 10
25.6%
3 6
15.4%
4 2
 
5.1%
6 2
 
5.1%
8 2
 
5.1%
11 1
 
2.6%
18 1
 
2.6%
12 1
 
2.6%
13 1
 
2.6%
ValueCountFrequency (%)
1 12
30.8%
2 10
25.6%
3 6
15.4%
4 2
 
5.1%
6 2
 
5.1%
8 2
 
5.1%
11 1
 
2.6%
12 1
 
2.6%
13 1
 
2.6%
18 1
 
2.6%
ValueCountFrequency (%)
20 1
 
2.6%
18 1
 
2.6%
13 1
 
2.6%
12 1
 
2.6%
11 1
 
2.6%
8 2
 
5.1%
6 2
 
5.1%
4 2
 
5.1%
3 6
15.4%
2 10
25.6%

구분
Categorical

Distinct3
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size444.0 B
공영
29 
사설
6 
타기관
4 

Length

Max length3
Median length2
Mean length2.1025641
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공영 29
74.4%
사설 6
 
15.4%
타기관 4
 
10.3%

Length

2023-12-12T21:03:32.896900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:03:33.047182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공영 29
74.4%
사설 6
 
15.4%
타기관 4
 
10.3%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size444.0 B
2023-11-20
39 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-11-20
2nd row2023-11-20
3rd row2023-11-20
4th row2023-11-20
5th row2023-11-20

Common Values

ValueCountFrequency (%)
2023-11-20 39
100.0%

Length

2023-12-12T21:03:33.204990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:03:33.331542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-11-20 39
100.0%

Interactions

2023-12-12T21:03:28.821211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:28.130385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:28.473848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:28.940614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:28.240861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:28.585820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:29.133360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:28.363431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:03:28.689285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:03:33.418188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치일위도값경도값권역장소주소설치수량구분
설치일1.0000.4230.0000.2891.0000.0000.0000.000
위도값0.4231.0000.5990.8051.0001.0000.2780.231
경도값0.0000.5991.0000.7241.0001.0000.4560.000
권역0.2890.8050.7241.0001.0001.0000.8550.347
장소1.0001.0001.0001.0001.0001.0001.0001.000
주소0.0001.0001.0001.0001.0001.0001.0000.000
설치수량0.0000.2780.4560.8551.0001.0001.0000.458
구분0.0000.2310.0000.3471.0000.0000.4581.000
2023-12-12T21:03:33.573787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분설치일권역
구분1.0000.0000.328
설치일0.0001.0000.182
권역0.3280.1821.000
2023-12-12T21:03:33.676746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도값경도값설치수량설치일권역구분
위도값1.0000.045-0.3610.2780.5700.099
경도값0.0451.0000.1820.0000.5160.000
설치수량-0.3610.1821.0000.0000.4970.297
설치일0.2780.0000.0001.0000.1820.000
권역0.5700.5160.4970.1821.0000.328
구분0.0990.0000.2970.0000.3281.000

Missing values

2023-12-12T21:03:29.668488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:03:29.883286image/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

설치일위도값경도값권역장소주소설치수량구분데이터기준일
0202037.538936126.865468목동목사랑공영주차장서울특별시 양천구 목동중앙남로 57-101공영2023-11-20
1202037.536745126.880625목동체비지주차장서울특별시 양천구 목동 908-261공영2023-11-20
2202037.531793126.826956신월동신월3동주민센터서울특별시 양천구 남부순환로 54길1공영2023-11-20
3202037.538526126.827164신월동신월5동주민센터서울특별시 양천구 화곡로4길 101공영2023-11-20
4202037.519925126.834856신월동해맞이역사도서관서울특별시 양천구 지양로 37(신월동)1공영2023-11-20
5202037.524328126.845069신월동경창시장공영주차장서울특별시 양천구 신월동 482-111공영2023-11-20
6202037.52765126.831854신월동서서울예술교육센터서울특별시 양천구 남부순환로64길 21타기관2023-11-20
7202037.512806126.834581기타이든채서울특별시 양천구 신정로7길 7511사설2023-11-20
8202037.511901126.852975기타신트리3단지서울특별시 양천구 신정로 29018사설2023-11-20
9202037.544705126.864428목동목3동주민센터서울특별시 양천구 목동중앙남로16나길 552공영2023-11-20
설치일위도값경도값권역장소주소설치수량구분데이터기준일
29201937.528679126.878501목동목동공영주차장서울특별시 양천구 목동 91513공영2023-11-20
30201937.533394126.876581목동양천도서관서울특별시 양천구 목동 905-322타기관2023-11-20
31201937.516771126.8657신정동양천경찰서서울특별시 양천구 신정동 3212타기관2023-11-20
32201937.52563126.871223목동이마트목동점서울특별시 양천구 목동 962-120사설2023-11-20
33201937.533517126.879719목동목동5단지서울특별시 양천구 목동 9133사설2023-11-20
34201937.534397126.828531신월동신우공영주차장(주차건물)서울특별시 양천구 신월동 166-233공영2023-11-20
35201937.516439126.863346신정동양천문화회관서울특별시 양천구 신정동 3223공영2023-11-20
36201937.516179126.864421신정동양천구민체육센터서울특별시 양천구 신정동 322-103공영2023-11-20
37201937.516916126.866473신정동양천구청서울특별시 양천구 신정동 321-46공영2023-11-20
38201937.519925126.834856신월동해맞이 공영주차장서울특별시 양천구 신월동 9878공영2023-11-20