Overview

Dataset statistics

Number of variables4
Number of observations117
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.1 KiB
Average record size in memory36.1 B

Variable types

Numeric3
Text1

Dataset

Description순번,명칭,X좌표,Y좌표
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-11987/S/1/datasetView.do

Alerts

순번 has unique valuesUnique
X좌표 has unique valuesUnique
Y좌표 has unique valuesUnique

Reproduction

Analysis started2023-12-11 05:26:38.837904
Analysis finished2023-12-11 05:26:40.249163
Duration1.41 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct117
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59
Minimum1
Maximum117
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T14:26:40.362647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.8
Q130
median59
Q388
95-th percentile111.2
Maximum117
Range116
Interquartile range (IQR)58

Descriptive statistics

Standard deviation33.919021
Coefficient of variation (CV)0.57489866
Kurtosis-1.2
Mean59
Median Absolute Deviation (MAD)29
Skewness0
Sum6903
Variance1150.5
MonotonicityNot monotonic
2023-12-11T14:26:40.572879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34 1
 
0.9%
108 1
 
0.9%
3 1
 
0.9%
2 1
 
0.9%
1 1
 
0.9%
117 1
 
0.9%
116 1
 
0.9%
115 1
 
0.9%
114 1
 
0.9%
113 1
 
0.9%
Other values (107) 107
91.5%
ValueCountFrequency (%)
1 1
0.9%
2 1
0.9%
3 1
0.9%
4 1
0.9%
5 1
0.9%
6 1
0.9%
7 1
0.9%
8 1
0.9%
9 1
0.9%
10 1
0.9%
ValueCountFrequency (%)
117 1
0.9%
116 1
0.9%
115 1
0.9%
114 1
0.9%
113 1
0.9%
112 1
0.9%
111 1
0.9%
110 1
0.9%
109 1
0.9%
108 1
0.9%

명칭
Text

Distinct115
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-11T14:26:40.903623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length20
Mean length10.350427
Min length2

Characters and Unicode

Total characters1211
Distinct characters209
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique113 ?
Unique (%)96.6%

Sample

1st row지하철 분당선 양재시민의숲역
2nd row불국사
3rd row매헌 윤봉길의사 기념관
4th row코스 8-3 명상길 시작점
5th row양재 시민의 숲
ValueCountFrequency (%)
코스 25
 
8.2%
지하철 19
 
6.2%
앞 11
 
3.6%
출구 8
 
2.6%
4번출구 7
 
2.3%
시작점 5
 
1.6%
6호선 4
 
1.3%
끝부분 4
 
1.3%
4호선 3
 
1.0%
4번 3
 
1.0%
Other values (174) 215
70.7%
2023-12-11T14:26:41.440777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
187
 
15.4%
역 33
 
2.7%
지 31
 
2.6%
구 31
 
2.6%
- 30
 
2.5%
원 28
 
2.3%
코 27
 
2.2%
스 27
 
2.2%
선 25
 
2.1%
번 23
 
1.9%
Other values (199) 769
63.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 863
71.3%
Space Separator 187
 
15.4%
Decimal Number 118
 
9.7%
Dash Punctuation 30
 
2.5%
Other Punctuation 8
 
0.7%
Open Punctuation 2
 
0.2%
Close Punctuation 2
 
0.2%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
역 33
 
3.8%
지 31
 
3.6%
구 31
 
3.6%
원 28
 
3.2%
코 27
 
3.1%
스 27
 
3.1%
선 25
 
2.9%
번 23
 
2.7%
출 23
 
2.7%
사 22
 
2.5%
Other values (182) 593
68.7%
Decimal Number
ValueCountFrequency (%)
1 22
18.6%
4 20
16.9%
3 19
16.1%
2 19
16.1%
6 11
9.3%
7 7
 
5.9%
5 7
 
5.9%
8 7
 
5.9%
9 4
 
3.4%
0 2
 
1.7%
Other Punctuation
ValueCountFrequency (%)
. 6
75.0%
/ 2
 
25.0%
Space Separator
ValueCountFrequency (%)
187
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 863
71.3%
Common 347
28.7%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
역 33
 
3.8%
지 31
 
3.6%
구 31
 
3.6%
원 28
 
3.2%
코 27
 
3.1%
스 27
 
3.1%
선 25
 
2.9%
번 23
 
2.7%
출 23
 
2.7%
사 22
 
2.5%
Other values (182) 593
68.7%
Common
ValueCountFrequency (%)
187
53.9%
- 30
 
8.6%
1 22
 
6.3%
4 20
 
5.8%
3 19
 
5.5%
2 19
 
5.5%
6 11
 
3.2%
7 7
 
2.0%
5 7
 
2.0%
8 7
 
2.0%
Other values (6) 18
 
5.2%
Latin
ValueCountFrequency (%)
m 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 863
71.3%
ASCII 348
28.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
187
53.7%
- 30
 
8.6%
1 22
 
6.3%
4 20
 
5.7%
3 19
 
5.5%
2 19
 
5.5%
6 11
 
3.2%
7 7
 
2.0%
5 7
 
2.0%
8 7
 
2.0%
Other values (7) 19
 
5.5%
Hangul
ValueCountFrequency (%)
역 33
 
3.8%
지 31
 
3.6%
구 31
 
3.6%
원 28
 
3.2%
코 27
 
3.1%
스 27
 
3.1%
선 25
 
2.9%
번 23
 
2.7%
출 23
 
2.7%
사 22
 
2.5%
Other values (182) 593
68.7%

X좌표
Real number (ℝ)

UNIQUE 

Distinct117
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean200953
Minimum187218.45
Maximum214130.65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T14:26:41.622748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum187218.45
5-th percentile188584.85
Q1193141.99
median201685.27
Q3208165.91
95-th percentile212652.15
Maximum214130.65
Range26912.198
Interquartile range (IQR)15023.922

Descriptive statistics

Standard deviation8159.2494
Coefficient of variation (CV)0.040602774
Kurtosis-1.3690808
Mean200953
Median Absolute Deviation (MAD)7292.985
Skewness-0.11587911
Sum23511502
Variance66573350
MonotonicityNot monotonic
2023-12-11T14:26:41.789798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
203385.861 1
 
0.9%
200596.794 1
 
0.9%
208152.47 1
 
0.9%
204239.756 1
 
0.9%
204113.489 1
 
0.9%
209451.677 1
 
0.9%
212414.435 1
 
0.9%
213861.314 1
 
0.9%
203207.451 1
 
0.9%
201453.706 1
 
0.9%
Other values (107) 107
91.5%
ValueCountFrequency (%)
187218.45 1
0.9%
187250.429 1
0.9%
187327.598 1
0.9%
187928.696 1
0.9%
188038.177 1
0.9%
188572.844 1
0.9%
188587.856 1
0.9%
189038.697 1
0.9%
189116.66 1
0.9%
189606.814 1
0.9%
ValueCountFrequency (%)
214130.648 1
0.9%
214081.484 1
0.9%
213861.314 1
0.9%
213644.911 1
0.9%
213644.068 1
0.9%
213603.009 1
0.9%
212414.435 1
0.9%
212285.621 1
0.9%
211751.408 1
0.9%
211487.799 1
0.9%

Y좌표
Real number (ℝ)

UNIQUE 

Distinct117
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean451214.32
Minimum437173.09
Maximum465532.43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T14:26:41.937366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum437173.09
5-th percentile439522.72
Q1442290.75
median451330.34
Q3457931.52
95-th percentile464421.25
Maximum465532.43
Range28359.335
Interquartile range (IQR)15640.769

Descriptive statistics

Standard deviation8374.3771
Coefficient of variation (CV)0.018559644
Kurtosis-1.2277463
Mean451214.32
Median Absolute Deviation (MAD)7989.014
Skewness0.019319557
Sum52792076
Variance70130193
MonotonicityNot monotonic
2023-12-11T14:26:42.105614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
441237.91 1
 
0.9%
462361.825 1
 
0.9%
464185.252 1
 
0.9%
465532.426 1
 
0.9%
465475.962 1
 
0.9%
443210.309 1
 
0.9%
445888.91 1
 
0.9%
450653.967 1
 
0.9%
465155.772 1
 
0.9%
462448.022 1
 
0.9%
Other values (107) 107
91.5%
ValueCountFrequency (%)
437173.091 1
0.9%
437204.548 1
0.9%
437214.826 1
0.9%
437220.777 1
0.9%
438523.028 1
0.9%
439225.924 1
0.9%
439596.915 1
0.9%
439727.672 1
0.9%
440208.998 1
0.9%
440795.73 1
0.9%
ValueCountFrequency (%)
465532.426 1
0.9%
465509.294 1
0.9%
465475.962 1
0.9%
465475.355 1
0.9%
465155.772 1
0.9%
465008.508 1
0.9%
464274.438 1
0.9%
464185.252 1
0.9%
463411.972 1
0.9%
463197.473 1
0.9%

Interactions

2023-12-11T14:26:39.754194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T14:26:39.042684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T14:26:39.393818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T14:26:39.857625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T14:26:39.152696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T14:26:39.501984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T14:26:39.954512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T14:26:39.268769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T14:26:39.638158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T14:26:42.215689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번X좌표Y좌표
순번1.0000.8440.825
X좌표0.8441.0000.853
Y좌표0.8250.8531.000
2023-12-11T14:26:42.631999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번X좌표Y좌표
순번1.000-0.4590.052
X좌표-0.4591.0000.110
Y좌표0.0520.1101.000

Missing values

2023-12-11T14:26:40.088841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T14:26:40.204490image/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

순번명칭X좌표Y좌표
034지하철 분당선 양재시민의숲역203385.861441237.91
135불국사206637.963442003.833
236매헌 윤봉길의사 기념관203237.21441151.776
337코스 8-3 명상길 시작점198428.979457039.475
438양재 시민의 숲203131.376441330.863
539대성사201935.407441589.125
640대원사198899.288441496.243
741지하철 2호선 4호선 사당역 4번출구198369.821441728.195
842헌인릉206641.421440854.625
943서울특별시 인재개발원201805.942442290.753
순번명칭X좌표Y좌표
10724광나루역 2번출구209230.254449543.41
10825암사동선사주거지211487.799451233.832
10926샘터공원214081.484451391.104
11027명일공원214130.648450494.042
11128길동자연생태공원213603.009448918.131
11229일자산허브천문공원213644.911448649.161
11330방이동 생태경관보전지역212285.621445834.428
11431문정근린공원211751.408443341.328
11532가든파이브211059.522442028.15
11633수서역 5번출구209054.066443092.489