Overview

Dataset statistics

Number of variables4
Number of observations53
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 KiB
Average record size in memory36.5 B

Variable types

Text2
Numeric2

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15251/F/1/datasetView.do

Alerts

DSRC_ID has unique valuesUnique
SET_LOC_NAME has unique valuesUnique
XPOINT has unique valuesUnique
YPOINT has unique valuesUnique

Reproduction

Analysis started2023-12-11 06:43:55.779861
Analysis finished2023-12-11 06:43:56.559491
Duration0.78 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

DSRC_ID
Text

UNIQUE 

Distinct53
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size556.0 B
2023-12-11T15:43:56.750663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters530
Distinct characters21
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique53 ?
Unique (%)100.0%

Sample

1st rowDDBN900430
2nd rowDDGH900410
3rd rowDDHH900480
4th rowDDGG900420
5th rowDDDD900440
ValueCountFrequency (%)
ddbn900430 1
 
1.9%
ddgg900100 1
 
1.9%
ddgg900120 1
 
1.9%
ddgg900130 1
 
1.9%
ddge900140 1
 
1.9%
ddbn900150 1
 
1.9%
ddbb900160 1
 
1.9%
ddbb900170 1
 
1.9%
ddbb900180 1
 
1.9%
ddbb900190 1
 
1.9%
Other values (43) 43
81.1%
2023-12-11T15:43:57.172944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 196
37.0%
D 114
21.5%
9 52
 
9.8%
G 17
 
3.2%
3 16
 
3.0%
1 16
 
3.0%
2 16
 
3.0%
4 15
 
2.8%
H 13
 
2.5%
B 12
 
2.3%
Other values (11) 63
 
11.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 332
62.6%
Uppercase Letter 198
37.4%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
D 114
57.6%
G 17
 
8.6%
H 13
 
6.6%
B 12
 
6.1%
K 10
 
5.1%
A 8
 
4.0%
S 8
 
4.0%
N 6
 
3.0%
Q 5
 
2.5%
T 4
 
2.0%
Decimal Number
ValueCountFrequency (%)
0 196
59.0%
9 52
 
15.7%
3 16
 
4.8%
1 16
 
4.8%
2 16
 
4.8%
4 15
 
4.5%
5 6
 
1.8%
8 5
 
1.5%
7 5
 
1.5%
6 5
 
1.5%

Most occurring scripts

ValueCountFrequency (%)
Common 332
62.6%
Latin 198
37.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
D 114
57.6%
G 17
 
8.6%
H 13
 
6.6%
B 12
 
6.1%
K 10
 
5.1%
A 8
 
4.0%
S 8
 
4.0%
N 6
 
3.0%
Q 5
 
2.5%
T 4
 
2.0%
Common
ValueCountFrequency (%)
0 196
59.0%
9 52
 
15.7%
3 16
 
4.8%
1 16
 
4.8%
2 16
 
4.8%
4 15
 
4.5%
5 6
 
1.8%
8 5
 
1.5%
7 5
 
1.5%
6 5
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 530
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 196
37.0%
D 114
21.5%
9 52
 
9.8%
G 17
 
3.2%
3 16
 
3.0%
1 16
 
3.0%
2 16
 
3.0%
4 15
 
2.8%
H 13
 
2.5%
B 12
 
2.3%
Other values (11) 63
 
11.9%

SET_LOC_NAME
Text

UNIQUE 

Distinct53
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size556.0 B
2023-12-11T15:43:57.438843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length13
Mean length9.1132075
Min length4

Characters and Unicode

Total characters483
Distinct characters119
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique53 ?
Unique (%)100.0%

Sample

1st row한강중교앞 교차로
2nd row한남2 고가차도 북단 부근
3rd row종암사거리
4th row교보타워사거리
5th row이수교차로
ValueCountFrequency (%)
교차로 9
 
9.3%
북측(진출부 5
 
5.2%
동단 4
 
4.1%
앞 4
 
4.1%
서단 3
 
3.1%
통합 3
 
3.1%
vms 2
 
2.1%
고척교 2
 
2.1%
신정교 2
 
2.1%
목동교 2
 
2.1%
Other values (61) 61
62.9%
2023-12-11T15:43:57.874084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
46
 
9.5%
교 38
 
7.9%
차 24
 
5.0%
로 21
 
4.3%
사 14
 
2.9%
단 14
 
2.9%
리 13
 
2.7%
거 12
 
2.5%
역 11
 
2.3%
) 11
 
2.3%
Other values (109) 279
57.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 387
80.1%
Space Separator 46
 
9.5%
Uppercase Letter 23
 
4.8%
Close Punctuation 11
 
2.3%
Open Punctuation 11
 
2.3%
Decimal Number 5
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 38
 
9.8%
차 24
 
6.2%
로 21
 
5.4%
사 14
 
3.6%
단 14
 
3.6%
리 13
 
3.4%
거 12
 
3.1%
역 11
 
2.8%
서 11
 
2.8%
북 9
 
2.3%
Other values (94) 220
56.8%
Uppercase Letter
ValueCountFrequency (%)
C 8
34.8%
I 5
21.7%
V 3
 
13.0%
T 2
 
8.7%
M 2
 
8.7%
S 2
 
8.7%
J 1
 
4.3%
Decimal Number
ValueCountFrequency (%)
7 1
20.0%
3 1
20.0%
6 1
20.0%
2 1
20.0%
1 1
20.0%
Space Separator
ValueCountFrequency (%)
46
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 387
80.1%
Common 73
 
15.1%
Latin 23
 
4.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 38
 
9.8%
차 24
 
6.2%
로 21
 
5.4%
사 14
 
3.6%
단 14
 
3.6%
리 13
 
3.4%
거 12
 
3.1%
역 11
 
2.8%
서 11
 
2.8%
북 9
 
2.3%
Other values (94) 220
56.8%
Common
ValueCountFrequency (%)
46
63.0%
) 11
 
15.1%
( 11
 
15.1%
7 1
 
1.4%
3 1
 
1.4%
6 1
 
1.4%
2 1
 
1.4%
1 1
 
1.4%
Latin
ValueCountFrequency (%)
C 8
34.8%
I 5
21.7%
V 3
 
13.0%
T 2
 
8.7%
M 2
 
8.7%
S 2
 
8.7%
J 1
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 387
80.1%
ASCII 96
 
19.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
46
47.9%
) 11
 
11.5%
( 11
 
11.5%
C 8
 
8.3%
I 5
 
5.2%
V 3
 
3.1%
T 2
 
2.1%
M 2
 
2.1%
S 2
 
2.1%
J 1
 
1.0%
Other values (5) 5
 
5.2%
Hangul
ValueCountFrequency (%)
교 38
 
9.8%
차 24
 
6.2%
로 21
 
5.4%
사 14
 
3.6%
단 14
 
3.6%
리 13
 
3.4%
거 12
 
3.1%
역 11
 
2.8%
서 11
 
2.8%
북 9
 
2.3%
Other values (94) 220
56.8%

XPOINT
Real number (ℝ)

UNIQUE 

Distinct53
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean197124.91
Minimum185549.18
Maximum209481.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size609.0 B
2023-12-11T15:43:58.059872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum185549.18
5-th percentile188215.37
Q1190418.88
median198822.29
Q3201740.81
95-th percentile206200.71
Maximum209481.9
Range23932.72
Interquartile range (IQR)11321.932

Descriptive statistics

Standard deviation6397.4901
Coefficient of variation (CV)0.032453992
Kurtosis-1.242164
Mean197124.91
Median Absolute Deviation (MAD)4864.0114
Skewness-0.16492021
Sum10447620
Variance40927880
MonotonicityNot monotonic
2023-12-11T15:43:58.258228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
199302.10486 1
 
1.9%
199152.87677 1
 
1.9%
203017.60056 1
 
1.9%
203458.89998 1
 
1.9%
206310.15976 1
 
1.9%
198822.28519 1
 
1.9%
199888.1679 1
 
1.9%
200276.38033 1
 
1.9%
200674.64518 1
 
1.9%
200982.88538 1
 
1.9%
Other values (43) 43
81.1%
ValueCountFrequency (%)
185549.17553 1
1.9%
186397.30261 1
1.9%
187768.07672 1
1.9%
188513.56219 1
1.9%
188724.73989 1
1.9%
188969.42066 1
1.9%
189142.74032 1
1.9%
189577.83208 1
1.9%
189617.69932 1
1.9%
189794.0621 1
1.9%
ValueCountFrequency (%)
209481.89573 1
1.9%
207674.54541 1
1.9%
206310.15976 1
1.9%
206127.74736 1
1.9%
205006.95248 1
1.9%
204328.37072 1
1.9%
203686.2966 1
1.9%
203458.89998 1
1.9%
203186.83467 1
1.9%
203017.60056 1
1.9%

YPOINT
Real number (ℝ)

UNIQUE 

Distinct53
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean446336.75
Minimum437355.98
Maximum459811.81
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size609.0 B
2023-12-11T15:43:58.437971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum437355.98
5-th percentile439931.49
Q1442747.56
median446486.09
Q3448025.53
95-th percentile457018.91
Maximum459811.81
Range22455.833
Interquartile range (IQR)5277.9767

Descriptive statistics

Standard deviation4989.11
Coefficient of variation (CV)0.011177906
Kurtosis0.85092932
Mean446336.75
Median Absolute Deviation (MAD)2282.0657
Skewness0.91684415
Sum23655848
Variance24891219
MonotonicityNot monotonic
2023-12-11T15:43:58.614319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
447358.61823 1
 
1.9%
446771.5169 1
 
1.9%
442747.5552 1
 
1.9%
441097.371 1
 
1.9%
439784.81985 1
 
1.9%
448765.15995 1
 
1.9%
445564.72929 1
 
1.9%
444751.17778 1
 
1.9%
443572.25295 1
 
1.9%
442718.32176 1
 
1.9%
Other values (43) 43
81.1%
ValueCountFrequency (%)
437355.9772 1
1.9%
438910.0612 1
1.9%
439784.81985 1
1.9%
440029.266 1
1.9%
440752.8605 1
1.9%
440776.44839 1
1.9%
440927.3073 1
1.9%
441097.371 1
1.9%
441712.09826 1
1.9%
441922.72481 1
1.9%
ValueCountFrequency (%)
459811.81004 1
1.9%
457972.46977 1
1.9%
457336.29221 1
1.9%
456807.31366 1
1.9%
456363.72426 1
1.9%
455993.42748 1
1.9%
449504.83452 1
1.9%
449402.80727 1
1.9%
449380.78437 1
1.9%
448765.15995 1
1.9%

Interactions

2023-12-11T15:43:56.194325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:43:55.973433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:43:56.294018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:43:56.088342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T15:43:58.724201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
DSRC_IDSET_LOC_NAMEXPOINTYPOINT
DSRC_ID1.0001.0001.0001.000
SET_LOC_NAME1.0001.0001.0001.000
XPOINT1.0001.0001.0000.680
YPOINT1.0001.0000.6801.000
2023-12-11T15:43:58.824481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
XPOINTYPOINT
XPOINT1.0000.081
YPOINT0.0811.000

Missing values

2023-12-11T15:43:56.409104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T15:43:56.515755image/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

DSRC_IDSET_LOC_NAMEXPOINTYPOINT
0DDBN900430한강중교앞 교차로199302.10486447358.61823
1DDGH900410한남2 고가차도 북단 부근200499.28069448555.27812
2DDHH900480종암사거리202830.42141455993.42748
3DDGG900420교보타워사거리202154.21417444965.96762
4DDDD900440이수교차로198428.594444453.906
5DDDD900450이수역교차로198400.2954442857.75732
6DDNN900460경남아파트앞 교차로200145.72646441712.09826
7DDNN900470양재전화국 교차로203686.2966442890.87813
8DDG9000310신월IC185549.17553447397.31364
9DDG9000320화곡지하차도186397.30261447553.08532
DSRC_IDSET_LOC_NAMEXPOINTYPOINT
43DDHH900260상월곡교차로204328.37072456363.72426
44DDHH900270돌곶이역사거리205006.95248456807.31366
45DDHH900280월릉교교차로206127.74736457336.29221
46DDHH900290화랑대역사거리207674.54541457972.46977
47DDHH900300삼육대교차로209481.89573459811.81004
48DDQ0000010시흥대교 교차로190481.3267438910.0612
49DDQ0000020소하JCT(교량 7번) (CCTV 통합)191186.3878437355.9772
50DDQ0000030관악IC (VMS 통합)195296.4782440752.8605
51DDQ0000040사당IC (VMS 통합)198773.0448440927.3073
52DDQ0000050서초터널 종점201504.3392440029.266