Overview

Dataset statistics

Number of variables3
Number of observations114
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.9 KiB
Average record size in memory26.2 B

Variable types

Numeric1
Text1
Categorical1

Dataset

Description부산교통공사_부산도시철도승강장안전문현황_20220630
Author부산교통공사
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15061228

Alerts

역번호 is highly overall correlated with 설치(준공)일High correlation
설치(준공)일 is highly overall correlated with 역번호High correlation
역번호 has unique valuesUnique

Reproduction

Analysis started2023-12-10 17:00:57.676199
Analysis finished2023-12-10 17:00:58.264013
Duration0.59 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

역번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct114
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean220.03509
Minimum95
Maximum414
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T02:00:58.376623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum95
5-th percentile100.65
Q1123.25
median217.5
Q3302.75
95-th percentile408.35
Maximum414
Range319
Interquartile range (IQR)179.5

Descriptive statistics

Standard deviation97.980216
Coefficient of variation (CV)0.4452936
Kurtosis-0.67703366
Mean220.03509
Median Absolute Deviation (MAD)90
Skewness0.5341204
Sum25084
Variance9600.1227
MonotonicityStrictly increasing
2023-12-11T02:00:58.620368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
95 1
 
0.9%
304 1
 
0.9%
302 1
 
0.9%
301 1
 
0.9%
243 1
 
0.9%
242 1
 
0.9%
241 1
 
0.9%
240 1
 
0.9%
239 1
 
0.9%
238 1
 
0.9%
Other values (104) 104
91.2%
ValueCountFrequency (%)
95 1
0.9%
96 1
0.9%
97 1
0.9%
98 1
0.9%
99 1
0.9%
100 1
0.9%
101 1
0.9%
102 1
0.9%
103 1
0.9%
104 1
0.9%
ValueCountFrequency (%)
414 1
0.9%
413 1
0.9%
412 1
0.9%
411 1
0.9%
410 1
0.9%
409 1
0.9%
408 1
0.9%
407 1
0.9%
406 1
0.9%
405 1
0.9%

역 명
Text

Distinct112
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-11T02:00:59.106515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length2
Mean length2.7982456
Min length2

Characters and Unicode

Total characters319
Distinct characters132
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique110 ?
Unique (%)96.5%

Sample

1st row다대포해수욕장
2nd row다대포항
3rd row낫개
4th row신장림
5th row장림
ValueCountFrequency (%)
동래 2
 
1.6%
덕 2
 
1.6%
산 2
 
1.6%
미 2
 
1.6%
서면 2
 
1.6%
윗반송 1
 
0.8%
영산대 1
 
0.8%
수정 1
 
0.8%
미남 1
 
0.8%
망 1
 
0.8%
Other values (111) 111
88.1%
2023-12-11T02:00:59.799394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
35
 
11.0%
산 17
 
5.3%
대 16
 
5.0%
동 10
 
3.1%
장 9
 
2.8%
포 8
 
2.5%
남 8
 
2.5%
부 7
 
2.2%
사 6
 
1.9%
서 6
 
1.9%
Other values (122) 197
61.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 284
89.0%
Space Separator 35
 
11.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 17
 
6.0%
대 16
 
5.6%
동 10
 
3.5%
장 9
 
3.2%
포 8
 
2.8%
남 8
 
2.8%
부 7
 
2.5%
사 6
 
2.1%
서 6
 
2.1%
천 5
 
1.8%
Other values (121) 192
67.6%
Space Separator
ValueCountFrequency (%)
35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 284
89.0%
Common 35
 
11.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 17
 
6.0%
대 16
 
5.6%
동 10
 
3.5%
장 9
 
3.2%
포 8
 
2.8%
남 8
 
2.8%
부 7
 
2.5%
사 6
 
2.1%
서 6
 
2.1%
천 5
 
1.8%
Other values (121) 192
67.6%
Common
ValueCountFrequency (%)
35
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 284
89.0%
ASCII 35
 
11.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
35
100.0%
Hangul
ValueCountFrequency (%)
산 17
 
6.0%
대 16
 
5.6%
동 10
 
3.5%
장 9
 
3.2%
포 8
 
2.8%
남 8
 
2.8%
부 7
 
2.5%
사 6
 
2.1%
서 6
 
2.1%
천 5
 
1.8%
Other values (121) 192
67.6%

설치(준공)일
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)21.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2005-10-15
17 
2011-03-30
14 
2016-08-18
11 
2016-04-07
10 
2014-04-17
8 
Other values (20)
54 

Length

Max length29
Median length10
Mean length10.833333
Min length10

Unique

Unique12 ?
Unique (%)10.5%

Sample

1st row2017-03-28
2nd row2017-03-28
3rd row2017-03-28
4th row2017-03-28
5th row2017-03-28

Common Values

ValueCountFrequency (%)
2005-10-15 17
14.9%
2011-03-30 14
12.3%
2016-08-18 11
9.6%
2016-04-07 10
8.8%
2014-04-17 8
 
7.0%
2014-03-20 7
 
6.1%
2014-05-22 7
 
6.1%
2017-03-28 6
 
5.3%
2015-02-24 6
 
5.3%
2015-02-11 5
 
4.4%
Other values (15) 23
20.2%

Length

2023-12-11T02:01:00.035666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2005-10-15 17
13.7%
2011-03-30 14
11.3%
2016-08-18 11
 
8.9%
2016-04-07 10
 
8.1%
2014-04-17 8
 
6.5%
2014-03-20 7
 
5.6%
2014-05-22 7
 
5.6%
2017-03-28 6
 
4.8%
2015-02-24 6
 
4.8%
개량 5
 
4.0%
Other values (17) 33
26.6%

Interactions

2023-12-11T02:00:57.866011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T02:01:00.183504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
역번호설치(준공)일
역번호1.0000.939
설치(준공)일0.9391.000
2023-12-11T02:01:00.319761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
역번호설치(준공)일
역번호1.0000.698
설치(준공)일0.6981.000

Missing values

2023-12-11T02:00:58.076527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T02:00:58.212076image/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

역번호역 명설치(준공)일
095다대포해수욕장2017-03-28
196다대포항2017-03-28
297낫개2017-03-28
398신장림2017-03-28
499장림2017-03-28
5100동매2017-03-28
6101신평2016-04-07
7102하단2014-05-22
8103당리2016-04-07
9104사하2016-04-07
역번호역 명설치(준공)일
104405충렬사2011-03-30
105406명장2011-03-30
106407서동2011-03-30
107408금사2011-03-30
108409반여농산물시장2011-03-30
109410석대2011-03-30
110411영산대2011-03-30
111412윗반송2011-03-30
112413고촌2011-03-30
113414안평2011-03-30