Overview

Dataset statistics

Number of variables6
Number of observations129
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.3 KiB
Average record size in memory50.0 B

Variable types

Categorical3
Numeric1
Text2

Dataset

Description대구1호선에 포함된 도시광역철도역들의 철도운영기관명,선명,역명,출구번호,출구별 주요시설명, 주소 등의 데이터 입니다.
Author국가철도공단
URLhttps://www.data.go.kr/data/15068955/fileData.do

Alerts

철도운영기관명 has constant value ""Constant
선명 has constant value ""Constant

Reproduction

Analysis started2023-12-12 14:01:39.982298
Analysis finished2023-12-12 14:01:40.499466
Duration0.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

철도운영기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
대구교통공사
129 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대구교통공사 129
100.0%

Length

2023-12-12T23:01:40.602919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:01:40.704040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대구교통공사 129
100.0%

선명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
1호선
129 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1호선
2nd row1호선
3rd row1호선
4th row1호선
5th row1호선

Common Values

ValueCountFrequency (%)
1호선 129
100.0%

Length

2023-12-12T23:01:40.810068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:01:40.902143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1호선 129
100.0%

역명
Categorical

Distinct30
Distinct (%)23.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
상인
 
8
월촌
 
8
신천(경북대입구)
 
8
안심(혁신도시·첨복단지)
 
4
월배
 
4
Other values (25)
97 

Length

Max length16
Median length13
Mean length4.2403101
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대곡(정부대구청사)
2nd row대곡(정부대구청사)
3rd row대곡(정부대구청사)
4th row대곡(정부대구청사)
5th row진천

Common Values

ValueCountFrequency (%)
상인 8
 
6.2%
월촌 8
 
6.2%
신천(경북대입구) 8
 
6.2%
안심(혁신도시·첨복단지) 4
 
3.1%
월배 4
 
3.1%
송현 4
 
3.1%
안지랑 4
 
3.1%
현충로 4
 
3.1%
교대 4
 
3.1%
명덕(2.28민주운동기념회관) 4
 
3.1%
Other values (20) 77
59.7%

Length

2023-12-12T23:01:41.044851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
상인 8
 
6.2%
월촌 8
 
6.2%
신천(경북대입구 8
 
6.2%
대곡(정부대구청사 4
 
3.1%
칠성시장 4
 
3.1%
각산 4
 
3.1%
반야월 4
 
3.1%
신기 4
 
3.1%
율하 4
 
3.1%
용계 4
 
3.1%
Other values (20) 77
59.7%

출구번호
Real number (ℝ)

Distinct9
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0077519
Minimum1
Maximum23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-12T23:01:41.162671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile6.6
Maximum23
Range22
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.4060345
Coefficient of variation (CV)0.79994445
Kurtosis36.805573
Mean3.0077519
Median Absolute Deviation (MAD)1
Skewness4.7970095
Sum388
Variance5.7890019
MonotonicityNot monotonic
2023-12-12T23:01:41.288086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 30
23.3%
3 30
23.3%
2 29
22.5%
4 26
20.2%
5 4
 
3.1%
6 3
 
2.3%
7 3
 
2.3%
8 3
 
2.3%
23 1
 
0.8%
ValueCountFrequency (%)
1 30
23.3%
2 29
22.5%
3 30
23.3%
4 26
20.2%
5 4
 
3.1%
6 3
 
2.3%
7 3
 
2.3%
8 3
 
2.3%
23 1
 
0.8%
ValueCountFrequency (%)
23 1
 
0.8%
8 3
 
2.3%
7 3
 
2.3%
6 3
 
2.3%
5 4
 
3.1%
4 26
20.2%
3 30
23.3%
2 29
22.5%
1 30
23.3%

출구별 주요시설명
Text

Distinct124
Distinct (%)96.1%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-12T23:01:41.569970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length6.9689922
Min length3

Characters and Unicode

Total characters899
Distinct characters176
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique119 ?
Unique (%)92.2%

Sample

1st row화원읍사무소
2nd row대구교도소
3rd row정부대구지방합동청사
4th row월배차량기지사업소
5th row월배차량기지사업소
ValueCountFrequency (%)
주민센터 3
 
2.1%
월배차량기지사업소 2
 
1.4%
안심2동주민센터 2
 
1.4%
동구청 2
 
1.4%
칠성동주민센터 2
 
1.4%
진천동 2
 
1.4%
상인점 2
 
1.4%
홈플러스 2
 
1.4%
아양교 1
 
0.7%
동부소방서 1
 
0.7%
Other values (121) 121
86.4%
2023-12-12T23:01:42.001921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 57
 
6.3%
대 31
 
3.4%
센 31
 
3.4%
터 31
 
3.4%
구 29
 
3.2%
교 26
 
2.9%
민 25
 
2.8%
주 23
 
2.6%
학 18
 
2.0%
안 17
 
1.9%
Other values (166) 611
68.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 851
94.7%
Decimal Number 31
 
3.4%
Space Separator 11
 
1.2%
Other Punctuation 2
 
0.2%
Uppercase Letter 2
 
0.2%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 57
 
6.7%
대 31
 
3.6%
센 31
 
3.6%
터 31
 
3.6%
구 29
 
3.4%
교 26
 
3.1%
민 25
 
2.9%
주 23
 
2.7%
학 18
 
2.1%
안 17
 
2.0%
Other values (152) 563
66.2%
Decimal Number
ValueCountFrequency (%)
1 15
48.4%
2 6
 
19.4%
9 3
 
9.7%
4 2
 
6.5%
3 2
 
6.5%
0 1
 
3.2%
6 1
 
3.2%
5 1
 
3.2%
Uppercase Letter
ValueCountFrequency (%)
T 1
50.0%
K 1
50.0%
Space Separator
ValueCountFrequency (%)
11
100.0%
Other Punctuation
ValueCountFrequency (%)
· 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 851
94.7%
Common 46
 
5.1%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 57
 
6.7%
대 31
 
3.6%
센 31
 
3.6%
터 31
 
3.6%
구 29
 
3.4%
교 26
 
3.1%
민 25
 
2.9%
주 23
 
2.7%
학 18
 
2.1%
안 17
 
2.0%
Other values (152) 563
66.2%
Common
ValueCountFrequency (%)
1 15
32.6%
11
23.9%
2 6
 
13.0%
9 3
 
6.5%
4 2
 
4.3%
· 2
 
4.3%
3 2
 
4.3%
( 1
 
2.2%
) 1
 
2.2%
0 1
 
2.2%
Other values (2) 2
 
4.3%
Latin
ValueCountFrequency (%)
T 1
50.0%
K 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 851
94.7%
ASCII 46
 
5.1%
None 2
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 57
 
6.7%
대 31
 
3.6%
센 31
 
3.6%
터 31
 
3.6%
구 29
 
3.4%
교 26
 
3.1%
민 25
 
2.9%
주 23
 
2.7%
학 18
 
2.1%
안 17
 
2.0%
Other values (152) 563
66.2%
ASCII
ValueCountFrequency (%)
1 15
32.6%
11
23.9%
2 6
 
13.0%
9 3
 
6.5%
4 2
 
4.3%
3 2
 
4.3%
( 1
 
2.2%
) 1
 
2.2%
0 1
 
2.2%
6 1
 
2.2%
Other values (3) 3
 
6.5%
None
ValueCountFrequency (%)
· 2
100.0%

주소
Text

Distinct117
Distinct (%)90.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-12T23:01:42.351135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length18
Mean length13.387597
Min length9

Characters and Unicode

Total characters1727
Distinct characters108
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique107 ?
Unique (%)82.9%

Sample

1st row대구 달성군 화원읍 비슬로 2594
2nd row대구 달성군 화원읍 비슬로 2625
3rd row대구 달서구 화암로 301 정부대구지방합동청사
4th row대구 달서구 월배로 5길 39(유천동)
5th row대구 달서구 월배로 5길 39(유천동)
ValueCountFrequency (%)
대구 129
27.4%
동구 56
 
11.9%
달서구 32
 
6.8%
남구 19
 
4.0%
중구 14
 
3.0%
월배로 13
 
2.8%
북구 6
 
1.3%
송현로 4
 
0.9%
아양로 3
 
0.6%
송현동 3
 
0.6%
Other values (164) 191
40.6%
2023-12-12T23:01:42.874663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
341
19.7%
구 261
15.1%
대 149
 
8.6%
동 107
 
6.2%
로 96
 
5.6%
1 64
 
3.7%
2 48
 
2.8%
길 43
 
2.5%
3 41
 
2.4%
달 37
 
2.1%
Other values (98) 540
31.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1031
59.7%
Space Separator 341
 
19.7%
Decimal Number 341
 
19.7%
Dash Punctuation 9
 
0.5%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 261
25.3%
대 149
14.5%
동 107
10.4%
로 96
 
9.3%
길 43
 
4.2%
달 37
 
3.6%
서 35
 
3.4%
남 22
 
2.1%
중 19
 
1.8%
월 19
 
1.8%
Other values (83) 243
23.6%
Decimal Number
ValueCountFrequency (%)
1 64
18.8%
2 48
14.1%
3 41
12.0%
5 30
8.8%
0 30
8.8%
9 28
8.2%
7 26
7.6%
4 26
7.6%
8 26
7.6%
6 22
 
6.5%
Space Separator
ValueCountFrequency (%)
341
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1031
59.7%
Common 696
40.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 261
25.3%
대 149
14.5%
동 107
10.4%
로 96
 
9.3%
길 43
 
4.2%
달 37
 
3.6%
서 35
 
3.4%
남 22
 
2.1%
중 19
 
1.8%
월 19
 
1.8%
Other values (83) 243
23.6%
Common
ValueCountFrequency (%)
341
49.0%
1 64
 
9.2%
2 48
 
6.9%
3 41
 
5.9%
5 30
 
4.3%
0 30
 
4.3%
9 28
 
4.0%
7 26
 
3.7%
4 26
 
3.7%
8 26
 
3.7%
Other values (5) 36
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1031
59.7%
ASCII 696
40.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
341
49.0%
1 64
 
9.2%
2 48
 
6.9%
3 41
 
5.9%
5 30
 
4.3%
0 30
 
4.3%
9 28
 
4.0%
7 26
 
3.7%
4 26
 
3.7%
8 26
 
3.7%
Other values (5) 36
 
5.2%
Hangul
ValueCountFrequency (%)
구 261
25.3%
대 149
14.5%
동 107
10.4%
로 96
 
9.3%
길 43
 
4.2%
달 37
 
3.6%
서 35
 
3.4%
남 22
 
2.1%
중 19
 
1.8%
월 19
 
1.8%
Other values (83) 243
23.6%

Interactions

2023-12-12T23:01:40.208429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:01:42.981071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
역명출구번호
역명1.0000.000
출구번호0.0001.000
2023-12-12T23:01:43.068774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
출구번호역명
출구번호1.0000.000
역명0.0001.000

Missing values

2023-12-12T23:01:40.309381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:01:40.441546image/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

철도운영기관명선명역명출구번호출구별 주요시설명주소
0대구교통공사1호선대곡(정부대구청사)1화원읍사무소대구 달성군 화원읍 비슬로 2594
1대구교통공사1호선대곡(정부대구청사)2대구교도소대구 달성군 화원읍 비슬로 2625
2대구교통공사1호선대곡(정부대구청사)3정부대구지방합동청사대구 달서구 화암로 301 정부대구지방합동청사
3대구교통공사1호선대곡(정부대구청사)4월배차량기지사업소대구 달서구 월배로 5길 39(유천동)
4대구교통공사1호선진천1월배차량기지사업소대구 달서구 월배로 5길 39(유천동)
5대구교통공사1호선진천2진천우체국대구 달서구 월배로 32
6대구교통공사1호선진천3보강병원대구 달서구 월배로 102
7대구교통공사1호선진천4진천동 주민센터대구 달서구 진천로9길 33
8대구교통공사1호선월배1진천동 주민센터대구 달서구 진천로9길 33
9대구교통공사1호선월배2월배시장대구 달서구 월배로24길 13
철도운영기관명선명역명출구번호출구별 주요시설명주소
119대구교통공사1호선반야월3대구가톨릭대학교 부설유치원대구 동구 안심로300
120대구교통공사1호선반야월4대구안심우체국대구 동구 경안로 780
121대구교통공사1호선각산2동호동우체국대구 동구 동호로63
122대구교통공사1호선각산1반야월 자동차 정비사업소대구 동구 동호동
123대구교통공사1호선각산4이마트반야월점대구 동구 안심로389-2
124대구교통공사1호선각산3강동초중고등학교대구 동구 동호로7길 17
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