Overview

Dataset statistics

Number of variables6
Number of observations626
Missing cells552
Missing cells (%)14.7%
Duplicate rows1
Duplicate rows (%)0.2%
Total size in memory30.1 KiB
Average record size in memory49.2 B

Variable types

Categorical3
Numeric1
Text2

Dataset

Description인천1호선에 포함된 도시광역철도역들의 철도운영기관명,선명,역명,출구번호,출구별 주요시설명, 주소 등의 데이터 입니다.
Author국가철도공단
URLhttps://www.data.go.kr/data/15073466/fileData.do

Alerts

철도운영기관명 has constant value ""Constant
선명 has constant value ""Constant
Dataset has 1 (0.2%) duplicate rowsDuplicates
주소 has 552 (88.2%) missing valuesMissing

Reproduction

Analysis started2023-12-12 20:46:49.283340
Analysis finished2023-12-12 20:46:49.983520
Duration0.7 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

철도운영기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
인천교통공사
626 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
인천교통공사 626
100.0%

Length

2023-12-13T05:46:50.060795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:46:50.246441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인천교통공사 626
100.0%

선명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
인천1호선
626 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row인천1호선
2nd row인천1호선
3rd row인천1호선
4th row인천1호선
5th row인천1호선

Common Values

ValueCountFrequency (%)
인천1호선 626
100.0%

Length

2023-12-13T05:46:50.379216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:46:50.515164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인천1호선 626
100.0%

역명
Categorical

Distinct27
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
계산
71 
작전
52 
예술회관
41 
인천시청
39 
동춘
39 
Other values (22)
384 

Length

Max length6
Median length5
Mean length3.3242812
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
계산 71
 
11.3%
작전 52
 
8.3%
예술회관 41
 
6.5%
인천시청 39
 
6.2%
동춘 39
 
6.2%
원인재 35
 
5.6%
인천터미널 34
 
5.4%
부평시장 29
 
4.6%
경인교대입구 28
 
4.5%
임학 27
 
4.3%
Other values (17) 231
36.9%

Length

2023-12-13T05:46:50.662774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
계산 71
 
11.3%
작전 52
 
8.3%
예술회관 41
 
6.5%
인천시청 39
 
6.2%
동춘 39
 
6.2%
원인재 35
 
5.6%
인천터미널 34
 
5.4%
부평시장 29
 
4.6%
경인교대입구 28
 
4.5%
임학 27
 
4.3%
Other values (17) 231
36.9%

출구번호
Real number (ℝ)

Distinct11
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.4233227
Minimum1
Maximum11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2023-12-13T05:46:50.821053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile7
Maximum11
Range10
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.0454122
Coefficient of variation (CV)0.59749326
Kurtosis0.86084605
Mean3.4233227
Median Absolute Deviation (MAD)1
Skewness0.95863632
Sum2143
Variance4.1837112
MonotonicityNot monotonic
2023-12-13T05:46:50.974625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
4 129
20.6%
2 123
19.6%
1 121
19.3%
3 101
16.1%
5 56
8.9%
6 53
8.5%
7 14
 
2.2%
8 10
 
1.6%
9 10
 
1.6%
10 8
 
1.3%
ValueCountFrequency (%)
1 121
19.3%
2 123
19.6%
3 101
16.1%
4 129
20.6%
5 56
8.9%
6 53
8.5%
7 14
 
2.2%
8 10
 
1.6%
9 10
 
1.6%
10 8
 
1.3%
ValueCountFrequency (%)
11 1
 
0.2%
10 8
 
1.3%
9 10
 
1.6%
8 10
 
1.6%
7 14
 
2.2%
6 53
8.5%
5 56
8.9%
4 129
20.6%
3 101
16.1%
2 123
19.6%

출구별 주요시설명
Text

Distinct532
Distinct (%)85.0%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2023-12-13T05:46:51.282115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length15
Mean length5.9217252
Min length2

Characters and Unicode

Total characters3707
Distinct characters341
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique468 ?
Unique (%)74.8%

Sample

1st row간석여자중학교
2nd row신명여자고등학교
3rd row인천교통정보센터
4th row인천지하철공사
5th row간석동우체국
ValueCountFrequency (%)
중앙공원 9
 
1.4%
국민은행 8
 
1.2%
남동국가산업단지 6
 
0.9%
새마을금고 5
 
0.8%
연수중학교 4
 
0.6%
한국씨티은행 4
 
0.6%
우리은행 3
 
0.5%
계양1동 3
 
0.5%
남동공단 3
 
0.5%
계양경찰서 3
 
0.5%
Other values (536) 595
92.5%
2023-12-13T05:46:51.834009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 136
 
3.7%
학 110
 
3.0%
동 94
 
2.5%
계 72
 
1.9%
인 69
 
1.9%
트 66
 
1.8%
소 66
 
1.8%
아 66
 
1.8%
파 65
 
1.8%
천 63
 
1.7%
Other values (331) 2900
78.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3479
93.8%
Uppercase Letter 83
 
2.2%
Decimal Number 70
 
1.9%
Other Punctuation 41
 
1.1%
Space Separator 17
 
0.5%
Close Punctuation 6
 
0.2%
Open Punctuation 6
 
0.2%
Dash Punctuation 3
 
0.1%
Other Symbol 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 136
 
3.9%
학 110
 
3.2%
동 94
 
2.7%
계 72
 
2.1%
인 69
 
2.0%
트 66
 
1.9%
소 66
 
1.9%
아 66
 
1.9%
파 65
 
1.9%
천 63
 
1.8%
Other values (301) 2672
76.8%
Uppercase Letter
ValueCountFrequency (%)
A 37
44.6%
T 7
 
8.4%
C 5
 
6.0%
E 5
 
6.0%
R 4
 
4.8%
M 4
 
4.8%
G 4
 
4.8%
V 4
 
4.8%
K 4
 
4.8%
Y 2
 
2.4%
Other values (5) 7
 
8.4%
Decimal Number
ValueCountFrequency (%)
1 28
40.0%
2 23
32.9%
3 12
17.1%
4 3
 
4.3%
6 2
 
2.9%
9 1
 
1.4%
5 1
 
1.4%
Other Punctuation
ValueCountFrequency (%)
, 35
85.4%
/ 4
 
9.8%
& 2
 
4.9%
Space Separator
ValueCountFrequency (%)
17
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3481
93.9%
Common 143
 
3.9%
Latin 83
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 136
 
3.9%
학 110
 
3.2%
동 94
 
2.7%
계 72
 
2.1%
인 69
 
2.0%
트 66
 
1.9%
소 66
 
1.9%
아 66
 
1.9%
파 65
 
1.9%
천 63
 
1.8%
Other values (302) 2674
76.8%
Latin
ValueCountFrequency (%)
A 37
44.6%
T 7
 
8.4%
C 5
 
6.0%
E 5
 
6.0%
R 4
 
4.8%
M 4
 
4.8%
G 4
 
4.8%
V 4
 
4.8%
K 4
 
4.8%
Y 2
 
2.4%
Other values (5) 7
 
8.4%
Common
ValueCountFrequency (%)
, 35
24.5%
1 28
19.6%
2 23
16.1%
17
11.9%
3 12
 
8.4%
) 6
 
4.2%
( 6
 
4.2%
/ 4
 
2.8%
4 3
 
2.1%
- 3
 
2.1%
Other values (4) 6
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3479
93.8%
ASCII 226
 
6.1%
None 2
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 136
 
3.9%
학 110
 
3.2%
동 94
 
2.7%
계 72
 
2.1%
인 69
 
2.0%
트 66
 
1.9%
소 66
 
1.9%
아 66
 
1.9%
파 65
 
1.9%
천 63
 
1.8%
Other values (301) 2672
76.8%
ASCII
ValueCountFrequency (%)
A 37
16.4%
, 35
15.5%
1 28
12.4%
2 23
10.2%
17
 
7.5%
3 12
 
5.3%
T 7
 
3.1%
) 6
 
2.7%
( 6
 
2.7%
C 5
 
2.2%
Other values (19) 50
22.1%
None
ValueCountFrequency (%)
㈜ 2
100.0%

주소
Text

MISSING 

Distinct66
Distinct (%)89.2%
Missing552
Missing (%)88.2%
Memory size5.0 KiB
2023-12-13T05:46:52.318802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length21
Mean length17.972973
Min length1

Characters and Unicode

Total characters1330
Distinct characters94
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)81.1%

Sample

1st row인천광역시 남동구 간석로25번길 13
2nd row인천광역시 남동구 용천로205번길 42
3rd row인천광역시 남동구 석산로197번길 19
4th row인천광역시 남동구 석촌로 21
5th row인천광역시 남동구 남동대로922번길 54
ValueCountFrequency (%)
인천광역시 73
25.3%
연수구 25
 
8.7%
계양구 20
 
6.9%
남동구 18
 
6.2%
원인재로 8
 
2.8%
19 7
 
2.4%
부평구 6
 
2.1%
231 4
 
1.4%
남구 4
 
1.4%
12 4
 
1.4%
Other values (99) 119
41.3%
2023-12-13T05:46:52.986117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
216
16.2%
인 87
 
6.5%
구 76
 
5.7%
시 75
 
5.6%
천 74
 
5.6%
광 73
 
5.5%
역 73
 
5.5%
로 68
 
5.1%
1 55
 
4.1%
2 35
 
2.6%
Other values (84) 498
37.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 888
66.8%
Decimal Number 224
 
16.8%
Space Separator 216
 
16.2%
Dash Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 87
 
9.8%
구 76
 
8.6%
시 75
 
8.4%
천 74
 
8.3%
광 73
 
8.2%
역 73
 
8.2%
로 68
 
7.7%
동 26
 
2.9%
수 25
 
2.8%
연 25
 
2.8%
Other values (72) 286
32.2%
Decimal Number
ValueCountFrequency (%)
1 55
24.6%
2 35
15.6%
3 24
10.7%
5 21
 
9.4%
4 19
 
8.5%
9 19
 
8.5%
8 14
 
6.2%
6 13
 
5.8%
7 13
 
5.8%
0 11
 
4.9%
Space Separator
ValueCountFrequency (%)
216
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 888
66.8%
Common 442
33.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 87
 
9.8%
구 76
 
8.6%
시 75
 
8.4%
천 74
 
8.3%
광 73
 
8.2%
역 73
 
8.2%
로 68
 
7.7%
동 26
 
2.9%
수 25
 
2.8%
연 25
 
2.8%
Other values (72) 286
32.2%
Common
ValueCountFrequency (%)
216
48.9%
1 55
 
12.4%
2 35
 
7.9%
3 24
 
5.4%
5 21
 
4.8%
4 19
 
4.3%
9 19
 
4.3%
8 14
 
3.2%
6 13
 
2.9%
7 13
 
2.9%
Other values (2) 13
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 888
66.8%
ASCII 442
33.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
216
48.9%
1 55
 
12.4%
2 35
 
7.9%
3 24
 
5.4%
5 21
 
4.8%
4 19
 
4.3%
9 19
 
4.3%
8 14
 
3.2%
6 13
 
2.9%
7 13
 
2.9%
Other values (2) 13
 
2.9%
Hangul
ValueCountFrequency (%)
인 87
 
9.8%
구 76
 
8.6%
시 75
 
8.4%
천 74
 
8.3%
광 73
 
8.2%
역 73
 
8.2%
로 68
 
7.7%
동 26
 
2.9%
수 25
 
2.8%
연 25
 
2.8%
Other values (72) 286
32.2%

Interactions

2023-12-13T05:46:49.681814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:46:53.145500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
역명출구번호주소
역명1.0000.6030.983
출구번호0.6031.0000.832
주소0.9830.8321.000
2023-12-13T05:46:53.277108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
출구번호역명
출구번호1.0000.254
역명0.2541.000

Missing values

2023-12-13T05:46:49.815433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:46:49.937698image/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
0인천교통공사인천1호선간석오거리1간석여자중학교인천광역시 남동구 간석로25번길 13
1인천교통공사인천1호선간석오거리1신명여자고등학교인천광역시 남동구 용천로205번길 42
2인천교통공사인천1호선간석오거리1인천교통정보센터<NA>
3인천교통공사인천1호선간석오거리1인천지하철공사<NA>
4인천교통공사인천1호선간석오거리2간석동우체국<NA>
5인천교통공사인천1호선간석오거리2목화예식장<NA>
6인천교통공사인천1호선간석오거리3간석동우체국<NA>
7인천교통공사인천1호선간석오거리3대한교원공제회관<NA>
8인천교통공사인천1호선간석오거리3로얄호텔<NA>
9인천교통공사인천1호선간석오거리3상인천중학교<NA>
철도운영기관명선명역명출구번호출구별 주요시설명주소
616인천교통공사인천1호선테크노파크3경제자유구역청<NA>
617인천교통공사인천1호선테크노파크3다례원<NA>
618인천교통공사인천1호선테크노파크3도시축전조직위원회<NA>
619인천교통공사인천1호선테크노파크3미추홀공원<NA>
620인천교통공사인천1호선테크노파크3미추홀타워((재)테크노파크)<NA>
621인천교통공사인천1호선테크노파크3웰카운티<NA>
622인천교통공사인천1호선테크노파크3인천가톨릭대학교<NA>
623인천교통공사인천1호선테크노파크3해송중교<NA>
624인천교통공사인천1호선테크노파크3해송초교<NA>
625인천교통공사인천1호선테크노파크4갯벌타워인천광역시 연수구 갯벌로 12

Duplicate rows

Most frequently occurring

철도운영기관명선명역명출구번호출구별 주요시설명주소# duplicates
0인천교통공사인천1호선계산6계산고교<NA>2