Overview

Dataset statistics

Number of variables11
Number of observations70
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.3 KiB
Average record size in memory92.9 B

Variable types

Categorical6
Text2
Numeric3

Dataset

Description인천지하철 1,2호선 터널시설물 내진실태 2023년 5월 31일 기준 현황입니다. (구분도로별,호선명,터널명,관리기관,위치,총연장,총폭,터널형식,준공연도,평가결과,내진설계적용여부)
URLhttps://www.data.go.kr/data/15083792/fileData.do

Alerts

구분도로별 has constant value ""Constant
관리기관 has constant value ""Constant
호선명 is highly overall correlated with 준공연도 and 3 other fieldsHigh correlation
평가결과 is highly overall correlated with 준공연도 and 3 other fieldsHigh correlation
총폭 is highly overall correlated with 내진설계 적용여부(내진설계기준 제정 전_후)High correlation
준공연도 is highly overall correlated with 호선명 and 2 other fieldsHigh correlation
터널형식 is highly overall correlated with 호선명 and 1 other fieldsHigh correlation
내진설계 적용여부(내진설계기준 제정 전_후) is highly overall correlated with 총폭 and 3 other fieldsHigh correlation
터널명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 23:26:31.320522
Analysis finished2023-12-12 23:26:32.963984
Duration1.64 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분도로별
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size692.0 B
도시철도
70 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
도시철도 70
100.0%

Length

2023-12-13T08:26:33.040018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:26:33.163105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
도시철도 70
100.0%

호선명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size692.0 B
1호선
32 
2호선
25 
7호선
13 

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 32
45.7%
2호선 25
35.7%
7호선 13
18.6%

Length

2023-12-13T08:26:33.298113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:26:33.410772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1호선 32
45.7%
2호선 25
35.7%
7호선 13
18.6%

터널명
Text

UNIQUE 

Distinct70
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size692.0 B
2023-12-13T08:26:33.631640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length13
Mean length11.942857
Min length5

Characters and Unicode

Total characters836
Distinct characters127
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique70 ?
Unique (%)100.0%

Sample

1st rowBOX시점-박촌
2nd row박촌-임학
3rd row임학-계산
4th row계산-경인교대입구
5th row경인교대입구-작전
ValueCountFrequency (%)
1127 2
 
1.7%
box시점-박촌 1
 
0.8%
7112 1
 
0.8%
7106 1
 
0.8%
박촌-임학 1
 
0.8%
석천사거리-모래내시장 1
 
0.8%
2127 1
 
0.8%
만수-남동구청 1
 
0.8%
2129 1
 
0.8%
남동구청-인천대공원 1
 
0.8%
Other values (108) 108
90.8%
2023-12-13T08:26:33.991861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 73
 
8.7%
- 70
 
8.4%
49
 
5.9%
2 46
 
5.5%
시 22
 
2.6%
천 21
 
2.5%
7 19
 
2.3%
인 18
 
2.2%
0 18
 
2.2%
부 18
 
2.2%
Other values (117) 482
57.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 516
61.7%
Decimal Number 192
 
23.0%
Dash Punctuation 70
 
8.4%
Space Separator 49
 
5.9%
Open Punctuation 3
 
0.4%
Close Punctuation 3
 
0.4%
Uppercase Letter 3
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 22
 
4.3%
천 21
 
4.1%
인 18
 
3.5%
부 18
 
3.5%
동 17
 
3.3%
구 16
 
3.1%
청 16
 
3.1%
장 15
 
2.9%
석 11
 
2.1%
평 11
 
2.1%
Other values (100) 351
68.0%
Decimal Number
ValueCountFrequency (%)
1 73
38.0%
2 46
24.0%
7 19
 
9.9%
0 18
 
9.4%
3 11
 
5.7%
4 5
 
2.6%
5 5
 
2.6%
8 5
 
2.6%
6 5
 
2.6%
9 5
 
2.6%
Uppercase Letter
ValueCountFrequency (%)
O 1
33.3%
X 1
33.3%
B 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 70
100.0%
Space Separator
ValueCountFrequency (%)
49
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 516
61.7%
Common 317
37.9%
Latin 3
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 22
 
4.3%
천 21
 
4.1%
인 18
 
3.5%
부 18
 
3.5%
동 17
 
3.3%
구 16
 
3.1%
청 16
 
3.1%
장 15
 
2.9%
석 11
 
2.1%
평 11
 
2.1%
Other values (100) 351
68.0%
Common
ValueCountFrequency (%)
1 73
23.0%
- 70
22.1%
49
15.5%
2 46
14.5%
7 19
 
6.0%
0 18
 
5.7%
3 11
 
3.5%
4 5
 
1.6%
5 5
 
1.6%
8 5
 
1.6%
Other values (4) 16
 
5.0%
Latin
ValueCountFrequency (%)
O 1
33.3%
X 1
33.3%
B 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 516
61.7%
ASCII 320
38.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 73
22.8%
- 70
21.9%
49
15.3%
2 46
14.4%
7 19
 
5.9%
0 18
 
5.6%
3 11
 
3.4%
4 5
 
1.6%
5 5
 
1.6%
8 5
 
1.6%
Other values (7) 19
 
5.9%
Hangul
ValueCountFrequency (%)
시 22
 
4.3%
천 21
 
4.1%
인 18
 
3.5%
부 18
 
3.5%
동 17
 
3.3%
구 16
 
3.1%
청 16
 
3.1%
장 15
 
2.9%
석 11
 
2.1%
평 11
 
2.1%
Other values (100) 351
68.0%

관리기관
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size692.0 B
인천교통공사
70 

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 70
100.0%

Length

2023-12-13T08:26:34.130973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:26:34.218990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인천교통공사 70
100.0%

위 치
Text

Distinct40
Distinct (%)57.1%
Missing0
Missing (%)0.0%
Memory size692.0 B
2023-12-13T08:26:34.411081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length14.442857
Min length12

Characters and Unicode

Total characters1011
Distinct characters79
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

Unique22 ?
Unique (%)31.4%

Sample

1st row인천광역시 계양구 장제로
2nd row인천광역시 계양구 장제로
3rd row인천광역시 계양구 장제로
4th row인천광역시 계양구 경명대로
5th row인천광역시 계양구 계양대로
ValueCountFrequency (%)
인천광역시 63
27.8%
서구 15
 
6.6%
연수구 12
 
5.3%
부평구 12
 
5.3%
남동구 10
 
4.4%
계양구 8
 
3.5%
미추홀구 6
 
2.6%
경원대로 6
 
2.6%
경기도 6
 
2.6%
부천시 6
 
2.6%
Other values (49) 83
36.6%
2023-12-13T08:26:34.797212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
157
15.5%
천 74
 
7.3%
인 73
 
7.2%
시 70
 
6.9%
구 67
 
6.6%
광 65
 
6.4%
역 63
 
6.2%
로 45
 
4.5%
동 41
 
4.1%
부 24
 
2.4%
Other values (69) 332
32.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 797
78.8%
Space Separator 157
 
15.5%
Decimal Number 51
 
5.0%
Dash Punctuation 6
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 74
 
9.3%
인 73
 
9.2%
시 70
 
8.8%
구 67
 
8.4%
광 65
 
8.2%
역 63
 
7.9%
로 45
 
5.6%
동 41
 
5.1%
부 24
 
3.0%
경 19
 
2.4%
Other values (57) 256
32.1%
Decimal Number
ValueCountFrequency (%)
1 16
31.4%
4 6
 
11.8%
6 6
 
11.8%
7 5
 
9.8%
0 5
 
9.8%
2 4
 
7.8%
9 3
 
5.9%
3 2
 
3.9%
8 2
 
3.9%
5 2
 
3.9%
Space Separator
ValueCountFrequency (%)
157
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 797
78.8%
Common 214
 
21.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 74
 
9.3%
인 73
 
9.2%
시 70
 
8.8%
구 67
 
8.4%
광 65
 
8.2%
역 63
 
7.9%
로 45
 
5.6%
동 41
 
5.1%
부 24
 
3.0%
경 19
 
2.4%
Other values (57) 256
32.1%
Common
ValueCountFrequency (%)
157
73.4%
1 16
 
7.5%
4 6
 
2.8%
- 6
 
2.8%
6 6
 
2.8%
7 5
 
2.3%
0 5
 
2.3%
2 4
 
1.9%
9 3
 
1.4%
3 2
 
0.9%
Other values (2) 4
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 797
78.8%
ASCII 214
 
21.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
157
73.4%
1 16
 
7.5%
4 6
 
2.8%
- 6
 
2.8%
6 6
 
2.8%
7 5
 
2.3%
0 5
 
2.3%
2 4
 
1.9%
9 3
 
1.4%
3 2
 
0.9%
Other values (2) 4
 
1.9%
Hangul
ValueCountFrequency (%)
천 74
 
9.3%
인 73
 
9.2%
시 70
 
8.8%
구 67
 
8.4%
광 65
 
8.2%
역 63
 
7.9%
로 45
 
5.6%
동 41
 
5.1%
부 24
 
3.0%
경 19
 
2.4%
Other values (57) 256
32.1%

총연장
Real number (ℝ)

Distinct67
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean955.02714
Minimum196
Maximum2563.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size762.0 B
2023-12-13T08:26:34.927085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum196
5-th percentile322.2
Q1796.75
median932.2
Q31121.25
95-th percentile1680.6
Maximum2563.9
Range2367.9
Interquartile range (IQR)324.5

Descriptive statistics

Standard deviation403.11644
Coefficient of variation (CV)0.42209946
Kurtosis3.7520963
Mean955.02714
Median Absolute Deviation (MAD)166.8
Skewness1.1841394
Sum66851.9
Variance162502.86
MonotonicityNot monotonic
2023-12-13T08:26:35.057328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1150.0 2
 
2.9%
810.0 2
 
2.9%
720.0 2
 
2.9%
255.0 1
 
1.4%
548.0 1
 
1.4%
462.0 1
 
1.4%
386.0 1
 
1.4%
196.0 1
 
1.4%
897.0 1
 
1.4%
799.0 1
 
1.4%
Other values (57) 57
81.4%
ValueCountFrequency (%)
196.0 1
1.4%
229.0 1
1.4%
255.0 1
1.4%
270.0 1
1.4%
386.0 1
1.4%
407.6 1
1.4%
430.6 1
1.4%
462.0 1
1.4%
526.5 1
1.4%
548.0 1
1.4%
ValueCountFrequency (%)
2563.9 1
1.4%
2161.0 1
1.4%
1782.5 1
1.4%
1722.0 1
1.4%
1630.0 1
1.4%
1435.0 1
1.4%
1428.8 1
1.4%
1364.0 1
1.4%
1213.0 1
1.4%
1186.0 1
1.4%

총폭
Real number (ℝ)

HIGH CORRELATION 

Distinct51
Distinct (%)72.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.902086
Minimum4.4
Maximum28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size762.0 B
2023-12-13T08:26:35.239546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.4
5-th percentile7.945
Q19.1
median9.81
Q316.875
95-th percentile24.1782
Maximum28
Range23.6
Interquartile range (IQR)7.775

Descriptive statistics

Standard deviation5.9039598
Coefficient of variation (CV)0.45759732
Kurtosis-0.24457803
Mean12.902086
Median Absolute Deviation (MAD)1.31
Skewness1.0762956
Sum903.146
Variance34.856741
MonotonicityNot monotonic
2023-12-13T08:26:35.407822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9.3 6
 
8.6%
8.4 3
 
4.3%
9.1 3
 
4.3%
8.5 3
 
4.3%
18.9 2
 
2.9%
9.8 2
 
2.9%
10.6 2
 
2.9%
9.6 2
 
2.9%
10.4 2
 
2.9%
24.0 2
 
2.9%
Other values (41) 43
61.4%
ValueCountFrequency (%)
4.4 1
 
1.4%
7.4 2
2.9%
7.9 1
 
1.4%
8.0 1
 
1.4%
8.2 1
 
1.4%
8.3 1
 
1.4%
8.4 3
4.3%
8.5 3
4.3%
8.6 1
 
1.4%
8.7 1
 
1.4%
ValueCountFrequency (%)
28.0 1
1.4%
25.7 1
1.4%
25.3 1
1.4%
24.324 1
1.4%
24.0 2
2.9%
23.8 1
1.4%
22.8 1
1.4%
22.0 1
1.4%
21.8 1
1.4%
21.7 1
1.4%

터널형식
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Memory size692.0 B
개착식
32 
NATM
29 
Shield
 
3
개착+natm
 
2
SAV-CUT
 
2

Length

Max length7
Median length6
Mean length3.8571429
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row개착식
2nd row개착식
3rd row개착식
4th rowNATM
5th row개착식

Common Values

ValueCountFrequency (%)
개착식 32
45.7%
NATM 29
41.4%
Shield 3
 
4.3%
개착+natm 2
 
2.9%
SAV-CUT 2
 
2.9%
RC-Box 2
 
2.9%

Length

2023-12-13T08:26:35.562259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:26:35.684119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개착식 32
45.7%
natm 29
41.4%
shield 3
 
4.3%
개착+natm 2
 
2.9%
sav-cut 2
 
2.9%
rc-box 2
 
2.9%

준공연도
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2008.9429
Minimum1999
Maximum2021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size762.0 B
2023-12-13T08:26:35.780113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1999
5-th percentile1999
Q11999
median2012
Q32016
95-th percentile2016
Maximum2021
Range22
Interquartile range (IQR)17

Descriptive statistics

Standard deviation7.7569711
Coefficient of variation (CV)0.0038612204
Kurtosis-1.5903425
Mean2008.9429
Median Absolute Deviation (MAD)4
Skewness-0.28461717
Sum140626
Variance60.1706
MonotonicityNot monotonic
2023-12-13T08:26:35.869930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2016 25
35.7%
1999 20
28.6%
2012 10
 
14.3%
2009 7
 
10.0%
2000 5
 
7.1%
2021 3
 
4.3%
ValueCountFrequency (%)
1999 20
28.6%
2000 5
 
7.1%
2009 7
 
10.0%
2012 10
 
14.3%
2016 25
35.7%
2021 3
 
4.3%
ValueCountFrequency (%)
2021 3
 
4.3%
2016 25
35.7%
2012 10
 
14.3%
2009 7
 
10.0%
2000 5
 
7.1%
1999 20
28.6%

평가결과
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size692.0 B
OK
32 
시기미도래
28 
실시예정
10 

Length

Max length5
Median length4
Mean length3.4857143
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
OK 32
45.7%
시기미도래 28
40.0%
실시예정 10
 
14.3%

Length

2023-12-13T08:26:35.980388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:26:36.119041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
ok 32
45.7%
시기미도래 28
40.0%
실시예정 10
 
14.3%

내진설계 적용여부(내진설계기준 제정 전_후)
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size692.0 B
적용(제정후)
45 
미적용(제정전)
25 

Length

Max length8
Median length7
Mean length7.3571429
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row미적용(제정전)
2nd row미적용(제정전)
3rd row미적용(제정전)
4th row미적용(제정전)
5th row미적용(제정전)

Common Values

ValueCountFrequency (%)
적용(제정후) 45
64.3%
미적용(제정전) 25
35.7%

Length

2023-12-13T08:26:36.244255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:26:36.330450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
적용(제정후 45
64.3%
미적용(제정전 25
35.7%

Interactions

2023-12-13T08:26:32.386813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:26:31.813256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:26:32.087009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:26:32.465250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:26:31.911321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:26:32.179717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:26:32.540676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:26:31.993464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:26:32.272448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:26:36.396006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
호선명터널명위 치총연장총폭터널형식준공연도평가결과내진설계 적용여부(내진설계기준 제정 전_후)
호선명1.0001.0001.0000.4630.5840.8551.0000.9950.539
터널명1.0001.0001.0001.0001.0001.0001.0001.0001.000
위 치1.0001.0001.0000.8130.5090.9961.0001.0000.994
총연장0.4631.0000.8131.0000.1330.5690.3180.3070.000
총폭0.5841.0000.5090.1331.0000.0000.7770.5340.874
터널형식0.8551.0000.9960.5690.0001.0000.5370.8820.559
준공연도1.0001.0001.0000.3180.7770.5371.0001.0001.000
평가결과0.9951.0001.0000.3070.5340.8821.0001.0000.539
내진설계 적용여부(내진설계기준 제정 전_후)0.5391.0000.9940.0000.8740.5591.0000.5391.000
2023-12-13T08:26:36.505330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
내진설계 적용여부(내진설계기준 제정 전_후)호선명터널형식평가결과
내진설계 적용여부(내진설계기준 제정 전_후)1.0000.8000.3920.800
호선명0.8001.0000.5380.916
터널형식0.3920.5381.0000.577
평가결과0.8000.9160.5771.000
2023-12-13T08:26:36.612403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
총연장총폭준공연도호선명터널형식평가결과내진설계 적용여부(내진설계기준 제정 전_후)
총연장1.0000.135-0.1240.2270.3520.1560.000
총폭0.1351.000-0.3020.4030.0000.3560.664
준공연도-0.124-0.3021.0000.9850.3850.9850.978
호선명0.2270.4030.9851.0000.5380.9160.800
터널형식0.3520.0000.3850.5381.0000.5770.392
평가결과0.1560.3560.9850.9160.5771.0000.800
내진설계 적용여부(내진설계기준 제정 전_후)0.0000.6640.9780.8000.3920.8001.000

Missing values

2023-12-13T08:26:32.700920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:26:32.902532image/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

구분도로별호선명터널명관리기관위 치총연장총폭터널형식준공연도평가결과내진설계 적용여부(내진설계기준 제정 전_후)
0도시철도1호선BOX시점-박촌인천교통공사인천광역시 계양구 장제로1163.921.8개착식2000OK미적용(제정전)
1도시철도1호선박촌-임학인천교통공사인천광역시 계양구 장제로1047.021.7개착식2000OK미적용(제정전)
2도시철도1호선임학-계산인천교통공사인천광역시 계양구 장제로1110.08.8개착식1999OK미적용(제정전)
3도시철도1호선계산-경인교대입구인천교통공사인천광역시 계양구 경명대로900.09.3NATM1999OK미적용(제정전)
4도시철도1호선경인교대입구-작전인천교통공사인천광역시 계양구 계양대로910.016.8개착식1999OK미적용(제정전)
5도시철도1호선작전-갈산인천교통공사인천광역시 계양구 계양대로1435.016.9개착식1999OK미적용(제정전)
6도시철도1호선갈산-부평구청인천교통공사인천광역시 부평구 부평대로988.08.0개착식1999OK미적용(제정전)
7도시철도1호선부평구청-부평시장인천교통공사인천광역시 부평구 부평대로1135.08.2개착식1999OK미적용(제정전)
8도시철도1호선부평시장-부평인천교통공사인천광역시 부평구 부평대로892.77.9NATM1999OK미적용(제정전)
9도시철도1호선부평-동수인천교통공사인천광역시 부평구 광장로857.38.6NATM1999OK미적용(제정전)
구분도로별호선명터널명관리기관위 치총연장총폭터널형식준공연도평가결과내진설계 적용여부(내진설계기준 제정 전_후)
60도시철도7호선7104 춘의-신중동인천교통공사경기도 부천시 춘의동 길주로 406945.08.4Shield2012실시예정적용(제정후)
61도시철도7호선7105 신중동-부천시청인천교통공사경기도 부천시 중동 길주로 3141150.08.4Shield2012실시예정적용(제정후)
62도시철도7호선7106 부천시청-상동인천교통공사경기도 부천시 중동 길주로 202935.08.4Shield2012실시예정적용(제정후)
63도시철도7호선7107 상동-삼산체육관인천교통공사경기도 부천시 상동 길주로 1041080.08.8개착식2012실시예정적용(제정후)
64도시철도7호선7108 삼산체육관-굴포천인천교통공사인천광역시 부평구 부개동 503867.510.6개착식2012실시예정적용(제정후)
65도시철도7호선7109 굴포천-부평구청인천교통공사인천광역시 부평구 부개동 487934.410.2개착식2012실시예정적용(제정후)
66도시철도7호선7110 부평구청-종단부인천교통공사인천광역시 부평구 부평동 917-1430.612.0개착식2012실시예정적용(제정후)
67도시철도7호선7111 부평구청 종단-산곡인천교통공사인천광역시 부평구 청천동 112-11160.523.8NATM2021시기미도래적용(제정후)
68도시철도7호선7112 산곡-석남인천교통공사인천광역시 부평구 산곡동 116-92563.924.0NATM2021시기미도래적용(제정후)
69도시철도7호선7113 석남-석남종점인천교통공사인천광역시 서구 석남동 609407.624.0NATM2021시기미도래적용(제정후)