Overview

Dataset statistics

Number of variables12
Number of observations72
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.2 KiB
Average record size in memory101.8 B

Variable types

Numeric4
Text3
Categorical5

Dataset

Description인천광역시 보도육교(시설물명, 시설물 위치, 길이, 폭, 준공년도, 상부형식, 하부형식, 관리주체 등)에 관한 현황 자료 입니다.
Author인천광역시
URLhttps://www.data.go.kr/data/15045184/fileData.do

Alerts

구분 is highly overall correlated with 관리주체 and 1 other fieldsHigh correlation
폭(미터) is highly overall correlated with 상부 형식High correlation
준공년도 is highly overall correlated with 상부 형식 and 1 other fieldsHigh correlation
상부 형식 is highly overall correlated with 폭(미터) and 3 other fieldsHigh correlation
하부 형식 is highly overall correlated with 상부 형식 and 2 other fieldsHigh correlation
설계하중 is highly overall correlated with 상부 형식 and 1 other fieldsHigh correlation
관리주체 is highly overall correlated with 구분 and 2 other fieldsHigh correlation
비고 is highly overall correlated with 구분 and 2 other fieldsHigh correlation
설계하중 is highly imbalanced (51.7%)Imbalance
구분 has unique valuesUnique
시설물명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 12:25:45.583658
Analysis finished2023-12-12 12:25:48.653806
Duration3.07 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct72
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.5
Minimum1
Maximum72
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size780.0 B
2023-12-12T21:25:48.779439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.55
Q118.75
median36.5
Q354.25
95-th percentile68.45
Maximum72
Range71
Interquartile range (IQR)35.5

Descriptive statistics

Standard deviation20.92845
Coefficient of variation (CV)0.57338218
Kurtosis-1.2
Mean36.5
Median Absolute Deviation (MAD)18
Skewness0
Sum2628
Variance438
MonotonicityStrictly increasing
2023-12-12T21:25:48.973232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.4%
38 1
 
1.4%
54 1
 
1.4%
53 1
 
1.4%
52 1
 
1.4%
51 1
 
1.4%
50 1
 
1.4%
49 1
 
1.4%
48 1
 
1.4%
47 1
 
1.4%
Other values (62) 62
86.1%
ValueCountFrequency (%)
1 1
1.4%
2 1
1.4%
3 1
1.4%
4 1
1.4%
5 1
1.4%
6 1
1.4%
7 1
1.4%
8 1
1.4%
9 1
1.4%
10 1
1.4%
ValueCountFrequency (%)
72 1
1.4%
71 1
1.4%
70 1
1.4%
69 1
1.4%
68 1
1.4%
67 1
1.4%
66 1
1.4%
65 1
1.4%
64 1
1.4%
63 1
1.4%

시설물명
Text

UNIQUE 

Distinct72
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size708.0 B
2023-12-12T21:25:49.286901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length8.5
Mean length6.0972222
Min length2

Characters and Unicode

Total characters439
Distinct characters123
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

Unique72 ?
Unique (%)100.0%

Sample

1st row도원
2nd row축항로
3rd row연안
4th row인천항
5th row남육교
ValueCountFrequency (%)
보도육교 10
 
11.9%
도원 1
 
1.2%
장숙교 1
 
1.2%
장경교 1
 
1.2%
충민교 1
 
1.2%
갈현보도육교 1
 
1.2%
삼산2보도육교 1
 
1.2%
삼산1보도육교 1
 
1.2%
여울보도육교 1
 
1.2%
진산초교보도육교 1
 
1.2%
Other values (65) 65
77.4%
2023-12-12T21:25:49.789418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 65
 
14.8%
육 50
 
11.4%
도 47
 
10.7%
보 42
 
9.6%
12
 
2.7%
동 10
 
2.3%
초 9
 
2.1%
현 7
 
1.6%
지 6
 
1.4%
산 6
 
1.4%
Other values (113) 185
42.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 417
95.0%
Space Separator 12
 
2.7%
Decimal Number 6
 
1.4%
Uppercase Letter 2
 
0.5%
Open Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 65
 
15.6%
육 50
 
12.0%
도 47
 
11.3%
보 42
 
10.1%
동 10
 
2.4%
초 9
 
2.2%
현 7
 
1.7%
지 6
 
1.4%
산 6
 
1.4%
장 6
 
1.4%
Other values (106) 169
40.5%
Decimal Number
ValueCountFrequency (%)
2 3
50.0%
1 3
50.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
50.0%
I 1
50.0%
Space Separator
ValueCountFrequency (%)
12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 417
95.0%
Common 20
 
4.6%
Latin 2
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 65
 
15.6%
육 50
 
12.0%
도 47
 
11.3%
보 42
 
10.1%
동 10
 
2.4%
초 9
 
2.2%
현 7
 
1.7%
지 6
 
1.4%
산 6
 
1.4%
장 6
 
1.4%
Other values (106) 169
40.5%
Common
ValueCountFrequency (%)
12
60.0%
2 3
 
15.0%
1 3
 
15.0%
( 1
 
5.0%
) 1
 
5.0%
Latin
ValueCountFrequency (%)
C 1
50.0%
I 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 417
95.0%
ASCII 22
 
5.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 65
 
15.6%
육 50
 
12.0%
도 47
 
11.3%
보 42
 
10.1%
동 10
 
2.4%
초 9
 
2.2%
현 7
 
1.7%
지 6
 
1.4%
산 6
 
1.4%
장 6
 
1.4%
Other values (106) 169
40.5%
ASCII
ValueCountFrequency (%)
12
54.5%
2 3
 
13.6%
1 3
 
13.6%
C 1
 
4.5%
I 1
 
4.5%
( 1
 
4.5%
) 1
 
4.5%

위치(군구)
Text

Distinct60
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Memory size708.0 B
2023-12-12T21:25:50.153029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17
Mean length10.291667
Min length5

Characters and Unicode

Total characters741
Distinct characters88
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

Unique55 ?
Unique (%)76.4%

Sample

1st row미추홀구 용현동
2nd row미추홀구 용현동
3rd row미추홀구 용현동
4th row미추홀구 도화동
5th row미추홀구 도화동
ValueCountFrequency (%)
미추홀구 14
 
7.8%
서구 14
 
7.8%
남동구 14
 
7.8%
부평구 11
 
6.1%
일원 11
 
6.1%
중구 11
 
6.1%
삼산동 6
 
3.4%
연수구 5
 
2.8%
논현동 4
 
2.2%
용현동 4
 
2.2%
Other values (74) 85
47.5%
2023-12-12T21:25:50.719150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
107
 
14.4%
동 87
 
11.7%
구 73
 
9.9%
1 23
 
3.1%
2 18
 
2.4%
부 17
 
2.3%
남 16
 
2.2%
미 15
 
2.0%
추 15
 
2.0%
홀 15
 
2.0%
Other values (78) 355
47.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 495
66.8%
Decimal Number 115
 
15.5%
Space Separator 107
 
14.4%
Dash Punctuation 13
 
1.8%
Open Punctuation 5
 
0.7%
Close Punctuation 5
 
0.7%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 87
17.6%
구 73
 
14.7%
부 17
 
3.4%
남 16
 
3.2%
미 15
 
3.0%
추 15
 
3.0%
홀 15
 
3.0%
서 14
 
2.8%
번 14
 
2.8%
평 14
 
2.8%
Other values (63) 215
43.4%
Decimal Number
ValueCountFrequency (%)
1 23
20.0%
2 18
15.7%
5 12
10.4%
8 11
9.6%
4 10
8.7%
6 10
8.7%
3 10
8.7%
7 7
 
6.1%
0 7
 
6.1%
9 7
 
6.1%
Space Separator
ValueCountFrequency (%)
107
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 495
66.8%
Common 246
33.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 87
17.6%
구 73
 
14.7%
부 17
 
3.4%
남 16
 
3.2%
미 15
 
3.0%
추 15
 
3.0%
홀 15
 
3.0%
서 14
 
2.8%
번 14
 
2.8%
평 14
 
2.8%
Other values (63) 215
43.4%
Common
ValueCountFrequency (%)
107
43.5%
1 23
 
9.3%
2 18
 
7.3%
- 13
 
5.3%
5 12
 
4.9%
8 11
 
4.5%
4 10
 
4.1%
6 10
 
4.1%
3 10
 
4.1%
7 7
 
2.8%
Other values (5) 25
 
10.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 495
66.8%
ASCII 246
33.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
107
43.5%
1 23
 
9.3%
2 18
 
7.3%
- 13
 
5.3%
5 12
 
4.9%
8 11
 
4.5%
4 10
 
4.1%
6 10
 
4.1%
3 10
 
4.1%
7 7
 
2.8%
Other values (5) 25
 
10.2%
Hangul
ValueCountFrequency (%)
동 87
17.6%
구 73
 
14.7%
부 17
 
3.4%
남 16
 
3.2%
미 15
 
3.0%
추 15
 
3.0%
홀 15
 
3.0%
서 14
 
2.8%
번 14
 
2.8%
평 14
 
2.8%
Other values (63) 215
43.4%

도로명주소 또는 지번
Text

Distinct67
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Memory size708.0 B
2023-12-12T21:25:51.111878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length17
Mean length10.722222
Min length5

Characters and Unicode

Total characters772
Distinct characters100
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

Unique64 ?
Unique (%)88.9%

Sample

1st row참외전로 212-3
2nd row축항대로 274
3rd row축항대로 240
4th row서해대로 307
5th row운서동 2785-12
ValueCountFrequency (%)
서구 21
 
13.1%
운서동 5
 
3.1%
가정동 4
 
2.5%
석남동 4
 
2.5%
청라2동 3
 
1.9%
수인로 2
 
1.2%
굴포로(삼산동 2
 
1.2%
용현동 2
 
1.2%
청라1동 2
 
1.2%
은봉로 2
 
1.2%
Other values (111) 113
70.6%
2023-12-12T21:25:51.711996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
88
 
11.4%
동 58
 
7.5%
2 42
 
5.4%
로 40
 
5.2%
1 38
 
4.9%
5 31
 
4.0%
서 28
 
3.6%
4 28
 
3.6%
8 27
 
3.5%
- 26
 
3.4%
Other values (90) 366
47.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 359
46.5%
Decimal Number 254
32.9%
Space Separator 88
 
11.4%
Dash Punctuation 26
 
3.4%
Close Punctuation 22
 
2.8%
Open Punctuation 22
 
2.8%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 58
 
16.2%
로 40
 
11.1%
서 28
 
7.8%
구 22
 
6.1%
대 12
 
3.3%
석 7
 
1.9%
남 7
 
1.9%
청 7
 
1.9%
산 7
 
1.9%
라 6
 
1.7%
Other values (75) 165
46.0%
Decimal Number
ValueCountFrequency (%)
2 42
16.5%
1 38
15.0%
5 31
12.2%
4 28
11.0%
8 27
10.6%
3 22
8.7%
7 22
8.7%
6 20
7.9%
0 13
 
5.1%
9 11
 
4.3%
Space Separator
ValueCountFrequency (%)
88
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 26
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 413
53.5%
Hangul 359
46.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 58
 
16.2%
로 40
 
11.1%
서 28
 
7.8%
구 22
 
6.1%
대 12
 
3.3%
석 7
 
1.9%
남 7
 
1.9%
청 7
 
1.9%
산 7
 
1.9%
라 6
 
1.7%
Other values (75) 165
46.0%
Common
ValueCountFrequency (%)
88
21.3%
2 42
10.2%
1 38
9.2%
5 31
 
7.5%
4 28
 
6.8%
8 27
 
6.5%
- 26
 
6.3%
3 22
 
5.3%
) 22
 
5.3%
7 22
 
5.3%
Other values (5) 67
16.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 413
53.5%
Hangul 359
46.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
88
21.3%
2 42
10.2%
1 38
9.2%
5 31
 
7.5%
4 28
 
6.8%
8 27
 
6.5%
- 26
 
6.3%
3 22
 
5.3%
) 22
 
5.3%
7 22
 
5.3%
Other values (5) 67
16.2%
Hangul
ValueCountFrequency (%)
동 58
 
16.2%
로 40
 
11.1%
서 28
 
7.8%
구 22
 
6.1%
대 12
 
3.3%
석 7
 
1.9%
남 7
 
1.9%
청 7
 
1.9%
산 7
 
1.9%
라 6
 
1.7%
Other values (75) 165
46.0%

길이(미터)
Real number (ℝ)

Distinct59
Distinct (%)81.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean60.58375
Minimum17
Maximum164.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size780.0 B
2023-12-12T21:25:51.894853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum17
5-th percentile25.7885
Q132.375
median44.2
Q380.75
95-th percentile135.25
Maximum164.6
Range147.6
Interquartile range (IQR)48.375

Descriptive statistics

Standard deviation36.941529
Coefficient of variation (CV)0.6097597
Kurtosis0.55331238
Mean60.58375
Median Absolute Deviation (MAD)14.2
Skewness1.2214452
Sum4362.03
Variance1364.6766
MonotonicityNot monotonic
2023-12-12T21:25:52.074171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30.0 4
 
5.6%
88.0 3
 
4.2%
32.0 3
 
4.2%
41.5 3
 
4.2%
40.0 3
 
4.2%
49.0 2
 
2.8%
70.0 2
 
2.8%
26.0 1
 
1.4%
62.0 1
 
1.4%
42.0 1
 
1.4%
Other values (49) 49
68.1%
ValueCountFrequency (%)
17.0 1
 
1.4%
19.0 1
 
1.4%
25.5 1
 
1.4%
25.53 1
 
1.4%
26.0 1
 
1.4%
28.4 1
 
1.4%
29.0 1
 
1.4%
29.5 1
 
1.4%
29.7 1
 
1.4%
30.0 4
5.6%
ValueCountFrequency (%)
164.6 1
1.4%
158.0 1
1.4%
150.0 1
1.4%
138.0 1
1.4%
133.0 1
1.4%
130.0 1
1.4%
126.0 1
1.4%
125.0 1
1.4%
118.0 1
1.4%
110.0 1
1.4%

폭(미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct13
Distinct (%)18.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.5027778
Minimum2.6
Maximum11.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size780.0 B
2023-12-12T21:25:52.220777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.6
5-th percentile3
Q14
median4
Q35
95-th percentile6.5
Maximum11.5
Range8.9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.4303523
Coefficient of variation (CV)0.31765998
Kurtosis7.3324568
Mean4.5027778
Median Absolute Deviation (MAD)0.75
Skewness2.1349403
Sum324.2
Variance2.0459077
MonotonicityNot monotonic
2023-12-12T21:25:52.356635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
4.0 35
48.6%
5.0 10
 
13.9%
3.0 10
 
13.9%
6.0 5
 
6.9%
6.5 4
 
5.6%
2.6 1
 
1.4%
2.9 1
 
1.4%
5.5 1
 
1.4%
8.1 1
 
1.4%
6.3 1
 
1.4%
Other values (3) 3
 
4.2%
ValueCountFrequency (%)
2.6 1
 
1.4%
2.9 1
 
1.4%
3.0 10
 
13.9%
3.5 1
 
1.4%
4.0 35
48.6%
5.0 10
 
13.9%
5.5 1
 
1.4%
6.0 5
 
6.9%
6.3 1
 
1.4%
6.5 4
 
5.6%
ValueCountFrequency (%)
11.5 1
 
1.4%
8.1 1
 
1.4%
7.8 1
 
1.4%
6.5 4
 
5.6%
6.3 1
 
1.4%
6.0 5
 
6.9%
5.5 1
 
1.4%
5.0 10
 
13.9%
4.0 35
48.6%
3.5 1
 
1.4%

준공년도
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2001.2222
Minimum1971
Maximum2015
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size780.0 B
2023-12-12T21:25:52.525202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1971
5-th percentile1992
Q11997
median2001
Q32006
95-th percentile2012
Maximum2015
Range44
Interquartile range (IQR)9

Descriptive statistics

Standard deviation7.4968955
Coefficient of variation (CV)0.0037461585
Kurtosis2.3244119
Mean2001.2222
Median Absolute Deviation (MAD)5
Skewness-0.77604015
Sum144088
Variance56.203443
MonotonicityNot monotonic
2023-12-12T21:25:53.020952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
2000 7
 
9.7%
2012 6
 
8.3%
1992 6
 
8.3%
2004 6
 
8.3%
2006 5
 
6.9%
1998 5
 
6.9%
2010 5
 
6.9%
2001 4
 
5.6%
1997 3
 
4.2%
1996 3
 
4.2%
Other values (14) 22
30.6%
ValueCountFrequency (%)
1971 1
 
1.4%
1987 1
 
1.4%
1991 1
 
1.4%
1992 6
8.3%
1993 3
4.2%
1994 1
 
1.4%
1995 1
 
1.4%
1996 3
4.2%
1997 3
4.2%
1998 5
6.9%
ValueCountFrequency (%)
2015 1
 
1.4%
2012 6
8.3%
2011 2
 
2.8%
2010 5
6.9%
2009 1
 
1.4%
2007 1
 
1.4%
2006 5
6.9%
2005 2
 
2.8%
2004 6
8.3%
2003 2
 
2.8%

상부 형식
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)26.4%
Missing0
Missing (%)0.0%
Memory size708.0 B
강박스
39 
스틸박스
8 
RCS
5 
STB
 
2
STEEL BOX
 
2
Other values (14)
16 

Length

Max length18
Median length3
Mean length3.5972222
Min length2

Unique

Unique12 ?
Unique (%)16.7%

Sample

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

Common Values

ValueCountFrequency (%)
강박스 39
54.2%
스틸박스 8
 
11.1%
RCS 5
 
6.9%
STB 2
 
2.8%
STEEL BOX 2
 
2.8%
사장교 2
 
2.8%
트러스 2
 
2.8%
I빔 1
 
1.4%
강관형 1
 
1.4%
PC 빔 1
 
1.4%
Other values (9) 9
 
12.5%

Length

2023-12-12T21:25:53.198078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
강박스 39
48.8%
스틸박스 8
 
10.0%
rcs 5
 
6.2%
steel 3
 
3.8%
box 3
 
3.8%
rc 2
 
2.5%
stb 2
 
2.5%
사장교 2
 
2.5%
트러스 2
 
2.5%
h형강 1
 
1.2%
Other values (13) 13
 
16.2%

하부 형식
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size708.0 B
강재
19 
기둥식
17 
라멘식
5 
<NA>
5 
원형강관
3 
Other values (13)
23 

Length

Max length10
Median length7
Mean length3.1388889
Min length2

Unique

Unique7 ?
Unique (%)9.7%

Sample

1st row기둥식
2nd row기둥식
3rd row강재
4th row기둥식
5th row기둥식

Common Values

ValueCountFrequency (%)
강재 19
26.4%
기둥식 17
23.6%
라멘식 5
 
6.9%
<NA> 5
 
6.9%
원형강관 3
 
4.2%
라멘 3
 
4.2%
역T형 3
 
4.2%
강 재 3
 
4.2%
반중력식 3
 
4.2%
T형 2
 
2.8%
Other values (8) 9
12.5%

Length

2023-12-12T21:25:53.409957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
강재 19
24.4%
기둥식 17
21.8%
라멘식 5
 
6.4%
na 5
 
6.4%
원형강관 3
 
3.8%
라멘 3
 
3.8%
역t형 3
 
3.8%
강 3
 
3.8%
재 3
 
3.8%
반중력식 3
 
3.8%
Other values (11) 14
17.9%

설계하중
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size708.0 B
DB-13.5
54 
<NA>
8 
보행하중
7 
지가장 L=≤80m이므로 3.5*10-3(MPa)의 등분포 하중 재하
 
1
DB-18
 
1

Length

Max length38
Median length7
Mean length6.7777778
Min length4

Unique

Unique3 ?
Unique (%)4.2%

Sample

1st rowDB-13.5
2nd rowDB-13.5
3rd rowDB-13.5
4th rowDB-13.5
5th rowDB-13.5

Common Values

ValueCountFrequency (%)
DB-13.5 54
75.0%
<NA> 8
 
11.1%
보행하중 7
 
9.7%
지가장 L=≤80m이므로 3.5*10-3(MPa)의 등분포 하중 재하 1
 
1.4%
DB-18 1
 
1.4%
DB-24.0 1
 
1.4%

Length

2023-12-12T21:25:53.605680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:25:53.769244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
db-13.5 54
70.1%
na 8
 
10.4%
보행하중 7
 
9.1%
지가장 1
 
1.3%
l=≤80m이므로 1
 
1.3%
3.5*10-3(mpa)의 1
 
1.3%
등분포 1
 
1.3%
하중 1
 
1.3%
재하 1
 
1.3%
db-18 1
 
1.3%

관리주체
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size708.0 B
서구 도로과
21 
남동구
14 
부평구 도로과
11 
미추홀구 건설과
9 
중구 기반시설과
6 
Other values (4)
11 

Length

Max length8
Median length7
Mean length5.8055556
Min length2

Unique

Unique2 ?
Unique (%)2.8%

Sample

1st row중구 건설과
2nd row중구 건설과
3rd row중구 건설과
4th row중구 건설과
5th row중구 기반시설과

Common Values

ValueCountFrequency (%)
서구 도로과 21
29.2%
남동구 14
19.4%
부평구 도로과 11
15.3%
미추홀구 건설과 9
12.5%
중구 기반시설과 6
 
8.3%
연수구청 5
 
6.9%
중구 건설과 4
 
5.6%
동구 1
 
1.4%
계양구 건설과 1
 
1.4%

Length

2023-12-12T21:25:53.916621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:25:54.082030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
도로과 32
25.8%
서구 21
16.9%
남동구 14
11.3%
건설과 14
11.3%
부평구 11
 
8.9%
중구 10
 
8.1%
미추홀구 9
 
7.3%
기반시설과 6
 
4.8%
연수구청 5
 
4.0%
동구 1
 
0.8%

비고
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size708.0 B
3종
34 
3종
23 
일반
15 

Length

Max length3
Median length2
Mean length2.4722222
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3종
2nd row3종
3rd row3종
4th row3종
5th row일반

Common Values

ValueCountFrequency (%)
3종 34
47.2%
3종 23
31.9%
일반 15
20.8%

Length

2023-12-12T21:25:54.273019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:25:54.414803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3종 57
79.2%
일반 15
 
20.8%

Interactions

2023-12-12T21:25:47.886671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:25:46.611573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:25:47.015983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:25:47.451033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:25:47.997018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:25:46.709878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:25:47.125096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:25:47.560204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:25:48.104998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:25:46.820708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:25:47.217571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:25:47.666662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:25:48.203503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:25:46.921783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:25:47.318244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:25:47.753384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:25:54.501773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분시설물명위치(군구)도로명주소 또는 지번길이(미터)폭(미터)준공년도상부 형식하부 형식설계하중관리주체비고
구분1.0001.0001.0000.9850.0000.5320.5300.7260.7180.7540.8650.780
시설물명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
위치(군구)1.0001.0001.0000.9930.8270.0000.6510.9910.9450.0000.9700.862
도로명주소 또는 지번0.9851.0000.9931.0000.0000.9300.9140.9850.9611.0001.0001.000
길이(미터)0.0001.0000.8270.0001.0000.2250.0000.7580.5880.4870.0000.307
폭(미터)0.5321.0000.0000.9300.2251.0000.5390.8830.6960.5660.2050.617
준공년도0.5301.0000.6510.9140.0000.5391.0000.7900.6670.6330.3580.646
상부 형식0.7261.0000.9910.9850.7580.8830.7901.0000.9630.9400.8450.754
하부 형식0.7181.0000.9450.9610.5880.6960.6670.9631.0000.9100.9210.706
설계하중0.7541.0000.0001.0000.4870.5660.6330.9400.9101.0000.2360.540
관리주체0.8651.0000.9701.0000.0000.2050.3580.8450.9210.2361.0000.982
비고0.7801.0000.8621.0000.3070.6170.6460.7540.7060.5400.9821.000
2023-12-12T21:25:54.661001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설계하중관리주체상부 형식비고하부 형식
설계하중1.0000.1450.7410.4720.696
관리주체0.1451.0000.4900.7990.648
상부 형식0.7410.4901.0000.4900.750
비고0.4720.7990.4901.0000.450
하부 형식0.6960.6480.7500.4501.000
2023-12-12T21:25:54.782932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분길이(미터)폭(미터)준공년도상부 형식하부 형식설계하중관리주체비고
구분1.0000.0030.1970.1850.3400.3490.3900.6260.627
길이(미터)0.0031.0000.0480.1680.3710.2490.2080.0000.178
폭(미터)0.1970.0481.0000.1310.5760.3750.3800.0920.468
준공년도0.1850.1680.1311.0000.5400.4640.4480.1620.524
상부 형식0.3400.3710.5760.5401.0000.7500.7410.4900.490
하부 형식0.3490.2490.3750.4640.7501.0000.6960.6480.450
설계하중0.3900.2080.3800.4480.7410.6961.0000.1450.472
관리주체0.6260.0000.0920.1620.4900.6480.1451.0000.799
비고0.6270.1780.4680.5240.4900.4500.4720.7991.000

Missing values

2023-12-12T21:25:48.356159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:25:48.564842image/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

구분시설물명위치(군구)도로명주소 또는 지번길이(미터)폭(미터)준공년도상부 형식하부 형식설계하중관리주체비고
01도원미추홀구 용현동참외전로 212-326.05.01997강박스기둥식DB-13.5중구 건설과3종
12축항로미추홀구 용현동축항대로 27444.44.02004강박스기둥식DB-13.5중구 건설과3종
23연안미추홀구 용현동축항대로 24044.64.01993강박스강재DB-13.5중구 건설과3종
34인천항미추홀구 도화동서해대로 30745.34.01993강박스기둥식DB-13.5중구 건설과3종
45남육교미추홀구 도화동운서동 2785-1288.05.02000강박스기둥식DB-13.5중구 기반시설과일반
56상업지구육교미추홀구 용현동운서동 2787-388.05.02000강박스기둥식DB-13.5중구 기반시설과일반
67중앙공원육교서구 왕길동운서동 2709-198.05.02000강박스기둥식DB-13.5중구 기반시설과일반
78북육교중구 영종동(신도시남로)운서동 2708-3125.05.02000강박스기둥식DB-13.5중구 기반시설과일반
89방조제육교중구 영종동(영종해안북로)운서동 282670.05.02000강박스기둥식DB-13.5중구 기반시설과일반
910미단시티육교중구 영종동(신도시북로)운북동 1305164.63.02011RC 및 철골구조기둥식<NA>중구 기반시설과일반
구분시설물명위치(군구)도로명주소 또는 지번길이(미터)폭(미터)준공년도상부 형식하부 형식설계하중관리주체비고
6263당하부평구 삼산동서구 당하동32.56.02005강박스역T형DB-13.5서구 도로과3종
6364검단초교 보도육교계양구 갈현동서구 마전동32.03.02006STEEL BOXSTEEL PILEDB-13.5서구 도로과3종
6465백석초교앞서구 가정동서구 백석동29.74.01996강박스기둥식DB-13.5서구 도로과3종
6566네개동서구 가정동 632서구 석남동63.04.01996강박스기둥식DB-13.5서구 도로과3종
6667문화회관서구 가정동서구 석남동17.04.01998강박스기둥식DB-13.5서구 도로과3종
6768석남서구 가정동서구 석남동52.95.01991강박스강 재DB-13.5서구 도로과3종
6869원적산터널서구 가좌동서구 석남3동75.04.02004강박스기둥식DB-13.5서구 도로과3종
6970원당동 보도육교서구 가좌1,3동서구 원당동32.03.52006STEEL BOXSTEEL PILEDB-13.5서구 도로과3종
7071거북시장 보도육교서구 당하동서구 석남동 55774.04.01998RC SLAB, STEEL BOX교각T형<NA>서구 도로과3종
7172허암교서구 마전동서구 청라동 84-1155.56.52012사장교역T형보행하중서구 도로과일반