Overview

Dataset statistics

Number of variables13
Number of observations32
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.5 KiB
Average record size in memory112.1 B

Variable types

Numeric4
Categorical7
Text2

Dataset

Description인천광역시 남동구 도로부속시설 점검결과에 대한 데이터로 시설명, 위치, 길이(미터), 폭(미터), 준공년도, 구조형식(상/하부), 설계하중, 시설물 안전 관리법규, 2023년 하반기 정기점검 안전등급 등을 제공합니다.
Author인천광역시 남동구
URLhttps://www.data.go.kr/data/15113331/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
설계하중 is highly overall correlated with 연번 and 4 other fieldsHigh correlation
구조 형식(상부) is highly overall correlated with 준공년도 and 4 other fieldsHigh correlation
구분 is highly overall correlated with 연번 and 6 other fieldsHigh correlation
구조 형식(하부) is highly overall correlated with 구분 and 3 other fieldsHigh correlation
2023년 하반기 안전점검 등급 is highly overall correlated with 길이(미터) and 5 other fieldsHigh correlation
연번 is highly overall correlated with 폭(미터) and 2 other fieldsHigh correlation
길이(미터) is highly overall correlated with 구분 and 1 other fieldsHigh correlation
폭(미터) is highly overall correlated with 연번 and 2 other fieldsHigh correlation
준공년도 is highly overall correlated with 구조 형식(상부)High correlation
2023년 하반기 안전점검 등급 is highly imbalanced (59.3%)Imbalance
연번 has unique valuesUnique
시설명 has unique valuesUnique

Reproduction

Analysis started2024-04-21 02:18:38.511875
Analysis finished2024-04-21 02:18:42.693340
Duration4.18 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.5
Minimum1
Maximum32
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2024-04-21T11:18:42.771173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.55
Q18.75
median16.5
Q324.25
95-th percentile30.45
Maximum32
Range31
Interquartile range (IQR)15.5

Descriptive statistics

Standard deviation9.3808315
Coefficient of variation (CV)0.56853524
Kurtosis-1.2
Mean16.5
Median Absolute Deviation (MAD)8
Skewness0
Sum528
Variance88
MonotonicityStrictly increasing
2024-04-21T11:18:42.917466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
1 1
 
3.1%
18 1
 
3.1%
32 1
 
3.1%
31 1
 
3.1%
30 1
 
3.1%
29 1
 
3.1%
28 1
 
3.1%
27 1
 
3.1%
26 1
 
3.1%
25 1
 
3.1%
Other values (22) 22
68.8%
ValueCountFrequency (%)
1 1
3.1%
2 1
3.1%
3 1
3.1%
4 1
3.1%
5 1
3.1%
6 1
3.1%
7 1
3.1%
8 1
3.1%
9 1
3.1%
10 1
3.1%
ValueCountFrequency (%)
32 1
3.1%
31 1
3.1%
30 1
3.1%
29 1
3.1%
28 1
3.1%
27 1
3.1%
26 1
3.1%
25 1
3.1%
24 1
3.1%
23 1
3.1%

구분
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)21.9%
Missing0
Missing (%)0.0%
Memory size388.0 B
보도육교
13 
일반교량
9 
보차도육교
4 
지하차도
3 
절토사면
 
1
Other values (2)
2 

Length

Max length5
Median length4
Mean length4.0625
Min length2

Unique

Unique3 ?
Unique (%)9.4%

Sample

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

Common Values

ValueCountFrequency (%)
보도육교 13
40.6%
일반교량 9
28.1%
보차도육교 4
 
12.5%
지하차도 3
 
9.4%
절토사면 1
 
3.1%
지하보도 1
 
3.1%
옹벽 1
 
3.1%

Length

2024-04-21T11:18:43.065612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:18:43.194398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
보도육교 13
40.6%
일반교량 9
28.1%
보차도육교 4
 
12.5%
지하차도 3
 
9.4%
절토사면 1
 
3.1%
지하보도 1
 
3.1%
옹벽 1
 
3.1%

시설명
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2024-04-21T11:18:43.404725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length7
Mean length4.59375
Min length2

Characters and Unicode

Total characters147
Distinct characters67
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)100.0%

Sample

1st row수현교
2nd row함박교
3rd row장수3교
4th row아암1교
5th row아암2교
ValueCountFrequency (%)
수현교 1
 
2.8%
함박교 1
 
2.8%
도림 1
 
2.8%
논현1택지 1
 
2.8%
운연동 1
 
2.8%
신월초교 1
 
2.8%
논현2택지1 1
 
2.8%
소래초(논현 1
 
2.8%
논현택지2 1
 
2.8%
해안도로 1
 
2.8%
Other values (26) 26
72.2%
2024-04-21T11:18:43.801012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 11
 
7.5%
도 6
 
4.1%
1 6
 
4.1%
현 6
 
4.1%
동 6
 
4.1%
논 5
 
3.4%
2 5
 
3.4%
아 4
 
2.7%
지 4
 
2.7%
4
 
2.7%
Other values (57) 90
61.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 126
85.7%
Decimal Number 13
 
8.8%
Space Separator 4
 
2.7%
Open Punctuation 2
 
1.4%
Close Punctuation 2
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 11
 
8.7%
도 6
 
4.8%
현 6
 
4.8%
동 6
 
4.8%
논 5
 
4.0%
아 4
 
3.2%
지 4
 
3.2%
수 4
 
3.2%
암 3
 
2.4%
림 3
 
2.4%
Other values (51) 74
58.7%
Decimal Number
ValueCountFrequency (%)
1 6
46.2%
2 5
38.5%
3 2
 
15.4%
Space Separator
ValueCountFrequency (%)
4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 126
85.7%
Common 21
 
14.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 11
 
8.7%
도 6
 
4.8%
현 6
 
4.8%
동 6
 
4.8%
논 5
 
4.0%
아 4
 
3.2%
지 4
 
3.2%
수 4
 
3.2%
암 3
 
2.4%
림 3
 
2.4%
Other values (51) 74
58.7%
Common
ValueCountFrequency (%)
1 6
28.6%
2 5
23.8%
4
19.0%
( 2
 
9.5%
) 2
 
9.5%
3 2
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 126
85.7%
ASCII 21
 
14.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 11
 
8.7%
도 6
 
4.8%
현 6
 
4.8%
동 6
 
4.8%
논 5
 
4.0%
아 4
 
3.2%
지 4
 
3.2%
수 4
 
3.2%
암 3
 
2.4%
림 3
 
2.4%
Other values (51) 74
58.7%
ASCII
ValueCountFrequency (%)
1 6
28.6%
2 5
23.8%
4
19.0%
( 2
 
9.5%
) 2
 
9.5%
3 2
 
9.5%

위치
Text

Distinct30
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Memory size388.0 B
2024-04-21T11:18:44.082373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length34
Mean length27.9375
Min length18

Characters and Unicode

Total characters894
Distinct characters125
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

Unique28 ?
Unique (%)87.5%

Sample

1st row인천광역시 남동구 장수로 42 (청소년수련관 인근)
2nd row인천광역시 남동구 함박뫼로 294 (승기천 횡단, 신연수역 앞)
3rd row인천광역시 남동구 장수동 763-1번지
4th row인천광역시 남동구 아암대로 1247
5th row인천광역시 남동구 아암대로 1247
ValueCountFrequency (%)
인천광역시 32
 
18.3%
남동구 32
 
18.3%
간석동 4
 
2.3%
인근 3
 
1.7%
횡단 3
 
1.7%
서창동 3
 
1.7%
아암대로 3
 
1.7%
1247 2
 
1.1%
승기천 2
 
1.1%
부근 2
 
1.1%
Other values (83) 89
50.9%
2024-04-21T11:18:44.480091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
145
 
16.2%
동 47
 
5.3%
구 41
 
4.6%
인 39
 
4.4%
남 35
 
3.9%
천 35
 
3.9%
역 34
 
3.8%
시 34
 
3.8%
광 32
 
3.6%
로 24
 
2.7%
Other values (115) 428
47.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 571
63.9%
Space Separator 145
 
16.2%
Decimal Number 115
 
12.9%
Close Punctuation 21
 
2.3%
Open Punctuation 21
 
2.3%
Dash Punctuation 8
 
0.9%
Math Symbol 6
 
0.7%
Other Punctuation 4
 
0.4%
Uppercase Letter 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 47
 
8.2%
구 41
 
7.2%
인 39
 
6.8%
남 35
 
6.1%
천 35
 
6.1%
역 34
 
6.0%
시 34
 
6.0%
광 32
 
5.6%
로 24
 
4.2%
지 12
 
2.1%
Other values (95) 238
41.7%
Decimal Number
ValueCountFrequency (%)
1 23
20.0%
2 19
16.5%
4 15
13.0%
6 11
9.6%
3 10
8.7%
7 9
 
7.8%
5 9
 
7.8%
8 7
 
6.1%
9 7
 
6.1%
0 5
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
T 1
33.3%
P 1
33.3%
A 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 3
75.0%
· 1
 
25.0%
Space Separator
ValueCountFrequency (%)
145
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 571
63.9%
Common 320
35.8%
Latin 3
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 47
 
8.2%
구 41
 
7.2%
인 39
 
6.8%
남 35
 
6.1%
천 35
 
6.1%
역 34
 
6.0%
시 34
 
6.0%
광 32
 
5.6%
로 24
 
4.2%
지 12
 
2.1%
Other values (95) 238
41.7%
Common
ValueCountFrequency (%)
145
45.3%
1 23
 
7.2%
) 21
 
6.6%
( 21
 
6.6%
2 19
 
5.9%
4 15
 
4.7%
6 11
 
3.4%
3 10
 
3.1%
7 9
 
2.8%
5 9
 
2.8%
Other values (7) 37
 
11.6%
Latin
ValueCountFrequency (%)
T 1
33.3%
P 1
33.3%
A 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 571
63.9%
ASCII 322
36.0%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
145
45.0%
1 23
 
7.1%
) 21
 
6.5%
( 21
 
6.5%
2 19
 
5.9%
4 15
 
4.7%
6 11
 
3.4%
3 10
 
3.1%
7 9
 
2.8%
5 9
 
2.8%
Other values (9) 39
 
12.1%
Hangul
ValueCountFrequency (%)
동 47
 
8.2%
구 41
 
7.2%
인 39
 
6.8%
남 35
 
6.1%
천 35
 
6.1%
역 34
 
6.0%
시 34
 
6.0%
광 32
 
5.6%
로 24
 
4.2%
지 12
 
2.1%
Other values (95) 238
41.7%
None
ValueCountFrequency (%)
· 1
100.0%

길이(미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct27
Distinct (%)84.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean139.96562
Minimum19
Maximum1210
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2024-04-21T11:18:44.614336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19
5-th percentile23.65
Q131.725
median47.5
Q3121
95-th percentile458.525
Maximum1210
Range1191
Interquartile range (IQR)89.275

Descriptive statistics

Standard deviation232.99918
Coefficient of variation (CV)1.6646886
Kurtosis14.638774
Mean139.96562
Median Absolute Deviation (MAD)22.5
Skewness3.5561974
Sum4478.9
Variance54288.618
MonotonicityNot monotonic
2024-04-21T11:18:44.746115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
25.0 3
 
9.4%
30.0 2
 
6.2%
50.0 2
 
6.2%
40.0 2
 
6.2%
39.8 1
 
3.1%
196.4 1
 
3.1%
22.0 1
 
3.1%
1210.0 1
 
3.1%
110.0 1
 
3.1%
80.0 1
 
3.1%
Other values (17) 17
53.1%
ValueCountFrequency (%)
19.0 1
 
3.1%
22.0 1
 
3.1%
25.0 3
9.4%
28.4 1
 
3.1%
30.0 2
6.2%
32.3 1
 
3.1%
33.5 1
 
3.1%
39.8 1
 
3.1%
40.0 2
6.2%
43.3 1
 
3.1%
ValueCountFrequency (%)
1210.0 1
3.1%
560.0 1
3.1%
375.5 1
3.1%
370.0 1
3.1%
315.0 1
3.1%
196.4 1
3.1%
157.0 1
3.1%
130.0 1
3.1%
118.0 1
3.1%
110.0 1
3.1%

폭(미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct16
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.6125
Minimum2.2
Maximum40
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2024-04-21T11:18:44.896946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.2
5-th percentile3
Q14
median6.3
Q317.25
95-th percentile24.5
Maximum40
Range37.8
Interquartile range (IQR)13.25

Descriptive statistics

Standard deviation8.9903084
Coefficient of variation (CV)0.84714331
Kurtosis2.4680447
Mean10.6125
Median Absolute Deviation (MAD)3.3
Skewness1.5408633
Sum339.6
Variance80.825645
MonotonicityNot monotonic
2024-04-21T11:18:45.028900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
4.0 8
25.0%
20.0 5
15.6%
3.0 3
 
9.4%
5.0 3
 
9.4%
11.4 2
 
6.2%
10.8 1
 
3.1%
6.6 1
 
3.1%
2.2 1
 
3.1%
40.0 1
 
3.1%
6.0 1
 
3.1%
Other values (6) 6
18.8%
ValueCountFrequency (%)
2.2 1
 
3.1%
3.0 3
 
9.4%
4.0 8
25.0%
5.0 3
 
9.4%
6.0 1
 
3.1%
6.6 1
 
3.1%
9.2 1
 
3.1%
10.0 1
 
3.1%
10.8 1
 
3.1%
11.0 1
 
3.1%
ValueCountFrequency (%)
40.0 1
 
3.1%
30.0 1
 
3.1%
20.0 5
15.6%
18.0 1
 
3.1%
17.0 1
 
3.1%
11.4 2
 
6.2%
11.0 1
 
3.1%
10.8 1
 
3.1%
10.0 1
 
3.1%
9.2 1
 
3.1%

준공년도
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)68.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2000.8438
Minimum1976
Maximum2018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2024-04-21T11:18:45.173016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1976
5-th percentile1983.75
Q11995
median2001.5
Q32009.25
95-th percentile2016.9
Maximum2018
Range42
Interquartile range (IQR)14.25

Descriptive statistics

Standard deviation10.432917
Coefficient of variation (CV)0.005214259
Kurtosis-0.17254966
Mean2000.8438
Median Absolute Deviation (MAD)7
Skewness-0.35000746
Sum64027
Variance108.84577
MonotonicityNot monotonic
2024-04-21T11:18:45.286870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
2003 4
 
12.5%
1997 3
 
9.4%
1998 2
 
6.2%
2012 2
 
6.2%
2018 2
 
6.2%
2010 2
 
6.2%
1995 2
 
6.2%
1976 1
 
3.1%
1986 1
 
3.1%
2005 1
 
3.1%
Other values (12) 12
37.5%
ValueCountFrequency (%)
1976 1
 
3.1%
1981 1
 
3.1%
1986 1
 
3.1%
1987 1
 
3.1%
1989 1
 
3.1%
1993 1
 
3.1%
1994 1
 
3.1%
1995 2
6.2%
1996 1
 
3.1%
1997 3
9.4%
ValueCountFrequency (%)
2018 2
6.2%
2016 1
 
3.1%
2013 1
 
3.1%
2012 2
6.2%
2010 2
6.2%
2009 1
 
3.1%
2007 1
 
3.1%
2006 1
 
3.1%
2005 1
 
3.1%
2003 4
12.5%

구조 형식(상부)
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)28.1%
Missing0
Missing (%)0.0%
Memory size388.0 B
강박스
16 
라멘
7 
강박스거더
2 
<NA>
2 
스라브
 
1
Other values (4)
4 

Length

Max length5
Median length3
Mean length3.09375
Min length2

Unique

Unique5 ?
Unique (%)15.6%

Sample

1st row스라브
2nd rowPSCI빔
3rd rowIC슬래브
4th row강박스거더
5th row강박스거더

Common Values

ValueCountFrequency (%)
강박스 16
50.0%
라멘 7
21.9%
강박스거더 2
 
6.2%
<NA> 2
 
6.2%
스라브 1
 
3.1%
PSCI빔 1
 
3.1%
IC슬래브 1
 
3.1%
PC빔 1
 
3.1%
역T형 1
 
3.1%

Length

2024-04-21T11:18:45.425468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:18:45.685235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강박스 16
50.0%
라멘 7
21.9%
강박스거더 2
 
6.2%
na 2
 
6.2%
스라브 1
 
3.1%
psci빔 1
 
3.1%
ic슬래브 1
 
3.1%
pc빔 1
 
3.1%
역t형 1
 
3.1%

구조 형식(하부)
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
반중력식
8 
강재
7 
라멘
6 
<NA>
6 
역T
2 
Other values (3)
3 

Length

Max length4
Median length3.5
Mean length2.96875
Min length2

Unique

Unique3 ?
Unique (%)9.4%

Sample

1st row반중력식
2nd row라멘
3rd row벽식
4th row역T
5th row역T

Common Values

ValueCountFrequency (%)
반중력식 8
25.0%
강재 7
21.9%
라멘 6
18.8%
<NA> 6
18.8%
역T 2
 
6.2%
벽식 1
 
3.1%
PC파일 1
 
3.1%
기둥식 1
 
3.1%

Length

2024-04-21T11:18:45.865853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:18:46.225379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
반중력식 8
25.0%
강재 7
21.9%
라멘 6
18.8%
na 6
18.8%
역t 2
 
6.2%
벽식 1
 
3.1%
pc파일 1
 
3.1%
기둥식 1
 
3.1%

설계하중
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size388.0 B
DB-24
15 
DB-13.5
12 
<NA>
3 
DB-18
2 

Length

Max length7
Median length5
Mean length5.65625
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDB-18
2nd rowDB-24
3rd rowDB-24
4th rowDB-24
5th rowDB-24

Common Values

ValueCountFrequency (%)
DB-24 15
46.9%
DB-13.5 12
37.5%
<NA> 3
 
9.4%
DB-18 2
 
6.2%

Length

2024-04-21T11:18:46.371412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:18:46.487223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
db-24 15
46.9%
db-13.5 12
37.5%
na 3
 
9.4%
db-18 2
 
6.2%

시설물 안전 관리법규
Categorical

Distinct4
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size388.0 B
시특법(3종)
22 
시특법(2종)
6 
비대상
3 
시특법(1종)
 
1

Length

Max length7
Median length7
Mean length6.625
Min length3

Unique

Unique1 ?
Unique (%)3.1%

Sample

1st row시특법(3종)
2nd row시특법(3종)
3rd row시특법(3종)
4th row시특법(1종)
5th row시특법(2종)

Common Values

ValueCountFrequency (%)
시특법(3종) 22
68.8%
시특법(2종) 6
 
18.8%
비대상 3
 
9.4%
시특법(1종) 1
 
3.1%

Length

2024-04-21T11:18:46.625942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:18:46.775368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
시특법(3종 22
68.8%
시특법(2종 6
 
18.8%
비대상 3
 
9.4%
시특법(1종 1
 
3.1%

2023년 하반기 안전점검 등급
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Memory size388.0 B
B등급(양호)
28 
<NA>
3 
C등급(보통)
 
1

Length

Max length7
Median length7
Mean length6.71875
Min length4

Unique

Unique1 ?
Unique (%)3.1%

Sample

1st rowB등급(양호)
2nd rowB등급(양호)
3rd rowB등급(양호)
4th rowB등급(양호)
5th rowB등급(양호)

Common Values

ValueCountFrequency (%)
B등급(양호) 28
87.5%
<NA> 3
 
9.4%
C등급(보통) 1
 
3.1%

Length

2024-04-21T11:18:46.913783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:18:47.025407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
b등급(양호 28
87.5%
na 3
 
9.4%
c등급(보통 1
 
3.1%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size388.0 B
2024-03-26
32 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-03-26
2nd row2024-03-26
3rd row2024-03-26
4th row2024-03-26
5th row2024-03-26

Common Values

ValueCountFrequency (%)
2024-03-26 32
100.0%

Length

2024-04-21T11:18:47.129844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:18:47.228166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-03-26 32
100.0%

Interactions

2024-04-21T11:18:41.947097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:18:40.825945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:18:41.219255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:18:41.578088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:18:42.034784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:18:40.962234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:18:41.311200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:18:41.670104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:18:42.126990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:18:41.052149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:18:41.409714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:18:41.771912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:18:42.271563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:18:41.136666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:18:41.495749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:18:41.866856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T11:18:47.307868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구분시설명위치길이(미터)폭(미터)준공년도구조 형식(상부)구조 형식(하부)설계하중시설물 안전 관리법규2023년 하반기 안전점검 등급
연번1.0000.8421.0000.8830.0000.5810.6990.4920.4610.7640.5790.000
구분0.8421.0001.0001.0000.7580.9300.6160.7610.6960.6270.5371.000
시설명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
위치0.8831.0001.0001.0001.0001.0001.0001.0001.0001.0000.0001.000
길이(미터)0.0000.7581.0001.0001.0000.8580.2670.8350.4260.0000.5301.000
폭(미터)0.5810.9301.0001.0000.8581.0000.6240.6200.6310.7820.6401.000
준공년도0.6990.6161.0001.0000.2670.6241.0000.7510.3100.3750.4510.000
구조 형식(상부)0.4920.7611.0001.0000.8350.6200.7511.0000.9350.6940.817NaN
구조 형식(하부)0.4610.6961.0001.0000.4260.6310.3100.9351.0000.7230.486NaN
설계하중0.7640.6271.0001.0000.0000.7820.3750.6940.7231.0000.300NaN
시설물 안전 관리법규0.5790.5371.0000.0000.5300.6400.4510.8170.4860.3001.0000.164
2023년 하반기 안전점검 등급0.0001.0001.0001.0001.0001.0000.000NaNNaNNaN0.1641.000
2024-04-21T11:18:47.457582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설계하중구조 형식(상부)시설물 안전 관리법규구분구조 형식(하부)2023년 하반기 안전점검 등급
설계하중1.0000.5540.2760.6330.5811.000
구조 형식(상부)0.5541.0000.4390.5620.6091.000
시설물 안전 관리법규0.2760.4391.0000.3710.3160.261
구분0.6330.5620.3711.0000.5160.903
구조 형식(하부)0.5810.6090.3160.5161.0001.000
2023년 하반기 안전점검 등급1.0001.0000.2610.9031.0001.000
2024-04-21T11:18:47.575866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번길이(미터)폭(미터)준공년도구분구조 형식(상부)구조 형식(하부)설계하중시설물 안전 관리법규2023년 하반기 안전점검 등급
연번1.0000.251-0.623-0.0460.5940.2220.1940.5410.3300.000
길이(미터)0.2511.0000.124-0.1260.5940.4590.2670.0000.4450.943
폭(미터)-0.6230.1241.000-0.0710.6000.3780.4190.4280.4670.903
준공년도-0.046-0.126-0.0711.0000.3210.5650.0000.4660.2080.000
구분0.5940.5940.6000.3211.0000.5620.5160.6330.3710.903
구조 형식(상부)0.2220.4590.3780.5650.5621.0000.6090.5540.4391.000
구조 형식(하부)0.1940.2670.4190.0000.5160.6091.0000.5810.3161.000
설계하중0.5410.0000.4280.4660.6330.5540.5811.0000.2761.000
시설물 안전 관리법규0.3300.4450.4670.2080.3710.4390.3160.2761.0000.261
2023년 하반기 안전점검 등급0.0000.9430.9030.0000.9031.0001.0001.0000.2611.000

Missing values

2024-04-21T11:18:42.396794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T11:18:42.588414image/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

연번구분시설명위치길이(미터)폭(미터)준공년도구조 형식(상부)구조 형식(하부)설계하중시설물 안전 관리법규2023년 하반기 안전점검 등급데이터기준일자
01일반교량수현교인천광역시 남동구 장수로 42 (청소년수련관 인근)25.010.81976스라브반중력식DB-18시특법(3종)B등급(양호)2024-03-26
12일반교량함박교인천광역시 남동구 함박뫼로 294 (승기천 횡단, 신연수역 앞)90.120.01989PSCI빔라멘DB-24시특법(3종)B등급(양호)2024-03-26
23일반교량장수3교인천광역시 남동구 장수동 763-1번지30.011.01997IC슬래브벽식DB-24시특법(3종)B등급(양호)2024-03-26
34일반교량아암1교인천광역시 남동구 아암대로 1247370.011.42012강박스거더역TDB-24시특법(1종)B등급(양호)2024-03-26
45일반교량아암2교인천광역시 남동구 아암대로 1247315.011.42012강박스거더역TDB-24시특법(2종)B등급(양호)2024-03-26
56일반교량서창1교인천광역시 남동구 서창동 758 (서창에코에비뉴APT)19.018.02013라멘라멘DB-24비대상<NA>2024-03-26
67일반교량매사리2교인천광역시 남동구 서창동 24-125.020.02018라멘<NA>DB-24비대상<NA>2024-03-26
78일반교량매사리1교인천광역시 남동구 서창동 24-125.020.02018라멘<NA>DB-24비대상<NA>2024-03-26
89일반교량운연3교인천광역시 남동구 운연동 195-10450.020.02016강박스<NA>DB-24시특법(2종)B등급(양호)2024-03-26
910보차도육교서창인천광역시 남동구 장아산로 216 (서창1지구~서창2지구)50.09.21994강박스반중력식DB-24시특법(3종)B등급(양호)2024-03-26
연번구분시설명위치길이(미터)폭(미터)준공년도구조 형식(상부)구조 형식(하부)설계하중시설물 안전 관리법규2023년 하반기 안전점검 등급데이터기준일자
2223보도육교운연동인천광역시 남동구 수인로 3548 (연락골지구 추어마을)32.34.02000강박스강재DB-13.5시특법(3종)B등급(양호)2024-03-26
2324보도육교신월초교인천광역시 남동구 인주대로 781 (신월초, 미추홀도서관 입구)33.54.02003강박스반중력식DB-13.5시특법(3종)B등급(양호)2024-03-26
2425보도육교논현2택지1인천광역시 남동구 은봉로 288 (신일해피트리~리틀야구장)130.04.02006강박스강재DB-13.5시특법(3종)B등급(양호)2024-03-26
2526보도육교소래초(논현)인천광역시 남동구 장도로 2 (소래초교 옆 논현주유소 부근)157.03.02007강박스반중력식DB-13.5시특법(3종)B등급(양호)2024-03-26
2627보도육교논현택지2인천광역시 남동구 은봉로166번길 27 (논현주공2~3단지)92.04.02009강박스강재DB-13.5시특법(3종)B등급(양호)2024-03-26
2728보도육교해안도로인천광역시 남동구 아암대로 1239 (운전면허시험장 부근)80.03.02010강박스강재DB-13.5시특법(3종)B등급(양호)2024-03-26
2829보도육교승기천 횡단인천광역시 남동구 남동서로205번길 32 (원인재역~남동공단 승기천 횡단)110.03.02010강박스반중력식DB-13.5시특법(3종)B등급(양호)2024-03-26
2930절토사면만월산 절토사면인천광역시 남동구 간석동 1-8071210.040.01995<NA><NA><NA>시특법(2종)C등급(보통)2024-03-26
3031지하보도간석동 지하보도인천광역시 남동구 간석동 494-122.02.22005<NA><NA><NA>시특법(3종)B등급(양호)2024-03-26
3132옹벽동암초 옹벽인천광역시 남동구 간석동 116-4196.46.61986역T형<NA><NA>시특법(2종)B등급(양호)2024-03-26