Overview

Dataset statistics

Number of variables7
Number of observations335
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory20.9 KiB
Average record size in memory64.0 B

Variable types

Categorical6
Text1

Dataset

Description국도상에 위치한 특수교량의 계측데이터를 관리하는 업무로 특수교통합계측관리시스템의 재난관리 개요 등 재난관련 정보를 제공함
Author국토교통부
URLhttps://www.data.go.kr/data/15123648/fileData.do

Alerts

비교값구분명 is highly overall correlated with 채널코드 and 3 other fieldsHigh correlation
비교값구분 is highly overall correlated with 데이터종류명 and 1 other fieldsHigh correlation
채널코드 is highly overall correlated with 데이터종류 and 2 other fieldsHigh correlation
데이터종류명 is highly overall correlated with 채널코드 and 3 other fieldsHigh correlation
데이터종류 is highly overall correlated with 채널코드 and 2 other fieldsHigh correlation

Reproduction

Analysis started2023-12-12 12:34:41.120932
Analysis finished2023-12-12 12:34:41.793601
Duration0.67 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

특수교량코드
Categorical

Distinct33
Distinct (%)9.9%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
서안동대교
55 
동강대교
 
16
진도대교
 
14
삼천포대교
 
13
제2진도대교
 
13
Other values (28)
224 

Length

Max length6
Median length4
Mean length4.5014925
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서안동대교 55
 
16.4%
동강대교 16
 
4.8%
진도대교 14
 
4.2%
삼천포대교 13
 
3.9%
제2진도대교 13
 
3.9%
완도대교 13
 
3.9%
동이대교 13
 
3.9%
화태대교 12
 
3.6%
소록대교 12
 
3.6%
목포대교 11
 
3.3%
Other values (23) 163
48.7%

Length

2023-12-12T21:34:41.875840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서안동대교 55
 
16.4%
동강대교 16
 
4.8%
진도대교 14
 
4.2%
삼천포대교 13
 
3.9%
제2진도대교 13
 
3.9%
완도대교 13
 
3.9%
동이대교 13
 
3.9%
화태대교 12
 
3.6%
소록대교 12
 
3.6%
목포대교 11
 
3.3%
Other values (23) 163
48.7%

특수교량명
Text

Distinct242
Distinct (%)72.2%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
2023-12-12T21:34:42.245548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length8.1850746
Min length6

Characters and Unicode

Total characters2742
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique177 ?
Unique (%)52.8%

Sample

1st rowEQK_GGBX
2nd rowEQK_GGBY
3rd rowEQK_GGBY
4th rowEQK_GGBZ
5th rowEQK_GGGE
ValueCountFrequency (%)
wg_s2m_01 10
 
3.0%
wgd001 8
 
2.4%
vis001_x 6
 
1.8%
eqk001_z 4
 
1.2%
eqk001_y 4
 
1.2%
eqk001_x 4
 
1.2%
wgd002 4
 
1.2%
wg_s2m_02 4
 
1.2%
eqk_waq_y 2
 
0.6%
eqk_mpgx 2
 
0.6%
Other values (232) 287
85.7%
2023-12-12T21:34:42.786317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
_ 431
15.7%
Q 301
 
11.0%
E 277
 
10.1%
K 261
 
9.5%
G 142
 
5.2%
0 128
 
4.7%
Z 115
 
4.2%
B 112
 
4.1%
Y 104
 
3.8%
D 94
 
3.4%
Other values (22) 777
28.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 2063
75.2%
Connector Punctuation 431
 
15.7%
Decimal Number 247
 
9.0%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
Q 301
14.6%
E 277
13.4%
K 261
12.7%
G 142
 
6.9%
Z 115
 
5.6%
B 112
 
5.4%
Y 104
 
5.0%
D 94
 
4.6%
C 86
 
4.2%
S 78
 
3.8%
Other values (13) 493
23.9%
Decimal Number
ValueCountFrequency (%)
0 128
51.8%
1 54
21.9%
2 37
 
15.0%
3 13
 
5.3%
4 9
 
3.6%
5 5
 
2.0%
6 1
 
0.4%
Connector Punctuation
ValueCountFrequency (%)
_ 431
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2063
75.2%
Common 679
 
24.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
Q 301
14.6%
E 277
13.4%
K 261
12.7%
G 142
 
6.9%
Z 115
 
5.6%
B 112
 
5.4%
Y 104
 
5.0%
D 94
 
4.6%
C 86
 
4.2%
S 78
 
3.8%
Other values (13) 493
23.9%
Common
ValueCountFrequency (%)
_ 431
63.5%
0 128
 
18.9%
1 54
 
8.0%
2 37
 
5.4%
3 13
 
1.9%
4 9
 
1.3%
5 5
 
0.7%
6 1
 
0.1%
- 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2742
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
_ 431
15.7%
Q 301
 
11.0%
E 277
 
10.1%
K 261
 
9.5%
G 142
 
5.2%
0 128
 
4.7%
Z 115
 
4.2%
B 112
 
4.1%
Y 104
 
3.8%
D 94
 
3.4%
Other values (22) 777
28.3%

채널코드
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
DT_10
216 
DT_Trigger
119 

Length

Max length10
Median length5
Mean length6.7761194
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDT_Trigger
2nd rowDT_10
3rd rowDT_Trigger
4th rowDT_Trigger
5th rowDT_Trigger

Common Values

ValueCountFrequency (%)
DT_10 216
64.5%
DT_Trigger 119
35.5%

Length

2023-12-12T21:34:42.980930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:34:43.116189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
dt_10 216
64.5%
dt_trigger 119
35.5%

데이터종류
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
10분
216 
이상신호
119 

Length

Max length4
Median length3
Mean length3.3552239
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row이상신호
2nd row10분
3rd row이상신호
4th row이상신호
5th row이상신호

Common Values

ValueCountFrequency (%)
10분 216
64.5%
이상신호 119
35.5%

Length

2023-12-12T21:34:43.258295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:34:43.386490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10분 216
64.5%
이상신호 119
35.5%

데이터종류명
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
CV_MinMax
152 
CV_MinMaxAvg
109 
CV_Avg
52 
CV_Static
21 
CV_Max
 
1

Length

Max length12
Median length9
Mean length9.5014925
Min length6

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st rowCV_MinMaxAvg
2nd rowCV_MinMax
3rd rowCV_MinMaxAvg
4th rowCV_MinMaxAvg
5th rowCV_MinMaxAvg

Common Values

ValueCountFrequency (%)
CV_MinMax 152
45.4%
CV_MinMaxAvg 109
32.5%
CV_Avg 52
 
15.5%
CV_Static 21
 
6.3%
CV_Max 1
 
0.3%

Length

2023-12-12T21:34:43.502130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:34:43.610139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
cv_minmax 152
45.4%
cv_minmaxavg 109
32.5%
cv_avg 52
 
15.5%
cv_static 21
 
6.3%
cv_max 1
 
0.3%

비교값구분
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
최대
262 
평균
52 
정적데이타
 
21

Length

Max length5
Median length2
Mean length2.1880597
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
최대 262
78.2%
평균 52
 
15.5%
정적데이타 21
 
6.3%

Length

2023-12-12T21:34:43.754329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:34:43.881496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
최대 262
78.2%
평균 52
 
15.5%
정적데이타 21
 
6.3%

비교값구분명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
최소
152 
최소(평균적용)
109 
<NA>
74 

Length

Max length8
Median length4
Mean length4.3940299
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row최소(평균적용)
2nd row최소
3rd row최소(평균적용)
4th row최소(평균적용)
5th row최소(평균적용)

Common Values

ValueCountFrequency (%)
최소 152
45.4%
최소(평균적용) 109
32.5%
<NA> 74
22.1%

Length

2023-12-12T21:34:44.004958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:34:44.108675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
최소 152
45.4%
최소(평균적용 109
32.5%
na 74
22.1%

Correlations

2023-12-12T21:34:44.406811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
특수교량코드채널코드데이터종류데이터종류명비교값구분비교값구분명
특수교량코드1.0000.4620.4620.4690.2710.577
채널코드0.4621.0001.0000.8190.1481.000
데이터종류0.4621.0001.0000.8190.1481.000
데이터종류명0.4690.8190.8191.0001.0001.000
비교값구분0.2710.1480.1481.0001.000NaN
비교값구분명0.5771.0001.0001.000NaN1.000
2023-12-12T21:34:44.506269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비교값구분명비교값구분채널코드특수교량코드데이터종류명데이터종류
비교값구분명1.0001.0000.9920.4620.9920.992
비교값구분1.0001.0000.2440.1230.9970.244
채널코드0.9920.2441.0000.3740.9410.993
특수교량코드0.4620.1230.3741.0000.2320.374
데이터종류명0.9920.9970.9410.2321.0000.941
데이터종류0.9920.2440.9930.3740.9411.000
2023-12-12T21:34:44.622737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
특수교량코드채널코드데이터종류데이터종류명비교값구분비교값구분명
특수교량코드1.0000.3740.3740.2320.1230.462
채널코드0.3741.0000.9930.9410.2440.992
데이터종류0.3740.9931.0000.9410.2440.992
데이터종류명0.2320.9410.9411.0000.9970.992
비교값구분0.1230.2440.2440.9971.0001.000
비교값구분명0.4620.9920.9920.9921.0001.000

Missing values

2023-12-12T21:34:41.594429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:34:41.743942image/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

특수교량코드특수교량명채널코드데이터종류데이터종류명비교값구분비교값구분명
GGB거금대교EQK_GGBXDT_Trigger이상신호CV_MinMaxAvg최대최소(평균적용)
GGB거금대교EQK_GGBYDT_1010분CV_MinMax최대최소
GGB거금대교EQK_GGBYDT_Trigger이상신호CV_MinMaxAvg최대최소(평균적용)
GGB거금대교EQK_GGBZDT_Trigger이상신호CV_MinMaxAvg최대최소(평균적용)
GGB거금대교EQK_GGGEDT_Trigger이상신호CV_MinMaxAvg최대최소(평균적용)
GGB거금대교EQK_GGGNDT_Trigger이상신호CV_MinMaxAvg최대최소(평균적용)
GGB거금대교EQK_GGGZDT_Trigger이상신호CV_MinMaxAvg최대최소(평균적용)
GGB거금대교EQK_GGQYDT_1010분CV_MinMax최대최소
GGB거금대교VIS001_XDT_1010분CV_Static정적데이타<NA>
GGB거금대교WGD002DT_1010분CV_Avg평균<NA>
특수교량코드특수교량명채널코드데이터종류데이터종류명비교값구분비교값구분명
HTB화태대교EQK_HTBYDT_Trigger이상신호CV_MinMaxAvg최대최소(평균적용)
HTB화태대교EQK_HTBZDT_Trigger이상신호CV_MinMaxAvg최대최소(평균적용)
HTB화태대교EQK_HTGEDT_1010분CV_MinMax최대최소
HTB화태대교EQK_HTGEDT_Trigger이상신호CV_MinMaxAvg최대최소(평균적용)
HTB화태대교EQK_HTGNDT_Trigger이상신호CV_MinMaxAvg최대최소(평균적용)
HTB화태대교EQK_HTGZDT_Trigger이상신호CV_MinMaxAvg최대최소(평균적용)
HTB화태대교EQK_HTHZDT_1010분CV_MinMax최대최소
HTB화태대교EQK_HTQYDT_1010분CV_MinMax최대최소
HTB화태대교EQK_HTQZDT_1010분CV_MinMax최대최소
HTB화태대교WGD_H03DT_1010분CV_Avg평균<NA>