Overview

Dataset statistics

Number of variables17
Number of observations24
Missing cells28
Missing cells (%)6.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 KiB
Average record size in memory156.5 B

Variable types

Numeric6
Categorical10
Text1

Dataset

Description국토안전관리원에서 제공하는 데이터이며 시설물의 안전관리에 관한 특별법에 의거하여 국토안전관리원에서 관리중인 특수교량인 사장교에 대한 계측기 설치 현황을 제공합니다.
URLhttps://www.data.go.kr/data/15040882/fileData.do

Alerts

형식 has constant value ""Constant
3D풍향풍속계 is highly overall correlated with 정적변형률계 and 1 other fieldsHigh correlation
처짐계 is highly overall correlated with 동적변형률계 and 2 other fieldsHigh correlation
지진계 is highly overall correlated with 경사계 and 1 other fieldsHigh correlation
2D풍향풍속계 is highly overall correlated with 가속도계 and 3 other fieldsHigh correlation
정적변형률계 is highly overall correlated with 케이블가속도계 and 6 other fieldsHigh correlation
GPS센서 is highly overall correlated with 순번 and 3 other fieldsHigh correlation
시정계 is highly overall correlated with 순번 and 12 other fieldsHigh correlation
신축변위계 is highly overall correlated with 동적변형률계 and 5 other fieldsHigh correlation
순번 is highly overall correlated with GPS센서 and 1 other fieldsHigh correlation
가속도계 is highly overall correlated with 동적변형률계 and 2 other fieldsHigh correlation
경사계 is highly overall correlated with 케이블가속도계 and 3 other fieldsHigh correlation
케이블가속도계 is highly overall correlated with 경사계 and 2 other fieldsHigh correlation
동적변형률계 is highly overall correlated with 가속도계 and 6 other fieldsHigh correlation
온도계 is highly overall correlated with 신축변위계 and 1 other fieldsHigh correlation
신축변위계 is highly imbalanced (75.0%)Imbalance
하중계 is highly imbalanced (75.0%)Imbalance
경사계 has 10 (41.7%) missing valuesMissing
동적변형률계 has 18 (75.0%) missing valuesMissing
순번 has unique valuesUnique
교량명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 18:31:54.360022
Analysis finished2023-12-12 18:32:00.292538
Duration5.93 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.5
Minimum1
Maximum24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-13T03:32:00.359818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.15
Q16.75
median12.5
Q318.25
95-th percentile22.85
Maximum24
Range23
Interquartile range (IQR)11.5

Descriptive statistics

Standard deviation7.0710678
Coefficient of variation (CV)0.56568542
Kurtosis-1.2
Mean12.5
Median Absolute Deviation (MAD)6
Skewness0
Sum300
Variance50
MonotonicityStrictly increasing
2023-12-13T03:32:00.495066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1 1
 
4.2%
14 1
 
4.2%
24 1
 
4.2%
23 1
 
4.2%
22 1
 
4.2%
21 1
 
4.2%
20 1
 
4.2%
19 1
 
4.2%
18 1
 
4.2%
17 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
1 1
4.2%
2 1
4.2%
3 1
4.2%
4 1
4.2%
5 1
4.2%
6 1
4.2%
7 1
4.2%
8 1
4.2%
9 1
4.2%
10 1
4.2%
ValueCountFrequency (%)
24 1
4.2%
23 1
4.2%
22 1
4.2%
21 1
4.2%
20 1
4.2%
19 1
4.2%
18 1
4.2%
17 1
4.2%
16 1
4.2%
15 1
4.2%

형식
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
사장교
24 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사장교 24
100.0%

Length

2023-12-13T03:32:00.624657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:32:00.712075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사장교 24
100.0%

교량명
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-13T03:32:00.899343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.5
Min length3

Characters and Unicode

Total characters108
Distinct characters44
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)100.0%

Sample

1st row진도대교
2nd row제2진도대교
3rd row동강대교
4th row거금대교
5th row거북선대교
ValueCountFrequency (%)
진도대교 1
 
4.2%
제2진도대교 1
 
4.2%
임자1대교 1
 
4.2%
원산안면대교 1
 
4.2%
칠산대교 1
 
4.2%
둔병대교 1
 
4.2%
화양조발대교 1
 
4.2%
삼천포대교 1
 
4.2%
천사대교1 1
 
4.2%
세풍대교 1
 
4.2%
Other values (14) 14
58.3%
2023-12-13T03:32:01.272196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 24
22.2%
대 22
20.4%
도 4
 
3.7%
동 3
 
2.8%
자 3
 
2.8%
천 3
 
2.8%
진 2
 
1.9%
포 2
 
1.9%
산 2
 
1.9%
1 2
 
1.9%
Other values (34) 41
38.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 104
96.3%
Decimal Number 4
 
3.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 24
23.1%
대 22
21.2%
도 4
 
3.8%
동 3
 
2.9%
자 3
 
2.9%
천 3
 
2.9%
진 2
 
1.9%
포 2
 
1.9%
산 2
 
1.9%
장 2
 
1.9%
Other values (32) 37
35.6%
Decimal Number
ValueCountFrequency (%)
1 2
50.0%
2 2
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 104
96.3%
Common 4
 
3.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 24
23.1%
대 22
21.2%
도 4
 
3.8%
동 3
 
2.9%
자 3
 
2.9%
천 3
 
2.9%
진 2
 
1.9%
포 2
 
1.9%
산 2
 
1.9%
장 2
 
1.9%
Other values (32) 37
35.6%
Common
ValueCountFrequency (%)
1 2
50.0%
2 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 104
96.3%
ASCII 4
 
3.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 24
23.1%
대 22
21.2%
도 4
 
3.8%
동 3
 
2.9%
자 3
 
2.9%
천 3
 
2.9%
진 2
 
1.9%
포 2
 
1.9%
산 2
 
1.9%
장 2
 
1.9%
Other values (32) 37
35.6%
ASCII
ValueCountFrequency (%)
1 2
50.0%
2 2
50.0%

가속도계
Real number (ℝ)

HIGH CORRELATION 

Distinct10
Distinct (%)41.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.7083333
Minimum1
Maximum14
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-13T03:32:01.442002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q36.25
95-th percentile12.25
Maximum14
Range13
Interquartile range (IQR)4.25

Descriptive statistics

Standard deviation3.4575584
Coefficient of variation (CV)0.73434869
Kurtosis1.8172304
Mean4.7083333
Median Absolute Deviation (MAD)2
Skewness1.3978644
Sum113
Variance11.95471
MonotonicityNot monotonic
2023-12-13T03:32:01.566218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
4 4
16.7%
2 4
16.7%
3 4
16.7%
1 3
12.5%
7 2
8.3%
6 2
8.3%
8 2
8.3%
14 1
 
4.2%
13 1
 
4.2%
5 1
 
4.2%
ValueCountFrequency (%)
1 3
12.5%
2 4
16.7%
3 4
16.7%
4 4
16.7%
5 1
 
4.2%
6 2
8.3%
7 2
8.3%
8 2
8.3%
13 1
 
4.2%
14 1
 
4.2%
ValueCountFrequency (%)
14 1
 
4.2%
13 1
 
4.2%
8 2
8.3%
7 2
8.3%
6 2
8.3%
5 1
 
4.2%
4 4
16.7%
3 4
16.7%
2 4
16.7%
1 3
12.5%

경사계
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct6
Distinct (%)42.9%
Missing10
Missing (%)41.7%
Infinite0
Infinite (%)0.0%
Mean3.6428571
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-13T03:32:01.712260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile8.35
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.4994505
Coefficient of variation (CV)0.68612366
Kurtosis0.38898365
Mean3.6428571
Median Absolute Deviation (MAD)1
Skewness1.0957554
Sum51
Variance6.2472527
MonotonicityNot monotonic
2023-12-13T03:32:01.850942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2 5
20.8%
4 4
 
16.7%
1 2
 
8.3%
9 1
 
4.2%
6 1
 
4.2%
8 1
 
4.2%
(Missing) 10
41.7%
ValueCountFrequency (%)
1 2
 
8.3%
2 5
20.8%
4 4
16.7%
6 1
 
4.2%
8 1
 
4.2%
9 1
 
4.2%
ValueCountFrequency (%)
9 1
 
4.2%
8 1
 
4.2%
6 1
 
4.2%
4 4
16.7%
2 5
20.8%
1 2
 
8.3%

케이블가속도계
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.5833333
Minimum1
Maximum25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-13T03:32:01.995191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q15.5
median7
Q310.25
95-th percentile22.1
Maximum25
Range24
Interquartile range (IQR)4.75

Descriptive statistics

Standard deviation6.0427223
Coefficient of variation (CV)0.70400648
Kurtosis2.0870182
Mean8.5833333
Median Absolute Deviation (MAD)3
Skewness1.5085057
Sum206
Variance36.514493
MonotonicityNot monotonic
2023-12-13T03:32:02.108474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
7 8
33.3%
3 4
16.7%
11 2
 
8.3%
6 2
 
8.3%
15 1
 
4.2%
17 1
 
4.2%
4 1
 
4.2%
1 1
 
4.2%
23 1
 
4.2%
10 1
 
4.2%
Other values (2) 2
 
8.3%
ValueCountFrequency (%)
1 1
 
4.2%
3 4
16.7%
4 1
 
4.2%
6 2
 
8.3%
7 8
33.3%
9 1
 
4.2%
10 1
 
4.2%
11 2
 
8.3%
15 1
 
4.2%
17 1
 
4.2%
ValueCountFrequency (%)
25 1
 
4.2%
23 1
 
4.2%
17 1
 
4.2%
15 1
 
4.2%
11 2
 
8.3%
10 1
 
4.2%
9 1
 
4.2%
7 8
33.3%
6 2
 
8.3%
4 1
 
4.2%

처짐계
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size324.0 B
1
14 
<NA>
7 
3
3 

Length

Max length4
Median length1
Mean length1.875
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 14
58.3%
<NA> 7
29.2%
3 3
 
12.5%

Length

2023-12-13T03:32:02.228223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:32:02.335563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 14
58.3%
na 7
29.2%
3 3
 
12.5%

동적변형률계
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct6
Distinct (%)100.0%
Missing18
Missing (%)75.0%
Infinite0
Infinite (%)0.0%
Mean14.166667
Minimum4
Maximum26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-13T03:32:02.457772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile4.5
Q16.5
median12.5
Q322.25
95-th percentile25.5
Maximum26
Range22
Interquartile range (IQR)15.75

Descriptive statistics

Standard deviation9.5166521
Coefficient of variation (CV)0.67176368
Kurtosis-2.358434
Mean14.166667
Median Absolute Deviation (MAD)7.5
Skewness0.27865071
Sum85
Variance90.566667
MonotonicityNot monotonic
2023-12-13T03:32:02.587209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
6 1
 
4.2%
26 1
 
4.2%
8 1
 
4.2%
24 1
 
4.2%
17 1
 
4.2%
4 1
 
4.2%
(Missing) 18
75.0%
ValueCountFrequency (%)
4 1
4.2%
6 1
4.2%
8 1
4.2%
17 1
4.2%
24 1
4.2%
26 1
4.2%
ValueCountFrequency (%)
26 1
4.2%
24 1
4.2%
17 1
4.2%
8 1
4.2%
6 1
4.2%
4 1
4.2%

지진계
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
8
9 
7
6 
9
4 
<NA>
3 
2
1 

Length

Max length4
Median length1
Mean length1.375
Min length1

Unique

Unique2 ?
Unique (%)8.3%

Sample

1st row8
2nd row<NA>
3rd row2
4th row8
5th row9

Common Values

ValueCountFrequency (%)
8 9
37.5%
7 6
25.0%
9 4
16.7%
<NA> 3
 
12.5%
2 1
 
4.2%
6 1
 
4.2%

Length

2023-12-13T03:32:02.733526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:32:02.849904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
8 9
37.5%
7 6
25.0%
9 4
16.7%
na 3
 
12.5%
2 1
 
4.2%
6 1
 
4.2%

신축변위계
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size324.0 B
2
23 
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)4.2%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 23
95.8%
4 1
 
4.2%

Length

2023-12-13T03:32:02.987169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:32:03.083804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 23
95.8%
4 1
 
4.2%

하중계
Categorical

IMBALANCE 

Distinct2
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size324.0 B
<NA>
23 
4
 
1

Length

Max length4
Median length4
Mean length3.875
Min length1

Unique

Unique1 ?
Unique (%)4.2%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 23
95.8%
4 1
 
4.2%

Length

2023-12-13T03:32:03.190796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:32:03.305471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 23
95.8%
4 1
 
4.2%

GPS센서
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size324.0 B
<NA>
16 
3
4 
1
3 
4
 
1

Length

Max length4
Median length4
Mean length3
Min length1

Unique

Unique1 ?
Unique (%)4.2%

Sample

1st row3
2nd row3
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 16
66.7%
3 4
 
16.7%
1 3
 
12.5%
4 1
 
4.2%

Length

2023-12-13T03:32:03.414527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:32:03.552561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 16
66.7%
3 4
 
16.7%
1 3
 
12.5%
4 1
 
4.2%

정적변형률계
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
<NA>
18 
8
2 
16
 
1
14
 
1
13
 
1

Length

Max length4
Median length4
Mean length3.4166667
Min length1

Unique

Unique4 ?
Unique (%)16.7%

Sample

1st row16
2nd row14
3rd row13
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 18
75.0%
8 2
 
8.3%
16 1
 
4.2%
14 1
 
4.2%
13 1
 
4.2%
32 1
 
4.2%

Length

2023-12-13T03:32:04.043317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:32:04.198107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 18
75.0%
8 2
 
8.3%
16 1
 
4.2%
14 1
 
4.2%
13 1
 
4.2%
32 1
 
4.2%

온도계
Real number (ℝ)

HIGH CORRELATION 

Distinct17
Distinct (%)70.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.875
Minimum1
Maximum43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-13T03:32:04.339487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5
Q112.5
median15
Q322.25
95-th percentile30.4
Maximum43
Range42
Interquartile range (IQR)9.75

Descriptive statistics

Standard deviation9.5020021
Coefficient of variation (CV)0.5630816
Kurtosis1.1658979
Mean16.875
Median Absolute Deviation (MAD)5.5
Skewness0.76802136
Sum405
Variance90.288043
MonotonicityNot monotonic
2023-12-13T03:32:04.486614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
15 4
16.7%
27 2
 
8.3%
5 2
 
8.3%
13 2
 
8.3%
17 2
 
8.3%
14 1
 
4.2%
26 1
 
4.2%
11 1
 
4.2%
22 1
 
4.2%
6 1
 
4.2%
Other values (7) 7
29.2%
ValueCountFrequency (%)
1 1
 
4.2%
5 2
8.3%
6 1
 
4.2%
7 1
 
4.2%
11 1
 
4.2%
13 2
8.3%
14 1
 
4.2%
15 4
16.7%
17 2
8.3%
18 1
 
4.2%
ValueCountFrequency (%)
43 1
 
4.2%
31 1
 
4.2%
27 2
8.3%
26 1
 
4.2%
23 1
 
4.2%
22 1
 
4.2%
19 1
 
4.2%
18 1
 
4.2%
17 2
8.3%
15 4
16.7%

시정계
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size324.0 B
<NA>
16 
1
8 

Length

Max length4
Median length4
Mean length3
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row<NA>
3rd row<NA>
4th row1
5th row1

Common Values

ValueCountFrequency (%)
<NA> 16
66.7%
1 8
33.3%

Length

2023-12-13T03:32:04.661599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:32:04.772937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 16
66.7%
1 8
33.3%

2D풍향풍속계
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size324.0 B
2
12 
1
8 
<NA>
4 

Length

Max length4
Median length1
Mean length1.5
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row<NA>
3rd row<NA>
4th row2
5th row1

Common Values

ValueCountFrequency (%)
2 12
50.0%
1 8
33.3%
<NA> 4
 
16.7%

Length

2023-12-13T03:32:04.896069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:32:05.024673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 12
50.0%
1 8
33.3%
na 4
 
16.7%

3D풍향풍속계
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size324.0 B
1
17 
2
5 
<NA>
2 

Length

Max length4
Median length1
Mean length1.25
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row1
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
1 17
70.8%
2 5
 
20.8%
<NA> 2
 
8.3%

Length

2023-12-13T03:32:05.209065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:32:05.344140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 17
70.8%
2 5
 
20.8%
na 2
 
8.3%

Interactions

2023-12-13T03:31:58.965270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:31:55.186853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:31:55.840340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:31:56.814904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:31:57.563895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:31:58.259441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:31:59.063616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:31:55.274841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:31:55.947503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:31:56.934391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:31:57.675002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:31:58.367653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:31:59.192168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:31:55.364628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:31:56.084635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:31:57.057037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:31:57.793997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:31:58.467313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:31:59.301205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:31:55.489479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:31:56.211646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:31:57.194737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:31:57.929707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:31:58.603754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:31:59.389912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:31:55.641089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:31:56.317127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:31:57.327936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:31:58.051302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:31:58.742653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:31:59.492944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:31:55.734380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:31:56.727518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:31:57.459484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:31:58.164376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:31:58.863383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T03:32:05.458840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번교량명가속도계경사계케이블가속도계처짐계동적변형률계지진계신축변위계GPS센서정적변형률계온도계2D풍향풍속계3D풍향풍속계
순번1.0001.0000.0000.5270.5290.0000.5730.0000.5271.0000.0000.0000.0000.226
교량명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
가속도계0.0001.0001.0000.8130.3090.0000.5730.4150.0000.4030.8590.4220.6260.000
경사계0.5271.0000.8131.0000.0000.8040.4160.6640.0000.0000.6470.6460.1780.000
케이블가속도계0.5291.0000.3090.0001.0000.0000.5730.4420.0000.4531.0000.5030.0000.613
처짐계0.0001.0000.0000.8040.0001.0001.0000.0000.000NaN1.0000.3290.0000.088
동적변형률계0.5731.0000.5730.4160.5731.0001.0000.0001.000NaN1.0000.7591.0000.000
지진계0.0001.0000.4150.6640.4420.0000.0001.0000.0000.5580.4160.0000.5360.000
신축변위계0.5271.0000.0000.0000.0000.0001.0000.0001.000NaN1.0001.000NaN0.000
GPS센서1.0001.0000.4030.0000.453NaNNaN0.558NaN1.000NaN0.0000.0000.203
정적변형률계0.0001.0000.8590.6471.0001.0001.0000.4161.000NaN1.0000.9420.0001.000
온도계0.0001.0000.4220.6460.5030.3290.7590.0001.0000.0000.9421.0000.7760.372
2D풍향풍속계0.0001.0000.6260.1780.0000.0001.0000.536NaN0.0000.0000.7761.0000.183
3D풍향풍속계0.2261.0000.0000.0000.6130.0880.0000.0000.0000.2031.0000.3720.1831.000
2023-12-13T03:32:05.644932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
3D풍향풍속계처짐계지진계2D풍향풍속계하중계정적변형률계GPS센서시정계신축변위계
3D풍향풍속계1.0000.0000.0000.102NaN0.5000.2361.0000.000
처짐계0.0001.0000.0000.000NaN0.577NaN1.0000.000
지진계0.0000.0001.0000.329NaN0.0000.4081.0000.000
2D풍향풍속계0.1020.0000.3291.000NaN0.0000.0001.0001.000
하중계NaNNaNNaNNaN1.000NaNNaNNaNNaN
정적변형률계0.5000.5770.0000.000NaN1.0001.0001.0000.500
GPS센서0.236NaN0.4080.000NaN1.0001.0001.0001.000
시정계1.0001.0001.0001.000NaN1.0001.0001.0001.000
신축변위계0.0000.0000.0001.000NaN0.5001.0001.0001.000
2023-12-13T03:32:05.796244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번가속도계경사계케이블가속도계동적변형률계온도계처짐계지진계신축변위계하중계GPS센서정적변형률계시정계2D풍향풍속계3D풍향풍속계
순번1.000-0.1520.107-0.115-0.257-0.3230.0000.0000.302NaN0.7750.0001.0000.0000.126
가속도계-0.1521.0000.4420.0370.657-0.0440.0000.2300.000NaN0.2470.0001.0000.5650.000
경사계0.1070.4421.0000.6080.6710.1630.4170.5330.000NaN0.0000.0001.0000.0000.000
케이블가속도계-0.1150.0370.6081.000-0.0870.1960.0000.2520.000NaN0.3161.0001.0000.0000.372
동적변형률계-0.2570.6570.671-0.0871.0000.4640.5770.0000.707NaNNaN1.0001.0000.8160.000
온도계-0.323-0.0440.1630.1960.4641.0000.1720.0000.826NaN0.0000.2501.0000.4760.200
처짐계0.0000.0000.4170.0000.5770.1721.0000.0000.000NaNNaN0.5771.0000.0000.000
지진계0.0000.2300.5330.2520.0000.0000.0001.0000.000NaN0.4080.0001.0000.3290.000
신축변위계0.3020.0000.0000.0000.7070.8260.0000.0001.000NaN1.0000.5001.0001.0000.000
하중계NaNNaNNaNNaNNaNNaNNaNNaNNaN1.0000.000NaNNaNNaNNaN
GPS센서0.7750.2470.0000.316NaN0.000NaN0.4081.0000.0001.0001.0001.0000.0000.236
정적변형률계0.0000.0000.0001.0001.0000.2500.5770.0000.500NaN1.0001.0001.0000.0000.500
시정계1.0001.0001.0001.0001.0001.0001.0001.0001.000NaN1.0001.0001.0001.0001.000
2D풍향풍속계0.0000.5650.0000.0000.8160.4760.0000.3291.000NaN0.0000.0001.0001.0000.102
3D풍향풍속계0.1260.0000.0000.3720.0000.2000.0000.0000.000NaN0.2360.5001.0000.1021.000

Missing values

2023-12-13T03:31:59.667850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:31:59.984540image/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.
2023-12-13T03:32:00.172343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

순번형식교량명가속도계경사계케이블가속도계처짐계동적변형률계지진계신축변위계하중계GPS센서정적변형률계온도계시정계2D풍향풍속계3D풍향풍속계
01사장교진도대교1215<NA>682<NA>31627112
12사장교제2진도대교44171<NA><NA>2<NA>31415<NA><NA>2
23사장교동강대교7141<NA>22<NA><NA>1318<NA><NA>1
34사장교거금대교44312682<NA><NA><NA>3112<NA>
45사장교거북선대교7111<NA>92<NA><NA><NA>111<NA>
56사장교완도대교2473884<NA><NA>3243<NA><NA>2
67사장교목포대교14923124724<NA>827121
78사장교서안동대교13673<NA><NA>2<NA><NA><NA>13<NA>21
89사장교동이대교2<NA>71<NA>82<NA><NA><NA>7<NA>11
910사장교영광대교12111<NA>72<NA><NA><NA>19<NA>21
순번형식교량명가속도계경사계케이블가속도계처짐계동적변형률계지진계신축변위계하중계GPS센서정적변형률계온도계시정계2D풍향풍속계3D풍향풍속계
1415사장교장자교2231<NA>72<NA><NA><NA>17<NA>12
1516사장교세풍대교2<NA>10<NA><NA>92<NA>3<NA>6<NA>11
1617사장교천사대교16<NA>9<NA><NA>72<NA>3<NA>22121
1718사장교삼천포대교88253<NA>92<NA><NA><NA>5<NA><NA>2
1819사장교화양조발대교3<NA>6<NA><NA>72<NA>1<NA>11<NA>11
1920사장교둔병대교4<NA>6<NA><NA>62<NA>4<NA>17<NA>21
2021사장교칠산대교3<NA>71<NA>82<NA><NA><NA>26121
2122사장교원산안면대교1<NA>31<NA>82<NA><NA><NA>5<NA>11
2223사장교임자1대교327<NA><NA>72<NA>1<NA>15<NA>21
2324사장교임자2대교427<NA><NA>82<NA>1<NA>15<NA>21