Overview

Dataset statistics

Number of variables10
Number of observations65
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.5 KiB
Average record size in memory87.0 B

Variable types

Numeric4
Categorical4
Text2

Dataset

Description계룡시 관내의 현수막 게시대에 관한 데이터로서, 게시대 유형, 게시대 명칭, 위치, 규격, 일반용, 행정용, 형식, 기수에 대한 공공데이터를 제공합니다.
URLhttps://www.data.go.kr/data/15093929/fileData.do

Alerts

규격(단위) is highly overall correlated with 소계 and 5 other fieldsHigh correlation
게시대유형 is highly overall correlated with 연번 and 5 other fieldsHigh correlation
형식 is highly overall correlated with 연번 and 4 other fieldsHigh correlation
연번 is highly overall correlated with 소계 and 2 other fieldsHigh correlation
소계 is highly overall correlated with 연번 and 5 other fieldsHigh correlation
행정용 is highly overall correlated with 게시대유형 and 2 other fieldsHigh correlation
기수 is highly overall correlated with 소계 and 1 other fieldsHigh correlation
일반용 is highly overall correlated with 소계 and 2 other fieldsHigh correlation
연번 has unique valuesUnique
행정용 has 11 (16.9%) zerosZeros

Reproduction

Analysis started2023-12-12 12:12:21.758933
Analysis finished2023-12-12 12:12:24.492183
Duration2.73 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct65
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33
Minimum1
Maximum65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size717.0 B
2023-12-12T21:12:24.598059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.2
Q117
median33
Q349
95-th percentile61.8
Maximum65
Range64
Interquartile range (IQR)32

Descriptive statistics

Standard deviation18.90767
Coefficient of variation (CV)0.57295971
Kurtosis-1.2
Mean33
Median Absolute Deviation (MAD)16
Skewness0
Sum2145
Variance357.5
MonotonicityStrictly increasing
2023-12-12T21:12:24.788902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.5%
50 1
 
1.5%
36 1
 
1.5%
37 1
 
1.5%
38 1
 
1.5%
39 1
 
1.5%
40 1
 
1.5%
41 1
 
1.5%
42 1
 
1.5%
43 1
 
1.5%
Other values (55) 55
84.6%
ValueCountFrequency (%)
1 1
1.5%
2 1
1.5%
3 1
1.5%
4 1
1.5%
5 1
1.5%
6 1
1.5%
7 1
1.5%
8 1
1.5%
9 1
1.5%
10 1
1.5%
ValueCountFrequency (%)
65 1
1.5%
64 1
1.5%
63 1
1.5%
62 1
1.5%
61 1
1.5%
60 1
1.5%
59 1
1.5%
58 1
1.5%
57 1
1.5%
56 1
1.5%

게시대유형
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size652.0 B
5단형
34 
저단형
31 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5단형
2nd row5단형
3rd row5단형
4th row5단형
5th row5단형

Common Values

ValueCountFrequency (%)
5단형 34
52.3%
저단형 31
47.7%

Length

2023-12-12T21:12:24.969763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:12:25.092933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5단형 34
52.3%
저단형 31
47.7%

게시대명칭
Text

Distinct53
Distinct (%)81.5%
Missing0
Missing (%)0.0%
Memory size652.0 B
2023-12-12T21:12:25.357800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length8
Mean length5.4923077
Min length3

Characters and Unicode

Total characters357
Distinct characters111
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)63.1%

Sample

1st row계룡과선교
2nd row포스코아파트
3rd row포스코아파트
4th row계룡IC4가
5th row왕대4가
ValueCountFrequency (%)
4가 6
 
7.2%
정문 4
 
4.8%
3가 4
 
4.8%
기상전대 2
 
2.4%
해군아파트 2
 
2.4%
용남고 2
 
2.4%
포스코 2
 
2.4%
포스코아파트 2
 
2.4%
수변공원 2
 
2.4%
남선교 2
 
2.4%
Other values (48) 55
66.3%
2023-12-12T21:12:25.882364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
가 25
 
7.0%
18
 
5.0%
4 17
 
4.8%
사 12
 
3.4%
리 11
 
3.1%
3 9
 
2.5%
정 9
 
2.5%
@ 9
 
2.5%
교 8
 
2.2%
룡 8
 
2.2%
Other values (101) 231
64.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 298
83.5%
Decimal Number 28
 
7.8%
Space Separator 18
 
5.0%
Other Punctuation 9
 
2.5%
Letter Number 2
 
0.6%
Uppercase Letter 2
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
가 25
 
8.4%
사 12
 
4.0%
리 11
 
3.7%
정 9
 
3.0%
교 8
 
2.7%
룡 8
 
2.7%
계 8
 
2.7%
트 7
 
2.3%
파 7
 
2.3%
아 7
 
2.3%
Other values (92) 196
65.8%
Decimal Number
ValueCountFrequency (%)
4 17
60.7%
3 9
32.1%
2 2
 
7.1%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
50.0%
Ⅱ 1
50.0%
Uppercase Letter
ValueCountFrequency (%)
I 1
50.0%
C 1
50.0%
Space Separator
ValueCountFrequency (%)
18
100.0%
Other Punctuation
ValueCountFrequency (%)
@ 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 298
83.5%
Common 55
 
15.4%
Latin 4
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
가 25
 
8.4%
사 12
 
4.0%
리 11
 
3.7%
정 9
 
3.0%
교 8
 
2.7%
룡 8
 
2.7%
계 8
 
2.7%
트 7
 
2.3%
파 7
 
2.3%
아 7
 
2.3%
Other values (92) 196
65.8%
Common
ValueCountFrequency (%)
18
32.7%
4 17
30.9%
3 9
16.4%
@ 9
16.4%
2 2
 
3.6%
Latin
ValueCountFrequency (%)
Ⅰ 1
25.0%
Ⅱ 1
25.0%
I 1
25.0%
C 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 298
83.5%
ASCII 57
 
16.0%
Number Forms 2
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
가 25
 
8.4%
사 12
 
4.0%
리 11
 
3.7%
정 9
 
3.0%
교 8
 
2.7%
룡 8
 
2.7%
계 8
 
2.7%
트 7
 
2.3%
파 7
 
2.3%
아 7
 
2.3%
Other values (92) 196
65.8%
ASCII
ValueCountFrequency (%)
18
31.6%
4 17
29.8%
3 9
15.8%
@ 9
15.8%
2 2
 
3.5%
I 1
 
1.8%
C 1
 
1.8%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
50.0%
Ⅱ 1
50.0%

위치
Text

Distinct55
Distinct (%)84.6%
Missing0
Missing (%)0.0%
Memory size652.0 B
2023-12-12T21:12:26.196615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length21
Mean length17.707692
Min length15

Characters and Unicode

Total characters1151
Distinct characters43
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

Unique47 ?
Unique (%)72.3%

Sample

1st row충청남도 계룡시 두계리 36-20
2nd row충청남도 계룡시 두계리 62-19
3rd row충청남도 계룡시 두계리 62-31
4th row충청남도 계룡시 왕대리 195-4
5th row충청남도 계룡시 왕대리 240
ValueCountFrequency (%)
충청남도 65
24.4%
계룡시 65
24.4%
금암동 19
 
7.1%
엄사리 16
 
6.0%
남선리 11
 
4.1%
두계리 7
 
2.6%
479 4
 
1.5%
482 4
 
1.5%
1336 3
 
1.1%
1346-1 3
 
1.1%
Other values (59) 69
25.9%
2023-12-12T21:12:26.645316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
201
17.5%
남 78
 
6.8%
계 72
 
6.3%
도 66
 
5.7%
충 65
 
5.6%
청 65
 
5.6%
룡 65
 
5.6%
시 65
 
5.6%
1 56
 
4.9%
리 44
 
3.8%
Other values (33) 374
32.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 659
57.3%
Decimal Number 255
 
22.2%
Space Separator 201
 
17.5%
Dash Punctuation 29
 
2.5%
Other Punctuation 7
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 78
11.8%
계 72
10.9%
도 66
10.0%
충 65
9.9%
청 65
9.9%
룡 65
9.9%
시 65
9.9%
리 44
6.7%
암 20
 
3.0%
금 20
 
3.0%
Other values (20) 99
15.0%
Decimal Number
ValueCountFrequency (%)
1 56
22.0%
2 31
12.2%
4 29
11.4%
6 29
11.4%
3 29
11.4%
5 22
 
8.6%
7 19
 
7.5%
0 16
 
6.3%
9 14
 
5.5%
8 10
 
3.9%
Space Separator
ValueCountFrequency (%)
201
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 659
57.3%
Common 492
42.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 78
11.8%
계 72
10.9%
도 66
10.0%
충 65
9.9%
청 65
9.9%
룡 65
9.9%
시 65
9.9%
리 44
6.7%
암 20
 
3.0%
금 20
 
3.0%
Other values (20) 99
15.0%
Common
ValueCountFrequency (%)
201
40.9%
1 56
 
11.4%
2 31
 
6.3%
4 29
 
5.9%
6 29
 
5.9%
- 29
 
5.9%
3 29
 
5.9%
5 22
 
4.5%
7 19
 
3.9%
0 16
 
3.3%
Other values (3) 31
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 659
57.3%
ASCII 492
42.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
201
40.9%
1 56
 
11.4%
2 31
 
6.3%
4 29
 
5.9%
6 29
 
5.9%
- 29
 
5.9%
3 29
 
5.9%
5 22
 
4.5%
7 19
 
3.9%
0 16
 
3.3%
Other values (3) 31
 
6.3%
Hangul
ValueCountFrequency (%)
남 78
11.8%
계 72
10.9%
도 66
10.0%
충 65
9.9%
청 65
9.9%
룡 65
9.9%
시 65
9.9%
리 44
6.7%
암 20
 
3.0%
금 20
 
3.0%
Other values (20) 99
15.0%

규격(단위)
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)12.3%
Missing0
Missing (%)0.0%
Memory size652.0 B
13m x 0.2m
18 
6.2m x 6.18m
14 
7m x 0.2m
13 
12.5m x 5.8m
12 
18.6m x 5.8m
5 
Other values (3)
3 

Length

Max length12
Median length12
Mean length10.8
Min length9

Unique

Unique3 ?
Unique (%)4.6%

Sample

1st row6.2m x 6.18m
2nd row6.2m x 6.18m
3rd row6.2m x 6.18m
4th row12.5m x 5.8m
5th row6.2m x 6.18m

Common Values

ValueCountFrequency (%)
13m x 0.2m 18
27.7%
6.2m x 6.18m 14
21.5%
7m x 0.2m 13
20.0%
12.5m x 5.8m 12
18.5%
18.6m x 5.8m 5
 
7.7%
6.15m x 5.9m 1
 
1.5%
24.8m x 5.8m 1
 
1.5%
2m x 6.6m 1
 
1.5%

Length

2023-12-12T21:12:26.846856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:12:27.007978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
x 65
33.3%
0.2m 31
15.9%
13m 18
 
9.2%
5.8m 18
 
9.2%
6.2m 14
 
7.2%
6.18m 14
 
7.2%
7m 13
 
6.7%
12.5m 12
 
6.2%
18.6m 5
 
2.6%
6.15m 1
 
0.5%
Other values (4) 4
 
2.1%

소계
Real number (ℝ)

HIGH CORRELATION 

Distinct9
Distinct (%)13.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.2769231
Minimum1
Maximum30
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size717.0 B
2023-12-12T21:12:27.153804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median5
Q310
95-th percentile15
Maximum30
Range29
Interquartile range (IQR)8

Descriptive statistics

Standard deviation5.3165652
Coefficient of variation (CV)0.84700181
Kurtosis4.8101307
Mean6.2769231
Median Absolute Deviation (MAD)3
Skewness1.7451259
Sum408
Variance28.265865
MonotonicityNot monotonic
2023-12-12T21:12:27.268871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
2 18
27.7%
5 13
20.0%
10 12
18.5%
15 7
 
10.8%
1 6
 
9.2%
4 4
 
6.2%
8 3
 
4.6%
30 1
 
1.5%
6 1
 
1.5%
ValueCountFrequency (%)
1 6
 
9.2%
2 18
27.7%
4 4
 
6.2%
5 13
20.0%
6 1
 
1.5%
8 3
 
4.6%
10 12
18.5%
15 7
 
10.8%
30 1
 
1.5%
ValueCountFrequency (%)
30 1
 
1.5%
15 7
 
10.8%
10 12
18.5%
8 3
 
4.6%
6 1
 
1.5%
5 13
20.0%
4 4
 
6.2%
2 18
27.7%
1 6
 
9.2%

일반용
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size652.0 B
0
41 
5
10 
10
8 
15
5 
2
 
1

Length

Max length2
Median length1
Mean length1.2
Min length1

Unique

Unique1 ?
Unique (%)1.5%

Sample

1st row5
2nd row0
3rd row5
4th row10
5th row5

Common Values

ValueCountFrequency (%)
0 41
63.1%
5 10
 
15.4%
10 8
 
12.3%
15 5
 
7.7%
2 1
 
1.5%

Length

2023-12-12T21:12:27.416631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:12:27.546887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 41
63.1%
5 10
 
15.4%
10 8
 
12.3%
15 5
 
7.7%
2 1
 
1.5%

행정용
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct9
Distinct (%)13.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1692308
Minimum0
Maximum15
Zeros11
Zeros (%)16.9%
Negative0
Negative (%)0.0%
Memory size717.0 B
2023-12-12T21:12:27.668315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q35
95-th percentile7.6
Maximum15
Range15
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.6550025
Coefficient of variation (CV)0.83774352
Kurtosis4.7255985
Mean3.1692308
Median Absolute Deviation (MAD)2
Skewness1.4657743
Sum206
Variance7.0490385
MonotonicityNot monotonic
2023-12-12T21:12:27.793668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
5 20
30.8%
2 18
27.7%
0 11
16.9%
1 6
 
9.2%
4 4
 
6.2%
8 3
 
4.6%
3 1
 
1.5%
15 1
 
1.5%
6 1
 
1.5%
ValueCountFrequency (%)
0 11
16.9%
1 6
 
9.2%
2 18
27.7%
3 1
 
1.5%
4 4
 
6.2%
5 20
30.8%
6 1
 
1.5%
8 3
 
4.6%
15 1
 
1.5%
ValueCountFrequency (%)
15 1
 
1.5%
8 3
 
4.6%
6 1
 
1.5%
5 20
30.8%
4 4
 
6.2%
3 1
 
1.5%
2 18
27.7%
1 6
 
9.2%
0 11
16.9%

형식
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Memory size652.0 B
접철식
34 
연립형
18 
단독형
13 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
접철식 34
52.3%
연립형 18
27.7%
단독형 13
 
20.0%

Length

2023-12-12T21:12:27.918782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:12:28.015470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
접철식 34
52.3%
연립형 18
27.7%
단독형 13
 
20.0%

기수
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.8923077
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size717.0 B
2023-12-12T21:12:28.107044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile5.6
Maximum8
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.5321867
Coefficient of variation (CV)0.80969217
Kurtosis7.4588182
Mean1.8923077
Median Absolute Deviation (MAD)0
Skewness2.6336374
Sum123
Variance2.3475962
MonotonicityNot monotonic
2023-12-12T21:12:28.213031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 36
55.4%
2 17
26.2%
3 7
 
10.8%
6 2
 
3.1%
8 2
 
3.1%
4 1
 
1.5%
ValueCountFrequency (%)
1 36
55.4%
2 17
26.2%
3 7
 
10.8%
4 1
 
1.5%
6 2
 
3.1%
8 2
 
3.1%
ValueCountFrequency (%)
8 2
 
3.1%
6 2
 
3.1%
4 1
 
1.5%
3 7
 
10.8%
2 17
26.2%
1 36
55.4%

Interactions

2023-12-12T21:12:23.552965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:12:22.292768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:12:22.652559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:12:23.008886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:12:23.734226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:12:22.373976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:12:22.733516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:12:23.119484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:12:23.902681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:12:22.453664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:12:22.817960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:12:23.253859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:12:24.059109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:12:22.561194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:12:22.905726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:12:23.389297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:12:28.314978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번게시대유형게시대명칭위치규격(단위)소계일반용행정용형식기수
연번1.0000.9990.9580.9370.6410.6270.6840.5320.7940.428
게시대유형0.9991.0000.9720.9351.0000.9700.5880.7371.0000.551
게시대명칭0.9580.9721.0000.9800.9080.9350.7460.9410.7200.955
위치0.9370.9350.9801.0000.5990.8200.9980.0000.0000.299
규격(단위)0.6411.0000.9080.5991.0000.9110.7640.7921.0000.754
소계0.6270.9700.9350.8200.9111.0000.7070.8680.8830.966
일반용0.6840.5880.7460.9980.7640.7071.0000.5020.5290.591
행정용0.5320.7370.9410.0000.7920.8680.5021.0000.7520.769
형식0.7941.0000.7200.0001.0000.8830.5290.7521.0000.679
기수0.4280.5510.9550.2990.7540.9660.5910.7690.6791.000
2023-12-12T21:12:28.452639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
규격(단위)게시대유형일반용형식
규격(단위)1.0000.9510.5920.959
게시대유형0.9511.0000.6920.992
일반용0.5920.6921.0000.459
형식0.9590.9920.4591.000
2023-12-12T21:12:28.557003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번소계행정용기수게시대유형규격(단위)일반용형식
연번1.000-0.727-0.140-0.2650.9060.3640.3330.641
소계-0.7271.0000.3240.7190.8180.7820.5670.577
행정용-0.1400.3241.0000.2480.7300.6220.2980.627
기수-0.2650.7190.2481.0000.3850.5380.4460.354
게시대유형0.9060.8180.7300.3851.0000.9510.6920.992
규격(단위)0.3640.7820.6220.5380.9511.0000.5920.959
일반용0.3330.5670.2980.4460.6920.5921.0000.459
형식0.6410.5770.6270.3540.9920.9590.4591.000

Missing values

2023-12-12T21:12:24.227141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:12:24.422077image/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

연번게시대유형게시대명칭위치규격(단위)소계일반용행정용형식기수
015단형계룡과선교충청남도 계룡시 두계리 36-206.2m x 6.18m1055접철식2
125단형포스코아파트충청남도 계룡시 두계리 62-196.2m x 6.18m505접철식1
235단형포스코아파트충청남도 계룡시 두계리 62-316.2m x 6.18m550접철식1
345단형계룡IC4가충청남도 계룡시 왕대리 195-412.5m x 5.8m15105접철식3
455단형왕대4가충청남도 계룡시 왕대리 2406.2m x 6.18m1055접철식2
565단형광석굴다리충청남도 계룡시 광석리 4466.2m x 6.18m523접철식1
675단형삼진3가충청남도 계룡시 엄사리239-3412.5m x 5.8m10100접철식2
785단형양정과선교충청남도 계룡시 엄사리 산14-112.5m x 5.8m1055접철식2
895단형양정3가Ⅰ충청남도 계룡시 엄사리 454-118.6m x 5.8m15150접철식3
9105단형양정3가Ⅱ충청남도 계룡시 엄사리 223-1312.5m x 5.8m1055접철식2
연번게시대유형게시대명칭위치규격(단위)소계일반용행정용형식기수
5556저단형유림회관4가충청남도 계룡시 금암동 46213m x 0.2m202연립형1
5657저단형유림회관4가충청남도 계룡시 금암동 4627m x 0.2m101단독형1
5758저단형시청 4가충청남도 계룡시 금암동 465, 48213m x 0.2m202연립형1
5859저단형시청 4가충청남도 계룡시 금암동 465, 4827m x 0.2m101단독형1
5960저단형신성2차입구충청남도 계룡시 금암동46513m x 0.2m202연립형1
6061저단형우림@ 정문충청남도 계룡시 금암동 48213m x 0.2m202연립형1
6162저단형금암주공@ 4가충청남도 계룡시 금암동 47913m x 0.2m202연립형1
6263저단형시외버스터미널충청남도 계룡시 금암동 47913m x 0.2m202연립형1
6364저단형리슈빌@충청남도 계룡시 두마면 농소리 10877m x 0.2m202단독형1
6465저단형푸르지오@충청남도 계룡시 두마면 농소리 10877m x 0.2m202단독형2