Overview

Dataset statistics

Number of variables11
Number of observations59
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.3 KiB
Average record size in memory92.2 B

Variable types

Categorical6
Text3
Numeric2

Dataset

Description경기도 의왕시 교통/도로 현수막 지정게시대의 위치, 명칭, 규격, 부착 금액, 용도구분, 위도, 경도 등에 대한 정보입니다.
Author경기도 의왕시
URLhttps://www.data.go.kr/data/15042826/fileData.do

Alerts

규격(센티미터) has constant value ""Constant
데이터기준일자 has constant value ""Constant
부착금액 is highly overall correlated with 용도구분 and 1 other fieldsHigh correlation
용도구분 is highly overall correlated with 부착금액 and 1 other fieldsHigh correlation
위도 is highly overall correlated with 경도 and 1 other fieldsHigh correlation
경도 is highly overall correlated with 위도High correlation
동 is highly overall correlated with 위도High correlation
면수 is highly overall correlated with 용도구분 and 1 other fieldsHigh correlation
게시대명칭 has unique valuesUnique

Reproduction

Analysis started2023-12-12 01:42:15.993078
Analysis finished2023-12-12 01:42:17.799304
Duration1.81 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

동
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)20.3%
Missing0
Missing (%)0.0%
Memory size604.0 B
청계동
17 
부곡동
15 
오전동
8 
고천동
7 
내손 2동
2 
Other values (7)
10 

Length

Max length5
Median length3
Mean length3.4067797
Min length3

Unique

Unique4 ?
Unique (%)6.8%

Sample

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

Common Values

ValueCountFrequency (%)
청계동 17
28.8%
부곡동 15
25.4%
오전동 8
13.6%
고천동 7
11.9%
내손 2동 2
 
3.4%
내손 3동 2
 
3.4%
내손 4동 2
 
3.4%
내손 5동 2
 
3.4%
내손 1동 1
 
1.7%
내손 6동 1
 
1.7%
Other values (2) 2
 
3.4%

Length

2023-12-12T10:42:17.894181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
청계동 17
23.9%
부곡동 15
21.1%
내손 12
16.9%
오전동 8
11.3%
고천동 7
9.9%
2동 2
 
2.8%
3동 2
 
2.8%
4동 2
 
2.8%
5동 2
 
2.8%
1동 1
 
1.4%
Other values (3) 3
 
4.2%

용도구분
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size604.0 B
상업용
27 
상업용/행정용
19 
행정용
13 

Length

Max length7
Median length3
Mean length4.2881356
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row행정용
2nd row상업용
3rd row행정용
4th row행정용
5th row상업용/행정용

Common Values

ValueCountFrequency (%)
상업용 27
45.8%
상업용/행정용 19
32.2%
행정용 13
22.0%

Length

2023-12-12T10:42:18.081862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:42:18.241199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상업용 27
45.8%
상업용/행정용 19
32.2%
행정용 13
22.0%

게시대명칭
Text

UNIQUE 

Distinct59
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size604.0 B
2023-12-12T10:42:18.574096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length15
Mean length11.610169
Min length4

Characters and Unicode

Total characters685
Distinct characters138
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

Unique59 ?
Unique (%)100.0%

Sample

1st row시청 앞
2nd row아름채 입구
3rd row청소년수련관 삼거리
4th row고천사거리
5th row제일모직 앞
ValueCountFrequency (%)
입구 12
 
7.5%
앞 11
 
6.9%
b 10
 
6.2%
a 10
 
6.2%
사거리 9
 
5.6%
옆 7
 
4.4%
삼거리 6
 
3.8%
의왕어린이집 4
 
2.5%
롯데마트 4
 
2.5%
ic 4
 
2.5%
Other values (59) 83
51.9%
2023-12-12T10:42:19.093705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
108
 
15.8%
리 31
 
4.5%
거 29
 
4.2%
사 17
 
2.5%
( 16
 
2.3%
) 16
 
2.3%
교 15
 
2.2%
구 14
 
2.0%
로 13
 
1.9%
삼 13
 
1.9%
Other values (128) 413
60.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 503
73.4%
Space Separator 108
 
15.8%
Uppercase Letter 40
 
5.8%
Open Punctuation 16
 
2.3%
Close Punctuation 16
 
2.3%
Other Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 31
 
6.2%
거 29
 
5.8%
사 17
 
3.4%
교 15
 
3.0%
구 14
 
2.8%
로 13
 
2.6%
삼 13
 
2.6%
트 13
 
2.6%
입 13
 
2.6%
아 12
 
2.4%
Other values (119) 333
66.2%
Uppercase Letter
ValueCountFrequency (%)
B 11
27.5%
A 11
27.5%
C 9
22.5%
I 6
15.0%
D 3
 
7.5%
Space Separator
ValueCountFrequency (%)
108
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 503
73.4%
Common 142
 
20.7%
Latin 40
 
5.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 31
 
6.2%
거 29
 
5.8%
사 17
 
3.4%
교 15
 
3.0%
구 14
 
2.8%
로 13
 
2.6%
삼 13
 
2.6%
트 13
 
2.6%
입 13
 
2.6%
아 12
 
2.4%
Other values (119) 333
66.2%
Latin
ValueCountFrequency (%)
B 11
27.5%
A 11
27.5%
C 9
22.5%
I 6
15.0%
D 3
 
7.5%
Common
ValueCountFrequency (%)
108
76.1%
( 16
 
11.3%
) 16
 
11.3%
, 2
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 503
73.4%
ASCII 182
 
26.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
108
59.3%
( 16
 
8.8%
) 16
 
8.8%
B 11
 
6.0%
A 11
 
6.0%
C 9
 
4.9%
I 6
 
3.3%
D 3
 
1.6%
, 2
 
1.1%
Hangul
ValueCountFrequency (%)
리 31
 
6.2%
거 29
 
5.8%
사 17
 
3.4%
교 15
 
3.0%
구 14
 
2.8%
로 13
 
2.6%
삼 13
 
2.6%
트 13
 
2.6%
입 13
 
2.6%
아 12
 
2.4%
Other values (119) 333
66.2%

부착금액
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size604.0 B
12900
27 
상업용: 12900/행정용: 9900
19 
9900
13 

Length

Max length20
Median length5
Mean length9.6101695
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row9900
2nd row12900
3rd row9900
4th row9900
5th row상업용: 12900/행정용: 9900

Common Values

ValueCountFrequency (%)
12900 27
45.8%
상업용: 12900/행정용: 9900 19
32.2%
9900 13
22.0%

Length

2023-12-12T10:42:19.297177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:42:19.455060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
9900 32
33.0%
12900 27
27.8%
상업용 19
19.6%
12900/행정용 19
19.6%

규격(센티미터)
Categorical

CONSTANT 

Distinct1
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size604.0 B
580 x 70
59 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row580 x 70
2nd row580 x 70
3rd row580 x 70
4th row580 x 70
5th row580 x 70

Common Values

ValueCountFrequency (%)
580 x 70 59
100.0%

Length

2023-12-12T10:42:19.589555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:42:19.706576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
580 59
33.3%
x 59
33.3%
70 59
33.3%

면수
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)18.6%
Missing0
Missing (%)0.0%
Memory size604.0 B
7
18 
6
15 
상업용5/행정용1
5 
상업용6/행정용1
5 
상업용4/행정용2
4 
Other values (6)
12 

Length

Max length9
Median length1
Mean length3.5762712
Min length1

Unique

Unique3 ?
Unique (%)5.1%

Sample

1st row6
2nd row6
3rd row3
4th row3
5th row상업용5/행정용1

Common Values

ValueCountFrequency (%)
7 18
30.5%
6 15
25.4%
상업용5/행정용1 5
 
8.5%
상업용6/행정용1 5
 
8.5%
상업용4/행정용2 4
 
6.8%
3 3
 
5.1%
상업용5/행정용2 3
 
5.1%
5 3
 
5.1%
2 1
 
1.7%
상업용4/행정용3 1
 
1.7%

Length

2023-12-12T10:42:19.848429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
7 18
30.5%
6 15
25.4%
상업용5/행정용1 5
 
8.5%
상업용6/행정용1 5
 
8.5%
상업용4/행정용2 4
 
6.8%
3 3
 
5.1%
상업용5/행정용2 3
 
5.1%
5 3
 
5.1%
2 1
 
1.7%
상업용4/행정용3 1
 
1.7%

게시대 지번주소
Text

Distinct46
Distinct (%)78.0%
Missing0
Missing (%)0.0%
Memory size604.0 B
2023-12-12T10:42:20.164784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length8.9152542
Min length7

Characters and Unicode

Total characters526
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)57.6%

Sample

1st row고천동 182-4
2nd row고천동 85-5
3rd row고천동 103-9
4th row왕곡동 609
5th row고천동 산 11-22
ValueCountFrequency (%)
내손동 12
 
9.7%
포일동 11
 
8.9%
오전동 8
 
6.5%
삼동 7
 
5.6%
산 6
 
4.8%
이동 5
 
4.0%
고천동 4
 
3.2%
청계동 3
 
2.4%
745 3
 
2.4%
월암동 3
 
2.4%
Other values (47) 62
50.0%
2023-12-12T10:42:20.743955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
65
 
12.4%
동 59
 
11.2%
- 47
 
8.9%
1 40
 
7.6%
2 27
 
5.1%
7 26
 
4.9%
4 25
 
4.8%
6 25
 
4.8%
3 24
 
4.6%
8 22
 
4.2%
Other values (22) 166
31.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 243
46.2%
Other Letter 171
32.5%
Space Separator 65
 
12.4%
Dash Punctuation 47
 
8.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 59
34.5%
손 12
 
7.0%
내 12
 
7.0%
일 11
 
6.4%
포 11
 
6.4%
전 8
 
4.7%
오 8
 
4.7%
삼 7
 
4.1%
산 6
 
3.5%
이 5
 
2.9%
Other values (10) 32
18.7%
Decimal Number
ValueCountFrequency (%)
1 40
16.5%
2 27
11.1%
7 26
10.7%
4 25
10.3%
6 25
10.3%
3 24
9.9%
8 22
9.1%
5 20
8.2%
0 18
7.4%
9 16
 
6.6%
Space Separator
ValueCountFrequency (%)
65
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 47
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 355
67.5%
Hangul 171
32.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 59
34.5%
손 12
 
7.0%
내 12
 
7.0%
일 11
 
6.4%
포 11
 
6.4%
전 8
 
4.7%
오 8
 
4.7%
삼 7
 
4.1%
산 6
 
3.5%
이 5
 
2.9%
Other values (10) 32
18.7%
Common
ValueCountFrequency (%)
65
18.3%
- 47
13.2%
1 40
11.3%
2 27
7.6%
7 26
 
7.3%
4 25
 
7.0%
6 25
 
7.0%
3 24
 
6.8%
8 22
 
6.2%
5 20
 
5.6%
Other values (2) 34
9.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 355
67.5%
Hangul 171
32.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
65
18.3%
- 47
13.2%
1 40
11.3%
2 27
7.6%
7 26
 
7.3%
4 25
 
7.0%
6 25
 
7.0%
3 24
 
6.8%
8 22
 
6.2%
5 20
 
5.6%
Other values (2) 34
9.6%
Hangul
ValueCountFrequency (%)
동 59
34.5%
손 12
 
7.0%
내 12
 
7.0%
일 11
 
6.4%
포 11
 
6.4%
전 8
 
4.7%
오 8
 
4.7%
삼 7
 
4.1%
산 6
 
3.5%
이 5
 
2.9%
Other values (10) 32
18.7%

게시대 도로명주소
Text

Distinct53
Distinct (%)89.8%
Missing0
Missing (%)0.0%
Memory size604.0 B
2023-12-12T10:42:21.095863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length7.2542373
Min length5

Characters and Unicode

Total characters428
Distinct characters77
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)83.1%

Sample

1st row시청로 26
2nd row오봉로 27
3rd row오봉로 35
4th row경수대로 200
5th row고산로 49
ValueCountFrequency (%)
오봉로 8
 
6.8%
안양판교로 7
 
5.9%
포일로 4
 
3.4%
모락로 4
 
3.4%
사거리 4
 
3.4%
철도박물관로 4
 
3.4%
계원대학로 3
 
2.5%
48 3
 
2.5%
복지로 3
 
2.5%
사천로 2
 
1.7%
Other values (63) 76
64.4%
2023-12-12T10:42:21.613817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
59
 
13.8%
로 57
 
13.3%
2 24
 
5.6%
4 15
 
3.5%
8 14
 
3.3%
6 13
 
3.0%
3 12
 
2.8%
5 11
 
2.6%
1 11
 
2.6%
9 10
 
2.3%
Other values (67) 202
47.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 240
56.1%
Decimal Number 127
29.7%
Space Separator 59
 
13.8%
Dash Punctuation 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 57
23.8%
오 10
 
4.2%
봉 8
 
3.3%
안 7
 
2.9%
교 7
 
2.9%
판 7
 
2.9%
양 7
 
2.9%
일 7
 
2.9%
대 7
 
2.9%
사 6
 
2.5%
Other values (55) 117
48.8%
Decimal Number
ValueCountFrequency (%)
2 24
18.9%
4 15
11.8%
8 14
11.0%
6 13
10.2%
3 12
9.4%
5 11
8.7%
1 11
8.7%
9 10
7.9%
7 10
7.9%
0 7
 
5.5%
Space Separator
ValueCountFrequency (%)
59
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 240
56.1%
Common 188
43.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 57
23.8%
오 10
 
4.2%
봉 8
 
3.3%
안 7
 
2.9%
교 7
 
2.9%
판 7
 
2.9%
양 7
 
2.9%
일 7
 
2.9%
대 7
 
2.9%
사 6
 
2.5%
Other values (55) 117
48.8%
Common
ValueCountFrequency (%)
59
31.4%
2 24
12.8%
4 15
 
8.0%
8 14
 
7.4%
6 13
 
6.9%
3 12
 
6.4%
5 11
 
5.9%
1 11
 
5.9%
9 10
 
5.3%
7 10
 
5.3%
Other values (2) 9
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 240
56.1%
ASCII 188
43.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
59
31.4%
2 24
12.8%
4 15
 
8.0%
8 14
 
7.4%
6 13
 
6.9%
3 12
 
6.4%
5 11
 
5.9%
1 11
 
5.9%
9 10
 
5.3%
7 10
 
5.3%
Other values (2) 9
 
4.8%
Hangul
ValueCountFrequency (%)
로 57
23.8%
오 10
 
4.2%
봉 8
 
3.3%
안 7
 
2.9%
교 7
 
2.9%
판 7
 
2.9%
양 7
 
2.9%
일 7
 
2.9%
대 7
 
2.9%
사 6
 
2.5%
Other values (55) 117
48.8%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct47
Distinct (%)79.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.361991
Minimum37.305812
Maximum37.396556
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size663.0 B
2023-12-12T10:42:21.786801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.305812
5-th percentile37.315952
Q137.33885
median37.365756
Q337.387501
95-th percentile37.394196
Maximum37.396556
Range0.09074449
Interquartile range (IQR)0.048651835

Descriptive statistics

Standard deviation0.028473306
Coefficient of variation (CV)0.00076209283
Kurtosis-1.1606897
Mean37.361991
Median Absolute Deviation (MAD)0.02297461
Skewness-0.45111865
Sum2204.3575
Variance0.00081072914
MonotonicityNot monotonic
2023-12-12T10:42:21.959511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
37.37952531 3
 
5.1%
37.332993 2
 
3.4%
37.38147139 2
 
3.4%
37.38627463 2
 
3.4%
37.39330404 2
 
3.4%
37.35906082 2
 
3.4%
37.39419609 2
 
3.4%
37.38944839 2
 
3.4%
37.323031 2
 
3.4%
37.334918 2
 
3.4%
Other values (37) 38
64.4%
ValueCountFrequency (%)
37.305812 1
1.7%
37.30592505 1
1.7%
37.306296 1
1.7%
37.317025 1
1.7%
37.318463 1
1.7%
37.320135 1
1.7%
37.323031 2
3.4%
37.323355 1
1.7%
37.32638 1
1.7%
37.332654 1
1.7%
ValueCountFrequency (%)
37.39655649 1
1.7%
37.39647562 1
1.7%
37.39419609 2
3.4%
37.394081 1
1.7%
37.39330404 2
3.4%
37.39261037 1
1.7%
37.392479 1
1.7%
37.392478 1
1.7%
37.39194435 1
1.7%
37.38969051 1
1.7%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct47
Distinct (%)79.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.96625
Minimum126.69177
Maximum127.01345
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size663.0 B
2023-12-12T10:42:22.110698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.69177
5-th percentile126.94811
Q1126.96343
median126.9752
Q3126.98778
95-th percentile127.00351
Maximum127.01345
Range0.321683
Interquartile range (IQR)0.0243508

Descriptive statistics

Standard deviation0.05445359
Coefficient of variation (CV)0.0004288824
Kurtosis21.57564
Mean126.96625
Median Absolute Deviation (MAD)0.0125863
Skewness-4.5082808
Sum7491.0087
Variance0.0029651934
MonotonicityNot monotonic
2023-12-12T10:42:22.307898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
126.9751972 3
 
5.1%
126.95667 2
 
3.4%
126.9747223 2
 
3.4%
126.9785596 2
 
3.4%
126.9877835 2
 
3.4%
126.9660843 2
 
3.4%
126.9881673 2
 
3.4%
126.9944467 2
 
3.4%
126.948357 2
 
3.4%
126.691769 2
 
3.4%
Other values (37) 38
64.4%
ValueCountFrequency (%)
126.691769 2
3.4%
126.945933 1
1.7%
126.948357 2
3.4%
126.94907 1
1.7%
126.950035 1
1.7%
126.950266 1
1.7%
126.955098 1
1.7%
126.956184 1
1.7%
126.95667 2
3.4%
126.958068 1
1.7%
ValueCountFrequency (%)
127.013452 1
1.7%
127.013451 1
1.7%
127.0084492 1
1.7%
127.002965 1
1.7%
126.9989977 1
1.7%
126.9988057 1
1.7%
126.9970554 1
1.7%
126.9958131 1
1.7%
126.9944467 2
3.4%
126.9886193 1
1.7%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size604.0 B
2021-09-15
59 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-09-15
2nd row2021-09-15
3rd row2021-09-15
4th row2021-09-15
5th row2021-09-15

Common Values

ValueCountFrequency (%)
2021-09-15 59
100.0%

Length

2023-12-12T10:42:22.458732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:42:22.612536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-09-15 59
100.0%

Interactions

2023-12-12T10:42:16.881622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:42:16.665349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:42:17.291483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:42:16.760383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T10:42:22.696718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
동용도구분게시대명칭부착금액면수게시대 지번주소게시대 도로명주소위도경도
동1.0000.0001.0000.0000.0000.7801.0000.8480.837
용도구분0.0001.0001.0001.0000.8400.8910.5230.3760.000
게시대명칭1.0001.0001.0001.0001.0001.0001.0001.0001.000
부착금액0.0001.0001.0001.0000.8400.8910.5230.3760.000
면수0.0000.8401.0000.8401.0000.9950.9950.5140.185
게시대 지번주소0.7800.8911.0000.8910.9951.0000.9981.0001.000
게시대 도로명주소1.0000.5231.0000.5230.9950.9981.0001.0001.000
위도0.8480.3761.0000.3760.5141.0001.0001.0000.949
경도0.8370.0001.0000.0000.1851.0001.0000.9491.000
2023-12-12T10:42:22.814799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부착금액동면수용도구분
부착금액1.0000.0000.6801.000
동0.0001.0000.0000.000
면수0.6800.0001.0000.680
용도구분1.0000.0000.6801.000
2023-12-12T10:42:22.910992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도동용도구분부착금액면수
위도1.0000.8680.5590.2230.2230.239
경도0.8681.0000.4900.0000.0000.090
동0.5590.4901.0000.0000.0000.000
용도구분0.2230.0000.0001.0001.0000.680
부착금액0.2230.0000.0001.0001.0000.680
면수0.2390.0900.0000.6800.6801.000

Missing values

2023-12-12T10:42:17.485927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T10:42:17.729925image/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

동용도구분게시대명칭부착금액규격(센티미터)면수게시대 지번주소게시대 도로명주소위도경도데이터기준일자
0고천동행정용시청 앞9900580 x 706고천동 182-4시청로 2637.345196126.9715652021-09-15
1고천동상업용아름채 입구12900580 x 706고천동 85-5오봉로 2737.343529126.972922021-09-15
2고천동행정용청소년수련관 삼거리9900580 x 703고천동 103-9오봉로 3537.342781126.9716222021-09-15
3고천동행정용고천사거리9900580 x 703왕곡동 609경수대로 20037.344593126.976262021-09-15
4고천동상업용/행정용제일모직 앞상업용: 12900/행정용: 9900580 x 70상업용5/행정용1고천동 산 11-22고산로 4937.351528126.9654222021-09-15
5고천동상업용/행정용충무아파트 사거리 A상업용: 12900/행정용: 9900580 x 70상업용6/행정용1왕곡동 610사천로 2437.345557126.977062021-09-15
6고천동상업용/행정용충무아파트 사거리 B상업용: 12900/행정용: 9900580 x 70상업용6/행정용1왕곡동 610사천로 2237.345557126.977062021-09-15
7부곡동상업용/행정용의왕ICD 사거리 A(오봉역)상업용: 12900/행정용: 9900580 x 70상업용6/행정용1이동 387-19오봉로 16937.334918126.6917692021-09-15
8부곡동상업용의왕ICD 사거리 B(오봉역)12900580 x 706이동 387-19오봉로 16937.334918126.6917692021-09-15
9부곡동행정용부곡 IC 입구 교차로 A9900580 x 707이동 289-2오봉로 22637.332654126.9561842021-09-15
동용도구분게시대명칭부착금액규격(센티미터)면수게시대 지번주소게시대 도로명주소위도경도데이터기준일자
49청계동상업용/행정용휴먼시아 입구 삼거리(덕장로 삼거리) B상업용: 12900/행정용: 9900580 x 70상업용5/행정용1포일동 111-20안양판교로 20837.389448126.9944472021-09-15
50청계동상업용북청계 IC 입구12900580 x 706학의동 195-3안양판교로 34937.391944127.0084492021-09-15
51청계동행정용청계동주민센터 앞9900580 x 706포일동 602-76안양판교로 232-637.388638126.9958132021-09-15
52청계동상업용청계체육공원 입구 옆12900580 x 707포일동 127-8백운로 56937.386304126.9970552021-09-15
53청계동상업용교통안전자전거교육장 입구12900580 x 707학의동 340-64의일로 26737.38461126.9988062021-09-15
54청계동상업용교통안전자전거교육장 옆(교각밑)12900580 x 707학의동 243-1의일로 26837.384917126.9989982021-09-15
55청계동상업용/행정용건너말 삼거리(청계사 가는 길)상업용: 12900/행정용: 9900580 x 70상업용6/행정용1청계동 997청계로 6837.394081127.0029652021-09-15
56청계동상업용청계, 판교간 국도 A12900580 x 707청계동 253-46안양판교로 39637.392479127.0134522021-09-15
57청계동상업용청계, 판교간 국도 B12900580 x 706청계동 253-46안양판교로 39437.392478127.0134512021-09-15
58청계동상업용/행정용포일생태습지(에이스청계타워 사거리)상업용: 12900/행정용: 9900580 x 70상업용5/행정용2포일동 679-10포일세거리로 2437.396556126.9862812021-09-15