Overview

Dataset statistics

Number of variables19
Number of observations72
Missing cells51
Missing cells (%)3.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.6 KiB
Average record size in memory164.8 B

Variable types

Categorical12
Text3
Numeric4

Dataset

Description의왕시 현수막지정게시대에 대한 정보를 제공합니다.게시대명,소재지도로명주소,소재지지번주소,위도,경도,현수막규격(너비),현수막규격(높이),게시면수(행정용),부착금액(행정용)에 대한 정보를 포함합니다.
Author경기도 의왕시
URLhttps://www.data.go.kr/data/15090078/fileData.do

Alerts

시군명 has constant value ""Constant
게시대수 has constant value ""Constant
현수막규격(너비) has constant value ""Constant
현수막규격(높이) has constant value ""Constant
관리기관명 has constant value ""Constant
관리기관전화번호 has constant value ""Constant
부착금액(민원수수료) is highly overall correlated with 게시면수(행정용) and 5 other fieldsHigh correlation
부착금액(상업용) is highly overall correlated with 게시면수(행정용) and 5 other fieldsHigh correlation
부착일수 is highly overall correlated with 게시면수(행정용) and 5 other fieldsHigh correlation
부착금액(행정용) is highly overall correlated with 게시면수(행정용) and 5 other fieldsHigh correlation
용도구분 is highly overall correlated with 게시면수(행정용) and 5 other fieldsHigh correlation
위도 is highly overall correlated with 경도 and 1 other fieldsHigh correlation
경도 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
게시면수(행정용) is highly overall correlated with 게시면수(상업용) and 5 other fieldsHigh correlation
게시면수(상업용) is highly overall correlated with 게시면수(행정용) and 5 other fieldsHigh correlation
읍면동명 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
소재지도로명주소 has 31 (43.1%) missing valuesMissing
위도 has 10 (13.9%) missing valuesMissing
경도 has 10 (13.9%) missing valuesMissing
게시대명 has unique valuesUnique
게시면수(행정용) has 29 (40.3%) zerosZeros
게시면수(상업용) has 24 (33.3%) zerosZeros

Reproduction

Analysis started2024-05-04 08:04:44.124075
Analysis finished2024-05-04 08:04:53.206216
Duration9.08 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size708.0 B
의왕시
72 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
의왕시 72
100.0%

Length

2024-05-04T08:04:53.510115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T08:04:53.891997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
의왕시 72
100.0%

읍면동명
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size708.0 B
청계동
23 
부곡동
18 
내손 1동
9 
고천동
8 
오전동
8 

Length

Max length5
Median length3
Mean length3.4166667
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
청계동 23
31.9%
부곡동 18
25.0%
내손 1동 9
 
12.5%
고천동 8
 
11.1%
오전동 8
 
11.1%
내손 2동 6
 
8.3%

Length

2024-05-04T08:04:54.360593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T08:04:54.832855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
청계동 23
26.4%
부곡동 18
20.7%
내손 15
17.2%
1동 9
 
10.3%
고천동 8
 
9.2%
오전동 8
 
9.2%
2동 6
 
6.9%

용도구분
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size708.0 B
상업용
29 
행정용
24 
상업용+행정용
19 

Length

Max length7
Median length3
Mean length4.0555556
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
상업용 29
40.3%
행정용 24
33.3%
상업용+행정용 19
26.4%

Length

2024-05-04T08:04:55.374915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T08:04:55.828697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상업용 29
40.3%
행정용 24
33.3%
상업용+행정용 19
26.4%

게시대명
Text

UNIQUE 

Distinct72
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size708.0 B
2024-05-04T08:04:56.464202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length14
Mean length11.361111
Min length5

Characters and Unicode

Total characters818
Distinct characters139
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

Unique72 ?
Unique (%)100.0%

Sample

1st row시청삼거리 A
2nd row시청삼거리 B
3rd row시청삼거리 C
4th row고천사거리
5th row롯데첨단소재 앞
ValueCountFrequency (%)
b 13
 
7.0%
a 11
 
5.9%
앞 11
 
5.9%
사거리 11
 
5.9%
삼거리 10
 
5.4%
입구 7
 
3.8%
2단 6
 
3.2%
옆 5
 
2.7%
의왕역 4
 
2.2%
의왕어린이집 4
 
2.2%
Other values (73) 103
55.7%
2024-05-04T08:04:57.740883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
113
 
13.8%
리 47
 
5.7%
거 46
 
5.6%
로 26
 
3.2%
교 23
 
2.8%
사 23
 
2.8%
삼 21
 
2.6%
) 17
 
2.1%
( 17
 
2.1%
A 16
 
2.0%
Other values (129) 469
57.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 602
73.6%
Space Separator 113
 
13.8%
Uppercase Letter 52
 
6.4%
Close Punctuation 17
 
2.1%
Open Punctuation 17
 
2.1%
Decimal Number 17
 
2.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 47
 
7.8%
거 46
 
7.6%
로 26
 
4.3%
교 23
 
3.8%
사 23
 
3.8%
삼 21
 
3.5%
왕 14
 
2.3%
앞 13
 
2.2%
의 13
 
2.2%
계 12
 
2.0%
Other values (117) 364
60.5%
Uppercase Letter
ValueCountFrequency (%)
A 16
30.8%
B 15
28.8%
C 11
21.2%
I 7
13.5%
D 3
 
5.8%
Decimal Number
ValueCountFrequency (%)
2 7
41.2%
3 5
29.4%
1 3
17.6%
0 2
 
11.8%
Space Separator
ValueCountFrequency (%)
113
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 602
73.6%
Common 164
 
20.0%
Latin 52
 
6.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 47
 
7.8%
거 46
 
7.6%
로 26
 
4.3%
교 23
 
3.8%
사 23
 
3.8%
삼 21
 
3.5%
왕 14
 
2.3%
앞 13
 
2.2%
의 13
 
2.2%
계 12
 
2.0%
Other values (117) 364
60.5%
Common
ValueCountFrequency (%)
113
68.9%
) 17
 
10.4%
( 17
 
10.4%
2 7
 
4.3%
3 5
 
3.0%
1 3
 
1.8%
0 2
 
1.2%
Latin
ValueCountFrequency (%)
A 16
30.8%
B 15
28.8%
C 11
21.2%
I 7
13.5%
D 3
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 602
73.6%
ASCII 216
 
26.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
113
52.3%
) 17
 
7.9%
( 17
 
7.9%
A 16
 
7.4%
B 15
 
6.9%
C 11
 
5.1%
I 7
 
3.2%
2 7
 
3.2%
3 5
 
2.3%
1 3
 
1.4%
Other values (2) 5
 
2.3%
Hangul
ValueCountFrequency (%)
리 47
 
7.8%
거 46
 
7.6%
로 26
 
4.3%
교 23
 
3.8%
사 23
 
3.8%
삼 21
 
3.5%
왕 14
 
2.3%
앞 13
 
2.2%
의 13
 
2.2%
계 12
 
2.0%
Other values (117) 364
60.5%

소재지도로명주소
Text

MISSING 

Distinct37
Distinct (%)90.2%
Missing31
Missing (%)43.1%
Memory size708.0 B
2024-05-04T08:04:58.303338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length15.463415
Min length13

Characters and Unicode

Total characters634
Distinct characters68
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

Unique33 ?
Unique (%)80.5%

Sample

1st row경기도 의왕시 경수대로 200
2nd row경기도 의왕시 고산로 49
3rd row경기도 의왕시 사천로 24
4th row경기도 의왕시 사천로 22
5th row경기도 의왕시 경수대로 220-2
ValueCountFrequency (%)
경기도 41
25.0%
의왕시 41
25.0%
안양판교로 6
 
3.7%
오봉로 5
 
3.0%
철도박물관로 4
 
2.4%
모락로 3
 
1.8%
복지로 3
 
1.8%
경수대로 3
 
1.8%
48 2
 
1.2%
갈미로 2
 
1.2%
Other values (45) 54
32.9%
2024-05-04T08:04:59.261889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
123
19.4%
도 45
 
7.1%
경 44
 
6.9%
의 43
 
6.8%
왕 41
 
6.5%
시 41
 
6.5%
기 41
 
6.5%
로 40
 
6.3%
2 24
 
3.8%
4 10
 
1.6%
Other values (58) 182
28.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 408
64.4%
Space Separator 123
 
19.4%
Decimal Number 101
 
15.9%
Dash Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 45
11.0%
경 44
10.8%
의 43
10.5%
왕 41
10.0%
시 41
10.0%
기 41
10.0%
로 40
9.8%
양 6
 
1.5%
오 6
 
1.5%
안 6
 
1.5%
Other values (46) 95
23.3%
Decimal Number
ValueCountFrequency (%)
2 24
23.8%
4 10
9.9%
8 10
9.9%
7 9
 
8.9%
9 9
 
8.9%
6 9
 
8.9%
3 8
 
7.9%
0 8
 
7.9%
1 7
 
6.9%
5 7
 
6.9%
Space Separator
ValueCountFrequency (%)
123
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 408
64.4%
Common 226
35.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 45
11.0%
경 44
10.8%
의 43
10.5%
왕 41
10.0%
시 41
10.0%
기 41
10.0%
로 40
9.8%
양 6
 
1.5%
오 6
 
1.5%
안 6
 
1.5%
Other values (46) 95
23.3%
Common
ValueCountFrequency (%)
123
54.4%
2 24
 
10.6%
4 10
 
4.4%
8 10
 
4.4%
7 9
 
4.0%
9 9
 
4.0%
6 9
 
4.0%
3 8
 
3.5%
0 8
 
3.5%
1 7
 
3.1%
Other values (2) 9
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 408
64.4%
ASCII 226
35.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
123
54.4%
2 24
 
10.6%
4 10
 
4.4%
8 10
 
4.4%
7 9
 
4.0%
9 9
 
4.0%
6 9
 
4.0%
3 8
 
3.5%
0 8
 
3.5%
1 7
 
3.1%
Other values (2) 9
 
4.0%
Hangul
ValueCountFrequency (%)
도 45
11.0%
경 44
10.8%
의 43
10.5%
왕 41
10.0%
시 41
10.0%
기 41
10.0%
로 40
9.8%
양 6
 
1.5%
오 6
 
1.5%
안 6
 
1.5%
Other values (46) 95
23.3%

소재지지번주소
Text

Distinct53
Distinct (%)73.6%
Missing0
Missing (%)0.0%
Memory size708.0 B
2024-05-04T08:04:59.976485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length18
Mean length16.902778
Min length14

Characters and Unicode

Total characters1217
Distinct characters38
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

Unique36 ?
Unique (%)50.0%

Sample

1st row경기도 의왕시 고천동 103-9
2nd row경기도 의왕시 고천동 103-9
3rd row경기도 의왕시 고천동 103-9
4th row경기도 의왕시 왕곡동 609
5th row경기도 의왕시 고천동 산 11-22
ValueCountFrequency (%)
경기도 72
24.6%
의왕시 72
24.6%
내손동 15
 
5.1%
포일동 10
 
3.4%
삼동 9
 
3.1%
학의동 8
 
2.7%
오전동 8
 
2.7%
이동 6
 
2.0%
산 5
 
1.7%
청계동 5
 
1.7%
Other values (56) 83
28.3%
2024-05-04T08:05:01.119558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
221
18.2%
의 80
 
6.6%
왕 76
 
6.2%
경 72
 
5.9%
도 72
 
5.9%
시 72
 
5.9%
기 72
 
5.9%
동 72
 
5.9%
1 57
 
4.7%
- 56
 
4.6%
Other values (28) 367
30.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 644
52.9%
Decimal Number 296
24.3%
Space Separator 221
 
18.2%
Dash Punctuation 56
 
4.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 80
12.4%
왕 76
11.8%
경 72
11.2%
도 72
11.2%
시 72
11.2%
기 72
11.2%
동 72
11.2%
손 15
 
2.3%
내 15
 
2.3%
일 10
 
1.6%
Other values (16) 88
13.7%
Decimal Number
ValueCountFrequency (%)
1 57
19.3%
3 32
10.8%
4 32
10.8%
7 28
9.5%
9 28
9.5%
6 26
8.8%
0 25
8.4%
2 25
8.4%
5 23
7.8%
8 20
 
6.8%
Space Separator
ValueCountFrequency (%)
221
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 56
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 644
52.9%
Common 573
47.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 80
12.4%
왕 76
11.8%
경 72
11.2%
도 72
11.2%
시 72
11.2%
기 72
11.2%
동 72
11.2%
손 15
 
2.3%
내 15
 
2.3%
일 10
 
1.6%
Other values (16) 88
13.7%
Common
ValueCountFrequency (%)
221
38.6%
1 57
 
9.9%
- 56
 
9.8%
3 32
 
5.6%
4 32
 
5.6%
7 28
 
4.9%
9 28
 
4.9%
6 26
 
4.5%
0 25
 
4.4%
2 25
 
4.4%
Other values (2) 43
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 644
52.9%
ASCII 573
47.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
221
38.6%
1 57
 
9.9%
- 56
 
9.8%
3 32
 
5.6%
4 32
 
5.6%
7 28
 
4.9%
9 28
 
4.9%
6 26
 
4.5%
0 25
 
4.4%
2 25
 
4.4%
Other values (2) 43
 
7.5%
Hangul
ValueCountFrequency (%)
의 80
12.4%
왕 76
11.8%
경 72
11.2%
도 72
11.2%
시 72
11.2%
기 72
11.2%
동 72
11.2%
손 15
 
2.3%
내 15
 
2.3%
일 10
 
1.6%
Other values (16) 88
13.7%

위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct50
Distinct (%)80.6%
Missing10
Missing (%)13.9%
Infinite0
Infinite (%)0.0%
Mean37.362755
Minimum37.305812
Maximum37.396556
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size780.0 B
2024-05-04T08:05:01.886277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.305812
5-th percentile37.317173
Q137.337337
median37.372753
Q337.388015
95-th percentile37.39419
Maximum37.396556
Range0.090744
Interquartile range (IQR)0.05067861

Descriptive statistics

Standard deviation0.028123223
Coefficient of variation (CV)0.00075270742
Kurtosis-1.0434941
Mean37.362755
Median Absolute Deviation (MAD)0.01945806
Skewness-0.56884328
Sum2316.4908
Variance0.00079091565
MonotonicityNot monotonic
2024-05-04T08:05:02.827258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.379525 3
 
4.2%
37.345558 2
 
2.8%
37.38856548 2
 
2.8%
37.334918 2
 
2.8%
37.332993 2
 
2.8%
37.393304 2
 
2.8%
37.394196 2
 
2.8%
37.323031 2
 
2.8%
37.381471 2
 
2.8%
37.389448 2
 
2.8%
Other values (40) 41
56.9%
(Missing) 10
 
13.9%
ValueCountFrequency (%)
37.305812 1
1.4%
37.305925 1
1.4%
37.306296 1
1.4%
37.317025 1
1.4%
37.31998162 1
1.4%
37.320135 1
1.4%
37.32114835 1
1.4%
37.323031 2
2.8%
37.323355 1
1.4%
37.3263801 1
1.4%
ValueCountFrequency (%)
37.396556 1
1.4%
37.396476 1
1.4%
37.394196 2
2.8%
37.394081 1
1.4%
37.393304 2
2.8%
37.392479 1
1.4%
37.392478 1
1.4%
37.391944 1
1.4%
37.389691 1
1.4%
37.389448 2
2.8%

경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct50
Distinct (%)80.6%
Missing10
Missing (%)13.9%
Infinite0
Infinite (%)0.0%
Mean126.96839
Minimum126.69177
Maximum127.01345
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size780.0 B
2024-05-04T08:05:03.456988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.69177
5-th percentile126.94838
Q1126.9625
median126.9752
Q3126.98817
95-th percentile127.00426
Maximum127.01345
Range0.321683
Interquartile range (IQR)0.02567175

Descriptive statistics

Standard deviation0.053934448
Coefficient of variation (CV)0.0004247864
Kurtosis21.933982
Mean126.96839
Median Absolute Deviation (MAD)0.0133045
Skewness-4.5033947
Sum7872.0405
Variance0.0029089246
MonotonicityNot monotonic
2024-05-04T08:05:04.163958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.975197 3
 
4.2%
126.977061 2
 
2.8%
126.9747835 2
 
2.8%
126.691769 2
 
2.8%
126.9566701 2
 
2.8%
126.987784 2
 
2.8%
126.988167 2
 
2.8%
126.948357 2
 
2.8%
126.974722 2
 
2.8%
126.994447 2
 
2.8%
Other values (40) 41
56.9%
(Missing) 10
 
13.9%
ValueCountFrequency (%)
126.691769 2
2.8%
126.948357 2
2.8%
126.9487625 1
1.4%
126.9490701 1
1.4%
126.950035 1
1.4%
126.950266 1
1.4%
126.9539801 1
1.4%
126.955098 1
1.4%
126.9566701 2
2.8%
126.958068 1
1.4%
ValueCountFrequency (%)
127.013452 1
1.4%
127.013451 1
1.4%
127.008449 1
1.4%
127.0042819 1
1.4%
127.0038303 1
1.4%
127.002965 1
1.4%
127.0022836 1
1.4%
127.0017192 1
1.4%
126.9990316 1
1.4%
126.998998 1
1.4%

게시대수
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size708.0 B
1
72 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 72
100.0%

Length

2024-05-04T08:05:04.852924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T08:05:05.288319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 72
100.0%

현수막규격(너비)
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size708.0 B
580
72 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
580 72
100.0%

Length

2024-05-04T08:05:05.759722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T08:05:06.135978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
580 72
100.0%

현수막규격(높이)
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size708.0 B
70
72 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row70
2nd row70
3rd row70
4th row70
5th row70

Common Values

ValueCountFrequency (%)
70 72
100.0%

Length

2024-05-04T08:05:06.627824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T08:05:06.954440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
70 72
100.0%

게시면수(행정용)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct8
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.75
Minimum0
Maximum7
Zeros29
Zeros (%)40.3%
Negative0
Negative (%)0.0%
Memory size780.0 B
2024-05-04T08:05:07.362109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32.25
95-th percentile7
Maximum7
Range7
Interquartile range (IQR)2.25

Descriptive statistics

Standard deviation2.1213203
Coefficient of variation (CV)1.2121831
Kurtosis0.82941708
Mean1.75
Median Absolute Deviation (MAD)1
Skewness1.3123447
Sum126
Variance4.5
MonotonicityNot monotonic
2024-05-04T08:05:07.717463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 29
40.3%
2 14
19.4%
1 11
 
15.3%
3 7
 
9.7%
7 5
 
6.9%
6 3
 
4.2%
4 2
 
2.8%
5 1
 
1.4%
ValueCountFrequency (%)
0 29
40.3%
1 11
 
15.3%
2 14
19.4%
3 7
 
9.7%
4 2
 
2.8%
5 1
 
1.4%
6 3
 
4.2%
7 5
 
6.9%
ValueCountFrequency (%)
7 5
 
6.9%
6 3
 
4.2%
5 1
 
1.4%
4 2
 
2.8%
3 7
 
9.7%
2 14
19.4%
1 11
 
15.3%
0 29
40.3%

게시면수(상업용)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct6
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.7638889
Minimum0
Maximum7
Zeros24
Zeros (%)33.3%
Negative0
Negative (%)0.0%
Memory size780.0 B
2024-05-04T08:05:08.143713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q36
95-th percentile7
Maximum7
Range7
Interquartile range (IQR)6

Descriptive statistics

Standard deviation2.8259016
Coefficient of variation (CV)0.75079305
Kurtosis-1.5392357
Mean3.7638889
Median Absolute Deviation (MAD)2
Skewness-0.4226874
Sum271
Variance7.9857199
MonotonicityNot monotonic
2024-05-04T08:05:08.529900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 24
33.3%
6 14
19.4%
5 13
18.1%
7 13
18.1%
4 7
 
9.7%
3 1
 
1.4%
ValueCountFrequency (%)
0 24
33.3%
3 1
 
1.4%
4 7
 
9.7%
5 13
18.1%
6 14
19.4%
7 13
18.1%
ValueCountFrequency (%)
7 13
18.1%
6 14
19.4%
5 13
18.1%
4 7
 
9.7%
3 1
 
1.4%
0 24
33.3%

부착일수
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size708.0 B
7
48 
0
24 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row7
2nd row0
3rd row0
4th row0
5th row7

Common Values

ValueCountFrequency (%)
7 48
66.7%
0 24
33.3%

Length

2024-05-04T08:05:09.030101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T08:05:09.461731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
7 48
66.7%
0 24
33.3%

부착금액(행정용)
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size708.0 B
9900
43 
0
29 

Length

Max length4
Median length4
Mean length2.7916667
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row9900
3rd row9900
4th row9900
5th row9900

Common Values

ValueCountFrequency (%)
9900 43
59.7%
0 29
40.3%

Length

2024-05-04T08:05:10.018842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T08:05:10.435833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
9900 43
59.7%
0 29
40.3%

부착금액(상업용)
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size708.0 B
12900
48 
0
24 

Length

Max length5
Median length5
Mean length3.6666667
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row12900
2nd row0
3rd row0
4th row0
5th row12900

Common Values

ValueCountFrequency (%)
12900 48
66.7%
0 24
33.3%

Length

2024-05-04T08:05:10.885372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T08:05:11.262005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
12900 48
66.7%
0 24
33.3%

부착금액(민원수수료)
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size708.0 B
3000
48 
0
24 

Length

Max length4
Median length4
Mean length3
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3000
2nd row0
3rd row0
4th row0
5th row3000

Common Values

ValueCountFrequency (%)
3000 48
66.7%
0 24
33.3%

Length

2024-05-04T08:05:11.700927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T08:05:12.089320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3000 48
66.7%
0 24
33.3%

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size708.0 B
경기도옥외광고협회 의왕시지부
72 

Length

Max length15
Median length15
Mean length15
Min length15

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기도옥외광고협회 의왕시지부
2nd row경기도옥외광고협회 의왕시지부
3rd row경기도옥외광고협회 의왕시지부
4th row경기도옥외광고협회 의왕시지부
5th row경기도옥외광고협회 의왕시지부

Common Values

ValueCountFrequency (%)
경기도옥외광고협회 의왕시지부 72
100.0%

Length

2024-05-04T08:05:12.588960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T08:05:13.030537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도옥외광고협회 72
50.0%
의왕시지부 72
50.0%

관리기관전화번호
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size708.0 B
031-458-8808
72 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row031-458-8808
2nd row031-458-8808
3rd row031-458-8808
4th row031-458-8808
5th row031-458-8808

Common Values

ValueCountFrequency (%)
031-458-8808 72
100.0%

Length

2024-05-04T08:05:13.496723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T08:05:13.832846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
031-458-8808 72
100.0%

Interactions

2024-05-04T08:04:49.613049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:04:46.246437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:04:47.285643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:04:48.314356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:04:49.932162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:04:46.562829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:04:47.532337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:04:48.556806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:04:50.278951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:04:46.790049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:04:47.795719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:04:48.826745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:04:50.608656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:04:47.027866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:04:48.055123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:04:49.315131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-04T08:05:14.078065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동명용도구분게시대명소재지도로명주소소재지지번주소위도경도게시면수(행정용)게시면수(상업용)부착일수부착금액(행정용)부착금액(상업용)부착금액(민원수수료)
읍면동명1.0000.3661.0001.0001.0000.8620.7350.2350.0000.0000.4180.0000.000
용도구분0.3661.0001.0000.8070.9050.2030.0000.8710.9821.0001.0001.0001.000
게시대명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지도로명주소1.0000.8071.0001.0001.0001.0001.0000.8970.9190.6350.5270.6350.635
소재지지번주소1.0000.9051.0001.0001.0001.0001.0000.7520.9400.7100.6580.7100.710
위도0.8620.2031.0001.0001.0001.0000.9070.0000.1770.0000.4090.0000.000
경도0.7350.0001.0001.0001.0000.9071.0000.0000.0000.0000.0000.0000.000
게시면수(행정용)0.2350.8711.0000.8970.7520.0000.0001.0000.7230.9230.9960.9230.923
게시면수(상업용)0.0000.9821.0000.9190.9400.1770.0000.7231.0000.9950.9300.9950.995
부착일수0.0001.0001.0000.6350.7100.0000.0000.9230.9951.0000.7520.9990.999
부착금액(행정용)0.4181.0001.0000.5270.6580.4090.0000.9960.9300.7521.0000.7520.752
부착금액(상업용)0.0001.0001.0000.6350.7100.0000.0000.9230.9950.9990.7521.0000.999
부착금액(민원수수료)0.0001.0001.0000.6350.7100.0000.0000.9230.9950.9990.7520.9991.000
2024-05-04T08:05:14.576474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부착금액(민원수수료)부착금액(상업용)읍면동명부착일수부착금액(행정용)용도구분
부착금액(민원수수료)1.0000.9680.0000.9680.5420.993
부착금액(상업용)0.9681.0000.0000.9680.5420.993
읍면동명0.0000.0001.0000.0000.2910.156
부착일수0.9680.9680.0001.0000.5420.993
부착금액(행정용)0.5420.5420.2910.5421.0000.993
용도구분0.9930.9930.1560.9930.9931.000
2024-05-04T08:05:15.010092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도게시면수(행정용)게시면수(상업용)읍면동명용도구분부착일수부착금액(행정용)부착금액(상업용)부착금액(민원수수료)
위도1.0000.773-0.1650.1840.6590.1050.0000.2890.0000.000
경도0.7731.000-0.0940.0560.5600.0000.0000.0000.0000.000
게시면수(행정용)-0.165-0.0941.000-0.8910.1250.8040.7250.9000.7250.725
게시면수(상업용)0.1840.056-0.8911.0000.0000.8160.9080.7410.9080.908
읍면동명0.6590.5600.1250.0001.0000.1560.0000.2910.0000.000
용도구분0.1050.0000.8040.8160.1561.0000.9930.9930.9930.993
부착일수0.0000.0000.7250.9080.0000.9931.0000.5420.9680.968
부착금액(행정용)0.2890.0000.9000.7410.2910.9930.5421.0000.5420.542
부착금액(상업용)0.0000.0000.7250.9080.0000.9930.9680.5421.0000.968
부착금액(민원수수료)0.0000.0000.7250.9080.0000.9930.9680.5420.9681.000

Missing values

2024-05-04T08:04:51.197091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-04T08:04:52.203869image/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.
2024-05-04T08:04:52.999801image/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

시군명읍면동명용도구분게시대명소재지도로명주소소재지지번주소위도경도게시대수현수막규격(너비)현수막규격(높이)게시면수(행정용)게시면수(상업용)부착일수부착금액(행정용)부착금액(상업용)부착금액(민원수수료)관리기관명관리기관전화번호
0의왕시고천동상업용시청삼거리 A<NA>경기도 의왕시 고천동 103-9<NA><NA>1580700670129003000경기도옥외광고협회 의왕시지부031-458-8808
1의왕시고천동행정용시청삼거리 B<NA>경기도 의왕시 고천동 103-9<NA><NA>158070300990000경기도옥외광고협회 의왕시지부031-458-8808
2의왕시고천동행정용시청삼거리 C<NA>경기도 의왕시 고천동 103-9<NA><NA>158070600990000경기도옥외광고협회 의왕시지부031-458-8808
3의왕시고천동행정용고천사거리경기도 의왕시 경수대로 200경기도 의왕시 왕곡동 60937.344593126.97626158070300990000경기도옥외광고협회 의왕시지부031-458-8808
4의왕시고천동상업용+행정용롯데첨단소재 앞경기도 의왕시 고산로 49경기도 의왕시 고천동 산 11-2237.351528126.9654221580701579900129003000경기도옥외광고협회 의왕시지부031-458-8808
5의왕시고천동상업용+행정용인스빌아파트 사거리 A경기도 의왕시 사천로 24경기도 의왕시 왕곡동 61037.345558126.9770611580701579900129003000경기도옥외광고협회 의왕시지부031-458-8808
6의왕시고천동상업용+행정용인스빌아파트 사거리 B경기도 의왕시 사천로 22경기도 의왕시 왕곡동 61037.345558126.9770611580701579900129003000경기도옥외광고협회 의왕시지부031-458-8808
7의왕시고천동행정용고천사거리 2단경기도 의왕시 경수대로 220-2경기도 의왕시 왕곡동 61137.346419126.975269158070200990000경기도옥외광고협회 의왕시지부031-458-8808
8의왕시부곡동상업용+행정용의왕ICD 사거리 A(오봉역)경기도 의왕시 오봉로 169경기도 의왕시 이동 387-1937.334918126.6917691580701579900129003000경기도옥외광고협회 의왕시지부031-458-8808
9의왕시부곡동상업용의왕ICD 사거리 B(오봉역)경기도 의왕시 오봉로 169경기도 의왕시 이동 387-1937.334918126.6917691580700670129003000경기도옥외광고협회 의왕시지부031-458-8808
시군명읍면동명용도구분게시대명소재지도로명주소소재지지번주소위도경도게시대수현수막규격(너비)현수막규격(높이)게시면수(행정용)게시면수(상업용)부착일수부착금액(행정용)부착금액(상업용)부착금액(민원수수료)관리기관명관리기관전화번호
62의왕시청계동상업용새터말 삼거리 A(안양판교로)경기도 의왕시 안양판교로 396경기도 의왕시 청계동 253-4637.392479127.0134521580700770129003000경기도옥외광고협회 의왕시지부031-458-8808
63의왕시청계동상업용새터말 삼거리 B경기도 의왕시 안양판교로 394경기도 의왕시 청계동 253-4637.392478127.0134511580700670129003000경기도옥외광고협회 의왕시지부031-458-8808
64의왕시청계동상업용+행정용포일숲속마을A 1단지 정문 사거리경기도 의왕시 포일세거리로 24경기도 의왕시 포일동 679-1037.396556126.9862811580701579900129003000경기도옥외광고협회 의왕시지부031-458-8808
65의왕시청계동행정용효성해링턴 203동 앞 삼거리<NA>경기도 의왕시 학의동 689-737.372005127.004282158070400990000경기도옥외광고협회 의왕시지부031-458-8808
66의왕시청계동상업용백운호수 청계IC 삼거리<NA>경기도 의왕시 학의동 916-137.369807127.0022841580700470129003000경기도옥외광고협회 의왕시지부031-458-8808
67의왕시청계동상업용오링개제3교 앞 사거리<NA>경기도 의왕시 학의동 915-837.368752127.0017191580700470129003000경기도옥외광고협회 의왕시지부031-458-8808
68의왕시청계동상업용+행정용교통안전자전거교육장 B<NA>경기도 의왕시 학의동 340-937.384304126.9990321580702479900129003000경기도옥외광고협회 의왕시지부031-458-8808
69의왕시청계동행정용백운로사거리전복촌앞 2단<NA>경기도 의왕시 학의동 697-137.373501127.00383158070200990000경기도옥외광고협회 의왕시지부031-458-8808
70의왕시청계동행정용청계교삼거리 3단 A<NA>경기도 의왕시 청계동 993<NA><NA>158070300990000경기도옥외광고협회 의왕시지부031-458-8808
71의왕시청계동행정용청계교삼거리 3단 B<NA>경기도 의왕시 청계동 993<NA><NA>158070300990000경기도옥외광고협회 의왕시지부031-458-8808