Overview

Dataset statistics

Number of variables17
Number of observations70
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.8 KiB
Average record size in memory142.9 B

Variable types

Categorical11
Text3
Numeric3

Dataset

Description경기도 의왕시 그늘막 현황 정보입니다.설치장소명, 도로명주소, 지번주소, 설치일시, 전체높이, 펼침지름에 대한 정보를 제공합니다.
Author경기도 의왕시
URLhttps://www.data.go.kr/data/15038905/fileData.do

Alerts

기준년도 has constant value ""Constant
시군명 has constant value ""Constant
당해년도운영시작일자 has constant value ""Constant
당해년도운영종료일자 has constant value ""Constant
관리기관명 has constant value ""Constant
관리기관전화번호 has constant value ""Constant
높이 is highly overall correlated with 펼침지름 and 2 other fieldsHigh correlation
원단 is highly overall correlated with 펼침지름 and 1 other fieldsHigh correlation
펼침지름 is highly overall correlated with 설치일자 and 2 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
읍면동명 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
설치일자 is highly overall correlated with 펼침지름 and 1 other fieldsHigh correlation
소재지도로명주소 is highly imbalanced (64.3%)Imbalance
관리번호 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique

Reproduction

Analysis started2024-04-29 22:28:20.090869
Analysis finished2024-04-29 22:28:23.523451
Duration3.43 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size692.0 B
2024
70 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024
2nd row2024
3rd row2024
4th row2024
5th row2024

Common Values

ValueCountFrequency (%)
2024 70
100.0%

Length

2024-04-30T07:28:23.595549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T07:28:23.697049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024 70
100.0%

시군명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size692.0 B
의왕시
70 

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 70
100.0%

Length

2024-04-30T07:28:23.800766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T07:28:23.901466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
의왕시 70
100.0%

읍면동명
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Memory size692.0 B
청계동
26 
고천동
13 
내손2동
10 
부곡동
8 
오전동
8 

Length

Max length4
Median length3
Mean length3.2142857
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
청계동 26
37.1%
고천동 13
18.6%
내손2동 10
 
14.3%
부곡동 8
 
11.4%
오전동 8
 
11.4%
내손1동 5
 
7.1%

Length

2024-04-30T07:28:23.999884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T07:28:24.118630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
청계동 26
37.1%
고천동 13
18.6%
내손2동 10
 
14.3%
부곡동 8
 
11.4%
오전동 8
 
11.4%
내손1동 5
 
7.1%

관리번호
Text

UNIQUE 

Distinct70
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size692.0 B
2024-04-30T07:28:24.384397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length2
Mean length2.1571429
Min length1

Characters and Unicode

Total characters151
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique70 ?
Unique (%)100.0%

Sample

1st row2
2nd row10
3rd row17
4th row18
5th row37
ValueCountFrequency (%)
2 1
 
1.4%
58 1
 
1.4%
32 1
 
1.4%
31 1
 
1.4%
30 1
 
1.4%
29 1
 
1.4%
21 1
 
1.4%
42 1
 
1.4%
50 1
 
1.4%
34 1
 
1.4%
Other values (60) 60
85.7%
2024-04-30T07:28:24.767412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 18
11.9%
1 18
11.9%
3 18
11.9%
6 16
10.6%
5 16
10.6%
4 13
8.6%
8 7
 
4.6%
7 7
 
4.6%
0 7
 
4.6%
9 7
 
4.6%
Other values (6) 24
15.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 127
84.1%
Other Letter 20
 
13.2%
Dash Punctuation 4
 
2.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 18
14.2%
1 18
14.2%
3 18
14.2%
6 16
12.6%
5 16
12.6%
4 13
10.2%
8 7
 
5.5%
7 7
 
5.5%
0 7
 
5.5%
9 7
 
5.5%
Other Letter
ValueCountFrequency (%)
중 4
20.0%
앙 4
20.0%
도 4
20.0%
서 4
20.0%
관 4
20.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 131
86.8%
Hangul 20
 
13.2%

Most frequent character per script

Common
ValueCountFrequency (%)
2 18
13.7%
1 18
13.7%
3 18
13.7%
6 16
12.2%
5 16
12.2%
4 13
9.9%
8 7
 
5.3%
7 7
 
5.3%
0 7
 
5.3%
9 7
 
5.3%
Hangul
ValueCountFrequency (%)
중 4
20.0%
앙 4
20.0%
도 4
20.0%
서 4
20.0%
관 4
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 131
86.8%
Hangul 20
 
13.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 18
13.7%
1 18
13.7%
3 18
13.7%
6 16
12.2%
5 16
12.2%
4 13
9.9%
8 7
 
5.3%
7 7
 
5.3%
0 7
 
5.3%
9 7
 
5.3%
Hangul
ValueCountFrequency (%)
중 4
20.0%
앙 4
20.0%
도 4
20.0%
서 4
20.0%
관 4
20.0%

설치장소명
Text

Distinct66
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Memory size692.0 B
2024-04-30T07:28:24.992196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length17.5
Mean length13.214286
Min length5

Characters and Unicode

Total characters925
Distinct characters174
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique64 ?
Unique (%)91.4%

Sample

1st row기업은행 맞은 편
2nd row고천사거리(선경원효A앞)
3rd row왕곡초교사거리 파리바게트 앞
4th row왕곡초교사거리 왕곡초교 앞
5th row고천사거리 횡단보도
ValueCountFrequency (%)
앞 34
 
19.1%
횡단보도 15
 
8.4%
삼거리 5
 
2.8%
중앙도서관 4
 
2.2%
내 4
 
2.2%
교통섬 3
 
1.7%
엘센트로 3
 
1.7%
교차로 3
 
1.7%
모락로사거리 3
 
1.7%
사거리 2
 
1.1%
Other values (92) 102
57.3%
2024-04-30T07:28:25.401624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
113
 
12.2%
앞 45
 
4.9%
리 35
 
3.8%
거 33
 
3.6%
로 29
 
3.1%
사 24
 
2.6%
단 24
 
2.6%
교 20
 
2.2%
도 20
 
2.2%
보 18
 
1.9%
Other values (164) 564
61.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 745
80.5%
Space Separator 113
 
12.2%
Open Punctuation 17
 
1.8%
Close Punctuation 17
 
1.8%
Decimal Number 17
 
1.8%
Uppercase Letter 5
 
0.5%
Dash Punctuation 4
 
0.4%
Lowercase Letter 4
 
0.4%
Other Punctuation 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
앞 45
 
6.0%
리 35
 
4.7%
거 33
 
4.4%
로 29
 
3.9%
사 24
 
3.2%
단 24
 
3.2%
교 20
 
2.7%
도 20
 
2.7%
보 18
 
2.4%
지 18
 
2.4%
Other values (147) 479
64.3%
Decimal Number
ValueCountFrequency (%)
1 9
52.9%
2 6
35.3%
6 1
 
5.9%
0 1
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
A 2
40.0%
G 1
20.0%
L 1
20.0%
E 1
20.0%
Lowercase Letter
ValueCountFrequency (%)
l 1
25.0%
i 1
25.0%
s 1
25.0%
o 1
25.0%
Space Separator
ValueCountFrequency (%)
113
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 745
80.5%
Common 171
 
18.5%
Latin 9
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앞 45
 
6.0%
리 35
 
4.7%
거 33
 
4.4%
로 29
 
3.9%
사 24
 
3.2%
단 24
 
3.2%
교 20
 
2.7%
도 20
 
2.7%
보 18
 
2.4%
지 18
 
2.4%
Other values (147) 479
64.3%
Common
ValueCountFrequency (%)
113
66.1%
( 17
 
9.9%
) 17
 
9.9%
1 9
 
5.3%
2 6
 
3.5%
- 4
 
2.3%
, 3
 
1.8%
6 1
 
0.6%
0 1
 
0.6%
Latin
ValueCountFrequency (%)
A 2
22.2%
l 1
11.1%
i 1
11.1%
s 1
11.1%
o 1
11.1%
G 1
11.1%
L 1
11.1%
E 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 745
80.5%
ASCII 180
 
19.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
113
62.8%
( 17
 
9.4%
) 17
 
9.4%
1 9
 
5.0%
2 6
 
3.3%
- 4
 
2.2%
, 3
 
1.7%
A 2
 
1.1%
l 1
 
0.6%
i 1
 
0.6%
Other values (7) 7
 
3.9%
Hangul
ValueCountFrequency (%)
앞 45
 
6.0%
리 35
 
4.7%
거 33
 
4.4%
로 29
 
3.9%
사 24
 
3.2%
단 24
 
3.2%
교 20
 
2.7%
도 20
 
2.7%
보 18
 
2.4%
지 18
 
2.4%
Other values (147) 479
64.3%

소재지도로명주소
Categorical

IMBALANCE 

Distinct9
Distinct (%)12.9%
Missing0
Missing (%)0.0%
Memory size692.0 B
58 
경기도 의왕시 골우물길 49 (고천동)
 
4
경기도 의왕시 내손순환로 4 (내손동)
 
2
경기도 의왕시 경수대로 220-2 (왕곡동)
 
1
경기도 의왕시 부곡중앙로 51 (삼동)
 
1
Other values (4)
 
4

Length

Max length27
Median length1
Mean length4.8714286
Min length1

Unique

Unique6 ?
Unique (%)8.6%

Sample

1st row
2nd row
3rd row
4th row
5th row경기도 의왕시 경수대로 220-2 (왕곡동)

Common Values

ValueCountFrequency (%)
58
82.9%
경기도 의왕시 골우물길 49 (고천동) 4
 
5.7%
경기도 의왕시 내손순환로 4 (내손동) 2
 
2.9%
경기도 의왕시 경수대로 220-2 (왕곡동) 1
 
1.4%
경기도 의왕시 부곡중앙로 51 (삼동) 1
 
1.4%
경기도 의왕시 내손로 14 (내손동) 1
 
1.4%
경기도 의왕시 복지로 109 (내손동) 1
 
1.4%
경기도 의왕시 안양판교로 227 (청계동) 1
 
1.4%
경기도 의왕시 안양판교로 146 (포일동) 1
 
1.4%

Length

2024-04-30T07:28:25.553127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T07:28:25.669271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 12
20.0%
의왕시 12
20.0%
골우물길 4
 
6.7%
49 4
 
6.7%
고천동 4
 
6.7%
내손동 4
 
6.7%
내손순환로 2
 
3.3%
4 2
 
3.3%
안양판교로 2
 
3.3%
14 1
 
1.7%
Other values (13) 13
21.7%

소재지지번주소
Text

Distinct54
Distinct (%)77.1%
Missing0
Missing (%)0.0%
Memory size692.0 B
2024-04-30T07:28:25.873773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length17.428571
Min length15

Characters and Unicode

Total characters1220
Distinct characters34
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

Unique45 ?
Unique (%)64.3%

Sample

1st row경기도 의왕시 고천동 308-5
2nd row경기도 의왕시 왕곡동 608
3rd row경기도 의왕시 왕곡동 613
4th row경기도 의왕시 왕곡동 613
5th row경기도 의왕시 왕곡동 611
ValueCountFrequency (%)
경기도 70
24.7%
의왕시 70
24.7%
포일동 18
 
6.4%
내손동 15
 
5.3%
고천동 9
 
3.2%
오전동 8
 
2.8%
학의동 7
 
2.5%
삼동 7
 
2.5%
680 5
 
1.8%
159 4
 
1.4%
Other values (56) 70
24.7%
2024-04-30T07:28:26.231163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
283
23.2%
의 77
 
6.3%
왕 74
 
6.1%
경 70
 
5.7%
도 70
 
5.7%
시 70
 
5.7%
기 70
 
5.7%
동 70
 
5.7%
- 46
 
3.8%
1 43
 
3.5%
Other values (24) 347
28.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 625
51.2%
Space Separator 283
23.2%
Decimal Number 266
21.8%
Dash Punctuation 46
 
3.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 77
12.3%
왕 74
11.8%
경 70
11.2%
도 70
11.2%
시 70
11.2%
기 70
11.2%
동 70
11.2%
일 18
 
2.9%
포 18
 
2.9%
내 15
 
2.4%
Other values (12) 73
11.7%
Decimal Number
ValueCountFrequency (%)
1 43
16.2%
8 42
15.8%
4 29
10.9%
5 26
9.8%
6 26
9.8%
3 25
9.4%
7 21
7.9%
0 20
7.5%
9 19
7.1%
2 15
 
5.6%
Space Separator
ValueCountFrequency (%)
283
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 625
51.2%
Common 595
48.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 77
12.3%
왕 74
11.8%
경 70
11.2%
도 70
11.2%
시 70
11.2%
기 70
11.2%
동 70
11.2%
일 18
 
2.9%
포 18
 
2.9%
내 15
 
2.4%
Other values (12) 73
11.7%
Common
ValueCountFrequency (%)
283
47.6%
- 46
 
7.7%
1 43
 
7.2%
8 42
 
7.1%
4 29
 
4.9%
5 26
 
4.4%
6 26
 
4.4%
3 25
 
4.2%
7 21
 
3.5%
0 20
 
3.4%
Other values (2) 34
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 625
51.2%
ASCII 595
48.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
283
47.6%
- 46
 
7.7%
1 43
 
7.2%
8 42
 
7.1%
4 29
 
4.9%
5 26
 
4.4%
6 26
 
4.4%
3 25
 
4.2%
7 21
 
3.5%
0 20
 
3.4%
Other values (2) 34
 
5.7%
Hangul
ValueCountFrequency (%)
의 77
12.3%
왕 74
11.8%
경 70
11.2%
도 70
11.2%
시 70
11.2%
기 70
11.2%
동 70
11.2%
일 18
 
2.9%
포 18
 
2.9%
내 15
 
2.4%
Other values (12) 73
11.7%

설치일자
Categorical

HIGH CORRELATION 

Distinct24
Distinct (%)34.3%
Missing0
Missing (%)0.0%
Memory size692.0 B
2019-08-08
15 
2020-03-24
7 
2017-08-11
7 
2018-08-06
6 
2023-03-31
5 
Other values (19)
30 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique13 ?
Unique (%)18.6%

Sample

1st row2017-08-11
2nd row2018-08-06
3rd row2019-08-08
4th row2019-08-08
5th row2020-03-24

Common Values

ValueCountFrequency (%)
2019-08-08 15
21.4%
2020-03-24 7
10.0%
2017-08-11 7
10.0%
2018-08-06 6
 
8.6%
2023-03-31 5
 
7.1%
2020-03-30 4
 
5.7%
2019-07-29 3
 
4.3%
2021-07-23 3
 
4.3%
2022-07-04 3
 
4.3%
2020-03-20 2
 
2.9%
Other values (14) 15
21.4%

Length

2024-04-30T07:28:26.367372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2019-08-08 15
21.4%
2017-08-11 7
10.0%
2020-03-24 7
10.0%
2018-08-06 6
 
8.6%
2023-03-31 5
 
7.1%
2020-03-30 4
 
5.7%
2021-07-23 3
 
4.3%
2022-07-04 3
 
4.3%
2019-07-29 3
 
4.3%
2020-03-20 2
 
2.9%
Other values (14) 15
21.4%

높이
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size692.0 B
3.65
52 
3.0
18 

Length

Max length4
Median length4
Mean length3.7428571
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3.65
2nd row3.65
3rd row3.65
4th row3.65
5th row3.65

Common Values

ValueCountFrequency (%)
3.65 52
74.3%
3.0 18
 
25.7%

Length

2024-04-30T07:28:26.481242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T07:28:26.584340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3.65 52
74.3%
3.0 18
 
25.7%

펼침지름
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.4314286
Minimum3
Maximum5.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size762.0 B
2024-04-30T07:28:26.696147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile3.5
Q14
median4
Q35
95-th percentile5.4
Maximum5.4
Range2.4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.70248892
Coefficient of variation (CV)0.15852426
Kurtosis-1.2366384
Mean4.4314286
Median Absolute Deviation (MAD)0.5
Skewness0.042144911
Sum310.2
Variance0.49349068
MonotonicityNot monotonic
2024-04-30T07:28:26.816854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
4.0 27
38.6%
5.0 15
21.4%
5.4 14
20.0%
3.5 8
 
11.4%
4.4 4
 
5.7%
3.0 2
 
2.9%
ValueCountFrequency (%)
3.0 2
 
2.9%
3.5 8
 
11.4%
4.0 27
38.6%
4.4 4
 
5.7%
5.0 15
21.4%
5.4 14
20.0%
ValueCountFrequency (%)
5.4 14
20.0%
5.0 15
21.4%
4.4 4
 
5.7%
4.0 27
38.6%
3.5 8
 
11.4%
3.0 2
 
2.9%

원단
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size692.0 B
메쉬
51 
방수
18 
매쉬
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)1.4%

Sample

1st row매쉬
2nd row메쉬
3rd row메쉬
4th row메쉬
5th row메쉬

Common Values

ValueCountFrequency (%)
메쉬 51
72.9%
방수 18
 
25.7%
매쉬 1
 
1.4%

Length

2024-04-30T07:28:26.940984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T07:28:27.052987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
메쉬 51
72.9%
방수 18
 
25.7%
매쉬 1
 
1.4%

위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct70
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.368864
Minimum37.318453
Maximum37.400772
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size762.0 B
2024-04-30T07:28:27.180820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.318453
5-th percentile37.320833
Q137.345608
median37.375613
Q337.390516
95-th percentile37.397478
Maximum37.400772
Range0.0823191
Interquartile range (IQR)0.04490835

Descriptive statistics

Standard deviation0.025549576
Coefficient of variation (CV)0.00068371294
Kurtosis-0.95985801
Mean37.368864
Median Absolute Deviation (MAD)0.0174103
Skewness-0.57356492
Sum2615.8205
Variance0.00065278084
MonotonicityNot monotonic
2024-04-30T07:28:27.320672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.3493984 1
 
1.4%
37.4004333 1
 
1.4%
37.3919196 1
 
1.4%
37.3927731 1
 
1.4%
37.3922204 1
 
1.4%
37.3703722 1
 
1.4%
37.3703743 1
 
1.4%
37.3893426 1
 
1.4%
37.388992 1
 
1.4%
37.3931001 1
 
1.4%
Other values (60) 60
85.7%
ValueCountFrequency (%)
37.3184527 1
1.4%
37.3190375 1
1.4%
37.3191849 1
1.4%
37.3207478 1
1.4%
37.3209374 1
1.4%
37.3209918 1
1.4%
37.3212617 1
1.4%
37.3294115 1
1.4%
37.3422387 1
1.4%
37.3422543 1
1.4%
ValueCountFrequency (%)
37.4007718 1
1.4%
37.4004333 1
1.4%
37.400291 1
1.4%
37.3975798 1
1.4%
37.3973542 1
1.4%
37.3970299 1
1.4%
37.396541 1
1.4%
37.3957305 1
1.4%
37.3957161 1
1.4%
37.3955585 1
1.4%

경도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct70
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.97835
Minimum126.94568
Maximum127.01107
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size762.0 B
2024-04-30T07:28:27.459191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.94568
5-th percentile126.95319
Q1126.96938
median126.97745
Q3126.98656
95-th percentile127.00722
Maximum127.01107
Range0.0653966
Interquartile range (IQR)0.017187025

Descriptive statistics

Standard deviation0.014619595
Coefficient of variation (CV)0.00011513454
Kurtosis0.20193391
Mean126.97835
Median Absolute Deviation (MAD)0.0083531
Skewness0.16546883
Sum8888.4847
Variance0.00021373255
MonotonicityNot monotonic
2024-04-30T07:28:27.603593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.9734933 1
 
1.4%
126.9862051 1
 
1.4%
126.9880395 1
 
1.4%
126.9868249 1
 
1.4%
126.9882856 1
 
1.4%
127.0068299 1
 
1.4%
127.0069637 1
 
1.4%
126.9964269 1
 
1.4%
126.9964334 1
 
1.4%
126.9869288 1
 
1.4%
Other values (60) 60
85.7%
ValueCountFrequency (%)
126.9456783 1
1.4%
126.9487167 1
1.4%
126.9492177 1
1.4%
126.9531069 1
1.4%
126.9532881 1
1.4%
126.9575019 1
1.4%
126.9578026 1
1.4%
126.9578201 1
1.4%
126.9649804 1
1.4%
126.9653434 1
1.4%
ValueCountFrequency (%)
127.0110749 1
1.4%
127.0085782 1
1.4%
127.0077001 1
1.4%
127.0074325 1
1.4%
127.0069637 1
1.4%
127.0068299 1
1.4%
127.003717 1
1.4%
126.9964334 1
1.4%
126.9964269 1
1.4%
126.9882856 1
1.4%

당해년도운영시작일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size692.0 B
2024-05-20
70 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-05-20
2nd row2024-05-20
3rd row2024-05-20
4th row2024-05-20
5th row2024-05-20

Common Values

ValueCountFrequency (%)
2024-05-20 70
100.0%

Length

2024-04-30T07:28:27.968757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T07:28:28.060459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-05-20 70
100.0%

당해년도운영종료일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size692.0 B
2024-09-30
70 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-09-30
2nd row2024-09-30
3rd row2024-09-30
4th row2024-09-30
5th row2024-09-30

Common Values

ValueCountFrequency (%)
2024-09-30 70
100.0%

Length

2024-04-30T07:28:28.145080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T07:28:28.230731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-09-30 70
100.0%

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size692.0 B
의왕시
70 

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 70
100.0%

Length

2024-04-30T07:28:28.323017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T07:28:28.423250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
의왕시 70
100.0%

관리기관전화번호
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size692.0 B
031-345-2917
70 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row031-345-2917
2nd row031-345-2917
3rd row031-345-2917
4th row031-345-2917
5th row031-345-2917

Common Values

ValueCountFrequency (%)
031-345-2917 70
100.0%

Length

2024-04-30T07:28:28.537266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T07:28:28.633031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
031-345-2917 70
100.0%

Interactions

2024-04-30T07:28:22.865955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:28:22.311050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:28:22.603032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:28:22.952452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:28:22.437615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:28:22.690902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:28:23.045152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:28:22.509821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:28:22.769368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-30T07:28:28.699903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동명관리번호설치장소명소재지도로명주소소재지지번주소설치일자높이펼침지름원단위도경도
읍면동명1.0001.0001.0000.5171.0000.5270.4980.5870.4970.9650.834
관리번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
설치장소명1.0001.0001.0001.0001.0000.9940.8260.9960.9781.0001.000
소재지도로명주소0.5171.0001.0001.0001.0000.7750.0000.0000.0000.5700.369
소재지지번주소1.0001.0001.0001.0001.0000.4610.0000.7500.8831.0000.994
설치일자0.5271.0000.9940.7750.4611.0000.9800.9730.7580.6120.676
높이0.4981.0000.8260.0000.0000.9801.0001.0001.0000.4280.535
펼침지름0.5871.0000.9960.0000.7500.9731.0001.0000.9380.4390.341
원단0.4971.0000.9780.0000.8830.7581.0000.9381.0000.2670.311
위도0.9651.0001.0000.5701.0000.6120.4280.4390.2671.0000.930
경도0.8341.0001.0000.3690.9940.6760.5350.3410.3110.9301.000
2024-04-30T07:28:28.821021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치일자높이읍면동명소재지도로명주소원단
설치일자1.0000.7310.1910.3660.405
높이0.7311.0000.3470.0000.993
읍면동명0.1910.3471.0000.2770.228
소재지도로명주소0.3660.0000.2771.0000.000
원단0.4050.9930.2280.0001.000
2024-04-30T07:28:28.917993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
펼침지름위도경도읍면동명소재지도로명주소설치일자높이원단
펼침지름1.0000.2210.1460.2440.0000.6650.9700.682
위도0.2211.0000.7190.8780.2970.2300.3060.151
경도0.1460.7191.0000.6160.1700.2740.3850.181
읍면동명0.2440.8780.6161.0000.2770.1910.3470.228
소재지도로명주소0.0000.2970.1700.2771.0000.3660.0000.000
설치일자0.6650.2300.2740.1910.3661.0000.7310.405
높이0.9700.3060.3850.3470.0000.7311.0000.993
원단0.6820.1510.1810.2280.0000.4050.9931.000

Missing values

2024-04-30T07:28:23.201320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-30T07:28:23.423867image/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

기준년도시군명읍면동명관리번호설치장소명소재지도로명주소소재지지번주소설치일자높이펼침지름원단위도경도당해년도운영시작일자당해년도운영종료일자관리기관명관리기관전화번호
02024의왕시고천동2기업은행 맞은 편경기도 의왕시 고천동 308-52017-08-113.655.0매쉬37.349398126.9734932024-05-202024-09-30의왕시031-345-2917
12024의왕시고천동10고천사거리(선경원효A앞)경기도 의왕시 왕곡동 6082018-08-063.655.0메쉬37.344989126.9761462024-05-202024-09-30의왕시031-345-2917
22024의왕시고천동17왕곡초교사거리 파리바게트 앞경기도 의왕시 왕곡동 6132019-08-083.654.0메쉬37.346221126.9801822024-05-202024-09-30의왕시031-345-2917
32024의왕시고천동18왕곡초교사거리 왕곡초교 앞경기도 의왕시 왕곡동 6132019-08-083.654.0메쉬37.346051126.9800352024-05-202024-09-30의왕시031-345-2917
42024의왕시고천동37고천사거리 횡단보도경기도 의왕시 경수대로 220-2 (왕곡동)경기도 의왕시 왕곡동 6112020-03-243.654.0메쉬37.34546126.9757472024-05-202024-09-30의왕시031-345-2917
52024의왕시고천동63고천사거리(의왕소방서쪽)경기도 의왕시 고천동 233-242023-03-313.653.5메쉬37.344798126.9756032024-05-202024-09-30의왕시031-345-2917
62024의왕시고천동66의왕시보건소 앞 횡단보도경기도 의왕시 고천동 1042023-05-123.653.5메쉬37.343802126.9726782024-05-202024-09-30의왕시031-345-2917
72024의왕시고천동67시청삼거리(의왕보건소쪽)경기도 의왕시 고천동 109-22023-05-193.653.5메쉬37.343303126.97162024-05-202024-09-30의왕시031-345-2917
82024의왕시고천동68아름채노인복지관 앞 횡단보도경기도 의왕시 고천동 182-42023-08-073.653.5메쉬37.3435126.97262024-05-202024-09-30의왕시031-345-2917
92024의왕시고천동중앙도서관-1중앙도서관 내경기도 의왕시 골우물길 49 (고천동)경기도 의왕시 고천동 1592020-03-303.654.0메쉬37.342261126.9693772024-05-202024-09-30의왕시031-345-2917
기준년도시군명읍면동명관리번호설치장소명소재지도로명주소소재지지번주소설치일자높이펼침지름원단위도경도당해년도운영시작일자당해년도운영종료일자관리기관명관리기관전화번호
602024의왕시청계동55에이스청계타워 앞 횡단보도경기도 의왕시 포일동 6802022-03-163.05.4방수37.397354126.9867742024-05-202024-09-30의왕시031-345-2917
612024의왕시청계동56엘센트로 상가 앞 횡단보도경기도 의왕시 포일동 635-142022-07-043.04.4방수37.395716126.9840312024-05-202024-09-30의왕시031-345-2917
622024의왕시청계동57엘센트로 정문삼거리 스마일타워 앞 횡단보도경기도 의왕시 포일동 6802022-07-043.04.4방수37.395558126.984922024-05-202024-09-30의왕시031-345-2917
632024의왕시청계동59바라산로-의일로 교차로 횡단보도경기도 의왕시 학의동 965-472022-09-083.05.4방수37.374813127.0074322024-05-202024-09-30의왕시031-345-2917
642024의왕시청계동60바라산로-백운호수로 교차로 횡단보도경기도 의왕시 학의동 575-12022-09-083.05.4방수37.374358127.0085782024-05-202024-09-30의왕시031-345-2917
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