Overview

Dataset statistics

Number of variables17
Number of observations21
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.0 KiB
Average record size in memory146.3 B

Variable types

Text4
Categorical10
Numeric2
DateTime1

Dataset

Description전라남도 곡성군 그늘막 현황 데이터 정보를 제공합니다 ( 읍면동, 종류, 관리번호, 설치장소명, 도로명주소, 지번주소, 경도, 위도 등 포함하여 제공)
URLhttps://www.data.go.kr/data/15106416/fileData.do

Alerts

시도 has constant value ""Constant
시군구 has constant value ""Constant
원단명 has constant value ""Constant
펼침지름(미터) is highly overall correlated with 읍면동 and 3 other fieldsHigh correlation
관리부서번호 is highly overall correlated with 경도 and 5 other fieldsHigh correlation
읍면동 is highly overall correlated with 경도 and 5 other fieldsHigh correlation
영조물보험 가입여부 is highly overall correlated with 읍면동 and 3 other fieldsHigh correlation
관리부서 is highly overall correlated with 경도 and 5 other fieldsHigh correlation
경도 is highly overall correlated with 위도 and 3 other fieldsHigh correlation
위도 is highly overall correlated with 경도 and 3 other fieldsHigh correlation
종류 is highly overall correlated with 전체높이(미터)High correlation
전체높이(미터) is highly overall correlated with 종류High correlation
펼침지름(미터) is highly imbalanced (65.4%)Imbalance
영조물보험 가입여부 is highly imbalanced (54.6%)Imbalance
연번 has unique valuesUnique
관리번호 has unique valuesUnique
경도 has unique valuesUnique
위도 has unique valuesUnique

Reproduction

Analysis started2023-12-12 00:17:59.023847
Analysis finished2023-12-12 00:18:00.313098
Duration1.29 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-12T09:18:00.424264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters105
Distinct characters13
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

Unique21 ?
Unique (%)100.0%

Sample

1st row곡성-01
2nd row곡성-02
3rd row곡성-03
4th row곡성-04
5th row곡성-05
ValueCountFrequency (%)
곡성-01 1
 
4.8%
곡성-12 1
 
4.8%
곡성-20 1
 
4.8%
곡성-19 1
 
4.8%
곡성-18 1
 
4.8%
곡성-17 1
 
4.8%
곡성-16 1
 
4.8%
곡성-15 1
 
4.8%
곡성-14 1
 
4.8%
곡성-13 1
 
4.8%
Other values (11) 11
52.4%
2023-12-12T09:18:00.701066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
곡 21
20.0%
성 21
20.0%
- 21
20.0%
1 13
12.4%
0 11
10.5%
2 4
 
3.8%
3 2
 
1.9%
4 2
 
1.9%
5 2
 
1.9%
6 2
 
1.9%
Other values (3) 6
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 42
40.0%
Decimal Number 42
40.0%
Dash Punctuation 21
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
31.0%
0 11
26.2%
2 4
 
9.5%
3 2
 
4.8%
4 2
 
4.8%
5 2
 
4.8%
6 2
 
4.8%
7 2
 
4.8%
8 2
 
4.8%
9 2
 
4.8%
Other Letter
ValueCountFrequency (%)
곡 21
50.0%
성 21
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 63
60.0%
Hangul 42
40.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 21
33.3%
1 13
20.6%
0 11
17.5%
2 4
 
6.3%
3 2
 
3.2%
4 2
 
3.2%
5 2
 
3.2%
6 2
 
3.2%
7 2
 
3.2%
8 2
 
3.2%
Hangul
ValueCountFrequency (%)
곡 21
50.0%
성 21
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 63
60.0%
Hangul 42
40.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
곡 21
50.0%
성 21
50.0%
ASCII
ValueCountFrequency (%)
- 21
33.3%
1 13
20.6%
0 11
17.5%
2 4
 
6.3%
3 2
 
3.2%
4 2
 
3.2%
5 2
 
3.2%
6 2
 
3.2%
7 2
 
3.2%
8 2
 
3.2%

시도
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
전라남도
21 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전라남도 21
100.0%

Length

2023-12-12T09:18:00.823153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:18:00.911832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라남도 21
100.0%

시군구
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
곡성군
21 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
곡성군 21
100.0%

Length

2023-12-12T09:18:01.001006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:18:01.093286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
곡성군 21
100.0%

읍면동
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)23.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
곡성읍
15 
오곡면
2 
겸면
2 
옥과면
 
1
오산면
 
1

Length

Max length3
Median length3
Mean length2.9047619
Min length2

Unique

Unique2 ?
Unique (%)9.5%

Sample

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

Common Values

ValueCountFrequency (%)
곡성읍 15
71.4%
오곡면 2
 
9.5%
겸면 2
 
9.5%
옥과면 1
 
4.8%
오산면 1
 
4.8%

Length

2023-12-12T09:18:01.227263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:18:01.354562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
곡성읍 15
71.4%
오곡면 2
 
9.5%
겸면 2
 
9.5%
옥과면 1
 
4.8%
오산면 1
 
4.8%

종류
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
그늘막(고정형)
12 
그늘막(스마트형)
9 

Length

Max length9
Median length8
Mean length8.4285714
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row그늘막(스마트형)
2nd row그늘막(스마트형)
3rd row그늘막(스마트형)
4th row그늘막(스마트형)
5th row그늘막(고정형)

Common Values

ValueCountFrequency (%)
그늘막(고정형) 12
57.1%
그늘막(스마트형) 9
42.9%

Length

2023-12-12T09:18:01.477427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:18:01.614384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
그늘막(고정형 12
57.1%
그늘막(스마트형 9
42.9%

관리번호
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-12T09:18:01.785104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters105
Distinct characters13
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

Unique21 ?
Unique (%)100.0%

Sample

1st row곡성-01
2nd row곡성-02
3rd row곡성-03
4th row곡성-04
5th row곡성-05
ValueCountFrequency (%)
곡성-01 1
 
4.8%
곡성-12 1
 
4.8%
곡성-20 1
 
4.8%
곡성-19 1
 
4.8%
곡성-18 1
 
4.8%
곡성-17 1
 
4.8%
곡성-16 1
 
4.8%
곡성-15 1
 
4.8%
곡성-14 1
 
4.8%
곡성-13 1
 
4.8%
Other values (11) 11
52.4%
2023-12-12T09:18:02.072479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
곡 21
20.0%
성 21
20.0%
- 21
20.0%
1 13
12.4%
0 11
10.5%
2 4
 
3.8%
3 2
 
1.9%
4 2
 
1.9%
5 2
 
1.9%
6 2
 
1.9%
Other values (3) 6
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 42
40.0%
Decimal Number 42
40.0%
Dash Punctuation 21
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
31.0%
0 11
26.2%
2 4
 
9.5%
3 2
 
4.8%
4 2
 
4.8%
5 2
 
4.8%
6 2
 
4.8%
7 2
 
4.8%
8 2
 
4.8%
9 2
 
4.8%
Other Letter
ValueCountFrequency (%)
곡 21
50.0%
성 21
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 63
60.0%
Hangul 42
40.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 21
33.3%
1 13
20.6%
0 11
17.5%
2 4
 
6.3%
3 2
 
3.2%
4 2
 
3.2%
5 2
 
3.2%
6 2
 
3.2%
7 2
 
3.2%
8 2
 
3.2%
Hangul
ValueCountFrequency (%)
곡 21
50.0%
성 21
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 63
60.0%
Hangul 42
40.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
곡 21
50.0%
성 21
50.0%
ASCII
ValueCountFrequency (%)
- 21
33.3%
1 13
20.6%
0 11
17.5%
2 4
 
6.3%
3 2
 
3.2%
4 2
 
3.2%
5 2
 
3.2%
6 2
 
3.2%
7 2
 
3.2%
8 2
 
3.2%

설치장소명
Text

Distinct20
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-12T09:18:02.249480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length16
Mean length12.619048
Min length7

Characters and Unicode

Total characters265
Distinct characters84
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)90.5%

Sample

1st row문화센터 앞 횡단보도
2nd row기차마을 전통시장앞 횡단보도
3rd row영운공원 앞 횡단보도
4th row기차마을 앞 횡단보도
5th row뚝방마켓 주차장 앞 횡단보도
ValueCountFrequency (%)
앞 12
19.7%
횡단보도 11
18.0%
기차마을 3
 
4.9%
내 3
 
4.9%
한마음센터 2
 
3.3%
주차장 2
 
3.3%
인도 2
 
3.3%
곡성역회전사거리 2
 
3.3%
건너편 2
 
3.3%
영운공원 2
 
3.3%
Other values (20) 20
32.8%
2023-12-12T09:18:02.553738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
40
 
15.1%
앞 16
 
6.0%
도 13
 
4.9%
횡 11
 
4.2%
단 11
 
4.2%
보 11
 
4.2%
마 7
 
2.6%
차 6
 
2.3%
리 5
 
1.9%
터 5
 
1.9%
Other values (74) 140
52.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 202
76.2%
Space Separator 40
 
15.1%
Decimal Number 9
 
3.4%
Close Punctuation 4
 
1.5%
Open Punctuation 4
 
1.5%
Lowercase Letter 4
 
1.5%
Uppercase Letter 2
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
앞 16
 
7.9%
도 13
 
6.4%
횡 11
 
5.4%
단 11
 
5.4%
보 11
 
5.4%
마 7
 
3.5%
차 6
 
3.0%
리 5
 
2.5%
터 5
 
2.5%
원 5
 
2.5%
Other values (61) 112
55.4%
Decimal Number
ValueCountFrequency (%)
0 3
33.3%
1 3
33.3%
2 2
22.2%
9 1
 
11.1%
Lowercase Letter
ValueCountFrequency (%)
d 1
25.0%
o 1
25.0%
r 1
25.0%
a 1
25.0%
Uppercase Letter
ValueCountFrequency (%)
P 1
50.0%
C 1
50.0%
Space Separator
ValueCountFrequency (%)
40
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 202
76.2%
Common 57
 
21.5%
Latin 6
 
2.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앞 16
 
7.9%
도 13
 
6.4%
횡 11
 
5.4%
단 11
 
5.4%
보 11
 
5.4%
마 7
 
3.5%
차 6
 
3.0%
리 5
 
2.5%
터 5
 
2.5%
원 5
 
2.5%
Other values (61) 112
55.4%
Common
ValueCountFrequency (%)
40
70.2%
) 4
 
7.0%
( 4
 
7.0%
0 3
 
5.3%
1 3
 
5.3%
2 2
 
3.5%
9 1
 
1.8%
Latin
ValueCountFrequency (%)
d 1
16.7%
o 1
16.7%
r 1
16.7%
a 1
16.7%
P 1
16.7%
C 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 202
76.2%
ASCII 63
 
23.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
40
63.5%
) 4
 
6.3%
( 4
 
6.3%
0 3
 
4.8%
1 3
 
4.8%
2 2
 
3.2%
d 1
 
1.6%
o 1
 
1.6%
r 1
 
1.6%
a 1
 
1.6%
Other values (3) 3
 
4.8%
Hangul
ValueCountFrequency (%)
앞 16
 
7.9%
도 13
 
6.4%
횡 11
 
5.4%
단 11
 
5.4%
보 11
 
5.4%
마 7
 
3.5%
차 6
 
3.0%
리 5
 
2.5%
터 5
 
2.5%
원 5
 
2.5%
Other values (61) 112
55.4%

지번주소
Text

Distinct19
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-12T09:18:02.724831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length23
Mean length21.904762
Min length19

Characters and Unicode

Total characters460
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

Unique17 ?
Unique (%)81.0%

Sample

1st row전라남도 곡성군 곡성읍 209-1
2nd row전라남도 곡성군 곡성읍 읍내리 209-1
3rd row전라남도 곡성군 곡성읍 읍내리 97-2
4th row전라남도 곡성군 곡성읍 읍내리 94-5
5th row전라남도 곡성군 곡성읍 읍내리 127-4
ValueCountFrequency (%)
전라남도 21
20.2%
곡성군 21
20.2%
곡성읍 15
14.4%
읍내리 14
13.5%
127-4 2
 
1.9%
오지리 2
 
1.9%
오곡면 2
 
1.9%
209-1 2
 
1.9%
남양리 2
 
1.9%
겸면 2
 
1.9%
Other values (20) 21
20.2%
2023-12-12T09:18:03.013734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
104
22.6%
곡 38
 
8.3%
성 36
 
7.8%
읍 29
 
6.3%
남 23
 
5.0%
전 21
 
4.6%
도 21
 
4.6%
군 21
 
4.6%
라 21
 
4.6%
리 20
 
4.3%
Other values (24) 126
27.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 268
58.3%
Space Separator 104
 
22.6%
Decimal Number 74
 
16.1%
Dash Punctuation 14
 
3.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
곡 38
14.2%
성 36
13.4%
읍 29
10.8%
남 23
8.6%
전 21
7.8%
도 21
7.8%
군 21
7.8%
라 21
7.8%
리 20
7.5%
내 14
 
5.2%
Other values (12) 24
9.0%
Decimal Number
ValueCountFrequency (%)
2 13
17.6%
1 12
16.2%
0 9
12.2%
9 9
12.2%
4 7
9.5%
3 6
8.1%
6 6
8.1%
7 5
 
6.8%
5 4
 
5.4%
8 3
 
4.1%
Space Separator
ValueCountFrequency (%)
104
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 268
58.3%
Common 192
41.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
곡 38
14.2%
성 36
13.4%
읍 29
10.8%
남 23
8.6%
전 21
7.8%
도 21
7.8%
군 21
7.8%
라 21
7.8%
리 20
7.5%
내 14
 
5.2%
Other values (12) 24
9.0%
Common
ValueCountFrequency (%)
104
54.2%
- 14
 
7.3%
2 13
 
6.8%
1 12
 
6.2%
0 9
 
4.7%
9 9
 
4.7%
4 7
 
3.6%
3 6
 
3.1%
6 6
 
3.1%
7 5
 
2.6%
Other values (2) 7
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 268
58.3%
ASCII 192
41.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
104
54.2%
- 14
 
7.3%
2 13
 
6.8%
1 12
 
6.2%
0 9
 
4.7%
9 9
 
4.7%
4 7
 
3.6%
3 6
 
3.1%
6 6
 
3.1%
7 5
 
2.6%
Other values (2) 7
 
3.6%
Hangul
ValueCountFrequency (%)
곡 38
14.2%
성 36
13.4%
읍 29
10.8%
남 23
8.6%
전 21
7.8%
도 21
7.8%
군 21
7.8%
라 21
7.8%
리 20
7.5%
내 14
 
5.2%
Other values (12) 24
9.0%

경도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.2719
Minimum127.12395
Maximum127.30753
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T09:18:03.121672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.12395
5-th percentile127.14186
Q1127.29373
median127.29733
Q3127.30246
95-th percentile127.30526
Maximum127.30753
Range0.1835876
Interquartile range (IQR)0.0087301

Descriptive statistics

Standard deviation0.060151194
Coefficient of variation (CV)0.00047261959
Kurtosis1.5186463
Mean127.2719
Median Absolute Deviation (MAD)0.004922
Skewness-1.7814948
Sum2672.71
Variance0.0036181662
MonotonicityNot monotonic
2023-12-12T09:18:03.291309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
127.2972109 1
 
4.8%
127.2973328 1
 
4.8%
127.123945 1
 
4.8%
127.1723867 1
 
4.8%
127.1721234 1
 
4.8%
127.1418587 1
 
4.8%
127.3075326 1
 
4.8%
127.3052621 1
 
4.8%
127.3029647 1
 
4.8%
127.2933107 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
127.123945 1
4.8%
127.1418587 1
4.8%
127.1721234 1
4.8%
127.1723867 1
4.8%
127.2933107 1
4.8%
127.2937338 1
4.8%
127.293883 1
4.8%
127.2953097 1
4.8%
127.296812 1
4.8%
127.2972109 1
4.8%
ValueCountFrequency (%)
127.3075326 1
4.8%
127.3052621 1
4.8%
127.3029647 1
4.8%
127.3028642 1
4.8%
127.3027143 1
4.8%
127.3024639 1
4.8%
127.3022548 1
4.8%
127.3020736 1
4.8%
127.3019659 1
4.8%
127.3019526 1
4.8%

위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.277449
Minimum35.256608
Maximum35.28314
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T09:18:03.417009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.256608
5-th percentile35.256627
Q135.278424
median35.279762
Q335.281961
95-th percentile35.283134
Maximum35.28314
Range0.0265317
Interquartile range (IQR)0.0035374

Descriptive statistics

Standard deviation0.007828155
Coefficient of variation (CV)0.00022190253
Kurtosis3.6560275
Mean35.277449
Median Absolute Deviation (MAD)0.0021993
Skewness-2.1337295
Sum740.82642
Variance6.1280011 × 10-5
MonotonicityNot monotonic
2023-12-12T09:18:03.529418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
35.2798983 1
 
4.8%
35.2797619 1
 
4.8%
35.2660666 1
 
4.8%
35.2566272 1
 
4.8%
35.2566081 1
 
4.8%
35.276201 1
 
4.8%
35.2769658 1
 
4.8%
35.2791003 1
 
4.8%
35.2831398 1
 
4.8%
35.2793817 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
35.2566081 1
4.8%
35.2566272 1
4.8%
35.2660666 1
4.8%
35.276201 1
4.8%
35.2769658 1
4.8%
35.2784238 1
4.8%
35.2785516 1
4.8%
35.2791003 1
4.8%
35.2793817 1
4.8%
35.2795127 1
4.8%
ValueCountFrequency (%)
35.2831398 1
4.8%
35.2831339 1
4.8%
35.2823195 1
4.8%
35.282091 1
4.8%
35.2820469 1
4.8%
35.2819612 1
4.8%
35.2819051 1
4.8%
35.2816545 1
4.8%
35.2810694 1
4.8%
35.2798983 1
4.8%

설치일시
Date

Distinct6
Distinct (%)28.6%
Missing0
Missing (%)0.0%
Memory size300.0 B
Minimum2019-08-27 00:00:00
Maximum2022-08-26 00:00:00
2023-12-12T09:18:03.623105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:18:03.713260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)

원단명
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
메쉬
21 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
메쉬 21
100.0%

Length

2023-12-12T09:18:03.806894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:18:03.889449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
메쉬 21
100.0%

전체높이(미터)
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
3.7
13 
3.0
8 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3.0
2nd row3.0
3rd row3.7
4th row3.0
5th row3.7

Common Values

ValueCountFrequency (%)
3.7 13
61.9%
3.0 8
38.1%

Length

2023-12-12T09:18:03.986337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:18:04.073636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3.7 13
61.9%
3.0 8
38.1%

펼침지름(미터)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size300.0 B
5.0
19 
4.4
 
1
3.0
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique2 ?
Unique (%)9.5%

Sample

1st row5.0
2nd row5.0
3rd row5.0
4th row5.0
5th row5.0

Common Values

ValueCountFrequency (%)
5.0 19
90.5%
4.4 1
 
4.8%
3.0 1
 
4.8%

Length

2023-12-12T09:18:04.165217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:18:04.249536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5.0 19
90.5%
4.4 1
 
4.8%
3.0 1
 
4.8%

영조물보험 가입여부
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
O
19 
X
2 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
O 19
90.5%
X 2
 
9.5%

Length

2023-12-12T09:18:04.339432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:18:04.428749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
o 19
90.5%
x 2
 
9.5%

관리부서
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)23.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
곡성읍사무소
15 
오곡면사무소
2 
겸면사무소
2 
옥과면사무소
 
1
오산면사무소
 
1

Length

Max length6
Median length6
Mean length5.9047619
Min length5

Unique

Unique2 ?
Unique (%)9.5%

Sample

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

Common Values

ValueCountFrequency (%)
곡성읍사무소 15
71.4%
오곡면사무소 2
 
9.5%
겸면사무소 2
 
9.5%
옥과면사무소 1
 
4.8%
오산면사무소 1
 
4.8%

Length

2023-12-12T09:18:04.528109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:18:04.643346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
곡성읍사무소 15
71.4%
오곡면사무소 2
 
9.5%
겸면사무소 2
 
9.5%
옥과면사무소 1
 
4.8%
오산면사무소 1
 
4.8%

관리부서번호
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)23.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
061-360-7161
15 
061-360-7701
2 
061-360-8012
2 
061-360-7813
 
1
061-360-8110
 
1

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique2 ?
Unique (%)9.5%

Sample

1st row061-360-7161
2nd row061-360-7161
3rd row061-360-7161
4th row061-360-7161
5th row061-360-7161

Common Values

ValueCountFrequency (%)
061-360-7161 15
71.4%
061-360-7701 2
 
9.5%
061-360-8012 2
 
9.5%
061-360-7813 1
 
4.8%
061-360-8110 1
 
4.8%

Length

2023-12-12T09:18:04.763536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:18:04.880964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
061-360-7161 15
71.4%
061-360-7701 2
 
9.5%
061-360-8012 2
 
9.5%
061-360-7813 1
 
4.8%
061-360-8110 1
 
4.8%

Interactions

2023-12-12T09:17:59.770144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:17:59.616453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:17:59.850880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:17:59.693922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T09:18:04.976952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번읍면동종류관리번호설치장소명지번주소경도위도설치일시전체높이(미터)펼침지름(미터)영조물보험 가입여부관리부서관리부서번호
연번1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
읍면동1.0001.0000.2631.0001.0001.0001.0000.9780.3660.2620.6521.0001.0001.000
종류1.0000.2631.0001.0001.0001.0000.1820.0001.0000.9490.1350.0000.2630.263
관리번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
설치장소명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
지번주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
경도1.0001.0000.1821.0001.0001.0001.0000.8670.0000.1420.0000.0001.0001.000
위도1.0000.9780.0001.0001.0001.0000.8671.0000.0000.0000.4120.2220.9780.978
설치일시1.0000.3661.0001.0001.0001.0000.0000.0001.0000.9861.0001.0000.3660.366
전체높이(미터)1.0000.2620.9491.0001.0001.0000.1420.0000.9861.0000.1760.1840.2620.262
펼침지름(미터)1.0000.6520.1351.0001.0001.0000.0000.4121.0000.1761.0001.0000.6520.652
영조물보험 가입여부1.0001.0000.0001.0001.0001.0000.0000.2221.0000.1841.0001.0001.0001.000
관리부서1.0001.0000.2631.0001.0001.0001.0000.9780.3660.2620.6521.0001.0001.000
관리부서번호1.0001.0000.2631.0001.0001.0001.0000.9780.3660.2620.6521.0001.0001.000
2023-12-12T09:18:05.124965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
펼침지름(미터)관리부서번호종류읍면동전체높이(미터)영조물보험 가입여부관리부서
펼침지름(미터)1.0000.5770.2060.5770.2730.9730.577
관리부서번호0.5771.0000.2791.0000.2770.9181.000
종류0.2060.2791.0000.2790.7950.0000.279
읍면동0.5771.0000.2791.0000.2770.9181.000
전체높이(미터)0.2730.2770.7950.2771.0000.1070.277
영조물보험 가입여부0.9730.9180.0000.9180.1071.0000.918
관리부서0.5771.0000.2791.0000.2770.9181.000
2023-12-12T09:18:05.291811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
경도위도읍면동종류전체높이(미터)펼침지름(미터)영조물보험 가입여부관리부서관리부서번호
경도1.0000.6660.9430.2840.2170.0000.0000.9430.943
위도0.6661.0000.7830.0000.0000.3090.2290.7830.783
읍면동0.9430.7831.0000.2790.2770.5770.9181.0001.000
종류0.2840.0000.2791.0000.7950.2060.0000.2790.279
전체높이(미터)0.2170.0000.2770.7951.0000.2730.1070.2770.277
펼침지름(미터)0.0000.3090.5770.2060.2731.0000.9730.5770.577
영조물보험 가입여부0.0000.2290.9180.0000.1070.9731.0000.9180.918
관리부서0.9430.7831.0000.2790.2770.5770.9181.0001.000
관리부서번호0.9430.7831.0000.2790.2770.5770.9181.0001.000

Missing values

2023-12-12T09:18:00.008287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:18:00.244141image/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

연번시도시군구읍면동종류관리번호설치장소명지번주소경도위도설치일시원단명전체높이(미터)펼침지름(미터)영조물보험 가입여부관리부서관리부서번호
0곡성-01전라남도곡성군곡성읍그늘막(스마트형)곡성-01문화센터 앞 횡단보도전라남도 곡성군 곡성읍 209-1127.29721135.2798982020-07-28메쉬3.05.0O곡성읍사무소061-360-7161
1곡성-02전라남도곡성군곡성읍그늘막(스마트형)곡성-02기차마을 전통시장앞 횡단보도전라남도 곡성군 곡성읍 읍내리 209-1127.29733335.2797622020-07-28메쉬3.05.0O곡성읍사무소061-360-7161
2곡성-03전라남도곡성군곡성읍그늘막(스마트형)곡성-03영운공원 앞 횡단보도전라남도 곡성군 곡성읍 읍내리 97-2127.30225535.2820472020-07-28메쉬3.75.0O곡성읍사무소061-360-7161
3곡성-04전라남도곡성군곡성읍그늘막(스마트형)곡성-04기차마을 앞 횡단보도전라남도 곡성군 곡성읍 읍내리 94-5127.30246435.2819052020-07-28메쉬3.05.0O곡성읍사무소061-360-7161
4곡성-05전라남도곡성군곡성읍그늘막(고정형)곡성-05뚝방마켓 주차장 앞 횡단보도전라남도 곡성군 곡성읍 읍내리 127-4127.30196635.2816552019-08-27메쉬3.75.0O곡성읍사무소061-360-7161
5곡성-06전라남도곡성군곡성읍그늘막(고정형)곡성-06터미널 앞 횡단보도전라남도 곡성군 곡성읍 읍내리 246-1127.29388335.2785522019-08-27메쉬3.75.0O곡성읍사무소061-360-7161
6곡성-07전라남도곡성군곡성읍그늘막(고정형)곡성-07롯데리아 앞 횡단보도전라남도 곡성군 곡성읍 읍내리 796-8127.29373435.2784242019-08-27메쉬3.75.0O곡성읍사무소061-360-7161
7곡성-08전라남도곡성군곡성읍그늘막(고정형)곡성-08곡성역사거리(기차마을 입구 비석앞)전라남도 곡성군 곡성읍 읍내리 96-6127.30286435.2823192019-08-27메쉬3.75.0O곡성읍사무소061-360-7161
8곡성-09전라남도곡성군곡성읍그늘막(고정형)곡성-09영운공원 앞(드림하이 건너편)전라남도 곡성군 곡성읍 읍내리 97127.30207435.2820912019-08-27메쉬3.75.0O곡성읍사무소061-360-7161
9곡성-10전라남도곡성군곡성읍그늘막(고정형)곡성-10드림하이센터 옆(영운공원 건너편)전라남도 곡성군 곡성읍 읍내리 127-4127.30195335.2819612019-08-27메쉬3.75.0O곡성읍사무소061-360-7161
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