Overview

Dataset statistics

Number of variables15
Number of observations1083
Missing cells1055
Missing cells (%)6.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory132.3 KiB
Average record size in memory125.1 B

Variable types

Numeric5
Categorical4
Text4
DateTime2

Dataset

Description경기도 용인시 그늘막 설치 위치 정보를 제공합니다.(기준년도, 시군명, 읍면동명, 관리번호, 설치장소명, 소재지도로명주소, 소재지지번주소, 설치일자, 높이, 펼침지름, 원단, 위도, 경도, 관리기관명, 데이터기준일자)
Author경기도 용인시
URLhttps://www.data.go.kr/data/15112628/fileData.do

Alerts

시군명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
기준년도 is highly overall correlated with 관리기관명High correlation
높이(미터) is highly overall correlated with 펼침지름(미터) and 3 other fieldsHigh correlation
펼침지름(미터) is highly overall correlated with 높이(미터) and 1 other fieldsHigh correlation
위도 is highly overall correlated with 높이(미터) and 2 other fieldsHigh correlation
경도 is highly overall correlated with 높이(미터) and 2 other fieldsHigh correlation
읍면동명 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
원단 is highly overall correlated with 관리기관명High correlation
관리기관명 is highly overall correlated with 기준년도 and 3 other fieldsHigh correlation
원단 is highly imbalanced (62.4%)Imbalance
관리기관명 is highly imbalanced (60.7%)Imbalance
기준년도 has 38 (3.5%) missing valuesMissing
설치장소명 has 169 (15.6%) missing valuesMissing
소재지도로명주소 has 600 (55.4%) missing valuesMissing
설치일자 has 38 (3.5%) missing valuesMissing
높이(미터) has 205 (18.9%) missing valuesMissing

Reproduction

Analysis started2024-04-17 11:37:22.145008
Analysis finished2024-04-17 11:37:25.433124
Duration3.29 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct7
Distinct (%)0.7%
Missing38
Missing (%)3.5%
Infinite0
Infinite (%)0.0%
Mean2020.7397
Minimum2017
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.6 KiB
2024-04-17T20:37:25.471336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2017
5-th percentile2018
Q12020
median2021
Q32022
95-th percentile2023
Maximum2023
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.5521589
Coefficient of variation (CV)0.00076811421
Kurtosis-0.88353099
Mean2020.7397
Median Absolute Deviation (MAD)1
Skewness-0.14770829
Sum2111673
Variance2.4091972
MonotonicityNot monotonic
2024-04-17T20:37:25.567441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2020 244
22.5%
2022 213
19.7%
2019 179
16.5%
2021 170
15.7%
2023 170
15.7%
2018 53
 
4.9%
2017 16
 
1.5%
(Missing) 38
 
3.5%
ValueCountFrequency (%)
2017 16
 
1.5%
2018 53
 
4.9%
2019 179
16.5%
2020 244
22.5%
2021 170
15.7%
2022 213
19.7%
2023 170
15.7%
ValueCountFrequency (%)
2023 170
15.7%
2022 213
19.7%
2021 170
15.7%
2020 244
22.5%
2019 179
16.5%
2018 53
 
4.9%
2017 16
 
1.5%

시군명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
용인시
1083 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
용인시 1083
100.0%

Length

2024-04-17T20:37:25.666476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T20:37:25.741940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
용인시 1083
100.0%

읍면동명
Categorical

HIGH CORRELATION 

Distinct40
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
성복동
 
66
동천동
 
64
신봉동
 
59
상현1동
 
55
구갈동
 
53
Other values (35)
786 

Length

Max length5
Median length3
Mean length3.3342567
Min length3

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
성복동 66
 
6.1%
동천동 64
 
5.9%
신봉동 59
 
5.4%
상현1동 55
 
5.1%
구갈동 53
 
4.9%
유림동 53
 
4.9%
역북동 50
 
4.6%
신갈동 44
 
4.1%
풍덕천1동 40
 
3.7%
영덕1동 37
 
3.4%
Other values (30) 562
51.9%

Length

2024-04-17T20:37:25.832146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
성복동 66
 
6.1%
동천동 64
 
5.9%
신봉동 59
 
5.4%
상현1동 55
 
5.1%
구갈동 53
 
4.9%
유림동 53
 
4.9%
역북동 50
 
4.6%
신갈동 44
 
4.1%
풍덕천1동 40
 
3.7%
영덕1동 37
 
3.4%
Other values (30) 562
51.9%

관리번호
Text

Distinct1082
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
2024-04-17T20:37:26.089110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.1089566
Min length4

Characters and Unicode

Total characters5533
Distinct characters53
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

Unique1081 ?
Unique (%)99.8%

Sample

1st row포곡-1
2nd row포곡-2
3rd row포곡-3
4th row포곡-4
5th row포곡-5
ValueCountFrequency (%)
기흥-33 2
 
0.2%
수지-186 1
 
0.1%
수지-161 1
 
0.1%
수지-318 1
 
0.1%
수지-317 1
 
0.1%
수지-301 1
 
0.1%
수지-256 1
 
0.1%
수지-249 1
 
0.1%
수지-248 1
 
0.1%
수지-247 1
 
0.1%
Other values (1072) 1072
99.0%
2024-04-17T20:37:26.484475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1083
19.6%
1 452
 
8.2%
지 412
 
7.4%
2 394
 
7.1%
수 390
 
7.0%
3 332
 
6.0%
4 198
 
3.6%
0 169
 
3.1%
5 167
 
3.0%
6 155
 
2.8%
Other values (43) 1781
32.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2280
41.2%
Other Letter 2170
39.2%
Dash Punctuation 1083
19.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 412
19.0%
수 390
18.0%
갈 106
 
4.9%
동 101
 
4.7%
구 88
 
4.1%
북 82
 
3.8%
백 78
 
3.6%
림 53
 
2.4%
유 53
 
2.4%
보 50
 
2.3%
Other values (32) 757
34.9%
Decimal Number
ValueCountFrequency (%)
1 452
19.8%
2 394
17.3%
3 332
14.6%
4 198
8.7%
0 169
 
7.4%
5 167
 
7.3%
6 155
 
6.8%
7 141
 
6.2%
8 140
 
6.1%
9 132
 
5.8%
Dash Punctuation
ValueCountFrequency (%)
- 1083
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3363
60.8%
Hangul 2170
39.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 412
19.0%
수 390
18.0%
갈 106
 
4.9%
동 101
 
4.7%
구 88
 
4.1%
북 82
 
3.8%
백 78
 
3.6%
림 53
 
2.4%
유 53
 
2.4%
보 50
 
2.3%
Other values (32) 757
34.9%
Common
ValueCountFrequency (%)
- 1083
32.2%
1 452
13.4%
2 394
 
11.7%
3 332
 
9.9%
4 198
 
5.9%
0 169
 
5.0%
5 167
 
5.0%
6 155
 
4.6%
7 141
 
4.2%
8 140
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3363
60.8%
Hangul 2170
39.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1083
32.2%
1 452
13.4%
2 394
 
11.7%
3 332
 
9.9%
4 198
 
5.9%
0 169
 
5.0%
5 167
 
5.0%
6 155
 
4.6%
7 141
 
4.2%
8 140
 
4.2%
Hangul
ValueCountFrequency (%)
지 412
19.0%
수 390
18.0%
갈 106
 
4.9%
동 101
 
4.7%
구 88
 
4.1%
북 82
 
3.8%
백 78
 
3.6%
림 53
 
2.4%
유 53
 
2.4%
보 50
 
2.3%
Other values (32) 757
34.9%

설치장소명
Text

MISSING 

Distinct801
Distinct (%)87.6%
Missing169
Missing (%)15.6%
Memory size8.6 KiB
2024-04-17T20:37:26.687411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length27
Mean length16.440919
Min length2

Characters and Unicode

Total characters15027
Distinct characters428
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique720 ?
Unique (%)78.8%

Sample

1st row둔전초 정문(둔전리 109-19)
2nd row신원APT사거리 식재자마트 앞(둔전리 379-9)
3rd row신원APT사거리 GS리테일 앞(둔전리 391-3)
4th row도사마을사거리 장가네 앞(삼계리 86-7)
5th row도사마을사거리 형제크레인 앞(삼계리 88-1)
ValueCountFrequency (%)
앞 179
 
6.5%
사거리 92
 
3.4%
쪽 92
 
3.4%
삼거리 50
 
1.8%
정문 43
 
1.6%
인근 40
 
1.5%
횡단보도 32
 
1.2%
건너편 30
 
1.1%
입구 28
 
1.0%
맞은 21
 
0.8%
Other values (1253) 2137
77.9%
2024-04-17T20:37:27.015965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1833
 
12.2%
리 657
 
4.4%
) 535
 
3.6%
( 535
 
3.6%
거 515
 
3.4%
사 350
 
2.3%
앞 328
 
2.2%
동 325
 
2.2%
교 296
 
2.0%
1 246
 
1.6%
Other values (418) 9407
62.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10552
70.2%
Space Separator 1833
 
12.2%
Decimal Number 1259
 
8.4%
Close Punctuation 535
 
3.6%
Open Punctuation 535
 
3.6%
Dash Punctuation 156
 
1.0%
Uppercase Letter 119
 
0.8%
Other Punctuation 24
 
0.2%
Lowercase Letter 13
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 657
 
6.2%
거 515
 
4.9%
사 350
 
3.3%
앞 328
 
3.1%
동 325
 
3.1%
교 296
 
2.8%
지 239
 
2.3%
삼 221
 
2.1%
구 166
 
1.6%
단 164
 
1.6%
Other values (376) 7291
69.1%
Uppercase Letter
ValueCountFrequency (%)
G 20
16.8%
C 19
16.0%
A 15
12.6%
S 15
12.6%
L 10
8.4%
K 9
7.6%
I 8
 
6.7%
T 8
 
6.7%
U 5
 
4.2%
R 2
 
1.7%
Other values (6) 8
 
6.7%
Decimal Number
ValueCountFrequency (%)
1 246
19.5%
3 158
12.5%
2 156
12.4%
5 126
10.0%
7 105
8.3%
0 101
8.0%
6 98
 
7.8%
9 96
 
7.6%
4 89
 
7.1%
8 84
 
6.7%
Other Punctuation
ValueCountFrequency (%)
, 9
37.5%
@ 8
33.3%
& 3
 
12.5%
· 2
 
8.3%
# 1
 
4.2%
. 1
 
4.2%
Lowercase Letter
ValueCountFrequency (%)
e 5
38.5%
c 3
23.1%
k 2
 
15.4%
b 2
 
15.4%
u 1
 
7.7%
Space Separator
ValueCountFrequency (%)
1833
100.0%
Close Punctuation
ValueCountFrequency (%)
) 535
100.0%
Open Punctuation
ValueCountFrequency (%)
( 535
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 156
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10552
70.2%
Common 4343
28.9%
Latin 132
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 657
 
6.2%
거 515
 
4.9%
사 350
 
3.3%
앞 328
 
3.1%
동 325
 
3.1%
교 296
 
2.8%
지 239
 
2.3%
삼 221
 
2.1%
구 166
 
1.6%
단 164
 
1.6%
Other values (376) 7291
69.1%
Common
ValueCountFrequency (%)
1833
42.2%
) 535
 
12.3%
( 535
 
12.3%
1 246
 
5.7%
3 158
 
3.6%
2 156
 
3.6%
- 156
 
3.6%
5 126
 
2.9%
7 105
 
2.4%
0 101
 
2.3%
Other values (11) 392
 
9.0%
Latin
ValueCountFrequency (%)
G 20
15.2%
C 19
14.4%
A 15
11.4%
S 15
11.4%
L 10
7.6%
K 9
6.8%
I 8
 
6.1%
T 8
 
6.1%
e 5
 
3.8%
U 5
 
3.8%
Other values (11) 18
13.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10552
70.2%
ASCII 4473
29.8%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1833
41.0%
) 535
 
12.0%
( 535
 
12.0%
1 246
 
5.5%
3 158
 
3.5%
2 156
 
3.5%
- 156
 
3.5%
5 126
 
2.8%
7 105
 
2.3%
0 101
 
2.3%
Other values (31) 522
 
11.7%
Hangul
ValueCountFrequency (%)
리 657
 
6.2%
거 515
 
4.9%
사 350
 
3.3%
앞 328
 
3.1%
동 325
 
3.1%
교 296
 
2.8%
지 239
 
2.3%
삼 221
 
2.1%
구 166
 
1.6%
단 164
 
1.6%
Other values (376) 7291
69.1%
None
ValueCountFrequency (%)
· 2
100.0%

소재지도로명주소
Text

MISSING 

Distinct147
Distinct (%)30.4%
Missing600
Missing (%)55.4%
Memory size8.6 KiB
2024-04-17T20:37:27.492231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length1
Mean length12.403727
Min length1

Characters and Unicode

Total characters5991
Distinct characters172
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique82 ?
Unique (%)17.0%

Sample

1st row
2nd row
3rd row
4th row
5th row경기도 용인시 처인구 포곡읍 백옥대로 1901
ValueCountFrequency (%)
경기도 233
17.9%
용인시 233
17.9%
수지구 131
 
10.1%
기흥구 85
 
6.5%
처인구 17
 
1.3%
2 13
 
1.0%
중부대로 13
 
1.0%
광교마을로 10
 
0.8%
지하 9
 
0.7%
성복2로 7
 
0.5%
Other values (265) 550
42.3%
2024-04-17T20:37:27.849706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1449
24.2%
기 343
 
5.7%
인 255
 
4.3%
구 247
 
4.1%
용 242
 
4.0%
시 237
 
4.0%
도 235
 
3.9%
경 234
 
3.9%
로 233
 
3.9%
지 177
 
3.0%
Other values (162) 2339
39.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3596
60.0%
Space Separator 1449
24.2%
Decimal Number 781
 
13.0%
Open Punctuation 53
 
0.9%
Close Punctuation 53
 
0.9%
Other Punctuation 40
 
0.7%
Dash Punctuation 18
 
0.3%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 343
 
9.5%
인 255
 
7.1%
구 247
 
6.9%
용 242
 
6.7%
시 237
 
6.6%
도 235
 
6.5%
경 234
 
6.5%
로 233
 
6.5%
지 177
 
4.9%
수 150
 
4.2%
Other values (146) 1243
34.6%
Decimal Number
ValueCountFrequency (%)
1 172
22.0%
2 121
15.5%
3 80
10.2%
4 72
9.2%
6 71
9.1%
5 65
 
8.3%
8 56
 
7.2%
0 51
 
6.5%
7 50
 
6.4%
9 43
 
5.5%
Space Separator
ValueCountFrequency (%)
1449
100.0%
Open Punctuation
ValueCountFrequency (%)
( 53
100.0%
Close Punctuation
ValueCountFrequency (%)
) 53
100.0%
Other Punctuation
ValueCountFrequency (%)
, 40
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3595
60.0%
Common 2394
40.0%
Latin 1
 
< 0.1%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 343
 
9.5%
인 255
 
7.1%
구 247
 
6.9%
용 242
 
6.7%
시 237
 
6.6%
도 235
 
6.5%
경 234
 
6.5%
로 233
 
6.5%
지 177
 
4.9%
수 150
 
4.2%
Other values (145) 1242
34.5%
Common
ValueCountFrequency (%)
1449
60.5%
1 172
 
7.2%
2 121
 
5.1%
3 80
 
3.3%
4 72
 
3.0%
6 71
 
3.0%
5 65
 
2.7%
8 56
 
2.3%
( 53
 
2.2%
) 53
 
2.2%
Other values (5) 202
 
8.4%
Latin
ValueCountFrequency (%)
e 1
100.0%
Han
ValueCountFrequency (%)
愛 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3595
60.0%
ASCII 2395
40.0%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1449
60.5%
1 172
 
7.2%
2 121
 
5.1%
3 80
 
3.3%
4 72
 
3.0%
6 71
 
3.0%
5 65
 
2.7%
8 56
 
2.3%
( 53
 
2.2%
) 53
 
2.2%
Other values (6) 203
 
8.5%
Hangul
ValueCountFrequency (%)
기 343
 
9.5%
인 255
 
7.1%
구 247
 
6.9%
용 242
 
6.7%
시 237
 
6.6%
도 235
 
6.5%
경 234
 
6.5%
로 233
 
6.5%
지 177
 
4.9%
수 150
 
4.2%
Other values (145) 1242
34.5%
CJK
ValueCountFrequency (%)
愛 1
100.0%

소재지지번주소
Text

Distinct706
Distinct (%)65.2%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
2024-04-17T20:37:28.123538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length34
Mean length21.790397
Min length17

Characters and Unicode

Total characters23599
Distinct characters157
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique479 ?
Unique (%)44.2%

Sample

1st row경기도 용인시 처인구 포곡읍 둔전리 109-19
2nd row경기도 용인시 처인구 포곡읍 둔전리 379-9
3rd row경기도 용인시 처인구 포곡읍 둔전리 391-3
4th row경기도 용인시 처인구 포곡읍 삼계리 86-7
5th row경기도 용인시 처인구 포곡읍 삼계리 88-1
ValueCountFrequency (%)
경기도 1083
19.5%
용인시 1083
19.5%
기흥구 413
 
7.4%
수지구 392
 
7.1%
처인구 267
 
4.8%
상현동 73
 
1.3%
성복동 66
 
1.2%
죽전동 66
 
1.2%
풍덕천동 64
 
1.2%
동천동 64
 
1.2%
Other values (765) 1973
35.6%
2024-04-17T20:37:28.508682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4731
20.0%
기 1500
 
6.4%
인 1350
 
5.7%
구 1126
 
4.8%
동 1116
 
4.7%
시 1086
 
4.6%
도 1085
 
4.6%
경 1083
 
4.6%
용 1083
 
4.6%
1 776
 
3.3%
Other values (147) 8663
36.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14113
59.8%
Space Separator 4731
 
20.0%
Decimal Number 4182
 
17.7%
Dash Punctuation 553
 
2.3%
Open Punctuation 10
 
< 0.1%
Close Punctuation 10
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 1500
10.6%
인 1350
 
9.6%
구 1126
 
8.0%
동 1116
 
7.9%
시 1086
 
7.7%
도 1085
 
7.7%
경 1083
 
7.7%
용 1083
 
7.7%
지 660
 
4.7%
흥 417
 
3.0%
Other values (133) 3607
25.6%
Decimal Number
ValueCountFrequency (%)
1 776
18.6%
3 430
10.3%
5 420
10.0%
6 415
9.9%
7 400
9.6%
2 387
9.3%
4 352
8.4%
9 346
8.3%
8 328
7.8%
0 328
7.8%
Space Separator
ValueCountFrequency (%)
4731
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 553
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14113
59.8%
Common 9486
40.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 1500
10.6%
인 1350
 
9.6%
구 1126
 
8.0%
동 1116
 
7.9%
시 1086
 
7.7%
도 1085
 
7.7%
경 1083
 
7.7%
용 1083
 
7.7%
지 660
 
4.7%
흥 417
 
3.0%
Other values (133) 3607
25.6%
Common
ValueCountFrequency (%)
4731
49.9%
1 776
 
8.2%
- 553
 
5.8%
3 430
 
4.5%
5 420
 
4.4%
6 415
 
4.4%
7 400
 
4.2%
2 387
 
4.1%
4 352
 
3.7%
9 346
 
3.6%
Other values (4) 676
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14113
59.8%
ASCII 9486
40.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4731
49.9%
1 776
 
8.2%
- 553
 
5.8%
3 430
 
4.5%
5 420
 
4.4%
6 415
 
4.4%
7 400
 
4.2%
2 387
 
4.1%
4 352
 
3.7%
9 346
 
3.6%
Other values (4) 676
 
7.1%
Hangul
ValueCountFrequency (%)
기 1500
10.6%
인 1350
 
9.6%
구 1126
 
8.0%
동 1116
 
7.9%
시 1086
 
7.7%
도 1085
 
7.7%
경 1083
 
7.7%
용 1083
 
7.7%
지 660
 
4.7%
흥 417
 
3.0%
Other values (133) 3607
25.6%

설치일자
Date

MISSING 

Distinct83
Distinct (%)7.9%
Missing38
Missing (%)3.5%
Memory size8.6 KiB
Minimum2017-08-16 00:00:00
Maximum2023-10-10 00:00:00
2024-04-17T20:37:28.632146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:37:28.769269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

높이(미터)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct14
Distinct (%)1.6%
Missing205
Missing (%)18.9%
Infinite0
Infinite (%)0.0%
Mean3.4477221
Minimum2.8
Maximum4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.6 KiB
2024-04-17T20:37:28.878593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.8
5-th percentile3.1
Q13.4
median3.4
Q33.7
95-th percentile3.8
Maximum4
Range1.2
Interquartile range (IQR)0.3

Descriptive statistics

Standard deviation0.21491014
Coefficient of variation (CV)0.06233395
Kurtosis-0.67357991
Mean3.4477221
Median Absolute Deviation (MAD)0.15
Skewness-0.11757782
Sum3027.1
Variance0.046186367
MonotonicityNot monotonic
2024-04-17T20:37:28.985159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
3.4 384
35.5%
3.7 184
17.0%
3.1 134
 
12.4%
3.8 58
 
5.4%
3.5 47
 
4.3%
3.55 28
 
2.6%
3.2 23
 
2.1%
3.0 7
 
0.6%
3.65 4
 
0.4%
3.6 3
 
0.3%
Other values (4) 6
 
0.6%
(Missing) 205
18.9%
ValueCountFrequency (%)
2.8 1
 
0.1%
3.0 7
 
0.6%
3.1 134
 
12.4%
3.2 23
 
2.1%
3.3 1
 
0.1%
3.4 384
35.5%
3.45 2
 
0.2%
3.5 47
 
4.3%
3.55 28
 
2.6%
3.6 3
 
0.3%
ValueCountFrequency (%)
4.0 2
 
0.2%
3.8 58
 
5.4%
3.7 184
17.0%
3.65 4
 
0.4%
3.6 3
 
0.3%
3.55 28
 
2.6%
3.5 47
 
4.3%
3.45 2
 
0.2%
3.4 384
35.5%
3.3 1
 
0.1%

펼침지름(미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)0.6%
Missing5
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean3.6269944
Minimum0.3
Maximum5.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.6 KiB
2024-04-17T20:37:29.083017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.3
5-th percentile3
Q13
median4
Q34
95-th percentile4
Maximum5.4
Range5.1
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.51128805
Coefficient of variation (CV)0.14096742
Kurtosis0.58937754
Mean3.6269944
Median Absolute Deviation (MAD)0
Skewness-0.40142888
Sum3909.9
Variance0.26141547
MonotonicityNot monotonic
2024-04-17T20:37:29.166545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
4.0 633
58.4%
3.0 392
36.2%
3.5 40
 
3.7%
5.0 8
 
0.7%
5.4 4
 
0.4%
0.3 1
 
0.1%
(Missing) 5
 
0.5%
ValueCountFrequency (%)
0.3 1
 
0.1%
3.0 392
36.2%
3.5 40
 
3.7%
4.0 633
58.4%
5.0 8
 
0.7%
5.4 4
 
0.4%
ValueCountFrequency (%)
5.4 4
 
0.4%
5.0 8
 
0.7%
4.0 633
58.4%
3.5 40
 
3.7%
3.0 392
36.2%
0.3 1
 
0.1%

원단
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
매쉬
833 
<NA>
208 
아크릴
 
33
HBPE 폴라르원단
 
4
HDPE 매쉬
 
4

Length

Max length10
Median length2
Mean length2.4626039
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
매쉬 833
76.9%
<NA> 208
 
19.2%
아크릴 33
 
3.0%
HBPE 폴라르원단 4
 
0.4%
HDPE 매쉬 4
 
0.4%
매휘 1
 
0.1%

Length

2024-04-17T20:37:29.276209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T20:37:29.373359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
매쉬 837
76.7%
na 208
 
19.1%
아크릴 33
 
3.0%
hbpe 4
 
0.4%
폴라르원단 4
 
0.4%
hdpe 4
 
0.4%
매휘 1
 
0.1%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct1061
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.279962
Minimum37.113095
Maximum37.345358
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.6 KiB
2024-04-17T20:37:29.482806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.113095
5-th percentile37.219757
Q137.247269
median37.283011
Q337.318196
95-th percentile37.336178
Maximum37.345358
Range0.2322627
Interquartile range (IQR)0.07092715

Descriptive statistics

Standard deviation0.043449003
Coefficient of variation (CV)0.0011654787
Kurtosis0.43502582
Mean37.279962
Median Absolute Deviation (MAD)0.0356596
Skewness-0.75502634
Sum40374.199
Variance0.0018878159
MonotonicityNot monotonic
2024-04-17T20:37:29.608031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.3316 4
 
0.4%
37.3318 3
 
0.3%
37.3276 3
 
0.3%
37.3017758 2
 
0.2%
37.3450947 2
 
0.2%
37.3103793 2
 
0.2%
37.2309941 2
 
0.2%
37.309178 2
 
0.2%
37.301143 2
 
0.2%
37.328385 2
 
0.2%
Other values (1051) 1059
97.8%
ValueCountFrequency (%)
37.1130953 1
0.1%
37.1412025 1
0.1%
37.141287 1
0.1%
37.1513925 1
0.1%
37.1514581 1
0.1%
37.1515763 1
0.1%
37.1516792 1
0.1%
37.1532186 1
0.1%
37.1533647 1
0.1%
37.153498 1
0.1%
ValueCountFrequency (%)
37.345358 1
0.1%
37.345267 1
0.1%
37.3450947 2
0.2%
37.3450234 1
0.1%
37.344144 1
0.1%
37.344053 1
0.1%
37.3433333 1
0.1%
37.3431697 1
0.1%
37.3423804 1
0.1%
37.3419194 1
0.1%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct1070
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.1302
Minimum127.05923
Maximum127.37624
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.6 KiB
2024-04-17T20:37:29.738211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.05923
5-th percentile127.06808
Q1127.08626
median127.11386
Q3127.1624
95-th percentile127.22309
Maximum127.37624
Range0.3170159
Interquartile range (IQR)0.0761337

Descriptive statistics

Standard deviation0.058065805
Coefficient of variation (CV)0.00045674283
Kurtosis2.3121184
Mean127.1302
Median Absolute Deviation (MAD)0.0338176
Skewness1.3867485
Sum137682
Variance0.0033716377
MonotonicityNot monotonic
2024-04-17T20:37:29.863830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0665 2
 
0.2%
127.068403 2
 
0.2%
127.114 2
 
0.2%
127.0772 2
 
0.2%
127.0673 2
 
0.2%
127.0865136 2
 
0.2%
127.1154894 2
 
0.2%
127.0859 2
 
0.2%
127.0821 2
 
0.2%
127.0678 2
 
0.2%
Other values (1060) 1063
98.2%
ValueCountFrequency (%)
127.0592288 1
0.1%
127.059451 1
0.1%
127.0594675 1
0.1%
127.059699 1
0.1%
127.0597911 1
0.1%
127.0610164 1
0.1%
127.061633 1
0.1%
127.0617151 1
0.1%
127.0617277 1
0.1%
127.061872 1
0.1%
ValueCountFrequency (%)
127.3762447 1
0.1%
127.3760194 1
0.1%
127.3759434 1
0.1%
127.3758288 1
0.1%
127.3742859 1
0.1%
127.3736456 1
0.1%
127.3734104 1
0.1%
127.369832 1
0.1%
127.3691195 1
0.1%
127.3686835 1
0.1%

관리기관명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct20
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
필랜드
802 
(주)유퍼니
 
59
유퍼니
 
56
경기상사
 
42
㈜나라에스앤씨
 
26
Other values (15)
98 

Length

Max length10
Median length3
Mean length3.534626
Min length3

Unique

Unique2 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
필랜드 802
74.1%
(주)유퍼니 59
 
5.4%
유퍼니 56
 
5.2%
경기상사 42
 
3.9%
㈜나라에스앤씨 26
 
2.4%
피닉스코리아 26
 
2.4%
㈜드림레저 20
 
1.8%
영풍산업 7
 
0.6%
메탈크래프트 6
 
0.6%
㈜드림레져 6
 
0.6%
Other values (10) 33
 
3.0%

Length

2024-04-17T20:37:29.994160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
필랜드 802
74.1%
주)유퍼니 59
 
5.4%
유퍼니 56
 
5.2%
경기상사 42
 
3.9%
㈜나라에스앤씨 26
 
2.4%
피닉스코리아 26
 
2.4%
㈜드림레저 20
 
1.8%
영풍산업 7
 
0.6%
메탈크래프트 6
 
0.6%
㈜드림레져 6
 
0.6%
Other values (10) 33
 
3.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size8.6 KiB
Minimum2024-03-05 00:00:00
Maximum2024-03-05 00:00:00
2024-04-17T20:37:30.085281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:37:30.166054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-04-17T20:37:24.603654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:37:22.988581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:37:23.389952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:37:23.805857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:37:24.195243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:37:24.690155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:37:23.068743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:37:23.471927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:37:23.887421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:37:24.278373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:37:24.775799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:37:23.148993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:37:23.554478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:37:23.967252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:37:24.366210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:37:24.855686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:37:23.228467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:37:23.631329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:37:24.039646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:37:24.446265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:37:24.934434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:37:23.305095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:37:23.710093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:37:24.114440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:37:24.521510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-17T20:37:30.235873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도읍면동명설치일자높이(미터)펼침지름(미터)원단위도경도관리기관명
기준년도1.0000.6441.0000.6980.4390.3240.2680.2730.880
읍면동명0.6441.0000.9050.7720.5190.4500.9760.9840.785
설치일자1.0000.9051.0000.9230.9090.9770.8240.8160.982
높이(미터)0.6980.7720.9231.0000.6200.4060.7210.6400.914
펼침지름(미터)0.4390.5190.9090.6201.0000.6570.3030.2460.922
원단0.3240.4500.9770.4060.6571.0000.3980.2300.931
위도0.2680.9760.8240.7210.3030.3981.0000.8410.513
경도0.2730.9840.8160.6400.2460.2300.8411.0000.362
관리기관명0.8800.7850.9820.9140.9220.9310.5130.3621.000
2024-04-17T20:37:30.350198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리기관명읍면동명원단
관리기관명1.0000.2750.675
읍면동명0.2751.0000.224
원단0.6750.2241.000
2024-04-17T20:37:30.435212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도높이(미터)펼침지름(미터)위도경도읍면동명원단관리기관명
기준년도1.000-0.190-0.326-0.0780.1230.3250.2240.604
높이(미터)-0.1901.0000.5290.584-0.6190.4030.2490.646
펼침지름(미터)-0.3260.5291.0000.113-0.1360.2480.2980.660
위도-0.0780.5840.1131.000-0.5840.7610.1760.186
경도0.123-0.619-0.136-0.5841.0000.8000.0970.122
읍면동명0.3250.4030.2480.7610.8001.0000.2240.275
원단0.2240.2490.2980.1760.0970.2241.0000.675
관리기관명0.6040.6460.6600.1860.1220.2750.6751.000

Missing values

2024-04-17T20:37:25.052703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T20:37:25.230586image/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.
2024-04-17T20:37:25.355970image/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

기준년도시군명읍면동명관리번호설치장소명소재지도로명주소소재지지번주소설치일자높이(미터)펼침지름(미터)원단위도경도관리기관명데이터기준일자
02019용인시포곡읍포곡-1둔전초 정문(둔전리 109-19)경기도 용인시 처인구 포곡읍 둔전리 109-192019-07-263.13.0아크릴37.268222127.224708필랜드2024-03-05
12019용인시포곡읍포곡-2신원APT사거리 식재자마트 앞(둔전리 379-9)경기도 용인시 처인구 포곡읍 둔전리 379-92019-08-163.44.0매쉬37.26887127.216048필랜드2024-03-05
22019용인시포곡읍포곡-3신원APT사거리 GS리테일 앞(둔전리 391-3)경기도 용인시 처인구 포곡읍 둔전리 391-32019-08-163.44.0매쉬37.268878127.216701필랜드2024-03-05
32020용인시포곡읍포곡-4도사마을사거리 장가네 앞(삼계리 86-7)경기도 용인시 처인구 포곡읍 삼계리 86-72020-04-303.44.0매쉬37.296321127.2338필랜드2024-03-05
42020용인시포곡읍포곡-5도사마을사거리 형제크레인 앞(삼계리 88-1)경기도 용인시 처인구 포곡읍 백옥대로 1901경기도 용인시 처인구 포곡읍 삼계리 88-12020-04-303.44.0매쉬37.296301127.233461필랜드2024-03-05
52020용인시포곡읍포곡-6포곡중 정문(전대리 547-4)경기도 용인시 처인구 포곡읍 석성로 1176경기도 용인시 처인구 포곡읍 전대리 547-42020-07-103.44.0매쉬37.279938127.223164필랜드2024-03-05
62022용인시포곡읍포곡-7포곡고삼거리(둔전리 65-1)경기도 용인시 처인구 포곡읍 둔전리 65-12022-08-193.13.0매쉬37.275244127.226345필랜드2024-03-05
72022용인시포곡읍포곡-8포곡중학교 후문(전대리 547-9)경기도 용인시 처인구 포곡읍 전대리 547-92022-08-193.44.0매쉬37.280433127.221801필랜드2024-03-05
82022용인시포곡읍포곡-9포곡중학교 후문(전대리 547)경기도 용인시 처인구 포곡읍 전대리 547-132022-08-193.44.0매쉬37.280478127.221767필랜드2024-03-05
92022용인시포곡읍포곡-10전대·에버랜드역 3번출구 앞(전대리 210-38)경기도 용인시 처인구 포곡읍 곡현로 76경기도 용인시 처인구 포곡읍 전대리 210-82022-08-193.44.0매쉬37.286208127.219821필랜드2024-03-05
기준년도시군명읍면동명관리번호설치장소명소재지도로명주소소재지지번주소설치일자높이(미터)펼침지름(미터)원단위도경도관리기관명데이터기준일자
10732023용인시성복동수지-383벽산체시빌 2차 정문 앞 좌측<NA>경기도 용인시 수지구 성복동 277-82023-07-02<NA>3.0<NA>37.3163127.0681필랜드2024-03-05
10742023용인시상현동수지-384솔개초등학교 정문 앞<NA>경기도 용인시 수지구 상현동 8412023-07-02<NA>3.0<NA>37.3049127.0821필랜드2024-03-05
10752023용인시신봉동수지-385신봉마을 자이2차 후문<NA>경기도 용인시 수지구 신봉동 9222023-07-02<NA>3.0<NA>37.3267127.0754필랜드2024-03-05
10762023용인시신봉동수지-386정문 앞 횡단보도 좌측<NA>경기도 용인시 수지구 신봉동 9932023-07-02<NA>3.0<NA>37.3325127.0665필랜드2024-03-05
10772023용인시신봉동수지-387정문 앞 횡단보도 좌측<NA>경기도 용인시 수지구 신봉동 9932023-07-02<NA>3.0<NA>37.3325127.0664필랜드2024-03-05
10782023용인시동천동수지-388손곡1교 우측<NA>경기도 용인시 수지구 동천동 9572023-07-02<NA>4.0<NA>37.3383127.0855필랜드2024-03-05
10792023용인시동천동수지-389손곡1교 좌측<NA>경기도 용인시 수지구 동천동 9572023-07-02<NA>4.0<NA>37.338127.0845필랜드2024-03-05
10802023용인시동천동수지-390손곡1교 부근 횡단보도<NA>경기도 용인시 수지구 동천동 9572023-07-02<NA>4.0<NA>37.3382127.0845필랜드2024-03-05
10812023용인시성복동수지-391성서중학교 정문 횡단보도<NA>경기도 용인시 수지구 성복동 459-402023-07-02<NA>3.0<NA>37.3162127.0634필랜드2024-03-05
10822023용인시성복동수지-392성서중학교 정문 횡단보도<NA>경기도 용인시 수지구 성복동 459-402023-07-02<NA>4.0<NA>37.3175127.0629필랜드2024-03-05