Overview

Dataset statistics

Number of variables15
Number of observations340
Missing cells680
Missing cells (%)13.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory42.0 KiB
Average record size in memory126.4 B

Variable types

Categorical7
Text4
Numeric2
Unsupported2

Dataset

Description경기도 고양시_제설함설치현황에 대한 데이터로 경기도 고양시 제설함 설치장소명, 위치, 제설함수, 관리기관 등의 항목을 제공합니다.
Author경기도 고양시
URLhttps://www.data.go.kr/data/3079135/fileData.do

Alerts

시군명 has constant value ""Constant
제설함수 has constant value ""Constant
데이터기준일자 has constant value ""Constant
관리기관전화번호 is highly overall correlated with 경도 and 3 other fieldsHigh correlation
읍면동명 is highly overall correlated with 위도 and 4 other fieldsHigh correlation
염화칼슘비치량 is highly overall correlated with 경도 and 3 other fieldsHigh correlation
관리기관명 is highly overall correlated with 경도 and 3 other fieldsHigh correlation
위도 is highly overall correlated with 읍면동명High correlation
경도 is highly overall correlated with 읍면동명 and 3 other fieldsHigh correlation
소금비치량 has 340 (100.0%) missing valuesMissing
모래비치량 has 340 (100.0%) missing valuesMissing
소금비치량 is an unsupported type, check if it needs cleaning or further analysisUnsupported
모래비치량 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-06 08:28:23.006764
Analysis finished2024-04-06 08:28:26.075847
Duration3.07 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
고양시
340 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
고양시 340
100.0%

Length

2024-04-06T17:28:26.257452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:28:26.592965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
고양시 340
100.0%

읍면동명
Categorical

HIGH CORRELATION 

Distinct49
Distinct (%)14.4%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
덕이동
33 
일산1동
28 
일산2동
28 
대화동
25 
중산동
 
19
Other values (44)
207 

Length

Max length4
Median length3
Mean length3.2911765
Min length2

Unique

Unique7 ?
Unique (%)2.1%

Sample

1st row벽제동
2nd row벽제동
3rd row벽제동
4th row벽제동
5th row고양동

Common Values

ValueCountFrequency (%)
덕이동 33
 
9.7%
일산1동 28
 
8.2%
일산2동 28
 
8.2%
대화동 25
 
7.4%
중산동 19
 
5.6%
일산3동 17
 
5.0%
풍동 14
 
4.1%
식사동 13
 
3.8%
성석동 11
 
3.2%
가좌동 11
 
3.2%
Other values (39) 141
41.5%

Length

2024-04-06T17:28:26.804749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
덕이동 33
 
9.7%
일산2동 28
 
8.2%
일산1동 28
 
8.2%
대화동 25
 
7.4%
중산동 19
 
5.6%
일산3동 17
 
5.0%
풍동 14
 
4.1%
식사동 13
 
3.8%
성석동 11
 
3.2%
가좌동 11
 
3.2%
Other values (39) 141
41.5%

관리번호
Text

Distinct334
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2024-04-06T17:28:27.382630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.4852941
Min length5

Characters and Unicode

Total characters2205
Distinct characters28
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

Unique330 ?
Unique (%)97.1%

Sample

1st row덕양구-1
2nd row덕양구-2
3rd row덕양구-3
4th row덕양구-4
5th row덕양구-5
ValueCountFrequency (%)
덕이동-29 4
 
1.2%
일산3동-03 2
 
0.6%
주엽1동-07 2
 
0.6%
덕이동-26 2
 
0.6%
덕이동-27 1
 
0.3%
일산3동-12 1
 
0.3%
일산3동-11 1
 
0.3%
일산3동-10 1
 
0.3%
일산3동-09 1
 
0.3%
일산3동-08 1
 
0.3%
Other values (324) 324
95.3%
2024-04-06T17:28:28.263660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 340
15.4%
동 261
11.8%
구 159
 
7.2%
일 153
 
6.9%
산 153
 
6.9%
1 153
 
6.9%
2 134
 
6.1%
0 119
 
5.4%
덕 112
 
5.1%
양 79
 
3.6%
Other values (18) 542
24.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1100
49.9%
Decimal Number 765
34.7%
Dash Punctuation 340
 
15.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 261
23.7%
구 159
14.5%
일 153
13.9%
산 153
13.9%
덕 112
10.2%
양 79
 
7.2%
이 33
 
3.0%
대 25
 
2.3%
화 25
 
2.3%
주 16
 
1.5%
Other values (7) 84
 
7.6%
Decimal Number
ValueCountFrequency (%)
1 153
20.0%
2 134
17.5%
0 119
15.6%
3 74
9.7%
4 56
 
7.3%
6 55
 
7.2%
5 55
 
7.2%
7 54
 
7.1%
8 33
 
4.3%
9 32
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 340
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1105
50.1%
Hangul 1100
49.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 261
23.7%
구 159
14.5%
일 153
13.9%
산 153
13.9%
덕 112
10.2%
양 79
 
7.2%
이 33
 
3.0%
대 25
 
2.3%
화 25
 
2.3%
주 16
 
1.5%
Other values (7) 84
 
7.6%
Common
ValueCountFrequency (%)
- 340
30.8%
1 153
13.8%
2 134
 
12.1%
0 119
 
10.8%
3 74
 
6.7%
4 56
 
5.1%
6 55
 
5.0%
5 55
 
5.0%
7 54
 
4.9%
8 33
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1105
50.1%
Hangul 1100
49.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 340
30.8%
1 153
13.8%
2 134
 
12.1%
0 119
 
10.8%
3 74
 
6.7%
4 56
 
5.1%
6 55
 
5.0%
5 55
 
5.0%
7 54
 
4.9%
8 33
 
3.0%
Hangul
ValueCountFrequency (%)
동 261
23.7%
구 159
14.5%
일 153
13.9%
산 153
13.9%
덕 112
10.2%
양 79
 
7.2%
이 33
 
3.0%
대 25
 
2.3%
화 25
 
2.3%
주 16
 
1.5%
Other values (7) 84
 
7.6%

설치장소명
Text

Distinct339
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2024-04-06T17:28:28.783921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length24
Mean length15.65
Min length3

Characters and Unicode

Total characters5321
Distinct characters344
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique338 ?
Unique (%)99.4%

Sample

1st row보광로 고갯마루 쉼터 인근
2nd row보광로 산3-13 인근
3rd row호국로 1군단 인근
4th row호국로 목암삼거리 인근
5th row푸른마을로 목암초등학교 인근
ValueCountFrequency (%)
앞 134
 
13.0%
인근 23
 
2.2%
중산동 20
 
1.9%
일산동 18
 
1.7%
식사동 12
 
1.2%
삼거리 11
 
1.1%
정문 11
 
1.1%
고양대로 11
 
1.1%
풍동 10
 
1.0%
사거리 10
 
1.0%
Other values (592) 769
74.7%
2024-04-06T17:28:29.717299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
692
 
13.0%
앞 193
 
3.6%
로 171
 
3.2%
동 165
 
3.1%
1 142
 
2.7%
) 129
 
2.4%
( 129
 
2.4%
리 125
 
2.3%
사 110
 
2.1%
지 105
 
2.0%
Other values (334) 3360
63.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3689
69.3%
Space Separator 692
 
13.0%
Decimal Number 589
 
11.1%
Close Punctuation 129
 
2.4%
Open Punctuation 129
 
2.4%
Dash Punctuation 39
 
0.7%
Uppercase Letter 30
 
0.6%
Other Punctuation 20
 
0.4%
Math Symbol 3
 
0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
앞 193
 
5.2%
로 171
 
4.6%
동 165
 
4.5%
리 125
 
3.4%
사 110
 
3.0%
지 105
 
2.8%
거 102
 
2.8%
산 97
 
2.6%
교 81
 
2.2%
일 78
 
2.1%
Other values (306) 2462
66.7%
Decimal Number
ValueCountFrequency (%)
1 142
24.1%
2 80
13.6%
0 64
10.9%
3 52
 
8.8%
8 47
 
8.0%
5 47
 
8.0%
4 47
 
8.0%
7 42
 
7.1%
6 39
 
6.6%
9 29
 
4.9%
Uppercase Letter
ValueCountFrequency (%)
C 6
20.0%
I 5
16.7%
S 4
13.3%
G 4
13.3%
B 3
10.0%
L 2
 
6.7%
Y 2
 
6.7%
M 2
 
6.7%
K 1
 
3.3%
W 1
 
3.3%
Other Punctuation
ValueCountFrequency (%)
# 10
50.0%
, 10
50.0%
Space Separator
ValueCountFrequency (%)
692
100.0%
Close Punctuation
ValueCountFrequency (%)
) 129
100.0%
Open Punctuation
ValueCountFrequency (%)
( 129
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 39
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3689
69.3%
Common 1601
30.1%
Latin 31
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앞 193
 
5.2%
로 171
 
4.6%
동 165
 
4.5%
리 125
 
3.4%
사 110
 
3.0%
지 105
 
2.8%
거 102
 
2.8%
산 97
 
2.6%
교 81
 
2.2%
일 78
 
2.1%
Other values (306) 2462
66.7%
Common
ValueCountFrequency (%)
692
43.2%
1 142
 
8.9%
) 129
 
8.1%
( 129
 
8.1%
2 80
 
5.0%
0 64
 
4.0%
3 52
 
3.2%
8 47
 
2.9%
5 47
 
2.9%
4 47
 
2.9%
Other values (7) 172
 
10.7%
Latin
ValueCountFrequency (%)
C 6
19.4%
I 5
16.1%
S 4
12.9%
G 4
12.9%
B 3
9.7%
L 2
 
6.5%
Y 2
 
6.5%
M 2
 
6.5%
K 1
 
3.2%
W 1
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3689
69.3%
ASCII 1632
30.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
692
42.4%
1 142
 
8.7%
) 129
 
7.9%
( 129
 
7.9%
2 80
 
4.9%
0 64
 
3.9%
3 52
 
3.2%
8 47
 
2.9%
5 47
 
2.9%
4 47
 
2.9%
Other values (18) 203
 
12.4%
Hangul
ValueCountFrequency (%)
앞 193
 
5.2%
로 171
 
4.6%
동 165
 
4.5%
리 125
 
3.4%
사 110
 
3.0%
지 105
 
2.8%
거 102
 
2.8%
산 97
 
2.6%
교 81
 
2.2%
일 78
 
2.1%
Other values (306) 2462
66.7%

소재지도로명주소
Text

Distinct262
Distinct (%)77.1%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2024-04-06T17:28:30.569814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length25
Mean length19.832353
Min length12

Characters and Unicode

Total characters6743
Distinct characters129
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique224 ?
Unique (%)65.9%

Sample

1st row경기도 고양시 덕양구 보광로 379
2nd row경기도 고양시 덕양구 보광로 285
3rd row경기도 고양시 호국로
4th row경기도 고양시 호국로
5th row경기도 고양시 덕양구 푸른마을로 63
ValueCountFrequency (%)
경기도 340
21.6%
고양시 340
21.6%
일산서구 181
 
11.5%
일산동구 79
 
5.0%
일산동 40
 
2.5%
덕이동 23
 
1.5%
덕양구 16
 
1.0%
중앙로 15
 
1.0%
일산로 14
 
0.9%
대화동 14
 
0.9%
Other values (338) 513
32.6%
2024-04-06T17:28:31.888195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1298
19.2%
양 369
 
5.5%
고 354
 
5.2%
시 346
 
5.1%
도 344
 
5.1%
산 342
 
5.1%
경 341
 
5.1%
기 340
 
5.0%
일 328
 
4.9%
구 281
 
4.2%
Other values (119) 2400
35.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4324
64.1%
Space Separator 1298
 
19.2%
Decimal Number 1023
 
15.2%
Dash Punctuation 94
 
1.4%
Uppercase Letter 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
양 369
 
8.5%
고 354
 
8.2%
시 346
 
8.0%
도 344
 
8.0%
산 342
 
7.9%
경 341
 
7.9%
기 340
 
7.9%
일 328
 
7.6%
구 281
 
6.5%
동 208
 
4.8%
Other values (105) 1071
24.8%
Decimal Number
ValueCountFrequency (%)
1 195
19.1%
2 126
12.3%
5 121
11.8%
6 118
11.5%
3 111
10.9%
4 102
10.0%
8 70
 
6.8%
0 67
 
6.5%
7 64
 
6.3%
9 49
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
C 2
50.0%
I 2
50.0%
Space Separator
ValueCountFrequency (%)
1298
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 94
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4324
64.1%
Common 2415
35.8%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
양 369
 
8.5%
고 354
 
8.2%
시 346
 
8.0%
도 344
 
8.0%
산 342
 
7.9%
경 341
 
7.9%
기 340
 
7.9%
일 328
 
7.6%
구 281
 
6.5%
동 208
 
4.8%
Other values (105) 1071
24.8%
Common
ValueCountFrequency (%)
1298
53.7%
1 195
 
8.1%
2 126
 
5.2%
5 121
 
5.0%
6 118
 
4.9%
3 111
 
4.6%
4 102
 
4.2%
- 94
 
3.9%
8 70
 
2.9%
0 67
 
2.8%
Other values (2) 113
 
4.7%
Latin
ValueCountFrequency (%)
C 2
50.0%
I 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4324
64.1%
ASCII 2419
35.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1298
53.7%
1 195
 
8.1%
2 126
 
5.2%
5 121
 
5.0%
6 118
 
4.9%
3 111
 
4.6%
4 102
 
4.2%
- 94
 
3.9%
8 70
 
2.9%
0 67
 
2.8%
Other values (4) 117
 
4.8%
Hangul
ValueCountFrequency (%)
양 369
 
8.5%
고 354
 
8.2%
시 346
 
8.0%
도 344
 
8.0%
산 342
 
7.9%
경 341
 
7.9%
기 340
 
7.9%
일 328
 
7.6%
구 281
 
6.5%
동 208
 
4.8%
Other values (105) 1071
24.8%

소재지지번주소
Text

Distinct294
Distinct (%)86.5%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2024-04-06T17:28:32.383929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length35
Mean length23.794118
Min length18

Characters and Unicode

Total characters8090
Distinct characters135
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique267 ?
Unique (%)78.5%

Sample

1st row경기도 고양시 덕양구 벽제동 4-4번지
2nd row경기도 고양시 덕양구 벽제동 618-2번지
3rd row경기도 고양시 덕양구 벽제동 111-5
4th row경기도 고양시 덕양구 벽제동 133-12
5th row경기도 고양시 덕양구 고양동 722번지
ValueCountFrequency (%)
경기도 340
19.4%
고양시 340
19.4%
일산서구 181
 
10.3%
일산동구 80
 
4.6%
덕양구 79
 
4.5%
일산동 73
 
4.2%
덕이동 33
 
1.9%
대화동 31
 
1.8%
중산동 19
 
1.1%
주엽동 16
 
0.9%
Other values (368) 558
31.9%
2024-04-06T17:28:33.280201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1410
17.4%
동 425
 
5.3%
양 423
 
5.2%
산 379
 
4.7%
시 344
 
4.3%
일 344
 
4.3%
구 344
 
4.3%
도 342
 
4.2%
고 342
 
4.2%
경 340
 
4.2%
Other values (125) 3397
42.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5046
62.4%
Decimal Number 1448
 
17.9%
Space Separator 1410
 
17.4%
Dash Punctuation 185
 
2.3%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 425
 
8.4%
양 423
 
8.4%
산 379
 
7.5%
시 344
 
6.8%
일 344
 
6.8%
구 344
 
6.8%
도 342
 
6.8%
고 342
 
6.8%
경 340
 
6.7%
기 340
 
6.7%
Other values (112) 1423
28.2%
Decimal Number
ValueCountFrequency (%)
1 309
21.3%
2 174
12.0%
5 153
10.6%
4 134
9.3%
0 134
9.3%
3 131
9.0%
6 121
 
8.4%
7 101
 
7.0%
8 99
 
6.8%
9 92
 
6.4%
Space Separator
ValueCountFrequency (%)
1410
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 185
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5046
62.4%
Common 3044
37.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 425
 
8.4%
양 423
 
8.4%
산 379
 
7.5%
시 344
 
6.8%
일 344
 
6.8%
구 344
 
6.8%
도 342
 
6.8%
고 342
 
6.8%
경 340
 
6.7%
기 340
 
6.7%
Other values (112) 1423
28.2%
Common
ValueCountFrequency (%)
1410
46.3%
1 309
 
10.2%
- 185
 
6.1%
2 174
 
5.7%
5 153
 
5.0%
4 134
 
4.4%
0 134
 
4.4%
3 131
 
4.3%
6 121
 
4.0%
7 101
 
3.3%
Other values (3) 192
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5046
62.4%
ASCII 3044
37.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1410
46.3%
1 309
 
10.2%
- 185
 
6.1%
2 174
 
5.7%
5 153
 
5.0%
4 134
 
4.4%
0 134
 
4.4%
3 131
 
4.3%
6 121
 
4.0%
7 101
 
3.3%
Other values (3) 192
 
6.3%
Hangul
ValueCountFrequency (%)
동 425
 
8.4%
양 423
 
8.4%
산 379
 
7.5%
시 344
 
6.8%
일 344
 
6.8%
구 344
 
6.8%
도 342
 
6.8%
고 342
 
6.8%
경 340
 
6.7%
기 340
 
6.7%
Other values (112) 1423
28.2%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct327
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.6749
Minimum37.36883
Maximum37.747068
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-04-06T17:28:33.592839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.36883
5-th percentile37.61673
Q137.667147
median37.682534
Q337.69319
95-th percentile37.708715
Maximum37.747068
Range0.37823776
Interquartile range (IQR)0.026042565

Descriptive statistics

Standard deviation0.034993342
Coefficient of variation (CV)0.00092882376
Kurtosis32.978152
Mean37.6749
Median Absolute Deviation (MAD)0.012590175
Skewness-4.3166348
Sum12809.466
Variance0.001224534
MonotonicityNot monotonic
2024-04-06T17:28:33.893566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.6670849 3
 
0.9%
37.677301 2
 
0.6%
37.61071788 2
 
0.6%
37.67332109 2
 
0.6%
37.677601 2
 
0.6%
37.66202282 2
 
0.6%
37.59966954 2
 
0.6%
37.6694411 2
 
0.6%
37.696901 2
 
0.6%
37.697201 2
 
0.6%
Other values (317) 319
93.8%
ValueCountFrequency (%)
37.36883012 1
0.3%
37.37066101 1
0.3%
37.59346916 1
0.3%
37.59561218 1
0.3%
37.5982738 1
0.3%
37.59966954 2
0.6%
37.60405437 1
0.3%
37.60494078 1
0.3%
37.60502802 1
0.3%
37.60544319 1
0.3%
ValueCountFrequency (%)
37.74706788 1
0.3%
37.7394012 1
0.3%
37.7251492 1
0.3%
37.717401 1
0.3%
37.71734666 1
0.3%
37.716801 1
0.3%
37.7154001 1
0.3%
37.714501 1
0.3%
37.71395527 1
0.3%
37.713801 1
0.3%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct329
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.78992
Minimum126.37605
Maximum126.95627
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-04-06T17:28:34.237595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.37605
5-th percentile126.73323
Q1126.76088
median126.77496
Q3126.81854
95-th percentile126.89293
Maximum126.95627
Range0.5802214
Interquartile range (IQR)0.057661775

Descriptive statistics

Standard deviation0.057466302
Coefficient of variation (CV)0.00045324031
Kurtosis14.935107
Mean126.78992
Median Absolute Deviation (MAD)0.02419985
Skewness-1.5512267
Sum43108.573
Variance0.0033023758
MonotonicityNot monotonic
2024-04-06T17:28:34.538997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.746817 3
 
0.9%
126.753589 2
 
0.6%
126.736619 2
 
0.6%
126.737079 2
 
0.6%
126.8134001 2
 
0.6%
126.8351487 2
 
0.6%
126.754675 2
 
0.6%
126.8205408 2
 
0.6%
126.8732916 2
 
0.6%
126.8055001 2
 
0.6%
Other values (319) 319
93.8%
ValueCountFrequency (%)
126.3760497 1
0.3%
126.3766967 1
0.3%
126.7107664 1
0.3%
126.7108168 1
0.3%
126.715915701 1
0.3%
126.716863 1
0.3%
126.7182846 1
0.3%
126.718508601 1
0.3%
126.718922601 1
0.3%
126.720903 1
0.3%
ValueCountFrequency (%)
126.9562711 1
0.3%
126.9511887 1
0.3%
126.9481668 1
0.3%
126.9205289 1
0.3%
126.9139739 1
0.3%
126.912779 1
0.3%
126.912191 1
0.3%
126.9091101 1
0.3%
126.9090899 1
0.3%
126.9077842 1
0.3%

제설함수
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
1
340 

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 (%)
1 340
100.0%

Length

2024-04-06T17:28:34.876037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:28:35.134245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 340
100.0%

염화칼슘비치량
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
3
260 
5
80 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 260
76.5%
5 80
 
23.5%

Length

2024-04-06T17:28:35.369981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:28:35.586179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 260
76.5%
5 80
 
23.5%

소금비치량
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing340
Missing (%)100.0%
Memory size3.1 KiB

모래비치량
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing340
Missing (%)100.0%
Memory size3.1 KiB

관리기관명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
일산서구청 안전건설과
181 
일산동구청 안전건설과
80 
덕양구청 안전건설과
79 

Length

Max length11
Median length11
Mean length10.767647
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row덕양구청 안전건설과
2nd row덕양구청 안전건설과
3rd row덕양구청 안전건설과
4th row덕양구청 안전건설과
5th row덕양구청 안전건설과

Common Values

ValueCountFrequency (%)
일산서구청 안전건설과 181
53.2%
일산동구청 안전건설과 80
23.5%
덕양구청 안전건설과 79
23.2%

Length

2024-04-06T17:28:35.836268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:28:36.073382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
안전건설과 340
50.0%
일산서구청 181
26.6%
일산동구청 80
 
11.8%
덕양구청 79
 
11.6%

관리기관전화번호
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
031-8075-7314
181 
031-8075-6312
80 
031-8075-5314
79 

Length

Max length13
Median length13
Mean length13
Min length13

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row031-8075-5314
2nd row031-8075-5314
3rd row031-8075-5314
4th row031-8075-5314
5th row031-8075-5314

Common Values

ValueCountFrequency (%)
031-8075-7314 181
53.2%
031-8075-6312 80
23.5%
031-8075-5314 79
23.2%

Length

2024-04-06T17:28:36.747737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:28:36.987520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
031-8075-7314 181
53.2%
031-8075-6312 80
23.5%
031-8075-5314 79
23.2%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2024-03-29
340 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-03-29
2nd row2024-03-29
3rd row2024-03-29
4th row2024-03-29
5th row2024-03-29

Common Values

ValueCountFrequency (%)
2024-03-29 340
100.0%

Length

2024-04-06T17:28:37.238075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:28:37.442178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-03-29 340
100.0%

Interactions

2024-04-06T17:28:25.006252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:24.440297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:25.218261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:28:24.775311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:28:37.669607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동명위도경도염화칼슘비치량관리기관명관리기관전화번호
읍면동명1.0000.9670.9671.0001.0001.000
위도0.9671.0000.6160.2240.8080.808
경도0.9670.6161.0000.9350.9840.984
염화칼슘비치량1.0000.2240.9351.0001.0001.000
관리기관명1.0000.8080.9841.0001.0001.000
관리기관전화번호1.0000.8080.9841.0001.0001.000
2024-04-06T17:28:37.936358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리기관전화번호읍면동명염화칼슘비치량관리기관명
관리기관전화번호1.0000.9290.9991.000
읍면동명0.9291.0000.9280.929
염화칼슘비치량0.9990.9281.0000.999
관리기관명1.0000.9290.9991.000
2024-04-06T17:28:38.227577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도읍면동명염화칼슘비치량관리기관명관리기관전화번호
위도1.000-0.2600.7690.1600.4880.488
경도-0.2601.0000.7690.7680.8400.840
읍면동명0.7690.7691.0000.9280.9290.929
염화칼슘비치량0.1600.7680.9281.0000.9990.999
관리기관명0.4880.8400.9290.9991.0001.000
관리기관전화번호0.4880.8400.9290.9991.0001.000

Missing values

2024-04-06T17:28:25.477598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:28:25.919784image/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

시군명읍면동명관리번호설치장소명소재지도로명주소소재지지번주소위도경도제설함수염화칼슘비치량소금비치량모래비치량관리기관명관리기관전화번호데이터기준일자
0고양시벽제동덕양구-1보광로 고갯마루 쉼터 인근경기도 고양시 덕양구 보광로 379경기도 고양시 덕양구 벽제동 4-4번지37.747068126.91219113<NA><NA>덕양구청 안전건설과031-8075-53142024-03-29
1고양시벽제동덕양구-2보광로 산3-13 인근경기도 고양시 덕양구 보광로 285경기도 고양시 덕양구 벽제동 618-2번지37.739401126.91277913<NA><NA>덕양구청 안전건설과031-8075-53142024-03-29
2고양시벽제동덕양구-3호국로 1군단 인근경기도 고양시 호국로경기도 고양시 덕양구 벽제동 111-537.717347126.91397413<NA><NA>덕양구청 안전건설과031-8075-53142024-03-29
3고양시벽제동덕양구-4호국로 목암삼거리 인근경기도 고양시 호국로경기도 고양시 덕양구 벽제동 133-1237.713955126.9090913<NA><NA>덕양구청 안전건설과031-8075-53142024-03-29
4고양시고양동덕양구-5푸른마을로 목암초등학교 인근경기도 고양시 덕양구 푸른마을로 63경기도 고양시 덕양구 고양동 722번지37.713735126.90458813<NA><NA>덕양구청 안전건설과031-8075-53142024-03-29
5고양시대자동덕양구-6대양로 대자동 회전교차로경기도 고양시 대양로경기도 고양시 덕양구 대자동 1066-737.694908126.87880613<NA><NA>덕양구청 안전건설과031-8075-53142024-03-29
6고양시관산동덕양구-7YBM물류센터, 중장비학원경기도 고양시 동헌로경기도 고양시 덕양구 관산동 산70-1237.707649126.87208313<NA><NA>덕양구청 안전건설과031-8075-53142024-03-29
7고양시대자동덕양구-8동헌로 간촌삼거리경기도 고양시 동헌로경기도 고양시 덕양구 대자동 826-437.708269126.87825113<NA><NA>덕양구청 안전건설과031-8075-53142024-03-29
8고양시대자동덕양구-9동헌로 중부대학교 인근경기도 고양시 동헌로경기도 고양시 덕양구 대자동 611-337.711514126.88872513<NA><NA>덕양구청 안전건설과031-8075-53142024-03-29
9고양시원당동덕양구-10호국로 낙타고개 군부대 인근경기도 고양시 호국로경기도 고양시 덕양구 원당동 산 38-5137.673543126.86775613<NA><NA>덕양구청 안전건설과031-8075-53142024-03-29
시군명읍면동명관리번호설치장소명소재지도로명주소소재지지번주소위도경도제설함수염화칼슘비치량소금비치량모래비치량관리기관명관리기관전화번호데이터기준일자
330고양시덕이동덕이동-24덕이로292번길 13(오일뱅크주유소) 앞경기도 고양시 일산서구 덕이동 1510-3경기도 고양시 일산서구 덕이동 1510-337.702643126.7329413<NA><NA>일산서구청 안전건설과031-8075-73142024-03-29
331고양시덕이동덕이동-25탄현마을교 초입 버스정류장(20130) 부근경기도 고양시 일산서구 덕이동 304-6경기도 고양시 일산서구 덕이동 304-637.699277126.75975813<NA><NA>일산서구청 안전건설과031-8075-73142024-03-29
332고양시덕이동덕이동-26탄현덕이보도육교 (광성교회 뒤)경기도 고양시 일산서구 덕이동 336경기도 고양시 일산서구 덕이동 33637.703519126.75467513<NA><NA>일산서구청 안전건설과031-8075-73142024-03-29
333고양시덕이동덕이동-26하이파크1육교경기도 고양시 일산서구 덕이동 336경기도 고양시 일산서구 덕이동 33637.703519126.75467513<NA><NA>일산서구청 안전건설과031-8075-73142024-03-29
334고양시덕이동덕이동-27하이파크2육교경기도 고양시 일산서구 덕이동 346-1경기도 고양시 일산서구 덕이동 346-137.700828126.75188313<NA><NA>일산서구청 안전건설과031-8075-73142024-03-29
335고양시덕이동덕이동-28하이파크3육교경기도 고양시 일산서구 덕이동 산142-3경기도 고양시 일산서구 덕이동 1524번지 하이파크시티일산아이파크1단지37.700034126.75133113<NA><NA>일산서구청 안전건설과031-8075-73142024-03-29
336고양시덕이동덕이동-29하이파크4육교경기도 고양시 일산서구 덕이동 374-2경기도 고양시 일산서구 덕이동 1535번지 하이파크시티일산파밀리에4단지37.697657126.75223413<NA><NA>일산서구청 안전건설과031-8075-73142024-03-29
337고양시덕이동덕이동-29덕이 스카이캐슬 앞경기도 고양시 일산서구 덕이동 739-37경기도 고양시 일산서구 덕이동 739-3737.699235126.74026613<NA><NA>일산서구청 안전건설과031-8075-73142024-03-29
338고양시덕이동덕이동-29삼성홈타운 진입도로(경사로)경기도 고양시 일산서구 덕이동 379-47경기도 고양시 일산서구 덕이동 379-4737.69485126.75388813<NA><NA>일산서구청 안전건설과031-8075-73142024-03-29
339고양시덕이동덕이동-29하이파크로 145 (명장10 건너편)경기도 고양시 일산서구 덕이동 330-2경기도 고양시 일산서구 덕이동 330-237.703926126.75679113<NA><NA>일산서구청 안전건설과031-8075-73142024-03-29