Overview

Dataset statistics

Number of variables7
Number of observations232
Missing cells76
Missing cells (%)4.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.3 KiB
Average record size in memory58.6 B

Variable types

Text4
Numeric2
DateTime1

Dataset

Description서울특별시 서초구 서리풀 원두막(그늘막) 현황에 대한 데이터로 관리번호, 도로명주소, 지번주소, 설치위치, 위도, 경도 등을 제공합니다.
URLhttps://www.data.go.kr/data/15117442/fileData.do

Alerts

데이터 기준일 has constant value ""Constant
도로명주소 has 51 (22.0%) missing valuesMissing
지번주소 has 25 (10.8%) missing valuesMissing
관리번호 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique

Reproduction

Analysis started2023-12-12 21:57:09.612447
Analysis finished2023-12-12 21:57:11.169511
Duration1.56 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Text

UNIQUE 

Distinct232
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-13T06:57:11.370801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length2.9008621
Min length1

Characters and Unicode

Total characters673
Distinct characters30
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

Unique232 ?
Unique (%)100.0%

Sample

1st row1
2nd row2
3rd row3
4th row4
5th row6
ValueCountFrequency (%)
1 1
 
0.4%
164 1
 
0.4%
178 1
 
0.4%
153 1
 
0.4%
154 1
 
0.4%
155 1
 
0.4%
156 1
 
0.4%
157 1
 
0.4%
158 1
 
0.4%
159 1
 
0.4%
Other values (222) 222
95.7%
2023-12-13T06:57:11.844636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 157
23.3%
2 62
 
9.2%
3 44
 
6.5%
4 44
 
6.5%
7 43
 
6.4%
9 43
 
6.4%
6 43
 
6.4%
8 42
 
6.2%
0 41
 
6.1%
5 40
 
5.9%
Other values (20) 114
16.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 559
83.1%
Other Letter 113
 
16.8%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 25
22.1%
관 15
13.3%
리 12
10.6%
물 12
10.6%
보 4
 
3.5%
성 4
 
3.5%
여 4
 
3.5%
육 4
 
3.5%
지 3
 
2.7%
문 3
 
2.7%
Other values (9) 27
23.9%
Decimal Number
ValueCountFrequency (%)
1 157
28.1%
2 62
 
11.1%
3 44
 
7.9%
4 44
 
7.9%
7 43
 
7.7%
9 43
 
7.7%
6 43
 
7.7%
8 42
 
7.5%
0 41
 
7.3%
5 40
 
7.2%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 560
83.2%
Hangul 113
 
16.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 25
22.1%
관 15
13.3%
리 12
10.6%
물 12
10.6%
보 4
 
3.5%
성 4
 
3.5%
여 4
 
3.5%
육 4
 
3.5%
지 3
 
2.7%
문 3
 
2.7%
Other values (9) 27
23.9%
Common
ValueCountFrequency (%)
1 157
28.0%
2 62
 
11.1%
3 44
 
7.9%
4 44
 
7.9%
7 43
 
7.7%
9 43
 
7.7%
6 43
 
7.7%
8 42
 
7.5%
0 41
 
7.3%
5 40
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 560
83.2%
Hangul 113
 
16.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 157
28.0%
2 62
 
11.1%
3 44
 
7.9%
4 44
 
7.9%
7 43
 
7.7%
9 43
 
7.7%
6 43
 
7.7%
8 42
 
7.5%
0 41
 
7.3%
5 40
 
7.1%
Hangul
ValueCountFrequency (%)
과 25
22.1%
관 15
13.3%
리 12
10.6%
물 12
10.6%
보 4
 
3.5%
성 4
 
3.5%
여 4
 
3.5%
육 4
 
3.5%
지 3
 
2.7%
문 3
 
2.7%
Other values (9) 27
23.9%

도로명주소
Text

MISSING 

Distinct155
Distinct (%)85.6%
Missing51
Missing (%)22.0%
Memory size1.9 KiB
2023-12-13T06:57:12.175371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length27
Mean length16.834254
Min length4

Characters and Unicode

Total characters3047
Distinct characters121
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique134 ?
Unique (%)74.0%

Sample

1st row서초구 남부순환로 2583 (서초동)
2nd row서초구 반포대로 222 (반포동)
3rd row서초구 서초대로 지하294 (서초동)
4th row서초구 서초중앙로 72 (서초동)
5th row서초구 서초대로 396 (서초동)
ValueCountFrequency (%)
서초구 163
24.1%
서초동 47
 
6.9%
반포동 26
 
3.8%
방배동 22
 
3.2%
서초대로 20
 
3.0%
잠원동 19
 
2.8%
양재동 16
 
2.4%
강남대로 14
 
2.1%
방배로 14
 
2.1%
반포대로 13
 
1.9%
Other values (196) 323
47.7%
2023-12-13T06:57:12.646658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
496
16.3%
서 247
 
8.1%
초 243
 
8.0%
로 178
 
5.8%
구 163
 
5.3%
동 151
 
5.0%
( 145
 
4.8%
) 145
 
4.8%
2 91
 
3.0%
1 82
 
2.7%
Other values (111) 1106
36.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1747
57.3%
Decimal Number 498
 
16.3%
Space Separator 496
 
16.3%
Open Punctuation 145
 
4.8%
Close Punctuation 145
 
4.8%
Other Punctuation 11
 
0.4%
Dash Punctuation 5
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 247
14.1%
초 243
13.9%
로 178
 
10.2%
구 163
 
9.3%
동 151
 
8.6%
대 74
 
4.2%
반 59
 
3.4%
포 59
 
3.4%
방 46
 
2.6%
배 43
 
2.5%
Other values (96) 484
27.7%
Decimal Number
ValueCountFrequency (%)
2 91
18.3%
1 82
16.5%
3 63
12.7%
5 51
10.2%
4 44
8.8%
8 37
7.4%
9 37
7.4%
0 35
 
7.0%
6 30
 
6.0%
7 28
 
5.6%
Space Separator
ValueCountFrequency (%)
496
100.0%
Open Punctuation
ValueCountFrequency (%)
( 145
100.0%
Close Punctuation
ValueCountFrequency (%)
) 145
100.0%
Other Punctuation
ValueCountFrequency (%)
, 11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1747
57.3%
Common 1300
42.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 247
14.1%
초 243
13.9%
로 178
 
10.2%
구 163
 
9.3%
동 151
 
8.6%
대 74
 
4.2%
반 59
 
3.4%
포 59
 
3.4%
방 46
 
2.6%
배 43
 
2.5%
Other values (96) 484
27.7%
Common
ValueCountFrequency (%)
496
38.2%
( 145
 
11.2%
) 145
 
11.2%
2 91
 
7.0%
1 82
 
6.3%
3 63
 
4.8%
5 51
 
3.9%
4 44
 
3.4%
8 37
 
2.8%
9 37
 
2.8%
Other values (5) 109
 
8.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1747
57.3%
ASCII 1300
42.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
496
38.2%
( 145
 
11.2%
) 145
 
11.2%
2 91
 
7.0%
1 82
 
6.3%
3 63
 
4.8%
5 51
 
3.9%
4 44
 
3.4%
8 37
 
2.8%
9 37
 
2.8%
Other values (5) 109
 
8.4%
Hangul
ValueCountFrequency (%)
서 247
14.1%
초 243
13.9%
로 178
 
10.2%
구 163
 
9.3%
동 151
 
8.6%
대 74
 
4.2%
반 59
 
3.4%
포 59
 
3.4%
방 46
 
2.6%
배 43
 
2.5%
Other values (96) 484
27.7%

지번주소
Text

MISSING 

Distinct177
Distinct (%)85.5%
Missing25
Missing (%)10.8%
Memory size1.9 KiB
2023-12-13T06:57:13.058224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length20
Mean length13.405797
Min length7

Characters and Unicode

Total characters2775
Distinct characters45
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

Unique155 ?
Unique (%)74.9%

Sample

1st row서초구 서초동 1366-12
2nd row서초구 반포동 505
3rd row서초구 서초동 1748-4
4th row서초구 서초동 1624-1
5th row서초구 서초동 1321-4
ValueCountFrequency (%)
서초구 191
30.3%
서초동 60
 
9.5%
방배동 41
 
6.5%
반포동 30
 
4.8%
잠원동 26
 
4.1%
서울특별시 23
 
3.6%
양재동 21
 
3.3%
우면동 11
 
1.7%
내곡동 6
 
1.0%
신원동 4
 
0.6%
Other values (179) 218
34.5%
2023-12-13T06:57:13.637328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
425
15.3%
서 284
 
10.2%
초 258
 
9.3%
동 207
 
7.5%
1 203
 
7.3%
구 191
 
6.9%
- 150
 
5.4%
2 104
 
3.7%
3 93
 
3.4%
4 81
 
2.9%
Other values (35) 779
28.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1346
48.5%
Decimal Number 854
30.8%
Space Separator 425
 
15.3%
Dash Punctuation 150
 
5.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 284
21.1%
초 258
19.2%
동 207
15.4%
구 191
14.2%
방 41
 
3.0%
배 41
 
3.0%
원 30
 
2.2%
포 30
 
2.2%
반 30
 
2.2%
잠 26
 
1.9%
Other values (23) 208
15.5%
Decimal Number
ValueCountFrequency (%)
1 203
23.8%
2 104
12.2%
3 93
10.9%
4 81
 
9.5%
5 79
 
9.3%
7 73
 
8.5%
8 69
 
8.1%
6 63
 
7.4%
0 56
 
6.6%
9 33
 
3.9%
Space Separator
ValueCountFrequency (%)
425
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 150
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1429
51.5%
Hangul 1346
48.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 284
21.1%
초 258
19.2%
동 207
15.4%
구 191
14.2%
방 41
 
3.0%
배 41
 
3.0%
원 30
 
2.2%
포 30
 
2.2%
반 30
 
2.2%
잠 26
 
1.9%
Other values (23) 208
15.5%
Common
ValueCountFrequency (%)
425
29.7%
1 203
14.2%
- 150
 
10.5%
2 104
 
7.3%
3 93
 
6.5%
4 81
 
5.7%
5 79
 
5.5%
7 73
 
5.1%
8 69
 
4.8%
6 63
 
4.4%
Other values (2) 89
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1429
51.5%
Hangul 1346
48.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
425
29.7%
1 203
14.2%
- 150
 
10.5%
2 104
 
7.3%
3 93
 
6.5%
4 81
 
5.7%
5 79
 
5.5%
7 73
 
5.1%
8 69
 
4.8%
6 63
 
4.4%
Other values (2) 89
 
6.2%
Hangul
ValueCountFrequency (%)
서 284
21.1%
초 258
19.2%
동 207
15.4%
구 191
14.2%
방 41
 
3.0%
배 41
 
3.0%
원 30
 
2.2%
포 30
 
2.2%
반 30
 
2.2%
잠 26
 
1.9%
Other values (23) 208
15.5%

설치위치
Text

Distinct223
Distinct (%)96.1%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-13T06:57:13.995148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length22
Mean length15.844828
Min length5

Characters and Unicode

Total characters3676
Distinct characters343
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique217 ?
Unique (%)93.5%

Sample

1st row서희건설 앞 교통섬(서초구청 건너)
2nd row서울성모병원 사거리 서래공원앞
3rd row교대역 12번출구 앞 교통섬
4th row서울교대 사거리
5th row진흥아파트 사거리횡단보도 강남빌딩 코너
ValueCountFrequency (%)
앞 136
 
16.9%
횡단보도 86
 
10.7%
교통섬 32
 
4.0%
사거리 23
 
2.9%
건너편 13
 
1.6%
양재천 11
 
1.4%
교차로 10
 
1.2%
1번출구 8
 
1.0%
옆 7
 
0.9%
정문 7
 
0.9%
Other values (347) 470
58.5%
2023-12-13T06:57:14.551945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
571
 
15.5%
앞 178
 
4.8%
도 99
 
2.7%
단 99
 
2.7%
보 96
 
2.6%
횡 92
 
2.5%
교 89
 
2.4%
리 69
 
1.9%
구 64
 
1.7%
서 64
 
1.7%
Other values (333) 2255
61.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2877
78.3%
Space Separator 571
 
15.5%
Decimal Number 153
 
4.2%
Close Punctuation 21
 
0.6%
Uppercase Letter 21
 
0.6%
Open Punctuation 20
 
0.5%
Lowercase Letter 6
 
0.2%
Dash Punctuation 2
 
0.1%
Other Punctuation 2
 
0.1%
Letter Number 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
앞 178
 
6.2%
도 99
 
3.4%
단 99
 
3.4%
보 96
 
3.3%
횡 92
 
3.2%
교 89
 
3.1%
리 69
 
2.4%
구 64
 
2.2%
서 64
 
2.2%
동 58
 
2.0%
Other values (298) 1969
68.4%
Uppercase Letter
ValueCountFrequency (%)
C 4
19.0%
G 2
9.5%
S 2
9.5%
R 2
9.5%
D 2
9.5%
K 2
9.5%
F 1
 
4.8%
A 1
 
4.8%
T 1
 
4.8%
W 1
 
4.8%
Other values (3) 3
14.3%
Decimal Number
ValueCountFrequency (%)
1 57
37.3%
2 25
16.3%
3 17
 
11.1%
0 15
 
9.8%
4 11
 
7.2%
5 8
 
5.2%
8 6
 
3.9%
6 6
 
3.9%
7 5
 
3.3%
9 3
 
2.0%
Lowercase Letter
ValueCountFrequency (%)
s 2
33.3%
g 2
33.3%
u 1
16.7%
c 1
16.7%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
50.0%
Ⅱ 1
50.0%
Space Separator
ValueCountFrequency (%)
571
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Other Punctuation
ValueCountFrequency (%)
& 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2877
78.3%
Common 770
 
20.9%
Latin 29
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앞 178
 
6.2%
도 99
 
3.4%
단 99
 
3.4%
보 96
 
3.3%
횡 92
 
3.2%
교 89
 
3.1%
리 69
 
2.4%
구 64
 
2.2%
서 64
 
2.2%
동 58
 
2.0%
Other values (298) 1969
68.4%
Latin
ValueCountFrequency (%)
C 4
13.8%
G 2
 
6.9%
S 2
 
6.9%
s 2
 
6.9%
g 2
 
6.9%
R 2
 
6.9%
D 2
 
6.9%
K 2
 
6.9%
F 1
 
3.4%
A 1
 
3.4%
Other values (9) 9
31.0%
Common
ValueCountFrequency (%)
571
74.2%
1 57
 
7.4%
2 25
 
3.2%
) 21
 
2.7%
( 20
 
2.6%
3 17
 
2.2%
0 15
 
1.9%
4 11
 
1.4%
5 8
 
1.0%
8 6
 
0.8%
Other values (6) 19
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2877
78.3%
ASCII 797
 
21.7%
Number Forms 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
571
71.6%
1 57
 
7.2%
2 25
 
3.1%
) 21
 
2.6%
( 20
 
2.5%
3 17
 
2.1%
0 15
 
1.9%
4 11
 
1.4%
5 8
 
1.0%
8 6
 
0.8%
Other values (23) 46
 
5.8%
Hangul
ValueCountFrequency (%)
앞 178
 
6.2%
도 99
 
3.4%
단 99
 
3.4%
보 96
 
3.3%
횡 92
 
3.2%
교 89
 
3.1%
리 69
 
2.4%
구 64
 
2.2%
서 64
 
2.2%
동 58
 
2.0%
Other values (298) 1969
68.4%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
50.0%
Ⅱ 1
50.0%

위도
Real number (ℝ)

UNIQUE 

Distinct232
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.488484
Minimum37.447119
Maximum37.520578
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-13T06:57:14.750870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.447119
5-th percentile37.457992
Q137.478381
median37.489775
Q337.501075
95-th percentile37.512884
Maximum37.520578
Range0.073459
Interquartile range (IQR)0.022693

Descriptive statistics

Standard deviation0.015623422
Coefficient of variation (CV)0.00041675257
Kurtosis-0.33769671
Mean37.488484
Median Absolute Deviation (MAD)0.0114075
Skewness-0.33255884
Sum8697.3284
Variance0.00024409132
MonotonicityNot monotonic
2023-12-13T06:57:14.948576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.484628 1
 
0.4%
37.457198 1
 
0.4%
37.511897 1
 
0.4%
37.487469 1
 
0.4%
37.474662 1
 
0.4%
37.490351 1
 
0.4%
37.491057 1
 
0.4%
37.455777 1
 
0.4%
37.518302 1
 
0.4%
37.493132 1
 
0.4%
Other values (222) 222
95.7%
ValueCountFrequency (%)
37.447119 1
0.4%
37.454348 1
0.4%
37.454368 1
0.4%
37.454508 1
0.4%
37.454514 1
0.4%
37.454646 1
0.4%
37.454736 1
0.4%
37.455777 1
0.4%
37.45647 1
0.4%
37.456965 1
0.4%
ValueCountFrequency (%)
37.520578 1
0.4%
37.519823 1
0.4%
37.518302 1
0.4%
37.517169 1
0.4%
37.51715 1
0.4%
37.516337 1
0.4%
37.515752 1
0.4%
37.515254 1
0.4%
37.514636 1
0.4%
37.513476 1
0.4%

경도
Real number (ℝ)

UNIQUE 

Distinct232
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.01391
Minimum126.98202
Maximum127.0638
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-13T06:57:15.128682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.98202
5-th percentile126.98295
Q1126.99792
median127.01254
Q3127.02669
95-th percentile127.04627
Maximum127.0638
Range0.081782
Interquartile range (IQR)0.02877225

Descriptive statistics

Standard deviation0.020056716
Coefficient of variation (CV)0.0001579096
Kurtosis-0.40013022
Mean127.01391
Median Absolute Deviation (MAD)0.0142695
Skewness0.35246084
Sum29467.227
Variance0.00040227187
MonotonicityNot monotonic
2023-12-13T06:57:15.337972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.033597 1
 
0.4%
127.015231 1
 
0.4%
127.009555 1
 
0.4%
126.984985 1
 
0.4%
126.98214 1
 
0.4%
127.01445 1
 
0.4%
127.004471 1
 
0.4%
127.062577 1
 
0.4%
127.014767 1
 
0.4%
127.011229 1
 
0.4%
Other values (222) 222
95.7%
ValueCountFrequency (%)
126.982022 1
0.4%
126.982127 1
0.4%
126.98214 1
0.4%
126.982263 1
0.4%
126.982289 1
0.4%
126.982462 1
0.4%
126.982531 1
0.4%
126.982549 1
0.4%
126.982673 1
0.4%
126.982745 1
0.4%
ValueCountFrequency (%)
127.063804 1
0.4%
127.06333 1
0.4%
127.062577 1
0.4%
127.061749 1
0.4%
127.06066 1
0.4%
127.060225 1
0.4%
127.060129 1
0.4%
127.05968 1
0.4%
127.059328 1
0.4%
127.056128 1
0.4%

데이터 기준일
Date

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
Minimum2023-07-25 00:00:00
Maximum2023-07-25 00:00:00
2023-12-13T06:57:15.513163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:57:15.622207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T06:57:10.281712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:57:10.023118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:57:10.736221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:57:10.140837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:57:15.699680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.838
경도0.8381.000
2023-12-13T06:57:15.809021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.000-0.413
경도-0.4131.000

Missing values

2023-12-13T06:57:10.883887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:57:11.021480image/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.
2023-12-13T06:57:11.125916image/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

관리번호도로명주소지번주소설치위치위도경도데이터 기준일
01서초구 남부순환로 2583 (서초동)서초구 서초동 1366-12서희건설 앞 교통섬(서초구청 건너)37.484628127.0335972023-07-25
12서초구 반포대로 222 (반포동)서초구 반포동 505서울성모병원 사거리 서래공원앞37.501782127.0031812023-07-25
23서초구 서초대로 지하294 (서초동)서초구 서초동 1748-4교대역 12번출구 앞 교통섬37.493588127.0139232023-07-25
34서초구 서초중앙로 72 (서초동)서초구 서초동 1624-1서울교대 사거리37.488313127.0148442023-07-25
46서초구 서초대로 396 (서초동)서초구 서초동 1321-4진흥아파트 사거리횡단보도 강남빌딩 코너37.496723127.0245082023-07-25
57서초구 강남대로 291 (서초동)서초구 서초동 1340-6뱅뱅사거리 횡단보도 스타벅스 앞37.489622127.0312452023-07-25
68서초구 반포대로 4 (서초동)서초구 서초동 1451-81예술의전당앞 교차로 커피빈 앞 교통섬37.480935127.0132452023-07-25
79서초구 반포대로 4 (서초동)서초구 서초동 1451-81예술의전당앞 교차로 한가람미술관 앞37.480567127.0134542023-07-25
810서초구 반포대로 3 (서초동)서초구 서초동 1464-30예술의전당앞 교차로 스타벅스 앞 교통섬37.480783127.0128262023-07-25
911서초구 반포대로 38 (서초동)서초구 서초동 1459-2서초3동 사거리 와라와라앞37.483936127.0118532023-07-25
관리번호도로명주소지번주소설치위치위도경도데이터 기준일
222물관리과7<NA><NA>양재천 수변 무대37.47619127.0406352023-07-25
223물관리과8<NA><NA>양재천 아이리스원(영동1교쪽 갈색데크)37.474231127.0376112023-07-25
224물관리과9<NA><NA>양재천 아이리스원(영동1교쪽 갈색데크)37.474237127.0375682023-07-25
225여성보육과14<NA>서초동1498-1서리풀문화광장137.490796127.0050472023-07-25
226여성보육과15<NA>서초동1498-1서리풀문화광장237.490759127.004952023-07-25
227여성보육과16<NA>서초동1498-1서리풀문화광장337.490674127.0048782023-07-25
228여성보육과17<NA>서초동1498-1서리풀문화광장437.490573127.0048032023-07-25
229자치행정과18<NA>서울 서초구 사임당로 89 서초1동주민자치센터서초1동청사 앞마당 137.489968127.0194772023-07-25
230자치행정과19<NA>서울 서초구 사임당로 89 서초1동주민자치센터서초1동청사 앞마당 237.489983127.0195162023-07-25
231자치행정과20<NA>서울 서초구 사임당로 89 서초1동주민자치센터서초1동청사 앞마당 337.489997127.0195532023-07-25