Overview

Dataset statistics

Number of variables16
Number of observations1701
Missing cells1736
Missing cells (%)6.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory219.4 KiB
Average record size in memory132.1 B

Variable types

Text4
Categorical7
Unsupported1
Numeric3
DateTime1

Dataset

Description관리번호,자치구,와이파이명,도로명주소,상세주소,설치위치(층),설치유형,설치기관,서비스구분,망종류,설치년도,실내외구분,wifi접속환경,X좌표,Y좌표,작업일자
Author강서구
URLhttps://data.seoul.go.kr/dataList/OA-20904/S/1/datasetView.do

Alerts

자치구 has constant value ""Constant
망종류 is highly overall correlated with 설치년도 and 4 other fieldsHigh correlation
wifi접속환경 is highly overall correlated with 설치년도 and 7 other fieldsHigh correlation
설치유형 is highly overall correlated with 설치년도 and 5 other fieldsHigh correlation
실내외구분 is highly overall correlated with 설치유형 and 3 other fieldsHigh correlation
서비스구분 is highly overall correlated with 설치년도 and 7 other fieldsHigh correlation
설치기관 is highly overall correlated with 설치년도 and 5 other fieldsHigh correlation
설치년도 is highly overall correlated with 설치유형 and 4 other fieldsHigh correlation
X좌표 is highly overall correlated with Y좌표 and 2 other fieldsHigh correlation
Y좌표 is highly overall correlated with X좌표 and 2 other fieldsHigh correlation
wifi접속환경 is highly imbalanced (93.9%)Imbalance
도로명주소 has 33 (1.9%) missing valuesMissing
설치위치(층) has 1701 (100.0%) missing valuesMissing
X좌표 is highly skewed (γ1 = 41.24059101)Skewed
Y좌표 is highly skewed (γ1 = -41.23899888)Skewed
관리번호 has unique valuesUnique
설치위치(층) is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-18 04:29:48.012204
Analysis finished2024-05-18 04:30:01.102065
Duration13.09 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Text

UNIQUE 

Distinct1701
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size13.4 KiB
2024-05-18T13:30:01.836872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length8
Mean length8.1046443
Min length7

Characters and Unicode

Total characters13786
Distinct characters24
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1701 ?
Unique (%)100.0%

Sample

1st rowBS100171
2nd rowBS100172
3rd rowBS100173
4th rowBS100174
5th rowBS100175
ValueCountFrequency (%)
bs100171 1
 
0.1%
sbs210588 1
 
0.1%
sbs210480 1
 
0.1%
sbs210475 1
 
0.1%
sbs210473 1
 
0.1%
sbs210466 1
 
0.1%
sbs210456 1
 
0.1%
sbs210439 1
 
0.1%
sbs210411 1
 
0.1%
sbs210400 1
 
0.1%
Other values (1691) 1691
99.4%
2024-05-18T13:30:03.673521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3284
23.8%
1 1685
12.2%
S 1331
9.7%
G 1182
 
8.6%
3 788
 
5.7%
2 751
 
5.4%
6 519
 
3.8%
9 507
 
3.7%
4 495
 
3.6%
5 484
 
3.5%
Other values (14) 2760
20.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9381
68.0%
Uppercase Letter 3573
 
25.9%
Other Letter 493
 
3.6%
Dash Punctuation 339
 
2.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3284
35.0%
1 1685
18.0%
3 788
 
8.4%
2 751
 
8.0%
6 519
 
5.5%
9 507
 
5.4%
4 495
 
5.3%
5 484
 
5.2%
8 447
 
4.8%
7 421
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
S 1331
37.3%
G 1182
33.1%
W 159
 
4.5%
F 159
 
4.5%
I 154
 
4.3%
M 154
 
4.3%
U 154
 
4.3%
L 154
 
4.3%
B 121
 
3.4%
H 5
 
0.1%
Other Letter
ValueCountFrequency (%)
울 239
48.5%
서 239
48.5%
차 15
 
3.0%
Dash Punctuation
ValueCountFrequency (%)
- 339
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9720
70.5%
Latin 3573
 
25.9%
Hangul 493
 
3.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3284
33.8%
1 1685
17.3%
3 788
 
8.1%
2 751
 
7.7%
6 519
 
5.3%
9 507
 
5.2%
4 495
 
5.1%
5 484
 
5.0%
8 447
 
4.6%
7 421
 
4.3%
Latin
ValueCountFrequency (%)
S 1331
37.3%
G 1182
33.1%
W 159
 
4.5%
F 159
 
4.5%
I 154
 
4.3%
M 154
 
4.3%
U 154
 
4.3%
L 154
 
4.3%
B 121
 
3.4%
H 5
 
0.1%
Hangul
ValueCountFrequency (%)
울 239
48.5%
서 239
48.5%
차 15
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13293
96.4%
Hangul 493
 
3.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3284
24.7%
1 1685
12.7%
S 1331
10.0%
G 1182
 
8.9%
3 788
 
5.9%
2 751
 
5.6%
6 519
 
3.9%
9 507
 
3.8%
4 495
 
3.7%
5 484
 
3.6%
Other values (11) 2267
17.1%
Hangul
ValueCountFrequency (%)
울 239
48.5%
서 239
48.5%
차 15
 
3.0%

자치구
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.4 KiB
강서구
1701 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
강서구 1701
100.0%

Length

2024-05-18T13:30:04.317729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T13:30:04.756121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강서구 1701
100.0%

와이파이명
Text

Distinct240
Distinct (%)14.1%
Missing0
Missing (%)0.0%
Memory size13.4 KiB
2024-05-18T13:30:05.384478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length25
Mean length6.3104056
Min length3

Characters and Unicode

Total characters10734
Distinct characters294
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique101 ?
Unique (%)5.9%

Sample

1st row버스정류소_KBS스포츠월드
2nd row버스정류소_KBS스포츠월드
3rd row버스정류소_KT가양지사
4th row버스정류소_KT가양지사
5th row버스정류소_가로공원.나누리병원
ValueCountFrequency (%)
서울식물원 154
 
8.9%
화곡1동 68
 
3.9%
화곡본동 51
 
3.0%
우장산역 49
 
2.8%
방화1동 45
 
2.6%
화곡4동 45
 
2.6%
방화2동 43
 
2.5%
우장산동 41
 
2.4%
화곡3동 38
 
2.2%
강서구청(본관 38
 
2.2%
Other values (239) 1155
66.9%
2024-05-18T13:30:06.621289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 763
 
7.1%
화 542
 
5.0%
서 381
 
3.5%
곡 344
 
3.2%
1 294
 
2.7%
관 269
 
2.5%
원 263
 
2.5%
지 244
 
2.3%
산 237
 
2.2%
강 215
 
2.0%
Other values (284) 7182
66.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9631
89.7%
Decimal Number 793
 
7.4%
Connector Punctuation 121
 
1.1%
Other Punctuation 48
 
0.4%
Open Punctuation 45
 
0.4%
Close Punctuation 45
 
0.4%
Space Separator 26
 
0.2%
Uppercase Letter 19
 
0.2%
Lowercase Letter 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 763
 
7.9%
화 542
 
5.6%
서 381
 
4.0%
곡 344
 
3.6%
관 269
 
2.8%
원 263
 
2.7%
지 244
 
2.5%
산 237
 
2.5%
강 215
 
2.2%
사 215
 
2.2%
Other values (256) 6158
63.9%
Decimal Number
ValueCountFrequency (%)
1 294
37.1%
2 141
17.8%
3 123
15.5%
4 89
 
11.2%
6 50
 
6.3%
5 34
 
4.3%
8 27
 
3.4%
7 18
 
2.3%
9 12
 
1.5%
0 5
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
K 4
21.1%
H 3
15.8%
W 2
10.5%
I 2
10.5%
S 2
10.5%
T 2
10.5%
B 2
10.5%
R 1
 
5.3%
D 1
 
5.3%
Other Punctuation
ValueCountFrequency (%)
. 39
81.2%
, 8
 
16.7%
& 1
 
2.1%
Lowercase Letter
ValueCountFrequency (%)
l 4
66.7%
i 2
33.3%
Connector Punctuation
ValueCountFrequency (%)
_ 121
100.0%
Open Punctuation
ValueCountFrequency (%)
( 45
100.0%
Close Punctuation
ValueCountFrequency (%)
) 45
100.0%
Space Separator
ValueCountFrequency (%)
26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9631
89.7%
Common 1078
 
10.0%
Latin 25
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 763
 
7.9%
화 542
 
5.6%
서 381
 
4.0%
곡 344
 
3.6%
관 269
 
2.8%
원 263
 
2.7%
지 244
 
2.5%
산 237
 
2.5%
강 215
 
2.2%
사 215
 
2.2%
Other values (256) 6158
63.9%
Common
ValueCountFrequency (%)
1 294
27.3%
2 141
13.1%
3 123
11.4%
_ 121
11.2%
4 89
 
8.3%
6 50
 
4.6%
( 45
 
4.2%
) 45
 
4.2%
. 39
 
3.6%
5 34
 
3.2%
Other values (7) 97
 
9.0%
Latin
ValueCountFrequency (%)
K 4
16.0%
l 4
16.0%
H 3
12.0%
i 2
8.0%
W 2
8.0%
I 2
8.0%
S 2
8.0%
T 2
8.0%
B 2
8.0%
R 1
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9631
89.7%
ASCII 1103
 
10.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 763
 
7.9%
화 542
 
5.6%
서 381
 
4.0%
곡 344
 
3.6%
관 269
 
2.8%
원 263
 
2.7%
지 244
 
2.5%
산 237
 
2.5%
강 215
 
2.2%
사 215
 
2.2%
Other values (256) 6158
63.9%
ASCII
ValueCountFrequency (%)
1 294
26.7%
2 141
12.8%
3 123
11.2%
_ 121
11.0%
4 89
 
8.1%
6 50
 
4.5%
( 45
 
4.1%
) 45
 
4.1%
. 39
 
3.5%
5 34
 
3.1%
Other values (18) 122
11.1%

도로명주소
Text

MISSING 

Distinct1227
Distinct (%)73.6%
Missing33
Missing (%)1.9%
Memory size13.4 KiB
2024-05-18T13:30:07.761770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length35
Mean length14.38729
Min length4

Characters and Unicode

Total characters23998
Distinct characters381
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

Unique1160 ?
Unique (%)69.5%

Sample

1st row등촌동 665-13
2nd row화곡동 1136-1
3rd row강서로 442
4th row가양동 1070답
5th row가로공원로 184-2
ValueCountFrequency (%)
강서구 260
 
5.0%
화곡동 248
 
4.8%
서울특별시 210
 
4.1%
161 155
 
3.0%
마곡동로 154
 
3.0%
2층 96
 
1.9%
방화동 78
 
1.5%
내발산동 71
 
1.4%
염창동 65
 
1.3%
양천로 64
 
1.2%
Other values (1384) 3762
72.9%
2024-05-18T13:30:09.502733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3720
 
15.5%
1 1573
 
6.6%
동 1124
 
4.7%
2 975
 
4.1%
- 896
 
3.7%
6 877
 
3.7%
로 850
 
3.5%
3 813
 
3.4%
화 706
 
2.9%
서 691
 
2.9%
Other values (371) 11773
49.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11477
47.8%
Decimal Number 7495
31.2%
Space Separator 3720
 
15.5%
Dash Punctuation 896
 
3.7%
Uppercase Letter 107
 
0.4%
Close Punctuation 106
 
0.4%
Open Punctuation 106
 
0.4%
Other Punctuation 56
 
0.2%
Lowercase Letter 22
 
0.1%
Connector Punctuation 13
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1124
 
9.8%
로 850
 
7.4%
화 706
 
6.2%
서 691
 
6.0%
곡 623
 
5.4%
강 428
 
3.7%
길 409
 
3.6%
구 312
 
2.7%
층 296
 
2.6%
시 264
 
2.3%
Other values (334) 5774
50.3%
Uppercase Letter
ValueCountFrequency (%)
F 32
29.9%
C 24
22.4%
V 11
 
10.3%
T 11
 
10.3%
P 10
 
9.3%
B 8
 
7.5%
D 3
 
2.8%
R 2
 
1.9%
A 2
 
1.9%
O 1
 
0.9%
Other values (3) 3
 
2.8%
Decimal Number
ValueCountFrequency (%)
1 1573
21.0%
2 975
13.0%
6 877
11.7%
3 813
10.8%
5 655
8.7%
4 650
8.7%
8 507
 
6.8%
7 489
 
6.5%
9 484
 
6.5%
0 472
 
6.3%
Other Punctuation
ValueCountFrequency (%)
, 23
41.1%
& 12
21.4%
; 11
19.6%
. 7
 
12.5%
/ 1
 
1.8%
? 1
 
1.8%
' 1
 
1.8%
Lowercase Letter
ValueCountFrequency (%)
t 11
50.0%
g 11
50.0%
Space Separator
ValueCountFrequency (%)
3720
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 896
100.0%
Close Punctuation
ValueCountFrequency (%)
) 106
100.0%
Open Punctuation
ValueCountFrequency (%)
( 106
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12392
51.6%
Hangul 11477
47.8%
Latin 129
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1124
 
9.8%
로 850
 
7.4%
화 706
 
6.2%
서 691
 
6.0%
곡 623
 
5.4%
강 428
 
3.7%
길 409
 
3.6%
구 312
 
2.7%
층 296
 
2.6%
시 264
 
2.3%
Other values (334) 5774
50.3%
Common
ValueCountFrequency (%)
3720
30.0%
1 1573
12.7%
2 975
 
7.9%
- 896
 
7.2%
6 877
 
7.1%
3 813
 
6.6%
5 655
 
5.3%
4 650
 
5.2%
8 507
 
4.1%
7 489
 
3.9%
Other values (12) 1237
 
10.0%
Latin
ValueCountFrequency (%)
F 32
24.8%
C 24
18.6%
t 11
 
8.5%
g 11
 
8.5%
V 11
 
8.5%
T 11
 
8.5%
P 10
 
7.8%
B 8
 
6.2%
D 3
 
2.3%
R 2
 
1.6%
Other values (5) 6
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12521
52.2%
Hangul 11477
47.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3720
29.7%
1 1573
12.6%
2 975
 
7.8%
- 896
 
7.2%
6 877
 
7.0%
3 813
 
6.5%
5 655
 
5.2%
4 650
 
5.2%
8 507
 
4.0%
7 489
 
3.9%
Other values (27) 1366
 
10.9%
Hangul
ValueCountFrequency (%)
동 1124
 
9.8%
로 850
 
7.4%
화 706
 
6.2%
서 691
 
6.0%
곡 623
 
5.4%
강 428
 
3.7%
길 409
 
3.6%
구 312
 
2.7%
층 296
 
2.6%
시 264
 
2.3%
Other values (334) 5774
50.3%

상세주소
Text

Distinct1423
Distinct (%)83.8%
Missing2
Missing (%)0.1%
Memory size13.4 KiB
2024-05-18T13:30:10.185622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length35
Mean length13.299588
Min length1

Characters and Unicode

Total characters22596
Distinct characters406
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

Unique1314 ?
Unique (%)77.3%

Sample

1st row16-009
2nd row16-010
3rd row16-223
4th row16-224
5th row16-199
ValueCountFrequency (%)
화곡동 239
 
5.3%
2층 132
 
2.9%
1층 87
 
1.9%
3층 75
 
1.7%
화곡6동 60
 
1.3%
식물문화센터 60
 
1.3%
염창동 58
 
1.3%
방화동 56
 
1.2%
야외 55
 
1.2%
복도 54
 
1.2%
Other values (1483) 3665
80.7%
2024-05-18T13:30:11.571555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3067
 
13.6%
1 1457
 
6.4%
- 869
 
3.8%
2 867
 
3.8%
동 843
 
3.7%
화 805
 
3.6%
3 689
 
3.0%
6 662
 
2.9%
4 607
 
2.7%
5 509
 
2.3%
Other values (396) 12221
54.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11180
49.5%
Decimal Number 6410
28.4%
Space Separator 3067
 
13.6%
Dash Punctuation 869
 
3.8%
Close Punctuation 371
 
1.6%
Open Punctuation 371
 
1.6%
Uppercase Letter 211
 
0.9%
Other Punctuation 59
 
0.3%
Connector Punctuation 36
 
0.2%
Lowercase Letter 20
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 843
 
7.5%
화 805
 
7.2%
곡 431
 
3.9%
층 413
 
3.7%
로 357
 
3.2%
지 261
 
2.3%
산 257
 
2.3%
장 255
 
2.3%
옥 236
 
2.1%
내 232
 
2.1%
Other values (355) 7090
63.4%
Uppercase Letter
ValueCountFrequency (%)
F 94
44.5%
C 27
 
12.8%
T 23
 
10.9%
B 18
 
8.5%
V 15
 
7.1%
P 14
 
6.6%
A 6
 
2.8%
E 3
 
1.4%
D 2
 
0.9%
H 2
 
0.9%
Other values (7) 7
 
3.3%
Decimal Number
ValueCountFrequency (%)
1 1457
22.7%
2 867
13.5%
3 689
10.7%
6 662
10.3%
4 607
9.5%
5 509
 
7.9%
8 443
 
6.9%
0 434
 
6.8%
7 374
 
5.8%
9 368
 
5.7%
Other Punctuation
ValueCountFrequency (%)
, 29
49.2%
; 10
 
16.9%
& 10
 
16.9%
. 5
 
8.5%
/ 4
 
6.8%
? 1
 
1.7%
Lowercase Letter
ValueCountFrequency (%)
t 10
50.0%
g 10
50.0%
Space Separator
ValueCountFrequency (%)
3067
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 869
100.0%
Close Punctuation
ValueCountFrequency (%)
) 371
100.0%
Open Punctuation
ValueCountFrequency (%)
( 371
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 36
100.0%
Other Symbol
ValueCountFrequency (%)
▲ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11185
49.5%
Hangul 11180
49.5%
Latin 231
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 843
 
7.5%
화 805
 
7.2%
곡 431
 
3.9%
층 413
 
3.7%
로 357
 
3.2%
지 261
 
2.3%
산 257
 
2.3%
장 255
 
2.3%
옥 236
 
2.1%
내 232
 
2.1%
Other values (355) 7090
63.4%
Common
ValueCountFrequency (%)
3067
27.4%
1 1457
13.0%
- 869
 
7.8%
2 867
 
7.8%
3 689
 
6.2%
6 662
 
5.9%
4 607
 
5.4%
5 509
 
4.6%
8 443
 
4.0%
0 434
 
3.9%
Other values (12) 1581
14.1%
Latin
ValueCountFrequency (%)
F 94
40.7%
C 27
 
11.7%
T 23
 
10.0%
B 18
 
7.8%
V 15
 
6.5%
P 14
 
6.1%
t 10
 
4.3%
g 10
 
4.3%
A 6
 
2.6%
E 3
 
1.3%
Other values (9) 11
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11414
50.5%
Hangul 11180
49.5%
Geometric Shapes 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3067
26.9%
1 1457
12.8%
- 869
 
7.6%
2 867
 
7.6%
3 689
 
6.0%
6 662
 
5.8%
4 607
 
5.3%
5 509
 
4.5%
8 443
 
3.9%
0 434
 
3.8%
Other values (30) 1810
15.9%
Hangul
ValueCountFrequency (%)
동 843
 
7.5%
화 805
 
7.2%
곡 431
 
3.9%
층 413
 
3.7%
로 357
 
3.2%
지 261
 
2.3%
산 257
 
2.3%
장 255
 
2.3%
옥 236
 
2.1%
내 232
 
2.1%
Other values (355) 7090
63.4%
Geometric Shapes
ValueCountFrequency (%)
▲ 2
100.0%

설치위치(층)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1701
Missing (%)100.0%
Memory size15.1 KiB

설치유형
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size13.4 KiB
1. 주요거리
527 
3. 공원(하천)
179 
6-1. 복지 - 사회
175 
4. 문화관광
143 
7-2-3. 공공 - 동주민센터
129 
Other values (14)
548 

Length

Max length21
Median length20
Mean length10.652557
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5-1. 버스정류소(국비)
2nd row5-1. 버스정류소(국비)
3rd row5-1. 버스정류소(국비)
4th row5-1. 버스정류소(국비)
5th row5-1. 버스정류소(국비)

Common Values

ValueCountFrequency (%)
1. 주요거리 527
31.0%
3. 공원(하천) 179
 
10.5%
6-1. 복지 - 사회 175
 
10.3%
4. 문화관광 143
 
8.4%
7-2-3. 공공 - 동주민센터 129
 
7.6%
5. 버스정류소 111
 
6.5%
5-1. 버스정류소(국비) 88
 
5.2%
7-2-2. 공공 - 구의회 및 보건소 74
 
4.4%
6-2. 복지 - 노인 53
 
3.1%
6-3. 복지 - 장애인 42
 
2.5%
Other values (9) 180
 
10.6%

Length

2024-05-18T13:30:12.129535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
586
 
12.2%
1 527
 
11.0%
주요거리 527
 
11.0%
복지 301
 
6.3%
공공 285
 
5.9%
3 187
 
3.9%
공원(하천 179
 
3.7%
사회 175
 
3.6%
6-1 175
 
3.6%
4 143
 
3.0%
Other values (33) 1717
35.8%

설치기관
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size13.4 KiB
자치구에스넷1차
668 
자치구
355 
서울시(AP)
304 
디지털뉴딜(KT)
198 
버스정류소(국비)
88 
Other values (4)
88 

Length

Max length12
Median length9
Mean length7.0617284
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row버스정류소(국비)
2nd row버스정류소(국비)
3rd row버스정류소(국비)
4th row버스정류소(국비)
5th row버스정류소(국비)

Common Values

ValueCountFrequency (%)
자치구에스넷1차 668
39.3%
자치구 355
20.9%
서울시(AP) 304
17.9%
디지털뉴딜(KT) 198
 
11.6%
버스정류소(국비) 88
 
5.2%
디지털뉴딜(LG U+) 41
 
2.4%
버스정류소(시비) 33
 
1.9%
서울시(공유기) 9
 
0.5%
서울시(LTE) 5
 
0.3%

Length

2024-05-18T13:30:12.741284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T13:30:13.327895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자치구에스넷1차 668
38.3%
자치구 355
20.4%
서울시(ap 304
17.5%
디지털뉴딜(kt 198
 
11.4%
버스정류소(국비 88
 
5.1%
디지털뉴딜(lg 41
 
2.4%
u 41
 
2.4%
버스정류소(시비 33
 
1.9%
서울시(공유기 9
 
0.5%
서울시(lte 5
 
0.3%

서비스구분
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size13.4 KiB
<NA>
1023 
공공WiFi
366 
과기부WiFi(복지시설)
159 
과기부WiFi
 
88
과기부WiFi(핫플레이스)
 
65

Length

Max length14
Median length4
Mean length5.8089359
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1023
60.1%
공공WiFi 366
 
21.5%
과기부WiFi(복지시설) 159
 
9.3%
과기부WiFi 88
 
5.2%
과기부WiFi(핫플레이스) 65
 
3.8%

Length

2024-05-18T13:30:14.042717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T13:30:14.575249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1023
60.1%
공공wifi 366
 
21.5%
과기부wifi(복지시설 159
 
9.3%
과기부wifi 88
 
5.2%
과기부wifi(핫플레이스 65
 
3.8%

망종류
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size13.4 KiB
자가망_U무선망
1208 
인터넷망_뉴딜용
239 
임대망
221 
<NA>
 
33

Length

Max length8
Median length8
Mean length7.2727807
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
자가망_U무선망 1208
71.0%
인터넷망_뉴딜용 239
 
14.1%
임대망 221
 
13.0%
<NA> 33
 
1.9%

Length

2024-05-18T13:30:15.058573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T13:30:15.470141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자가망_u무선망 1208
71.0%
인터넷망_뉴딜용 239
 
14.1%
임대망 221
 
13.0%
na 33
 
1.9%

설치년도
Real number (ℝ)

HIGH CORRELATION 

Distinct9
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2020.3039
Minimum2016
Maximum2024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.1 KiB
2024-05-18T13:30:15.808893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2016
5-th percentile2018
Q12020
median2020
Q32021
95-th percentile2023
Maximum2024
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.3987102
Coefficient of variation (CV)0.00069232665
Kurtosis-0.081502397
Mean2020.3039
Median Absolute Deviation (MAD)1
Skewness0.12884301
Sum3436537
Variance1.9563904
MonotonicityNot monotonic
2024-05-18T13:30:16.165849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
2020 723
42.5%
2022 290
17.0%
2021 217
 
12.8%
2019 184
 
10.8%
2018 163
 
9.6%
2023 76
 
4.5%
2017 26
 
1.5%
2024 21
 
1.2%
2016 1
 
0.1%
ValueCountFrequency (%)
2016 1
 
0.1%
2017 26
 
1.5%
2018 163
 
9.6%
2019 184
 
10.8%
2020 723
42.5%
2021 217
 
12.8%
2022 290
17.0%
2023 76
 
4.5%
2024 21
 
1.2%
ValueCountFrequency (%)
2024 21
 
1.2%
2023 76
 
4.5%
2022 290
17.0%
2021 217
 
12.8%
2020 723
42.5%
2019 184
 
10.8%
2018 163
 
9.6%
2017 26
 
1.5%
2016 1
 
0.1%

실내외구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.4 KiB
실외
1050 
실내
651 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
실외 1050
61.7%
실내 651
38.3%

Length

2024-05-18T13:30:16.626531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T13:30:16.956592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
실외 1050
61.7%
실내 651
38.3%

wifi접속환경
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.4 KiB
<NA>
1689 
10G 백홀, WIFI6E
 
12

Length

Max length14
Median length4
Mean length4.0705467
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 1689
99.3%
10G 백홀, WIFI6E 12
 
0.7%

Length

2024-05-18T13:30:17.303936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T13:30:17.761549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1689
97.9%
10g 12
 
0.7%
백홀 12
 
0.7%
wifi6e 12
 
0.7%

X좌표
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct1131
Distinct (%)66.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.60861
Minimum37.481415
Maximum126.83411
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.1 KiB
2024-05-18T13:30:18.118654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.481415
5-th percentile37.531876
Q137.54778
median37.556057
Q337.567223
95-th percentile37.57791
Maximum126.83411
Range89.352695
Interquartile range (IQR)0.019443

Descriptive statistics

Standard deviation2.1647179
Coefficient of variation (CV)0.057559104
Kurtosis1700.8575
Mean37.60861
Median Absolute Deviation (MAD)0.009993
Skewness41.240591
Sum63972.245
Variance4.6860036
MonotonicityNot monotonic
2024-05-18T13:30:18.540974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.570023 52
 
3.1%
37.550938 37
 
2.2%
37.56181 20
 
1.2%
37.570286 20
 
1.2%
37.55528 19
 
1.1%
37.564777 18
 
1.1%
37.564034 18
 
1.1%
37.565613 16
 
0.9%
37.571747 14
 
0.8%
37.56178 12
 
0.7%
Other values (1121) 1475
86.7%
ValueCountFrequency (%)
37.481415 2
0.1%
37.5283 1
0.1%
37.52841 1
0.1%
37.528427 1
0.1%
37.528477 1
0.1%
37.528774 1
0.1%
37.528904 1
0.1%
37.528954 1
0.1%
37.52897 1
0.1%
37.529007 1
0.1%
ValueCountFrequency (%)
126.83411 1
 
0.1%
37.5865 3
0.2%
37.586285 2
0.1%
37.586014 3
0.2%
37.585487 1
 
0.1%
37.58527 1
 
0.1%
37.584743 1
 
0.1%
37.584663 2
0.1%
37.58452 2
0.1%
37.58435 1
 
0.1%

Y좌표
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct1082
Distinct (%)63.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.78734
Minimum37.577824
Maximum126.94137
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.1 KiB
2024-05-18T13:30:19.047783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.577824
5-th percentile126.80786
Q1126.83209
median126.84204
Q3126.85149
95-th percentile126.86565
Maximum126.94137
Range89.363546
Interquartile range (IQR)0.0194

Descriptive statistics

Standard deviation2.1643579
Coefficient of variation (CV)0.017070773
Kurtosis1700.7699
Mean126.78734
Median Absolute Deviation (MAD)0.00963
Skewness-41.238999
Sum215665.26
Variance4.6844449
MonotonicityNot monotonic
2024-05-18T13:30:19.474818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.83503 53
 
3.1%
126.84964 37
 
2.2%
126.84158 20
 
1.2%
126.84319 20
 
1.2%
126.80476 20
 
1.2%
126.82501 19
 
1.1%
126.85543 18
 
1.1%
126.85225 16
 
0.9%
126.80582 14
 
0.8%
126.862144 14
 
0.8%
Other values (1072) 1470
86.4%
ValueCountFrequency (%)
37.577824 1
 
0.1%
126.79565 4
0.2%
126.79856 1
 
0.1%
126.79872 1
 
0.1%
126.798874 1
 
0.1%
126.79918 3
0.2%
126.799866 1
 
0.1%
126.80035 1
 
0.1%
126.8015 1
 
0.1%
126.80222 1
 
0.1%
ValueCountFrequency (%)
126.94137 2
0.1%
126.87792 1
0.1%
126.877625 1
0.1%
126.877556 1
0.1%
126.87722 1
0.1%
126.876564 1
0.1%
126.875885 1
0.1%
126.87588 1
0.1%
126.87586 2
0.1%
126.875175 1
0.1%

작업일자
Date

Distinct12
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size13.4 KiB
Minimum2024-05-18 11:12:52
Maximum2024-05-18 11:13:05
2024-05-18T13:30:19.824109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:30:20.187788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)

Interactions

2024-05-18T13:29:58.056108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:29:55.589838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:29:56.692189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:29:58.530914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:29:56.012917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:29:57.126963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:29:58.968282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:29:56.347664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:29:57.602663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T13:30:20.452062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치유형설치기관서비스구분망종류설치년도실내외구분X좌표Y좌표작업일자
설치유형1.0000.9430.9670.9440.8750.9430.1780.1780.883
설치기관0.9431.0000.8710.9090.8060.7230.0000.0000.931
서비스구분0.9670.8711.0000.7120.8090.874NaNNaN0.997
망종류0.9440.9090.7121.0000.7880.1840.0000.0000.971
설치년도0.8750.8060.8090.7881.0000.6030.2770.2770.859
실내외구분0.9430.7230.8740.1840.6031.0000.0000.0000.710
X좌표0.1780.000NaN0.0000.2770.0001.0000.7060.000
Y좌표0.1780.000NaN0.0000.2770.0000.7061.0000.000
작업일자0.8830.9310.9970.9710.8590.7100.0000.0001.000
2024-05-18T13:30:20.790260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
망종류wifi접속환경설치유형실내외구분서비스구분설치기관
망종류1.0001.0000.7450.3020.7510.896
wifi접속환경1.0001.0001.0001.0001.0001.000
설치유형0.7451.0001.0000.9150.8990.754
실내외구분0.3021.0000.9151.0000.6770.734
서비스구분0.7511.0000.8990.6771.0000.806
설치기관0.8961.0000.7540.7340.8061.000
2024-05-18T13:30:21.083477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치년도X좌표Y좌표설치유형설치기관서비스구분망종류실내외구분wifi접속환경
설치년도1.000-0.0890.0440.5760.5300.7090.7060.4551.000
X좌표-0.0891.000-0.5140.1570.0001.0000.0000.0001.000
Y좌표0.044-0.5141.0000.1570.0001.0000.0000.0001.000
설치유형0.5760.1570.1571.0000.7540.8990.7450.9151.000
설치기관0.5300.0000.0000.7541.0000.8060.8960.7341.000
서비스구분0.7091.0001.0000.8990.8061.0000.7510.6771.000
망종류0.7060.0000.0000.7450.8960.7511.0000.3021.000
실내외구분0.4550.0000.0000.9150.7340.6770.3021.0001.000
wifi접속환경1.0001.0001.0001.0001.0001.0001.0001.0001.000

Missing values

2024-05-18T13:29:59.385636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T13:30:00.254747image/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.
2024-05-18T13:30:00.877771image/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

관리번호자치구와이파이명도로명주소상세주소설치위치(층)설치유형설치기관서비스구분망종류설치년도실내외구분wifi접속환경X좌표Y좌표작업일자
0BS100171강서구버스정류소_KBS스포츠월드등촌동 665-1316-009<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.556602126.8504642024-05-18 11:12:52.0
1BS100172강서구버스정류소_KBS스포츠월드화곡동 1136-116-010<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.55691126.8492362024-05-18 11:12:52.0
2BS100173강서구버스정류소_KT가양지사강서로 44216-223<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.56482126.840442024-05-18 11:12:52.0
3BS100174강서구버스정류소_KT가양지사가양동 1070답16-224<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.564888126.8400962024-05-18 11:12:52.0
4BS100175강서구버스정류소_가로공원.나누리병원가로공원로 184-216-199<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.536827126.836452024-05-18 11:12:52.0
5BS100176강서구버스정류소_가로공원.나누리병원가로공원로 18116-200<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.537178126.8362962024-05-18 11:12:52.0
6BS100177강서구버스정류소_가양2단지성지아파트.동양고등학교허준로 4716-230<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.56948126.847642024-05-18 11:12:52.0
7BS100178강서구버스정류소_가양2동강변아파트가양2 1475-416-238<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.56418126.855642024-05-18 11:12:52.0
8BS100179강서구버스정류소_가양3동도시개발9단지아파트가양3 1489-116-243<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.55981126.8633042024-05-18 11:12:52.0
9BS100180강서구버스정류소_가양도시개발5단지아파트가양동 1475-316-237<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.564243126.855132024-05-18 11:12:52.0
관리번호자치구와이파이명도로명주소상세주소설치위치(층)설치유형설치기관서비스구분망종류설치년도실내외구분wifi접속환경X좌표Y좌표작업일자
1691서울4차-6155강서구강서한강공원서울특별시 강서구 방화동 2-32강서안내센터 옥상_1<NA>3. 공원(하천)디지털뉴딜(LG U+)공공WiFi인터넷망_뉴딜용2022실외<NA>37.586014126.817172024-05-18 11:13:05.0
1692서울4차-6156강서구강서한강공원서울특별시 강서구 방화동 2-32강서지구 38_1<NA>3. 공원(하천)디지털뉴딜(LG U+)공공WiFi인터넷망_뉴딜용2022실외<NA>37.58527126.819092024-05-18 11:13:05.0
1693서울4차-6157강서구강서한강공원서울특별시 강서구 방화동 2-32가로등 강서3. 공원(하천)44_1<NA>3. 공원(하천)디지털뉴딜(LG U+)공공WiFi인터넷망_뉴딜용2022실외<NA>37.584663126.820592024-05-18 11:13:05.0
1694서울4차-6158강서구강서한강공원서울특별시 강서구 방화동 2-32가로등 강서3. 공원(하천)44_1<NA>3. 공원(하천)디지털뉴딜(LG U+)공공WiFi인터넷망_뉴딜용2022실외<NA>37.584663126.820592024-05-18 11:13:05.0
1695서울4차-6159강서구강서한강공원서울특별시 강서구 방화동 2-32가로등 강서3. 공원(하천)48_1<NA>3. 공원(하천)디지털뉴딜(LG U+)공공WiFi인터넷망_뉴딜용2022실외<NA>37.58435126.821642024-05-18 11:13:05.0
1696서울4차-6160강서구강서한강공원서울특별시 강서구 방화동 2-32가로등 강서3. 공원(하천) 48_1<NA>3. 공원(하천)디지털뉴딜(LG U+)공공WiFi인터넷망_뉴딜용2022실외<NA>37.58426126.821622024-05-18 11:13:05.0
1697서울4차-6161강서구강서한강공원서울특별시 강서구 방화동 2-32음수대 옆 폴대_1<NA>3. 공원(하천)디지털뉴딜(LG U+)공공WiFi인터넷망_뉴딜용2022실외<NA>37.583847126.822372024-05-18 11:13:05.0
1698서울4차-6162강서구강서한강공원서울특별시 강서구 방화동 2-32음수대 옆 폴대_1<NA>3. 공원(하천)디지털뉴딜(LG U+)공공WiFi인터넷망_뉴딜용2022실외<NA>37.583847126.822372024-05-18 11:13:05.0
1699서울4차-6163강서구강서한강공원서울특별시 강서구 방화동 2-32암벽등반 맞은편 강서지구13뽈대_1<NA>3. 공원(하천)디지털뉴딜(LG U+)공공WiFi인터넷망_뉴딜용2022실외<NA>37.583508126.822942024-05-18 11:13:05.0
1700서울4차-6164강서구강서한강공원서울특별시 강서구 방화동 2-32암벽등반 맞은편 강서지구13뽈대_1<NA>3. 공원(하천)디지털뉴딜(LG U+)공공WiFi인터넷망_뉴딜용2022실외<NA>37.583508126.822942024-05-18 11:13:05.0