Overview

Dataset statistics

Number of variables16
Number of observations688
Missing cells53
Missing cells (%)0.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory88.1 KiB
Average record size in memory131.2 B

Variable types

Text4
Categorical8
Numeric3
DateTime1

Dataset

Description관리번호,자치구,와이파이명,도로명주소,상세주소,설치위치(층),설치유형,설치기관,서비스구분,망종류,설치년도,실내외구분,wifi접속환경,X좌표,Y좌표,작업일자
Author성북구
URLhttps://data.seoul.go.kr/dataList/OA-20896/S/1/datasetView.do

Alerts

자치구 has constant value ""Constant
설치위치(층) is highly overall correlated with 설치년도 and 4 other fieldsHigh correlation
설치유형 is highly overall correlated with 설치년도 and 5 other fieldsHigh correlation
wifi접속환경 is highly overall correlated with 설치년도 and 7 other fieldsHigh correlation
실내외구분 is highly overall correlated with 설치년도 and 4 other fieldsHigh correlation
망종류 is highly overall correlated with 설치년도 and 4 other fieldsHigh correlation
서비스구분 is highly overall correlated with 설치위치(층) and 4 other fieldsHigh correlation
설치기관 is highly overall correlated with 설치년도 and 5 other fieldsHigh correlation
설치년도 is highly overall correlated with 설치위치(층) and 5 other fieldsHigh correlation
X좌표 is highly overall correlated with wifi접속환경High correlation
Y좌표 is highly overall correlated with wifi접속환경High correlation
설치위치(층) is highly imbalanced (73.9%)Imbalance
wifi접속환경 is highly imbalanced (80.5%)Imbalance
도로명주소 has 34 (4.9%) missing valuesMissing
상세주소 has 19 (2.8%) missing valuesMissing
관리번호 has unique valuesUnique

Reproduction

Analysis started2024-05-18 05:25:43.672511
Analysis finished2024-05-18 05:25:52.516458
Duration8.84 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Text

UNIQUE 

Distinct688
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
2024-05-18T14:25:53.067917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length8.8502907
Min length7

Characters and Unicode

Total characters6089
Distinct characters18
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

Unique688 ?
Unique (%)100.0%

Sample

1st rowBS100805
2nd rowBS100806
3rd rowBS100807
4th rowBS100808
5th rowBS100809
ValueCountFrequency (%)
bs100805 1
 
0.1%
서울4차-3145-1 1
 
0.1%
서울4차-3180-2 1
 
0.1%
서울4차-3138 1
 
0.1%
서울4차-3138-1 1
 
0.1%
서울4차-3138-2 1
 
0.1%
서울4차-3144 1
 
0.1%
서울4차-3144-1 1
 
0.1%
서울4차-3144-2 1
 
0.1%
서울4차-3145 1
 
0.1%
Other values (678) 678
98.5%
2024-05-18T14:25:54.603651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 724
11.9%
0 697
11.4%
- 630
10.3%
2 518
 
8.5%
서 409
 
6.7%
울 409
 
6.7%
4 387
 
6.4%
3 278
 
4.6%
차 259
 
4.3%
7 246
 
4.0%
Other values (8) 1532
25.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3790
62.2%
Other Letter 1077
 
17.7%
Dash Punctuation 630
 
10.3%
Uppercase Letter 592
 
9.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 724
19.1%
0 697
18.4%
2 518
13.7%
4 387
10.2%
3 278
 
7.3%
7 246
 
6.5%
5 244
 
6.4%
8 240
 
6.3%
6 237
 
6.3%
9 219
 
5.8%
Uppercase Letter
ValueCountFrequency (%)
S 208
35.1%
B 174
29.4%
W 105
17.7%
F 105
17.7%
Other Letter
ValueCountFrequency (%)
서 409
38.0%
울 409
38.0%
차 259
24.0%
Dash Punctuation
ValueCountFrequency (%)
- 630
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4420
72.6%
Hangul 1077
 
17.7%
Latin 592
 
9.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 724
16.4%
0 697
15.8%
- 630
14.3%
2 518
11.7%
4 387
8.8%
3 278
 
6.3%
7 246
 
5.6%
5 244
 
5.5%
8 240
 
5.4%
6 237
 
5.4%
Latin
ValueCountFrequency (%)
S 208
35.1%
B 174
29.4%
W 105
17.7%
F 105
17.7%
Hangul
ValueCountFrequency (%)
서 409
38.0%
울 409
38.0%
차 259
24.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5012
82.3%
Hangul 1077
 
17.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 724
14.4%
0 697
13.9%
- 630
12.6%
2 518
10.3%
4 387
7.7%
3 278
 
5.5%
7 246
 
4.9%
5 244
 
4.9%
8 240
 
4.8%
6 237
 
4.7%
Other values (5) 811
16.2%
Hangul
ValueCountFrequency (%)
서 409
38.0%
울 409
38.0%
차 259
24.0%

자치구
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
성북구
688 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
성북구 688
100.0%

Length

2024-05-18T14:25:55.105508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T14:25:55.556419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
성북구 688
100.0%

와이파이명
Text

Distinct198
Distinct (%)28.8%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
2024-05-18T14:25:56.245389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length17
Mean length8.5668605
Min length2

Characters and Unicode

Total characters5894
Distinct characters243
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)10.8%

Sample

1st row버스정류소_KT월곡지사
2nd row버스정류소_광운초교
3rd row버스정류소_구민회관입구
4th row버스정류소_국민대앞
5th row버스정류소_길음뉴타운
ValueCountFrequency (%)
성북구청 49
 
6.6%
서울시립성북노인종합복지관 30
 
4.1%
생명의전화 23
 
3.1%
종합사회복지관 23
 
3.1%
길음종합사회복지관 21
 
2.8%
성북구육아종합지원센터 16
 
2.2%
월곡종합사회복지관 15
 
2.0%
성북정보도서관 14
 
1.9%
성북동거리 13
 
1.8%
고려대거리 11
 
1.5%
Other values (193) 525
70.9%
2024-05-18T14:25:57.505279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
성 247
 
4.2%
북 240
 
4.1%
관 206
 
3.5%
지 200
 
3.4%
터 177
 
3.0%
센 165
 
2.8%
소 149
 
2.5%
정 146
 
2.5%
복 142
 
2.4%
종 138
 
2.3%
Other values (233) 4084
69.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5707
96.8%
Connector Punctuation 71
 
1.2%
Space Separator 52
 
0.9%
Decimal Number 27
 
0.5%
Other Punctuation 15
 
0.3%
Close Punctuation 9
 
0.2%
Open Punctuation 9
 
0.2%
Uppercase Letter 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
성 247
 
4.3%
북 240
 
4.2%
관 206
 
3.6%
지 200
 
3.5%
터 177
 
3.1%
센 165
 
2.9%
소 149
 
2.6%
정 146
 
2.6%
복 142
 
2.5%
종 138
 
2.4%
Other values (222) 3897
68.3%
Decimal Number
ValueCountFrequency (%)
1 15
55.6%
2 10
37.0%
4 1
 
3.7%
0 1
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
T 2
50.0%
K 2
50.0%
Connector Punctuation
ValueCountFrequency (%)
_ 71
100.0%
Space Separator
ValueCountFrequency (%)
52
100.0%
Other Punctuation
ValueCountFrequency (%)
. 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5707
96.8%
Common 183
 
3.1%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
성 247
 
4.3%
북 240
 
4.2%
관 206
 
3.6%
지 200
 
3.5%
터 177
 
3.1%
센 165
 
2.9%
소 149
 
2.6%
정 146
 
2.6%
복 142
 
2.5%
종 138
 
2.4%
Other values (222) 3897
68.3%
Common
ValueCountFrequency (%)
_ 71
38.8%
52
28.4%
. 15
 
8.2%
1 15
 
8.2%
2 10
 
5.5%
) 9
 
4.9%
( 9
 
4.9%
4 1
 
0.5%
0 1
 
0.5%
Latin
ValueCountFrequency (%)
T 2
50.0%
K 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5707
96.8%
ASCII 187
 
3.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
성 247
 
4.3%
북 240
 
4.2%
관 206
 
3.6%
지 200
 
3.5%
터 177
 
3.1%
센 165
 
2.9%
소 149
 
2.6%
정 146
 
2.6%
복 142
 
2.5%
종 138
 
2.4%
Other values (222) 3897
68.3%
ASCII
ValueCountFrequency (%)
_ 71
38.0%
52
27.8%
. 15
 
8.0%
1 15
 
8.0%
2 10
 
5.3%
) 9
 
4.8%
( 9
 
4.8%
T 2
 
1.1%
K 2
 
1.1%
4 1
 
0.5%

도로명주소
Text

MISSING 

Distinct256
Distinct (%)39.1%
Missing34
Missing (%)4.9%
Memory size5.5 KiB
2024-05-18T14:25:58.307313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length32
Mean length16.06422
Min length4

Characters and Unicode

Total characters10506
Distinct characters139
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

Unique162 ?
Unique (%)24.8%

Sample

1st row종암동 92-33
2nd row장위동 158-51
3rd row돈암동산86-1
4th row정릉동861-1
5th row동소문로
ValueCountFrequency (%)
성북구 489
21.4%
서울특별시 259
 
11.3%
서울시 147
 
6.4%
보문로 53
 
2.3%
168 49
 
2.1%
종암로 42
 
1.8%
오패산로 38
 
1.7%
15길 31
 
1.4%
10 31
 
1.4%
화랑로 28
 
1.2%
Other values (356) 1120
49.0%
2024-05-18T14:25:59.880648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1635
 
15.6%
1 595
 
5.7%
로 550
 
5.2%
북 548
 
5.2%
성 538
 
5.1%
구 498
 
4.7%
서 413
 
3.9%
시 410
 
3.9%
울 409
 
3.9%
2 399
 
3.8%
Other values (129) 4511
42.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6110
58.2%
Decimal Number 2498
23.8%
Space Separator 1635
 
15.6%
Dash Punctuation 184
 
1.8%
Close Punctuation 30
 
0.3%
Open Punctuation 30
 
0.3%
Other Punctuation 19
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 550
 
9.0%
북 548
 
9.0%
성 538
 
8.8%
구 498
 
8.2%
서 413
 
6.8%
시 410
 
6.7%
울 409
 
6.7%
길 361
 
5.9%
특 259
 
4.2%
별 259
 
4.2%
Other values (112) 1865
30.5%
Decimal Number
ValueCountFrequency (%)
1 595
23.8%
2 399
16.0%
6 246
9.8%
3 245
9.8%
8 235
 
9.4%
5 205
 
8.2%
0 183
 
7.3%
4 146
 
5.8%
7 134
 
5.4%
9 110
 
4.4%
Other Punctuation
ValueCountFrequency (%)
, 13
68.4%
. 4
 
21.1%
? 2
 
10.5%
Space Separator
ValueCountFrequency (%)
1635
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 184
100.0%
Close Punctuation
ValueCountFrequency (%)
) 30
100.0%
Open Punctuation
ValueCountFrequency (%)
( 30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6110
58.2%
Common 4396
41.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 550
 
9.0%
북 548
 
9.0%
성 538
 
8.8%
구 498
 
8.2%
서 413
 
6.8%
시 410
 
6.7%
울 409
 
6.7%
길 361
 
5.9%
특 259
 
4.2%
별 259
 
4.2%
Other values (112) 1865
30.5%
Common
ValueCountFrequency (%)
1635
37.2%
1 595
 
13.5%
2 399
 
9.1%
6 246
 
5.6%
3 245
 
5.6%
8 235
 
5.3%
5 205
 
4.7%
- 184
 
4.2%
0 183
 
4.2%
4 146
 
3.3%
Other values (7) 323
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6110
58.2%
ASCII 4396
41.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1635
37.2%
1 595
 
13.5%
2 399
 
9.1%
6 246
 
5.6%
3 245
 
5.6%
8 235
 
5.3%
5 205
 
4.7%
- 184
 
4.2%
0 183
 
4.2%
4 146
 
3.3%
Other values (7) 323
 
7.3%
Hangul
ValueCountFrequency (%)
로 550
 
9.0%
북 548
 
9.0%
성 538
 
8.8%
구 498
 
8.2%
서 413
 
6.8%
시 410
 
6.7%
울 409
 
6.7%
길 361
 
5.9%
특 259
 
4.2%
별 259
 
4.2%
Other values (112) 1865
30.5%

상세주소
Text

MISSING 

Distinct594
Distinct (%)88.8%
Missing19
Missing (%)2.8%
Memory size5.5 KiB
2024-05-18T14:26:00.475287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length25
Mean length12.165919
Min length2

Characters and Unicode

Total characters8139
Distinct characters365
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

Unique547 ?
Unique (%)81.8%

Sample

1st row08-128
2nd row08-188
3rd row08-367
4th row08-108
5th row08-003
ValueCountFrequency (%)
성북구청 49
 
4.1%
1층 25
 
2.1%
복도 24
 
2.0%
생명의전화 23
 
1.9%
3층 23
 
1.9%
2층 19
 
1.6%
앞 14
 
1.2%
5층 12
 
1.0%
cctv 12
 
1.0%
4층 11
 
0.9%
Other values (730) 980
82.2%
2024-05-18T14:26:01.809325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
523
 
6.4%
_ 473
 
5.8%
1 452
 
5.6%
) 290
 
3.6%
( 289
 
3.6%
F 286
 
3.5%
2 284
 
3.5%
0 280
 
3.4%
3 224
 
2.8%
층 147
 
1.8%
Other values (355) 4891
60.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3936
48.4%
Decimal Number 1753
21.5%
Space Separator 523
 
6.4%
Uppercase Letter 509
 
6.3%
Connector Punctuation 473
 
5.8%
Close Punctuation 290
 
3.6%
Open Punctuation 289
 
3.6%
Lowercase Letter 240
 
2.9%
Dash Punctuation 114
 
1.4%
Other Punctuation 12
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
층 147
 
3.7%
실 131
 
3.3%
옥 120
 
3.0%
내 100
 
2.5%
복 98
 
2.5%
지 91
 
2.3%
사 84
 
2.1%
앞 82
 
2.1%
구 78
 
2.0%
북 77
 
2.0%
Other values (321) 2928
74.4%
Decimal Number
ValueCountFrequency (%)
1 452
25.8%
2 284
16.2%
0 280
16.0%
3 224
12.8%
8 134
 
7.6%
4 121
 
6.9%
6 78
 
4.4%
5 67
 
3.8%
9 61
 
3.5%
7 52
 
3.0%
Lowercase Letter
ValueCountFrequency (%)
c 105
43.8%
t 50
20.8%
v 50
20.8%
f 24
 
10.0%
g 7
 
2.9%
p 1
 
0.4%
b 1
 
0.4%
h 1
 
0.4%
s 1
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
F 286
56.2%
C 110
 
21.6%
T 33
 
6.5%
V 32
 
6.3%
B 20
 
3.9%
S 14
 
2.8%
G 11
 
2.2%
P 3
 
0.6%
Other Punctuation
ValueCountFrequency (%)
, 10
83.3%
. 2
 
16.7%
Space Separator
ValueCountFrequency (%)
523
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 473
100.0%
Close Punctuation
ValueCountFrequency (%)
) 290
100.0%
Open Punctuation
ValueCountFrequency (%)
( 289
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 114
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3936
48.4%
Common 3454
42.4%
Latin 749
 
9.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
층 147
 
3.7%
실 131
 
3.3%
옥 120
 
3.0%
내 100
 
2.5%
복 98
 
2.5%
지 91
 
2.3%
사 84
 
2.1%
앞 82
 
2.1%
구 78
 
2.0%
북 77
 
2.0%
Other values (321) 2928
74.4%
Common
ValueCountFrequency (%)
523
15.1%
_ 473
13.7%
1 452
13.1%
) 290
8.4%
( 289
8.4%
2 284
8.2%
0 280
8.1%
3 224
6.5%
8 134
 
3.9%
4 121
 
3.5%
Other values (7) 384
11.1%
Latin
ValueCountFrequency (%)
F 286
38.2%
C 110
 
14.7%
c 105
 
14.0%
t 50
 
6.7%
v 50
 
6.7%
T 33
 
4.4%
V 32
 
4.3%
f 24
 
3.2%
B 20
 
2.7%
S 14
 
1.9%
Other values (7) 25
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4203
51.6%
Hangul 3936
48.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
523
12.4%
_ 473
11.3%
1 452
10.8%
) 290
 
6.9%
( 289
 
6.9%
F 286
 
6.8%
2 284
 
6.8%
0 280
 
6.7%
3 224
 
5.3%
8 134
 
3.2%
Other values (24) 968
23.0%
Hangul
ValueCountFrequency (%)
층 147
 
3.7%
실 131
 
3.3%
옥 120
 
3.0%
내 100
 
2.5%
복 98
 
2.5%
지 91
 
2.3%
사 84
 
2.1%
앞 82
 
2.1%
구 78
 
2.0%
북 77
 
2.0%
Other values (321) 2928
74.4%

설치위치(층)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct18
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
<NA>
594 
1
 
13
2
 
12
-
 
12
3
 
9
Other values (13)
 
48

Length

Max length4
Median length4
Mean length3.622093
Min length1

Unique

Unique2 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 594
86.3%
1 13
 
1.9%
2 12
 
1.7%
- 12
 
1.7%
3 9
 
1.3%
4 8
 
1.2%
8 6
 
0.9%
9 5
 
0.7%
6 5
 
0.7%
10 4
 
0.6%
Other values (8) 20
 
2.9%

Length

2024-05-18T14:26:02.471865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 594
86.3%
1 13
 
1.9%
2 12
 
1.7%
12
 
1.7%
3 9
 
1.3%
4 8
 
1.2%
8 6
 
0.9%
9 5
 
0.7%
6 5
 
0.7%
7 4
 
0.6%
Other values (8) 20
 
2.9%

설치유형
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
4. 문화관광
105 
6-4. 복지 - 아동청소년
77 
6-2. 복지 - 노인
73 
3. 공원(하천)
62 
6-1. 복지 - 사회
61 
Other values (15)
310 

Length

Max length21
Median length17
Mean length12.351744
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 (%)
4. 문화관광 105
15.3%
6-4. 복지 - 아동청소년 77
11.2%
6-2. 복지 - 노인 73
10.6%
3. 공원(하천) 62
9.0%
6-1. 복지 - 사회 61
8.9%
7-2-1. 공공 - 구청사 및 별관 49
7.1%
1. 주요거리 40
 
5.8%
5-1. 버스정류소(국비) 37
 
5.4%
5-2. 버스정류소(시비) 34
 
4.9%
2. 전통시장 28
 
4.1%
Other values (10) 122
17.7%

Length

2024-05-18T14:26:02.972543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
380
16.6%
복지 225
 
9.9%
공공 155
 
6.8%
4 105
 
4.6%
문화관광 105
 
4.6%
6-4 77
 
3.4%
아동청소년 77
 
3.4%
및 74
 
3.2%
6-2 73
 
3.2%
노인 73
 
3.2%
Other values (34) 940
41.2%

설치기관
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
디지털뉴딜(LG U+)
409 
자치구
103 
서울시(AP)
79 
버스정류소(국비)
 
37
버스정류소(시비)
 
34

Length

Max length12
Median length12
Mean length9.6177326
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 (%)
디지털뉴딜(LG U+) 409
59.4%
자치구 103
 
15.0%
서울시(AP) 79
 
11.5%
버스정류소(국비) 37
 
5.4%
버스정류소(시비) 34
 
4.9%
서울시(공유기) 26
 
3.8%

Length

2024-05-18T14:26:03.499135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T14:26:03.845087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
디지털뉴딜(lg 409
37.3%
u 409
37.3%
자치구 103
 
9.4%
서울시(ap 79
 
7.2%
버스정류소(국비 37
 
3.4%
버스정류소(시비 34
 
3.1%
서울시(공유기 26
 
2.4%

서비스구분
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
공공WiFi
484 
과기부WiFi(복지시설)
82 
과기부WiFi(핫플레이스)
68 
과기부WiFi
 
37
<NA>
 
17

Length

Max length14
Median length6
Mean length7.6293605
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공공WiFi 484
70.3%
과기부WiFi(복지시설) 82
 
11.9%
과기부WiFi(핫플레이스) 68
 
9.9%
과기부WiFi 37
 
5.4%
<NA> 17
 
2.5%

Length

2024-05-18T14:26:04.250638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T14:26:04.666269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공wifi 484
70.3%
과기부wifi(복지시설 82
 
11.9%
과기부wifi(핫플레이스 68
 
9.9%
과기부wifi 37
 
5.4%
na 17
 
2.5%

망종류
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
인터넷망_뉴딜용
409 
자가망U-무선망
103 
임대망
86 
자가망_U무선망
56 
<NA>
 
34

Length

Max length8
Median length8
Mean length7.1773256
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
인터넷망_뉴딜용 409
59.4%
자가망U-무선망 103
 
15.0%
임대망 86
 
12.5%
자가망_U무선망 56
 
8.1%
<NA> 34
 
4.9%

Length

2024-05-18T14:26:05.109359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T14:26:05.699939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인터넷망_뉴딜용 409
59.4%
자가망u-무선망 103
 
15.0%
임대망 86
 
12.5%
자가망_u무선망 56
 
8.1%
na 34
 
4.9%

설치년도
Real number (ℝ)

HIGH CORRELATION 

Distinct7
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2020.9462
Minimum2017
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.2 KiB
2024-05-18T14:26:06.146091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2017
5-th percentile2017
Q12020
median2022
Q32022
95-th percentile2022
Maximum2023
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.5818338
Coefficient of variation (CV)0.0007827194
Kurtosis0.25630391
Mean2020.9462
Median Absolute Deviation (MAD)0
Skewness-1.1771371
Sum1390411
Variance2.5021982
MonotonicityNot monotonic
2024-05-18T14:26:06.508730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2022 392
57.0%
2019 105
 
15.3%
2021 71
 
10.3%
2020 51
 
7.4%
2017 46
 
6.7%
2023 17
 
2.5%
2018 6
 
0.9%
ValueCountFrequency (%)
2017 46
 
6.7%
2018 6
 
0.9%
2019 105
 
15.3%
2020 51
 
7.4%
2021 71
 
10.3%
2022 392
57.0%
2023 17
 
2.5%
ValueCountFrequency (%)
2023 17
 
2.5%
2022 392
57.0%
2021 71
 
10.3%
2020 51
 
7.4%
2019 105
 
15.3%
2018 6
 
0.9%
2017 46
 
6.7%

실내외구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
실내
470 
실외
218 

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 (%)
실내 470
68.3%
실외 218
31.7%

Length

2024-05-18T14:26:07.024806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T14:26:07.425565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
실내 470
68.3%
실외 218
31.7%

wifi접속환경
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
<NA>
657 
6.20~6.24 Proxy 서버개발 후 2~3개 임시적용 후 6월말 CNS링크 전체 적용 예정
 
18
10G 백홀, WIFI6E
 
13

Length

Max length53
Median length4
Mean length5.4709302
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> 657
95.5%
6.20~6.24 Proxy 서버개발 후 2~3개 임시적용 후 6월말 CNS링크 전체 적용 예정 18
 
2.6%
10G 백홀, WIFI6E 13
 
1.9%

Length

2024-05-18T14:26:07.743857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T14:26:08.061623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 657
72.0%
후 36
 
3.9%
6.20~6.24 18
 
2.0%
proxy 18
 
2.0%
서버개발 18
 
2.0%
2~3개 18
 
2.0%
임시적용 18
 
2.0%
6월말 18
 
2.0%
cns링크 18
 
2.0%
전체 18
 
2.0%
Other values (5) 75
 
8.2%

X좌표
Real number (ℝ)

HIGH CORRELATION 

Distinct294
Distinct (%)42.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.603256
Minimum37.57752
Maximum37.623825
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.2 KiB
2024-05-18T14:26:08.433127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.57752
5-th percentile37.584997
Q137.597794
median37.604637
Q337.609927
95-th percentile37.615924
Maximum37.623825
Range0.046305
Interquartile range (IQR)0.012133

Descriptive statistics

Standard deviation0.0088908804
Coefficient of variation (CV)0.00023643911
Kurtosis-0.072625467
Mean37.603256
Median Absolute Deviation (MAD)0.00576
Skewness-0.56257334
Sum25871.04
Variance7.9047754 × 10-5
MonotonicityNot monotonic
2024-05-18T14:26:08.855242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.60231 48
 
7.0%
37.597794 30
 
4.4%
37.60419 23
 
3.3%
37.60673 21
 
3.1%
37.604977 17
 
2.5%
37.60886 15
 
2.2%
37.61124 11
 
1.6%
37.61087 10
 
1.5%
37.611748 9
 
1.3%
37.609955 9
 
1.3%
Other values (284) 495
71.9%
ValueCountFrequency (%)
37.57752 1
 
0.1%
37.57965 1
 
0.1%
37.579834 1
 
0.1%
37.5806 1
 
0.1%
37.581467 6
0.9%
37.582092 1
 
0.1%
37.582615 1
 
0.1%
37.582947 1
 
0.1%
37.58319 1
 
0.1%
37.583385 1
 
0.1%
ValueCountFrequency (%)
37.623825 1
 
0.1%
37.623466 1
 
0.1%
37.623253 2
0.3%
37.6212 1
 
0.1%
37.62056 1
 
0.1%
37.6203 1
 
0.1%
37.619827 3
0.4%
37.618885 1
 
0.1%
37.618847 2
0.3%
37.61867 1
 
0.1%

Y좌표
Real number (ℝ)

HIGH CORRELATION 

Distinct294
Distinct (%)42.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.02398
Minimum126.95519
Maximum127.07031
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.2 KiB
2024-05-18T14:26:09.256824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.95519
5-th percentile126.95519
Q1127.01078
median127.02678
Q3127.04037
95-th percentile127.06052
Maximum127.07031
Range0.115115
Interquartile range (IQR)0.02959125

Descriptive statistics

Standard deviation0.026086775
Coefficient of variation (CV)0.0002053689
Kurtosis1.0903685
Mean127.02398
Median Absolute Deviation (MAD)0.01416
Skewness-0.96828834
Sum87392.498
Variance0.00068051982
MonotonicityNot monotonic
2024-05-18T14:26:09.708343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.95519 48
 
7.0%
127.034386 30
 
4.4%
127.03719 23
 
3.3%
127.02678 21
 
3.1%
127.05059 17
 
2.5%
127.0375 15
 
2.2%
127.00124 11
 
1.6%
127.0407 10
 
1.5%
127.02628 9
 
1.3%
127.02642 9
 
1.3%
Other values (284) 495
71.9%
ValueCountFrequency (%)
126.95519 48
7.0%
126.98648 2
 
0.3%
126.98805 1
 
0.1%
126.98831 1
 
0.1%
126.98832 1
 
0.1%
126.98938 1
 
0.1%
126.99066 1
 
0.1%
126.99075 1
 
0.1%
126.99135 1
 
0.1%
126.99313 1
 
0.1%
ValueCountFrequency (%)
127.070305 1
 
0.1%
127.07025 1
 
0.1%
127.07023 1
 
0.1%
127.07018 1
 
0.1%
127.07003 1
 
0.1%
127.066124 1
 
0.1%
127.0657 1
 
0.1%
127.06542 3
0.4%
127.06506 1
 
0.1%
127.06478 1
 
0.1%

작업일자
Date

Distinct11
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
Minimum2024-05-18 11:12:52
Maximum2024-05-18 11:13:06
2024-05-18T14:26:10.041935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:26:10.398867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)

Interactions

2024-05-18T14:25:49.556735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:25:47.308318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:25:48.443497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:25:49.865758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:25:47.698924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:25:48.800099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:25:50.179212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:25:48.087980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:25:49.266606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T14:26:10.876013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치위치(층)설치유형설치기관서비스구분망종류설치년도실내외구분wifi접속환경X좌표Y좌표작업일자
설치위치(층)1.0000.7221.000NaN1.0000.8630.956NaN0.7030.7011.000
설치유형0.7221.0000.9350.9810.8700.8460.9891.0000.7830.8030.906
설치기관1.0000.9351.0000.7820.8820.9560.677NaN0.3860.5480.959
서비스구분NaN0.9810.7821.0000.7890.5330.8610.9940.4570.5030.885
망종류1.0000.8700.8820.7891.0000.8300.293NaN0.4410.5640.965
설치년도0.8630.8460.9560.5330.8301.0000.734NaN0.4180.5260.894
실내외구분0.9560.9890.6770.8610.2930.7341.0000.9940.4600.3580.568
wifi접속환경NaN1.000NaN0.994NaNNaN0.9941.0000.7160.5380.000
X좌표0.7030.7830.3860.4570.4410.4180.4600.7161.0000.6710.533
Y좌표0.7010.8030.5480.5030.5640.5260.3580.5380.6711.0000.575
작업일자1.0000.9060.9590.8850.9650.8940.5680.0000.5330.5751.000
2024-05-18T14:26:11.229973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치위치(층)설치유형wifi접속환경실내외구분망종류서비스구분설치기관
설치위치(층)1.0000.353NaN0.8680.9151.0000.915
설치유형0.3531.0000.9650.9030.6800.8190.772
wifi접속환경NaN0.9651.0000.9311.0000.9311.000
실내외구분0.8680.9030.9311.0000.1940.6610.495
망종류0.9150.6801.0000.1941.0000.4280.874
서비스구분1.0000.8190.9310.6610.4281.0000.626
설치기관0.9150.7721.0000.4950.8740.6261.000
2024-05-18T14:26:11.557146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치년도X좌표Y좌표설치위치(층)설치유형설치기관서비스구분망종류실내외구분wifi접속환경
설치년도1.0000.1110.3260.5650.5790.6860.4680.7230.5231.000
X좌표0.1111.0000.4290.3860.3660.2140.2890.2770.3510.703
Y좌표0.3260.4291.0000.3620.4760.3080.3450.3960.3560.615
설치위치(층)0.5650.3860.3621.0000.3530.9151.0000.9150.8680.000
설치유형0.5790.3660.4760.3531.0000.7720.8190.6800.9030.965
설치기관0.6860.2140.3080.9150.7721.0000.6260.8740.4951.000
서비스구분0.4680.2890.3451.0000.8190.6261.0000.4280.6610.931
망종류0.7230.2770.3960.9150.6800.8740.4281.0000.1941.000
실내외구분0.5230.3510.3560.8680.9030.4950.6610.1941.0000.931
wifi접속환경1.0000.7030.6150.0000.9651.0000.9311.0000.9311.000

Missing values

2024-05-18T14:25:50.763917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T14:25:51.590941image/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.
2024-05-18T14:25:52.209250image/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
0BS100805성북구버스정류소_KT월곡지사종암동 92-3308-128<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.60248127.0338752024-05-18 11:12:52.0
1BS100806성북구버스정류소_광운초교장위동 158-5108-188<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.62056127.052922024-05-18 11:12:52.0
2BS100807성북구버스정류소_구민회관입구돈암동산86-108-367<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.596573127.006362024-05-18 11:12:52.0
3BS100808성북구버스정류소_국민대앞정릉동861-108-108<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.61093126.994312024-05-18 11:12:52.0
4BS100809성북구버스정류소_길음뉴타운동소문로08-003<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.603626127.024172024-05-18 11:12:52.0
5BS100810성북구버스정류소_길음뉴타운동소문로08-004<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.603184127.023692024-05-18 11:12:52.0
6BS100811성북구버스정류소_돈암사거리.성신여대입구동소문로08-007<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.593742127.0181352024-05-18 11:12:52.0
7BS100812성북구버스정류소_돈암사거리.성신여대입구동소문로08-008<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.593307127.017842024-05-18 11:12:52.0
8BS100813성북구버스정류소_돌곶이역석관동 255-108-209<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.610203127.0575562024-05-18 11:12:52.0
9BS100814성북구버스정류소_미아리고개.미아리예술극장동소문로08-005<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.598812127.0217062024-05-18 11:12:52.0
관리번호자치구와이파이명도로명주소상세주소설치위치(층)설치유형설치기관서비스구분망종류설치년도실내외구분wifi접속환경X좌표Y좌표작업일자
678서울5차-0806성북구동방어린이공원서울특별시 성북구 장위동 219-223(CCTV) c0092-3. 공원(하천)디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실외<NA>37.616325127.043372024-05-18 11:13:06.0
679서울5차-0807성북구간대어린이공원서울특별시 성북구 장위동 199-45(CCTV) g0088-3. 공원(하천)디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실외<NA>37.618343127.050862024-05-18 11:13:06.0
680서울5차-0808성북구간대어린이공원서울특별시 성북구 장위동 199-45(CCTV) g0086-3. 공원(하천)디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실외<NA>37.61801127.050742024-05-18 11:13:06.0
681서울5차-0811성북구성북종합레포츠타운서울특별시 성북구 한천로 58길 307테니스장 건물 처마-4. 문화관광디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실외<NA>37.610237127.070032024-05-18 11:13:06.0
682서울5차-0813성북구정릉족구장서울특별시 성북구 정릉동 산 87-372사무실 컨테이너 외벽-4. 문화관광디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실외<NA>37.607487127.003662024-05-18 11:13:06.0
683서울5차-0814성북구성북구보건소서울특별시 성북구 화랑로 63엘리베이터 앞지하1층7-2-2. 공공 - 구의회 및 보건소디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.602665127.039712024-05-18 11:13:06.0
684서울5차-0814-1성북구성북구보건소서울특별시 성북구 화랑로 63엘리베이터 앞지하2층7-2-2. 공공 - 구의회 및 보건소디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.602665127.039712024-05-18 11:13:06.0
685서울5차-0816성북구장위종합사회복지관서울특별시 성북구 화랑로 237봄실2층6-1. 복지 - 사회디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.610523127.05572024-05-18 11:13:06.0
686서울5차-0816-1성북구장위종합사회복지관서울특별시 성북구 화랑로 237여름실2층6-1. 복지 - 사회디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.610523127.05572024-05-18 11:13:06.0
687서울5차-0816-2성북구장위종합사회복지관서울특별시 성북구 화랑로 237가을실2층6-1. 복지 - 사회디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.610523127.05572024-05-18 11:13:06.0