Overview

Dataset statistics

Number of variables16
Number of observations779
Missing cells19
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory99.8 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
Author중랑구
URLhttps://data.seoul.go.kr/dataList/OA-20895/S/1/datasetView.do

Alerts

자치구 has constant value ""Constant
망종류 is highly overall correlated with 설치년도 and 5 other fieldsHigh correlation
설치위치(층) is highly overall correlated with 설치년도 and 4 other fieldsHigh correlation
서비스구분 is highly overall correlated with 설치년도 and 5 other fieldsHigh correlation
설치유형 is highly overall correlated with 설치위치(층) and 5 other fieldsHigh correlation
설치기관 is highly overall correlated with 설치년도 and 5 other fieldsHigh correlation
실내외구분 is highly overall correlated with 설치위치(층) and 3 other fieldsHigh correlation
wifi접속환경 is highly overall correlated with 설치년도 and 7 other fieldsHigh correlation
설치년도 is highly overall correlated with 설치위치(층) and 4 other fieldsHigh correlation
X좌표 is highly overall correlated with wifi접속환경High correlation
Y좌표 is highly overall correlated with wifi접속환경High correlation
설치위치(층) is highly imbalanced (87.8%)Imbalance
wifi접속환경 is highly imbalanced (76.5%)Imbalance
도로명주소 has 15 (1.9%) missing valuesMissing
관리번호 has unique valuesUnique

Reproduction

Analysis started2024-05-11 00:20:22.453213
Analysis finished2024-05-11 00:20:29.895498
Duration7.44 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Text

UNIQUE 

Distinct779
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
2024-05-11T00:20:30.702519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length8
Mean length8.224647
Min length7

Characters and Unicode

Total characters6407
Distinct characters20
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

Unique779 ?
Unique (%)100.0%

Sample

1st rowBS101249
2nd rowBS101250
3rd rowBS101251
4th rowBS101252
5th rowBS101253
ValueCountFrequency (%)
bs101249 1
 
0.1%
서울-2867 1
 
0.1%
서울-2639 1
 
0.1%
서울-2642-1 1
 
0.1%
서울-2639-1 1
 
0.1%
서울-2639-2 1
 
0.1%
서울-2640 1
 
0.1%
서울-2640-1 1
 
0.1%
서울-2640-2 1
 
0.1%
서울-2641 1
 
0.1%
Other values (769) 769
98.7%
2024-05-11T00:20:32.042659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1021
15.9%
1 789
12.3%
2 504
 
7.9%
- 501
 
7.8%
4 374
 
5.8%
서 368
 
5.7%
울 368
 
5.7%
6 337
 
5.3%
3 323
 
5.0%
J 277
 
4.3%
Other values (10) 1545
24.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4202
65.6%
Other Letter 867
 
13.5%
Uppercase Letter 837
 
13.1%
Dash Punctuation 501
 
7.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1021
24.3%
1 789
18.8%
2 504
12.0%
4 374
 
8.9%
6 337
 
8.0%
3 323
 
7.7%
8 238
 
5.7%
7 232
 
5.5%
5 224
 
5.3%
9 160
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
J 277
33.1%
N 277
33.1%
F 81
 
9.7%
W 81
 
9.7%
S 68
 
8.1%
B 53
 
6.3%
Other Letter
ValueCountFrequency (%)
서 368
42.4%
울 368
42.4%
차 131
 
15.1%
Dash Punctuation
ValueCountFrequency (%)
- 501
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4703
73.4%
Hangul 867
 
13.5%
Latin 837
 
13.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1021
21.7%
1 789
16.8%
2 504
10.7%
- 501
10.7%
4 374
 
8.0%
6 337
 
7.2%
3 323
 
6.9%
8 238
 
5.1%
7 232
 
4.9%
5 224
 
4.8%
Latin
ValueCountFrequency (%)
J 277
33.1%
N 277
33.1%
F 81
 
9.7%
W 81
 
9.7%
S 68
 
8.1%
B 53
 
6.3%
Hangul
ValueCountFrequency (%)
서 368
42.4%
울 368
42.4%
차 131
 
15.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5540
86.5%
Hangul 867
 
13.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1021
18.4%
1 789
14.2%
2 504
9.1%
- 501
9.0%
4 374
 
6.8%
6 337
 
6.1%
3 323
 
5.8%
J 277
 
5.0%
N 277
 
5.0%
8 238
 
4.3%
Other values (7) 899
16.2%
Hangul
ValueCountFrequency (%)
서 368
42.4%
울 368
42.4%
차 131
 
15.1%

자치구
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
중랑구
779 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
중랑구 779
100.0%

Length

2024-05-11T00:20:32.489308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:20:32.928623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중랑구 779
100.0%

와이파이명
Text

Distinct166
Distinct (%)21.3%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
2024-05-11T00:20:33.521743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length21
Mean length8.2747112
Min length3

Characters and Unicode

Total characters6446
Distinct characters239
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

Unique90 ?
Unique (%)11.6%

Sample

1st row버스정류소_경남아너스빌아파트앞
2nd row버스정류소_극동늘푸른아파트
3rd row버스정류소_금란교회
4th row버스정류소_금란교회
5th row버스정류소_동부제일병원.망우리공원
ValueCountFrequency (%)
중랑구청(의회ap없음 57
 
7.2%
서울의료원 57
 
7.2%
중랑캠핑숲공원 37
 
4.7%
동원전통시장 27
 
3.4%
버스정류소 26
 
3.3%
서울시립중랑청소년센터 22
 
2.8%
우림시장 21
 
2.6%
시립중랑노인종합복지관 20
 
2.5%
중랑천 19
 
2.4%
서울시립중랑노인전문요양원 18
 
2.3%
Other values (162) 491
61.8%
2024-05-11T00:20:34.751422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
중 279
 
4.3%
랑 268
 
4.2%
원 259
 
4.0%
터 179
 
2.8%
센 164
 
2.5%
시 159
 
2.5%
서 150
 
2.3%
동 147
 
2.3%
소 140
 
2.2%
지 135
 
2.1%
Other values (229) 4566
70.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6002
93.1%
Uppercase Letter 116
 
1.8%
Decimal Number 116
 
1.8%
Close Punctuation 60
 
0.9%
Open Punctuation 60
 
0.9%
Connector Punctuation 53
 
0.8%
Other Punctuation 23
 
0.4%
Space Separator 16
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
중 279
 
4.6%
랑 268
 
4.5%
원 259
 
4.3%
터 179
 
3.0%
센 164
 
2.7%
시 159
 
2.6%
서 150
 
2.5%
동 147
 
2.4%
소 140
 
2.3%
지 135
 
2.2%
Other values (209) 4122
68.7%
Decimal Number
ValueCountFrequency (%)
2 39
33.6%
1 28
24.1%
5 18
15.5%
3 9
 
7.8%
7 8
 
6.9%
8 5
 
4.3%
4 3
 
2.6%
9 3
 
2.6%
0 2
 
1.7%
6 1
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
A 57
49.1%
P 57
49.1%
K 1
 
0.9%
T 1
 
0.9%
Other Punctuation
ValueCountFrequency (%)
. 18
78.3%
, 5
 
21.7%
Close Punctuation
ValueCountFrequency (%)
) 60
100.0%
Open Punctuation
ValueCountFrequency (%)
( 60
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 53
100.0%
Space Separator
ValueCountFrequency (%)
16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6002
93.1%
Common 328
 
5.1%
Latin 116
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
중 279
 
4.6%
랑 268
 
4.5%
원 259
 
4.3%
터 179
 
3.0%
센 164
 
2.7%
시 159
 
2.6%
서 150
 
2.5%
동 147
 
2.4%
소 140
 
2.3%
지 135
 
2.2%
Other values (209) 4122
68.7%
Common
ValueCountFrequency (%)
) 60
18.3%
( 60
18.3%
_ 53
16.2%
2 39
11.9%
1 28
8.5%
5 18
 
5.5%
. 18
 
5.5%
16
 
4.9%
3 9
 
2.7%
7 8
 
2.4%
Other values (6) 19
 
5.8%
Latin
ValueCountFrequency (%)
A 57
49.1%
P 57
49.1%
K 1
 
0.9%
T 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6002
93.1%
ASCII 444
 
6.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
중 279
 
4.6%
랑 268
 
4.5%
원 259
 
4.3%
터 179
 
3.0%
센 164
 
2.7%
시 159
 
2.6%
서 150
 
2.5%
동 147
 
2.4%
소 140
 
2.3%
지 135
 
2.2%
Other values (209) 4122
68.7%
ASCII
ValueCountFrequency (%)
) 60
13.5%
( 60
13.5%
A 57
12.8%
P 57
12.8%
_ 53
11.9%
2 39
8.8%
1 28
6.3%
5 18
 
4.1%
. 18
 
4.1%
16
 
3.6%
Other values (10) 38
8.6%

도로명주소
Text

MISSING 

Distinct241
Distinct (%)31.5%
Missing15
Missing (%)1.9%
Memory size6.2 KiB
2024-05-11T00:20:35.683151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length27
Mean length13.722513
Min length3

Characters and Unicode

Total characters10484
Distinct characters125
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

Unique145 ?
Unique (%)19.0%

Sample

1st row면목동1529
2nd row묵동 379
3rd row망우로
4th row망우로
5th row망우로
ValueCountFrequency (%)
서울특별시 368
 
16.1%
중랑구 368
 
16.1%
봉화산로 104
 
4.5%
신내로 88
 
3.8%
179 79
 
3.5%
용마산로 60
 
2.6%
156 58
 
2.5%
망우동 43
 
1.9%
망우로 34
 
1.5%
중랑역로 28
 
1.2%
Other values (317) 1057
46.2%
2024-05-11T00:20:37.166605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1523
 
14.5%
1 652
 
6.2%
로 602
 
5.7%
중 421
 
4.0%
랑 407
 
3.9%
구 372
 
3.5%
서 372
 
3.5%
울 371
 
3.5%
시 370
 
3.5%
별 369
 
3.5%
Other values (115) 5025
47.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6033
57.5%
Decimal Number 2728
26.0%
Space Separator 1523
 
14.5%
Dash Punctuation 133
 
1.3%
Other Punctuation 35
 
0.3%
Open Punctuation 15
 
0.1%
Close Punctuation 15
 
0.1%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 602
 
10.0%
중 421
 
7.0%
랑 407
 
6.7%
구 372
 
6.2%
서 372
 
6.2%
울 371
 
6.1%
시 370
 
6.1%
별 369
 
6.1%
특 369
 
6.1%
산 225
 
3.7%
Other values (98) 2155
35.7%
Decimal Number
ValueCountFrequency (%)
1 652
23.9%
2 364
13.3%
5 320
11.7%
3 271
9.9%
9 240
 
8.8%
7 237
 
8.7%
6 176
 
6.5%
4 175
 
6.4%
8 153
 
5.6%
0 140
 
5.1%
Other Punctuation
ValueCountFrequency (%)
, 31
88.6%
. 4
 
11.4%
Space Separator
ValueCountFrequency (%)
1523
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 133
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Uppercase Letter
ValueCountFrequency (%)
F 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6033
57.5%
Common 4449
42.4%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 602
 
10.0%
중 421
 
7.0%
랑 407
 
6.7%
구 372
 
6.2%
서 372
 
6.2%
울 371
 
6.1%
시 370
 
6.1%
별 369
 
6.1%
특 369
 
6.1%
산 225
 
3.7%
Other values (98) 2155
35.7%
Common
ValueCountFrequency (%)
1523
34.2%
1 652
14.7%
2 364
 
8.2%
5 320
 
7.2%
3 271
 
6.1%
9 240
 
5.4%
7 237
 
5.3%
6 176
 
4.0%
4 175
 
3.9%
8 153
 
3.4%
Other values (6) 338
 
7.6%
Latin
ValueCountFrequency (%)
F 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6033
57.5%
ASCII 4451
42.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1523
34.2%
1 652
14.6%
2 364
 
8.2%
5 320
 
7.2%
3 271
 
6.1%
9 240
 
5.4%
7 237
 
5.3%
6 176
 
4.0%
4 175
 
3.9%
8 153
 
3.4%
Other values (7) 340
 
7.6%
Hangul
ValueCountFrequency (%)
로 602
 
10.0%
중 421
 
7.0%
랑 407
 
6.7%
구 372
 
6.2%
서 372
 
6.2%
울 371
 
6.1%
시 370
 
6.1%
별 369
 
6.1%
특 369
 
6.1%
산 225
 
3.7%
Other values (98) 2155
35.7%

상세주소
Text

Distinct647
Distinct (%)83.5%
Missing4
Missing (%)0.5%
Memory size6.2 KiB
2024-05-11T00:20:38.068619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length23
Mean length10.789677
Min length1

Characters and Unicode

Total characters8362
Distinct characters349
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

Unique578 ?
Unique (%)74.6%

Sample

1st row07-122
2nd row07-101
3rd row07-011
4th row07-012
5th row07-013
ValueCountFrequency (%)
복도 37
 
2.4%
1f 36
 
2.3%
옥내1 32
 
2.1%
앞 27
 
1.7%
민원실 24
 
1.6%
2f 24
 
1.6%
중랑청소년센터 22
 
1.4%
옥내3 21
 
1.4%
시립중랑노인종합복지관 20
 
1.3%
우림시장 19
 
1.2%
Other values (578) 1285
83.1%
2024-05-11T00:20:39.941501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
772
 
9.2%
1 327
 
3.9%
) 271
 
3.2%
( 271
 
3.2%
2 259
 
3.1%
옥 244
 
2.9%
F 199
 
2.4%
_ 191
 
2.3%
3 169
 
2.0%
내 169
 
2.0%
Other values (339) 5490
65.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5095
60.9%
Decimal Number 1266
 
15.1%
Space Separator 772
 
9.2%
Uppercase Letter 326
 
3.9%
Close Punctuation 271
 
3.2%
Open Punctuation 271
 
3.2%
Connector Punctuation 191
 
2.3%
Dash Punctuation 86
 
1.0%
Lowercase Letter 46
 
0.6%
Other Punctuation 37
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
옥 244
 
4.8%
내 169
 
3.3%
원 158
 
3.1%
실 145
 
2.8%
관 141
 
2.8%
외 137
 
2.7%
층 119
 
2.3%
복 118
 
2.3%
장 112
 
2.2%
사 110
 
2.2%
Other values (300) 3642
71.5%
Uppercase Letter
ValueCountFrequency (%)
F 199
61.0%
B 32
 
9.8%
C 30
 
9.2%
T 20
 
6.1%
V 12
 
3.7%
P 9
 
2.8%
S 6
 
1.8%
A 5
 
1.5%
U 4
 
1.2%
N 2
 
0.6%
Other values (6) 7
 
2.1%
Decimal Number
ValueCountFrequency (%)
1 327
25.8%
2 259
20.5%
3 169
13.3%
0 132
10.4%
4 109
 
8.6%
7 100
 
7.9%
5 79
 
6.2%
6 39
 
3.1%
8 29
 
2.3%
9 23
 
1.8%
Lowercase Letter
ValueCountFrequency (%)
c 22
47.8%
v 11
23.9%
t 11
23.9%
e 2
 
4.3%
Other Punctuation
ValueCountFrequency (%)
, 27
73.0%
# 7
 
18.9%
/ 3
 
8.1%
Space Separator
ValueCountFrequency (%)
772
100.0%
Close Punctuation
ValueCountFrequency (%)
) 271
100.0%
Open Punctuation
ValueCountFrequency (%)
( 271
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 191
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 86
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5095
60.9%
Common 2895
34.6%
Latin 372
 
4.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
옥 244
 
4.8%
내 169
 
3.3%
원 158
 
3.1%
실 145
 
2.8%
관 141
 
2.8%
외 137
 
2.7%
층 119
 
2.3%
복 118
 
2.3%
장 112
 
2.2%
사 110
 
2.2%
Other values (300) 3642
71.5%
Latin
ValueCountFrequency (%)
F 199
53.5%
B 32
 
8.6%
C 30
 
8.1%
c 22
 
5.9%
T 20
 
5.4%
V 12
 
3.2%
v 11
 
3.0%
t 11
 
3.0%
P 9
 
2.4%
S 6
 
1.6%
Other values (10) 20
 
5.4%
Common
ValueCountFrequency (%)
772
26.7%
1 327
11.3%
) 271
 
9.4%
( 271
 
9.4%
2 259
 
8.9%
_ 191
 
6.6%
3 169
 
5.8%
0 132
 
4.6%
4 109
 
3.8%
7 100
 
3.5%
Other values (9) 294
 
10.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5092
60.9%
ASCII 3267
39.1%
Compat Jamo 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
772
23.6%
1 327
10.0%
) 271
 
8.3%
( 271
 
8.3%
2 259
 
7.9%
F 199
 
6.1%
_ 191
 
5.8%
3 169
 
5.2%
0 132
 
4.0%
4 109
 
3.3%
Other values (29) 567
17.4%
Hangul
ValueCountFrequency (%)
옥 244
 
4.8%
내 169
 
3.3%
원 158
 
3.1%
실 145
 
2.8%
관 141
 
2.8%
외 137
 
2.7%
층 119
 
2.3%
복 118
 
2.3%
장 112
 
2.2%
사 110
 
2.2%
Other values (299) 3639
71.5%
Compat Jamo
ValueCountFrequency (%)
ㅎ 3
100.0%

설치위치(층)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
<NA>
755 
3층
 
12
1층
 
6
2층
 
6

Length

Max length4
Median length4
Mean length3.9383825
Min length2

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> 755
96.9%
3층 12
 
1.5%
1층 6
 
0.8%
2층 6
 
0.8%

Length

2024-05-11T00:20:40.650754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:20:41.793970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 755
96.9%
3층 12
 
1.5%
1층 6
 
0.8%
2층 6
 
0.8%

설치유형
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
3. 공원(하천)
116 
7-2-3. 공공 - 동주민센터
77 
2. 전통시장
72 
4. 문화관광
68 
6-2. 복지 - 노인
63 
Other values (12)
383 

Length

Max length21
Median length17
Mean length12.648267
Min length7

Unique

Unique1 ?
Unique (%)0.1%

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 (%)
3. 공원(하천) 116
14.9%
7-2-3. 공공 - 동주민센터 77
9.9%
2. 전통시장 72
9.2%
4. 문화관광 68
8.7%
6-2. 복지 - 노인 63
8.1%
7-2-1. 공공 - 구청사 및 별관 62
8.0%
7-1-3. 공공 - 시산하기관 60
7.7%
6-4. 복지 - 아동청소년 57
7.3%
6-1. 복지 - 사회 50
6.4%
5-2. 버스정류소(시비) 45
 
5.8%
Other values (7) 109
14.0%

Length

2024-05-11T00:20:42.385538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
403
 
16.0%
공공 229
 
9.1%
복지 174
 
6.9%
3 116
 
4.6%
공원(하천 116
 
4.6%
및 78
 
3.1%
7-2-3 77
 
3.1%
동주민센터 77
 
3.1%
2 72
 
2.9%
전통시장 72
 
2.9%
Other values (30) 1106
43.9%

설치기관
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
자치구
277 
디지털뉴딜(KT)
237 
디지털뉴딜(LG U+)
131 
서울시(AP)
77 
버스정류소(국비)
38 
Other values (2)
 
19

Length

Max length12
Median length9
Mean length7.1681643
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 (%)
자치구 277
35.6%
디지털뉴딜(KT) 237
30.4%
디지털뉴딜(LG U+) 131
16.8%
서울시(AP) 77
 
9.9%
버스정류소(국비) 38
 
4.9%
버스정류소(시비) 15
 
1.9%
서울시(공유기) 4
 
0.5%

Length

2024-05-11T00:20:42.975400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:20:43.402975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자치구 277
30.4%
디지털뉴딜(kt 237
26.0%
디지털뉴딜(lg 131
14.4%
u 131
14.4%
서울시(ap 77
 
8.5%
버스정류소(국비 38
 
4.2%
버스정류소(시비 15
 
1.6%
서울시(공유기 4
 
0.4%

서비스구분
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
공공WiFi
480 
과기부WiFi(핫플레이스)
133 
과기부WiFi(복지시설)
104 
과기부WiFi
 
38
<NA>
 
24

Length

Max length14
Median length6
Mean length8.2875481
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공공WiFi 480
61.6%
과기부WiFi(핫플레이스) 133
 
17.1%
과기부WiFi(복지시설) 104
 
13.4%
과기부WiFi 38
 
4.9%
<NA> 24
 
3.1%

Length

2024-05-11T00:20:44.100541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:20:44.519339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공wifi 480
61.6%
과기부wifi(핫플레이스 133
 
17.1%
과기부wifi(복지시설 104
 
13.4%
과기부wifi 38
 
4.9%
na 24
 
3.1%

망종류
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
인터넷망_뉴딜용
368 
자가망_U무선망
218 
임대망
178 
<NA>
 
15

Length

Max length8
Median length8
Mean length6.7804878
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
인터넷망_뉴딜용 368
47.2%
자가망_U무선망 218
28.0%
임대망 178
22.8%
<NA> 15
 
1.9%

Length

2024-05-11T00:20:44.985637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:20:45.492056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인터넷망_뉴딜용 368
47.2%
자가망_u무선망 218
28.0%
임대망 178
22.8%
na 15
 
1.9%

설치년도
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2020.4326
Minimum2014
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.0 KiB
2024-05-11T00:20:45.942180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2014
5-th percentile2014
Q12020
median2022
Q32022
95-th percentile2023
Maximum2023
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.5771419
Coefficient of variation (CV)0.0012755397
Kurtosis1.3417882
Mean2020.4326
Median Absolute Deviation (MAD)1
Skewness-1.5562016
Sum1573917
Variance6.6416604
MonotonicityNot monotonic
2024-05-11T00:20:46.259044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
2022 358
46.0%
2021 114
 
14.6%
2014 82
 
10.5%
2019 69
 
8.9%
2020 57
 
7.3%
2023 56
 
7.2%
2018 29
 
3.7%
2017 14
 
1.8%
ValueCountFrequency (%)
2014 82
 
10.5%
2017 14
 
1.8%
2018 29
 
3.7%
2019 69
 
8.9%
2020 57
 
7.3%
2021 114
 
14.6%
2022 358
46.0%
2023 56
 
7.2%
ValueCountFrequency (%)
2023 56
 
7.2%
2022 358
46.0%
2021 114
 
14.6%
2020 57
 
7.3%
2019 69
 
8.9%
2018 29
 
3.7%
2017 14
 
1.8%
2014 82
 
10.5%

실내외구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
실내
442 
실외
337 

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 442
56.7%
실외 337
43.3%

Length

2024-05-11T00:20:46.681298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:20:47.073293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
실내 442
56.7%
실외 337
43.3%

wifi접속환경
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
<NA>
749 
보안접속 임시적용(머큐리 Proxy 서버 개발중)
 
30

Length

Max length27
Median length4
Mean length4.885751
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> 749
96.1%
보안접속 임시적용(머큐리 Proxy 서버 개발중) 30
 
3.9%

Length

2024-05-11T00:20:47.521051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:20:47.893414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 749
83.3%
보안접속 30
 
3.3%
임시적용(머큐리 30
 
3.3%
proxy 30
 
3.3%
서버 30
 
3.3%
개발중 30
 
3.3%

X좌표
Real number (ℝ)

HIGH CORRELATION 

Distinct303
Distinct (%)38.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.598982
Minimum37.554962
Maximum37.61984
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.0 KiB
2024-05-11T00:20:48.226790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.554962
5-th percentile37.573223
Q137.589645
median37.604115
Q337.606739
95-th percentile37.614803
Maximum37.61984
Range0.064878
Interquartile range (IQR)0.0170935

Descriptive statistics

Standard deviation0.013033402
Coefficient of variation (CV)0.00034664242
Kurtosis-0.067426278
Mean37.598982
Median Absolute Deviation (MAD)0.007222
Skewness-0.8489227
Sum29289.607
Variance0.00016986957
MonotonicityNot monotonic
2024-05-11T00:20:48.671097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.606525 71
 
9.1%
37.61281 48
 
6.2%
37.573223 22
 
2.8%
37.588432 20
 
2.6%
37.59745 17
 
2.2%
37.604115 15
 
1.9%
37.61522 15
 
1.9%
37.606056 14
 
1.8%
37.608562 12
 
1.5%
37.609573 11
 
1.4%
Other values (293) 534
68.5%
ValueCountFrequency (%)
37.554962 5
 
0.6%
37.571575 1
 
0.1%
37.572117 9
1.2%
37.572388 9
1.2%
37.572857 1
 
0.1%
37.57304 1
 
0.1%
37.573135 1
 
0.1%
37.573223 22
2.8%
37.573273 1
 
0.1%
37.57338 1
 
0.1%
ValueCountFrequency (%)
37.61984 1
0.1%
37.619476 1
0.1%
37.619263 1
0.1%
37.618507 1
0.1%
37.61808 1
0.1%
37.617786 1
0.1%
37.617718 1
0.1%
37.61734 1
0.1%
37.617302 1
0.1%
37.617226 1
0.1%

Y좌표
Real number (ℝ)

HIGH CORRELATION 

Distinct299
Distinct (%)38.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.09092
Minimum127.07182
Maximum127.11376
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.0 KiB
2024-05-11T00:20:49.127055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.07182
5-th percentile127.07567
Q1127.08564
median127.09159
Q3127.09627
95-th percentile127.11037
Maximum127.11376
Range0.041945
Interquartile range (IQR)0.010627

Descriptive statistics

Standard deviation0.0099496823
Coefficient of variation (CV)7.8287907 × 10-5
Kurtosis-0.3847984
Mean127.09092
Median Absolute Deviation (MAD)0.00591
Skewness0.30189767
Sum99003.828
Variance9.8996177 × 10-5
MonotonicityNot monotonic
2024-05-11T00:20:49.654862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0928 71
 
9.1%
127.09822 48
 
6.2%
127.08597 22
 
2.8%
127.088264 20
 
2.6%
127.07784 20
 
2.6%
127.08694 16
 
2.1%
127.096054 15
 
1.9%
127.092155 14
 
1.8%
127.094765 12
 
1.5%
127.07599 11
 
1.4%
Other values (289) 530
68.0%
ValueCountFrequency (%)
127.071815 1
0.1%
127.072815 1
0.1%
127.07287 1
0.1%
127.073006 1
0.1%
127.07302 1
0.1%
127.07309 1
0.1%
127.0731 2
0.3%
127.07348 1
0.1%
127.07351 1
0.1%
127.07367 2
0.3%
ValueCountFrequency (%)
127.11376 3
0.4%
127.11345 2
0.3%
127.11322 2
0.3%
127.11303 1
 
0.1%
127.112724 1
 
0.1%
127.11221 1
 
0.1%
127.11158 1
 
0.1%
127.111435 1
 
0.1%
127.1114 1
 
0.1%
127.111374 1
 
0.1%

작업일자
Date

Distinct12
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
Minimum2024-05-10 11:12:51
Maximum2024-05-10 11:13:05
2024-05-11T00:20:50.147356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:20:50.506372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)

Interactions

2024-05-11T00:20:26.898641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:20:24.915592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:20:25.860676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:20:27.168378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:20:25.195956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:20:26.238291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:20:27.488876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:20:25.512415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:20:26.534140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T00:20:50.794219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치위치(층)설치유형설치기관서비스구분망종류설치년도실내외구분X좌표Y좌표작업일자
설치위치(층)1.000NaNNaNNaNNaNNaNNaN0.0000.000NaN
설치유형NaN1.0000.9020.9500.8860.7810.9450.7750.7710.882
설치기관NaN0.9021.0000.8750.9680.8750.4210.4550.5410.967
서비스구분NaN0.9500.8751.0000.5710.6270.8470.4890.4310.983
망종류NaN0.8860.9680.5711.0000.7680.2170.6030.5530.877
설치년도NaN0.7810.8750.6270.7681.0000.2860.4850.6110.836
실내외구분NaN0.9450.4210.8470.2170.2861.0000.3500.6070.618
X좌표0.0000.7750.4550.4890.6030.4850.3501.0000.6400.604
Y좌표0.0000.7710.5410.4310.5530.6110.6070.6401.0000.651
작업일자NaN0.8820.9670.9830.8770.8360.6180.6040.6511.000
2024-05-11T00:20:51.109565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
망종류설치위치(층)서비스구분설치유형설치기관실내외구분wifi접속환경
망종류1.0001.0000.5800.7560.7790.3551.000
설치위치(층)1.0001.000NaN1.0001.0001.000NaN
서비스구분0.580NaN1.0000.8540.8130.6441.000
설치유형0.7561.0000.8541.0000.6980.9221.000
설치기관0.7791.0000.8130.6981.0000.4501.000
실내외구분0.3551.0000.6440.9220.4501.0001.000
wifi접속환경1.000NaN1.0001.0001.0001.0001.000
2024-05-11T00:20:51.425496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치년도X좌표Y좌표설치위치(층)설치유형설치기관서비스구분망종류실내외구분wifi접속환경
설치년도1.0000.043-0.0211.0000.4910.5160.5000.7740.4161.000
X좌표0.0431.0000.2770.0000.4450.2600.3330.3260.3491.000
Y좌표-0.0210.2771.0000.0000.4330.3110.2700.3950.4671.000
설치위치(층)1.0000.0000.0001.0001.0001.0000.0001.0001.0000.000
설치유형0.4910.4450.4331.0001.0000.6980.8540.7560.9221.000
설치기관0.5160.2600.3111.0000.6981.0000.8130.7790.4501.000
서비스구분0.5000.3330.2700.0000.8540.8131.0000.5800.6441.000
망종류0.7740.3260.3951.0000.7560.7790.5801.0000.3551.000
실내외구분0.4160.3490.4671.0000.9220.4500.6440.3551.0001.000
wifi접속환경1.0001.0001.0000.0001.0001.0001.0001.0001.0001.000

Missing values

2024-05-11T00:20:28.112268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T00:20:28.924569image/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.
2024-05-11T00:20:29.634648image/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
0BS101249중랑구버스정류소_경남아너스빌아파트앞면목동152907-122<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.57475127.0801542024-05-10 11:12:51.0
1BS101250중랑구버스정류소_극동늘푸른아파트묵동 37907-101<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.614704127.07642024-05-10 11:12:51.0
2BS101251중랑구버스정류소_금란교회망우로07-011<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.600452127.1040342024-05-10 11:12:51.0
3BS101252중랑구버스정류소_금란교회망우로07-012<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.600307127.103382024-05-10 11:12:51.0
4BS101253중랑구버스정류소_동부제일병원.망우리공원망우로07-013<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.600464127.10892024-05-10 11:12:51.0
5BS101254중랑구버스정류소_동부제일병원.망우리공원망우로07-014<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.60048127.107762024-05-10 11:12:51.0
6BS101255중랑구버스정류소_망우역.망우지구대망우로07-007<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.59882127.0955662024-05-10 11:12:51.0
7BS101256중랑구버스정류소_망우역.망우지구대망우로07-008<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.598557127.094872024-05-10 11:12:51.0
8BS101257중랑구버스정류소_망우역.상봉터미널망우로07-001<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.597828127.091142024-05-10 11:12:51.0
9BS101258중랑구버스정류소_망우역.상봉터미널망우로07-002<NA>5-1. 버스정류소(국비)버스정류소(국비)과기부WiFi임대망2021실외<NA>37.597507127.090352024-05-10 11:12:51.0
관리번호자치구와이파이명도로명주소상세주소설치위치(층)설치유형설치기관서비스구분망종류설치년도실내외구분wifi접속환경X좌표Y좌표작업일자
769서울5차-0724-2중랑구중랑구립정보도서관서울특별시 중랑구 신내로15길 197로비3층4. 문화관광디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.61522127.086942024-05-10 11:13:05.0
770서울5차-0725중랑구장미마을소망도서관서울특별시 중랑구 동일로157라길 12-22IDF 위1층4. 문화관광디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.61101127.0751952024-05-10 11:13:05.0
771서울5차-0725-1중랑구장미마을소망도서관서울특별시 중랑구 동일로157라길 12-22엘리베이터 앞1층4. 문화관광디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.61101127.0751952024-05-10 11:13:05.0
772서울5차-0725-2중랑구장미마을소망도서관서울특별시 중랑구 동일로157라길 12-22출입구 위1층4. 문화관광디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.61101127.0751952024-05-10 11:13:05.0
773서울5차-0726중랑구장미마을소망도서관서울특별시 중랑구 동일로157라길 12-22안내데스크 위2층4. 문화관광디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.611015127.0751952024-05-10 11:13:05.0
774서울5차-0726-1중랑구장미마을소망도서관서울특별시 중랑구 동일로157라길 12-22엘리베이터 위2층4. 문화관광디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.611015127.0751952024-05-10 11:13:05.0
775서울5차-0726-2중랑구장미마을소망도서관서울특별시 중랑구 동일로157라길 12-22열람실2층4. 문화관광디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.611015127.0751952024-05-10 11:13:05.0
776서울5차-0727중랑구장미마을소망도서관서울특별시 중랑구 동일로157라길 12-22화장실 앞3층4. 문화관광디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.61101127.0751952024-05-10 11:13:05.0
777서울5차-0727-1중랑구장미마을소망도서관서울특별시 중랑구 동일로157라길 12-22엘리베이터 위3층4. 문화관광디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.61101127.0751952024-05-10 11:13:05.0
778서울5차-0727-2중랑구장미마을소망도서관서울특별시 중랑구 동일로157라길 12-22회의실3층4. 문화관광디지털뉴딜(LG U+)<NA>인터넷망_뉴딜용2023실내<NA>37.61101127.0751952024-05-10 11:13:05.0