Overview

Dataset statistics

Number of variables9
Number of observations41
Missing cells1
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.1 KiB
Average record size in memory78.2 B

Variable types

Numeric3
Categorical3
Text3

Dataset

Description인천광역시 계양구 관내 이재민 임시주거시설 현황에 대한 데이터로, 연번, 구분, 행정동, 시설명, 주소, 면적, 수용인원, 전화번호 등을 제공합니다.
Author인천광역시 계양구
URLhttps://www.data.go.kr/data/15040165/fileData.do

Alerts

연번 is highly overall correlated with 행정동High correlation
면적(제곱미터) is highly overall correlated with 수용인원 and 1 other fieldsHigh correlation
수용인원 is highly overall correlated with 면적(제곱미터) and 1 other fieldsHigh correlation
구분 is highly overall correlated with 면적(제곱미터) and 2 other fieldsHigh correlation
행정동 is highly overall correlated with 연번High correlation
위치상세 is highly overall correlated with 구분High correlation
구분 is highly imbalanced (50.5%)Imbalance
전화번호 has 1 (2.4%) missing valuesMissing
연번 has unique valuesUnique
시설명 has unique valuesUnique
주소 has unique valuesUnique

Reproduction

Analysis started2023-12-12 17:56:43.128649
Analysis finished2023-12-12 17:56:44.471781
Duration1.34 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21
Minimum1
Maximum41
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-13T02:56:44.547297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q111
median21
Q331
95-th percentile39
Maximum41
Range40
Interquartile range (IQR)20

Descriptive statistics

Standard deviation11.979149
Coefficient of variation (CV)0.57043565
Kurtosis-1.2
Mean21
Median Absolute Deviation (MAD)10
Skewness0
Sum861
Variance143.5
MonotonicityStrictly increasing
2023-12-13T02:56:44.695189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
1 1
 
2.4%
32 1
 
2.4%
24 1
 
2.4%
25 1
 
2.4%
26 1
 
2.4%
27 1
 
2.4%
28 1
 
2.4%
29 1
 
2.4%
30 1
 
2.4%
31 1
 
2.4%
Other values (31) 31
75.6%
ValueCountFrequency (%)
1 1
2.4%
2 1
2.4%
3 1
2.4%
4 1
2.4%
5 1
2.4%
6 1
2.4%
7 1
2.4%
8 1
2.4%
9 1
2.4%
10 1
2.4%
ValueCountFrequency (%)
41 1
2.4%
40 1
2.4%
39 1
2.4%
38 1
2.4%
37 1
2.4%
36 1
2.4%
35 1
2.4%
34 1
2.4%
33 1
2.4%
32 1
2.4%

구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)14.6%
Missing0
Missing (%)0.0%
Memory size460.0 B
학교
31 
관공서
5 
경로당
 
2
연수+숙박
 
1
기타시설
 
1

Length

Max length5
Median length2
Mean length2.3414634
Min length2

Unique

Unique3 ?
Unique (%)7.3%

Sample

1st row경로당
2nd row학교
3rd row학교
4th row관공서
5th row관공서

Common Values

ValueCountFrequency (%)
학교 31
75.6%
관공서 5
 
12.2%
경로당 2
 
4.9%
연수+숙박 1
 
2.4%
기타시설 1
 
2.4%
마을회관 1
 
2.4%

Length

2023-12-13T02:56:44.880631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:56:45.106657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
학교 31
75.6%
관공서 5
 
12.2%
경로당 2
 
4.9%
연수+숙박 1
 
2.4%
기타시설 1
 
2.4%
마을회관 1
 
2.4%

행정동
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)29.3%
Missing0
Missing (%)0.0%
Memory size460.0 B
계산2동
5 
계양1동
5 
효성2동
4 
계산4동
4 
작전1동
4 
Other values (7)
19 

Length

Max length5
Median length4
Mean length4.097561
Min length4

Unique

Unique1 ?
Unique (%)2.4%

Sample

1st row효성1동
2nd row효성1동
3rd row효성1동
4th row효성2동
5th row효성2동

Common Values

ValueCountFrequency (%)
계산2동 5
12.2%
계양1동 5
12.2%
효성2동 4
9.8%
계산4동 4
9.8%
작전1동 4
9.8%
작전서운동 4
9.8%
효성1동 3
7.3%
계산1동 3
7.3%
계산3동 3
7.3%
계양2동 3
7.3%
Other values (2) 3
7.3%

Length

2023-12-13T02:56:45.347131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
계산2동 5
12.2%
계양1동 5
12.2%
효성2동 4
9.8%
계산4동 4
9.8%
작전1동 4
9.8%
작전서운동 4
9.8%
효성1동 3
7.3%
계산1동 3
7.3%
계산3동 3
7.3%
계양2동 3
7.3%
Other values (2) 3
7.3%

시설명
Text

UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-12-13T02:56:45.614016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length9.5365854
Min length6

Characters and Unicode

Total characters391
Distinct characters76
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)100.0%

Sample

1st row효성1동 경로당
2nd row효성고등학교 체육관
3rd row효성남초등학교 교실
4th row효성체육문화센터
5th row효성2동 주민센터 본관
ValueCountFrequency (%)
강당 19
23.5%
체육관 7
 
8.6%
교실 4
 
4.9%
본관 4
 
4.9%
계양초등학교 2
 
2.5%
주민센터 2
 
2.5%
장기황어체육관 1
 
1.2%
작전고등학교 1
 
1.2%
작전여자고등학교 1
 
1.2%
화전초등학교 1
 
1.2%
Other values (39) 39
48.1%
2023-12-13T02:56:46.214910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
40
 
10.2%
교 37
 
9.5%
학 32
 
8.2%
등 24
 
6.1%
당 22
 
5.6%
강 19
 
4.9%
초 15
 
3.8%
관 15
 
3.8%
육 11
 
2.8%
계 10
 
2.6%
Other values (66) 166
42.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 348
89.0%
Space Separator 40
 
10.2%
Decimal Number 3
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 37
 
10.6%
학 32
 
9.2%
등 24
 
6.9%
당 22
 
6.3%
강 19
 
5.5%
초 15
 
4.3%
관 15
 
4.3%
육 11
 
3.2%
계 10
 
2.9%
체 10
 
2.9%
Other values (63) 153
44.0%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
1 1
33.3%
Space Separator
ValueCountFrequency (%)
40
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 348
89.0%
Common 43
 
11.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 37
 
10.6%
학 32
 
9.2%
등 24
 
6.9%
당 22
 
6.3%
강 19
 
5.5%
초 15
 
4.3%
관 15
 
4.3%
육 11
 
3.2%
계 10
 
2.9%
체 10
 
2.9%
Other values (63) 153
44.0%
Common
ValueCountFrequency (%)
40
93.0%
2 2
 
4.7%
1 1
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 348
89.0%
ASCII 43
 
11.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
40
93.0%
2 2
 
4.7%
1 1
 
2.3%
Hangul
ValueCountFrequency (%)
교 37
 
10.6%
학 32
 
9.2%
등 24
 
6.9%
당 22
 
6.3%
강 19
 
5.5%
초 15
 
4.3%
관 15
 
4.3%
육 11
 
3.2%
계 10
 
2.9%
체 10
 
2.9%
Other values (63) 153
44.0%

주소
Text

UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-12-13T02:56:46.571181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length26
Mean length23.804878
Min length20

Characters and Unicode

Total characters976
Distinct characters72
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)100.0%

Sample

1st row인천광역시 계양구 봉오대로538번길 7(효성동)
2nd row인천광역시 계양구 새벌로171번길 21(효성동)
3rd row인천광역시 계양구 새벌로 125(효성동)
4th row인천광역시 계양구 마장로544번길 13(효성동)
5th row인천광역시 계양구 아나지로 162(효성동)
ValueCountFrequency (%)
인천광역시 41
24.7%
계양구 41
24.7%
장제로 3
 
1.8%
주부토로 2
 
1.2%
6(계산동 2
 
1.2%
아나지로 2
 
1.2%
박촌로 2
 
1.2%
8(작전동 2
 
1.2%
5(계산동 2
 
1.2%
봉오대로 2
 
1.2%
Other values (67) 67
40.4%
2023-12-13T02:56:47.061826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
125
 
12.8%
계 60
 
6.1%
양 45
 
4.6%
동 43
 
4.4%
인 41
 
4.2%
( 41
 
4.2%
광 41
 
4.2%
역 41
 
4.2%
시 41
 
4.2%
구 41
 
4.2%
Other values (62) 457
46.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 629
64.4%
Decimal Number 138
 
14.1%
Space Separator 125
 
12.8%
Open Punctuation 41
 
4.2%
Close Punctuation 41
 
4.2%
Dash Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
계 60
 
9.5%
양 45
 
7.2%
동 43
 
6.8%
인 41
 
6.5%
광 41
 
6.5%
역 41
 
6.5%
시 41
 
6.5%
구 41
 
6.5%
천 41
 
6.5%
로 40
 
6.4%
Other values (48) 195
31.0%
Decimal Number
ValueCountFrequency (%)
1 26
18.8%
5 22
15.9%
2 19
13.8%
3 13
9.4%
8 13
9.4%
7 11
8.0%
6 11
8.0%
4 10
 
7.2%
0 8
 
5.8%
9 5
 
3.6%
Space Separator
ValueCountFrequency (%)
125
100.0%
Open Punctuation
ValueCountFrequency (%)
( 41
100.0%
Close Punctuation
ValueCountFrequency (%)
) 41
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 629
64.4%
Common 347
35.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
계 60
 
9.5%
양 45
 
7.2%
동 43
 
6.8%
인 41
 
6.5%
광 41
 
6.5%
역 41
 
6.5%
시 41
 
6.5%
구 41
 
6.5%
천 41
 
6.5%
로 40
 
6.4%
Other values (48) 195
31.0%
Common
ValueCountFrequency (%)
125
36.0%
( 41
 
11.8%
) 41
 
11.8%
1 26
 
7.5%
5 22
 
6.3%
2 19
 
5.5%
3 13
 
3.7%
8 13
 
3.7%
7 11
 
3.2%
6 11
 
3.2%
Other values (4) 25
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 629
64.4%
ASCII 347
35.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
125
36.0%
( 41
 
11.8%
) 41
 
11.8%
1 26
 
7.5%
5 22
 
6.3%
2 19
 
5.5%
3 13
 
3.7%
8 13
 
3.7%
7 11
 
3.2%
6 11
 
3.2%
Other values (4) 25
 
7.2%
Hangul
ValueCountFrequency (%)
계 60
 
9.5%
양 45
 
7.2%
동 43
 
6.8%
인 41
 
6.5%
광 41
 
6.5%
역 41
 
6.5%
시 41
 
6.5%
구 41
 
6.5%
천 41
 
6.5%
로 40
 
6.4%
Other values (48) 195
31.0%

면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct40
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1389.9098
Minimum66
Maximum18718
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-13T02:56:47.276748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum66
5-th percentile160
Q1487
median663
Q31288
95-th percentile3148.23
Maximum18718
Range18652
Interquartile range (IQR)801

Descriptive statistics

Standard deviation2888.4226
Coefficient of variation (CV)2.0781368
Kurtosis34.408875
Mean1389.9098
Median Absolute Deviation (MAD)388
Skewness5.6680099
Sum56986.3
Variance8342985
MonotonicityNot monotonic
2023-12-13T02:56:47.526200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
662.0 2
 
4.9%
775.0 1
 
2.4%
3070.5 1
 
2.4%
263.0 1
 
2.4%
160.0 1
 
2.4%
389.0 1
 
2.4%
18718.0 1
 
2.4%
1540.32 1
 
2.4%
487.0 1
 
2.4%
86.0 1
 
2.4%
Other values (30) 30
73.2%
ValueCountFrequency (%)
66.0 1
2.4%
86.0 1
2.4%
160.0 1
2.4%
180.45 1
2.4%
198.0 1
2.4%
263.0 1
2.4%
275.0 1
2.4%
389.0 1
2.4%
395.0 1
2.4%
407.0 1
2.4%
ValueCountFrequency (%)
18718.0 1
2.4%
3169.0 1
2.4%
3148.23 1
2.4%
3070.5 1
2.4%
2257.5 1
2.4%
2125.0 1
2.4%
1848.0 1
2.4%
1540.32 1
2.4%
1375.0 1
2.4%
1360.0 1
2.4%

수용인원
Real number (ℝ)

HIGH CORRELATION 

Distinct40
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean368.92683
Minimum18
Maximum5199
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-13T02:56:47.811223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum18
5-th percentile44
Q1135
median184
Q3312
95-th percentile852
Maximum5199
Range5181
Interquartile range (IQR)177

Descriptive statistics

Standard deviation799.03102
Coefficient of variation (CV)2.1658252
Kurtosis35.56555
Mean368.92683
Median Absolute Deviation (MAD)96
Skewness5.7983099
Sum15126
Variance638450.57
MonotonicityNot monotonic
2023-12-13T02:56:48.011787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
183 2
 
4.9%
215 1
 
2.4%
852 1
 
2.4%
73 1
 
2.4%
44 1
 
2.4%
108 1
 
2.4%
5199 1
 
2.4%
427 1
 
2.4%
135 1
 
2.4%
23 1
 
2.4%
Other values (30) 30
73.2%
ValueCountFrequency (%)
18 1
2.4%
23 1
2.4%
44 1
2.4%
50 1
2.4%
55 1
2.4%
73 1
2.4%
76 1
2.4%
108 1
2.4%
109 1
2.4%
113 1
2.4%
ValueCountFrequency (%)
5199 1
2.4%
880 1
2.4%
852 1
2.4%
627 1
2.4%
590 1
2.4%
513 1
2.4%
427 1
2.4%
381 1
2.4%
377 1
2.4%
357 1
2.4%

위치상세
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)29.3%
Missing0
Missing (%)0.0%
Memory size460.0 B
강당
18 
체육관
8 
본관
6 
2층(여) 및 3층(남)
 
1
2층 배드민턴장
 
1
Other values (7)
7 

Length

Max length13
Median length2
Mean length3.0731707
Min length2

Unique

Unique9 ?
Unique (%)22.0%

Sample

1st row2층(여) 및 3층(남)
2nd row체육관
3rd row본관
4th row2층 배드민턴장
5th row본관

Common Values

ValueCountFrequency (%)
강당 18
43.9%
체육관 8
19.5%
본관 6
 
14.6%
2층(여) 및 3층(남) 1
 
2.4%
2층 배드민턴장 1
 
2.4%
신관 1
 
2.4%
별관4층 다목적실 1
 
2.4%
2층 1
 
2.4%
신관3층 강당 1
 
2.4%
본관2층 1
 
2.4%
Other values (2) 2
 
4.9%

Length

2023-12-13T02:56:48.201097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
강당 19
41.3%
체육관 8
17.4%
본관 6
 
13.0%
2층 2
 
4.3%
2층(여 1
 
2.2%
및 1
 
2.2%
3층(남 1
 
2.2%
배드민턴장 1
 
2.2%
신관 1
 
2.2%
별관4층 1
 
2.2%
Other values (5) 5
 
10.9%

전화번호
Text

MISSING 

Distinct39
Distinct (%)97.5%
Missing1
Missing (%)2.4%
Memory size460.0 B
2023-12-13T02:56:48.489581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters480
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)95.0%

Sample

1st row032-548-4872
2nd row032-556-8181
3rd row032-554-0493
4th row032-541-1277
5th row032-450-4736
ValueCountFrequency (%)
032-450-4851 2
 
5.0%
032-450-4864 1
 
2.5%
032-556-8181 1
 
2.5%
032-555-1595 1
 
2.5%
032-555-6216 1
 
2.5%
032-542-6553 1
 
2.5%
032-546-3551 1
 
2.5%
032-456-2268 1
 
2.5%
032-542-2942 1
 
2.5%
032-511-7168 1
 
2.5%
Other values (29) 29
72.5%
2023-12-13T02:56:48.952316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 83
17.3%
- 80
16.7%
2 64
13.3%
0 61
12.7%
3 57
11.9%
4 48
10.0%
6 22
 
4.6%
8 21
 
4.4%
1 19
 
4.0%
7 17
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 400
83.3%
Dash Punctuation 80
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 83
20.8%
2 64
16.0%
0 61
15.2%
3 57
14.2%
4 48
12.0%
6 22
 
5.5%
8 21
 
5.2%
1 19
 
4.8%
7 17
 
4.2%
9 8
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
- 80
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 480
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 83
17.3%
- 80
16.7%
2 64
13.3%
0 61
12.7%
3 57
11.9%
4 48
10.0%
6 22
 
4.6%
8 21
 
4.4%
1 19
 
4.0%
7 17
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 480
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 83
17.3%
- 80
16.7%
2 64
13.3%
0 61
12.7%
3 57
11.9%
4 48
10.0%
6 22
 
4.6%
8 21
 
4.4%
1 19
 
4.0%
7 17
 
3.5%

Interactions

2023-12-13T02:56:44.006398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:56:43.513181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:56:43.764871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:56:44.085157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:56:43.601221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:56:43.846123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:56:44.163267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:56:43.692893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:56:43.930699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:56:49.123241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구분행정동시설명주소면적(제곱미터)수용인원위치상세전화번호
연번1.0000.0000.8901.0001.0000.0000.0000.5041.000
구분0.0001.0000.0001.0001.0000.9540.9250.8950.000
행정동0.8900.0001.0001.0001.0000.4880.0000.0001.000
시설명1.0001.0001.0001.0001.0001.0001.0001.0001.000
주소1.0001.0001.0001.0001.0001.0001.0001.0001.000
면적(제곱미터)0.0000.9540.4881.0001.0001.0000.9980.0001.000
수용인원0.0000.9250.0001.0001.0000.9981.0000.0001.000
위치상세0.5040.8950.0001.0001.0000.0000.0001.0001.000
전화번호1.0000.0001.0001.0001.0001.0001.0001.0001.000
2023-12-13T02:56:49.286076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동위치상세구분
행정동1.0000.0000.000
위치상세0.0001.0000.515
구분0.0000.5151.000
2023-12-13T02:56:49.436548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번면적(제곱미터)수용인원구분행정동위치상세
연번1.000-0.288-0.2870.0610.7220.143
면적(제곱미터)-0.2881.0000.9760.7080.2060.000
수용인원-0.2870.9761.0000.6420.0000.000
구분0.0610.7080.6421.0000.0000.515
행정동0.7220.2060.0000.0001.0000.000
위치상세0.1430.0000.0000.5150.0001.000

Missing values

2023-12-13T02:56:44.278406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:56:44.404341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

연번구분행정동시설명주소면적(제곱미터)수용인원위치상세전화번호
01경로당효성1동효성1동 경로당인천광역시 계양구 봉오대로538번길 7(효성동)180.45502층(여) 및 3층(남)032-548-4872
12학교효성1동효성고등학교 체육관인천광역시 계양구 새벌로171번길 21(효성동)1288.0357체육관032-556-8181
23학교효성1동효성남초등학교 교실인천광역시 계양구 새벌로 125(효성동)1360.0377본관032-554-0493
34관공서효성2동효성체육문화센터인천광역시 계양구 마장로544번길 13(효성동)1375.03812층 배드민턴장032-541-1277
45관공서효성2동효성2동 주민센터 본관인천광역시 계양구 아나지로 162(효성동)516.0143본관032-450-4736
56학교효성2동북인천여자중학교 체육관인천광역시 계양구 아나지로85번길 12(효성동)836.0232체육관032-340-8640
67학교효성2동효성서초등학교 교실인천광역시 계양구 봉오대로 457(효성동)528.0146신관032-547-5085
78학교계산1동경인교육대학교 체육관인천광역시 계양구 계산로 62(계산동)3169.0880체육관032-540-1415
89학교계산1동부평초등학교 강당인천광역시 계양구 어사대로 20(계산동)275.076별관4층 다목적실032-628-4407
910학교계산1동북인천중학교 강당인천광역시 계양구 계산로22번길 6(계산동)1066.0296강당032-554-5560
연번구분행정동시설명주소면적(제곱미터)수용인원위치상세전화번호
3132마을회관계양1동박촌마을회관 본관인천광역시 계양구 장제로 1000(박촌동)86.023본관032-450-4864
3233학교계양1동계양초등학교 강당인천광역시 계양구 장제로 1288(장기동)198.055강당032-515-4647
3334학교계양1동소양초등학교 강당인천광역시 계양구 박촌로 53(박촌동)584.0162강당032-515-5022
3435학교계양2동병방초등학교 강당인천광역시 계양구 병방로 2(병방동)551.3153강당032-548-8345
3536학교계산2동안산초등학교 강당인천광역시 계양구 임학서로 15(계산동)2257.5627강당032-555-6065
3637학교계양2동예일고등학교 강당인천광역시 계양구 박촌로 23(방축동)1011.0280강당032-555-6305
3738학교계양2동임학중학교 강당인천광역시 계양구 장제로 894(병방동)395.0109강당032-552-2124
3839학교계양1동계양초등학교 상야분교인천광역시 계양구 벌말로 572-1 (상야동)66.018강당032-544-5533
3940학교계양3동귤현초등학교 강당인천광역시 계양구 귤현길 15(귤현동)407.0113강당032-511-7168
4041학교계양3동당산초등학교 강당인천광역시 계양구 동양로 122(동양동)521.0144강당032-515-3873