Overview

Dataset statistics

Number of variables7
Number of observations71
Missing cells6
Missing cells (%)1.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.2 KiB
Average record size in memory60.9 B

Variable types

Numeric3
Categorical1
Text3

Dataset

Description인천광역시 연수구의 비상대피시설 현황 데이터로서 연번, 행정동, 시설명, 시설위치(도로명), 시설위치(지번), 시설규모, 활용가능인원 등의 항목으로 이루어져 있습니다.
URLhttps://www.data.go.kr/data/15116412/fileData.do

Alerts

연번 is highly overall correlated with 시설규모(㎡) and 2 other fieldsHigh correlation
시설규모(㎡) is highly overall correlated with 연번 and 1 other fieldsHigh correlation
활용가능인원(명) is highly overall correlated with 연번 and 1 other fieldsHigh correlation
행정동 is highly overall correlated with 연번High correlation
시설위치(도로명) has 6 (8.5%) missing valuesMissing
연번 has unique valuesUnique
시설명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 16:36:04.574124
Analysis finished2023-12-12 16:36:06.038182
Duration1.46 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct71
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36
Minimum1
Maximum71
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size771.0 B
2023-12-13T01:36:06.352240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.5
Q118.5
median36
Q353.5
95-th percentile67.5
Maximum71
Range70
Interquartile range (IQR)35

Descriptive statistics

Standard deviation20.639767
Coefficient of variation (CV)0.57332687
Kurtosis-1.2
Mean36
Median Absolute Deviation (MAD)18
Skewness0
Sum2556
Variance426
MonotonicityStrictly increasing
2023-12-13T01:36:06.494049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.4%
2 1
 
1.4%
53 1
 
1.4%
52 1
 
1.4%
51 1
 
1.4%
50 1
 
1.4%
49 1
 
1.4%
48 1
 
1.4%
47 1
 
1.4%
46 1
 
1.4%
Other values (61) 61
85.9%
ValueCountFrequency (%)
1 1
1.4%
2 1
1.4%
3 1
1.4%
4 1
1.4%
5 1
1.4%
6 1
1.4%
7 1
1.4%
8 1
1.4%
9 1
1.4%
10 1
1.4%
ValueCountFrequency (%)
71 1
1.4%
70 1
1.4%
69 1
1.4%
68 1
1.4%
67 1
1.4%
66 1
1.4%
65 1
1.4%
64 1
1.4%
63 1
1.4%
62 1
1.4%

행정동
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)21.1%
Missing0
Missing (%)0.0%
Memory size700.0 B
송도1동
9 
송도2동
9 
선학동
7 
옥련2동
7 
옥련1동
6 
Other values (10)
33 

Length

Max length4
Median length4
Mean length3.8450704
Min length3

Unique

Unique1 ?
Unique (%)1.4%

Sample

1st row동춘2동
2nd row동춘3동
3rd row연수2동
4th row연수3동
5th row선학동

Common Values

ValueCountFrequency (%)
송도1동 9
12.7%
송도2동 9
12.7%
선학동 7
9.9%
옥련2동 7
9.9%
옥련1동 6
8.5%
동춘3동 5
7.0%
연수2동 5
7.0%
송도4동 5
7.0%
청학동 4
 
5.6%
연수3동 3
 
4.2%
Other values (5) 11
15.5%

Length

2023-12-13T01:36:06.633637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
송도1동 9
12.7%
송도2동 9
12.7%
선학동 7
9.9%
옥련2동 7
9.9%
옥련1동 6
8.5%
동춘3동 5
7.0%
연수2동 5
7.0%
송도4동 5
7.0%
청학동 4
 
5.6%
연수3동 3
 
4.2%
Other values (5) 11
15.5%

시설명
Text

UNIQUE 

Distinct71
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size700.0 B
2023-12-13T01:36:06.804166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length25
Mean length16.323944
Min length3

Characters and Unicode

Total characters1159
Distinct characters147
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique71 ?
Unique (%)100.0%

Sample

1st row동막역
2nd row동춘역
3rd row원인재역 지하1층
4th row신연수역
5th row선학역
ValueCountFrequency (%)
지하주차장 56
29.2%
1층 36
18.8%
1~2층 16
 
8.3%
1~3층 2
 
1.0%
연수우성1차아파트 2
 
1.0%
삼성럭키아파트 1
 
0.5%
테크노파크역 1
 
0.5%
한양1차아파트 1
 
0.5%
연수풍림1차아파트 1
 
0.5%
옥련현대5차아파트 1
 
0.5%
Other values (75) 75
39.1%
2023-12-13T01:36:07.088671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
121
 
10.4%
지 74
 
6.4%
차 73
 
6.3%
1 71
 
6.1%
하 62
 
5.3%
주 61
 
5.3%
층 59
 
5.1%
장 57
 
4.9%
아 53
 
4.6%
파 53
 
4.6%
Other values (137) 475
41.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 908
78.3%
Space Separator 121
 
10.4%
Decimal Number 107
 
9.2%
Math Symbol 19
 
1.6%
Other Punctuation 2
 
0.2%
Uppercase Letter 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 74
 
8.1%
차 73
 
8.0%
하 62
 
6.8%
주 61
 
6.7%
층 59
 
6.5%
장 57
 
6.3%
아 53
 
5.8%
파 53
 
5.8%
트 52
 
5.7%
송 18
 
2.0%
Other values (124) 346
38.1%
Decimal Number
ValueCountFrequency (%)
1 71
66.4%
2 25
 
23.4%
3 5
 
4.7%
8 2
 
1.9%
4 1
 
0.9%
5 1
 
0.9%
0 1
 
0.9%
6 1
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
T 1
50.0%
I 1
50.0%
Space Separator
ValueCountFrequency (%)
121
100.0%
Math Symbol
ValueCountFrequency (%)
~ 19
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 908
78.3%
Common 249
 
21.5%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 74
 
8.1%
차 73
 
8.0%
하 62
 
6.8%
주 61
 
6.7%
층 59
 
6.5%
장 57
 
6.3%
아 53
 
5.8%
파 53
 
5.8%
트 52
 
5.7%
송 18
 
2.0%
Other values (124) 346
38.1%
Common
ValueCountFrequency (%)
121
48.6%
1 71
28.5%
2 25
 
10.0%
~ 19
 
7.6%
3 5
 
2.0%
8 2
 
0.8%
, 2
 
0.8%
4 1
 
0.4%
5 1
 
0.4%
0 1
 
0.4%
Latin
ValueCountFrequency (%)
T 1
50.0%
I 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 908
78.3%
ASCII 251
 
21.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
121
48.2%
1 71
28.3%
2 25
 
10.0%
~ 19
 
7.6%
3 5
 
2.0%
8 2
 
0.8%
, 2
 
0.8%
T 1
 
0.4%
I 1
 
0.4%
4 1
 
0.4%
Other values (3) 3
 
1.2%
Hangul
ValueCountFrequency (%)
지 74
 
8.1%
차 73
 
8.0%
하 62
 
6.8%
주 61
 
6.7%
층 59
 
6.5%
장 57
 
6.3%
아 53
 
5.8%
파 53
 
5.8%
트 52
 
5.7%
송 18
 
2.0%
Other values (124) 346
38.1%

시설위치(도로명)
Text

MISSING 

Distinct65
Distinct (%)100.0%
Missing6
Missing (%)8.5%
Memory size700.0 B
2023-12-13T01:36:07.319841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length41
Mean length35.061538
Min length28

Characters and Unicode

Total characters2279
Distinct characters173
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique65 ?
Unique (%)100.0%

Sample

1st row인천광역시 연수구 원인재로 115 (동춘동, 연수구청)
2nd row인천광역시 연수구 한나루로79번길 11 (옥련동, 백산1차아파트)
3rd row인천광역시 연수구 독배로40번길 18 (옥련동, 삼성아파트)
4th row인천광역시 연수구 독배로40번길 48 (옥련동, 우성1차아파트)
5th row인천광역시 연수구 청량로185번길 16 (옥련동, 서해아파트)
ValueCountFrequency (%)
인천광역시 65
 
16.0%
연수구 65
 
16.0%
송도동 27
 
6.7%
옥련동 13
 
3.2%
연수동 9
 
2.2%
원인재로 7
 
1.7%
동춘동 6
 
1.5%
지하 6
 
1.5%
인천타워대로 5
 
1.2%
선학동 5
 
1.2%
Other values (168) 198
48.8%
2023-12-13T01:36:07.716526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
341
 
15.0%
연 80
 
3.5%
수 80
 
3.5%
인 78
 
3.4%
동 74
 
3.2%
시 73
 
3.2%
천 72
 
3.2%
역 71
 
3.1%
구 68
 
3.0%
로 66
 
2.9%
Other values (163) 1276
56.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1505
66.0%
Space Separator 341
 
15.0%
Decimal Number 236
 
10.4%
Close Punctuation 65
 
2.9%
Open Punctuation 65
 
2.9%
Other Punctuation 65
 
2.9%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
연 80
 
5.3%
수 80
 
5.3%
인 78
 
5.2%
동 74
 
4.9%
시 73
 
4.9%
천 72
 
4.8%
역 71
 
4.7%
구 68
 
4.5%
로 66
 
4.4%
광 65
 
4.3%
Other values (146) 778
51.7%
Decimal Number
ValueCountFrequency (%)
1 60
25.4%
2 35
14.8%
4 24
 
10.2%
8 20
 
8.5%
0 20
 
8.5%
5 18
 
7.6%
3 17
 
7.2%
7 16
 
6.8%
6 16
 
6.8%
9 10
 
4.2%
Other Punctuation
ValueCountFrequency (%)
, 64
98.5%
& 1
 
1.5%
Uppercase Letter
ValueCountFrequency (%)
I 1
50.0%
T 1
50.0%
Space Separator
ValueCountFrequency (%)
341
100.0%
Close Punctuation
ValueCountFrequency (%)
) 65
100.0%
Open Punctuation
ValueCountFrequency (%)
( 65
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1505
66.0%
Common 772
33.9%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
연 80
 
5.3%
수 80
 
5.3%
인 78
 
5.2%
동 74
 
4.9%
시 73
 
4.9%
천 72
 
4.8%
역 71
 
4.7%
구 68
 
4.5%
로 66
 
4.4%
광 65
 
4.3%
Other values (146) 778
51.7%
Common
ValueCountFrequency (%)
341
44.2%
) 65
 
8.4%
( 65
 
8.4%
, 64
 
8.3%
1 60
 
7.8%
2 35
 
4.5%
4 24
 
3.1%
8 20
 
2.6%
0 20
 
2.6%
5 18
 
2.3%
Other values (5) 60
 
7.8%
Latin
ValueCountFrequency (%)
I 1
50.0%
T 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1505
66.0%
ASCII 774
34.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
341
44.1%
) 65
 
8.4%
( 65
 
8.4%
, 64
 
8.3%
1 60
 
7.8%
2 35
 
4.5%
4 24
 
3.1%
8 20
 
2.6%
0 20
 
2.6%
5 18
 
2.3%
Other values (7) 62
 
8.0%
Hangul
ValueCountFrequency (%)
연 80
 
5.3%
수 80
 
5.3%
인 78
 
5.2%
동 74
 
4.9%
시 73
 
4.9%
천 72
 
4.8%
역 71
 
4.7%
구 68
 
4.5%
로 66
 
4.4%
광 65
 
4.3%
Other values (146) 778
51.7%

시설위치(지번)
Text

Distinct69
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size700.0 B
2023-12-13T01:36:07.993697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length32
Mean length22.985915
Min length18

Characters and Unicode

Total characters1632
Distinct characters95
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique67 ?
Unique (%)94.4%

Sample

1st row인천광역시 연수구 동춘동 927번지 1호
2nd row인천광역시 연수구 동춘동 926번지 11호
3rd row인천광역시 연수구 연수동 647번지
4th row인천광역시 연수구 연수동 384번지
5th row인천광역시 연수구 선학동 241번지 2호
ValueCountFrequency (%)
인천광역시 71
20.2%
연수구 71
20.2%
송도동 27
 
7.7%
옥련동 13
 
3.7%
연수동 11
 
3.1%
동춘동 9
 
2.6%
1호 8
 
2.3%
선학동 7
 
2.0%
청학동 4
 
1.1%
7호 4
 
1.1%
Other values (110) 126
35.9%
2023-12-13T01:36:08.467763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
280
17.2%
연 84
 
5.1%
수 84
 
5.1%
동 83
 
5.1%
시 73
 
4.5%
천 72
 
4.4%
역 72
 
4.4%
인 71
 
4.4%
광 71
 
4.4%
구 71
 
4.4%
Other values (85) 671
41.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1101
67.5%
Space Separator 280
 
17.2%
Decimal Number 238
 
14.6%
Dash Punctuation 12
 
0.7%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
연 84
 
7.6%
수 84
 
7.6%
동 83
 
7.5%
시 73
 
6.6%
천 72
 
6.5%
역 72
 
6.5%
인 71
 
6.4%
광 71
 
6.4%
구 71
 
6.4%
지 45
 
4.1%
Other values (72) 375
34.1%
Decimal Number
ValueCountFrequency (%)
3 43
18.1%
1 40
16.8%
2 29
12.2%
5 26
10.9%
6 26
10.9%
4 22
9.2%
7 19
8.0%
9 16
 
6.7%
8 11
 
4.6%
0 6
 
2.5%
Space Separator
ValueCountFrequency (%)
280
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1101
67.5%
Common 531
32.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
연 84
 
7.6%
수 84
 
7.6%
동 83
 
7.5%
시 73
 
6.6%
천 72
 
6.5%
역 72
 
6.5%
인 71
 
6.4%
광 71
 
6.4%
구 71
 
6.4%
지 45
 
4.1%
Other values (72) 375
34.1%
Common
ValueCountFrequency (%)
280
52.7%
3 43
 
8.1%
1 40
 
7.5%
2 29
 
5.5%
5 26
 
4.9%
6 26
 
4.9%
4 22
 
4.1%
7 19
 
3.6%
9 16
 
3.0%
- 12
 
2.3%
Other values (3) 18
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1101
67.5%
ASCII 531
32.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
280
52.7%
3 43
 
8.1%
1 40
 
7.5%
2 29
 
5.5%
5 26
 
4.9%
6 26
 
4.9%
4 22
 
4.1%
7 19
 
3.6%
9 16
 
3.0%
- 12
 
2.3%
Other values (3) 18
 
3.4%
Hangul
ValueCountFrequency (%)
연 84
 
7.6%
수 84
 
7.6%
동 83
 
7.5%
시 73
 
6.6%
천 72
 
6.5%
역 72
 
6.5%
인 71
 
6.4%
광 71
 
6.4%
구 71
 
6.4%
지 45
 
4.1%
Other values (72) 375
34.1%

시설규모(㎡)
Real number (ℝ)

HIGH CORRELATION 

Distinct70
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11291.31
Minimum1215
Maximum96695
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size771.0 B
2023-12-13T01:36:08.597734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1215
5-th percentile1418.5
Q13654.5
median6227
Q312196
95-th percentile30729.5
Maximum96695
Range95480
Interquartile range (IQR)8541.5

Descriptive statistics

Standard deviation16872.017
Coefficient of variation (CV)1.494248
Kurtosis15.013035
Mean11291.31
Median Absolute Deviation (MAD)3172
Skewness3.7286045
Sum801683
Variance2.8466495 × 108
MonotonicityNot monotonic
2023-12-13T01:36:08.727997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4185 2
 
2.8%
2802 1
 
1.4%
10920 1
 
1.4%
6227 1
 
1.4%
2106 1
 
1.4%
9097 1
 
1.4%
4769 1
 
1.4%
2610 1
 
1.4%
5427 1
 
1.4%
16671 1
 
1.4%
Other values (60) 60
84.5%
ValueCountFrequency (%)
1215 1
1.4%
1349 1
1.4%
1372 1
1.4%
1382 1
1.4%
1455 1
1.4%
1669 1
1.4%
1762 1
1.4%
2106 1
1.4%
2162 1
1.4%
2347 1
1.4%
ValueCountFrequency (%)
96695 1
1.4%
85693 1
1.4%
67128 1
1.4%
40207 1
1.4%
21252 1
1.4%
21044 1
1.4%
20531 1
1.4%
19977 1
1.4%
19846 1
1.4%
18171 1
1.4%

활용가능인원(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct70
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13686.014
Minimum1472
Maximum117206
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size771.0 B
2023-12-13T01:36:08.865447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1472
5-th percentile1719
Q14429.5
median7547
Q314783
95-th percentile37247.5
Maximum117206
Range115734
Interquartile range (IQR)10353.5

Descriptive statistics

Standard deviation20450.982
Coefficient of variation (CV)1.4942979
Kurtosis15.013033
Mean13686.014
Median Absolute Deviation (MAD)3844
Skewness3.7286019
Sum971707
Variance4.1824268 × 108
MonotonicityNot monotonic
2023-12-13T01:36:09.009803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5072 2
 
2.8%
3396 1
 
1.4%
13236 1
 
1.4%
7547 1
 
1.4%
2552 1
 
1.4%
11027 1
 
1.4%
5780 1
 
1.4%
3163 1
 
1.4%
6578 1
 
1.4%
20207 1
 
1.4%
Other values (60) 60
84.5%
ValueCountFrequency (%)
1472 1
1.4%
1635 1
1.4%
1663 1
1.4%
1675 1
1.4%
1763 1
1.4%
2023 1
1.4%
2135 1
1.4%
2552 1
1.4%
2620 1
1.4%
2844 1
1.4%
ValueCountFrequency (%)
117206 1
1.4%
103870 1
1.4%
81367 1
1.4%
48735 1
1.4%
25760 1
1.4%
25508 1
1.4%
24886 1
1.4%
24214 1
1.4%
24055 1
1.4%
22025 1
1.4%

Interactions

2023-12-13T01:36:05.607923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:05.050486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:05.359411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:05.701970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:05.147380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:05.454292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:05.780056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:05.251218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:36:05.534317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:36:09.106038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번행정동시설명시설위치(도로명)시설위치(지번)시설규모(㎡)활용가능인원(명)
연번1.0000.8731.0001.0000.9710.3930.393
행정동0.8731.0001.0001.0000.9890.7340.734
시설명1.0001.0001.0001.0001.0001.0001.000
시설위치(도로명)1.0001.0001.0001.0001.0001.0001.000
시설위치(지번)0.9710.9891.0001.0001.0001.0001.000
시설규모(㎡)0.3930.7341.0001.0001.0001.0001.000
활용가능인원(명)0.3930.7341.0001.0001.0001.0001.000
2023-12-13T01:36:09.210134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시설규모(㎡)활용가능인원(명)행정동
연번1.0000.5400.5400.548
시설규모(㎡)0.5401.0001.0000.417
활용가능인원(명)0.5401.0001.0000.417
행정동0.5480.4170.4171.000

Missing values

2023-12-13T01:36:05.891734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:36:05.992672image/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

연번행정동시설명시설위치(도로명)시설위치(지번)시설규모(㎡)활용가능인원(명)
01동춘2동동막역<NA>인천광역시 연수구 동춘동 927번지 1호41855072
12동춘3동동춘역<NA>인천광역시 연수구 동춘동 926번지 11호41855072
23연수2동원인재역 지하1층<NA>인천광역시 연수구 연수동 647번지55346707
34연수3동신연수역<NA>인천광역시 연수구 연수동 384번지27113286
45선학동선학역<NA>인천광역시 연수구 선학동 241번지 2호30553703
56선학동문학경기장역<NA>인천광역시 연수구 선학동 117번지 1호934911332
67동춘3동연수구청 지하 1, 2층인천광역시 연수구 원인재로 115 (동춘동, 연수구청)인천광역시 연수구 동춘동 923번지 5호882310694
78옥련1동백산1차아파트 지하주차장 1층인천광역시 연수구 한나루로79번길 11 (옥련동, 백산1차아파트)인천광역시 연수구 옥련동 630번지17622135
89옥련1동삼성아파트 지하주차장 1,2층인천광역시 연수구 독배로40번길 18 (옥련동, 삼성아파트)인천광역시 연수구 옥련동 634-1 삼성아파트68108254
910옥련1동연수우성1차아파트 지하주차장 1~2층인천광역시 연수구 독배로40번길 48 (옥련동, 우성1차아파트)인천광역시 연수구 옥련동 636번지 1호65127893
연번행정동시설명시설위치(도로명)시설위치(지번)시설규모(㎡)활용가능인원(명)
6162송도2동송도더샵그린애비뉴8단지아파트 지하주차장 1~2층인천광역시 연수구 컨벤시아대로42번길 61 (송도동, 송도더샵그린애비뉴8단지)인천광역시 연수구 송도동 16번지 7호1764921392
6263송도2동송도더샵하버뷰13단지아파트 지하주차장 1~2층인천광역시 연수구 아트센터대로97번길 75 (송도동, 송도더샵하버뷰13단지)인천광역시 연수구 송도동 17번지 5호48045823
6364송도3동송도캐슬앤해모로아파트 지하주차장 1~2층인천광역시 연수구 송도과학로51번길 136 (송도동, 송도 캐슬&해모로)인천광역시 연수구 송도동 161-3 송도 캐슬&해모로1139013806
6465송도3동송도테크노파크IT센터 지하주차장 1층인천광역시 연수구 송도과학로 32 (송도동, 송도테크노파크IT센터)인천광역시 연수구 송도동 172번지 1호1447017539
6566송도3동송도더샵그린스퀘어 지하주차장 1~2층인천광역시 연수구 송도문화로28번길 81 (송도동, 송도더샵그린스퀘어)인천광역시 연수구 송도동 192번지 1호 송도더샵그린스퀘어6712881367
6667송도4동송도아라프라자 지하주차장 1~2층인천광역시 연수구 컨벤시아대로230번길 42, 송도아라플라자 (송도동)인천광역시 연수구 송도동 98번지 2호 송도아라플라자65787973
6768송도4동힐스테이트레이크송도2차아파트 지하주차장 1~2층인천광역시 연수구 아카데미로 446 (송도동, 힐스테이트 레이크 송도 2차)인천광역시 연수구 송도동 397-8 힐스테이트 레이크 송도 2차4020748735
6869송도5동랜드마크시티 센트럴더샵 지하주차장 1층인천광역시 연수구 랜드마크로 68, 지하층 (송도동, 랜드마크시티센트럴더샵)인천광역시 연수구 송도동 311 랜드마크시티센트럴더샵85693103870
6970동춘1동송도파크자이 아파트 지하주차장 1층~3층인천광역시 연수구 앵고개로104번길 22 (동춘동, 송도파크자이)인천광역시 연수구 동춘동 0 송도파크자이2053124886
7071송도2동송도달빛축제공원역인천광역시 연수구 인천타워대로 지하424, 송도달빛축제공원역 (송도동)인천광역시 연수구 송도동 340 송도달빛축제공원역933611316