Overview

Dataset statistics

Number of variables8
Number of observations50
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.4 KiB
Average record size in memory70.6 B

Variable types

Numeric4
Text3
Categorical1

Dataset

Description인천광역시 미추홀구 이재민수용기관에 관한 데이터이며 시설명, 도로명주소, 수용인원, 전화번호 위도, 경도 등의 항목을 제공합니다.
Author인천광역시 미추홀구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15087039&srcSe=7661IVAWM27C61E190

Alerts

연번 is highly overall correlated with 경도High correlation
경도 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique
시설명 has unique valuesUnique
전화번호 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique

Reproduction

Analysis started2024-03-18 04:45:43.113950
Analysis finished2024-03-18 04:45:46.258435
Duration3.14 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.5
Minimum1
Maximum50
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2024-03-18T13:45:46.333024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.45
Q113.25
median25.5
Q337.75
95-th percentile47.55
Maximum50
Range49
Interquartile range (IQR)24.5

Descriptive statistics

Standard deviation14.57738
Coefficient of variation (CV)0.57166195
Kurtosis-1.2
Mean25.5
Median Absolute Deviation (MAD)12.5
Skewness0
Sum1275
Variance212.5
MonotonicityStrictly increasing
2024-03-18T13:45:46.456022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
2.0%
39 1
 
2.0%
29 1
 
2.0%
30 1
 
2.0%
31 1
 
2.0%
32 1
 
2.0%
33 1
 
2.0%
34 1
 
2.0%
35 1
 
2.0%
36 1
 
2.0%
Other values (40) 40
80.0%
ValueCountFrequency (%)
1 1
2.0%
2 1
2.0%
3 1
2.0%
4 1
2.0%
5 1
2.0%
6 1
2.0%
7 1
2.0%
8 1
2.0%
9 1
2.0%
10 1
2.0%
ValueCountFrequency (%)
50 1
2.0%
49 1
2.0%
48 1
2.0%
47 1
2.0%
46 1
2.0%
45 1
2.0%
44 1
2.0%
43 1
2.0%
42 1
2.0%
41 1
2.0%

시설명
Text

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2024-03-18T13:45:46.643054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length7.16
Min length4

Characters and Unicode

Total characters358
Distinct characters86
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)100.0%

Sample

1st row숭의교회
2nd row동인천교회
3rd row용정초등학교
4th row인천남중학교
5th row용일초등학교
ValueCountFrequency (%)
교회 2
 
3.6%
천주교 2
 
3.6%
숭의교회 1
 
1.8%
인화여자중학교 1
 
1.8%
주안1동분회경로당 1
 
1.8%
데이앤나잇 1
 
1.8%
호텔 1
 
1.8%
인천기계공업고등학교 1
 
1.8%
주안초등학교 1
 
1.8%
미추홀노인복지관 1
 
1.8%
Other values (44) 44
78.6%
2024-03-18T13:45:46.941452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 50
 
14.0%
학 44
 
12.3%
등 28
 
7.8%
인 26
 
7.3%
천 21
 
5.9%
초 19
 
5.3%
회 12
 
3.4%
고 9
 
2.5%
주 8
 
2.2%
중 8
 
2.2%
Other values (76) 133
37.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 348
97.2%
Space Separator 6
 
1.7%
Decimal Number 3
 
0.8%
Other Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 50
14.4%
학 44
 
12.6%
등 28
 
8.0%
인 26
 
7.5%
천 21
 
6.0%
초 19
 
5.5%
회 12
 
3.4%
고 9
 
2.6%
주 8
 
2.3%
중 8
 
2.3%
Other values (71) 123
35.3%
Decimal Number
ValueCountFrequency (%)
3 1
33.3%
5 1
33.3%
1 1
33.3%
Space Separator
ValueCountFrequency (%)
6
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 348
97.2%
Common 10
 
2.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 50
14.4%
학 44
 
12.6%
등 28
 
8.0%
인 26
 
7.5%
천 21
 
6.0%
초 19
 
5.5%
회 12
 
3.4%
고 9
 
2.6%
주 8
 
2.3%
중 8
 
2.3%
Other values (71) 123
35.3%
Common
ValueCountFrequency (%)
6
60.0%
3 1
 
10.0%
5 1
 
10.0%
1 1
 
10.0%
. 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 348
97.2%
ASCII 10
 
2.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 50
14.4%
학 44
 
12.6%
등 28
 
8.0%
인 26
 
7.5%
천 21
 
6.0%
초 19
 
5.5%
회 12
 
3.4%
고 9
 
2.6%
주 8
 
2.3%
중 8
 
2.3%
Other values (71) 123
35.3%
ASCII
ValueCountFrequency (%)
6
60.0%
3 1
 
10.0%
5 1
 
10.0%
1 1
 
10.0%
. 1
 
10.0%

도로명주소
Text

Distinct47
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2024-03-18T13:45:47.148893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length32
Mean length25.38
Min length22

Characters and Unicode

Total characters1269
Distinct characters77
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

Unique46 ?
Unique (%)92.0%

Sample

1st row인천광역시 미추홀구 독배로 485(숭의동)
2nd row인천광역시 미추홀구 석정로 108-4 (숭의동)
3rd row인천광역시 미추홀구 독정안길 26(숭의동)
4th row인천광역시 미추홀구 수봉로 16-23 (숭의동)
5th row인천광역시 미추홀구 인주대로 244(용현동)
ValueCountFrequency (%)
인천광역시 50
24.3%
미추홀구 50
24.3%
석정로 5
 
2.4%
165(도화동 4
 
1.9%
낙섬동로 3
 
1.5%
인하로 3
 
1.5%
숭의동 2
 
1.0%
경인로 2
 
1.0%
학익소로37번길 2
 
1.0%
주안동 2
 
1.0%
Other values (80) 83
40.3%
2024-03-18T13:45:47.493532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
156
 
12.3%
인 59
 
4.6%
동 54
 
4.3%
홀 54
 
4.3%
미 51
 
4.0%
추 51
 
4.0%
시 50
 
3.9%
역 50
 
3.9%
광 50
 
3.9%
구 50
 
3.9%
Other values (67) 644
50.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 821
64.7%
Decimal Number 186
 
14.7%
Space Separator 156
 
12.3%
Close Punctuation 50
 
3.9%
Open Punctuation 50
 
3.9%
Dash Punctuation 6
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 59
 
7.2%
동 54
 
6.6%
홀 54
 
6.6%
미 51
 
6.2%
추 51
 
6.2%
시 50
 
6.1%
역 50
 
6.1%
광 50
 
6.1%
구 50
 
6.1%
천 50
 
6.1%
Other values (53) 302
36.8%
Decimal Number
ValueCountFrequency (%)
1 30
16.1%
2 28
15.1%
5 24
12.9%
3 22
11.8%
4 21
11.3%
6 21
11.3%
7 12
 
6.5%
0 12
 
6.5%
8 9
 
4.8%
9 7
 
3.8%
Space Separator
ValueCountFrequency (%)
156
100.0%
Close Punctuation
ValueCountFrequency (%)
) 50
100.0%
Open Punctuation
ValueCountFrequency (%)
( 50
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 821
64.7%
Common 448
35.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 59
 
7.2%
동 54
 
6.6%
홀 54
 
6.6%
미 51
 
6.2%
추 51
 
6.2%
시 50
 
6.1%
역 50
 
6.1%
광 50
 
6.1%
구 50
 
6.1%
천 50
 
6.1%
Other values (53) 302
36.8%
Common
ValueCountFrequency (%)
156
34.8%
) 50
 
11.2%
( 50
 
11.2%
1 30
 
6.7%
2 28
 
6.2%
5 24
 
5.4%
3 22
 
4.9%
4 21
 
4.7%
6 21
 
4.7%
7 12
 
2.7%
Other values (4) 34
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 821
64.7%
ASCII 448
35.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
156
34.8%
) 50
 
11.2%
( 50
 
11.2%
1 30
 
6.7%
2 28
 
6.2%
5 24
 
5.4%
3 22
 
4.9%
4 21
 
4.7%
6 21
 
4.7%
7 12
 
2.7%
Other values (4) 34
 
7.6%
Hangul
ValueCountFrequency (%)
인 59
 
7.2%
동 54
 
6.6%
홀 54
 
6.6%
미 51
 
6.2%
추 51
 
6.2%
시 50
 
6.1%
역 50
 
6.1%
광 50
 
6.1%
구 50
 
6.1%
천 50
 
6.1%
Other values (53) 302
36.8%

수용인원
Real number (ℝ)

Distinct45
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean389.7
Minimum25
Maximum2815
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2024-03-18T13:45:47.617339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum25
5-th percentile77.4
Q1217.75
median275.5
Q3429.75
95-th percentile814.65
Maximum2815
Range2790
Interquartile range (IQR)212

Descriptive statistics

Standard deviation441.36085
Coefficient of variation (CV)1.1325657
Kurtosis19.833179
Mean389.7
Median Absolute Deviation (MAD)94.5
Skewness4.0797737
Sum19485
Variance194799.4
MonotonicityNot monotonic
2024-03-18T13:45:47.713185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
635 2
 
4.0%
290 2
 
4.0%
328 2
 
4.0%
96 2
 
4.0%
241 2
 
4.0%
337 1
 
2.0%
25 1
 
2.0%
438 1
 
2.0%
293 1
 
2.0%
161 1
 
2.0%
Other values (35) 35
70.0%
ValueCountFrequency (%)
25 1
2.0%
50 1
2.0%
63 1
2.0%
95 1
2.0%
96 2
4.0%
110 1
2.0%
125 1
2.0%
161 1
2.0%
165 1
2.0%
197 1
2.0%
ValueCountFrequency (%)
2815 1
2.0%
1717 1
2.0%
879 1
2.0%
736 1
2.0%
643 1
2.0%
635 2
4.0%
600 1
2.0%
526 1
2.0%
483 1
2.0%
460 1
2.0%

전화번호
Text

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2024-03-18T13:45:47.896375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.98
Min length11

Characters and Unicode

Total characters599
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

Unique50 ?
Unique (%)100.0%

Sample

1st row032-880-8000
2nd row032-888-194
3rd row032-868-2382
4th row032-882-2503
5th row032-866-4280
ValueCountFrequency (%)
032-880-8000 1
 
2.0%
032-451-0503 1
 
2.0%
032-627-0807 1
 
2.0%
032-629-2971 1
 
2.0%
032-875-3231 1
 
2.0%
032-422-3597 1
 
2.0%
032-860-0106 1
 
2.0%
032-424-7687 1
 
2.0%
032-861-3001 1
 
2.0%
032-867-1053 1
 
2.0%
Other values (40) 40
80.0%
2024-03-18T13:45:48.186615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 100
16.7%
2 98
16.4%
0 84
14.0%
3 69
11.5%
8 58
9.7%
6 47
7.8%
1 32
 
5.3%
7 32
 
5.3%
4 29
 
4.8%
5 26
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 499
83.3%
Dash Punctuation 100
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 98
19.6%
0 84
16.8%
3 69
13.8%
8 58
11.6%
6 47
9.4%
1 32
 
6.4%
7 32
 
6.4%
4 29
 
5.8%
5 26
 
5.2%
9 24
 
4.8%
Dash Punctuation
ValueCountFrequency (%)
- 100
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 599
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 100
16.7%
2 98
16.4%
0 84
14.0%
3 69
11.5%
8 58
9.7%
6 47
7.8%
1 32
 
5.3%
7 32
 
5.3%
4 29
 
4.8%
5 26
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 599
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 100
16.7%
2 98
16.4%
0 84
14.0%
3 69
11.5%
8 58
9.7%
6 47
7.8%
1 32
 
5.3%
7 32
 
5.3%
4 29
 
4.8%
5 26
 
4.3%

구분
Categorical

Distinct4
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
학교
36 
교회
10 
경로당
 
3
연수+숙박
 
1

Length

Max length5
Median length2
Mean length2.12
Min length2

Unique

Unique1 ?
Unique (%)2.0%

Sample

1st row교회
2nd row교회
3rd row학교
4th row학교
5th row학교

Common Values

ValueCountFrequency (%)
학교 36
72.0%
교회 10
 
20.0%
경로당 3
 
6.0%
연수+숙박 1
 
2.0%

Length

2024-03-18T13:45:48.295035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T13:45:48.393076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
학교 36
72.0%
교회 10
 
20.0%
경로당 3
 
6.0%
연수+숙박 1
 
2.0%

위도
Real number (ℝ)

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.455824
Minimum37.435345
Maximum37.475251
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2024-03-18T13:45:48.518743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.435345
5-th percentile37.439202
Q137.446009
median37.45412
Q337.467121
95-th percentile37.474016
Maximum37.475251
Range0.03990525
Interquartile range (IQR)0.021112193

Descriptive statistics

Standard deviation0.01151645
Coefficient of variation (CV)0.00030746753
Kurtosis-1.2092297
Mean37.455824
Median Absolute Deviation (MAD)0.00906177
Skewness0.12043668
Sum1872.7912
Variance0.00013262861
MonotonicityNot monotonic
2024-03-18T13:45:48.633780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.46079661 1
 
2.0%
37.46835374 1
 
2.0%
37.4631554 1
 
2.0%
37.46088465 1
 
2.0%
37.45685484 1
 
2.0%
37.45476369 1
 
2.0%
37.44503186 1
 
2.0%
37.44921429 1
 
2.0%
37.44962322 1
 
2.0%
37.44492358 1
 
2.0%
Other values (40) 40
80.0%
ValueCountFrequency (%)
37.43534525 1
2.0%
37.43847712 1
2.0%
37.43907845 1
2.0%
37.43935285 1
2.0%
37.43985102 1
2.0%
37.43989979 1
2.0%
37.44431451 1
2.0%
37.44451078 1
2.0%
37.44492358 1
2.0%
37.44503186 1
2.0%
ValueCountFrequency (%)
37.4752505 1
2.0%
37.47519289 1
2.0%
37.47410103 1
2.0%
37.47391311 1
2.0%
37.4720507 1
2.0%
37.47166768 1
2.0%
37.46945372 1
2.0%
37.46903303 1
2.0%
37.46897695 1
2.0%
37.46876348 1
2.0%

경도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.6671
Minimum126.63914
Maximum126.69637
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2024-03-18T13:45:48.929804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.63914
5-th percentile126.64094
Q1126.65562
median126.6674
Q3126.67772
95-th percentile126.69325
Maximum126.69637
Range0.0572308
Interquartile range (IQR)0.022098725

Descriptive statistics

Standard deviation0.01600427
Coefficient of variation (CV)0.00012634907
Kurtosis-0.84550664
Mean126.6671
Median Absolute Deviation (MAD)0.0114567
Skewness0.087717513
Sum6333.3549
Variance0.00025613665
MonotonicityNot monotonic
2024-03-18T13:45:49.032687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.6448146 1
 
2.0%
126.6809948 1
 
2.0%
126.6764553 1
 
2.0%
126.681125 1
 
2.0%
126.6682895 1
 
2.0%
126.673664 1
 
2.0%
126.6712253 1
 
2.0%
126.673944 1
 
2.0%
126.6705289 1
 
2.0%
126.6719336 1
 
2.0%
Other values (40) 40
80.0%
ValueCountFrequency (%)
126.6391439 1
2.0%
126.639195 1
2.0%
126.640499 1
2.0%
126.6414793 1
2.0%
126.6439007 1
2.0%
126.6448146 1
2.0%
126.647556 1
2.0%
126.6509058 1
2.0%
126.6533763 1
2.0%
126.6536772 1
2.0%
ValueCountFrequency (%)
126.6963747 1
2.0%
126.6955916 1
2.0%
126.6934712 1
2.0%
126.6929879 1
2.0%
126.6917678 1
2.0%
126.6907125 1
2.0%
126.6867573 1
2.0%
126.6865343 1
2.0%
126.6854152 1
2.0%
126.6828825 1
2.0%

Interactions

2024-03-18T13:45:45.782152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:45:44.857421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:45:45.183927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:45:45.499231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:45:45.846380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:45:44.966056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:45:45.291986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:45:45.568150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:45:45.911366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:45:45.031986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:45:45.361835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:45:45.635867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:45:46.005330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:45:45.104169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:45:45.435282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:45:45.711682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-18T13:45:49.112306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시설명도로명주소수용인원전화번호구분위도경도
연번1.0001.0000.9320.1961.0000.2330.6400.710
시설명1.0001.0001.0001.0001.0001.0001.0001.000
도로명주소0.9321.0001.0000.9831.0001.0000.9590.977
수용인원0.1961.0000.9831.0001.0000.0000.3610.000
전화번호1.0001.0001.0001.0001.0001.0001.0001.000
구분0.2331.0001.0000.0001.0001.0000.0000.326
위도0.6401.0000.9590.3611.0000.0001.0000.000
경도0.7101.0000.9770.0001.0000.3260.0001.000
2024-03-18T13:45:49.214810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번수용인원위도경도구분
연번1.0000.047-0.1490.8630.116
수용인원0.0471.0000.1670.0170.000
위도-0.1490.1671.000-0.2350.000
경도0.8630.017-0.2351.0000.177
구분0.1160.0000.0000.1771.000

Missing values

2024-03-18T13:45:46.092760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T13:45:46.205963image/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

연번시설명도로명주소수용인원전화번호구분위도경도
01숭의교회인천광역시 미추홀구 독배로 485(숭의동)635032-880-8000교회37.460797126.644815
12동인천교회인천광역시 미추홀구 석정로 108-4 (숭의동)254032-888-194교회37.468127126.647556
23용정초등학교인천광역시 미추홀구 독정안길 26(숭의동)125032-868-2382학교37.459461126.657178
34인천남중학교인천광역시 미추홀구 수봉로 16-23 (숭의동)405032-882-2503학교37.464578126.654234
45용일초등학교인천광역시 미추홀구 인주대로 244(용현동)328032-866-4280학교37.452795126.663498
56정석항공공업고등학교인천광역시 미추홀구 인하로 100(용현동)215032-867-6242학교37.449576126.658357
67인천광역시 노인복지회관인천광역시 미추홀구 능해길 21(용현동)63032-874-7979경로당37.459499126.639195
78은석교회인천광역시 미추홀구 인주대로 166-1 (용현동)266032-882-4123교회37.455721126.655306
89용학초등학교인천광역시 미추홀구 용정공원로83번길 9(용현동)255032-627-6300학교37.444511126.643901
910용현여자중학교인천광역시 미추홀구 낙섬동로 28(용현동)389032-884-8462학교37.448863126.640499
연번시설명도로명주소수용인원전화번호구분위도경도
4041경원초등학교인천광역시 미추홀구 경인로 511(주안동)233032-424-1692학교37.461296126.695592
4142석암초등학교인천광역시 미추홀구 주안동로 46(주안동)110032-424-0143학교37.461838126.686757
4243인천남부초등학교인천광역시 미추홀구 인주대로366번길 22(주안동)252032-864-2096학교37.450444126.676379
4344인천주안남초등학교인천광역시 미추홀구 인주대로434번길 11(주안동)268032-428-1841학교37.450076126.685415
4445관교중학교인천광역시 미추홀구 경원대로670번길 19(관교동)290032-629-2887학교37.444315126.691768
4546관교초등학교인천광역시 미추홀구 인하로 414(관교동)226032-629-1357학교37.446021126.692988
4647남인천여자중학교인천광역시 미추홀구 인하로 426(관교동)329032-421-1825학교37.445751126.693471
4748승학초등학교인천광역시 미추홀구 주승로 259(관교동)643032-629-1644학교37.439851126.696375
4849문학정보고등학교인천광역시 미추홀구 소성로350번길 29(문학동)328032-627-0807학교37.435345126.686534
4950인천문학초등학교인천광역시 미추홀구 매소홀로 553(문학동)50032-425-2801학교37.439353126.682883