Overview

Dataset statistics

Number of variables10
Number of observations127
Missing cells3
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.4 KiB
Average record size in memory84.0 B

Variable types

Numeric3
Categorical4
Text3

Dataset

Description부평구 노인복지시설 현황(시설종류, 도로명주소, 전화번호)ex) 1,노인주거복지시설,협성양로원,21383,산곡동,인천광역시 부평구 화랑로 70 (산곡동),50,법인,032-518-9365,무료
Author인천광역시 부평구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=3078614&srcSe=7661IVAWM27C61E190

Alerts

연번 is highly overall correlated with 시설종류High correlation
우편번호 is highly overall correlated with 동명High correlation
시설종류 is highly overall correlated with 연번High correlation
동명 is highly overall correlated with 우편번호High correlation
기타 is highly imbalanced (88.3%)Imbalance
전화번호 has 3 (2.4%) missing valuesMissing
연번 has unique valuesUnique
시설명 has unique valuesUnique
정원 has 42 (33.1%) zerosZeros

Reproduction

Analysis started2024-01-28 15:12:15.759433
Analysis finished2024-01-28 15:12:17.137113
Duration1.38 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct127
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean64
Minimum1
Maximum127
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-01-29T00:12:17.196072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7.3
Q132.5
median64
Q395.5
95-th percentile120.7
Maximum127
Range126
Interquartile range (IQR)63

Descriptive statistics

Standard deviation36.805797
Coefficient of variation (CV)0.57509057
Kurtosis-1.2
Mean64
Median Absolute Deviation (MAD)32
Skewness0
Sum8128
Variance1354.6667
MonotonicityStrictly increasing
2024-01-29T00:12:17.303598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.8%
2 1
 
0.8%
95 1
 
0.8%
94 1
 
0.8%
93 1
 
0.8%
92 1
 
0.8%
91 1
 
0.8%
90 1
 
0.8%
89 1
 
0.8%
88 1
 
0.8%
Other values (117) 117
92.1%
ValueCountFrequency (%)
1 1
0.8%
2 1
0.8%
3 1
0.8%
4 1
0.8%
5 1
0.8%
6 1
0.8%
7 1
0.8%
8 1
0.8%
9 1
0.8%
10 1
0.8%
ValueCountFrequency (%)
127 1
0.8%
126 1
0.8%
125 1
0.8%
124 1
0.8%
123 1
0.8%
122 1
0.8%
121 1
0.8%
120 1
0.8%
119 1
0.8%
118 1
0.8%

시설종류
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
노인의료복지시설
65 
재가노인복지시설
59 
노인주거복지시설
 
3

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row노인주거복지시설
2nd row노인주거복지시설
3rd row노인주거복지시설
4th row노인의료복지시설
5th row노인의료복지시설

Common Values

ValueCountFrequency (%)
노인의료복지시설 65
51.2%
재가노인복지시설 59
46.5%
노인주거복지시설 3
 
2.4%

Length

2024-01-29T00:12:17.401373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T00:12:17.475972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
노인의료복지시설 65
51.2%
재가노인복지시설 59
46.5%
노인주거복지시설 3
 
2.4%

시설명
Text

UNIQUE 

Distinct127
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-01-29T00:12:17.637076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length19
Mean length8.8425197
Min length4

Characters and Unicode

Total characters1123
Distinct characters188
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique127 ?
Unique (%)100.0%

Sample

1st row협성양로원
2nd row요셉의집
3rd row동성양로원
4th row100세 효 요양원
5th row가족사랑 삼산요양원
ValueCountFrequency (%)
요양원 5
 
3.0%
재가노인복지센터 4
 
2.4%
주야간보호센터 3
 
1.8%
주간보호센터 2
 
1.2%
부평 2
 
1.2%
재가복지센터 2
 
1.2%
열우물 2
 
1.2%
사랑의요양원 2
 
1.2%
휴(休 2
 
1.2%
효사랑요양원 2
 
1.2%
Other values (143) 143
84.6%
2024-01-29T00:12:17.940896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
양 74
 
6.6%
요 73
 
6.5%
원 69
 
6.1%
센 56
 
5.0%
터 56
 
5.0%
복 45
 
4.0%
42
 
3.7%
지 39
 
3.5%
가 37
 
3.3%
재 35
 
3.1%
Other values (178) 597
53.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1066
94.9%
Space Separator 42
 
3.7%
Decimal Number 7
 
0.6%
Open Punctuation 4
 
0.4%
Close Punctuation 4
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
양 74
 
6.9%
요 73
 
6.8%
원 69
 
6.5%
센 56
 
5.3%
터 56
 
5.3%
복 45
 
4.2%
지 39
 
3.7%
가 37
 
3.5%
재 35
 
3.3%
인 32
 
3.0%
Other values (171) 550
51.6%
Decimal Number
ValueCountFrequency (%)
1 3
42.9%
0 2
28.6%
3 1
 
14.3%
2 1
 
14.3%
Space Separator
ValueCountFrequency (%)
42
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1064
94.7%
Common 57
 
5.1%
Han 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
양 74
 
7.0%
요 73
 
6.9%
원 69
 
6.5%
센 56
 
5.3%
터 56
 
5.3%
복 45
 
4.2%
지 39
 
3.7%
가 37
 
3.5%
재 35
 
3.3%
인 32
 
3.0%
Other values (170) 548
51.5%
Common
ValueCountFrequency (%)
42
73.7%
( 4
 
7.0%
) 4
 
7.0%
1 3
 
5.3%
0 2
 
3.5%
3 1
 
1.8%
2 1
 
1.8%
Han
ValueCountFrequency (%)
休 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1064
94.7%
ASCII 57
 
5.1%
CJK 2
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
양 74
 
7.0%
요 73
 
6.9%
원 69
 
6.5%
센 56
 
5.3%
터 56
 
5.3%
복 45
 
4.2%
지 39
 
3.7%
가 37
 
3.5%
재 35
 
3.3%
인 32
 
3.0%
Other values (170) 548
51.5%
ASCII
ValueCountFrequency (%)
42
73.7%
( 4
 
7.0%
) 4
 
7.0%
1 3
 
5.3%
0 2
 
3.5%
3 1
 
1.8%
2 1
 
1.8%
CJK
ValueCountFrequency (%)
休 2
100.0%

우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct61
Distinct (%)48.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21369.071
Minimum21300
Maximum21453
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-01-29T00:12:18.047325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21300
5-th percentile21311
Q121338.5
median21360
Q321402.5
95-th percentile21443.5
Maximum21453
Range153
Interquartile range (IQR)64

Descriptive statistics

Standard deviation42.332242
Coefficient of variation (CV)0.0019810053
Kurtosis-1.0793901
Mean21369.071
Median Absolute Deviation (MAD)38
Skewness0.23225668
Sum2713872
Variance1792.0187
MonotonicityNot monotonic
2024-01-29T00:12:18.164612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21344 15
 
11.8%
21316 5
 
3.9%
21360 5
 
3.9%
21311 4
 
3.1%
21405 4
 
3.1%
21317 4
 
3.1%
21321 4
 
3.1%
21383 3
 
2.4%
21351 3
 
2.4%
21318 3
 
2.4%
Other values (51) 77
60.6%
ValueCountFrequency (%)
21300 1
 
0.8%
21309 1
 
0.8%
21310 2
 
1.6%
21311 4
3.1%
21312 3
2.4%
21313 1
 
0.8%
21316 5
3.9%
21317 4
3.1%
21318 3
2.4%
21319 1
 
0.8%
ValueCountFrequency (%)
21453 1
 
0.8%
21450 1
 
0.8%
21447 3
2.4%
21446 1
 
0.8%
21445 1
 
0.8%
21440 1
 
0.8%
21438 2
1.6%
21435 1
 
0.8%
21433 1
 
0.8%
21432 1
 
0.8%

동명
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)6.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
부평동
39 
삼산동
23 
부개동
14 
산곡동
12 
갈산동
12 
Other values (3)
27 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row산곡동
2nd row삼산동
3rd row일신동
4th row삼산동
5th row삼산동

Common Values

ValueCountFrequency (%)
부평동 39
30.7%
삼산동 23
18.1%
부개동 14
 
11.0%
산곡동 12
 
9.4%
갈산동 12
 
9.4%
청천동 12
 
9.4%
십정동 11
 
8.7%
일신동 4
 
3.1%

Length

2024-01-29T00:12:18.271017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T00:12:18.357220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부평동 39
30.7%
삼산동 23
18.1%
부개동 14
 
11.0%
산곡동 12
 
9.4%
갈산동 12
 
9.4%
청천동 12
 
9.4%
십정동 11
 
8.7%
일신동 4
 
3.1%

도로명주소
Text

Distinct125
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-01-29T00:12:18.619389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length39
Mean length30.968504
Min length21

Characters and Unicode

Total characters3933
Distinct characters130
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique123 ?
Unique (%)96.9%

Sample

1st row인천광역시 부평구 화랑로 70 (산곡동)
2nd row인천광역시 부평구 장제로 372 (삼산동)
3rd row인천광역시 부평구 일신로 18 (일신동)
4th row인천광역시 부평구 충선로209번길 41, 5,6층(삼산동)
5th row인천광역시 부평구 체육관로 38, 901, 1002호 (삼산동, 세원빌딩)
ValueCountFrequency (%)
인천광역시 127
 
16.4%
부평구 127
 
16.4%
부평동 37
 
4.8%
삼산동 22
 
2.8%
부개동 13
 
1.7%
장제로 13
 
1.7%
청천동 12
 
1.5%
갈산동 11
 
1.4%
십정동 11
 
1.4%
산곡동 11
 
1.4%
Other values (235) 392
50.5%
2024-01-29T00:12:18.970962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
649
 
16.5%
부 212
 
5.4%
평 182
 
4.6%
1 157
 
4.0%
천 147
 
3.7%
, 147
 
3.7%
동 137
 
3.5%
인 133
 
3.4%
로 128
 
3.3%
광 128
 
3.3%
Other values (120) 1913
48.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2191
55.7%
Decimal Number 677
 
17.2%
Space Separator 649
 
16.5%
Other Punctuation 148
 
3.8%
Close Punctuation 127
 
3.2%
Open Punctuation 127
 
3.2%
Dash Punctuation 10
 
0.3%
Math Symbol 2
 
0.1%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 212
 
9.7%
평 182
 
8.3%
천 147
 
6.7%
동 137
 
6.3%
인 133
 
6.1%
로 128
 
5.8%
광 128
 
5.8%
구 127
 
5.8%
시 127
 
5.8%
역 127
 
5.8%
Other values (101) 743
33.9%
Decimal Number
ValueCountFrequency (%)
1 157
23.2%
2 106
15.7%
0 91
13.4%
3 79
11.7%
4 62
 
9.2%
6 53
 
7.8%
5 41
 
6.1%
9 30
 
4.4%
8 29
 
4.3%
7 29
 
4.3%
Other Punctuation
ValueCountFrequency (%)
, 147
99.3%
· 1
 
0.7%
Uppercase Letter
ValueCountFrequency (%)
H 1
50.0%
K 1
50.0%
Space Separator
ValueCountFrequency (%)
649
100.0%
Close Punctuation
ValueCountFrequency (%)
) 127
100.0%
Open Punctuation
ValueCountFrequency (%)
( 127
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2191
55.7%
Common 1740
44.2%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 212
 
9.7%
평 182
 
8.3%
천 147
 
6.7%
동 137
 
6.3%
인 133
 
6.1%
로 128
 
5.8%
광 128
 
5.8%
구 127
 
5.8%
시 127
 
5.8%
역 127
 
5.8%
Other values (101) 743
33.9%
Common
ValueCountFrequency (%)
649
37.3%
1 157
 
9.0%
, 147
 
8.4%
) 127
 
7.3%
( 127
 
7.3%
2 106
 
6.1%
0 91
 
5.2%
3 79
 
4.5%
4 62
 
3.6%
6 53
 
3.0%
Other values (7) 142
 
8.2%
Latin
ValueCountFrequency (%)
H 1
50.0%
K 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2191
55.7%
ASCII 1741
44.3%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
649
37.3%
1 157
 
9.0%
, 147
 
8.4%
) 127
 
7.3%
( 127
 
7.3%
2 106
 
6.1%
0 91
 
5.2%
3 79
 
4.5%
4 62
 
3.6%
6 53
 
3.0%
Other values (8) 143
 
8.2%
Hangul
ValueCountFrequency (%)
부 212
 
9.7%
평 182
 
8.3%
천 147
 
6.7%
동 137
 
6.3%
인 133
 
6.1%
로 128
 
5.8%
광 128
 
5.8%
구 127
 
5.8%
시 127
 
5.8%
역 127
 
5.8%
Other values (101) 743
33.9%
None
ValueCountFrequency (%)
· 1
100.0%

정원
Real number (ℝ)

ZEROS 

Distinct46
Distinct (%)36.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.968504
Minimum0
Maximum160
Zeros42
Zeros (%)33.1%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-01-29T00:12:19.076967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median24
Q340
95-th percentile80.8
Maximum160
Range160
Interquartile range (IQR)40

Descriptive statistics

Standard deviation31.236156
Coefficient of variation (CV)1.1582458
Kurtosis3.9977012
Mean26.968504
Median Absolute Deviation (MAD)24
Skewness1.747934
Sum3425
Variance975.69741
MonotonicityNot monotonic
2024-01-29T00:12:19.197040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
0 42
33.1%
29 14
 
11.0%
9 12
 
9.4%
26 4
 
3.1%
27 4
 
3.1%
48 3
 
2.4%
56 2
 
1.6%
24 2
 
1.6%
47 2
 
1.6%
71 2
 
1.6%
Other values (36) 40
31.5%
ValueCountFrequency (%)
0 42
33.1%
6 1
 
0.8%
9 12
 
9.4%
14 2
 
1.6%
15 1
 
0.8%
18 2
 
1.6%
20 2
 
1.6%
21 1
 
0.8%
24 2
 
1.6%
25 1
 
0.8%
ValueCountFrequency (%)
160 1
0.8%
152 1
0.8%
123 1
0.8%
116 1
0.8%
95 1
0.8%
86 1
0.8%
82 1
0.8%
78 1
0.8%
75 1
0.8%
71 2
1.6%

운영주체
Categorical

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
개인
112 
법인
15 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row법인
2nd row개인
3rd row개인
4th row개인
5th row개인

Common Values

ValueCountFrequency (%)
개인 112
88.2%
법인 15
 
11.8%

Length

2024-01-29T00:12:19.302161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T00:12:19.627815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 112
88.2%
법인 15
 
11.8%

전화번호
Text

MISSING 

Distinct118
Distinct (%)95.2%
Missing3
Missing (%)2.4%
Memory size1.1 KiB
2024-01-29T00:12:19.812658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.024194
Min length12

Characters and Unicode

Total characters1491
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

Unique112 ?
Unique (%)90.3%

Sample

1st row032-518-9365
2nd row032-526-8615
3rd row070-4090-5284
4th row032-724-9191
5th row032-275-7500
ValueCountFrequency (%)
032-517-2211 2
 
1.6%
032-505-0034 2
 
1.6%
032-263-9988 2
 
1.6%
032-502-5361 2
 
1.6%
032-518-9365 2
 
1.6%
032-298-1004 2
 
1.6%
032-503-2201 1
 
0.8%
032-212-6101 1
 
0.8%
032-429-9004 1
 
0.8%
032-212-5109 1
 
0.8%
Other values (108) 108
87.1%
2024-01-29T00:12:20.120270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 252
16.9%
- 248
16.6%
2 236
15.8%
3 205
13.7%
5 144
9.7%
1 114
7.6%
8 63
 
4.2%
7 62
 
4.2%
9 60
 
4.0%
4 54
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1243
83.4%
Dash Punctuation 248
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 252
20.3%
2 236
19.0%
3 205
16.5%
5 144
11.6%
1 114
9.2%
8 63
 
5.1%
7 62
 
5.0%
9 60
 
4.8%
4 54
 
4.3%
6 53
 
4.3%
Dash Punctuation
ValueCountFrequency (%)
- 248
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1491
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 252
16.9%
- 248
16.6%
2 236
15.8%
3 205
13.7%
5 144
9.7%
1 114
7.6%
8 63
 
4.2%
7 62
 
4.2%
9 60
 
4.0%
4 54
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1491
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 252
16.9%
- 248
16.6%
2 236
15.8%
3 205
13.7%
5 144
9.7%
1 114
7.6%
8 63
 
4.2%
7 62
 
4.2%
9 60
 
4.0%
4 54
 
3.6%

기타
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
유료
125 
무료
 
2

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row무료
2nd row유료
3rd row유료
4th row유료
5th row유료

Common Values

ValueCountFrequency (%)
유료 125
98.4%
무료 2
 
1.6%

Length

2024-01-29T00:12:20.227670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T00:12:20.303971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유료 125
98.4%
무료 2
 
1.6%

Interactions

2024-01-29T00:12:16.708085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:12:16.220764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:12:16.470085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:12:16.781136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:12:16.292528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:12:16.546262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:12:16.876408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:12:16.394107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:12:16.622996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-29T00:12:20.352853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시설종류우편번호동명정원운영주체기타
연번1.0000.8200.0000.2360.4260.2390.000
시설종류0.8201.0000.1280.3650.4960.0560.236
우편번호0.0000.1281.0000.8900.2830.1580.000
동명0.2360.3650.8901.0000.0000.0000.160
정원0.4260.4960.2830.0001.0000.2630.163
운영주체0.2390.0560.1580.0000.2631.0000.357
기타0.0000.2360.0000.1600.1630.3571.000
2024-01-29T00:12:20.435268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
동명운영주체시설종류기타
동명1.0000.0000.2430.115
운영주체0.0001.0000.0910.232
시설종류0.2430.0911.0000.384
기타0.1150.2320.3841.000
2024-01-29T00:12:20.514687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번우편번호정원시설종류동명운영주체기타
연번1.0000.144-0.4370.7010.1110.1760.000
우편번호0.1441.000-0.1290.0670.6990.0980.000
정원-0.437-0.1291.0000.3840.0000.2000.105
시설종류0.7010.0670.3841.0000.2430.0910.384
동명0.1110.6990.0000.2431.0000.0000.115
운영주체0.1760.0980.2000.0910.0001.0000.232
기타0.0000.0000.1050.3840.1150.2321.000

Missing values

2024-01-29T00:12:16.982971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-29T00:12:17.090284image/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

연번시설종류시설명우편번호동명도로명주소정원운영주체전화번호기타
01노인주거복지시설협성양로원21383산곡동인천광역시 부평구 화랑로 70 (산곡동)50법인032-518-9365무료
12노인주거복지시설요셉의집21318삼산동인천광역시 부평구 장제로 372 (삼산동)9개인032-526-8615유료
23노인주거복지시설동성양로원21422일신동인천광역시 부평구 일신로 18 (일신동)9개인070-4090-5284유료
34노인의료복지시설100세 효 요양원21344삼산동인천광역시 부평구 충선로209번길 41, 5,6층(삼산동)29개인032-724-9191유료
45노인의료복지시설가족사랑 삼산요양원21344삼산동인천광역시 부평구 체육관로 38, 901, 1002호 (삼산동, 세원빌딩)38개인032-275-7500유료
56노인의료복지시설가족요양원21376산곡동인천광역시 부평구 마장로 256, 301호 (산곡동, 산곡프라자)29개인032-361-8495유료
67노인의료복지시설간호박사요양원21344삼산동인천광역시 부평구 체육관로 40, 10 (삼산동, 신영프라자)28개인032-511-6078유료
78노인의료복지시설고은미소요양원21316갈산동인천광역시 부평구 주부토로 261, 501호 (갈산동)18개인032-517-2211유료
89노인의료복지시설고은손 요양원21316갈산동인천광역시 부평구 주부토로 261, 6층 (갈산동, 신협빌딩)33개인032-517-2211유료
910노인의료복지시설굿힐링요양원21329갈산동인천광역시 부평구 주부토로 223, 601호 (갈산동, 금강프라자)26개인032-505-9700유료
연번시설종류시설명우편번호동명도로명주소정원운영주체전화번호기타
117118재가노인복지시설인천광역시 사회서비스원 인복드림종합재가센터 부평센터21312청천동인천광역시 부평구 마장로410번길 6, 3층 (청천동)0법인032-721-7193유료
118119재가노인복지시설정다운노인요양센터21333갈산동인천광역시 부평구 굴포로7번길 31, 2층 (갈산동)47법인032-715-5994무료
119120재가노인복지시설참사랑노인복지센터21313청천동인천광역시 부평구 세월천로 41, 2층 (청천동)56개인032-515-7568유료
120121재가노인복지시설하이노인주간보호센터21365부평동인천광역시 부평구 원적로 469, 4층 (부평동, 성훈빌딩)61개인032-508-1979유료
121122재가노인복지시설한사랑주야간보호센터21398부개동인천광역시 부평구 동수천로 132, 6층 (부개동)6개인032-502-5361유료
122123재가노인복지시설행복나무재가노인복지센터21316갈산동인천광역시 부평구 부평북로 313, 202호 (갈산동)0개인032-361-5900유료
123124재가노인복지시설호별노인복지케어센터21356부평동인천광역시 부평구 주부토로 92 (부평동)24개인032-527-8855유료
124125재가노인복지시설홈스재가복지센터21376산곡동인천광역시 부평구 부흥로123번길 34, 5층 502호 (산곡동)0개인032-719-7080유료
125126재가노인복지시설효담요양복지센터21394부평동인천광역시 부평구 부평대로 24, 1307호 (부평동)0개인032-528-9696유료
126127재가노인복지시설효드림노인복지센터21361산곡동인천광역시 부평구 마장로 338, 3층 (산곡동, 남양빌딩)64개인032-518-1800유료