Overview

Dataset statistics

Number of variables11
Number of observations57
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.2 KiB
Average record size in memory94.3 B

Variable types

Numeric4
Categorical2
Text4
DateTime1

Dataset

Description경상북도 시군의 법인운영 장애인 거주 시설의 시군명, 시설명, 유형, 설치일, 소재지, 연락처, 종사자, 정원, 현원 등의 현황입니다.
Author경상북도
URLhttps://www.data.go.kr/data/15063016/fileData.do

Alerts

연번 is highly overall correlated with 시군명High correlation
종사자수 is highly overall correlated with 정원 and 1 other fieldsHigh correlation
정원 is highly overall correlated with 종사자수 and 1 other fieldsHigh correlation
현원 is highly overall correlated with 종사자수 and 1 other fieldsHigh correlation
시군명 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 09:40:11.410383
Analysis finished2023-12-12 09:40:14.146960
Duration2.74 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct57
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29
Minimum1
Maximum57
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size645.0 B
2023-12-12T18:40:14.210927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.8
Q115
median29
Q343
95-th percentile54.2
Maximum57
Range56
Interquartile range (IQR)28

Descriptive statistics

Standard deviation16.598193
Coefficient of variation (CV)0.57235147
Kurtosis-1.2
Mean29
Median Absolute Deviation (MAD)14
Skewness0
Sum1653
Variance275.5
MonotonicityStrictly increasing
2023-12-12T18:40:14.339885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.8%
44 1
 
1.8%
32 1
 
1.8%
33 1
 
1.8%
34 1
 
1.8%
35 1
 
1.8%
36 1
 
1.8%
37 1
 
1.8%
38 1
 
1.8%
39 1
 
1.8%
Other values (47) 47
82.5%
ValueCountFrequency (%)
1 1
1.8%
2 1
1.8%
3 1
1.8%
4 1
1.8%
5 1
1.8%
6 1
1.8%
7 1
1.8%
8 1
1.8%
9 1
1.8%
10 1
1.8%
ValueCountFrequency (%)
57 1
1.8%
56 1
1.8%
55 1
1.8%
54 1
1.8%
53 1
1.8%
52 1
1.8%
51 1
1.8%
50 1
1.8%
49 1
1.8%
48 1
1.8%

시군명
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)35.1%
Missing0
Missing (%)0.0%
Memory size588.0 B
포항시
8 
안동시
8 
영주시
7 
경산시
7 
경주시
5 
Other values (15)
22 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique9 ?
Unique (%)15.8%

Sample

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

Common Values

ValueCountFrequency (%)
포항시 8
14.0%
안동시 8
14.0%
영주시 7
12.3%
경산시 7
12.3%
경주시 5
8.8%
상주시 3
 
5.3%
영천시 2
 
3.5%
칠곡군 2
 
3.5%
고령군 2
 
3.5%
예천군 2
 
3.5%
Other values (10) 11
19.3%

Length

2023-12-12T18:40:14.456141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
포항시 8
14.0%
안동시 8
14.0%
영주시 7
12.3%
경산시 7
12.3%
경주시 5
8.8%
상주시 3
 
5.3%
고령군 2
 
3.5%
예천군 2
 
3.5%
김천시 2
 
3.5%
칠곡군 2
 
3.5%
Other values (10) 11
19.3%

시설명
Text

Distinct56
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size588.0 B
2023-12-12T18:40:14.647159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length7
Mean length5
Min length2

Characters and Unicode

Total characters285
Distinct characters104
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)96.5%

Sample

1st row마리아의집
2nd row향기마을
3rd row나전복지마을
4th row예우리
5th row도움터기쁨의집
ValueCountFrequency (%)
사랑마을 2
 
3.4%
극락마을 1
 
1.7%
향기마을 1
 
1.7%
더사랑의집 1
 
1.7%
영천팔레스 1
 
1.7%
마야예림원 1
 
1.7%
희망재활원 1
 
1.7%
행복재활원 1
 
1.7%
희망과사람 1
 
1.7%
성락원 1
 
1.7%
Other values (48) 48
81.4%
2023-12-12T18:40:14.972777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 19
 
6.7%
마 13
 
4.6%
집 13
 
4.6%
을 11
 
3.9%
동 11
 
3.9%
사 10
 
3.5%
의 10
 
3.5%
활 8
 
2.8%
재 8
 
2.8%
복 8
 
2.8%
Other values (94) 174
61.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 283
99.3%
Space Separator 2
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 19
 
6.7%
마 13
 
4.6%
집 13
 
4.6%
을 11
 
3.9%
동 11
 
3.9%
사 10
 
3.5%
의 10
 
3.5%
활 8
 
2.8%
재 8
 
2.8%
복 8
 
2.8%
Other values (93) 172
60.8%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 283
99.3%
Common 2
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 19
 
6.7%
마 13
 
4.6%
집 13
 
4.6%
을 11
 
3.9%
동 11
 
3.9%
사 10
 
3.5%
의 10
 
3.5%
활 8
 
2.8%
재 8
 
2.8%
복 8
 
2.8%
Other values (93) 172
60.8%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 283
99.3%
ASCII 2
 
0.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 19
 
6.7%
마 13
 
4.6%
집 13
 
4.6%
을 11
 
3.9%
동 11
 
3.9%
사 10
 
3.5%
의 10
 
3.5%
활 8
 
2.8%
재 8
 
2.8%
복 8
 
2.8%
Other values (93) 172
60.8%
ASCII
ValueCountFrequency (%)
2
100.0%

유형
Categorical

Distinct5
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Memory size588.0 B
중증
31 
지적 자폐성
21 
지체 뇌병변
 
2
지적
 
2
지적,자폐성
 
1

Length

Max length6
Median length2
Mean length3.6842105
Min length2

Unique

Unique1 ?
Unique (%)1.8%

Sample

1st row지체 뇌병변
2nd row중증
3rd row중증
4th row중증
5th row지적 자폐성

Common Values

ValueCountFrequency (%)
중증 31
54.4%
지적 자폐성 21
36.8%
지체 뇌병변 2
 
3.5%
지적 2
 
3.5%
지적,자폐성 1
 
1.8%

Length

2023-12-12T18:40:15.105840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:40:15.199782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중증 31
38.8%
지적 23
28.7%
자폐성 21
26.2%
지체 2
 
2.5%
뇌병변 2
 
2.5%
지적,자폐성 1
 
1.2%

설치일
Date

Distinct56
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size588.0 B
Minimum1957-02-07 00:00:00
Maximum2019-05-17 00:00:00
2023-12-12T18:40:15.306680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:40:15.440214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

소재지
Text

Distinct52
Distinct (%)91.2%
Missing0
Missing (%)0.0%
Memory size588.0 B
2023-12-12T18:40:15.760169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length13.122807
Min length7

Characters and Unicode

Total characters748
Distinct characters115
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

Unique48 ?
Unique (%)84.2%

Sample

1st row남구 대잠동길17-1(대잠동)
2nd row북구 흥해읍사방공원길 502
3rd row남구 장기면장기로1229번길 39
4th row남구 동해면금광로 79
5th row북구 기계면고지길 62-63
ValueCountFrequency (%)
북구 5
 
3.5%
진량읍 4
 
2.8%
북후면 3
 
2.1%
광평2길106-25 3
 
2.1%
남구 3
 
2.1%
영주시 2
 
1.4%
와룡면 2
 
1.4%
문수면 2
 
1.4%
문수로825번길 2
 
1.4%
북안면 2
 
1.4%
Other values (107) 115
80.4%
2023-12-12T18:40:16.254054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
86
 
11.5%
2 47
 
6.3%
길 44
 
5.9%
- 43
 
5.7%
면 40
 
5.3%
1 38
 
5.1%
5 27
 
3.6%
4 25
 
3.3%
3 23
 
3.1%
로 21
 
2.8%
Other values (105) 354
47.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 376
50.3%
Decimal Number 239
32.0%
Space Separator 86
 
11.5%
Dash Punctuation 43
 
5.7%
Open Punctuation 2
 
0.3%
Close Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
길 44
 
11.7%
면 40
 
10.6%
로 21
 
5.6%
산 11
 
2.9%
읍 10
 
2.7%
북 10
 
2.7%
성 9
 
2.4%
구 9
 
2.4%
동 8
 
2.1%
대 7
 
1.9%
Other values (91) 207
55.1%
Decimal Number
ValueCountFrequency (%)
2 47
19.7%
1 38
15.9%
5 27
11.3%
4 25
10.5%
3 23
9.6%
6 20
8.4%
0 17
 
7.1%
7 15
 
6.3%
8 14
 
5.9%
9 13
 
5.4%
Space Separator
ValueCountFrequency (%)
86
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 43
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 376
50.3%
Common 372
49.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
길 44
 
11.7%
면 40
 
10.6%
로 21
 
5.6%
산 11
 
2.9%
읍 10
 
2.7%
북 10
 
2.7%
성 9
 
2.4%
구 9
 
2.4%
동 8
 
2.1%
대 7
 
1.9%
Other values (91) 207
55.1%
Common
ValueCountFrequency (%)
86
23.1%
2 47
12.6%
- 43
11.6%
1 38
10.2%
5 27
 
7.3%
4 25
 
6.7%
3 23
 
6.2%
6 20
 
5.4%
0 17
 
4.6%
7 15
 
4.0%
Other values (4) 31
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 376
50.3%
ASCII 372
49.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
86
23.1%
2 47
12.6%
- 43
11.6%
1 38
10.2%
5 27
 
7.3%
4 25
 
6.7%
3 23
 
6.2%
6 20
 
5.4%
0 17
 
4.6%
7 15
 
4.0%
Other values (4) 31
 
8.3%
Hangul
ValueCountFrequency (%)
길 44
 
11.7%
면 40
 
10.6%
로 21
 
5.6%
산 11
 
2.9%
읍 10
 
2.7%
북 10
 
2.7%
성 9
 
2.4%
구 9
 
2.4%
동 8
 
2.1%
대 7
 
1.9%
Other values (91) 207
55.1%

연락처
Text

Distinct53
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Memory size588.0 B
2023-12-12T18:40:16.555147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters684
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

Unique49 ?
Unique (%)86.0%

Sample

1st row054-272-0586
2nd row054-262-9870
3rd row054-255-6001
4th row054-716-1616
5th row054-255-0041
ValueCountFrequency (%)
054-533-3501 2
 
3.5%
054-638-0688 2
 
3.5%
054-954-4176 2
 
3.5%
053-712-3200 2
 
3.5%
053-851-9800 1
 
1.8%
054-633-4967 1
 
1.8%
054-272-0586 1
 
1.8%
053-852-8885 1
 
1.8%
054-633-6761 1
 
1.8%
054-332-2841 1
 
1.8%
Other values (43) 43
75.4%
2023-12-12T18:40:17.106283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 114
16.7%
5 107
15.6%
0 105
15.4%
4 74
10.8%
3 60
8.8%
8 51
7.5%
6 46
6.7%
7 41
 
6.0%
2 37
 
5.4%
1 34
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 570
83.3%
Dash Punctuation 114
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 107
18.8%
0 105
18.4%
4 74
13.0%
3 60
10.5%
8 51
8.9%
6 46
8.1%
7 41
 
7.2%
2 37
 
6.5%
1 34
 
6.0%
9 15
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 114
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 684
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 114
16.7%
5 107
15.6%
0 105
15.4%
4 74
10.8%
3 60
8.8%
8 51
7.5%
6 46
6.7%
7 41
 
6.0%
2 37
 
5.4%
1 34
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 684
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 114
16.7%
5 107
15.6%
0 105
15.4%
4 74
10.8%
3 60
8.8%
8 51
7.5%
6 46
6.7%
7 41
 
6.0%
2 37
 
5.4%
1 34
 
5.0%

종사자수
Real number (ℝ)

HIGH CORRELATION 

Distinct31
Distinct (%)54.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.77193
Minimum5
Maximum86
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size645.0 B
2023-12-12T18:40:17.300520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile8.8
Q116
median22
Q327
95-th percentile48.4
Maximum86
Range81
Interquartile range (IQR)11

Descriptive statistics

Standard deviation15.313413
Coefficient of variation (CV)0.61817603
Kurtosis5.5900088
Mean24.77193
Median Absolute Deviation (MAD)6
Skewness2.0625963
Sum1412
Variance234.50063
MonotonicityNot monotonic
2023-12-12T18:40:17.451958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
22 6
 
10.5%
20 6
 
10.5%
25 4
 
7.0%
21 4
 
7.0%
24 3
 
5.3%
10 3
 
5.3%
11 3
 
5.3%
23 2
 
3.5%
29 2
 
3.5%
12 2
 
3.5%
Other values (21) 22
38.6%
ValueCountFrequency (%)
5 1
 
1.8%
6 1
 
1.8%
8 1
 
1.8%
9 1
 
1.8%
10 3
5.3%
11 3
5.3%
12 2
3.5%
14 1
 
1.8%
15 1
 
1.8%
16 1
 
1.8%
ValueCountFrequency (%)
86 1
1.8%
76 1
1.8%
62 1
1.8%
45 2
3.5%
44 1
1.8%
42 1
1.8%
37 1
1.8%
36 1
1.8%
34 1
1.8%
32 1
1.8%

정원
Real number (ℝ)

HIGH CORRELATION 

Distinct26
Distinct (%)45.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44.245614
Minimum7
Maximum200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size645.0 B
2023-12-12T18:40:17.642595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile15.8
Q130
median30
Q347
95-th percentile103.6
Maximum200
Range193
Interquartile range (IQR)17

Descriptive statistics

Standard deviation36.927187
Coefficient of variation (CV)0.83459543
Kurtosis10.210803
Mean44.245614
Median Absolute Deviation (MAD)3
Skewness3.0256947
Sum2522
Variance1363.6172
MonotonicityNot monotonic
2023-12-12T18:40:17.834851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
30 23
40.4%
50 3
 
5.3%
29 3
 
5.3%
80 2
 
3.5%
40 2
 
3.5%
200 2
 
3.5%
31 2
 
3.5%
22 2
 
3.5%
46 1
 
1.8%
63 1
 
1.8%
Other values (16) 16
28.1%
ValueCountFrequency (%)
7 1
 
1.8%
10 1
 
1.8%
15 1
 
1.8%
16 1
 
1.8%
20 1
 
1.8%
21 1
 
1.8%
22 2
 
3.5%
29 3
 
5.3%
30 23
40.4%
31 2
 
3.5%
ValueCountFrequency (%)
200 2
3.5%
130 1
 
1.8%
97 1
 
1.8%
80 2
3.5%
78 1
 
1.8%
75 1
 
1.8%
63 1
 
1.8%
60 1
 
1.8%
52 1
 
1.8%
50 3
5.3%

현원
Real number (ℝ)

HIGH CORRELATION 

Distinct34
Distinct (%)59.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39.631579
Minimum5
Maximum182
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size645.0 B
2023-12-12T18:40:18.353002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile9.6
Q129
median30
Q338
95-th percentile92
Maximum182
Range177
Interquartile range (IQR)9

Descriptive statistics

Standard deviation32.362143
Coefficient of variation (CV)0.81657465
Kurtosis9.0835122
Mean39.631579
Median Absolute Deviation (MAD)6
Skewness2.8222539
Sum2259
Variance1047.3083
MonotonicityNot monotonic
2023-12-12T18:40:18.519252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
30 15
26.3%
29 6
 
10.5%
72 2
 
3.5%
35 2
 
3.5%
31 2
 
3.5%
38 2
 
3.5%
45 1
 
1.8%
10 1
 
1.8%
157 1
 
1.8%
182 1
 
1.8%
Other values (24) 24
42.1%
ValueCountFrequency (%)
5 1
1.8%
7 1
1.8%
8 1
1.8%
10 1
1.8%
12 1
1.8%
15 1
1.8%
16 1
1.8%
18 1
1.8%
20 1
1.8%
21 1
1.8%
ValueCountFrequency (%)
182 1
1.8%
157 1
1.8%
128 1
1.8%
83 1
1.8%
77 1
1.8%
72 2
3.5%
61 1
1.8%
54 1
1.8%
53 1
1.8%
49 1
1.8%

법인명
Text

Distinct42
Distinct (%)73.7%
Missing0
Missing (%)0.0%
Memory size588.0 B
2023-12-12T18:40:18.800108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length5.9122807
Min length2

Characters and Unicode

Total characters337
Distinct characters99
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)54.4%

Sample

1st row성모자애원
2nd row안동애명복지촌
3rd row나전복지재단
4th row예티쉼터
5th row도움터복지재단
ValueCountFrequency (%)
안동애명복지촌 5
 
8.1%
성요셉복지재단 3
 
4.8%
사회복지법인 3
 
4.8%
대한불교조계종 2
 
3.2%
성모자애원 2
 
3.2%
사랑나눔 2
 
3.2%
대동시온재활원 2
 
3.2%
정토마을 2
 
3.2%
인람 2
 
3.2%
안동시온재단 2
 
3.2%
Other values (35) 37
59.7%
2023-12-12T18:40:19.275498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
복 27
 
8.0%
지 27
 
8.0%
재 25
 
7.4%
단 21
 
6.2%
동 11
 
3.3%
안 9
 
2.7%
사 9
 
2.7%
애 8
 
2.4%
회 8
 
2.4%
원 7
 
2.1%
Other values (89) 185
54.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 332
98.5%
Space Separator 5
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
복 27
 
8.1%
지 27
 
8.1%
재 25
 
7.5%
단 21
 
6.3%
동 11
 
3.3%
안 9
 
2.7%
사 9
 
2.7%
애 8
 
2.4%
회 8
 
2.4%
원 7
 
2.1%
Other values (88) 180
54.2%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 332
98.5%
Common 5
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
복 27
 
8.1%
지 27
 
8.1%
재 25
 
7.5%
단 21
 
6.3%
동 11
 
3.3%
안 9
 
2.7%
사 9
 
2.7%
애 8
 
2.4%
회 8
 
2.4%
원 7
 
2.1%
Other values (88) 180
54.2%
Common
ValueCountFrequency (%)
5
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 332
98.5%
ASCII 5
 
1.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
복 27
 
8.1%
지 27
 
8.1%
재 25
 
7.5%
단 21
 
6.3%
동 11
 
3.3%
안 9
 
2.7%
사 9
 
2.7%
애 8
 
2.4%
회 8
 
2.4%
원 7
 
2.1%
Other values (88) 180
54.2%
ASCII
ValueCountFrequency (%)
5
100.0%

Interactions

2023-12-12T18:40:13.513422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:40:12.277915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:40:12.702423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:40:13.129363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:40:13.598355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:40:12.367444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:40:12.816746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:40:13.228284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:40:13.690968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:40:12.482560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:40:12.920408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:40:13.327932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:40:13.798245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:40:12.595025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:40:13.024612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:40:13.422885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:40:19.407947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시군명시설명유형설치일소재지연락처종사자수정원현원법인명
연번1.0000.9720.9410.0000.9411.0000.9580.0000.4220.2470.908
시군명0.9721.0000.0000.0000.9941.0001.0000.0000.0000.0000.977
시설명0.9410.0001.0000.9710.9970.9890.9901.0001.0001.0000.975
유형0.0000.0000.9711.0000.0000.6720.9780.1380.4030.0000.287
설치일0.9410.9940.9970.0001.0000.9890.9901.0000.9730.9880.975
소재지1.0001.0000.9890.6720.9891.0000.9930.0000.0000.0001.000
연락처0.9581.0000.9900.9780.9900.9931.0000.0000.7080.0001.000
종사자수0.0000.0001.0000.1381.0000.0000.0001.0000.9050.9910.000
정원0.4220.0001.0000.4030.9730.0000.7080.9051.0000.9540.000
현원0.2470.0001.0000.0000.9880.0000.0000.9910.9541.0000.000
법인명0.9080.9770.9750.2870.9751.0001.0000.0000.0000.0001.000
2023-12-12T18:40:19.557693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명유형
시군명1.0000.000
유형0.0001.000
2023-12-12T18:40:19.670215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번종사자수정원현원시군명유형
연번1.000-0.084-0.020-0.0520.6520.000
종사자수-0.0841.0000.9270.9590.0000.066
정원-0.0200.9271.0000.9320.0000.263
현원-0.0520.9590.9321.0000.0000.000
시군명0.6520.0000.0000.0001.0000.000
유형0.0000.0660.2630.0000.0001.000

Missing values

2023-12-12T18:40:13.932163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:40:14.090462image/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

연번시군명시설명유형설치일소재지연락처종사자수정원현원법인명
01포항시마리아의집지체 뇌병변1984-10-24남구 대잠동길17-1(대잠동)054-272-0586304645성모자애원
12포항시향기마을중증2008-09-08북구 흥해읍사방공원길 502054-262-9870263131안동애명복지촌
23포항시나전복지마을중증2010-03-05남구 장기면장기로1229번길 39054-255-6001223030나전복지재단
34포항시예우리중증2010-07-01남구 동해면금광로 79054-716-1616243030예티쉼터
45포항시도움터기쁨의집지적 자폐성2010-08-18북구 기계면고지길 62-63054-255-0041203028도움터복지재단
56포항시민들레공동체중증2010-09-20북구 청하면용산길 277-6054-246-5005253535들꽃마을
67포항시엘림소망의집지적 자폐성2011-03-02북구 송라면동해대로 2792-100054-256-6003203029중앙엘림복지재단
78포항시베들레헴공동체중증2018-05-28북구 송라면 대전길 56-83054-262-8580101515사회복지법인 베들레헴
89경주시선인재활원지적 자폐성1998-07-21산내면 대현길436-42054-751-8896254735상록수
910경주시다사랑지적 자폐성2012-09-21서면 도리길35-137054-751-77036108다 애
연번시군명시설명유형설치일소재지연락처종사자수정원현원법인명
4748영양군경북행복재활원중증2012-12-27석보면 민실길 46054-683-0112233030국민복지재단
4849영덕군사랑마을중증2015-05-22영덕읍 영축로 285054-726-2080153024경상사회복지재단
4950고령군성요셉재활원중증1957-02-07성산면 성산로942-4054-954-4176366054성요셉복지재단
5051고령군성요셉요양원중증1994-05-12성산면 성산로942-4054-954-4176275046성요셉복지재단
5152성주군사회복지법인 해솔 예원의집지적 자폐성2006-12-11가천면 금봉길 27-8054-931-7331122121해솔
5253칠곡군밀알공동체중증2005-12-05가산면 유학로 918054-972-9301243030한밀복지재단
5354칠곡군행복한동행중증2018-02-01기산면 한솔1길 54054-976-08028305인의복지재단
5455예천군예천사랑마을중증1997-10-14용궁면 경서로1282-80054-653-6700254038안동애명복지촌
5556예천군극락마을중증2003-12-30풍양면 낙상1길58-50054-654-9003346353예천연꽃마을
5657울진군인덕사랑마을지적 자폐성2013-11-26후포면 만산길 201054-788-5051213030사랑나눔