Overview

Dataset statistics

Number of variables13
Number of observations74
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.7 KiB
Average record size in memory106.8 B

Variable types

Numeric1
Categorical6
Text6

Dataset

Description장애인복지시설거주시설안내20146
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=201955

Alerts

전라북도 is highly overall correlated with 종사자정원High correlation
종사자정원 is highly overall correlated with 전라북도 and 3 other fieldsHigh correlation
종사자현원 is highly overall correlated with 종사자정원 and 1 other fieldsHigh correlation
생활인정원 is highly overall correlated with 종사자정원 and 1 other fieldsHigh correlation
비고 is highly overall correlated with 종사자정원High correlation
총계 has unique valuesUnique
시설명 has unique valuesUnique

Reproduction

Analysis started2024-03-14 00:33:15.926318
Analysis finished2024-03-14 00:33:17.353204
Duration1.43 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

총계
Real number (ℝ)

UNIQUE 

Distinct74
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.5
Minimum1
Maximum74
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size798.0 B
2024-03-14T09:33:17.416015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.65
Q119.25
median37.5
Q355.75
95-th percentile70.35
Maximum74
Range73
Interquartile range (IQR)36.5

Descriptive statistics

Standard deviation21.505813
Coefficient of variation (CV)0.57348835
Kurtosis-1.2
Mean37.5
Median Absolute Deviation (MAD)18.5
Skewness0
Sum2775
Variance462.5
MonotonicityStrictly increasing
2024-03-14T09:33:17.543690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.4%
57 1
 
1.4%
55 1
 
1.4%
54 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%
Other values (64) 64
86.5%
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 (%)
74 1
1.4%
73 1
1.4%
72 1
1.4%
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%

전라북도
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size724.0 B
장애인거주시설
51 
장애인 공동생활가정
17 
장애인공동생활가정
 
4
장애인 단기거주시설
 
2

Length

Max length10
Median length7
Mean length7.8783784
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
장애인거주시설 51
68.9%
장애인 공동생활가정 17
 
23.0%
장애인공동생활가정 4
 
5.4%
장애인 단기거주시설 2
 
2.7%

Length

2024-03-14T09:33:17.658936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:33:17.742139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
장애인거주시설 51
54.8%
장애인 19
 
20.4%
공동생활가정 17
 
18.3%
장애인공동생활가정 4
 
4.3%
단기거주시설 2
 
2.2%

시설명
Text

UNIQUE 

Distinct74
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size724.0 B
2024-03-14T09:33:17.904944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length11
Mean length5.6891892
Min length2

Characters and Unicode

Total characters421
Distinct characters135
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

Unique74 ?
Unique (%)100.0%

Sample

1st row전주자림원
2nd row자림인애원
3rd row동암재활원
4th row소화진달네집
5th row평안의집
ValueCountFrequency (%)
집 4
 
4.8%
자림공동생활가정 2
 
2.4%
전주자림원 1
 
1.2%
정읍장애인복지관 1
 
1.2%
지구촌마을 1
 
1.2%
둥지지공동생활가정 1
 
1.2%
부설공동생활가정 1
 
1.2%
남원장애인복지관 1
 
1.2%
편한세상 1
 
1.2%
평화의집 1
 
1.2%
Other values (70) 70
83.3%
2024-03-14T09:33:18.201292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
집 28
 
6.7%
의 24
 
5.7%
원 16
 
3.8%
동 15
 
3.6%
11
 
2.6%
활 10
 
2.4%
공 10
 
2.4%
정 9
 
2.1%
은 9
 
2.1%
가 9
 
2.1%
Other values (125) 280
66.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 405
96.2%
Space Separator 11
 
2.6%
Decimal Number 5
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
집 28
 
6.9%
의 24
 
5.9%
원 16
 
4.0%
동 15
 
3.7%
활 10
 
2.5%
공 10
 
2.5%
정 9
 
2.2%
은 9
 
2.2%
가 9
 
2.2%
자 9
 
2.2%
Other values (121) 266
65.7%
Decimal Number
ValueCountFrequency (%)
2 2
40.0%
1 2
40.0%
3 1
20.0%
Space Separator
ValueCountFrequency (%)
11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 405
96.2%
Common 16
 
3.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
집 28
 
6.9%
의 24
 
5.9%
원 16
 
4.0%
동 15
 
3.7%
활 10
 
2.5%
공 10
 
2.5%
정 9
 
2.2%
은 9
 
2.2%
가 9
 
2.2%
자 9
 
2.2%
Other values (121) 266
65.7%
Common
ValueCountFrequency (%)
11
68.8%
2 2
 
12.5%
1 2
 
12.5%
3 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 405
96.2%
ASCII 16
 
3.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
집 28
 
6.9%
의 24
 
5.9%
원 16
 
4.0%
동 15
 
3.7%
활 10
 
2.5%
공 10
 
2.5%
정 9
 
2.2%
은 9
 
2.2%
가 9
 
2.2%
자 9
 
2.2%
Other values (121) 266
65.7%
ASCII
ValueCountFrequency (%)
11
68.8%
2 2
 
12.5%
1 2
 
12.5%
3 1
 
6.2%

설치신고일
Text

Distinct68
Distinct (%)91.9%
Missing0
Missing (%)0.0%
Memory size724.0 B
2024-03-14T09:33:18.401662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.0675676
Min length8

Characters and Unicode

Total characters597
Distinct characters12
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

Unique64 ?
Unique (%)86.5%

Sample

1st row80.12.20
2nd row87.07.01
3rd row90.09.03
4th row06.04.28
5th row10.12.30
ValueCountFrequency (%)
02.03.27 3
 
4.1%
07.03.09 3
 
4.1%
06.12.26 2
 
2.7%
08.07.31 2
 
2.7%
10.03.15 1
 
1.4%
80.12.20 1
 
1.4%
99.02.01 1
 
1.4%
52.05.05 1
 
1.4%
11.10.20 1
 
1.4%
06.10.09 1
 
1.4%
Other values (58) 58
78.4%
2024-03-14T09:33:19.017991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 161
27.0%
. 147
24.6%
1 80
13.4%
2 53
 
8.9%
7 32
 
5.4%
3 27
 
4.5%
6 25
 
4.2%
9 19
 
3.2%
8 18
 
3.0%
4 18
 
3.0%
Other values (2) 17
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 448
75.0%
Other Punctuation 149
 
25.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 161
35.9%
1 80
17.9%
2 53
 
11.8%
7 32
 
7.1%
3 27
 
6.0%
6 25
 
5.6%
9 19
 
4.2%
8 18
 
4.0%
4 18
 
4.0%
5 15
 
3.3%
Other Punctuation
ValueCountFrequency (%)
. 147
98.7%
, 2
 
1.3%

Most occurring scripts

ValueCountFrequency (%)
Common 597
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 161
27.0%
. 147
24.6%
1 80
13.4%
2 53
 
8.9%
7 32
 
5.4%
3 27
 
4.5%
6 25
 
4.2%
9 19
 
3.2%
8 18
 
3.0%
4 18
 
3.0%
Other values (2) 17
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 597
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 161
27.0%
. 147
24.6%
1 80
13.4%
2 53
 
8.9%
7 32
 
5.4%
3 27
 
4.5%
6 25
 
4.2%
9 19
 
3.2%
8 18
 
3.0%
4 18
 
3.0%
Other values (2) 17
 
2.8%

시설장
Text

Distinct64
Distinct (%)86.5%
Missing0
Missing (%)0.0%
Memory size724.0 B
2024-03-14T09:33:19.247361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.1216216
Min length3

Characters and Unicode

Total characters231
Distinct characters83
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

Unique58 ?
Unique (%)78.4%

Sample

1st row박미숙
2nd row홍규식
3rd row진용철
4th row박청자
5th row서영숙
ValueCountFrequency (%)
박미숙 4
 
5.1%
진숙선 3
 
3.8%
이건중 3
 
3.8%
권영조 2
 
2.6%
서철승 2
 
2.6%
이순자 2
 
2.6%
최규순 1
 
1.3%
양석현 1
 
1.3%
문영숙 1
 
1.3%
이용문 1
 
1.3%
Other values (58) 58
74.4%
2024-03-14T09:33:19.590570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
숙 14
 
6.1%
박 12
 
5.2%
12
 
5.2%
김 11
 
4.8%
이 10
 
4.3%
순 7
 
3.0%
정 6
 
2.6%
진 5
 
2.2%
권 5
 
2.2%
영 5
 
2.2%
Other values (73) 144
62.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 219
94.8%
Space Separator 12
 
5.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
숙 14
 
6.4%
박 12
 
5.5%
김 11
 
5.0%
이 10
 
4.6%
순 7
 
3.2%
정 6
 
2.7%
진 5
 
2.3%
권 5
 
2.3%
영 5
 
2.3%
종 5
 
2.3%
Other values (72) 139
63.5%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 219
94.8%
Common 12
 
5.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
숙 14
 
6.4%
박 12
 
5.5%
김 11
 
5.0%
이 10
 
4.6%
순 7
 
3.2%
정 6
 
2.7%
진 5
 
2.3%
권 5
 
2.3%
영 5
 
2.3%
종 5
 
2.3%
Other values (72) 139
63.5%
Common
ValueCountFrequency (%)
12
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 219
94.8%
ASCII 12
 
5.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
숙 14
 
6.4%
박 12
 
5.5%
김 11
 
5.0%
이 10
 
4.6%
순 7
 
3.2%
정 6
 
2.7%
진 5
 
2.3%
권 5
 
2.3%
영 5
 
2.3%
종 5
 
2.3%
Other values (72) 139
63.5%
ASCII
ValueCountFrequency (%)
12
100.0%

주 소
Text

Distinct71
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Memory size724.0 B
2024-03-14T09:33:19.853542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length26
Mean length18.445946
Min length9

Characters and Unicode

Total characters1365
Distinct characters155
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique68 ?
Unique (%)91.9%

Sample

1st row전주시 덕진구 번영로230-14(성덕동)
2nd row전주시 덕진구 번영로230-14(성덕동)
3rd row전주시 완산구 천잠로275(효자동3가)
4th row전주시 완산구 우림로595-32(용복동)
5th row전주시 완산구 선너머2길-15(중화산동2가)
ValueCountFrequency (%)
익산시 15
 
5.2%
전주시 14
 
4.9%
완주군 9
 
3.1%
정읍시 9
 
3.1%
전북 9
 
3.1%
군산시 8
 
2.8%
완산구 7
 
2.4%
덕진구 7
 
2.4%
남원시 4
 
1.4%
김제시 4
 
1.4%
Other values (175) 202
70.1%
2024-03-14T09:33:20.203277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
217
 
15.9%
1 77
 
5.6%
시 55
 
4.0%
길 43
 
3.2%
산 42
 
3.1%
- 40
 
2.9%
2 38
 
2.8%
5 36
 
2.6%
면 34
 
2.5%
0 34
 
2.5%
Other values (145) 749
54.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 735
53.8%
Decimal Number 325
23.8%
Space Separator 217
 
15.9%
Dash Punctuation 40
 
2.9%
Close Punctuation 16
 
1.2%
Open Punctuation 16
 
1.2%
Other Punctuation 12
 
0.9%
Lowercase Letter 4
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 55
 
7.5%
길 43
 
5.9%
산 42
 
5.7%
면 34
 
4.6%
로 29
 
3.9%
주 28
 
3.8%
군 28
 
3.8%
전 24
 
3.3%
동 23
 
3.1%
익 16
 
2.2%
Other values (127) 413
56.2%
Decimal Number
ValueCountFrequency (%)
1 77
23.7%
2 38
11.7%
5 36
11.1%
0 34
10.5%
6 28
 
8.6%
4 28
 
8.6%
3 26
 
8.0%
7 23
 
7.1%
8 19
 
5.8%
9 16
 
4.9%
Other Punctuation
ValueCountFrequency (%)
@ 6
50.0%
, 4
33.3%
/ 2
 
16.7%
Space Separator
ValueCountFrequency (%)
217
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 40
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Lowercase Letter
ValueCountFrequency (%)
a 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 735
53.8%
Common 626
45.9%
Latin 4
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 55
 
7.5%
길 43
 
5.9%
산 42
 
5.7%
면 34
 
4.6%
로 29
 
3.9%
주 28
 
3.8%
군 28
 
3.8%
전 24
 
3.3%
동 23
 
3.1%
익 16
 
2.2%
Other values (127) 413
56.2%
Common
ValueCountFrequency (%)
217
34.7%
1 77
 
12.3%
- 40
 
6.4%
2 38
 
6.1%
5 36
 
5.8%
0 34
 
5.4%
6 28
 
4.5%
4 28
 
4.5%
3 26
 
4.2%
7 23
 
3.7%
Other values (7) 79
 
12.6%
Latin
ValueCountFrequency (%)
a 4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 735
53.8%
ASCII 630
46.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
217
34.4%
1 77
 
12.2%
- 40
 
6.3%
2 38
 
6.0%
5 36
 
5.7%
0 34
 
5.4%
6 28
 
4.4%
4 28
 
4.4%
3 26
 
4.1%
7 23
 
3.7%
Other values (8) 83
 
13.2%
Hangul
ValueCountFrequency (%)
시 55
 
7.5%
길 43
 
5.9%
산 42
 
5.7%
면 34
 
4.6%
로 29
 
3.9%
주 28
 
3.8%
군 28
 
3.8%
전 24
 
3.3%
동 23
 
3.1%
익 16
 
2.2%
Other values (127) 413
56.2%

전화번호
Text

Distinct73
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size724.0 B
2024-03-14T09:33:20.413017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length8
Mean length8.1891892
Min length8

Characters and Unicode

Total characters606
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique72 ?
Unique (%)97.3%

Sample

1st row223-1568
2nd row276-1568
3rd row222-4444
4th row222-2786
5th row282-7728
ValueCountFrequency (%)
452-0911 2
 
2.7%
223-1568 1
 
1.4%
544-9756 1
 
1.4%
547-9464 1
 
1.4%
542-9466 1
 
1.4%
542-5844 1
 
1.4%
636-6204 1
 
1.4%
635-1546 1
 
1.4%
634-9988 1
 
1.4%
635-5004 1
 
1.4%
Other values (63) 63
85.1%
2024-03-14T09:33:20.731635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 76
12.5%
3 76
12.5%
5 75
12.4%
4 65
10.7%
2 62
10.2%
1 52
8.6%
6 50
8.3%
8 49
8.1%
0 34
5.6%
9 34
5.6%
Other values (2) 33
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 528
87.1%
Dash Punctuation 76
 
12.5%
Math Symbol 2
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 76
14.4%
5 75
14.2%
4 65
12.3%
2 62
11.7%
1 52
9.8%
6 50
9.5%
8 49
9.3%
0 34
6.4%
9 34
6.4%
7 31
5.9%
Dash Punctuation
ValueCountFrequency (%)
- 76
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 606
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 76
12.5%
3 76
12.5%
5 75
12.4%
4 65
10.7%
2 62
10.2%
1 52
8.6%
6 50
8.3%
8 49
8.1%
0 34
5.6%
9 34
5.6%
Other values (2) 33
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 606
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 76
12.5%
3 76
12.5%
5 75
12.4%
4 65
10.7%
2 62
10.2%
1 52
8.6%
6 50
8.3%
8 49
8.1%
0 34
5.6%
9 34
5.6%
Other values (2) 33
5.4%

종사자정원
Categorical

HIGH CORRELATION 

Distinct27
Distinct (%)36.5%
Missing0
Missing (%)0.0%
Memory size724.0 B
1
21 
8
4 
6
4 
22
4 
26
4 
Other values (22)
37 

Length

Max length4
Median length3
Mean length3.4864865
Min length3

Unique

Unique11 ?
Unique (%)14.9%

Sample

1st row 30
2nd row 40
3rd row 17
4th row 15
5th row 8

Common Values

ValueCountFrequency (%)
1 21
28.4%
8 4
 
5.4%
6 4
 
5.4%
22 4
 
5.4%
26 4
 
5.4%
7 3
 
4.1%
25 3
 
4.1%
10 3
 
4.1%
18 3
 
4.1%
27 2
 
2.7%
Other values (17) 23
31.1%

Length

2024-03-14T09:33:20.844323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1 21
28.4%
6 4
 
5.4%
22 4
 
5.4%
26 4
 
5.4%
8 4
 
5.4%
7 3
 
4.1%
25 3
 
4.1%
10 3
 
4.1%
18 3
 
4.1%
16 2
 
2.7%
Other values (17) 23
31.1%

종사자현원
Categorical

HIGH CORRELATION 

Distinct27
Distinct (%)36.5%
Missing0
Missing (%)0.0%
Memory size724.0 B
1
19 
10
4 
26
4 
25
4 
6
4 
Other values (22)
39 

Length

Max length4
Median length3
Mean length3.4864865
Min length3

Unique

Unique10 ?
Unique (%)13.5%

Sample

1st row 29
2nd row 40
3rd row 17
4th row 15
5th row 8

Common Values

ValueCountFrequency (%)
1 19
25.7%
10 4
 
5.4%
26 4
 
5.4%
25 4
 
5.4%
6 4
 
5.4%
4 3
 
4.1%
8 3
 
4.1%
21 3
 
4.1%
18 3
 
4.1%
22 3
 
4.1%
Other values (17) 24
32.4%

Length

2024-03-14T09:33:20.963678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1 19
25.7%
10 4
 
5.4%
26 4
 
5.4%
25 4
 
5.4%
6 4
 
5.4%
4 3
 
4.1%
8 3
 
4.1%
21 3
 
4.1%
18 3
 
4.1%
22 3
 
4.1%
Other values (17) 24
32.4%

생활인정원
Categorical

HIGH CORRELATION 

Distinct27
Distinct (%)36.5%
Missing0
Missing (%)0.0%
Memory size724.0 B
4
17 
40
7 
50
6 
30
5 
20
4 
Other values (22)
35 

Length

Max length5
Median length4
Mean length3.7432432
Min length3

Unique

Unique12 ?
Unique (%)16.2%

Sample

1st row 100
2nd row 72
3rd row 70
4th row 40
5th row 20

Common Values

ValueCountFrequency (%)
4 17
23.0%
40 7
 
9.5%
50 6
 
8.1%
30 5
 
6.8%
20 4
 
5.4%
15 3
 
4.1%
10 3
 
4.1%
29 3
 
4.1%
28 2
 
2.7%
9 2
 
2.7%
Other values (17) 22
29.7%

Length

2024-03-14T09:33:21.091177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
4 17
23.0%
40 7
 
9.5%
50 6
 
8.1%
30 5
 
6.8%
20 4
 
5.4%
15 3
 
4.1%
10 3
 
4.1%
29 3
 
4.1%
7 2
 
2.7%
25 2
 
2.7%
Other values (17) 22
29.7%

생활인현원
Text

Distinct41
Distinct (%)55.4%
Missing0
Missing (%)0.0%
Memory size724.0 B
2024-03-14T09:33:21.251263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.5810811
Min length1

Characters and Unicode

Total characters265
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)29.7%

Sample

1st row 72
2nd row 70
3rd row 51
4th row 35
5th row 20
ValueCountFrequency (%)
4 11
 
14.9%
35 4
 
5.4%
29 3
 
4.1%
3 3
 
4.1%
2 3
 
4.1%
8 3
 
4.1%
20 3
 
4.1%
47 2
 
2.7%
10 2
 
2.7%
2
 
2.7%
Other values (30) 38
51.4%
2024-03-14T09:33:21.505275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
142
53.6%
4 26
 
9.8%
2 20
 
7.5%
3 18
 
6.8%
0 11
 
4.2%
5 10
 
3.8%
7 10
 
3.8%
1 10
 
3.8%
8 7
 
2.6%
9 6
 
2.3%
Other values (2) 5
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Space Separator 142
53.6%
Decimal Number 121
45.7%
Dash Punctuation 2
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 26
21.5%
2 20
16.5%
3 18
14.9%
0 11
9.1%
5 10
 
8.3%
7 10
 
8.3%
1 10
 
8.3%
8 7
 
5.8%
9 6
 
5.0%
6 3
 
2.5%
Space Separator
ValueCountFrequency (%)
142
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 265
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
142
53.6%
4 26
 
9.8%
2 20
 
7.5%
3 18
 
6.8%
0 11
 
4.2%
5 10
 
3.8%
7 10
 
3.8%
1 10
 
3.8%
8 7
 
2.6%
9 6
 
2.3%
Other values (2) 5
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 265
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
142
53.6%
4 26
 
9.8%
2 20
 
7.5%
3 18
 
6.8%
0 11
 
4.2%
5 10
 
3.8%
7 10
 
3.8%
1 10
 
3.8%
8 7
 
2.6%
9 6
 
2.3%
Other values (2) 5
 
1.9%

운영주체(법인명)
Categorical

Distinct32
Distinct (%)43.2%
Missing0
Missing (%)0.0%
Memory size724.0 B
개인
22 
사복)중도원
6 
사복)자림복지재단
5 
사복)해오름복지재단
 
3
사복)전주가톨릭사회복지회
 
3
Other values (27)
35 

Length

Max length17
Median length15.5
Mean length7.1756757
Min length2

Unique

Unique20 ?
Unique (%)27.0%

Sample

1st row사복)자림복지재단
2nd row사복)자림복지재단
3rd row사복)동암
4th row사복)소화자매원
5th row개인

Common Values

ValueCountFrequency (%)
개인 22
29.7%
사복)중도원 6
 
8.1%
사복)자림복지재단 5
 
6.8%
사복)해오름복지재단 3
 
4.1%
사복)전주가톨릭사회복지회 3
 
4.1%
사복)창혜복지재단 3
 
4.1%
사복)전주카톨릭사회복지회 2
 
2.7%
사복)어깨동무복지재단 2
 
2.7%
사복)한기장복지재단 2
 
2.7%
사복)전북보성원 2
 
2.7%
Other values (22) 24
32.4%

Length

2024-03-14T09:33:21.646119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
개인 22
28.6%
사복)중도원 6
 
7.8%
사복)자림복지재단 5
 
6.5%
사복)해오름복지재단 3
 
3.9%
사복)전주가톨릭사회복지회 3
 
3.9%
사복)창혜복지재단 3
 
3.9%
사복)전북보성원 2
 
2.6%
사복)국제원 2
 
2.6%
사복)자애복지재단 2
 
2.6%
사복)한기장복지재단 2
 
2.6%
Other values (25) 27
35.1%

비고
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)14.9%
Missing0
Missing (%)0.0%
Memory size724.0 B
지적
27 
-
22 
중증
9 
지적
5 
지체
4 
Other values (6)
7 

Length

Max length20
Median length2
Mean length2.1486486
Min length1

Unique

Unique5 ?
Unique (%)6.8%

Sample

1st row지적
2nd row중증
3rd row지체
4th row지적(여)
5th row지적

Common Values

ValueCountFrequency (%)
지적 27
36.5%
- 22
29.7%
중증 9
 
12.2%
지적 5
 
6.8%
지체 4
 
5.4%
중증실비 2
 
2.7%
지적(여) 1
 
1.4%
휴지 중 14.6.18~15.5.31 1
 
1.4%
시각 1
 
1.4%
영유아 1
 
1.4%

Length

2024-03-14T09:33:21.752710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
지적 32
41.6%
22
28.6%
중증 9
 
11.7%
지체 4
 
5.2%
중증실비 2
 
2.6%
휴지 2
 
2.6%
중 2
 
2.6%
지적(여 1
 
1.3%
14.6.18~15.5.31 1
 
1.3%
시각 1
 
1.3%

Interactions

2024-03-14T09:33:17.060649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T09:33:21.827404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
총계전라북도시설명설치신고일시설장주 소전화번호종사자정원종사자현원생활인정원생활인현원운영주체(법인명)비고
총계1.0000.4901.0000.9720.9581.0001.0000.4350.5020.3610.7100.8660.450
전라북도0.4901.0001.0000.0000.9691.0001.0000.8890.7740.8220.8370.8860.637
시설명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
설치신고일0.9720.0001.0001.0000.9770.9930.9940.9490.9580.9730.9760.9870.000
시설장0.9580.9691.0000.9771.0000.9841.0000.9770.9840.9890.9791.0000.000
주 소1.0001.0001.0000.9930.9841.0000.9950.0000.8580.0000.0001.0000.669
전화번호1.0001.0001.0000.9941.0000.9951.0001.0001.0001.0001.0001.0001.000
종사자정원0.4350.8891.0000.9490.9770.0001.0001.0000.9940.9820.9690.7280.926
종사자현원0.5020.7741.0000.9580.9840.8581.0000.9941.0000.9650.9410.3380.881
생활인정원0.3610.8221.0000.9730.9890.0001.0000.9820.9651.0000.9810.5040.613
생활인현원0.7100.8371.0000.9760.9790.0001.0000.9690.9410.9811.0000.0000.733
운영주체(법인명)0.8660.8861.0000.9871.0001.0001.0000.7280.3380.5040.0001.0000.000
비고0.4500.6371.0000.0000.0000.6691.0000.9260.8810.6130.7330.0001.000
2024-03-14T09:33:21.950561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종사자현원종사자정원전라북도생활인정원운영주체(법인명)비고
종사자현원1.0000.7490.4300.5130.0000.475
종사자정원0.7491.0000.5690.6110.2130.566
전라북도0.4300.5691.0000.4820.4850.418
생활인정원0.5130.6110.4821.0000.0890.214
운영주체(법인명)0.0000.2130.4850.0891.0000.000
비고0.4750.5660.4180.2140.0001.000
2024-03-14T09:33:22.046576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
총계전라북도종사자정원종사자현원생활인정원운영주체(법인명)비고
총계1.0000.2980.1290.1610.0930.4260.203
전라북도0.2981.0000.5690.4300.4820.4850.418
종사자정원0.1290.5691.0000.7490.6110.2130.566
종사자현원0.1610.4300.7491.0000.5130.0000.475
생활인정원0.0930.4820.6110.5131.0000.0890.214
운영주체(법인명)0.4260.4850.2130.0000.0891.0000.000
비고0.2030.4180.5660.4750.2140.0001.000

Missing values

2024-03-14T09:33:17.157126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T09:33:17.298892image/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

총계전라북도시설명설치신고일시설장주 소전화번호종사자정원종사자현원생활인정원생활인현원운영주체(법인명)비고
01장애인거주시설전주자림원80.12.20박미숙전주시 덕진구 번영로230-14(성덕동)223-1568302910072사복)자림복지재단지적
12장애인거주시설자림인애원87.07.01홍규식전주시 덕진구 번영로230-14(성덕동)276-156840407270사복)자림복지재단중증
23장애인거주시설동암재활원90.09.03진용철전주시 완산구 천잠로275(효자동3가)222-444417177051사복)동암지체
34장애인거주시설소화진달네집06.04.28박청자전주시 완산구 우림로595-32(용복동)222-278615154035사복)소화자매원지적(여)
45장애인거주시설평안의집10.12.30서영숙전주시 완산구 선너머2길-15(중화산동2가)282-7728882020개인지적
56장애인 단기거주시설한마음단기보호센터02.03.27김학권전주시 완산구 계룡산길 44-8223-4935441010사)전북장애인부모회-
67장애인 공동생활가정자림공동생활가정 1호02.03.27박미숙전주시 덕진구 반월5길 8, 103동 308호 (삼오@)212-49351144사복)자림복지재단-
78장애인 공동생활가정자림공동생활가정2호04.01.02박미숙전주시 덕진구 반월5길8 102동210호(삼오@)226-49351142사복)자림복지재단-
89장애인 공동생활가정자림공동생활가정 3호07.01.22박미숙전주시 덕진구 반월5길 8 102동 1705호(삼오@)214-15681-4-사복)자림복지재단휴지 중 14.6.18~15.5.31
910장애인 공동생활가정작은예수의집05.12.13김경숙전주시 덕진구 덕용2길 6-2212-15891197재)작은예수수녀회-
총계전라북도시설명설치신고일시설장주 소전화번호종사자정원종사자현원생활인정원생활인현원운영주체(법인명)비고
6465장애인거주시설흰마실08.04.22박주종진안군 백운면 윤기길 4-35433-220016163030사복)낮은자리지적
6566장애인거주시설하은의 집07.12.24이근덕무주군 부남면 상평당길 41322-644818183533사복)하은복지재단지적
6667장애인거주시설벧엘장애인의집06.10.02서 정장수군 장계면 명덕양지길 106-1353-125165158개인지적
6768장애인거주시설만나의집06.05.08김태곤장수군 번암면 성암길 458-16352-3688----개인휴지 중
6869장애인거주시설로뎀하우스2006.01.24노 준임실군 신평면 석등슬치로 491-7643-188818183028사복)크리스찬복지재단지적
6970장애인공동생활가정소망장애인공동체2010.11.12추성은임실군 임실읍 호국로 1456-57643-70041142개인-
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