Overview

Dataset statistics

Number of variables11
Number of observations414
Missing cells44
Missing cells (%)1.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory36.1 KiB
Average record size in memory89.3 B

Variable types

Numeric1
Categorical1
Text9

Dataset

Description사회복지생활시설현황전라북도2016
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=201863

Alerts

종사자정원 has 13 (3.1%) missing valuesMissing
종사자현원 has 13 (3.1%) missing valuesMissing
생활정원 has 9 (2.2%) missing valuesMissing
생활현원 has 9 (2.2%) missing valuesMissing

Reproduction

Analysis started2024-03-14 02:09:14.159518
Analysis finished2024-03-14 02:09:15.976084
Duration1.82 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

Distinct98
Distinct (%)23.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.73913
Minimum1
Maximum99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.8 KiB
2024-03-14T11:09:16.039169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q18
median21
Q344.75
95-th percentile81
Maximum99
Range98
Interquartile range (IQR)36.75

Descriptive statistics

Standard deviation25.209717
Coefficient of variation (CV)0.87719137
Kurtosis-0.062087852
Mean28.73913
Median Absolute Deviation (MAD)15
Skewness0.96632344
Sum11898
Variance635.52985
MonotonicityNot monotonic
2024-03-14T11:09:16.155380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 14
 
3.4%
2 14
 
3.4%
3 14
 
3.4%
4 14
 
3.4%
5 14
 
3.4%
6 14
 
3.4%
7 13
 
3.1%
8 12
 
2.9%
9 10
 
2.4%
10 10
 
2.4%
Other values (88) 285
68.8%
ValueCountFrequency (%)
1 14
3.4%
2 14
3.4%
3 14
3.4%
4 14
3.4%
5 14
3.4%
6 14
3.4%
7 13
3.1%
8 12
2.9%
9 10
2.4%
10 10
2.4%
ValueCountFrequency (%)
99 1
0.2%
98 1
0.2%
97 1
0.2%
96 1
0.2%
95 1
0.2%
94 1
0.2%
93 1
0.2%
92 1
0.2%
91 1
0.2%
90 1
0.2%

시설구분
Categorical

Distinct22
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
노인요양시설
162 
노인요양공동생활가정
66 
장애인거주시설
51 
아동공동생활가정
35 
사회복귀시설
19 
Other values (17)
81 

Length

Max length10
Median length6
Mean length7.3164251
Min length6

Unique

Unique6 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
노인요양시설 162
39.1%
노인요양공동생활가정 66
15.9%
장애인거주시설 51
 
12.3%
아동공동생활가정 35
 
8.5%
사회복귀시설 19
 
4.6%
장애인 공동생활가정 17
 
4.1%
아동양육시설 14
 
3.4%
아동 공동생활시설 10
 
2.4%
노인양로시설 10
 
2.4%
한부모가족복지시설 7
 
1.7%
Other values (12) 23
 
5.6%

Length

2024-03-14T11:09:16.266190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
노인요양시설 162
36.1%
노인요양공동생활가정 66
14.7%
장애인거주시설 51
 
11.4%
아동공동생활가정 35
 
7.8%
사회복귀시설 19
 
4.2%
장애인 19
 
4.2%
공동생활가정 17
 
3.8%
아동양육시설 14
 
3.1%
아동 10
 
2.2%
공동생활시설 10
 
2.2%
Other values (16) 46
 
10.2%

시설명
Text

Distinct403
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
2024-03-14T11:09:16.443851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length6.7077295
Min length2

Characters and Unicode

Total characters2777
Distinct characters297
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

Unique392 ?
Unique (%)94.7%

Sample

1st row마음건강복지관
2nd row마음건강회복홈
3rd row마음건강힐링홈
4th row아름다운세상
5th row아름다운집
ValueCountFrequency (%)
집 13
 
2.9%
벧엘요양원 3
 
0.7%
행복한집 3
 
0.7%
1호 3
 
0.7%
자림공동생활가정 3
 
0.7%
사랑의집 2
 
0.4%
정심원 2
 
0.4%
효도의집 2
 
0.4%
엘림요양원 2
 
0.4%
소망의집 2
 
0.4%
Other values (396) 414
92.2%
2024-03-14T11:09:16.725515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
308
 
11.1%
원 190
 
6.8%
양 117
 
4.2%
요 108
 
3.9%
집 105
 
3.8%
의 90
 
3.2%
인 57
 
2.1%
노 49
 
1.8%
홈 42
 
1.5%
사 40
 
1.4%
Other values (287) 1671
60.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2460
88.6%
Space Separator 308
 
11.1%
Decimal Number 7
 
0.3%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 190
 
7.7%
양 117
 
4.8%
요 108
 
4.4%
집 105
 
4.3%
의 90
 
3.7%
인 57
 
2.3%
노 49
 
2.0%
홈 42
 
1.7%
사 40
 
1.6%
마 35
 
1.4%
Other values (281) 1627
66.1%
Decimal Number
ValueCountFrequency (%)
1 4
57.1%
2 2
28.6%
3 1
 
14.3%
Space Separator
ValueCountFrequency (%)
308
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2460
88.6%
Common 317
 
11.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 190
 
7.7%
양 117
 
4.8%
요 108
 
4.4%
집 105
 
4.3%
의 90
 
3.7%
인 57
 
2.3%
노 49
 
2.0%
홈 42
 
1.7%
사 40
 
1.6%
마 35
 
1.4%
Other values (281) 1627
66.1%
Common
ValueCountFrequency (%)
308
97.2%
1 4
 
1.3%
2 2
 
0.6%
( 1
 
0.3%
3 1
 
0.3%
) 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2460
88.6%
ASCII 317
 
11.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
308
97.2%
1 4
 
1.3%
2 2
 
0.6%
( 1
 
0.3%
3 1
 
0.3%
) 1
 
0.3%
Hangul
ValueCountFrequency (%)
원 190
 
7.7%
양 117
 
4.8%
요 108
 
4.4%
집 105
 
4.3%
의 90
 
3.7%
인 57
 
2.3%
노 49
 
2.0%
홈 42
 
1.7%
사 40
 
1.6%
마 35
 
1.4%
Other values (281) 1627
66.1%

설치신고일
Text

Distinct387
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
2024-03-14T11:09:16.991661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length14
Mean length9.7995169
Min length6

Characters and Unicode

Total characters4057
Distinct characters15
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique364 ?
Unique (%)87.9%

Sample

1st row00.12.08
2nd row11.07.04
3rd row15.09.11
4th row02.11.21
5th row11.05.26
ValueCountFrequency (%)
2006.11.10 5
 
1.2%
07.03.09 3
 
0.7%
2010.03.01 3
 
0.7%
2009.12.29 3
 
0.7%
08.12.31 2
 
0.5%
2010.03.11 2
 
0.5%
11.04.28 2
 
0.5%
2010.03.16 2
 
0.5%
2016.02.01 2
 
0.5%
06.12.26 2
 
0.5%
Other values (374) 388
93.7%
2024-03-14T11:09:17.541247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 988
24.4%
. 834
20.6%
1 590
14.5%
2 493
12.2%
275
 
6.8%
6 152
 
3.7%
3 145
 
3.6%
8 138
 
3.4%
9 121
 
3.0%
7 118
 
2.9%
Other values (5) 203
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2944
72.6%
Other Punctuation 836
 
20.6%
Space Separator 275
 
6.8%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 988
33.6%
1 590
20.0%
2 493
16.7%
6 152
 
5.2%
3 145
 
4.9%
8 138
 
4.7%
9 121
 
4.1%
7 118
 
4.0%
5 108
 
3.7%
4 91
 
3.1%
Other Punctuation
ValueCountFrequency (%)
. 834
99.8%
, 2
 
0.2%
Space Separator
ValueCountFrequency (%)
275
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4057
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 988
24.4%
. 834
20.6%
1 590
14.5%
2 493
12.2%
275
 
6.8%
6 152
 
3.7%
3 145
 
3.6%
8 138
 
3.4%
9 121
 
3.0%
7 118
 
2.9%
Other values (5) 203
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4057
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 988
24.4%
. 834
20.6%
1 590
14.5%
2 493
12.2%
275
 
6.8%
6 152
 
3.7%
3 145
 
3.6%
8 138
 
3.4%
9 121
 
3.0%
7 118
 
2.9%
Other values (5) 203
 
5.0%

시설장
Text

Distinct388
Distinct (%)93.7%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
2024-03-14T11:09:17.853580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.0458937
Min length1

Characters and Unicode

Total characters1261
Distinct characters175
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

Unique365 ?
Unique (%)88.2%

Sample

1st row박헌수
2nd row최유영
3rd row-
4th row김미경
5th row김성은
ValueCountFrequency (%)
4
 
1.0%
정란희 3
 
0.7%
하정만 2
 
0.5%
정영순 2
 
0.5%
손정녀 2
 
0.5%
김은희 2
 
0.5%
원종훈 2
 
0.5%
강옥선 2
 
0.5%
김옥희 2
 
0.5%
추교인 2
 
0.5%
Other values (383) 396
94.5%
2024-03-14T11:09:18.258836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 90
 
7.1%
이 63
 
5.0%
정 50
 
4.0%
영 45
 
3.6%
희 35
 
2.8%
숙 31
 
2.5%
박 29
 
2.3%
순 29
 
2.3%
최 26
 
2.1%
성 25
 
2.0%
Other values (165) 838
66.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1233
97.8%
Space Separator 24
 
1.9%
Dash Punctuation 4
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 90
 
7.3%
이 63
 
5.1%
정 50
 
4.1%
영 45
 
3.6%
희 35
 
2.8%
숙 31
 
2.5%
박 29
 
2.4%
순 29
 
2.4%
최 26
 
2.1%
성 25
 
2.0%
Other values (163) 810
65.7%
Space Separator
ValueCountFrequency (%)
24
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1233
97.8%
Common 28
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 90
 
7.3%
이 63
 
5.1%
정 50
 
4.1%
영 45
 
3.6%
희 35
 
2.8%
숙 31
 
2.5%
박 29
 
2.4%
순 29
 
2.4%
최 26
 
2.1%
성 25
 
2.0%
Other values (163) 810
65.7%
Common
ValueCountFrequency (%)
24
85.7%
- 4
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1233
97.8%
ASCII 28
 
2.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 90
 
7.3%
이 63
 
5.1%
정 50
 
4.1%
영 45
 
3.6%
희 35
 
2.8%
숙 31
 
2.5%
박 29
 
2.4%
순 29
 
2.4%
최 26
 
2.1%
성 25
 
2.0%
Other values (163) 810
65.7%
ASCII
ValueCountFrequency (%)
24
85.7%
- 4
 
14.3%

도로명주소
Text

Distinct402
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
2024-03-14T11:09:18.570087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length31
Mean length17.722222
Min length9

Characters and Unicode

Total characters7337
Distinct characters276
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique390 ?
Unique (%)94.2%

Sample

1st row전주시 완산구 물왕멀2길 20-29
2nd row전주시 완산구 물왕멀2길 25
3rd row전주시 완산구 물왕멀2길 20-17
4th row전주시 덕진구 아중7길 9-5
5th row전주시 덕진구 인교9길 11 (401호)
ValueCountFrequency (%)
전주시 95
 
5.9%
익산시 81
 
5.0%
군산시 60
 
3.7%
완산구 60
 
3.7%
덕진구 35
 
2.2%
완주군 33
 
2.0%
김제시 28
 
1.7%
정읍시 26
 
1.6%
전북 20
 
1.2%
남원시 19
 
1.2%
Other values (834) 1154
71.6%
2024-03-14T11:09:18.968435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1220
 
16.6%
1 390
 
5.3%
시 316
 
4.3%
산 298
 
4.1%
2 234
 
3.2%
길 222
 
3.0%
3 185
 
2.5%
로 184
 
2.5%
- 182
 
2.5%
면 172
 
2.3%
Other values (266) 3934
53.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4054
55.3%
Decimal Number 1656
22.6%
Space Separator 1220
 
16.6%
Dash Punctuation 182
 
2.5%
Open Punctuation 85
 
1.2%
Close Punctuation 85
 
1.2%
Other Punctuation 52
 
0.7%
Uppercase Letter 2
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 316
 
7.8%
산 298
 
7.4%
길 222
 
5.5%
로 184
 
4.5%
면 172
 
4.2%
군 165
 
4.1%
주 144
 
3.6%
전 136
 
3.4%
동 130
 
3.2%
구 115
 
2.8%
Other values (244) 2172
53.6%
Decimal Number
ValueCountFrequency (%)
1 390
23.6%
2 234
14.1%
3 185
11.2%
4 143
 
8.6%
0 131
 
7.9%
5 129
 
7.8%
7 123
 
7.4%
6 114
 
6.9%
8 106
 
6.4%
9 101
 
6.1%
Other Punctuation
ValueCountFrequency (%)
, 23
44.2%
/ 12
23.1%
@ 10
19.2%
. 5
 
9.6%
? 2
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
B 1
50.0%
A 1
50.0%
Space Separator
ValueCountFrequency (%)
1220
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 182
100.0%
Open Punctuation
ValueCountFrequency (%)
( 85
100.0%
Close Punctuation
ValueCountFrequency (%)
) 85
100.0%
Lowercase Letter
ValueCountFrequency (%)
a 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4054
55.3%
Common 3280
44.7%
Latin 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 316
 
7.8%
산 298
 
7.4%
길 222
 
5.5%
로 184
 
4.5%
면 172
 
4.2%
군 165
 
4.1%
주 144
 
3.6%
전 136
 
3.4%
동 130
 
3.2%
구 115
 
2.8%
Other values (244) 2172
53.6%
Common
ValueCountFrequency (%)
1220
37.2%
1 390
 
11.9%
2 234
 
7.1%
3 185
 
5.6%
- 182
 
5.5%
4 143
 
4.4%
0 131
 
4.0%
5 129
 
3.9%
7 123
 
3.8%
6 114
 
3.5%
Other values (9) 429
 
13.1%
Latin
ValueCountFrequency (%)
a 1
33.3%
B 1
33.3%
A 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4054
55.3%
ASCII 3283
44.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1220
37.2%
1 390
 
11.9%
2 234
 
7.1%
3 185
 
5.6%
- 182
 
5.5%
4 143
 
4.4%
0 131
 
4.0%
5 129
 
3.9%
7 123
 
3.7%
6 114
 
3.5%
Other values (12) 432
 
13.2%
Hangul
ValueCountFrequency (%)
시 316
 
7.8%
산 298
 
7.4%
길 222
 
5.5%
로 184
 
4.5%
면 172
 
4.2%
군 165
 
4.1%
주 144
 
3.6%
전 136
 
3.4%
동 130
 
3.2%
구 115
 
2.8%
Other values (244) 2172
53.6%

종사자정원
Text

MISSING 

Distinct55
Distinct (%)13.7%
Missing13
Missing (%)3.1%
Memory size3.4 KiB
2024-03-14T11:09:19.139246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.5461347
Min length1

Characters and Unicode

Total characters620
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

Unique9 ?
Unique (%)2.2%

Sample

1st row10
2nd row1
3rd row7
4th row2
5th row34
ValueCountFrequency (%)
2 55
 
13.7%
4 24
 
6.0%
5 21
 
5.2%
6 21
 
5.2%
12 17
 
4.2%
1 17
 
4.2%
7 16
 
4.0%
8 15
 
3.7%
11 14
 
3.5%
9 12
 
3.0%
Other values (45) 189
47.1%
2024-03-14T11:09:19.394904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 143
23.1%
1 121
19.5%
4 68
11.0%
3 63
10.2%
6 47
 
7.6%
5 46
 
7.4%
7 32
 
5.2%
0 30
 
4.8%
9 27
 
4.4%
8 25
 
4.0%
Other values (2) 18
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 602
97.1%
Space Separator 12
 
1.9%
Dash Punctuation 6
 
1.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 143
23.8%
1 121
20.1%
4 68
11.3%
3 63
10.5%
6 47
 
7.8%
5 46
 
7.6%
7 32
 
5.3%
0 30
 
5.0%
9 27
 
4.5%
8 25
 
4.2%
Space Separator
ValueCountFrequency (%)
12
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 620
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 143
23.1%
1 121
19.5%
4 68
11.0%
3 63
10.2%
6 47
 
7.6%
5 46
 
7.4%
7 32
 
5.2%
0 30
 
4.8%
9 27
 
4.4%
8 25
 
4.0%
Other values (2) 18
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 620
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 143
23.1%
1 121
19.5%
4 68
11.0%
3 63
10.2%
6 47
 
7.6%
5 46
 
7.4%
7 32
 
5.2%
0 30
 
4.8%
9 27
 
4.4%
8 25
 
4.0%
Other values (2) 18
 
2.9%

종사자현원
Text

MISSING 

Distinct55
Distinct (%)13.7%
Missing13
Missing (%)3.1%
Memory size3.4 KiB
2024-03-14T11:09:19.639652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.5261845
Min length1

Characters and Unicode

Total characters612
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

Unique9 ?
Unique (%)2.2%

Sample

1st row10
2nd row1
3rd row7
4th row2
5th row33
ValueCountFrequency (%)
2 57
 
14.2%
6 23
 
5.7%
5 22
 
5.5%
4 22
 
5.5%
1 18
 
4.5%
11 16
 
4.0%
7 15
 
3.7%
8 15
 
3.7%
12 13
 
3.2%
9 12
 
3.0%
Other values (45) 188
46.9%
2024-03-14T11:09:19.936688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 141
23.0%
1 136
22.2%
4 59
9.6%
3 54
 
8.8%
5 49
 
8.0%
6 42
 
6.9%
8 33
 
5.4%
7 32
 
5.2%
9 30
 
4.9%
0 27
 
4.4%
Other values (2) 9
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 603
98.5%
Space Separator 6
 
1.0%
Dash Punctuation 3
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 141
23.4%
1 136
22.6%
4 59
9.8%
3 54
 
9.0%
5 49
 
8.1%
6 42
 
7.0%
8 33
 
5.5%
7 32
 
5.3%
9 30
 
5.0%
0 27
 
4.5%
Space Separator
ValueCountFrequency (%)
6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 612
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 141
23.0%
1 136
22.2%
4 59
9.6%
3 54
 
8.8%
5 49
 
8.0%
6 42
 
6.9%
8 33
 
5.4%
7 32
 
5.2%
9 30
 
4.9%
0 27
 
4.4%
Other values (2) 9
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 612
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 141
23.0%
1 136
22.2%
4 59
9.6%
3 54
 
8.8%
5 49
 
8.0%
6 42
 
6.9%
8 33
 
5.4%
7 32
 
5.2%
9 30
 
4.9%
0 27
 
4.4%
Other values (2) 9
 
1.5%

생활정원
Text

MISSING 

Distinct82
Distinct (%)20.2%
Missing9
Missing (%)2.2%
Memory size3.4 KiB
2024-03-14T11:09:20.126144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.6938272
Min length1

Characters and Unicode

Total characters686
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

Unique40 ?
Unique (%)9.9%

Sample

1st row26
2nd row4
3rd row4
4th row20
5th row4
ValueCountFrequency (%)
9 54
 
13.3%
7 47
 
11.6%
4 24
 
5.9%
29 21
 
5.2%
50 20
 
4.9%
80 15
 
3.7%
20 13
 
3.2%
16 12
 
3.0%
60 11
 
2.7%
28 10
 
2.5%
Other values (72) 178
44.0%
2024-03-14T11:09:20.418076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 108
15.7%
9 90
13.1%
2 84
12.2%
5 75
10.9%
1 70
10.2%
7 67
9.8%
4 64
9.3%
8 48
7.0%
6 46
6.7%
3 31
 
4.5%
Other values (2) 3
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 683
99.6%
Space Separator 2
 
0.3%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 108
15.8%
9 90
13.2%
2 84
12.3%
5 75
11.0%
1 70
10.2%
7 67
9.8%
4 64
9.4%
8 48
7.0%
6 46
6.7%
3 31
 
4.5%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 686
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 108
15.7%
9 90
13.1%
2 84
12.2%
5 75
10.9%
1 70
10.2%
7 67
9.8%
4 64
9.3%
8 48
7.0%
6 46
6.7%
3 31
 
4.5%
Other values (2) 3
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 686
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 108
15.7%
9 90
13.1%
2 84
12.2%
5 75
10.9%
1 70
10.2%
7 67
9.8%
4 64
9.3%
8 48
7.0%
6 46
6.7%
3 31
 
4.5%
Other values (2) 3
 
0.4%

생활현원
Text

MISSING 

Distinct90
Distinct (%)22.2%
Missing9
Missing (%)2.2%
Memory size3.4 KiB
2024-03-14T11:09:20.624285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.6938272
Min length1

Characters and Unicode

Total characters686
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

Unique28 ?
Unique (%)6.9%

Sample

1st row26
2nd row4
3rd row4
4th row21
5th row3
ValueCountFrequency (%)
4 37
 
9.1%
9 23
 
5.7%
5 22
 
5.4%
6 19
 
4.7%
7 17
 
4.2%
8 12
 
3.0%
26 10
 
2.5%
10 10
 
2.5%
28 10
 
2.5%
19 9
 
2.2%
Other values (80) 236
58.3%
2024-03-14T11:09:20.926337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 100
14.6%
4 99
14.4%
2 91
13.3%
6 69
10.1%
5 64
9.3%
9 55
8.0%
3 52
7.6%
7 49
7.1%
8 42
6.1%
0 41
6.0%
Other values (2) 24
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 662
96.5%
Space Separator 16
 
2.3%
Dash Punctuation 8
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 100
15.1%
4 99
15.0%
2 91
13.7%
6 69
10.4%
5 64
9.7%
9 55
8.3%
3 52
7.9%
7 49
7.4%
8 42
6.3%
0 41
6.2%
Space Separator
ValueCountFrequency (%)
16
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 686
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 100
14.6%
4 99
14.4%
2 91
13.3%
6 69
10.1%
5 64
9.3%
9 55
8.0%
3 52
7.6%
7 49
7.1%
8 42
6.1%
0 41
6.0%
Other values (2) 24
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 686
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 100
14.6%
4 99
14.4%
2 91
13.3%
6 69
10.1%
5 64
9.3%
9 55
8.0%
3 52
7.6%
7 49
7.1%
8 42
6.1%
0 41
6.0%
Other values (2) 24
 
3.5%

운영주체
Text

Distinct150
Distinct (%)36.2%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
2024-03-14T11:09:21.084945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length20
Mean length5.6111111
Min length2

Characters and Unicode

Total characters2323
Distinct characters175
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

Unique115 ?
Unique (%)27.8%

Sample

1st row마음건강복지재단
2nd row마음건강복지재단
3rd row마음건강복지재단
4th row인산의료재단
5th row인산의료재단
ValueCountFrequency (%)
개인 192
41.0%
사회복지법인 35
 
7.5%
삼동회 9
 
1.9%
사복)중도원 6
 
1.3%
한기장복지재단 6
 
1.3%
원광효도마을 5
 
1.1%
한 5
 
1.1%
울 5
 
1.1%
안 5
 
1.1%
인산의료재단 4
 
0.9%
Other values (146) 196
41.9%
2024-03-14T11:09:21.368862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
324
 
13.9%
인 258
 
11.1%
개 197
 
8.5%
복 171
 
7.4%
지 128
 
5.5%
사 114
 
4.9%
회 100
 
4.3%
단 77
 
3.3%
재 77
 
3.3%
) 67
 
2.9%
Other values (165) 810
34.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1919
82.6%
Space Separator 324
 
13.9%
Close Punctuation 67
 
2.9%
Open Punctuation 12
 
0.5%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 258
 
13.4%
개 197
 
10.3%
복 171
 
8.9%
지 128
 
6.7%
사 114
 
5.9%
회 100
 
5.2%
단 77
 
4.0%
재 77
 
4.0%
원 56
 
2.9%
법 50
 
2.6%
Other values (161) 691
36.0%
Space Separator
ValueCountFrequency (%)
324
100.0%
Close Punctuation
ValueCountFrequency (%)
) 67
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1919
82.6%
Common 404
 
17.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 258
 
13.4%
개 197
 
10.3%
복 171
 
8.9%
지 128
 
6.7%
사 114
 
5.9%
회 100
 
5.2%
단 77
 
4.0%
재 77
 
4.0%
원 56
 
2.9%
법 50
 
2.6%
Other values (161) 691
36.0%
Common
ValueCountFrequency (%)
324
80.2%
) 67
 
16.6%
( 12
 
3.0%
, 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1919
82.6%
ASCII 404
 
17.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
324
80.2%
) 67
 
16.6%
( 12
 
3.0%
, 1
 
0.2%
Hangul
ValueCountFrequency (%)
인 258
 
13.4%
개 197
 
10.3%
복 171
 
8.9%
지 128
 
6.7%
사 114
 
5.9%
회 100
 
5.2%
단 77
 
4.0%
재 77
 
4.0%
원 56
 
2.9%
법 50
 
2.6%
Other values (161) 691
36.0%

Interactions

2024-03-14T11:09:15.597707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T11:09:21.445426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시설구분종사자정원종사자현원생활정원생활현원
순번1.0000.7670.4890.3940.5920.000
시설구분0.7671.0000.7970.7770.9060.891
종사자정원0.4890.7971.0000.9980.9660.983
종사자현원0.3940.7770.9981.0000.9710.983
생활정원0.5920.9060.9660.9711.0000.989
생활현원0.0000.8910.9830.9830.9891.000
2024-03-14T11:09:21.534159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시설구분
순번1.0000.406
시설구분0.4061.000

Missing values

2024-03-14T11:09:15.688906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T11:09:15.806947image/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.
2024-03-14T11:09:15.927254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

순번시설구분시설명설치신고일시설장도로명주소종사자정원종사자현원생활정원생활현원운영주체
01사회복귀시설마음건강복지관00.12.08박헌수전주시 완산구 물왕멀2길 20-2910102626마음건강복지재단
12사회복귀시설마음건강회복홈11.07.04최유영전주시 완산구 물왕멀2길 251144마음건강복지재단
23사회복귀시설마음건강힐링홈15.09.11-전주시 완산구 물왕멀2길 20-17<NA><NA>44마음건강복지재단
34사회복귀시설아름다운세상02.11.21김미경전주시 덕진구 아중7길 9-5772021인산의료재단
45사회복귀시설아름다운집11.05.26김성은전주시 덕진구 인교9길 11 (401호)2243인산의료재단
56사회복귀시설꿈이있는집12.05.08-전라북도 전주시 덕진구 우아동2가 913-13<NA><NA>44인산의료재단
67사회복귀시설행복한집14.05.27-전주시 덕진구 인교로35-25 (501호)<NA><NA>44인산의료재단
78정신요양시설참사랑낙원85.01.11이계룡전주시 완산구 바람쐬는길152(대성동)3433176164참사랑복지회
89노숙인 요양시설전주사랑의집82.03.04변영미전주시 덕진구 동부대로 92614146059전주가톨릭사회복지회
910노숙인 자활시설일꾼쉼터98.12.07이승재전주시 완산구 덕적골2길 35-70442517대한성공회유지재단
순번시설구분시설명설치신고일시설장도로명주소종사자정원종사자현원생활정원생활현원운영주체
40413아동보호치료시설희망샘학교73.08.01김정강전라북도 고창군 무장면 학천로 267-16 전북소청원33257065아모스
4051노인요양시설송산효도마을2005.09.08하정만부안군 주산면 동정리 388-149499079한 울 안
4062노인요양시설은총의 집2006.09.29주혜숙부안군 상서면 부안로 1539-2118182324개인
4073노인요양시설해성요양원2016.02.15.이병협전라북도 부안군 행안면 월륜길 515151819개인
4084노인요양시설로댐실버케어2011.07.29유희성부안군 하서면 고인돌로 34730304041개인
4095노인요양시설부안군노인요양원2010.03.11송용기부안군 부안읍 봉두길 52772015사복)한국장로교복지재단
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