Overview

Dataset statistics

Number of variables16
Number of observations32
Missing cells4
Missing cells (%)0.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.3 KiB
Average record size in memory136.1 B

Variable types

Text9
Categorical3
Numeric3
DateTime1

Dataset

Description충청남도 치매센터 정보로 치매센터명, 치매센터위치, 소재지도로명, 소재지지번주소명, 건축물면적, 부대시설정보 등의 데이터를 제공합니다.
URLhttps://www.data.go.kr/data/15119738/fileData.do

Alerts

치매센터유형 has constant value ""Constant
소재지지번주소 has 1 (3.1%) missing valuesMissing
부대시설정보 has 2 (6.2%) missing valuesMissing
관리기관전화번호 has 1 (3.1%) missing valuesMissing
사회복지사인원수 has 2 (6.2%) zerosZeros

Reproduction

Analysis started2023-12-12 16:26:49.477557
Analysis finished2023-12-12 16:26:51.895200
Duration2.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

치매센터명
Text

Distinct21
Distinct (%)65.6%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-13T01:26:52.036349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length9
Mean length9
Min length6

Characters and Unicode

Total characters288
Distinct characters37
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

Unique10 ?
Unique (%)31.2%

Sample

1st row서북구치매안심센터
2nd row동남구치매안심센터
3rd row공주시치매안심센터
4th row금산군치매안심센터
5th row부여군보건소 치매안심센터
ValueCountFrequency (%)
치매안심센터 3
 
8.6%
서북구치매안심센터 2
 
5.7%
아산시치매안심센터 2
 
5.7%
금산군치매안심센터 2
 
5.7%
서산시치매안심센터 2
 
5.7%
보령시치매안심센터 2
 
5.7%
공주시치매안심센터 2
 
5.7%
논산시치매안심센터 2
 
5.7%
동남구치매안심센터 2
 
5.7%
청양군치매안심센터 2
 
5.7%
Other values (12) 14
40.0%
2023-12-13T01:26:52.370053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
안 33
11.5%
매 32
11.1%
센 32
11.1%
터 32
11.1%
치 31
10.8%
심 31
10.8%
시 14
 
4.9%
군 13
 
4.5%
산 10
 
3.5%
서 5
 
1.7%
Other values (27) 55
19.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 285
99.0%
Space Separator 3
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 33
11.6%
매 32
11.2%
센 32
11.2%
터 32
11.2%
치 31
10.9%
심 31
10.9%
시 14
 
4.9%
군 13
 
4.6%
산 10
 
3.5%
서 5
 
1.8%
Other values (26) 52
18.2%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 285
99.0%
Common 3
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
안 33
11.6%
매 32
11.2%
센 32
11.2%
터 32
11.2%
치 31
10.9%
심 31
10.9%
시 14
 
4.9%
군 13
 
4.6%
산 10
 
3.5%
서 5
 
1.8%
Other values (26) 52
18.2%
Common
ValueCountFrequency (%)
3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 285
99.0%
ASCII 3
 
1.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
안 33
11.6%
매 32
11.2%
센 32
11.2%
터 32
11.2%
치 31
10.9%
심 31
10.9%
시 14
 
4.9%
군 13
 
4.6%
산 10
 
3.5%
서 5
 
1.8%
Other values (26) 52
18.2%
ASCII
ValueCountFrequency (%)
3
100.0%

치매센터유형
Categorical

CONSTANT 

Distinct1
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size388.0 B
치매안심센터
32 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
치매안심센터 32
100.0%

Length

2023-12-13T01:26:52.501748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:26:52.601537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
치매안심센터 32
100.0%

소재지도로명주소
Text

Distinct26
Distinct (%)81.2%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-13T01:26:52.803859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length24
Mean length20.5
Min length15

Characters and Unicode

Total characters656
Distinct characters76
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

Unique20 ?
Unique (%)62.5%

Sample

1st row충청남도 천안시 서북구 서부8길 29
2nd row충청남도 천안시 동남구 버들로 40
3rd row충청남도 공주시 봉황로 123 공주시보건소 1층
4th row충청남도 금산군 금산읍 비범1길 5
5th row충청남도 부여군 부여읍 성왕로 205 부여군보건소 3층
ValueCountFrequency (%)
충청남도 32
 
20.5%
천안시 4
 
2.6%
54 3
 
1.9%
부여군 2
 
1.3%
공주시 2
 
1.3%
청양읍 2
 
1.3%
칠갑산로 2
 
1.3%
예산군 2
 
1.3%
금산군 2
 
1.3%
금산읍 2
 
1.3%
Other values (68) 103
66.0%
2023-12-13T01:26:53.150234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
124
18.9%
청 39
 
5.9%
남 34
 
5.2%
충 32
 
4.9%
도 32
 
4.9%
로 26
 
4.0%
1 21
 
3.2%
시 20
 
3.0%
산 20
 
3.0%
군 19
 
2.9%
Other values (66) 289
44.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 427
65.1%
Space Separator 124
 
18.9%
Decimal Number 97
 
14.8%
Dash Punctuation 4
 
0.6%
Close Punctuation 2
 
0.3%
Open Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 39
 
9.1%
남 34
 
8.0%
충 32
 
7.5%
도 32
 
7.5%
로 26
 
6.1%
시 20
 
4.7%
산 20
 
4.7%
군 19
 
4.4%
서 15
 
3.5%
읍 14
 
3.3%
Other values (52) 176
41.2%
Decimal Number
ValueCountFrequency (%)
1 21
21.6%
2 18
18.6%
5 13
13.4%
6 12
12.4%
0 9
9.3%
4 7
 
7.2%
8 6
 
6.2%
3 5
 
5.2%
9 3
 
3.1%
7 3
 
3.1%
Space Separator
ValueCountFrequency (%)
124
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 427
65.1%
Common 229
34.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 39
 
9.1%
남 34
 
8.0%
충 32
 
7.5%
도 32
 
7.5%
로 26
 
6.1%
시 20
 
4.7%
산 20
 
4.7%
군 19
 
4.4%
서 15
 
3.5%
읍 14
 
3.3%
Other values (52) 176
41.2%
Common
ValueCountFrequency (%)
124
54.1%
1 21
 
9.2%
2 18
 
7.9%
5 13
 
5.7%
6 12
 
5.2%
0 9
 
3.9%
4 7
 
3.1%
8 6
 
2.6%
3 5
 
2.2%
- 4
 
1.7%
Other values (4) 10
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 427
65.1%
ASCII 229
34.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
124
54.1%
1 21
 
9.2%
2 18
 
7.9%
5 13
 
5.7%
6 12
 
5.2%
0 9
 
3.9%
4 7
 
3.1%
8 6
 
2.6%
3 5
 
2.2%
- 4
 
1.7%
Other values (4) 10
 
4.4%
Hangul
ValueCountFrequency (%)
청 39
 
9.1%
남 34
 
8.0%
충 32
 
7.5%
도 32
 
7.5%
로 26
 
6.1%
시 20
 
4.7%
산 20
 
4.7%
군 19
 
4.4%
서 15
 
3.5%
읍 14
 
3.3%
Other values (52) 176
41.2%

소재지지번주소
Text

MISSING 

Distinct24
Distinct (%)77.4%
Missing1
Missing (%)3.1%
Memory size388.0 B
2023-12-13T01:26:53.361519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length30
Mean length20.387097
Min length15

Characters and Unicode

Total characters632
Distinct characters69
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

Unique17 ?
Unique (%)54.8%

Sample

1st row충청남도 천안시 서북구 성정동 684-1
2nd row충청남도 천안시 동남구 문화동 112-1
3rd row충청남도 공주시 교동 120 공주시보건소 1층
4th row충청남도 부여군 부여읍 구아리 136 부여군보건소 3층
5th row충청남도 서산시 예천동 496-1
ValueCountFrequency (%)
충청남도 31
 
20.9%
천안시 4
 
2.7%
예산리 2
 
1.4%
동남구 2
 
1.4%
문화동 2
 
1.4%
112-1 2
 
1.4%
공주시 2
 
1.4%
교동 2
 
1.4%
서산시 2
 
1.4%
부여읍 2
 
1.4%
Other values (60) 97
65.5%
2023-12-13T01:26:53.726609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
117
18.5%
청 35
 
5.5%
남 33
 
5.2%
도 32
 
5.1%
충 31
 
4.9%
1 30
 
4.7%
동 20
 
3.2%
시 19
 
3.0%
- 18
 
2.8%
군 16
 
2.5%
Other values (59) 281
44.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 379
60.0%
Space Separator 117
 
18.5%
Decimal Number 116
 
18.4%
Dash Punctuation 18
 
2.8%
Open Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 35
 
9.2%
남 33
 
8.7%
도 32
 
8.4%
충 31
 
8.2%
동 20
 
5.3%
시 19
 
5.0%
군 16
 
4.2%
읍 15
 
4.0%
산 14
 
3.7%
리 13
 
3.4%
Other values (45) 151
39.8%
Decimal Number
ValueCountFrequency (%)
1 30
25.9%
7 16
13.8%
4 12
 
10.3%
2 12
 
10.3%
0 11
 
9.5%
3 11
 
9.5%
6 11
 
9.5%
8 6
 
5.2%
9 4
 
3.4%
5 3
 
2.6%
Space Separator
ValueCountFrequency (%)
117
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 379
60.0%
Common 253
40.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 35
 
9.2%
남 33
 
8.7%
도 32
 
8.4%
충 31
 
8.2%
동 20
 
5.3%
시 19
 
5.0%
군 16
 
4.2%
읍 15
 
4.0%
산 14
 
3.7%
리 13
 
3.4%
Other values (45) 151
39.8%
Common
ValueCountFrequency (%)
117
46.2%
1 30
 
11.9%
- 18
 
7.1%
7 16
 
6.3%
4 12
 
4.7%
2 12
 
4.7%
0 11
 
4.3%
3 11
 
4.3%
6 11
 
4.3%
8 6
 
2.4%
Other values (4) 9
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 379
60.0%
ASCII 253
40.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
117
46.2%
1 30
 
11.9%
- 18
 
7.1%
7 16
 
6.3%
4 12
 
4.7%
2 12
 
4.7%
0 11
 
4.3%
3 11
 
4.3%
6 11
 
4.3%
8 6
 
2.4%
Other values (4) 9
 
3.6%
Hangul
ValueCountFrequency (%)
청 35
 
9.2%
남 33
 
8.7%
도 32
 
8.4%
충 31
 
8.2%
동 20
 
5.3%
시 19
 
5.0%
군 16
 
4.2%
읍 15
 
4.0%
산 14
 
3.7%
리 13
 
3.4%
Other values (45) 151
39.8%

건축물면적
Real number (ℝ)

Distinct25
Distinct (%)78.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean512.25656
Minimum147.6
Maximum995
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-13T01:26:53.869736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum147.6
5-th percentile189.75
Q1373.895
median490.195
Q3630
95-th percentile906
Maximum995
Range847.4
Interquartile range (IQR)256.105

Descriptive statistics

Standard deviation215.80432
Coefficient of variation (CV)0.42128171
Kurtosis-0.22394221
Mean512.25656
Median Absolute Deviation (MAD)125
Skewness0.54195442
Sum16392.21
Variance46571.505
MonotonicityNot monotonic
2023-12-13T01:26:53.992660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
906.0 2
 
6.2%
500.0 2
 
6.2%
350.0 2
 
6.2%
330.0 2
 
6.2%
427.55 2
 
6.2%
730.27 2
 
6.2%
498.0 2
 
6.2%
287.0 1
 
3.1%
165.0 1
 
3.1%
720.0 1
 
3.1%
Other values (15) 15
46.9%
ValueCountFrequency (%)
147.6 1
3.1%
165.0 1
3.1%
210.0 1
3.1%
287.0 1
3.1%
330.0 2
6.2%
350.0 2
6.2%
381.86 1
3.1%
396.0 1
3.1%
419.0 1
3.1%
419.38 1
3.1%
ValueCountFrequency (%)
995.0 1
3.1%
906.0 2
6.2%
831.0 1
3.1%
771.68 1
3.1%
730.27 2
6.2%
720.0 1
3.1%
600.0 1
3.1%
578.0 1
3.1%
540.0 1
3.1%
500.0 2
6.2%

부대시설정보
Text

MISSING 

Distinct29
Distinct (%)96.7%
Missing2
Missing (%)6.2%
Memory size388.0 B
2023-12-13T01:26:54.188509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length27
Mean length22.166667
Min length1

Characters and Unicode

Total characters665
Distinct characters53
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

Unique28 ?
Unique (%)93.3%

Sample

1st row사무실 1 프로그램실 1 상담실 1 검사실 1 쉼터 1
2nd row사무실 1 프로그램실 1 상담실 2 검사실 1쉼터1가족카페1
3rd row상담실 검진실 쉼터 가족카페
4th row사무실(1) 쉼터(1) 프로그램실(1)
5th row사무실(1)+검진실(1)+상담실(1)+프로그램실(3)+가족카페(1)+로비(1)+사랑방(1)
ValueCountFrequency (%)
상담실 17
12.7%
등 15
 
11.2%
검진실 14
 
10.4%
가족카페 9
 
6.7%
프로그램실 8
 
6.0%
1 7
 
5.2%
쉼터 7
 
5.2%
사무실 7
 
5.2%
교육실 6
 
4.5%
치매인지프로그램실 6
 
4.5%
Other values (34) 38
28.4%
2023-12-13T01:26:54.533280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
105
 
15.8%
실 88
 
13.2%
1 32
 
4.8%
담 22
 
3.3%
상 22
 
3.3%
로 22
 
3.3%
검 22
 
3.3%
프 21
 
3.2%
그 21
 
3.2%
램 21
 
3.2%
Other values (43) 289
43.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 468
70.4%
Space Separator 105
 
15.8%
Decimal Number 39
 
5.9%
Close Punctuation 20
 
3.0%
Open Punctuation 20
 
3.0%
Math Symbol 13
 
2.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
실 88
18.8%
담 22
 
4.7%
상 22
 
4.7%
로 22
 
4.7%
검 22
 
4.7%
프 21
 
4.5%
그 21
 
4.5%
램 21
 
4.5%
진 20
 
4.3%
페 19
 
4.1%
Other values (35) 190
40.6%
Decimal Number
ValueCountFrequency (%)
1 32
82.1%
2 4
 
10.3%
3 2
 
5.1%
5 1
 
2.6%
Space Separator
ValueCountFrequency (%)
105
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Math Symbol
ValueCountFrequency (%)
+ 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 468
70.4%
Common 197
29.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
실 88
18.8%
담 22
 
4.7%
상 22
 
4.7%
로 22
 
4.7%
검 22
 
4.7%
프 21
 
4.5%
그 21
 
4.5%
램 21
 
4.5%
진 20
 
4.3%
페 19
 
4.1%
Other values (35) 190
40.6%
Common
ValueCountFrequency (%)
105
53.3%
1 32
 
16.2%
) 20
 
10.2%
( 20
 
10.2%
+ 13
 
6.6%
2 4
 
2.0%
3 2
 
1.0%
5 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 468
70.4%
ASCII 197
29.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
105
53.3%
1 32
 
16.2%
) 20
 
10.2%
( 20
 
10.2%
+ 13
 
6.6%
2 4
 
2.0%
3 2
 
1.0%
5 1
 
0.5%
Hangul
ValueCountFrequency (%)
실 88
18.8%
담 22
 
4.7%
상 22
 
4.7%
로 22
 
4.7%
검 22
 
4.7%
프 21
 
4.5%
그 21
 
4.5%
램 21
 
4.5%
진 20
 
4.3%
페 19
 
4.1%
Other values (35) 190
40.6%

의사인원수
Categorical

Distinct3
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Memory size388.0 B
1
18 
0
9 
2
5 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row2
4th row0
5th row1

Common Values

ValueCountFrequency (%)
1 18
56.2%
0 9
28.1%
2 5
 
15.6%

Length

2023-12-13T01:26:54.686241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:26:54.817805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 18
56.2%
0 9
28.1%
2 5
 
15.6%

간호사인원수
Real number (ℝ)

Distinct14
Distinct (%)43.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.40625
Minimum3
Maximum18
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-13T01:26:54.924514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile3.55
Q16
median10
Q312.25
95-th percentile16.35
Maximum18
Range15
Interquartile range (IQR)6.25

Descriptive statistics

Standard deviation4.3467405
Coefficient of variation (CV)0.46211195
Kurtosis-0.86773467
Mean9.40625
Median Absolute Deviation (MAD)4
Skewness0.30123863
Sum301
Variance18.894153
MonotonicityNot monotonic
2023-12-13T01:26:55.049705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
10 5
15.6%
6 4
12.5%
4 3
9.4%
15 3
9.4%
7 2
 
6.2%
5 2
 
6.2%
11 2
 
6.2%
14 2
 
6.2%
3 2
 
6.2%
18 2
 
6.2%
Other values (4) 5
15.6%
ValueCountFrequency (%)
3 2
 
6.2%
4 3
9.4%
5 2
 
6.2%
6 4
12.5%
7 2
 
6.2%
8 1
 
3.1%
9 1
 
3.1%
10 5
15.6%
11 2
 
6.2%
12 2
 
6.2%
ValueCountFrequency (%)
18 2
 
6.2%
15 3
9.4%
14 2
 
6.2%
13 1
 
3.1%
12 2
 
6.2%
11 2
 
6.2%
10 5
15.6%
9 1
 
3.1%
8 1
 
3.1%
7 2
 
6.2%

사회복지사인원수
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)18.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3125
Minimum0
Maximum5
Zeros2
Zeros (%)6.2%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-13T01:26:55.166913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.55
Q12
median2
Q33
95-th percentile4.45
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.2556325
Coefficient of variation (CV)0.5429762
Kurtosis-0.0050567164
Mean2.3125
Median Absolute Deviation (MAD)1
Skewness0.40329784
Sum74
Variance1.5766129
MonotonicityNot monotonic
2023-12-13T01:26:55.260195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2 14
43.8%
3 5
 
15.6%
1 5
 
15.6%
4 4
 
12.5%
5 2
 
6.2%
0 2
 
6.2%
ValueCountFrequency (%)
0 2
 
6.2%
1 5
 
15.6%
2 14
43.8%
3 5
 
15.6%
4 4
 
12.5%
5 2
 
6.2%
ValueCountFrequency (%)
5 2
 
6.2%
4 4
 
12.5%
3 5
 
15.6%
2 14
43.8%
1 5
 
15.6%
0 2
 
6.2%

기타인원현황
Categorical

Distinct10
Distinct (%)31.2%
Missing0
Missing (%)0.0%
Memory size388.0 B
4
7 
2
6 
5
5 
3
5 
작업치료사(1)
2 
Other values (5)
7 

Length

Max length21
Median length1
Mean length2.0625
Min length1

Unique

Unique3 ?
Unique (%)9.4%

Sample

1st row4
2nd row5
3rd row작업치료사1 임상심리사2 담당 공무원2
4th row5
5th row작업치료사(1)

Common Values

ValueCountFrequency (%)
4 7
21.9%
2 6
18.8%
5 5
15.6%
3 5
15.6%
작업치료사(1) 2
 
6.2%
6 2
 
6.2%
7 2
 
6.2%
작업치료사1 임상심리사2 담당 공무원2 1
 
3.1%
8 1
 
3.1%
1 1
 
3.1%

Length

2023-12-13T01:26:55.369116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:26:55.473770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4 7
20.0%
2 6
17.1%
5 5
14.3%
3 5
14.3%
작업치료사(1 2
 
5.7%
6 2
 
5.7%
7 2
 
5.7%
작업치료사1 1
 
2.9%
임상심리사2 1
 
2.9%
담당 1
 
2.9%
Other values (3) 3
8.6%

운영기관명
Text

Distinct20
Distinct (%)62.5%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-13T01:26:55.634089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length6
Mean length6.28125
Min length3

Characters and Unicode

Total characters201
Distinct characters37
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

Unique8 ?
Unique (%)25.0%

Sample

1st row서북구보건소
2nd row동남구보건소
3rd row공주시보건소
4th row금산군보건소
5th row충청남도 부여군보건소
ValueCountFrequency (%)
서북구보건소 2
 
5.7%
서천군보건소 2
 
5.7%
충청남도 2
 
5.7%
부여군보건소 2
 
5.7%
예산군보건소 2
 
5.7%
계룡시보건소 2
 
5.7%
청양군보건의료원 2
 
5.7%
홍성군보건소 2
 
5.7%
동남구보건소 2
 
5.7%
금산군보건소 2
 
5.7%
Other values (11) 15
42.9%
2023-12-13T01:26:55.897177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
보 32
15.9%
건 30
14.9%
소 28
13.9%
시 14
 
7.0%
군 14
 
7.0%
산 10
 
5.0%
서 6
 
3.0%
청 4
 
2.0%
남 4
 
2.0%
구 4
 
2.0%
Other values (27) 55
27.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 198
98.5%
Space Separator 3
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
보 32
16.2%
건 30
15.2%
소 28
14.1%
시 14
 
7.1%
군 14
 
7.1%
산 10
 
5.1%
서 6
 
3.0%
청 4
 
2.0%
남 4
 
2.0%
구 4
 
2.0%
Other values (26) 52
26.3%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 198
98.5%
Common 3
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
보 32
16.2%
건 30
15.2%
소 28
14.1%
시 14
 
7.1%
군 14
 
7.1%
산 10
 
5.1%
서 6
 
3.0%
청 4
 
2.0%
남 4
 
2.0%
구 4
 
2.0%
Other values (26) 52
26.3%
Common
ValueCountFrequency (%)
3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 198
98.5%
ASCII 3
 
1.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
보 32
16.2%
건 30
15.2%
소 28
14.1%
시 14
 
7.1%
군 14
 
7.1%
산 10
 
5.1%
서 6
 
3.0%
청 4
 
2.0%
남 4
 
2.0%
구 4
 
2.0%
Other values (26) 52
26.3%
ASCII
ValueCountFrequency (%)
3
100.0%

운영기관전화번호
Text

Distinct30
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-13T01:26:56.064403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.03125
Min length12

Characters and Unicode

Total characters385
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

Unique28 ?
Unique (%)87.5%

Sample

1st row041-574-0994
2nd row041-521-3340
3rd row041-840-8811
4th row041-750-4173
5th row041-830-8742
ValueCountFrequency (%)
041-630-9076 2
 
6.2%
042-840-3681 2
 
6.2%
041-574-0994 1
 
3.1%
041-830-8727 1
 
3.1%
041-537-3474 1
 
3.1%
041-746-6921 1
 
3.1%
041-950-6741 1
 
3.1%
041-940-4500 1
 
3.1%
041-671-5228 1
 
3.1%
041-930-0937 1
 
3.1%
Other values (20) 20
62.5%
2023-12-13T01:26:56.337596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 64
16.6%
0 63
16.4%
4 54
14.0%
1 52
13.5%
6 27
7.0%
3 27
7.0%
7 25
 
6.5%
5 21
 
5.5%
2 18
 
4.7%
9 17
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 321
83.4%
Dash Punctuation 64
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 63
19.6%
4 54
16.8%
1 52
16.2%
6 27
8.4%
3 27
8.4%
7 25
 
7.8%
5 21
 
6.5%
2 18
 
5.6%
9 17
 
5.3%
8 17
 
5.3%
Dash Punctuation
ValueCountFrequency (%)
- 64
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 385
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 64
16.6%
0 63
16.4%
4 54
14.0%
1 52
13.5%
6 27
7.0%
3 27
7.0%
7 25
 
6.5%
5 21
 
5.5%
2 18
 
4.7%
9 17
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 385
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 64
16.6%
0 63
16.4%
4 54
14.0%
1 52
13.5%
6 27
7.0%
3 27
7.0%
7 25
 
6.5%
5 21
 
5.5%
2 18
 
4.7%
9 17
 
4.4%

주요치매관리프로그램소개
Text

Distinct17
Distinct (%)53.1%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-13T01:26:56.509386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length340
Median length218
Mean length46.46875
Min length4

Characters and Unicode

Total characters1487
Distinct characters179
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

Unique15 ?
Unique (%)46.9%

Sample

1st row치매조기검진 인지재활 쉼터 가족지원사업 등
2nd row치매조기검진 인지재활 쉼터 가족지원사업 등
3rd row1. 치매조기검진2. 치매노인 지문등록3. 치매치료관리비 지원4. 조호물품(위생물품) 제공5. 치매예방교실6. 인지강화교실7. 인지재활프로그램8. 기타 인지자극 프로그램9. 헤아림 가족교실10. 치매가족 힐링 프로그램11. 치매공공후견 사업12. 치매어르신주간보호소 운영(위탁)13. 치매안심마을 운영14. 치매인식 개선 및 교육 홍보 사업15. 배회가능 어르신 인식표 발급 및 GPS 운영
4th row치매상담 등록관리 조기검진 인지재활프로그램 치매치료관리비지원 치매주간보호센터 운영 등
5th row치매노인 등록 및 관리 치매노인 및 보호자에 대한 상담 지원 치매조기검진 치매치료관리비 지원 및 치매환자 사례관리 치매인지재활 프로그램 치매가족교실 및 자조모임 등
ValueCountFrequency (%)
치매조기검진 23
 
8.7%
치매인식개선 17
 
6.4%
지역사회역량강화 16
 
6.0%
예방등록관리 16
 
6.0%
및 10
 
3.8%
등 8
 
3.0%
6
 
2.3%
치매환자 5
 
1.9%
운영 4
 
1.5%
지원 4
 
1.5%
Other values (131) 156
58.9%
2023-12-13T01:26:56.786759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
234
 
15.7%
치 99
 
6.7%
매 86
 
5.8%
지 44
 
3.0%
인 36
 
2.4%
조 35
 
2.4%
역 34
 
2.3%
등 34
 
2.3%
기 30
 
2.0%
리 30
 
2.0%
Other values (169) 825
55.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1179
79.3%
Space Separator 234
 
15.7%
Decimal Number 33
 
2.2%
Other Punctuation 27
 
1.8%
Close Punctuation 4
 
0.3%
Open Punctuation 4
 
0.3%
Math Symbol 3
 
0.2%
Uppercase Letter 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
치 99
 
8.4%
매 86
 
7.3%
지 44
 
3.7%
인 36
 
3.1%
조 35
 
3.0%
역 34
 
2.9%
등 34
 
2.9%
기 30
 
2.5%
리 30
 
2.5%
검 28
 
2.4%
Other values (150) 723
61.3%
Decimal Number
ValueCountFrequency (%)
1 10
30.3%
3 4
 
12.1%
2 4
 
12.1%
6 3
 
9.1%
0 3
 
9.1%
5 3
 
9.1%
4 3
 
9.1%
8 1
 
3.0%
7 1
 
3.0%
9 1
 
3.0%
Uppercase Letter
ValueCountFrequency (%)
S 1
33.3%
P 1
33.3%
G 1
33.3%
Other Punctuation
ValueCountFrequency (%)
. 21
77.8%
: 6
 
22.2%
Space Separator
ValueCountFrequency (%)
234
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Math Symbol
ValueCountFrequency (%)
+ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1179
79.3%
Common 305
 
20.5%
Latin 3
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
치 99
 
8.4%
매 86
 
7.3%
지 44
 
3.7%
인 36
 
3.1%
조 35
 
3.0%
역 34
 
2.9%
등 34
 
2.9%
기 30
 
2.5%
리 30
 
2.5%
검 28
 
2.4%
Other values (150) 723
61.3%
Common
ValueCountFrequency (%)
234
76.7%
. 21
 
6.9%
1 10
 
3.3%
: 6
 
2.0%
3 4
 
1.3%
2 4
 
1.3%
) 4
 
1.3%
( 4
 
1.3%
6 3
 
1.0%
+ 3
 
1.0%
Other values (6) 12
 
3.9%
Latin
ValueCountFrequency (%)
S 1
33.3%
P 1
33.3%
G 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1179
79.3%
ASCII 308
 
20.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
234
76.0%
. 21
 
6.8%
1 10
 
3.2%
: 6
 
1.9%
3 4
 
1.3%
2 4
 
1.3%
) 4
 
1.3%
( 4
 
1.3%
6 3
 
1.0%
+ 3
 
1.0%
Other values (9) 15
 
4.9%
Hangul
ValueCountFrequency (%)
치 99
 
8.4%
매 86
 
7.3%
지 44
 
3.7%
인 36
 
3.1%
조 35
 
3.0%
역 34
 
2.9%
등 34
 
2.9%
기 30
 
2.5%
리 30
 
2.5%
검 28
 
2.4%
Other values (150) 723
61.3%

관리기관전화번호
Text

MISSING 

Distinct25
Distinct (%)80.6%
Missing1
Missing (%)3.1%
Memory size388.0 B
2023-12-13T01:26:56.940668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters372
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

Unique21 ?
Unique (%)67.7%

Sample

1st row041-521-5928
2nd row041-521-3340
3rd row041-840-8527
4th row041-750-4171
5th row041-830-8600
ValueCountFrequency (%)
041-000-0000 4
 
12.9%
041-661-6598 2
 
6.5%
041-750-4171 2
 
6.5%
041-830-8600 2
 
6.5%
041-360-6075 1
 
3.2%
041-339-7114 1
 
3.2%
041-339-6140 1
 
3.2%
041-537-3474 1
 
3.2%
041-746-6939 1
 
3.2%
041-950-4055 1
 
3.2%
Other values (15) 15
48.4%
2023-12-13T01:26:57.198769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 86
23.1%
- 62
16.7%
1 49
13.2%
4 47
12.6%
6 25
 
6.7%
5 22
 
5.9%
3 20
 
5.4%
7 18
 
4.8%
9 17
 
4.6%
8 15
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 310
83.3%
Dash Punctuation 62
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 86
27.7%
1 49
15.8%
4 47
15.2%
6 25
 
8.1%
5 22
 
7.1%
3 20
 
6.5%
7 18
 
5.8%
9 17
 
5.5%
8 15
 
4.8%
2 11
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 62
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 372
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 86
23.1%
- 62
16.7%
1 49
13.2%
4 47
12.6%
6 25
 
6.7%
5 22
 
5.9%
3 20
 
5.4%
7 18
 
4.8%
9 17
 
4.6%
8 15
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 372
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 86
23.1%
- 62
16.7%
1 49
13.2%
4 47
12.6%
6 25
 
6.7%
5 22
 
5.9%
3 20
 
5.4%
7 18
 
4.8%
9 17
 
4.6%
8 15
 
4.0%

관리기관명
Text

Distinct30
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-13T01:26:57.369450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length5.5
Min length3

Characters and Unicode

Total characters176
Distinct characters45
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

Unique28 ?
Unique (%)87.5%

Sample

1st row충청남도 천안시청
2nd row충청남도 천안시청
3rd row공주시보건소
4th row충청남도청
5th row충청남도 부여군보건소
ValueCountFrequency (%)
충청남도 5
 
12.2%
아산시 2
 
4.9%
천안시청 2
 
4.9%
서산시 2
 
4.9%
태안군 2
 
4.9%
천안시 2
 
4.9%
보령시보건소 1
 
2.4%
예산군 1
 
2.4%
홍성군치매안심센터 1
 
2.4%
당진시보건소 1
 
2.4%
Other values (22) 22
53.7%
2023-12-13T01:26:57.687836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 18
 
10.2%
청 13
 
7.4%
군 12
 
6.8%
보 11
 
6.2%
9
 
5.1%
건 9
 
5.1%
산 8
 
4.5%
남 7
 
4.0%
소 7
 
4.0%
안 7
 
4.0%
Other values (35) 75
42.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 167
94.9%
Space Separator 9
 
5.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 18
 
10.8%
청 13
 
7.8%
군 12
 
7.2%
보 11
 
6.6%
건 9
 
5.4%
산 8
 
4.8%
남 7
 
4.2%
소 7
 
4.2%
안 7
 
4.2%
충 6
 
3.6%
Other values (34) 69
41.3%
Space Separator
ValueCountFrequency (%)
9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 167
94.9%
Common 9
 
5.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 18
 
10.8%
청 13
 
7.8%
군 12
 
7.2%
보 11
 
6.6%
건 9
 
5.4%
산 8
 
4.8%
남 7
 
4.2%
소 7
 
4.2%
안 7
 
4.2%
충 6
 
3.6%
Other values (34) 69
41.3%
Common
ValueCountFrequency (%)
9
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 167
94.9%
ASCII 9
 
5.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 18
 
10.8%
청 13
 
7.8%
군 12
 
7.2%
보 11
 
6.6%
건 9
 
5.4%
산 8
 
4.8%
남 7
 
4.2%
소 7
 
4.2%
안 7
 
4.2%
충 6
 
3.6%
Other values (34) 69
41.3%
ASCII
ValueCountFrequency (%)
9
100.0%

데이터기준일자
Date

Distinct16
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
Minimum2019-09-25 00:00:00
Maximum2021-02-15 00:00:00
2023-12-13T01:26:57.796072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:26:57.892759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)

Interactions

2023-12-13T01:26:50.921189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:26:50.336178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:26:50.598899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:26:51.268931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:26:50.410467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:26:50.694679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:26:51.347719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:26:50.511561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:26:50.819052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:26:57.972911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
치매센터명소재지도로명주소소재지지번주소건축물면적부대시설정보의사인원수간호사인원수사회복지사인원수기타인원현황운영기관명운영기관전화번호주요치매관리프로그램소개관리기관전화번호관리기관명데이터기준일자
치매센터명1.0000.9290.9530.8470.9440.0000.5980.9870.5700.9730.0000.4860.9540.9890.592
소재지도로명주소0.9291.0000.9820.8780.9610.0000.9330.9870.9010.9681.0000.7210.2530.9820.499
소재지지번주소0.9530.9821.0000.9280.9440.6640.9110.9990.9350.9760.9780.0000.8660.9780.000
건축물면적0.8470.8780.9281.0001.0000.5260.0000.6230.0000.9500.9630.0000.9250.0000.000
부대시설정보0.9440.9610.9441.0001.0001.0000.0001.0000.5320.9531.0001.0000.9820.9711.000
의사인원수0.0000.0000.6640.5261.0001.0000.6770.4820.0000.0000.9350.7940.8420.9350.805
간호사인원수0.5980.9330.9110.0000.0000.6771.0000.4970.5420.9221.0000.0000.5690.9350.000
사회복지사인원수0.9870.9870.9990.6231.0000.4820.4971.0000.0000.9921.0000.5010.9450.9620.374
기타인원현황0.5700.9010.9350.0000.5320.0000.5420.0001.0000.8590.9960.8000.7030.9730.796
운영기관명0.9730.9680.9760.9500.9530.0000.9220.9920.8591.0001.0000.4260.9000.8610.528
운영기관전화번호0.0001.0000.9780.9631.0000.9351.0001.0000.9961.0001.0000.9110.9530.9690.887
주요치매관리프로그램소개0.4860.7210.0000.0001.0000.7940.0000.5010.8000.4260.9111.0000.9340.9791.000
관리기관전화번호0.9540.2530.8660.9250.9820.8420.5690.9450.7030.9000.9530.9341.0000.9380.957
관리기관명0.9890.9820.9780.0000.9710.9350.9350.9620.9730.8610.9690.9790.9381.0000.976
데이터기준일자0.5920.4990.0000.0001.0000.8050.0000.3740.7960.5280.8871.0000.9570.9761.000
2023-12-13T01:26:58.134443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
의사인원수기타인원현황
의사인원수1.0000.000
기타인원현황0.0001.000
2023-12-13T01:26:58.228829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
건축물면적간호사인원수사회복지사인원수의사인원수기타인원현황
건축물면적1.0000.391-0.1550.2510.000
간호사인원수0.3911.000-0.2570.3030.278
사회복지사인원수-0.155-0.2571.0000.2030.000
의사인원수0.2510.3030.2031.0000.000
기타인원현황0.0000.2780.0000.0001.000

Missing values

2023-12-13T01:26:51.460920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:26:51.674991image/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.
2023-12-13T01:26:51.825542image/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

치매센터명치매센터유형소재지도로명주소소재지지번주소건축물면적부대시설정보의사인원수간호사인원수사회복지사인원수기타인원현황운영기관명운영기관전화번호주요치매관리프로그램소개관리기관전화번호관리기관명데이터기준일자
0서북구치매안심센터치매안심센터충청남도 천안시 서북구 서부8길 29충청남도 천안시 서북구 성정동 684-1287.0사무실 1 프로그램실 1 상담실 1 검사실 1 쉼터 10434서북구보건소041-574-0994치매조기검진 인지재활 쉼터 가족지원사업 등041-521-5928충청남도 천안시청2020-12-08
1동남구치매안심센터치매안심센터충청남도 천안시 동남구 버들로 40충청남도 천안시 동남구 문화동 112-1578.0사무실 1 프로그램실 1 상담실 2 검사실 1쉼터1가족카페10715동남구보건소041-521-3340치매조기검진 인지재활 쉼터 가족지원사업 등041-521-3340충청남도 천안시청2020-12-08
2공주시치매안심센터치매안심센터충청남도 공주시 봉황로 123 공주시보건소 1층충청남도 공주시 교동 120 공주시보건소 1층210.0상담실 검진실 쉼터 가족카페2102작업치료사1 임상심리사2 담당 공무원2공주시보건소041-840-88111. 치매조기검진2. 치매노인 지문등록3. 치매치료관리비 지원4. 조호물품(위생물품) 제공5. 치매예방교실6. 인지강화교실7. 인지재활프로그램8. 기타 인지자극 프로그램9. 헤아림 가족교실10. 치매가족 힐링 프로그램11. 치매공공후견 사업12. 치매어르신주간보호소 운영(위탁)13. 치매안심마을 운영14. 치매인식 개선 및 교육 홍보 사업15. 배회가능 어르신 인식표 발급 및 GPS 운영041-840-8527공주시보건소2019-09-25
3금산군치매안심센터치매안심센터충청남도 금산군 금산읍 비범1길 5<NA>419.38사무실(1) 쉼터(1) 프로그램실(1)01055금산군보건소041-750-4173치매상담 등록관리 조기검진 인지재활프로그램 치매치료관리비지원 치매주간보호센터 운영 등041-750-4171충청남도청2020-12-09
4부여군보건소 치매안심센터치매안심센터충청남도 부여군 부여읍 성왕로 205 부여군보건소 3층충청남도 부여군 부여읍 구아리 136 부여군보건소 3층500.0사무실(1)+검진실(1)+상담실(1)+프로그램실(3)+가족카페(1)+로비(1)+사랑방(1)173작업치료사(1)충청남도 부여군보건소041-830-8742치매노인 등록 및 관리 치매노인 및 보호자에 대한 상담 지원 치매조기검진 치매치료관리비 지원 및 치매환자 사례관리 치매인지재활 프로그램 치매가족교실 및 자조모임 등041-830-8600충청남도 부여군보건소2020-06-30
5서산시치매안심센터치매안심센터충청남도 서산시 호수공원6로 6 서산시보건소(예천동)충청남도 서산시 예천동 496-1350.0사무실(1)+쉼터(1)+검진실(1)+상담실(2)+가족까페(1)0542서산시보건소041-661-81001. 치매조기검진 : 치매를 조기에 발견하여 등록 및 관리 2. 치매쉼터프로그램 : 경도치매환자를 대상으로 원예치료 운동치료 수공예치료 인지치료 등을 제공하여 치매환자의 잔존기능을 향상시킴 3. 치매예방프로그램 : 60세 이상 어르신들에게 치매예방수칙 웃음치료 운동치료 등 제공4. 치매환자가족교실 및 자조모임 : 치매에 대해 올바르게 배우고 치매환자가족끼리 돌봄요령 등을 공유5. 치매환자 맞춤형 사례관리 : 등록된 치매환자의 욕구를 파악하여 서비스 제공 및 지역사회자원 연계 6. 치매치료관리비 지원 : 치매치료제를 복용 중인 치매환자에게 최대 월 3만원까지 투약비 지원(전국가구 평균소득의 120이하)041-661-6598충청남도 서산시 보건소2020-12-11
6동남구치매안심센터치매안심센터충청남도 천안시 동남구 버들로 40 7층충청남도 천안시 동남구 문화동 112-1 7층540.0치매인지프로그램실 교육실 검진실 상담실 등11124동남구보건소041-521-5008치매조기검진 예방등록관리 치매인식개선 지역사회역량강화041-000-0000천안시 동남구2021-02-15
7서북구치매안심센터치매안심센터충청남도 천안시 서북구 동서대로 111(금당빌딩 2층)충청남도 천안시 서북구 성정동 1268 (금당빌딩 2층)147.6사무실1 상담실1 가족카페1 프로그램실1 쉼터11636서북구보건소041-521-5987치매조기검진 예방등록관리 치매인식개선 지역사회역량강화041-521-5987천안시 서북구2021-02-15
8공주시치매안심센터치매안심센터충청남도 공주시 옛군청뒷길 8충청남도 공주시 교동 131466.66프로그램실 교육실 검진실 상담실 등11528공주시보건소041-5840-2632치매조기검진 예방등록관리 치매인식개선 지역사회역량강화041-000-0000공주시2021-02-15
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