Overview

Dataset statistics

Number of variables15
Number of observations114
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.0 KiB
Average record size in memory135.2 B

Variable types

Text1
Numeric5
Categorical9

Dataset

Description국민연금공단 노후준비상담 연계서비스 영역별 현황(건강),(지사명,합계,치매관리(지차제),금연클리닉(지자체),구강보건(지자체),일반건강검진(지자체),노인 독감 예방접종(지자체),노인 실명 예방(지자체),정신건강 상담(지자체),독거노인 중증장애인 응급안전알림(지자체),체력인증프로그램(국민체육진흥공단),건강증진프로그램(국민건강보험공단),공공의료복지 연계서비스(지방의료원연합회),치매상담전화센터(중앙치매센터),직접입력)
Author국민연금공단
URLhttps://www.data.go.kr/data/15073370/fileData.do

Alerts

공공의료복지 연계서비스(지방의료원연합회) has constant value ""Constant
직접입력 has constant value ""Constant
치매관리(지차제) is highly overall correlated with 일반건강검진(지자체) and 1 other fieldsHigh correlation
치매상담전화센터(중앙치매센터) is highly overall correlated with 일반건강검진(지자체) and 1 other fieldsHigh correlation
합계 is highly overall correlated with 체력인증프로그램(국민체육진흥공단) and 1 other fieldsHigh correlation
일반건강검진(지자체) is highly overall correlated with 치매관리(지차제) and 3 other fieldsHigh correlation
체력인증프로그램(국민체육진흥공단) is highly overall correlated with 합계 and 1 other fieldsHigh correlation
건강증진프로그램(국민건강보험공단) is highly overall correlated with 합계 and 2 other fieldsHigh correlation
노인 독감 예방접종(지자체) is highly overall correlated with 일반건강검진(지자체) and 1 other fieldsHigh correlation
정신건강 상담(지자체) is highly overall correlated with 독거노인 중증장애인 응급안전알림(지자체)High correlation
독거노인 중증장애인 응급안전알림(지자체) is highly overall correlated with 일반건강검진(지자체) and 1 other fieldsHigh correlation
치매관리(지차제) is highly imbalanced (74.5%)Imbalance
구강보건(지자체) is highly imbalanced (60.2%)Imbalance
노인 독감 예방접종(지자체) is highly imbalanced (84.0%)Imbalance
노인 실명 예방(지자체) is highly imbalanced (80.9%)Imbalance
정신건강 상담(지자체) is highly imbalanced (76.4%)Imbalance
독거노인 중증장애인 응급안전알림(지자체) is highly imbalanced (87.4%)Imbalance
치매상담전화센터(중앙치매센터) is highly imbalanced (92.7%)Imbalance
지사명 has unique valuesUnique
합계 has 3 (2.6%) zerosZeros
금연클리닉(지자체) has 58 (50.9%) zerosZeros
일반건강검진(지자체) has 95 (83.3%) zerosZeros
체력인증프로그램(국민체육진흥공단) has 7 (6.1%) zerosZeros
건강증진프로그램(국민건강보험공단) has 9 (7.9%) zerosZeros

Reproduction

Analysis started2023-12-13 00:25:19.079489
Analysis finished2023-12-13 00:25:21.503463
Duration2.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지사명
Text

UNIQUE 

Distinct114
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-13T09:25:21.666321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length3.2280702
Min length2

Characters and Unicode

Total characters368
Distinct characters106
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique114 ?
Unique (%)100.0%

Sample

1st row종로중구
2nd row동대문중랑
3rd row성북강북
4th row도봉노원
5th row성동광진
ValueCountFrequency (%)
종로중구 1
 
0.9%
세종 1
 
0.9%
공주부여 1
 
0.9%
보령 1
 
0.9%
홍성 1
 
0.9%
천안 1
 
0.9%
서청주 1
 
0.9%
옥천 1
 
0.9%
충주 1
 
0.9%
동청주 1
 
0.9%
Other values (104) 104
91.2%
2023-12-13T09:25:21.975279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
부 21
 
5.7%
산 20
 
5.4%
주 20
 
5.4%
천 16
 
4.3%
동 13
 
3.5%
남 11
 
3.0%
대 11
 
3.0%
서 11
 
3.0%
양 10
 
2.7%
역 9
 
2.4%
Other values (96) 226
61.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 368
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 21
 
5.7%
산 20
 
5.4%
주 20
 
5.4%
천 16
 
4.3%
동 13
 
3.5%
남 11
 
3.0%
대 11
 
3.0%
서 11
 
3.0%
양 10
 
2.7%
역 9
 
2.4%
Other values (96) 226
61.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 368
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 21
 
5.7%
산 20
 
5.4%
주 20
 
5.4%
천 16
 
4.3%
동 13
 
3.5%
남 11
 
3.0%
대 11
 
3.0%
서 11
 
3.0%
양 10
 
2.7%
역 9
 
2.4%
Other values (96) 226
61.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 368
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
부 21
 
5.7%
산 20
 
5.4%
주 20
 
5.4%
천 16
 
4.3%
동 13
 
3.5%
남 11
 
3.0%
대 11
 
3.0%
서 11
 
3.0%
양 10
 
2.7%
역 9
 
2.4%
Other values (96) 226
61.4%

합계
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct95
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean316.09649
Minimum0
Maximum1448
Zeros3
Zeros (%)2.6%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T09:25:22.083033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q133
median183.5
Q3548
95-th percentile1057.05
Maximum1448
Range1448
Interquartile range (IQR)515

Descriptive statistics

Standard deviation356.49754
Coefficient of variation (CV)1.1278124
Kurtosis0.37703167
Mean316.09649
Median Absolute Deviation (MAD)175.5
Skewness1.1592782
Sum36035
Variance127090.5
MonotonicityNot monotonic
2023-12-13T09:25:22.190118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 5
 
4.4%
0 3
 
2.6%
2 3
 
2.6%
3 3
 
2.6%
5 2
 
1.8%
33 2
 
1.8%
287 2
 
1.8%
81 2
 
1.8%
548 2
 
1.8%
42 2
 
1.8%
Other values (85) 88
77.2%
ValueCountFrequency (%)
0 3
2.6%
1 5
4.4%
2 3
2.6%
3 3
2.6%
4 1
 
0.9%
5 2
 
1.8%
8 2
 
1.8%
10 1
 
0.9%
14 1
 
0.9%
16 1
 
0.9%
ValueCountFrequency (%)
1448 1
0.9%
1232 1
0.9%
1135 1
0.9%
1128 1
0.9%
1127 1
0.9%
1059 1
0.9%
1056 1
0.9%
1039 1
0.9%
943 1
0.9%
937 1
0.9%

치매관리(지차제)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
0
104 
1
 
8
4
 
1
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)1.8%

Sample

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

Common Values

ValueCountFrequency (%)
0 104
91.2%
1 8
 
7.0%
4 1
 
0.9%
3 1
 
0.9%

Length

2023-12-13T09:25:22.308645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:25:22.611232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 104
91.2%
1 8
 
7.0%
4 1
 
0.9%
3 1
 
0.9%

금연클리닉(지자체)
Real number (ℝ)

ZEROS 

Distinct15
Distinct (%)13.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3333333
Minimum0
Maximum51
Zeros58
Zeros (%)50.9%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T09:25:22.681076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile8.35
Maximum51
Range51
Interquartile range (IQR)2

Descriptive statistics

Standard deviation6.6007061
Coefficient of variation (CV)2.8288741
Kurtosis34.594018
Mean2.3333333
Median Absolute Deviation (MAD)0
Skewness5.5389649
Sum266
Variance43.569322
MonotonicityNot monotonic
2023-12-13T09:25:22.762947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 58
50.9%
1 22
 
19.3%
2 14
 
12.3%
3 6
 
5.3%
8 3
 
2.6%
5 2
 
1.8%
7 1
 
0.9%
24 1
 
0.9%
13 1
 
0.9%
6 1
 
0.9%
Other values (5) 5
 
4.4%
ValueCountFrequency (%)
0 58
50.9%
1 22
 
19.3%
2 14
 
12.3%
3 6
 
5.3%
4 1
 
0.9%
5 2
 
1.8%
6 1
 
0.9%
7 1
 
0.9%
8 3
 
2.6%
9 1
 
0.9%
ValueCountFrequency (%)
51 1
 
0.9%
39 1
 
0.9%
24 1
 
0.9%
13 1
 
0.9%
11 1
 
0.9%
9 1
 
0.9%
8 3
2.6%
7 1
 
0.9%
6 1
 
0.9%
5 2
1.8%

구강보건(지자체)
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
0
105 
1
 
9

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 105
92.1%
1 9
 
7.9%

Length

2023-12-13T09:25:22.849549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:25:22.916574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 105
92.1%
1 9
 
7.9%

일반건강검진(지자체)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct9
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.50877193
Minimum0
Maximum11
Zeros95
Zeros (%)83.3%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T09:25:22.980564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3.35
Maximum11
Range11
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.6522745
Coefficient of variation (CV)3.2475739
Kurtosis21.77717
Mean0.50877193
Median Absolute Deviation (MAD)0
Skewness4.4534065
Sum58
Variance2.7300109
MonotonicityNot monotonic
2023-12-13T09:25:23.075951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 95
83.3%
1 9
 
7.9%
2 3
 
2.6%
4 2
 
1.8%
11 1
 
0.9%
5 1
 
0.9%
7 1
 
0.9%
9 1
 
0.9%
3 1
 
0.9%
ValueCountFrequency (%)
0 95
83.3%
1 9
 
7.9%
2 3
 
2.6%
3 1
 
0.9%
4 2
 
1.8%
5 1
 
0.9%
7 1
 
0.9%
9 1
 
0.9%
11 1
 
0.9%
ValueCountFrequency (%)
11 1
 
0.9%
9 1
 
0.9%
7 1
 
0.9%
5 1
 
0.9%
4 2
 
1.8%
3 1
 
0.9%
2 3
 
2.6%
1 9
 
7.9%
0 95
83.3%

노인 독감 예방접종(지자체)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
0
109 
1
 
3
2
 
1
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)1.8%

Sample

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

Common Values

ValueCountFrequency (%)
0 109
95.6%
1 3
 
2.6%
2 1
 
0.9%
3 1
 
0.9%

Length

2023-12-13T09:25:23.185277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:25:23.272735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 109
95.6%
1 3
 
2.6%
2 1
 
0.9%
3 1
 
0.9%

노인 실명 예방(지자체)
Categorical

IMBALANCE 

Distinct3
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
0
109 
1
 
3
2
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 109
95.6%
1 3
 
2.6%
2 2
 
1.8%

Length

2023-12-13T09:25:23.351191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:25:23.420428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 109
95.6%
1 3
 
2.6%
2 2
 
1.8%

정신건강 상담(지자체)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
0
104 
1
 
7
25
 
1
4
 
1
3
 
1

Length

Max length2
Median length1
Mean length1.0087719
Min length1

Unique

Unique3 ?
Unique (%)2.6%

Sample

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

Common Values

ValueCountFrequency (%)
0 104
91.2%
1 7
 
6.1%
25 1
 
0.9%
4 1
 
0.9%
3 1
 
0.9%

Length

2023-12-13T09:25:23.496397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:25:23.575235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 104
91.2%
1 7
 
6.1%
25 1
 
0.9%
4 1
 
0.9%
3 1
 
0.9%

독거노인 중증장애인 응급안전알림(지자체)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
0
111 
2
 
2
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
0 111
97.4%
2 2
 
1.8%
1 1
 
0.9%

Length

2023-12-13T09:25:23.653205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:25:23.723750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 111
97.4%
2 2
 
1.8%
1 1
 
0.9%

체력인증프로그램(국민체육진흥공단)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct81
Distinct (%)71.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean177.4386
Minimum0
Maximum989
Zeros7
Zeros (%)6.1%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T09:25:23.806130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q19
median50
Q3247
95-th percentile587.7
Maximum989
Range989
Interquartile range (IQR)238

Descriptive statistics

Standard deviation233.64227
Coefficient of variation (CV)1.31675
Kurtosis1.3640378
Mean177.4386
Median Absolute Deviation (MAD)49
Skewness1.4638489
Sum20228
Variance54588.709
MonotonicityNot monotonic
2023-12-13T09:25:23.913006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 9
 
7.9%
0 7
 
6.1%
12 4
 
3.5%
9 3
 
2.6%
3 3
 
2.6%
2 3
 
2.6%
15 3
 
2.6%
189 2
 
1.8%
247 2
 
1.8%
43 2
 
1.8%
Other values (71) 76
66.7%
ValueCountFrequency (%)
0 7
6.1%
1 9
7.9%
2 3
 
2.6%
3 3
 
2.6%
5 1
 
0.9%
6 2
 
1.8%
7 2
 
1.8%
9 3
 
2.6%
11 1
 
0.9%
12 4
3.5%
ValueCountFrequency (%)
989 1
0.9%
847 1
0.9%
825 1
0.9%
816 1
0.9%
763 1
0.9%
602 1
0.9%
580 1
0.9%
574 1
0.9%
569 1
0.9%
565 1
0.9%

건강증진프로그램(국민건강보험공단)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct81
Distinct (%)71.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean135.04386
Minimum0
Maximum946
Zeros9
Zeros (%)7.9%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T09:25:24.012580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16
median45
Q3186
95-th percentile569.45
Maximum946
Range946
Interquartile range (IQR)180

Descriptive statistics

Standard deviation201.308
Coefficient of variation (CV)1.490686
Kurtosis5.1049452
Mean135.04386
Median Absolute Deviation (MAD)43.5
Skewness2.226615
Sum15395
Variance40524.91
MonotonicityNot monotonic
2023-12-13T09:25:24.132604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9
 
7.9%
1 6
 
5.3%
2 5
 
4.4%
4 4
 
3.5%
43 3
 
2.6%
3 3
 
2.6%
9 2
 
1.8%
20 2
 
1.8%
25 2
 
1.8%
15 2
 
1.8%
Other values (71) 76
66.7%
ValueCountFrequency (%)
0 9
7.9%
1 6
5.3%
2 5
4.4%
3 3
 
2.6%
4 4
3.5%
5 1
 
0.9%
6 2
 
1.8%
7 1
 
0.9%
9 2
 
1.8%
10 1
 
0.9%
ValueCountFrequency (%)
946 1
0.9%
904 1
0.9%
887 1
0.9%
753 1
0.9%
606 1
0.9%
574 1
0.9%
567 1
0.9%
476 1
0.9%
451 1
0.9%
426 1
0.9%

공공의료복지 연계서비스(지방의료원연합회)
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
0
114 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 114
100.0%

Length

2023-12-13T09:25:24.223759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:25:24.291324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 114
100.0%

치매상담전화센터(중앙치매센터)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
0
113 
5
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
0 113
99.1%
5 1
 
0.9%

Length

2023-12-13T09:25:24.365310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:25:24.439095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 113
99.1%
5 1
 
0.9%

직접입력
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
0
114 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 114
100.0%

Length

2023-12-13T09:25:24.525914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:25:24.594510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 114
100.0%

Interactions

2023-12-13T09:25:20.937412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:19.626854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:19.937636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:20.279588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:20.625356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:21.001397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:19.693296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:20.000484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:20.368183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:20.692485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:21.065817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:19.754020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:20.075673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:20.453204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:20.755708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:21.125336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:19.817989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:20.144475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:20.509907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:20.814499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:21.186646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:19.878190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:20.205870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:20.568661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:25:20.877552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T09:25:24.645408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
합계치매관리(지차제)금연클리닉(지자체)구강보건(지자체)일반건강검진(지자체)노인 독감 예방접종(지자체)노인 실명 예방(지자체)정신건강 상담(지자체)독거노인 중증장애인 응급안전알림(지자체)체력인증프로그램(국민체육진흥공단)건강증진프로그램(국민건강보험공단)치매상담전화센터(중앙치매센터)
합계1.0000.3430.7780.0000.0000.5030.0000.4880.0000.8800.7320.266
치매관리(지차제)0.3431.0000.0000.1100.9690.3770.0000.0990.0000.4920.0001.000
금연클리닉(지자체)0.7780.0001.0000.1290.3530.4250.4230.4450.5720.7880.4790.000
구강보건(지자체)0.0000.1100.1291.0000.4670.0000.2910.3910.0990.0000.0000.000
일반건강검진(지자체)0.0000.9690.3530.4671.0000.8570.4630.6270.7720.0000.1891.000
노인 독감 예방접종(지자체)0.5030.3770.4250.0000.8571.0000.1650.4170.2420.1420.7260.000
노인 실명 예방(지자체)0.0000.0000.4230.2910.4630.1651.0000.4960.8130.0000.5130.000
정신건강 상담(지자체)0.4880.0990.4450.3910.6270.4170.4961.0000.5890.4410.0000.000
독거노인 중증장애인 응급안전알림(지자체)0.0000.0000.5720.0990.7720.2420.8130.5891.0000.0000.0000.000
체력인증프로그램(국민체육진흥공단)0.8800.4920.7880.0000.0000.1420.0000.4410.0001.0000.5470.322
건강증진프로그램(국민건강보험공단)0.7320.0000.4790.0000.1890.7260.5130.0000.0000.5471.0000.000
치매상담전화센터(중앙치매센터)0.2661.0000.0000.0001.0000.0000.0000.0000.0000.3220.0001.000
2023-12-13T09:25:24.764683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구강보건(지자체)치매관리(지차제)치매상담전화센터(중앙치매센터)노인 실명 예방(지자체)노인 독감 예방접종(지자체)독거노인 중증장애인 응급안전알림(지자체)정신건강 상담(지자체)
구강보건(지자체)1.0000.0700.0000.4690.0000.1630.469
치매관리(지차제)0.0701.0000.9910.0000.1540.0000.078
치매상담전화센터(중앙치매센터)0.0000.9911.0000.0000.0000.0000.000
노인 실명 예방(지자체)0.4690.0000.0001.0000.1550.4810.427
노인 독감 예방접종(지자체)0.0000.1540.0000.1551.0000.2300.350
독거노인 중증장애인 응급안전알림(지자체)0.1630.0000.0000.4810.2301.0000.534
정신건강 상담(지자체)0.4690.0780.0000.4270.3500.5341.000
2023-12-13T09:25:24.859133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
합계금연클리닉(지자체)일반건강검진(지자체)체력인증프로그램(국민체육진흥공단)건강증진프로그램(국민건강보험공단)치매관리(지차제)구강보건(지자체)노인 독감 예방접종(지자체)노인 실명 예방(지자체)정신건강 상담(지자체)독거노인 중증장애인 응급안전알림(지자체)치매상담전화센터(중앙치매센터)
합계1.0000.3620.1860.9090.8600.2040.0000.3140.0000.2170.0000.195
금연클리닉(지자체)0.3621.0000.1760.3790.3040.0000.0890.2830.1900.3190.2800.000
일반건강검진(지자체)0.1860.1761.0000.2230.0770.7500.3410.5240.3240.4440.6680.973
체력인증프로그램(국민체육진흥공단)0.9090.3790.2231.0000.6320.3060.0000.0790.0000.1920.0000.237
건강증진프로그램(국민건강보험공단)0.8600.3040.0770.6321.0000.0000.0000.5510.2550.0000.0000.000
치매관리(지차제)0.2040.0000.7500.3060.0001.0000.0700.1540.0000.0780.0000.991
구강보건(지자체)0.0000.0890.3410.0000.0000.0701.0000.0000.4690.4690.1630.000
노인 독감 예방접종(지자체)0.3140.2830.5240.0790.5510.1540.0001.0000.1550.3500.2300.000
노인 실명 예방(지자체)0.0000.1900.3240.0000.2550.0000.4690.1551.0000.4270.4810.000
정신건강 상담(지자체)0.2170.3190.4440.1920.0000.0780.4690.3500.4271.0000.5340.000
독거노인 중증장애인 응급안전알림(지자체)0.0000.2800.6680.0000.0000.0000.1630.2300.4810.5341.0000.000
치매상담전화센터(중앙치매센터)0.1950.0000.9730.2370.0000.9910.0000.0000.0000.0000.0001.000

Missing values

2023-12-13T09:25:21.273544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T09:25:21.441043image/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

지사명합계치매관리(지차제)금연클리닉(지자체)구강보건(지자체)일반건강검진(지자체)노인 독감 예방접종(지자체)노인 실명 예방(지자체)정신건강 상담(지자체)독거노인 중증장애인 응급안전알림(지자체)체력인증프로그램(국민체육진흥공단)건강증진프로그램(국민건강보험공단)공공의료복지 연계서비스(지방의료원연합회)치매상담전화센터(중앙치매센터)직접입력
0종로중구1900000000172000
1동대문중랑3200200000022593000
2성북강북20000000011000
3도봉노원3300000100266000
4성동광진5900000000257000
5송파7851002200027753000
6강동하남70010000001950000
7서울남부지역본부65121400001443000
8서초61400000000370244000
9관악1600000000610000
지사명합계치매관리(지차제)금연클리닉(지자체)구강보건(지자체)일반건강검진(지자체)노인 독감 예방접종(지자체)노인 실명 예방(지자체)정신건강 상담(지자체)독거노인 중증장애인 응급안전알림(지자체)체력인증프로그램(국민체육진흥공단)건강증진프로그램(국민건강보험공단)공공의료복지 연계서비스(지방의료원연합회)치매상담전화센터(중앙치매센터)직접입력
104창원9301900100082594000
105김해밀양2320000000018943000
106통영2060100000017233000
107진주50000000023000
108마산48503000010163318000
109거창2112030000123000
110양산138000000007365000
111사천남해10000000010000
112제주73011000001259000
113서귀포3400000000727000