Overview

Dataset statistics

Number of variables12
Number of observations41
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.4 KiB
Average record size in memory109.2 B

Variable types

Text1
Numeric10
DateTime1

Dataset

Description제주도내 읍면동별 성인병 건강실태 분석 관련 비만율, 흡연율, 스트레스 인지율 등 정보 제공
Author제주특별자치도
URLhttps://www.data.go.kr/data/15045340/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
30세이상 고혈압 평생의사진단 경험률 is highly overall correlated with 30세이상 당뇨병 평생의사진단 경험률 and 1 other fieldsHigh correlation
30세이상 당뇨병 평생의사진단 경험률 is highly overall correlated with 30세이상 고혈압 평생의사진단 경험률High correlation
좋지 않은 주관적 건강수준 인지율 is highly overall correlated with 30세이상 고혈압 평생의사진단 경험률High correlation
중등도 이상 운동 미실천율 is highly overall correlated with 아침 결식률High correlation
아침 결식률 is highly overall correlated with 중등도 이상 운동 미실천율High correlation
읍면동 has unique valuesUnique
좋지 않은 주관적 건강수준 인지율 has unique valuesUnique
흡연율 has unique valuesUnique
고위험 음주율 has unique valuesUnique
아침 결식률 has unique valuesUnique
우울감 경험률 has unique valuesUnique

Reproduction

Analysis started2023-12-12 02:11:09.876747
Analysis finished2023-12-12 02:11:22.264051
Duration12.39 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

읍면동
Text

UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-12-12T11:11:22.437421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.1707317
Min length2

Characters and Unicode

Total characters130
Distinct characters60
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

Unique41 ?
Unique (%)100.0%

Sample

1st row건입동
2nd row구좌읍
3rd row남원읍
4th row노형동
5th row대륜동
ValueCountFrequency (%)
건입동 1
 
2.4%
예래동 1
 
2.4%
외도동 1
 
2.4%
용담1동 1
 
2.4%
용담2동 1
 
2.4%
이도1동 1
 
2.4%
이도2동 1
 
2.4%
이호동 1
 
2.4%
일도1동 1
 
2.4%
일도2동 1
 
2.4%
Other values (31) 31
75.6%
2023-12-12T11:11:22.946858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
32
24.6%
8
 
6.2%
7
 
5.4%
2 4
 
3.1%
1 4
 
3.1%
4
 
3.1%
3
 
2.3%
3
 
2.3%
3
 
2.3%
3
 
2.3%
Other values (50) 59
45.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 122
93.8%
Decimal Number 8
 
6.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
32
26.2%
8
 
6.6%
7
 
5.7%
4
 
3.3%
3
 
2.5%
3
 
2.5%
3
 
2.5%
3
 
2.5%
2
 
1.6%
2
 
1.6%
Other values (48) 55
45.1%
Decimal Number
ValueCountFrequency (%)
2 4
50.0%
1 4
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 122
93.8%
Common 8
 
6.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
32
26.2%
8
 
6.6%
7
 
5.7%
4
 
3.3%
3
 
2.5%
3
 
2.5%
3
 
2.5%
3
 
2.5%
2
 
1.6%
2
 
1.6%
Other values (48) 55
45.1%
Common
ValueCountFrequency (%)
2 4
50.0%
1 4
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 122
93.8%
ASCII 8
 
6.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
32
26.2%
8
 
6.6%
7
 
5.7%
4
 
3.3%
3
 
2.5%
3
 
2.5%
3
 
2.5%
3
 
2.5%
2
 
1.6%
2
 
1.6%
Other values (48) 55
45.1%
ASCII
ValueCountFrequency (%)
2 4
50.0%
1 4
50.0%

30세이상 고혈압 평생의사진단 경험률
Real number (ℝ)

HIGH CORRELATION 

Distinct40
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.478049
Minimum9.06
Maximum37.63
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T11:11:23.166768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9.06
5-th percentile13.29
Q119.84
median23.23
Q325.34
95-th percentile31.03
Maximum37.63
Range28.57
Interquartile range (IQR)5.5

Descriptive statistics

Standard deviation5.6776862
Coefficient of variation (CV)0.25258804
Kurtosis0.6049598
Mean22.478049
Median Absolute Deviation (MAD)2.72
Skewness-0.10589827
Sum921.6
Variance32.236121
MonotonicityNot monotonic
2023-12-12T11:11:23.367678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
24.02 2
 
4.9%
25.55 1
 
2.4%
12.62 1
 
2.4%
27.95 1
 
2.4%
28.92 1
 
2.4%
18.2 1
 
2.4%
16.38 1
 
2.4%
13.69 1
 
2.4%
37.63 1
 
2.4%
21.52 1
 
2.4%
Other values (30) 30
73.2%
ValueCountFrequency (%)
9.06 1
2.4%
12.62 1
2.4%
13.29 1
2.4%
13.69 1
2.4%
13.92 1
2.4%
14.34 1
2.4%
16.38 1
2.4%
16.94 1
2.4%
18.2 1
2.4%
18.47 1
2.4%
ValueCountFrequency (%)
37.63 1
2.4%
31.56 1
2.4%
31.03 1
2.4%
28.92 1
2.4%
27.95 1
2.4%
27.8 1
2.4%
27.31 1
2.4%
27.21 1
2.4%
26.2 1
2.4%
25.55 1
2.4%

30세이상 당뇨병 평생의사진단 경험률
Real number (ℝ)

HIGH CORRELATION 

Distinct39
Distinct (%)95.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.6234146
Minimum2.37
Maximum14.14
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T11:11:23.548279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.37
5-th percentile2.99
Q16.17
median7.3
Q38.86
95-th percentile12.46
Maximum14.14
Range11.77
Interquartile range (IQR)2.69

Descriptive statistics

Standard deviation2.7891949
Coefficient of variation (CV)0.36587212
Kurtosis0.10905828
Mean7.6234146
Median Absolute Deviation (MAD)1.15
Skewness0.43645175
Sum312.56
Variance7.779608
MonotonicityNot monotonic
2023-12-12T11:11:23.728438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
6.15 2
 
4.9%
7.3 2
 
4.9%
5.34 1
 
2.4%
7.29 1
 
2.4%
12.46 1
 
2.4%
6.44 1
 
2.4%
7.95 1
 
2.4%
2.37 1
 
2.4%
10.72 1
 
2.4%
8.22 1
 
2.4%
Other values (29) 29
70.7%
ValueCountFrequency (%)
2.37 1
2.4%
2.41 1
2.4%
2.99 1
2.4%
4.28 1
2.4%
4.58 1
2.4%
4.89 1
2.4%
5.22 1
2.4%
5.34 1
2.4%
6.15 2
4.9%
6.17 1
2.4%
ValueCountFrequency (%)
14.14 1
2.4%
13.55 1
2.4%
12.46 1
2.4%
12.3 1
2.4%
11.37 1
2.4%
11.33 1
2.4%
10.72 1
2.4%
10.62 1
2.4%
9.97 1
2.4%
9.06 1
2.4%

비만율
Real number (ℝ)

Distinct39
Distinct (%)95.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27.787317
Minimum17.42
Maximum35.27
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T11:11:23.905542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum17.42
5-th percentile23.79
Q125.28
median27.81
Q329.75
95-th percentile34.28
Maximum35.27
Range17.85
Interquartile range (IQR)4.47

Descriptive statistics

Standard deviation3.8246091
Coefficient of variation (CV)0.13763866
Kurtosis0.77862872
Mean27.787317
Median Absolute Deviation (MAD)2.35
Skewness-0.25681849
Sum1139.28
Variance14.627635
MonotonicityNot monotonic
2023-12-12T11:11:24.112028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
27.81 3
 
7.3%
29.75 1
 
2.4%
34.28 1
 
2.4%
27.51 1
 
2.4%
18.87 1
 
2.4%
24.16 1
 
2.4%
23.86 1
 
2.4%
30.25 1
 
2.4%
35.27 1
 
2.4%
24.68 1
 
2.4%
Other values (29) 29
70.7%
ValueCountFrequency (%)
17.42 1
2.4%
18.87 1
2.4%
23.79 1
2.4%
23.86 1
2.4%
23.9 1
2.4%
24.16 1
2.4%
24.53 1
2.4%
24.68 1
2.4%
24.93 1
2.4%
25.25 1
2.4%
ValueCountFrequency (%)
35.27 1
2.4%
35.14 1
2.4%
34.28 1
2.4%
33.61 1
2.4%
32.88 1
2.4%
31.78 1
2.4%
31.6 1
2.4%
31.58 1
2.4%
30.25 1
2.4%
30.16 1
2.4%

좋지 않은 주관적 건강수준 인지율
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.767073
Minimum5.09
Maximum71.11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T11:11:24.278522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5.09
5-th percentile8.2
Q115.36
median17.99
Q320.8
95-th percentile24.17
Maximum71.11
Range66.02
Interquartile range (IQR)5.44

Descriptive statistics

Standard deviation9.6696981
Coefficient of variation (CV)0.51524806
Kurtosis21.999327
Mean18.767073
Median Absolute Deviation (MAD)2.8
Skewness3.9867095
Sum769.45
Variance93.503061
MonotonicityNot monotonic
2023-12-12T11:11:24.460424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
16.34 1
 
2.4%
20.36 1
 
2.4%
7.22 1
 
2.4%
19.03 1
 
2.4%
15.5 1
 
2.4%
9.89 1
 
2.4%
15.36 1
 
2.4%
13.07 1
 
2.4%
71.11 1
 
2.4%
18.1 1
 
2.4%
Other values (31) 31
75.6%
ValueCountFrequency (%)
5.09 1
2.4%
7.22 1
2.4%
8.2 1
2.4%
9.89 1
2.4%
9.95 1
2.4%
12.18 1
2.4%
13.07 1
2.4%
14.08 1
2.4%
14.67 1
2.4%
15.19 1
2.4%
ValueCountFrequency (%)
71.11 1
2.4%
26.87 1
2.4%
24.17 1
2.4%
24.05 1
2.4%
23.91 1
2.4%
23.58 1
2.4%
23.16 1
2.4%
22.06 1
2.4%
21.26 1
2.4%
21.02 1
2.4%

흡연율
Real number (ℝ)

UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.276341
Minimum16.23
Maximum37.54
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T11:11:24.632178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum16.23
5-th percentile19.29
Q122.76
median24.84
Q328.65
95-th percentile31.12
Maximum37.54
Range21.31
Interquartile range (IQR)5.89

Descriptive statistics

Standard deviation4.1805734
Coefficient of variation (CV)0.16539472
Kurtosis0.92721133
Mean25.276341
Median Absolute Deviation (MAD)2.5
Skewness0.40627735
Sum1036.33
Variance17.477194
MonotonicityNot monotonic
2023-12-12T11:11:24.772812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
19.29 1
 
2.4%
23.62 1
 
2.4%
22.25 1
 
2.4%
33.1 1
 
2.4%
31.12 1
 
2.4%
29.78 1
 
2.4%
24.93 1
 
2.4%
23.07 1
 
2.4%
20.86 1
 
2.4%
26.87 1
 
2.4%
Other values (31) 31
75.6%
ValueCountFrequency (%)
16.23 1
2.4%
17.36 1
2.4%
19.29 1
2.4%
19.55 1
2.4%
20.86 1
2.4%
21.36 1
2.4%
22.02 1
2.4%
22.25 1
2.4%
22.34 1
2.4%
22.64 1
2.4%
ValueCountFrequency (%)
37.54 1
2.4%
33.1 1
2.4%
31.12 1
2.4%
30.0 1
2.4%
29.78 1
2.4%
29.77 1
2.4%
29.24 1
2.4%
29.05 1
2.4%
28.77 1
2.4%
28.66 1
2.4%

고위험 음주율
Real number (ℝ)

UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.576341
Minimum6.24
Maximum40.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T11:11:24.941843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6.24
5-th percentile12.48
Q122.82
median26.32
Q328.73
95-th percentile34.16
Maximum40.9
Range34.66
Interquartile range (IQR)5.91

Descriptive statistics

Standard deviation7.2773768
Coefficient of variation (CV)0.28453549
Kurtosis0.57405286
Mean25.576341
Median Absolute Deviation (MAD)3.5
Skewness-0.51459203
Sum1048.63
Variance52.960214
MonotonicityNot monotonic
2023-12-12T11:11:25.119612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
26.65 1
 
2.4%
6.24 1
 
2.4%
32.17 1
 
2.4%
39.01 1
 
2.4%
22.6 1
 
2.4%
23.41 1
 
2.4%
27.83 1
 
2.4%
15.22 1
 
2.4%
12.48 1
 
2.4%
32.81 1
 
2.4%
Other values (31) 31
75.6%
ValueCountFrequency (%)
6.24 1
2.4%
11.16 1
2.4%
12.48 1
2.4%
13.49 1
2.4%
15.22 1
2.4%
17.15 1
2.4%
17.43 1
2.4%
19.43 1
2.4%
22.19 1
2.4%
22.6 1
2.4%
ValueCountFrequency (%)
40.9 1
2.4%
39.01 1
2.4%
34.16 1
2.4%
33.93 1
2.4%
33.06 1
2.4%
32.81 1
2.4%
32.69 1
2.4%
32.34 1
2.4%
32.17 1
2.4%
30.99 1
2.4%

중등도 이상 운동 미실천율
Real number (ℝ)

HIGH CORRELATION 

Distinct40
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean73.718049
Minimum44.63
Maximum89.04
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T11:11:25.289098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum44.63
5-th percentile49.32
Q169.16
median77.49
Q381.62
95-th percentile87.21
Maximum89.04
Range44.41
Interquartile range (IQR)12.46

Descriptive statistics

Standard deviation11.732592
Coefficient of variation (CV)0.15915494
Kurtosis0.40370015
Mean73.718049
Median Absolute Deviation (MAD)5.66
Skewness-1.0754715
Sum3022.44
Variance137.65371
MonotonicityNot monotonic
2023-12-12T11:11:25.452896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
75.89 2
 
4.9%
73.67 1
 
2.4%
86.92 1
 
2.4%
87.57 1
 
2.4%
81.07 1
 
2.4%
81.62 1
 
2.4%
83.07 1
 
2.4%
78.9 1
 
2.4%
82.9 1
 
2.4%
80.79 1
 
2.4%
Other values (30) 30
73.2%
ValueCountFrequency (%)
44.63 1
2.4%
45.3 1
2.4%
49.32 1
2.4%
52.45 1
2.4%
55.04 1
2.4%
59.77 1
2.4%
60.44 1
2.4%
62.17 1
2.4%
64.95 1
2.4%
68.95 1
2.4%
ValueCountFrequency (%)
89.04 1
2.4%
87.57 1
2.4%
87.21 1
2.4%
86.92 1
2.4%
84.42 1
2.4%
84.39 1
2.4%
84.05 1
2.4%
83.07 1
2.4%
82.9 1
2.4%
82.66 1
2.4%

아침 결식률
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.163659
Minimum4.85
Maximum33.47
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T11:11:25.595057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.85
5-th percentile9.23
Q112.54
median14.55
Q319.05
95-th percentile24.81
Maximum33.47
Range28.62
Interquartile range (IQR)6.51

Descriptive statistics

Standard deviation5.7692793
Coefficient of variation (CV)0.35692905
Kurtosis0.89080837
Mean16.163659
Median Absolute Deviation (MAD)3.61
Skewness0.81096386
Sum662.71
Variance33.284584
MonotonicityNot monotonic
2023-12-12T11:11:25.744743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
14.77 1
 
2.4%
10.43 1
 
2.4%
33.47 1
 
2.4%
28.03 1
 
2.4%
18.62 1
 
2.4%
14.25 1
 
2.4%
24.81 1
 
2.4%
22.56 1
 
2.4%
13.69 1
 
2.4%
19.05 1
 
2.4%
Other values (31) 31
75.6%
ValueCountFrequency (%)
4.85 1
2.4%
8.17 1
2.4%
9.23 1
2.4%
10.12 1
2.4%
10.43 1
2.4%
10.62 1
2.4%
10.68 1
2.4%
10.94 1
2.4%
11.64 1
2.4%
11.92 1
2.4%
ValueCountFrequency (%)
33.47 1
2.4%
28.03 1
2.4%
24.81 1
2.4%
24.09 1
2.4%
23.95 1
2.4%
22.69 1
2.4%
22.56 1
2.4%
21.98 1
2.4%
21.18 1
2.4%
20.16 1
2.4%

스트레스 인지율
Real number (ℝ)

Distinct40
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.484878
Minimum22.45
Maximum54.28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T11:11:25.902030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22.45
5-th percentile23.69
Q125.64
median28.47
Q331.8
95-th percentile36.92
Maximum54.28
Range31.83
Interquartile range (IQR)6.16

Descriptive statistics

Standard deviation5.8470078
Coefficient of variation (CV)0.19830531
Kurtosis7.2269337
Mean29.484878
Median Absolute Deviation (MAD)3.06
Skewness2.1691649
Sum1208.88
Variance34.187501
MonotonicityNot monotonic
2023-12-12T11:11:26.059037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
23.78 2
 
4.9%
32.4 1
 
2.4%
33.66 1
 
2.4%
31.03 1
 
2.4%
25.99 1
 
2.4%
29.14 1
 
2.4%
34.3 1
 
2.4%
54.28 1
 
2.4%
29.64 1
 
2.4%
24.19 1
 
2.4%
Other values (30) 30
73.2%
ValueCountFrequency (%)
22.45 1
2.4%
22.73 1
2.4%
23.69 1
2.4%
23.78 2
4.9%
24.19 1
2.4%
25.07 1
2.4%
25.28 1
2.4%
25.32 1
2.4%
25.41 1
2.4%
25.64 1
2.4%
ValueCountFrequency (%)
54.28 1
2.4%
42.07 1
2.4%
36.92 1
2.4%
36.13 1
2.4%
35.15 1
2.4%
34.3 1
2.4%
33.66 1
2.4%
33.02 1
2.4%
32.94 1
2.4%
32.4 1
2.4%

우울감 경험률
Real number (ℝ)

UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.5819512
Minimum1.85
Maximum17.69
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T11:11:26.219753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.85
5-th percentile2.87
Q14.41
median5.63
Q37.74
95-th percentile11.73
Maximum17.69
Range15.84
Interquartile range (IQR)3.33

Descriptive statistics

Standard deviation3.3785834
Coefficient of variation (CV)0.51331031
Kurtosis1.7083417
Mean6.5819512
Median Absolute Deviation (MAD)1.69
Skewness1.2397519
Sum269.86
Variance11.414826
MonotonicityNot monotonic
2023-12-12T11:11:26.372125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
9.85 1
 
2.4%
2.98 1
 
2.4%
5.63 1
 
2.4%
9.96 1
 
2.4%
5.52 1
 
2.4%
5.98 1
 
2.4%
10.78 1
 
2.4%
10.81 1
 
2.4%
11.64 1
 
2.4%
7.4 1
 
2.4%
Other values (31) 31
75.6%
ValueCountFrequency (%)
1.85 1
2.4%
2.25 1
2.4%
2.87 1
2.4%
2.96 1
2.4%
2.98 1
2.4%
3.04 1
2.4%
3.75 1
2.4%
3.88 1
2.4%
3.94 1
2.4%
3.95 1
2.4%
ValueCountFrequency (%)
17.69 1
2.4%
13.71 1
2.4%
11.73 1
2.4%
11.64 1
2.4%
10.81 1
2.4%
10.78 1
2.4%
10.71 1
2.4%
9.96 1
2.4%
9.85 1
2.4%
9.18 1
2.4%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size460.0 B
Minimum2015-12-31 00:00:00
Maximum2015-12-31 00:00:00
2023-12-12T11:11:26.486403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:26.594450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T11:11:20.372433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:10.272068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:11.463112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:12.623192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:14.093450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:15.181210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:16.116314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:17.216565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:18.247393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:19.284039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:20.814844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:10.382522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:11.613465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:12.739878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:14.229545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:15.280212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:16.228458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:17.327113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:18.331215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:19.394197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:20.920630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:10.486400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:11.733114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:12.869222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:14.327597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:15.365216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:16.366689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:17.464914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:18.430212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:19.512395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:21.044897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:10.612956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:11.865453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:12.982258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:14.429941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:15.474360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:16.493505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:17.559285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:18.527700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:19.613356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:21.157882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:10.736678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:11.988086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:13.113675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:14.539130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:15.583754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:16.607323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:17.652135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:18.619416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:19.731081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:21.275465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:10.842124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:12.083524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:13.236678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:14.656367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:15.664441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:16.708068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:17.733968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:18.713721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:19.827573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:21.398735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:10.972387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:12.179492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:13.663768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:14.792730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:15.750825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:16.807995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:17.845404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:18.828066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:19.951456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:21.511512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:11.093492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:12.286212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:13.764558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:14.894858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:15.836100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:16.901009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:17.947897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:18.942054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:20.042151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:21.628802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:11.202921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:12.394284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:13.867904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:14.989489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:15.925289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:17.002613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:18.039826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:19.030709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:20.137434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:21.762128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:11.337264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:12.505287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:13.974561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:15.086404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:16.018839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:17.110456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:18.142365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:19.145937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:20.238743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T11:11:26.697094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동30세이상 고혈압 평생의사진단 경험률30세이상 당뇨병 평생의사진단 경험률비만율좋지 않은 주관적 건강수준 인지율흡연율고위험 음주율중등도 이상 운동 미실천율아침 결식률스트레스 인지율우울감 경험률
읍면동1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
30세이상 고혈압 평생의사진단 경험률1.0001.0000.7170.0000.8300.0000.0000.0000.0000.5850.617
30세이상 당뇨병 평생의사진단 경험률1.0000.7171.0000.0000.6680.6910.2880.5930.3820.0000.407
비만율1.0000.0000.0001.0000.1800.0000.2920.3100.0000.2670.502
좋지 않은 주관적 건강수준 인지율1.0000.8300.6680.1801.0000.3520.5840.0000.0120.6340.377
흡연율1.0000.0000.6910.0000.3521.0000.4840.0000.6210.3920.234
고위험 음주율1.0000.0000.2880.2920.5840.4841.0000.1470.5690.5390.648
중등도 이상 운동 미실천율1.0000.0000.5930.3100.0000.0000.1471.0000.2590.0000.330
아침 결식률1.0000.0000.3820.0000.0120.6210.5690.2591.0000.0000.000
스트레스 인지율1.0000.5850.0000.2670.6340.3920.5390.0000.0001.0000.582
우울감 경험률1.0000.6170.4070.5020.3770.2340.6480.3300.0000.5821.000
2023-12-12T11:11:27.225282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
30세이상 고혈압 평생의사진단 경험률30세이상 당뇨병 평생의사진단 경험률비만율좋지 않은 주관적 건강수준 인지율흡연율고위험 음주율중등도 이상 운동 미실천율아침 결식률스트레스 인지율우울감 경험률
30세이상 고혈압 평생의사진단 경험률1.0000.6160.0170.547-0.264-0.344-0.149-0.253-0.200-0.021
30세이상 당뇨병 평생의사진단 경험률0.6161.0000.0290.2910.0010.003-0.068-0.2430.1510.140
비만율0.0170.0291.0000.031-0.2230.1980.140-0.0480.1250.126
좋지 않은 주관적 건강수준 인지율0.5470.2910.0311.000-0.274-0.369-0.422-0.217-0.126-0.089
흡연율-0.2640.001-0.223-0.2741.0000.4380.1520.1010.046-0.188
고위험 음주율-0.3440.0030.198-0.3690.4381.0000.3160.4190.335-0.071
중등도 이상 운동 미실천율-0.149-0.0680.140-0.4220.1520.3161.0000.5060.0570.121
아침 결식률-0.253-0.243-0.048-0.2170.1010.4190.5061.0000.3030.143
스트레스 인지율-0.2000.1510.125-0.1260.0460.3350.0570.3031.0000.418
우울감 경험률-0.0210.1400.126-0.089-0.188-0.0710.1210.1430.4181.000

Missing values

2023-12-12T11:11:21.953675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:11:22.175455image/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

읍면동30세이상 고혈압 평생의사진단 경험률30세이상 당뇨병 평생의사진단 경험률비만율좋지 않은 주관적 건강수준 인지율흡연율고위험 음주율중등도 이상 운동 미실천율아침 결식률스트레스 인지율우울감 경험률데이터기준일자
0건입동25.345.3429.7516.3419.2926.6573.6714.7732.49.852015-12-31
1구좌읍24.486.2225.2524.0524.8517.1560.4410.6822.452.872015-12-31
2남원읍22.766.925.2819.9124.9927.1155.0412.5422.732.962015-12-31
3노형동13.292.9926.828.226.9928.1884.3921.9827.433.952015-12-31
4대륜동24.4711.3335.1416.7722.0233.0680.6911.9227.575.032015-12-31
5대정읍21.817.2232.8820.5628.7723.469.5812.6428.965.452015-12-31
6대천동24.977.324.5319.0429.2433.9374.2615.0530.045.342015-12-31
7도두동9.064.2828.575.0929.0530.9977.7910.6230.9111.732015-12-31
8동홍동19.848.0628.7815.5226.2932.6979.6118.5833.026.212015-12-31
9봉개동21.8713.5523.7916.4237.5432.3462.1710.1232.944.412015-12-31
읍면동30세이상 고혈압 평생의사진단 경험률30세이상 당뇨병 평생의사진단 경험률비만율좋지 않은 주관적 건강수준 인지율흡연율고위험 음주율중등도 이상 운동 미실천율아침 결식률스트레스 인지율우울감 경험률데이터기준일자
31정방동25.557.2924.6820.3623.626.2482.6610.4324.192.982015-12-31
32조천읍24.026.1528.0720.824.725.4568.9518.0128.834.972015-12-31
33중문동27.319.0626.319.022.9128.781.4121.1830.712.252015-12-31
34중앙동31.5610.6229.6219.123.9225.1287.2114.5525.327.742015-12-31
35천지동27.2112.317.4214.0823.5911.1664.9513.6527.836.682015-12-31
36표선면22.44.8926.2222.0622.3423.2644.6313.7525.284.792015-12-31
37한경면25.188.8623.923.5824.8419.4345.39.2328.4713.712015-12-31
38한림읍23.287.5631.7823.1624.924.0671.8315.1829.326.782015-12-31
39화북동16.946.3825.9612.1826.426.3275.8914.3425.411.852015-12-31
40효돈동27.814.1429.2516.6316.2322.8277.4910.9425.816.162015-12-31