Overview

Dataset statistics

Number of variables19
Number of observations59
Missing cells2
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.9 KiB
Average record size in memory172.2 B

Variable types

Text1
Numeric18

Dataset

Description충청남도에서 발생한 감염병 발생 정보로 이를 통해 감염병 예방 및 퇴치할 수 있도록 개방하고자 합니다. 연도별 및 전국 발행 현황과 충남도의 현황을 제공합니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=418&beforeMenuCd=DOM_000000201001001000&publicdatapk=15019589

Alerts

2012년도 전국 is highly overall correlated with 2012년도 충남 and 16 other fieldsHigh correlation
2012년도 충남 is highly overall correlated with 2012년도 전국 and 16 other fieldsHigh correlation
2013년도 전국 is highly overall correlated with 2012년도 전국 and 16 other fieldsHigh correlation
2013년도 충남 is highly overall correlated with 2012년도 전국 and 16 other fieldsHigh correlation
2014년도 전국 is highly overall correlated with 2012년도 전국 and 16 other fieldsHigh correlation
2014년도 충남 is highly overall correlated with 2012년도 전국 and 16 other fieldsHigh correlation
2015년도 전국 is highly overall correlated with 2012년도 전국 and 16 other fieldsHigh correlation
2015년도 충남 is highly overall correlated with 2012년도 전국 and 16 other fieldsHigh correlation
2016년도 전국 is highly overall correlated with 2012년도 전국 and 16 other fieldsHigh correlation
2016년도 충남 is highly overall correlated with 2012년도 전국 and 16 other fieldsHigh correlation
2017년도전국 is highly overall correlated with 2012년도 전국 and 16 other fieldsHigh correlation
2017년도충남 is highly overall correlated with 2012년도 전국 and 16 other fieldsHigh correlation
2018년도전국 is highly overall correlated with 2012년도 전국 and 16 other fieldsHigh correlation
2018년도충남 is highly overall correlated with 2012년도 전국 and 16 other fieldsHigh correlation
2019년도전국 is highly overall correlated with 2012년도 전국 and 16 other fieldsHigh correlation
2019년도충남 is highly overall correlated with 2012년도 전국 and 16 other fieldsHigh correlation
2020년도전국 is highly overall correlated with 2012년도 전국 and 16 other fieldsHigh correlation
2020년도충남 is highly overall correlated with 2012년도 전국 and 16 other fieldsHigh correlation
2020년도전국 has 1 (1.7%) missing valuesMissing
2020년도충남 has 1 (1.7%) missing valuesMissing
구분 has unique valuesUnique
2012년도 전국 has 27 (45.8%) zerosZeros
2012년도 충남 has 35 (59.3%) zerosZeros
2013년도 전국 has 24 (40.7%) zerosZeros
2013년도 충남 has 33 (55.9%) zerosZeros
2014년도 전국 has 23 (39.0%) zerosZeros
2014년도 충남 has 30 (50.8%) zerosZeros
2015년도 전국 has 25 (42.4%) zerosZeros
2015년도 충남 has 35 (59.3%) zerosZeros
2016년도 전국 has 24 (40.7%) zerosZeros
2016년도 충남 has 32 (54.2%) zerosZeros
2017년도전국 has 21 (35.6%) zerosZeros
2017년도충남 has 28 (47.5%) zerosZeros
2018년도전국 has 21 (35.6%) zerosZeros
2018년도충남 has 31 (52.5%) zerosZeros
2019년도전국 has 20 (33.9%) zerosZeros
2019년도충남 has 31 (52.5%) zerosZeros
2020년도전국 has 20 (33.9%) zerosZeros
2020년도충남 has 30 (50.8%) zerosZeros

Reproduction

Analysis started2024-01-09 21:06:08.561112
Analysis finished2024-01-09 21:06:38.798429
Duration30.24 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Text

UNIQUE 

Distinct59
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size604.0 B
2024-01-10T06:06:38.978976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length12
Mean length5.8813559
Min length2

Characters and Unicode

Total characters347
Distinct characters142
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique59 ?
Unique (%)100.0%

Sample

1st row콜 레 라
2nd row장티푸스
3rd row파라티푸스
4th row세균성이질
5th row장출혈성대장균감염
ValueCountFrequency (%)
3
 
3.9%
2
 
2.6%
2
 
2.6%
2
 
2.6%
반코마이신내성황색포도알균(vrsa 1
 
1.3%
뎅기열 1
 
1.3%
1
 
1.3%
페스트 1
 
1.3%
카바페넴내성장내세균속균종(cre)감염증 1
 
1.3%
감염증 1
 
1.3%
Other values (61) 61
80.3%
2024-01-10T06:06:39.316889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17
 
4.9%
14
 
4.0%
13
 
3.7%
11
 
3.2%
9
 
2.6%
9
 
2.6%
7
 
2.0%
7
 
2.0%
6
 
1.7%
5
 
1.4%
Other values (132) 249
71.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 305
87.9%
Space Separator 17
 
4.9%
Uppercase Letter 17
 
4.9%
Lowercase Letter 3
 
0.9%
Close Punctuation 2
 
0.6%
Open Punctuation 2
 
0.6%
Other Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
14
 
4.6%
13
 
4.3%
11
 
3.6%
9
 
3.0%
9
 
3.0%
7
 
2.3%
7
 
2.3%
6
 
2.0%
5
 
1.6%
5
 
1.6%
Other values (116) 219
71.8%
Uppercase Letter
ValueCountFrequency (%)
C 3
17.6%
B 3
17.6%
R 2
11.8%
A 2
11.8%
D 2
11.8%
J 2
11.8%
V 1
 
5.9%
S 1
 
5.9%
E 1
 
5.9%
Lowercase Letter
ValueCountFrequency (%)
b 1
33.3%
c 1
33.3%
v 1
33.3%
Space Separator
ValueCountFrequency (%)
17
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 305
87.9%
Common 22
 
6.3%
Latin 20
 
5.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
14
 
4.6%
13
 
4.3%
11
 
3.6%
9
 
3.0%
9
 
3.0%
7
 
2.3%
7
 
2.3%
6
 
2.0%
5
 
1.6%
5
 
1.6%
Other values (116) 219
71.8%
Latin
ValueCountFrequency (%)
C 3
15.0%
B 3
15.0%
R 2
10.0%
A 2
10.0%
D 2
10.0%
J 2
10.0%
V 1
 
5.0%
S 1
 
5.0%
E 1
 
5.0%
b 1
 
5.0%
Other values (2) 2
10.0%
Common
ValueCountFrequency (%)
17
77.3%
) 2
 
9.1%
( 2
 
9.1%
/ 1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 305
87.9%
ASCII 42
 
12.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17
40.5%
C 3
 
7.1%
B 3
 
7.1%
R 2
 
4.8%
) 2
 
4.8%
A 2
 
4.8%
D 2
 
4.8%
J 2
 
4.8%
( 2
 
4.8%
V 1
 
2.4%
Other values (6) 6
 
14.3%
Hangul
ValueCountFrequency (%)
14
 
4.6%
13
 
4.3%
11
 
3.6%
9
 
3.0%
9
 
3.0%
7
 
2.3%
7
 
2.3%
6
 
2.0%
5
 
1.6%
5
 
1.6%
Other values (116) 219
71.8%

2012년도 전국
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct29
Distinct (%)49.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean872.79661
Minimum0
Maximum27763
Zeros27
Zeros (%)45.8%
Negative0
Negative (%)0.0%
Memory size663.0 B
2024-01-10T06:06:39.435734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q361
95-th percentile2943.4
Maximum27763
Range27763
Interquartile range (IQR)61

Descriptive statistics

Standard deviation3863.087
Coefficient of variation (CV)4.4261022
Kurtosis42.202792
Mean872.79661
Median Absolute Deviation (MAD)3
Skewness6.2435288
Sum51495
Variance14923441
MonotonicityNot monotonic
2024-01-10T06:06:39.551616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0 27
45.8%
58 2
 
3.4%
17 2
 
3.4%
3 2
 
3.4%
28 2
 
3.4%
5 1
 
1.7%
64 1
 
1.7%
41 1
 
1.7%
8604 1
 
1.7%
364 1
 
1.7%
Other values (19) 19
32.2%
ValueCountFrequency (%)
0 27
45.8%
1 1
 
1.7%
3 2
 
3.4%
4 1
 
1.7%
5 1
 
1.7%
10 1
 
1.7%
17 2
 
3.4%
20 1
 
1.7%
25 1
 
1.7%
26 1
 
1.7%
ValueCountFrequency (%)
27763 1
1.7%
8604 1
1.7%
7492 1
1.7%
2438 1
1.7%
1197 1
1.7%
968 1
1.7%
787 1
1.7%
542 1
1.7%
364 1
1.7%
289 1
1.7%

2012년도 충남
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct15
Distinct (%)25.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42.322034
Minimum0
Maximum1250
Zeros35
Zeros (%)59.3%
Negative0
Negative (%)0.0%
Memory size663.0 B
2024-01-10T06:06:39.669570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile78.4
Maximum1250
Range1250
Interquartile range (IQR)3

Descriptive statistics

Standard deviation189.14622
Coefficient of variation (CV)4.4692138
Kurtosis32.147102
Mean42.322034
Median Absolute Deviation (MAD)0
Skewness5.5482722
Sum2497
Variance35776.291
MonotonicityNot monotonic
2024-01-10T06:06:39.774417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 35
59.3%
2 6
 
10.2%
5 3
 
5.1%
4 2
 
3.4%
1 2
 
3.4%
3 2
 
3.4%
59 1
 
1.7%
253 1
 
1.7%
1250 1
 
1.7%
39 1
 
1.7%
Other values (5) 5
 
8.5%
ValueCountFrequency (%)
0 35
59.3%
1 2
 
3.4%
2 6
 
10.2%
3 2
 
3.4%
4 2
 
3.4%
5 3
 
5.1%
6 1
 
1.7%
20 1
 
1.7%
39 1
 
1.7%
44 1
 
1.7%
ValueCountFrequency (%)
1250 1
 
1.7%
738 1
 
1.7%
253 1
 
1.7%
59 1
 
1.7%
45 1
 
1.7%
44 1
 
1.7%
39 1
 
1.7%
20 1
 
1.7%
6 1
 
1.7%
5 3
5.1%

2013년도 전국
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct33
Distinct (%)55.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1283.7288
Minimum0
Maximum37361
Zeros24
Zeros (%)40.7%
Negative0
Negative (%)0.0%
Memory size663.0 B
2024-01-10T06:06:39.890108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median11
Q360
95-th percentile4346.7
Maximum37361
Range37361
Interquartile range (IQR)60

Descriptive statistics

Standard deviation5448.4865
Coefficient of variation (CV)4.2442659
Kurtosis35.078824
Mean1283.7288
Median Absolute Deviation (MAD)11
Skewness5.6852382
Sum75740
Variance29686005
MonotonicityNot monotonic
2024-01-10T06:06:40.022299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
0 24
40.7%
2 2
 
3.4%
11 2
 
3.4%
36 2
 
3.4%
3 1
 
1.7%
16 1
 
1.7%
21 1
 
1.7%
56 1
 
1.7%
19 1
 
1.7%
10365 1
 
1.7%
Other values (23) 23
39.0%
ValueCountFrequency (%)
0 24
40.7%
2 2
 
3.4%
3 1
 
1.7%
6 1
 
1.7%
7 1
 
1.7%
11 2
 
3.4%
14 1
 
1.7%
16 1
 
1.7%
18 1
 
1.7%
19 1
 
1.7%
ValueCountFrequency (%)
37361 1
1.7%
17024 1
1.7%
10365 1
1.7%
3678 1
1.7%
3211 1
1.7%
867 1
1.7%
798 1
1.7%
527 1
1.7%
445 1
1.7%
294 1
1.7%

2013년도 충남
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct18
Distinct (%)30.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean68.915254
Minimum0
Maximum1842
Zeros33
Zeros (%)55.9%
Negative0
Negative (%)0.0%
Memory size663.0 B
2024-01-10T06:06:40.145261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33.5
95-th percentile211.6
Maximum1842
Range1842
Interquartile range (IQR)3.5

Descriptive statistics

Standard deviation286.77056
Coefficient of variation (CV)4.1612059
Kurtosis27.706115
Mean68.915254
Median Absolute Deviation (MAD)0
Skewness5.1037321
Sum4066
Variance82237.355
MonotonicityNot monotonic
2024-01-10T06:06:40.257677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 33
55.9%
1 7
 
11.9%
2 2
 
3.4%
5 2
 
3.4%
3 2
 
3.4%
7 1
 
1.7%
6 1
 
1.7%
34 1
 
1.7%
4 1
 
1.7%
62 1
 
1.7%
Other values (8) 8
 
13.6%
ValueCountFrequency (%)
0 33
55.9%
1 7
 
11.9%
2 2
 
3.4%
3 2
 
3.4%
4 1
 
1.7%
5 2
 
3.4%
6 1
 
1.7%
7 1
 
1.7%
8 1
 
1.7%
14 1
 
1.7%
ValueCountFrequency (%)
1842 1
1.7%
1010 1
1.7%
775 1
1.7%
149 1
1.7%
79 1
1.7%
62 1
1.7%
49 1
1.7%
34 1
1.7%
14 1
1.7%
8 1
1.7%

2014년도 전국
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct34
Distinct (%)57.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1571.661
Minimum0
Maximum44450
Zeros23
Zeros (%)39.0%
Negative0
Negative (%)0.0%
Memory size663.0 B
2024-01-10T06:06:40.381313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median11
Q399
95-th percentile6041.1
Maximum44450
Range44450
Interquartile range (IQR)99

Descriptive statistics

Standard deviation6680.1621
Coefficient of variation (CV)4.2503835
Kurtosis32.356555
Mean1571.661
Median Absolute Deviation (MAD)11
Skewness5.5291028
Sum92728
Variance44624566
MonotonicityNot monotonic
2024-01-10T06:06:40.495654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
0 23
39.0%
11 2
 
3.4%
30 2
 
3.4%
1 2
 
3.4%
9 1
 
1.7%
8130 1
 
1.7%
58 1
 
1.7%
17 1
 
1.7%
344 1
 
1.7%
6 1
 
1.7%
Other values (24) 24
40.7%
ValueCountFrequency (%)
0 23
39.0%
1 2
 
3.4%
2 1
 
1.7%
5 1
 
1.7%
6 1
 
1.7%
9 1
 
1.7%
11 2
 
3.4%
13 1
 
1.7%
17 1
 
1.7%
23 1
 
1.7%
ValueCountFrequency (%)
44450 1
1.7%
25286 1
1.7%
8130 1
1.7%
5809 1
1.7%
3912 1
1.7%
1307 1
1.7%
1015 1
1.7%
638 1
1.7%
442 1
1.7%
344 1
1.7%

2014년도 충남
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct16
Distinct (%)27.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean72.050847
Minimum0
Maximum1917
Zeros30
Zeros (%)50.8%
Negative0
Negative (%)0.0%
Memory size663.0 B
2024-01-10T06:06:40.597673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34.5
95-th percentile349.2
Maximum1917
Range1917
Interquartile range (IQR)4.5

Descriptive statistics

Standard deviation289.92338
Coefficient of variation (CV)4.0238719
Kurtosis30.048342
Mean72.050847
Median Absolute Deviation (MAD)0
Skewness5.2469094
Sum4251
Variance84055.566
MonotonicityNot monotonic
2024-01-10T06:06:40.723134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 30
50.8%
1 6
 
10.2%
2 5
 
8.5%
3 3
 
5.1%
41 2
 
3.4%
12 2
 
3.4%
6 2
 
3.4%
9 1
 
1.7%
819 1
 
1.7%
297 1
 
1.7%
Other values (6) 6
 
10.2%
ValueCountFrequency (%)
0 30
50.8%
1 6
 
10.2%
2 5
 
8.5%
3 3
 
5.1%
6 2
 
3.4%
9 1
 
1.7%
12 2
 
3.4%
13 1
 
1.7%
19 1
 
1.7%
41 2
 
3.4%
ValueCountFrequency (%)
1917 1
1.7%
852 1
1.7%
819 1
1.7%
297 1
1.7%
111 1
1.7%
71 1
1.7%
41 2
3.4%
19 1
1.7%
13 1
1.7%
12 2
3.4%

2015년도 전국
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct34
Distinct (%)57.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1559.0847
Minimum0
Maximum46330
Zeros25
Zeros (%)42.4%
Negative0
Negative (%)0.0%
Memory size663.0 B
2024-01-10T06:06:40.839894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6
Q396
95-th percentile7253.1
Maximum46330
Range46330
Interquartile range (IQR)96

Descriptive statistics

Standard deviation6819.8024
Coefficient of variation (CV)4.3742346
Kurtosis34.427927
Mean1559.0847
Median Absolute Deviation (MAD)6
Skewness5.6663085
Sum91986
Variance46509705
MonotonicityNot monotonic
2024-01-10T06:06:40.950378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
0 25
42.4%
2 2
 
3.4%
33 1
 
1.7%
15 1
 
1.7%
9513 1
 
1.7%
104 1
 
1.7%
5 1
 
1.7%
384 1
 
1.7%
1006 1
 
1.7%
45 1
 
1.7%
Other values (24) 24
40.7%
ValueCountFrequency (%)
0 25
42.4%
2 2
 
3.4%
4 1
 
1.7%
5 1
 
1.7%
6 1
 
1.7%
7 1
 
1.7%
9 1
 
1.7%
11 1
 
1.7%
15 1
 
1.7%
22 1
 
1.7%
ValueCountFrequency (%)
46330 1
1.7%
23448 1
1.7%
9513 1
1.7%
7002 1
1.7%
1804 1
1.7%
1006 1
1.7%
699 1
1.7%
384 1
1.7%
255 1
1.7%
228 1
1.7%

2015년도 충남
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct18
Distinct (%)30.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean69.101695
Minimum0
Maximum1837
Zeros35
Zeros (%)59.3%
Negative0
Negative (%)0.0%
Memory size663.0 B
2024-01-10T06:06:41.056775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q36
95-th percentile399.9
Maximum1837
Range1837
Interquartile range (IQR)6

Descriptive statistics

Standard deviation281.45421
Coefficient of variation (CV)4.0730435
Kurtosis28.653843
Mean69.101695
Median Absolute Deviation (MAD)0
Skewness5.1280964
Sum4077
Variance79216.472
MonotonicityNot monotonic
2024-01-10T06:06:41.439140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 35
59.3%
1 4
 
6.8%
5 2
 
3.4%
8 2
 
3.4%
10 2
 
3.4%
6 2
 
3.4%
356 1
 
1.7%
16 1
 
1.7%
32 1
 
1.7%
40 1
 
1.7%
Other values (8) 8
 
13.6%
ValueCountFrequency (%)
0 35
59.3%
1 4
 
6.8%
2 1
 
1.7%
3 1
 
1.7%
5 2
 
3.4%
6 2
 
3.4%
7 1
 
1.7%
8 2
 
3.4%
10 2
 
3.4%
12 1
 
1.7%
ValueCountFrequency (%)
1837 1
1.7%
858 1
1.7%
795 1
1.7%
356 1
1.7%
57 1
1.7%
40 1
1.7%
32 1
1.7%
16 1
1.7%
12 1
1.7%
10 2
3.4%

2016년도 전국
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct31
Distinct (%)52.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1763.1017
Minimum0
Maximum54057
Zeros24
Zeros (%)40.7%
Negative0
Negative (%)0.0%
Memory size663.0 B
2024-01-10T06:06:41.556995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median10
Q3119
95-th percentile11185.5
Maximum54057
Range54057
Interquartile range (IQR)119

Descriptive statistics

Standard deviation7566.4335
Coefficient of variation (CV)4.2915468
Kurtosis40.893471
Mean1763.1017
Median Absolute Deviation (MAD)10
Skewness6.1057336
Sum104023
Variance57250916
MonotonicityNot monotonic
2024-01-10T06:06:41.679891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 24
40.7%
4 4
 
6.8%
56 2
 
3.4%
18 2
 
3.4%
313 1
 
1.7%
11105 1
 
1.7%
117 1
 
1.7%
575 1
 
1.7%
42 1
 
1.7%
1568 1
 
1.7%
Other values (21) 21
35.6%
ValueCountFrequency (%)
0 24
40.7%
4 4
 
6.8%
6 1
 
1.7%
10 1
 
1.7%
11 1
 
1.7%
16 1
 
1.7%
18 2
 
3.4%
24 1
 
1.7%
27 1
 
1.7%
28 1
 
1.7%
ValueCountFrequency (%)
54057 1
1.7%
17057 1
1.7%
11910 1
1.7%
11105 1
1.7%
4679 1
1.7%
1568 1
1.7%
673 1
1.7%
575 1
1.7%
441 1
1.7%
359 1
1.7%

2016년도 충남
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct20
Distinct (%)33.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean80.457627
Minimum0
Maximum2009
Zeros32
Zeros (%)54.2%
Negative0
Negative (%)0.0%
Memory size663.0 B
2024-01-10T06:06:41.793755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q35
95-th percentile582.4
Maximum2009
Range2009
Interquartile range (IQR)5

Descriptive statistics

Standard deviation307.64194
Coefficient of variation (CV)3.8236517
Kurtosis28.2786
Mean80.457627
Median Absolute Deviation (MAD)0
Skewness5.0531994
Sum4747
Variance94643.563
MonotonicityNot monotonic
2024-01-10T06:06:41.905189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0 32
54.2%
1 3
 
5.1%
4 3
 
5.1%
2 3
 
5.1%
5 2
 
3.4%
3 2
 
3.4%
1006 1
 
1.7%
9 1
 
1.7%
12 1
 
1.7%
8 1
 
1.7%
Other values (10) 10
 
16.9%
ValueCountFrequency (%)
0 32
54.2%
1 3
 
5.1%
2 3
 
5.1%
3 2
 
3.4%
4 3
 
5.1%
5 2
 
3.4%
7 1
 
1.7%
8 1
 
1.7%
9 1
 
1.7%
11 1
 
1.7%
ValueCountFrequency (%)
2009 1
1.7%
1006 1
1.7%
640 1
1.7%
576 1
1.7%
270 1
1.7%
65 1
1.7%
57 1
1.7%
21 1
1.7%
19 1
1.7%
12 1
1.7%

2017년도전국
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct36
Distinct (%)61.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2591
Minimum0
Maximum80092
Zeros21
Zeros (%)35.6%
Negative0
Negative (%)0.0%
Memory size663.0 B
2024-01-10T06:06:42.046223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median9
Q3184.5
95-th percentile11167.6
Maximum80092
Range80092
Interquartile range (IQR)184.5

Descriptive statistics

Standard deviation11014.488
Coefficient of variation (CV)4.2510568
Kurtosis43.988616
Mean2591
Median Absolute Deviation (MAD)9
Skewness6.364087
Sum152869
Variance1.2131895 × 108
MonotonicityNot monotonic
2024-01-10T06:06:42.201087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
0 21
35.6%
5 2
 
3.4%
3 2
 
3.4%
7 2
 
3.4%
6396 1
 
1.7%
10528 1
 
1.7%
103 1
 
1.7%
6 1
 
1.7%
531 1
 
1.7%
36 1
 
1.7%
Other values (26) 26
44.1%
ValueCountFrequency (%)
0 21
35.6%
2 1
 
1.7%
3 2
 
3.4%
5 2
 
3.4%
6 1
 
1.7%
7 2
 
3.4%
9 1
 
1.7%
11 1
 
1.7%
17 1
 
1.7%
18 1
 
1.7%
ValueCountFrequency (%)
80092 1
1.7%
22838 1
1.7%
16924 1
1.7%
10528 1
1.7%
6396 1
1.7%
5716 1
1.7%
4419 1
1.7%
2148 1
1.7%
531 1
1.7%
523 1
1.7%

2017년도충남
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)37.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean123.98305
Minimum0
Maximum3354
Zeros28
Zeros (%)47.5%
Negative0
Negative (%)0.0%
Memory size663.0 B
2024-01-10T06:06:42.351895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q39
95-th percentile745.9
Maximum3354
Range3354
Interquartile range (IQR)9

Descriptive statistics

Standard deviation486.27577
Coefficient of variation (CV)3.9221149
Kurtosis34.917658
Mean123.98305
Median Absolute Deviation (MAD)1
Skewness5.5979426
Sum7315
Variance236464.12
MonotonicityNot monotonic
2024-01-10T06:06:42.478854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 28
47.5%
1 7
 
11.9%
2 3
 
5.1%
3 3
 
5.1%
1250 1
 
1.7%
30 1
 
1.7%
13 1
 
1.7%
8 1
 
1.7%
106 1
 
1.7%
225 1
 
1.7%
Other values (12) 12
20.3%
ValueCountFrequency (%)
0 28
47.5%
1 7
 
11.9%
2 3
 
5.1%
3 3
 
5.1%
5 1
 
1.7%
7 1
 
1.7%
8 1
 
1.7%
10 1
 
1.7%
13 1
 
1.7%
14 1
 
1.7%
ValueCountFrequency (%)
3354 1
1.7%
1250 1
1.7%
1060 1
1.7%
711 1
1.7%
327 1
1.7%
225 1
1.7%
106 1
1.7%
85 1
1.7%
52 1
1.7%
30 1
1.7%

2018년도전국
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct35
Distinct (%)59.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2889.7966
Minimum0
Maximum96467
Zeros21
Zeros (%)35.6%
Negative0
Negative (%)0.0%
Memory size663.0 B
2024-01-10T06:06:42.627432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median14
Q3236
95-th percentile12336.3
Maximum96467
Range96467
Interquartile range (IQR)236

Descriptive statistics

Standard deviation12965.434
Coefficient of variation (CV)4.486625
Kurtosis48.800172
Mean2889.7966
Median Absolute Deviation (MAD)14
Skewness6.764289
Sum170498
Variance1.6810247 × 108
MonotonicityNot monotonic
2024-01-10T06:06:42.774476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
0 21
35.6%
2 3
 
5.1%
47 2
 
3.4%
3 2
 
3.4%
10811 1
 
1.7%
118 1
 
1.7%
5 1
 
1.7%
433 1
 
1.7%
6 1
 
1.7%
53 1
 
1.7%
Other values (25) 25
42.4%
ValueCountFrequency (%)
0 21
35.6%
1 1
 
1.7%
2 3
 
5.1%
3 2
 
3.4%
5 1
 
1.7%
6 1
 
1.7%
14 1
 
1.7%
15 1
 
1.7%
16 1
 
1.7%
17 1
 
1.7%
ValueCountFrequency (%)
96467 1
1.7%
19237 1
1.7%
15777 1
1.7%
11954 1
1.7%
10811 1
1.7%
6668 1
1.7%
2437 1
1.7%
2280 1
1.7%
980 1
1.7%
670 1
1.7%

2018년도충남
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)39.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean113
Minimum0
Maximum3187
Zeros31
Zeros (%)52.5%
Negative0
Negative (%)0.0%
Memory size663.0 B
2024-01-10T06:06:42.879386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q317
95-th percentile612.7
Maximum3187
Range3187
Interquartile range (IQR)17

Descriptive statistics

Standard deviation445.59139
Coefficient of variation (CV)3.9432867
Kurtosis40.497095
Mean113
Median Absolute Deviation (MAD)0
Skewness6.0466093
Sum6667
Variance198551.69
MonotonicityNot monotonic
2024-01-10T06:06:42.992916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 31
52.5%
2 3
 
5.1%
1 3
 
5.1%
6 2
 
3.4%
20 2
 
3.4%
9 1
 
1.7%
22 1
 
1.7%
4 1
 
1.7%
230 1
 
1.7%
389 1
 
1.7%
Other values (13) 13
22.0%
ValueCountFrequency (%)
0 31
52.5%
1 3
 
5.1%
2 3
 
5.1%
4 1
 
1.7%
6 2
 
3.4%
7 1
 
1.7%
8 1
 
1.7%
9 1
 
1.7%
16 1
 
1.7%
18 1
 
1.7%
ValueCountFrequency (%)
3187 1
1.7%
907 1
1.7%
826 1
1.7%
589 1
1.7%
389 1
1.7%
230 1
1.7%
207 1
1.7%
79 1
1.7%
64 1
1.7%
25 1
1.7%

2019년도전국
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct37
Distinct (%)62.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2710.4576
Minimum0
Maximum82871
Zeros20
Zeros (%)33.9%
Negative0
Negative (%)0.0%
Memory size663.0 B
2024-01-10T06:06:43.115396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median16
Q3281
95-th percentile15405.2
Maximum82871
Range82871
Interquartile range (IQR)281

Descriptive statistics

Standard deviation11305.654
Coefficient of variation (CV)4.1711235
Kurtosis45.29492
Mean2710.4576
Median Absolute Deviation (MAD)16
Skewness6.4510756
Sum159917
Variance1.278178 × 108
MonotonicityNot monotonic
2024-01-10T06:06:43.238661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
0 20
33.9%
1 2
 
3.4%
3 2
 
3.4%
21 2
 
3.4%
16 1
 
1.7%
8 1
 
1.7%
223 1
 
1.7%
224 1
 
1.7%
279 1
 
1.7%
40 1
 
1.7%
Other values (27) 27
45.8%
ValueCountFrequency (%)
0 20
33.9%
1 2
 
3.4%
2 1
 
1.7%
3 2
 
3.4%
8 1
 
1.7%
9 1
 
1.7%
14 1
 
1.7%
15 1
 
1.7%
16 1
 
1.7%
21 2
 
3.4%
ValueCountFrequency (%)
82871 1
1.7%
17638 1
1.7%
16064 1
1.7%
15332 1
1.7%
9804 1
1.7%
7612 1
1.7%
4023 1
1.7%
1745 1
1.7%
560 1
1.7%
523 1
1.7%

2019년도충남
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct24
Distinct (%)40.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean116.38983
Minimum0
Maximum3010
Zeros31
Zeros (%)52.5%
Negative0
Negative (%)0.0%
Memory size663.0 B
2024-01-10T06:06:43.345109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q314.5
95-th percentile473.8
Maximum3010
Range3010
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation442.77717
Coefficient of variation (CV)3.8042599
Kurtosis33.318303
Mean116.38983
Median Absolute Deviation (MAD)0
Skewness5.5011803
Sum6867
Variance196051.62
MonotonicityNot monotonic
2024-01-10T06:06:43.448555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 31
52.5%
1 4
 
6.8%
4 2
 
3.4%
21 2
 
3.4%
24 1
 
1.7%
8 1
 
1.7%
236 1
 
1.7%
382 1
 
1.7%
62 1
 
1.7%
57 1
 
1.7%
Other values (14) 14
23.7%
ValueCountFrequency (%)
0 31
52.5%
1 4
 
6.8%
2 1
 
1.7%
3 1
 
1.7%
4 2
 
3.4%
5 1
 
1.7%
7 1
 
1.7%
8 1
 
1.7%
9 1
 
1.7%
12 1
 
1.7%
ValueCountFrequency (%)
3010 1
1.7%
1439 1
1.7%
724 1
1.7%
446 1
1.7%
382 1
1.7%
323 1
1.7%
236 1
1.7%
62 1
1.7%
57 1
1.7%
27 1
1.7%

2020년도전국
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct33
Distinct (%)56.9%
Missing1
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean1922.7931
Minimum0
Maximum61769
Zeros20
Zeros (%)33.9%
Negative0
Negative (%)0.0%
Memory size663.0 B
2024-01-10T06:06:43.561599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6.5
Q3154.25
95-th percentile10110.1
Maximum61769
Range61769
Interquartile range (IQR)154.25

Descriptive statistics

Standard deviation8488.399
Coefficient of variation (CV)4.414619
Kurtosis45.17914
Mean1922.7931
Median Absolute Deviation (MAD)6.5
Skewness6.4755501
Sum111522
Variance72052917
MonotonicityNot monotonic
2024-01-10T06:06:43.685640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
0 20
33.9%
1 4
 
6.8%
70 2
 
3.4%
7 2
 
3.4%
6 2
 
3.4%
42 1
 
1.7%
15765 1
 
1.7%
9 1
 
1.7%
61769 1
 
1.7%
11108 1
 
1.7%
Other values (23) 23
39.0%
ValueCountFrequency (%)
0 20
33.9%
1 4
 
6.8%
2 1
 
1.7%
3 1
 
1.7%
5 1
 
1.7%
6 2
 
3.4%
7 2
 
3.4%
9 1
 
1.7%
17 1
 
1.7%
26 1
 
1.7%
ValueCountFrequency (%)
61769 1
1.7%
15765 1
1.7%
11108 1
1.7%
9934 1
1.7%
4122 1
1.7%
3520 1
1.7%
2305 1
1.7%
376 1
1.7%
336 1
1.7%
324 1
1.7%

2020년도충남
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct22
Distinct (%)37.9%
Missing1
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean62.5
Minimum0
Maximum1668
Zeros30
Zeros (%)50.8%
Negative0
Negative (%)0.0%
Memory size663.0 B
2024-01-10T06:06:43.802211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q39.75
95-th percentile359.2
Maximum1668
Range1668
Interquartile range (IQR)9.75

Descriptive statistics

Standard deviation235.67873
Coefficient of variation (CV)3.7708597
Kurtosis39.089183
Mean62.5
Median Absolute Deviation (MAD)0
Skewness5.9092101
Sum3625
Variance55544.465
MonotonicityNot monotonic
2024-01-10T06:06:43.914227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 30
50.8%
1 4
 
6.8%
3 2
 
3.4%
2 2
 
3.4%
18 2
 
3.4%
6 2
 
3.4%
21 1
 
1.7%
11 1
 
1.7%
1668 1
 
1.7%
261 1
 
1.7%
Other values (12) 12
 
20.3%
ValueCountFrequency (%)
0 30
50.8%
1 4
 
6.8%
2 2
 
3.4%
3 2
 
3.4%
4 1
 
1.7%
6 2
 
3.4%
7 1
 
1.7%
9 1
 
1.7%
10 1
 
1.7%
11 1
 
1.7%
ValueCountFrequency (%)
1668 1
1.7%
457 1
1.7%
366 1
1.7%
358 1
1.7%
261 1
1.7%
250 1
1.7%
76 1
1.7%
26 1
1.7%
22 1
1.7%
21 1
1.7%

Interactions

2024-01-10T06:06:36.829008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
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2024-01-10T06:06:15.382387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:16.908785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:18.510532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:19.997527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:21.759061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:23.330293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:24.918466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:26.839528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:28.420860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:30.016459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:31.792352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:33.190253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:34.606096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:36.274229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:37.805852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:10.437873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:11.959617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:13.563311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:15.467773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:16.993274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:18.604567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:20.075728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:21.846699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:23.420703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:25.006835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:26.925596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:28.509319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:30.109623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:31.873540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:33.268716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:34.683067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:36.356894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:37.891899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:10.511894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:12.041159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:13.648341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:15.550749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:17.094745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:18.700053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:20.145512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:21.936491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:23.495435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:25.090594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:27.007490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:28.605893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:30.188835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:31.946305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:33.339256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:34.763067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:36.433972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:37.982639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:10.594860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:12.120304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:13.728668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:15.636495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:17.193928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:18.802147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:20.489377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:22.022917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:23.576318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:25.173213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:27.092787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:28.686016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:30.272513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:32.026883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:33.418717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:34.845523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:36.518058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:38.061075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:10.668701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:12.189286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:13.824579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:15.714964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:17.278464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:18.895565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:20.549502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:22.102335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:23.646518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:25.257967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:27.166778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:28.771387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:30.348884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:32.097199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:33.485470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:34.917707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:36.593802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:38.142325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:10.745893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:12.266867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:13.913295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:15.795933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:17.366853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:19.001854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:20.626057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:22.184869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:23.723398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:25.363260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:27.250620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:28.858479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:30.424580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:32.177937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:33.564335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:34.998777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:36.669171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:38.242328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:10.822320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:12.342893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:14.005347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:15.875946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:17.440075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:19.087052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:20.700116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:22.274235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:23.800717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:25.706176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:27.333874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:28.961114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:30.510647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:32.256283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:33.636775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:35.076608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:06:36.747038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T06:06:44.036924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분2012년도 전국2012년도 충남2013년도 전국2013년도 충남2014년도 전국2014년도 충남2015년도 전국2015년도 충남2016년도 전국2016년도 충남2017년도전국2017년도충남2018년도전국2018년도충남2019년도전국2019년도충남2020년도전국2020년도충남
구분1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
2012년도 전국1.0001.0001.0001.0001.0000.9950.9801.0000.9800.9951.0000.9950.9950.7290.9800.9270.8790.7020.781
2012년도 충남1.0001.0001.0001.0001.0000.9950.9801.0000.9800.9951.0000.9950.9950.7290.9800.9270.8790.7020.781
2013년도 전국1.0001.0001.0001.0001.0000.9950.9801.0000.9800.9951.0000.9950.9950.7290.9800.9270.8790.7020.781
2013년도 충남1.0001.0001.0001.0001.0000.9950.9801.0000.9800.9951.0000.9950.9950.7290.9800.9270.8790.7020.781
2014년도 전국1.0000.9950.9950.9950.9951.0000.9891.0000.9891.0001.0000.9891.0000.7590.9790.9270.9230.7030.695
2014년도 충남1.0000.9800.9800.9800.9800.9891.0001.0001.0000.9891.0000.9890.9890.7590.9950.9030.8290.4050.782
2015년도 전국1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.8220.9010.6970.9810.3820.471
2015년도 충남1.0000.9800.9800.9800.9800.9891.0001.0001.0000.9891.0000.9890.9890.7590.9950.9030.8290.4050.782
2016년도 전국1.0000.9950.9950.9950.9951.0000.9891.0000.9891.0001.0000.9891.0000.7590.9790.9270.9230.7030.695
2016년도 충남1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.9840.9780.9600.9580.4340.734
2017년도전국1.0000.9950.9950.9950.9950.9890.9891.0000.9890.9891.0001.0000.9890.7920.9790.9030.8290.4050.695
2017년도충남1.0000.9950.9950.9950.9951.0000.9891.0000.9891.0001.0000.9891.0000.7590.9790.9270.9230.7030.695
2018년도전국1.0000.7290.7290.7290.7290.7590.7590.8220.7590.7590.9840.7920.7591.0000.8220.8560.8390.5690.419
2018년도충남1.0000.9800.9800.9800.9800.9790.9950.9010.9950.9790.9780.9790.9790.8221.0000.9240.8800.6960.836
2019년도전국1.0000.9270.9270.9270.9270.9270.9030.6970.9030.9270.9600.9030.9270.8560.9241.0000.8920.8770.894
2019년도충남1.0000.8790.8790.8790.8790.9230.8290.9810.8290.9230.9580.8290.9230.8390.8800.8921.0000.4710.680
2020년도전국1.0000.7020.7020.7020.7020.7030.4050.3820.4050.7030.4340.4050.7030.5690.6960.8770.4711.0000.986
2020년도충남1.0000.7810.7810.7810.7810.6950.7820.4710.7820.6950.7340.6950.6950.4190.8360.8940.6800.9861.000
2024-01-10T06:06:44.241689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2012년도 전국2012년도 충남2013년도 전국2013년도 충남2014년도 전국2014년도 충남2015년도 전국2015년도 충남2016년도 전국2016년도 충남2017년도전국2017년도충남2018년도전국2018년도충남2019년도전국2019년도충남2020년도전국2020년도충남
2012년도 전국1.0000.9030.9380.8640.9120.9050.7850.7000.7840.7500.6430.5870.6550.6210.6600.6250.5640.553
2012년도 충남0.9031.0000.8500.8710.8310.8010.7550.7160.7510.7740.6230.6190.6730.6520.6410.6120.5720.628
2013년도 전국0.9380.8501.0000.8910.9600.9280.8060.7020.8310.7960.6440.6020.6880.6560.7010.6600.5760.564
2013년도 충남0.8640.8710.8911.0000.8420.8270.7120.6940.7330.7320.6460.6440.6390.6180.5950.5770.5230.590
2014년도 전국0.9120.8310.9600.8421.0000.9230.8560.7520.8720.8510.6780.6430.7340.7160.7580.7200.6390.601
2014년도 충남0.9050.8010.9280.8270.9231.0000.7790.7610.7950.8050.6120.5800.6710.6810.6920.7230.5640.560
2015년도 전국0.7850.7550.8060.7120.8560.7791.0000.9090.9380.9020.7430.6950.8250.7600.8070.7700.7250.673
2015년도 충남0.7000.7160.7020.6940.7520.7610.9091.0000.8430.8620.6700.6620.7730.7420.7260.7770.6580.674
2016년도 전국0.7840.7510.8310.7330.8720.7950.9380.8431.0000.9310.7820.7290.8560.7860.8620.7970.7220.700
2016년도 충남0.7500.7740.7960.7320.8510.8050.9020.8620.9311.0000.7500.7490.8290.8130.8290.8310.7200.742
2017년도전국0.6430.6230.6440.6460.6780.6120.7430.6700.7820.7501.0000.9390.8860.8360.8720.8300.7590.755
2017년도충남0.5870.6190.6020.6440.6430.5800.6950.6620.7290.7490.9391.0000.8380.8190.8240.8120.7280.790
2018년도전국0.6550.6730.6880.6390.7340.6710.8250.7730.8560.8290.8860.8381.0000.9240.9620.9200.8510.838
2018년도충남0.6210.6520.6560.6180.7160.6810.7600.7420.7860.8130.8360.8190.9241.0000.9090.9630.8200.845
2019년도전국0.6600.6410.7010.5950.7580.6920.8070.7260.8620.8290.8720.8240.9620.9091.0000.9210.8640.803
2019년도충남0.6250.6120.6600.5770.7200.7230.7700.7770.7970.8310.8300.8120.9200.9630.9211.0000.8100.826
2020년도전국0.5640.5720.5760.5230.6390.5640.7250.6580.7220.7200.7590.7280.8510.8200.8640.8101.0000.916
2020년도충남0.5530.6280.5640.5900.6010.5600.6730.6740.7000.7420.7550.7900.8380.8450.8030.8260.9161.000

Missing values

2024-01-10T06:06:38.396760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:06:38.621032image/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.
2024-01-10T06:06:38.741513image/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

구분2012년도 전국2012년도 충남2013년도 전국2013년도 충남2014년도 전국2014년도 충남2015년도 전국2015년도 충남2016년도 전국2016년도 충남2017년도전국2017년도충남2018년도전국2018년도충남2019년도전국2019년도충남2020년도전국2020년도충남
0콜 레 라003100004050201000
1장티푸스12921561425119121812111128321371055716
2파라티푸스582542371442561732470610954
3세균성이질9052948110288511351112191191612413
4장출혈성대장균감염5826111112711104413811216163431810
5A형간염119759867491307711804574679270441932724372071763814393520250
6디프테리아000000000000000000
7백 일 해2304361881220571294318598020507211222
8파 상 풍171220230220242342312333306
9홍 역301070442137018371152283760
구분2012년도 전국2012년도 충남2013년도 전국2013년도 충남2014년도 전국2014년도 충남2015년도 전국2015년도 충남2016년도 전국2016년도 충남2017년도전국2017년도충남2018년도전국2018년도충남2019년도전국2019년도충남2020년도전국2020년도충남
49바이러스성출혈열00000000009613000000
50신종인플루엔자000000000000000000
51웨스트나일열1000000000313000000
52라임병30110131912700023121171
53진드기매개뇌000000000020000000
54유비저002020404051208010
55치쿤구니야열00201020101003016010
56중증열성혈소판00362552795165927230259222232424221
57중동호흡기증후군000000185160000100010
58지카바이러스감염증00000000160111309000