Overview

Dataset statistics

Number of variables20
Number of observations54
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.5 KiB
Average record size in memory180.4 B

Variable types

Text2
Numeric18

Dataset

Description언론인 의식조사 관련 "언론이 비중있게 다뤄야하는 사회 현안"에 관한 자료입니다. 자세한 내용은 재단 홈페이지에 방문하여 확인 바랍니다.
Author한국언론진흥재단
URLhttps://www.data.go.kr/data/15060164/fileData.do

Alerts

성별_이념_세대 갈등 해소 is highly overall correlated with 지역 균형 발전 and 2 other fieldsHigh correlation
지역 균형 발전 is highly overall correlated with 성별_이념_세대 갈등 해소 and 1 other fieldsHigh correlation
검찰 개혁 is highly overall correlated with 언론 개혁High correlation
언론 개혁 is highly overall correlated with 성별_이념_세대 갈등 해소 and 3 other fieldsHigh correlation
국제_외교 문제 is highly overall correlated with 언론 개혁High correlation
통일_남북관계 개선 is highly overall correlated with 성별_이념_세대 갈등 해소 and 1 other fieldsHigh correlation
정치 개혁 is highly overall correlated with 통일_남북관계 개선High correlation
구분 has unique valuesUnique
지역 균형 발전 has 1 (1.9%) zerosZeros
부동산_주거 안정 has 1 (1.9%) zerosZeros
기후 및 환경 위기 대응 has 1 (1.9%) zerosZeros
언론 개혁 has 1 (1.9%) zerosZeros
국민 안전 증진 has 1 (1.9%) zerosZeros
국제_외교 문제 has 1 (1.9%) zerosZeros
통일_남북관계 개선 has 3 (5.6%) zerosZeros
교육 문제 has 3 (5.6%) zerosZeros
기타 has 13 (24.1%) zerosZeros

Reproduction

Analysis started2024-03-14 14:02:14.071433
Analysis finished2024-03-14 14:03:31.042046
Duration1 minute and 16.97 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Text

UNIQUE 

Distinct54
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size560.0 B
2024-03-14T23:03:31.844412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.4259259
Min length3

Characters and Unicode

Total characters239
Distinct characters28
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

Unique54 ?
Unique (%)100.0%

Sample

1st row성별1
2nd row성별2
3rd row연령1
4th row연령2
5th row연령3
ValueCountFrequency (%)
성별1 1
 
1.9%
소속부서16 1
 
1.9%
권역1 1
 
1.9%
소속부서6 1
 
1.9%
소속부서7 1
 
1.9%
소속부서8 1
 
1.9%
소속부서9 1
 
1.9%
소속부서10 1
 
1.9%
소속부서11 1
 
1.9%
소속부서12 1
 
1.9%
Other values (44) 44
81.5%
2024-03-14T23:03:33.261638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
29
12.1%
29
12.1%
1 21
 
8.8%
18
 
7.5%
18
 
7.5%
15
 
6.3%
15
 
6.3%
2 9
 
3.8%
7
 
2.9%
4 7
 
2.9%
Other values (18) 71
29.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 174
72.8%
Decimal Number 65
 
27.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
29
16.7%
29
16.7%
18
10.3%
18
10.3%
15
8.6%
15
8.6%
7
 
4.0%
7
 
4.0%
5
 
2.9%
5
 
2.9%
Other values (8) 26
14.9%
Decimal Number
ValueCountFrequency (%)
1 21
32.3%
2 9
13.8%
4 7
 
10.8%
3 7
 
10.8%
5 6
 
9.2%
6 4
 
6.2%
7 4
 
6.2%
8 3
 
4.6%
9 2
 
3.1%
0 2
 
3.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 174
72.8%
Common 65
 
27.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
29
16.7%
29
16.7%
18
10.3%
18
10.3%
15
8.6%
15
8.6%
7
 
4.0%
7
 
4.0%
5
 
2.9%
5
 
2.9%
Other values (8) 26
14.9%
Common
ValueCountFrequency (%)
1 21
32.3%
2 9
13.8%
4 7
 
10.8%
3 7
 
10.8%
5 6
 
9.2%
6 4
 
6.2%
7 4
 
6.2%
8 3
 
4.6%
9 2
 
3.1%
0 2
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 174
72.8%
ASCII 65
 
27.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
29
16.7%
29
16.7%
18
10.3%
18
10.3%
15
8.6%
15
8.6%
7
 
4.0%
7
 
4.0%
5
 
2.9%
5
 
2.9%
Other values (8) 26
14.9%
ASCII
ValueCountFrequency (%)
1 21
32.3%
2 9
13.8%
4 7
 
10.8%
3 7
 
10.8%
5 6
 
9.2%
6 4
 
6.2%
7 4
 
6.2%
8 3
 
4.6%
9 2
 
3.1%
0 2
 
3.1%
Distinct52
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Memory size560.0 B
2024-03-14T23:03:34.091597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length5.5555556
Min length2

Characters and Unicode

Total characters300
Distinct characters104
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)92.6%

Sample

1st row남자
2nd row여자
3rd row20대
4th row30~34세
5th row35~39세
ValueCountFrequency (%)
뉴스통신사 2
 
3.4%
이상 2
 
3.4%
인터넷언론사 2
 
3.4%
1
 
1.7%
영상부 1
 
1.7%
남자 1
 
1.7%
기타 1
 
1.7%
국방/통일/북한 1
 
1.7%
편집(편성)/교열부 1
 
1.7%
여론/독자/심의부 1
 
1.7%
Other values (45) 45
77.6%
2024-03-14T23:03:35.463714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 20
 
6.7%
14
 
4.7%
11
 
3.7%
10
 
3.3%
4 8
 
2.7%
~ 8
 
2.7%
8
 
2.7%
7
 
2.3%
7
 
2.3%
0 7
 
2.3%
Other values (94) 200
66.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 223
74.3%
Decimal Number 36
 
12.0%
Other Punctuation 20
 
6.7%
Math Symbol 8
 
2.7%
Uppercase Letter 5
 
1.7%
Space Separator 4
 
1.3%
Close Punctuation 2
 
0.7%
Open Punctuation 2
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
14
 
6.3%
11
 
4.9%
10
 
4.5%
8
 
3.6%
7
 
3.1%
7
 
3.1%
6
 
2.7%
5
 
2.2%
5
 
2.2%
5
 
2.2%
Other values (79) 145
65.0%
Decimal Number
ValueCountFrequency (%)
4 8
22.2%
0 7
19.4%
5 5
13.9%
1 5
13.9%
9 4
11.1%
3 4
11.1%
2 2
 
5.6%
6 1
 
2.8%
Uppercase Letter
ValueCountFrequency (%)
I 4
80.0%
T 1
 
20.0%
Other Punctuation
ValueCountFrequency (%)
/ 20
100.0%
Math Symbol
ValueCountFrequency (%)
~ 8
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 223
74.3%
Common 72
 
24.0%
Latin 5
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
14
 
6.3%
11
 
4.9%
10
 
4.5%
8
 
3.6%
7
 
3.1%
7
 
3.1%
6
 
2.7%
5
 
2.2%
5
 
2.2%
5
 
2.2%
Other values (79) 145
65.0%
Common
ValueCountFrequency (%)
/ 20
27.8%
4 8
 
11.1%
~ 8
 
11.1%
0 7
 
9.7%
5 5
 
6.9%
1 5
 
6.9%
9 4
 
5.6%
4
 
5.6%
3 4
 
5.6%
) 2
 
2.8%
Other values (3) 5
 
6.9%
Latin
ValueCountFrequency (%)
I 4
80.0%
T 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 223
74.3%
ASCII 77
 
25.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 20
26.0%
4 8
 
10.4%
~ 8
 
10.4%
0 7
 
9.1%
5 5
 
6.5%
1 5
 
6.5%
9 4
 
5.2%
4
 
5.2%
3 4
 
5.2%
I 4
 
5.2%
Other values (5) 8
 
10.4%
Hangul
ValueCountFrequency (%)
14
 
6.3%
11
 
4.9%
10
 
4.5%
8
 
3.6%
7
 
3.1%
7
 
3.1%
6
 
2.7%
5
 
2.2%
5
 
2.2%
5
 
2.2%
Other values (79) 145
65.0%

사례수
Real number (ℝ)

Distinct50
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean297.92593
Minimum8
Maximum1392
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-14T23:03:35.855628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile19.85
Q177.25
median206
Q3404.25
95-th percentile1034.45
Maximum1392
Range1384
Interquartile range (IQR)327

Descriptive statistics

Standard deviation312.37307
Coefficient of variation (CV)1.0484924
Kurtosis4.5902915
Mean297.92593
Median Absolute Deviation (MAD)159
Skewness2.0456416
Sum16088
Variance97576.938
MonotonicityNot monotonic
2024-03-14T23:03:36.248643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
457 3
 
5.6%
160 2
 
3.7%
406 2
 
3.7%
1376 1
 
1.9%
71 1
 
1.9%
12 1
 
1.9%
87 1
 
1.9%
14 1
 
1.9%
34 1
 
1.9%
52 1
 
1.9%
Other values (40) 40
74.1%
ValueCountFrequency (%)
8 1
1.9%
12 1
1.9%
14 1
1.9%
23 1
1.9%
26 1
1.9%
33 1
1.9%
34 1
1.9%
44 1
1.9%
50 1
1.9%
52 1
1.9%
ValueCountFrequency (%)
1392 1
 
1.9%
1376 1
 
1.9%
1065 1
 
1.9%
1018 1
 
1.9%
635 1
 
1.9%
619 1
 
1.9%
457 3
5.6%
449 1
 
1.9%
432 1
 
1.9%
426 1
 
1.9%
Distinct49
Distinct (%)90.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.168519
Minimum13.8
Maximum63.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-14T23:03:36.719653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum13.8
5-th percentile18.495
Q124.925
median29.5
Q332.175
95-th percentile40.325
Maximum63.6
Range49.8
Interquartile range (IQR)7.25

Descriptive statistics

Standard deviation8.0098718
Coefficient of variation (CV)0.27460674
Kurtosis5.6883662
Mean29.168519
Median Absolute Deviation (MAD)3.25
Skewness1.4533383
Sum1575.1
Variance64.158047
MonotonicityNot monotonic
2024-03-14T23:03:36.967640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
31.2 2
 
3.7%
29.6 2
 
3.7%
29.4 2
 
3.7%
31.3 2
 
3.7%
30.1 2
 
3.7%
32.5 1
 
1.9%
26.4 1
 
1.9%
14.3 1
 
1.9%
32.4 1
 
1.9%
28.8 1
 
1.9%
Other values (39) 39
72.2%
ValueCountFrequency (%)
13.8 1
1.9%
14.3 1
1.9%
18.3 1
1.9%
18.6 1
1.9%
18.7 1
1.9%
20.0 1
1.9%
21.2 1
1.9%
21.3 1
1.9%
22.5 1
1.9%
22.7 1
1.9%
ValueCountFrequency (%)
63.6 1
1.9%
46.8 1
1.9%
42.6 1
1.9%
39.1 1
1.9%
38.5 1
1.9%
37.5 1
1.9%
35.6 1
1.9%
35.0 1
1.9%
33.1 1
1.9%
32.8 1
1.9%
Distinct41
Distinct (%)75.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.998148
Minimum7.1
Maximum33.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-14T23:03:37.354264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.1
5-th percentile12.695
Q115.525
median17.5
Q319.5
95-th percentile26.14
Maximum33.3
Range26.2
Interquartile range (IQR)3.975

Descriptive statistics

Standard deviation4.2517251
Coefficient of variation (CV)0.23623125
Kurtosis2.9383034
Mean17.998148
Median Absolute Deviation (MAD)2
Skewness0.99112513
Sum971.9
Variance18.077166
MonotonicityNot monotonic
2024-03-14T23:03:37.762334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
17.5 4
 
7.4%
17.6 3
 
5.6%
19.6 2
 
3.7%
15.3 2
 
3.7%
18.4 2
 
3.7%
19.5 2
 
3.7%
15.2 2
 
3.7%
12.8 2
 
3.7%
15.6 2
 
3.7%
16.9 2
 
3.7%
Other values (31) 31
57.4%
ValueCountFrequency (%)
7.1 1
1.9%
12.1 1
1.9%
12.5 1
1.9%
12.8 2
3.7%
13.0 1
1.9%
14.2 1
1.9%
14.8 1
1.9%
15.2 2
3.7%
15.3 2
3.7%
15.4 1
1.9%
ValueCountFrequency (%)
33.3 1
1.9%
27.3 1
1.9%
26.4 1
1.9%
26.0 1
1.9%
25.0 1
1.9%
23.9 1
1.9%
21.6 1
1.9%
21.5 1
1.9%
21.2 1
1.9%
20.7 1
1.9%

경제 양극화 해소
Real number (ℝ)

Distinct45
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.172222
Minimum21.5
Maximum50
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-14T23:03:38.142384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21.5
5-th percentile26.76
Q132.2
median34.05
Q336.8
95-th percentile40.935
Maximum50
Range28.5
Interquartile range (IQR)4.6

Descriptive statistics

Standard deviation4.846684
Coefficient of variation (CV)0.1418311
Kurtosis1.956223
Mean34.172222
Median Absolute Deviation (MAD)2.65
Skewness0.17821336
Sum1845.3
Variance23.490346
MonotonicityNot monotonic
2024-03-14T23:03:38.460843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
33.8 4
 
7.4%
35.7 3
 
5.6%
37.4 2
 
3.7%
37.9 2
 
3.7%
35.3 2
 
3.7%
32.8 2
 
3.7%
30.3 1
 
1.9%
33.0 1
 
1.9%
40.2 1
 
1.9%
28.6 1
 
1.9%
Other values (35) 35
64.8%
ValueCountFrequency (%)
21.5 1
1.9%
23.3 1
1.9%
26.5 1
1.9%
26.9 1
1.9%
27.3 1
1.9%
27.5 1
1.9%
28.6 1
1.9%
29.6 1
1.9%
29.8 1
1.9%
30.3 1
1.9%
ValueCountFrequency (%)
50.0 1
1.9%
44.2 1
1.9%
42.3 1
1.9%
40.2 1
1.9%
40.1 1
1.9%
38.7 1
1.9%
37.9 2
3.7%
37.8 1
1.9%
37.5 1
1.9%
37.4 2
3.7%

성별_이념_세대 갈등 해소
Real number (ℝ)

HIGH CORRELATION 

Distinct49
Distinct (%)90.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.259259
Minimum6.1
Maximum37.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-14T23:03:38.696518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6.1
5-th percentile12.725
Q119.85
median24.15
Q327.35
95-th percentile32.4
Maximum37.2
Range31.1
Interquartile range (IQR)7.5

Descriptive statistics

Standard deviation6.4425332
Coefficient of variation (CV)0.27698789
Kurtosis0.044184871
Mean23.259259
Median Absolute Deviation (MAD)4.1
Skewness-0.39064909
Sum1256
Variance41.506233
MonotonicityNot monotonic
2024-03-14T23:03:38.938911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
25.0 4
 
7.4%
32.4 2
 
3.7%
22.2 2
 
3.7%
12.9 1
 
1.9%
26.4 1
 
1.9%
21.4 1
 
1.9%
14.7 1
 
1.9%
28.8 1
 
1.9%
19.2 1
 
1.9%
31.4 1
 
1.9%
Other values (39) 39
72.2%
ValueCountFrequency (%)
6.1 1
1.9%
9.3 1
1.9%
12.4 1
1.9%
12.9 1
1.9%
13.8 1
1.9%
14.7 1
1.9%
15.0 1
1.9%
15.6 1
1.9%
15.9 1
1.9%
16.8 1
1.9%
ValueCountFrequency (%)
37.2 1
1.9%
33.2 1
1.9%
32.4 2
3.7%
31.9 1
1.9%
31.4 1
1.9%
31.3 1
1.9%
30.4 1
1.9%
30.0 1
1.9%
28.8 1
1.9%
28.6 1
1.9%

지역 균형 발전
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct49
Distinct (%)90.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.409259
Minimum0
Maximum58.5
Zeros1
Zeros (%)1.9%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-14T23:03:39.186522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile8.3
Q116.875
median22.2
Q327.3
95-th percentile49.22
Maximum58.5
Range58.5
Interquartile range (IQR)10.425

Descriptive statistics

Standard deviation11.389838
Coefficient of variation (CV)0.48655268
Kurtosis1.5248133
Mean23.409259
Median Absolute Deviation (MAD)5.15
Skewness0.97879087
Sum1264.1
Variance129.7284
MonotonicityNot monotonic
2024-03-14T23:03:39.513792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
27.3 2
 
3.7%
23.1 2
 
3.7%
18.1 2
 
3.7%
17.7 2
 
3.7%
8.3 2
 
3.7%
29.1 1
 
1.9%
20.7 1
 
1.9%
28.6 1
 
1.9%
35.3 1
 
1.9%
11.5 1
 
1.9%
Other values (39) 39
72.2%
ValueCountFrequency (%)
0.0 1
1.9%
7.0 1
1.9%
8.3 2
3.7%
9.9 1
1.9%
11.5 1
1.9%
12.0 1
1.9%
12.4 1
1.9%
13.0 1
1.9%
13.1 1
1.9%
13.6 1
1.9%
ValueCountFrequency (%)
58.5 1
1.9%
50.1 1
1.9%
50.0 1
1.9%
48.8 1
1.9%
42.4 1
1.9%
35.5 1
1.9%
35.3 1
1.9%
34.6 1
1.9%
31.9 1
1.9%
29.1 1
1.9%
Distinct43
Distinct (%)79.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.012963
Minimum14.3
Maximum41.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-14T23:03:39.911986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum14.3
5-th percentile17.53
Q124.925
median28.35
Q331.725
95-th percentile36.105
Maximum41.9
Range27.6
Interquartile range (IQR)6.8

Descriptive statistics

Standard deviation5.8740891
Coefficient of variation (CV)0.20969182
Kurtosis0.23906886
Mean28.012963
Median Absolute Deviation (MAD)3.45
Skewness-0.14224911
Sum1512.7
Variance34.504923
MonotonicityNot monotonic
2024-03-14T23:03:40.320441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
29.1 3
 
5.6%
25.0 3
 
5.6%
24.4 3
 
5.6%
31.5 2
 
3.7%
31.8 2
 
3.7%
30.0 2
 
3.7%
35.2 2
 
3.7%
27.3 2
 
3.7%
27.6 1
 
1.9%
14.3 1
 
1.9%
Other values (33) 33
61.1%
ValueCountFrequency (%)
14.3 1
 
1.9%
15.0 1
 
1.9%
17.4 1
 
1.9%
17.6 1
 
1.9%
18.0 1
 
1.9%
20.6 1
 
1.9%
21.0 1
 
1.9%
21.7 1
 
1.9%
24.2 1
 
1.9%
24.4 3
5.6%
ValueCountFrequency (%)
41.9 1
1.9%
40.4 1
1.9%
37.6 1
1.9%
35.3 1
1.9%
35.2 2
3.7%
35.1 1
1.9%
34.6 1
1.9%
33.8 1
1.9%
33.7 1
1.9%
33.0 1
1.9%

부동산_주거 안정
Real number (ℝ)

ZEROS 

Distinct45
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.551852
Minimum0
Maximum21.7
Zeros1
Zeros (%)1.9%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-14T23:03:40.732302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.8
Q19.55
median11.55
Q313.975
95-th percentile18.65
Maximum21.7
Range21.7
Interquartile range (IQR)4.425

Descriptive statistics

Standard deviation4.1144816
Coefficient of variation (CV)0.35617507
Kurtosis1.1170634
Mean11.551852
Median Absolute Deviation (MAD)2.4
Skewness-0.14649955
Sum623.8
Variance16.928959
MonotonicityNot monotonic
2024-03-14T23:03:41.151488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
14.3 2
 
3.7%
3.8 2
 
3.7%
13.6 2
 
3.7%
11.3 2
 
3.7%
10.8 2
 
3.7%
11.9 2
 
3.7%
12.6 2
 
3.7%
13.0 2
 
3.7%
20.6 2
 
3.7%
11.4 1
 
1.9%
Other values (35) 35
64.8%
ValueCountFrequency (%)
0.0 1
1.9%
3.7 1
1.9%
3.8 2
3.7%
6.0 1
1.9%
6.4 1
1.9%
6.9 1
1.9%
7.2 1
1.9%
7.8 1
1.9%
8.3 1
1.9%
8.6 1
1.9%
ValueCountFrequency (%)
21.7 1
1.9%
20.6 2
3.7%
17.6 1
1.9%
15.2 1
1.9%
15.1 1
1.9%
15.0 1
1.9%
14.9 1
1.9%
14.7 1
1.9%
14.6 1
1.9%
14.3 2
3.7%

기후 및 환경 위기 대응
Real number (ℝ)

ZEROS 

Distinct44
Distinct (%)81.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.622222
Minimum0
Maximum42.9
Zeros1
Zeros (%)1.9%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-14T23:03:41.563766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile14.455
Q119.875
median22.4
Q325.6
95-th percentile31.31
Maximum42.9
Range42.9
Interquartile range (IQR)5.725

Descriptive statistics

Standard deviation6.070332
Coefficient of variation (CV)0.26833491
Kurtosis4.5236447
Mean22.622222
Median Absolute Deviation (MAD)2.8
Skewness-0.21794863
Sum1221.6
Variance36.848931
MonotonicityNot monotonic
2024-03-14T23:03:41.986570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
25.6 3
 
5.6%
19.6 2
 
3.7%
26.6 2
 
3.7%
23.9 2
 
3.7%
25.0 2
 
3.7%
20.4 2
 
3.7%
21.7 2
 
3.7%
24.0 2
 
3.7%
24.6 2
 
3.7%
23.4 1
 
1.9%
Other values (34) 34
63.0%
ValueCountFrequency (%)
0.0 1
1.9%
13.0 1
1.9%
14.0 1
1.9%
14.7 1
1.9%
15.7 1
1.9%
16.1 1
1.9%
16.7 1
1.9%
17.0 1
1.9%
17.7 1
1.9%
18.1 1
1.9%
ValueCountFrequency (%)
42.9 1
1.9%
34.6 1
1.9%
31.7 1
1.9%
31.1 1
1.9%
29.0 1
1.9%
28.8 1
1.9%
28.3 1
1.9%
26.8 1
1.9%
26.6 2
3.7%
26.0 1
1.9%

검찰 개혁
Real number (ℝ)

HIGH CORRELATION 

Distinct43
Distinct (%)79.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.042593
Minimum3.8
Maximum26.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-14T23:03:42.383521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.8
5-th percentile8.025
Q110.75
median14.85
Q318.375
95-th percentile23.245
Maximum26.6
Range22.8
Interquartile range (IQR)7.625

Descriptive statistics

Standard deviation5.1694897
Coefficient of variation (CV)0.34365683
Kurtosis-0.43357763
Mean15.042593
Median Absolute Deviation (MAD)4.1
Skewness0.2163243
Sum812.3
Variance26.723623
MonotonicityNot monotonic
2024-03-14T23:03:42.793239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
15.8 3
 
5.6%
10.5 2
 
3.7%
14.7 2
 
3.7%
14.0 2
 
3.7%
9.1 2
 
3.7%
19.7 2
 
3.7%
16.3 2
 
3.7%
13.8 2
 
3.7%
16.7 2
 
3.7%
8.2 2
 
3.7%
Other values (33) 33
61.1%
ValueCountFrequency (%)
3.8 1
1.9%
6.9 1
1.9%
7.7 1
1.9%
8.2 2
3.7%
8.6 1
1.9%
9.1 2
3.7%
9.2 1
1.9%
9.6 1
1.9%
9.8 1
1.9%
10.1 1
1.9%
ValueCountFrequency (%)
26.6 1
1.9%
26.3 1
1.9%
23.7 1
1.9%
23.0 1
1.9%
22.5 1
1.9%
21.7 1
1.9%
21.6 1
1.9%
21.4 1
1.9%
20.9 1
1.9%
20.5 1
1.9%

언론 개혁
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct45
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.359259
Minimum0
Maximum30.8
Zeros1
Zeros (%)1.9%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-14T23:03:43.185234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4.325
Q18.85
median10.2
Q314.025
95-th percentile20.175
Maximum30.8
Range30.8
Interquartile range (IQR)5.175

Descriptive statistics

Standard deviation5.0900391
Coefficient of variation (CV)0.44809604
Kurtosis3.3369495
Mean11.359259
Median Absolute Deviation (MAD)2
Skewness1.1392326
Sum613.4
Variance25.908498
MonotonicityNot monotonic
2024-03-14T23:03:43.606219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
9.4 3
 
5.6%
9.8 2
 
3.7%
9.0 2
 
3.7%
10.6 2
 
3.7%
7.7 2
 
3.7%
10.3 2
 
3.7%
16.0 2
 
3.7%
9.5 2
 
3.7%
13.2 1
 
1.9%
20.5 1
 
1.9%
Other values (35) 35
64.8%
ValueCountFrequency (%)
0.0 1
1.9%
2.6 1
1.9%
4.0 1
1.9%
4.5 1
1.9%
6.0 1
1.9%
6.5 1
1.9%
6.9 1
1.9%
7.7 2
3.7%
8.2 1
1.9%
8.3 1
1.9%
ValueCountFrequency (%)
30.8 1
1.9%
22.7 1
1.9%
20.5 1
1.9%
20.0 1
1.9%
16.9 1
1.9%
16.7 1
1.9%
16.3 1
1.9%
16.2 1
1.9%
16.0 2
3.7%
15.9 1
1.9%
Distinct40
Distinct (%)74.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.688889
Minimum20
Maximum50
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-14T23:03:43.999600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile21.33
Q125
median28.7
Q331.6
95-th percentile35.6
Maximum50
Range30
Interquartile range (IQR)6.6

Descriptive statistics

Standard deviation5.2394608
Coefficient of variation (CV)0.18263032
Kurtosis3.7874536
Mean28.688889
Median Absolute Deviation (MAD)3.45
Skewness1.1380279
Sum1549.2
Variance27.45195
MonotonicityNot monotonic
2024-03-14T23:03:44.416154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
25.0 3
 
5.6%
28.7 3
 
5.6%
29.4 3
 
5.6%
31.3 2
 
3.7%
27.6 2
 
3.7%
26.9 2
 
3.7%
26.0 2
 
3.7%
22.7 2
 
3.7%
24.4 2
 
3.7%
36.9 2
 
3.7%
Other values (30) 31
57.4%
ValueCountFrequency (%)
20.0 1
1.9%
20.6 1
1.9%
21.2 1
1.9%
21.4 1
1.9%
21.5 1
1.9%
21.6 1
1.9%
22.7 2
3.7%
23.4 1
1.9%
24.4 2
3.7%
24.9 1
1.9%
ValueCountFrequency (%)
50.0 1
1.9%
36.9 2
3.7%
34.9 1
1.9%
34.8 2
3.7%
33.9 1
1.9%
33.3 1
1.9%
32.9 1
1.9%
32.8 1
1.9%
32.6 1
1.9%
32.4 1
1.9%

국민 안전 증진
Real number (ℝ)

ZEROS 

Distinct44
Distinct (%)81.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.0425926
Minimum0
Maximum25
Zeros1
Zeros (%)1.9%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-14T23:03:45.020988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.13
Q15.75
median8
Q39.925
95-th percentile11.67
Maximum25
Range25
Interquartile range (IQR)4.175

Descriptive statistics

Standard deviation3.7075447
Coefficient of variation (CV)0.46098875
Kurtosis7.6802427
Mean8.0425926
Median Absolute Deviation (MAD)2.1
Skewness1.7539322
Sum434.3
Variance13.745887
MonotonicityNot monotonic
2024-03-14T23:03:45.455189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
10.1 3
 
5.6%
9.2 3
 
5.6%
10.6 3
 
5.6%
6.7 2
 
3.7%
8.1 2
 
3.7%
7.4 2
 
3.7%
7.9 2
 
3.7%
16.9 1
 
1.9%
10.3 1
 
1.9%
7.1 1
 
1.9%
Other values (34) 34
63.0%
ValueCountFrequency (%)
0.0 1
1.9%
2.8 1
1.9%
3.0 1
1.9%
3.2 1
1.9%
3.9 1
1.9%
4.0 1
1.9%
4.1 1
1.9%
4.5 1
1.9%
5.2 1
1.9%
5.3 1
1.9%
ValueCountFrequency (%)
25.0 1
 
1.9%
16.9 1
 
1.9%
11.8 1
 
1.9%
11.6 1
 
1.9%
11.5 1
 
1.9%
11.0 1
 
1.9%
10.6 3
5.6%
10.3 1
 
1.9%
10.1 3
5.6%
10.0 1
 
1.9%

국제_외교 문제
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct45
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.0296296
Minimum0
Maximum34
Zeros1
Zeros (%)1.9%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-14T23:03:45.851377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.365
Q14.9
median6.8
Q38.225
95-th percentile25.665
Maximum34
Range34
Interquartile range (IQR)3.325

Descriptive statistics

Standard deviation6.6007041
Coefficient of variation (CV)0.8220434
Kurtosis7.1613541
Mean8.0296296
Median Absolute Deviation (MAD)1.75
Skewness2.6211802
Sum433.6
Variance43.569294
MonotonicityNot monotonic
2024-03-14T23:03:46.280848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
6.9 2
 
3.7%
9.1 2
 
3.7%
7.6 2
 
3.7%
5.9 2
 
3.7%
6.8 2
 
3.7%
2.4 2
 
3.7%
7.5 2
 
3.7%
4.9 2
 
3.7%
5.6 2
 
3.7%
6.3 1
 
1.9%
Other values (35) 35
64.8%
ValueCountFrequency (%)
0.0 1
1.9%
1.1 1
1.9%
2.3 1
1.9%
2.4 2
3.7%
2.8 1
1.9%
3.3 1
1.9%
3.9 1
1.9%
4.1 1
1.9%
4.4 1
1.9%
4.5 1
1.9%
ValueCountFrequency (%)
34.0 1
1.9%
30.4 1
1.9%
26.9 1
1.9%
25.0 1
1.9%
13.3 1
1.9%
12.5 1
1.9%
11.5 1
1.9%
10.3 1
1.9%
9.1 2
3.7%
8.8 1
1.9%

통일_남북관계 개선
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct36
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.362963
Minimum0
Maximum11.8
Zeros3
Zeros (%)5.6%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-14T23:03:46.682254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.52
Q11.875
median2.8
Q34.325
95-th percentile7.17
Maximum11.8
Range11.8
Interquartile range (IQR)2.45

Descriptive statistics

Standard deviation2.2446831
Coefficient of variation (CV)0.66747186
Kurtosis2.6546111
Mean3.362963
Median Absolute Deviation (MAD)1
Skewness1.3076236
Sum181.6
Variance5.0386024
MonotonicityNot monotonic
2024-03-14T23:03:47.102253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
2.7 3
 
5.6%
2.6 3
 
5.6%
1.6 3
 
5.6%
0.0 3
 
5.6%
3.3 2
 
3.7%
5.3 2
 
3.7%
2.3 2
 
3.7%
2.8 2
 
3.7%
6.1 2
 
3.7%
3.1 2
 
3.7%
Other values (26) 30
55.6%
ValueCountFrequency (%)
0.0 3
5.6%
0.8 1
 
1.9%
0.9 1
 
1.9%
1.3 2
3.7%
1.4 1
 
1.9%
1.5 1
 
1.9%
1.6 3
5.6%
1.8 2
3.7%
2.1 1
 
1.9%
2.2 1
 
1.9%
ValueCountFrequency (%)
11.8 1
1.9%
8.3 1
1.9%
7.3 1
1.9%
7.1 1
1.9%
6.2 1
1.9%
6.1 2
3.7%
6.0 1
1.9%
5.8 1
1.9%
5.6 1
1.9%
5.4 1
1.9%

교육 문제
Real number (ℝ)

ZEROS 

Distinct35
Distinct (%)64.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.312963
Minimum0
Maximum14.3
Zeros3
Zeros (%)5.6%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-14T23:03:47.487927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.755
Q15
median6.3
Q37.55
95-th percentile9.805
Maximum14.3
Range14.3
Interquartile range (IQR)2.55

Descriptive statistics

Standard deviation2.5155401
Coefficient of variation (CV)0.39847218
Kurtosis2.1639685
Mean6.312963
Median Absolute Deviation (MAD)1.3
Skewness-0.1352454
Sum340.9
Variance6.327942
MonotonicityNot monotonic
2024-03-14T23:03:47.835402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
5.0 4
 
7.4%
6.0 3
 
5.6%
7.1 3
 
5.6%
0.0 3
 
5.6%
9.1 2
 
3.7%
10.0 2
 
3.7%
5.5 2
 
3.7%
6.9 2
 
3.7%
6.1 2
 
3.7%
7.0 2
 
3.7%
Other values (25) 29
53.7%
ValueCountFrequency (%)
0.0 3
5.6%
2.7 1
 
1.9%
2.9 1
 
1.9%
3.8 1
 
1.9%
4.2 1
 
1.9%
4.3 1
 
1.9%
4.6 1
 
1.9%
4.7 1
 
1.9%
4.9 1
 
1.9%
5.0 4
7.4%
ValueCountFrequency (%)
14.3 1
1.9%
10.0 2
3.7%
9.7 1
1.9%
9.5 1
1.9%
9.3 1
1.9%
9.1 2
3.7%
8.7 1
1.9%
8.2 1
1.9%
8.0 1
1.9%
7.8 2
3.7%

정치 개혁
Real number (ℝ)

HIGH CORRELATION 

Distinct39
Distinct (%)72.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27.990741
Minimum14.9
Maximum43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-14T23:03:48.069507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum14.9
5-th percentile20.35
Q125
median27.2
Q330.6
95-th percentile37.745
Maximum43
Range28.1
Interquartile range (IQR)5.6

Descriptive statistics

Standard deviation5.6097041
Coefficient of variation (CV)0.20041285
Kurtosis0.75127482
Mean27.990741
Median Absolute Deviation (MAD)2.6
Skewness0.45370403
Sum1511.5
Variance31.468781
MonotonicityNot monotonic
2024-03-14T23:03:48.294196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
28.7 4
 
7.4%
27.3 3
 
5.6%
25.0 3
 
5.6%
21.6 2
 
3.7%
24.6 2
 
3.7%
32.7 2
 
3.7%
25.6 2
 
3.7%
26.9 2
 
3.7%
26.6 2
 
3.7%
35.7 2
 
3.7%
Other values (29) 30
55.6%
ValueCountFrequency (%)
14.9 1
1.9%
17.0 1
1.9%
19.7 1
1.9%
20.7 1
1.9%
21.6 2
3.7%
21.7 1
1.9%
22.0 1
1.9%
22.5 1
1.9%
23.1 1
1.9%
24.5 1
1.9%
ValueCountFrequency (%)
43.0 1
1.9%
42.3 1
1.9%
38.2 1
1.9%
37.5 1
1.9%
35.7 2
3.7%
34.5 1
1.9%
34.0 1
1.9%
33.3 1
1.9%
32.7 2
3.7%
32.0 1
1.9%

기타
Real number (ℝ)

ZEROS 

Distinct16
Distinct (%)29.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.96851852
Minimum0
Maximum8.3
Zeros13
Zeros (%)24.1%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-14T23:03:48.509071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.4
median0.8
Q31.075
95-th percentile3.215
Maximum8.3
Range8.3
Interquartile range (IQR)0.675

Descriptive statistics

Standard deviation1.3500278
Coefficient of variation (CV)1.3939102
Kurtosis17.295473
Mean0.96851852
Median Absolute Deviation (MAD)0.3
Skewness3.761261
Sum52.3
Variance1.8225751
MonotonicityNot monotonic
2024-03-14T23:03:48.693560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0.0 13
24.1%
0.9 6
11.1%
1.1 6
11.1%
0.5 5
 
9.3%
1.0 5
 
9.3%
0.8 4
 
7.4%
0.6 3
 
5.6%
1.3 2
 
3.7%
0.4 2
 
3.7%
0.7 2
 
3.7%
Other values (6) 6
11.1%
ValueCountFrequency (%)
0.0 13
24.1%
0.4 2
 
3.7%
0.5 5
 
9.3%
0.6 3
 
5.6%
0.7 2
 
3.7%
0.8 4
 
7.4%
0.9 6
11.1%
1.0 5
 
9.3%
1.1 6
11.1%
1.3 2
 
3.7%
ValueCountFrequency (%)
8.3 1
 
1.9%
4.9 1
 
1.9%
3.8 1
 
1.9%
2.9 1
 
1.9%
1.6 1
 
1.9%
1.5 1
 
1.9%
1.3 2
 
3.7%
1.1 6
11.1%
1.0 5
9.3%
0.9 6
11.1%

Interactions

2024-03-14T23:03:26.062344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:15.116852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:19.807801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:24.133078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:28.464679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:32.841150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:37.323156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:41.760477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:45.986365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:49.977812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:53.776316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:57.903488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:01.669639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:05.948534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:09.968524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:13.452139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:17.865619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:22.348234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:26.311144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:15.372175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:20.055812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:24.384545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:28.715157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:33.098315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:37.581081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:42.014963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:46.135735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:50.229450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:54.023117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:58.057060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:01.930327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:06.318832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:10.249044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:13.711887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:18.120116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:22.499355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:26.540988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:15.615214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:20.285378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:24.617880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:28.951560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:33.337244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:37.827117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:42.250575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:46.265759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:50.463473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:54.256785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:58.401995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:02.170180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:06.695312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:10.579397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:13.951231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:18.362593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:22.633565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:26.776701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:15.855124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:20.515737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:24.847452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:29.169345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:33.586628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:38.065651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:42.484880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:46.410315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:50.693269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:54.486894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:58.536934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:02.407046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:06.957517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:10.719704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:14.187137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:18.604230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:22.850727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:27.015063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:16.108317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:20.754162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:25.093328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:29.310831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:33.833098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:38.309541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:42.729428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:46.648756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:50.929561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:54.724163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:58.680052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:02.651937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:07.220726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:10.868197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:14.431802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:18.850968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:23.103072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:27.261339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:16.363610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:20.999250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:25.341315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:29.503532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:34.106932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:38.563262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:42.976058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:46.892277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:51.178868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:54.968296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:58.827909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:02.909048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:07.487999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:11.021427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:14.680740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:19.103358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:23.363820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:27.502271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:16.620051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:21.239866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:25.592152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:29.752423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:34.356959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:38.808193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:43.224482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:47.132592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:51.421198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:55.207910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:58.975594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:03.160973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:07.819320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:11.173761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:14.932826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:19.355087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:23.614676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:27.741859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:16.866224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:21.479204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:25.830771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:29.990623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:34.605683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:39.052755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:43.461230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:47.370070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:51.659276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:55.444646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:59.119336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:03.403897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:08.068622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:11.376748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:15.176830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:19.602341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:23.858491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:27.970141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:17.106606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:21.708236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:26.064752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:30.226866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:34.852633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:39.287308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:43.694918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:47.597563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:51.887075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:55.670673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:59.255364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:03.638800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:08.199940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:11.555641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:15.413406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:19.841882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:24.096820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:28.195996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:17.347739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:21.940245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:26.298761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:30.460258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:35.090875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:39.526984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:43.927464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:47.832653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:52.115589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:55.901166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:59.451833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:03.877051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:08.332858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:11.696179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:15.648393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:20.079280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:24.373625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:28.424054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:17.588811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:22.176538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:26.529394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:30.691908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:35.325342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:39.762794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:44.163543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:48.059366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:52.345643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:56.129228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:59.690822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:04.119575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:08.468210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:11.838637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:15.884864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:20.317494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:24.610333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:28.661720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:17.841607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:22.425744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:26.776863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:30.937527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:35.577235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:40.011859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:44.411973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:48.300669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:52.589087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:56.371792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:59.935718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:04.370968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:08.610785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:11.987745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:16.136124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:20.565776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:24.756639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:28.903999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:18.096729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:22.668660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:27.020413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:31.181886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:35.826860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:40.260429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:44.661117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:48.542742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:52.785908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:56.615129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:00.190656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:04.617613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:08.759505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:12.142862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:16.388475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:20.820832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:24.902570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:29.139962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:18.340995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:22.913107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:27.257109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:31.424766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:36.073436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:40.502605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:44.900806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:48.775335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:52.920587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:56.847860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:00.429046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:04.870938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:08.924322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:12.287945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:16.628147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:21.063732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:25.042801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:29.390629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:18.604457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:23.163712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:27.504068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:31.675597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:36.327895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:40.771211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:45.151726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:49.026669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:53.071425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:57.100069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:00.685058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:05.042492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:09.133906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:12.447156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:16.884019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:21.331231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:25.194061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:29.629612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:19.061345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:23.412695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:27.750024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:31.922608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:36.583406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:41.023287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:45.560430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:49.267012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:53.214992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:57.341159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:00.933543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:05.196402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:09.279146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:12.703255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:17.128584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:21.602644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:25.343539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:29.878242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:19.319684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:23.663091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:28.000766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:32.173382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:36.837488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:41.280182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:45.711885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:49.515217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:53.366501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:57.588665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:01.190633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:05.485373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:09.497205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:12.964949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:17.386049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:22.065383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:25.584567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:30.113302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:19.566674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:23.900325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:28.235118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:32.602016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:37.083002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:41.526485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:45.853940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:49.748822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:53.543464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:02:57.773001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:01.432852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:05.680906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:09.734743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:13.213485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:17.627185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:22.209096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:03:25.829129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T23:03:48.950909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분중분류사례수경제 성장 및 일자리 창출공공 영역 부정부패 청산경제 양극화 해소성별_이념_세대 갈등 해소지역 균형 발전사회적 약자 차별 해소부동산_주거 안정기후 및 환경 위기 대응검찰 개혁언론 개혁저출생_고령화 대응국민 안전 증진국제_외교 문제통일_남북관계 개선교육 문제정치 개혁기타
구분1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
중분류1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
사례수1.0001.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
경제 성장 및 일자리 창출1.0001.0000.0001.0000.0000.0380.6110.6870.5890.7280.7830.0000.0000.5240.3690.4810.0000.0550.1340.425
공공 영역 부정부패 청산1.0001.0000.0000.0001.0000.2640.0000.4090.3490.0000.5720.3860.6530.1340.4690.5890.7960.7620.1450.610
경제 양극화 해소1.0001.0000.0000.0380.2641.0000.5500.5440.5460.6090.4980.3420.7850.0000.4150.3900.6240.2040.3150.596
성별_이념_세대 갈등 해소1.0001.0000.0000.6110.0000.5501.0000.8650.4040.7710.5970.4450.6650.0870.2530.0000.4740.0000.6780.000
지역 균형 발전1.0001.0000.0000.6870.4090.5440.8651.0000.7670.9190.6170.0000.5310.6090.6920.6160.4590.3550.7030.467
사회적 약자 차별 해소1.0001.0000.0000.5890.3490.5460.4040.7671.0000.2460.4740.4150.0000.0000.0000.0000.1990.4430.3680.419
부동산_주거 안정1.0001.0000.0000.7280.0000.6090.7710.9190.2461.0000.6590.4300.4650.7070.7070.6540.4550.3210.7750.399
기후 및 환경 위기 대응1.0001.0000.0000.7830.5720.4980.5970.6170.4740.6591.0000.6050.0000.0000.5520.4600.4940.8110.5920.638
검찰 개혁1.0001.0000.0000.0000.3860.3420.4450.0000.4150.4300.6051.0000.4820.0000.6680.3680.4000.5610.4820.691
언론 개혁1.0001.0000.0000.0000.6530.7850.6650.5310.0000.4650.0000.4821.0000.3690.2620.5520.6960.0000.1960.352
저출생_고령화 대응1.0001.0000.0000.5240.1340.0000.0870.6090.0000.7070.0000.0000.3691.0000.8240.0000.4150.4190.4280.196
국민 안전 증진1.0001.0000.0000.3690.4690.4150.2530.6920.0000.7070.5520.6680.2620.8241.0000.5550.4080.5290.5590.572
국제_외교 문제1.0001.0000.0000.4810.5890.3900.0000.6160.0000.6540.4600.3680.5520.0000.5551.0000.5250.5270.4510.570
통일_남북관계 개선1.0001.0000.0000.0000.7960.6240.4740.4590.1990.4550.4940.4000.6960.4150.4080.5251.0000.6460.5340.857
교육 문제1.0001.0000.0000.0550.7620.2040.0000.3550.4430.3210.8110.5610.0000.4190.5290.5270.6461.0000.4600.575
정치 개혁1.0001.0000.0000.1340.1450.3150.6780.7030.3680.7750.5920.4820.1960.4280.5590.4510.5340.4601.0000.333
기타1.0001.0000.0000.4250.6100.5960.0000.4670.4190.3990.6380.6910.3520.1960.5720.5700.8570.5750.3331.000
2024-03-14T23:03:49.291413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사례수경제 성장 및 일자리 창출공공 영역 부정부패 청산경제 양극화 해소성별_이념_세대 갈등 해소지역 균형 발전사회적 약자 차별 해소부동산_주거 안정기후 및 환경 위기 대응검찰 개혁언론 개혁저출생_고령화 대응국민 안전 증진국제_외교 문제통일_남북관계 개선교육 문제정치 개혁기타
사례수1.0000.117-0.0660.0270.0770.2610.2420.170-0.043-0.1710.0380.256-0.027-0.000-0.1390.010-0.3570.241
경제 성장 및 일자리 창출0.1171.000-0.354-0.085-0.1820.055-0.3750.297-0.456-0.0030.2090.254-0.129-0.003-0.199-0.021-0.172-0.018
공공 영역 부정부패 청산-0.066-0.3541.0000.0910.252-0.3320.154-0.0040.029-0.056-0.282-0.1250.3830.157-0.028-0.2420.087-0.129
경제 양극화 해소0.027-0.0850.0911.0000.060-0.392-0.124-0.0450.270-0.157-0.3680.028-0.1580.234-0.036-0.1410.230-0.014
성별_이념_세대 갈등 해소0.077-0.1820.2520.0601.000-0.5010.1620.3410.383-0.414-0.5860.3900.4580.380-0.574-0.370-0.386-0.056
지역 균형 발전0.2610.055-0.332-0.392-0.5011.0000.152-0.164-0.3180.0570.507-0.310-0.277-0.4940.2270.364-0.110-0.004
사회적 약자 차별 해소0.242-0.3750.154-0.1240.1620.1521.000-0.1340.164-0.342-0.200-0.224-0.026-0.118-0.158-0.111-0.274-0.065
부동산_주거 안정0.1700.297-0.004-0.0450.341-0.164-0.1341.000-0.158-0.248-0.2070.3270.2620.332-0.187-0.184-0.3680.018
기후 및 환경 위기 대응-0.043-0.4560.0290.2700.383-0.3180.164-0.1581.000-0.159-0.4060.0170.0100.236-0.174-0.0740.0250.145
검찰 개혁-0.171-0.003-0.056-0.157-0.4140.057-0.342-0.248-0.1591.0000.547-0.295-0.082-0.3990.2820.4940.1380.006
언론 개혁0.0380.209-0.282-0.368-0.5860.507-0.200-0.207-0.4060.5471.000-0.279-0.043-0.6770.3160.2340.202-0.064
저출생_고령화 대응0.2560.254-0.1250.0280.390-0.310-0.2240.3270.017-0.295-0.2791.0000.2710.235-0.416-0.296-0.2990.210
국민 안전 증진-0.027-0.1290.383-0.1580.458-0.277-0.0260.2620.010-0.082-0.0430.2711.000-0.037-0.347-0.374-0.2700.088
국제_외교 문제-0.000-0.0030.1570.2340.380-0.494-0.1180.3320.236-0.399-0.6770.235-0.0371.0000.031-0.233-0.074-0.001
통일_남북관계 개선-0.139-0.199-0.028-0.036-0.5740.227-0.158-0.187-0.1740.2820.316-0.416-0.3470.0311.0000.2180.6120.127
교육 문제0.010-0.021-0.242-0.141-0.3700.364-0.111-0.184-0.0740.4940.234-0.296-0.374-0.2330.2181.000-0.025-0.097
정치 개혁-0.357-0.1720.0870.230-0.386-0.110-0.274-0.3680.0250.1380.202-0.299-0.270-0.0740.612-0.0251.000-0.091
기타0.241-0.018-0.129-0.014-0.056-0.004-0.0650.0180.1450.006-0.0640.2100.088-0.0010.127-0.097-0.0911.000

Missing values

2024-03-14T23:03:30.432057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T23:03:30.871393image/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

구분중분류사례수경제 성장 및 일자리 창출공공 영역 부정부패 청산경제 양극화 해소성별_이념_세대 갈등 해소지역 균형 발전사회적 약자 차별 해소부동산_주거 안정기후 및 환경 위기 대응검찰 개혁언론 개혁저출생_고령화 대응국민 안전 증진국제_외교 문제통일_남북관계 개선교육 문제정치 개혁기타
0성별1남자137631.217.432.819.827.326.211.419.616.613.231.36.76.33.86.828.70.9
1성별2여자63526.017.536.932.418.635.114.029.09.16.926.010.18.51.65.522.00.8
2연령120대21726.320.734.131.323.541.914.322.16.96.024.911.57.80.96.520.70.5
3연령230~34세39128.616.932.533.225.830.915.122.38.29.034.89.06.91.34.919.71.0
4연령335~39세38231.218.834.326.221.728.514.123.69.26.536.98.17.91.85.524.61.0
5연령440~44세31735.614.835.620.821.125.911.724.616.711.028.17.39.12.26.028.70.6
6연령545~49세22521.318.735.120.423.125.311.124.020.911.132.96.26.23.67.132.00.9
7연령650대37229.615.637.415.627.424.29.722.023.715.921.56.75.17.37.829.61.1
8연령760대 이상10732.719.621.59.334.631.83.714.015.930.820.62.84.75.69.343.00.0
9매체유형1신문사106532.815.233.122.028.929.412.721.511.710.032.45.98.33.46.425.60.8
구분중분류사례수경제 성장 및 일자리 창출공공 영역 부정부패 청산경제 양극화 해소성별_이념_세대 갈등 해소지역 균형 발전사회적 약자 차별 해소부동산_주거 안정기후 및 환경 위기 대응검찰 개혁언론 개혁저출생_고령화 대응국민 안전 증진국제_외교 문제통일_남북관계 개선교육 문제정치 개혁기타
44직위3부장/부장대우20922.521.537.812.427.324.47.219.626.316.328.79.14.86.26.728.70.5
45직위4차장/차장대우45731.517.537.425.624.725.611.622.513.88.529.36.86.82.46.329.10.4
46직위5평기자101829.117.732.128.621.632.014.724.09.68.331.99.28.62.36.023.11.1
47경력11~4년42630.320.230.325.126.135.214.619.210.110.630.511.07.01.66.121.60.5
48경력25~9년45730.416.833.928.426.929.113.623.49.89.432.68.17.21.55.022.51.1
49경력310~14년39932.617.033.822.622.328.613.020.815.89.830.87.58.03.06.327.11.0
50경력415~19년27230.118.434.623.521.324.610.726.815.810.727.66.35.92.97.032.71.1
51경력520년 이상45724.915.337.919.024.526.39.023.920.415.126.05.56.66.17.731.30.7
52권역1서울139230.717.937.126.913.127.313.924.613.99.031.17.99.13.36.027.30.9
53권역2그 외 지역61926.816.527.516.850.133.08.618.115.016.226.37.42.42.67.125.00.6