Overview

Dataset statistics

Number of variables9
Number of observations55
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.4 KiB
Average record size in memory81.3 B

Variable types

Text2
Numeric7

Dataset

Description언론인 의식조사 관련 "언론 전반 인식 평가"에 관한 자료입니다. 자세한 내용은 재단 홈페이지에 방문하여 확인 바랍니다.
Author한국언론진흥재단
URLhttps://www.data.go.kr/data/15060148/fileData.do

Alerts

우리나라 언론은 공정하다 is highly overall correlated with 우리나라 언론은 전문적이다 and 2 other fieldsHigh correlation
우리나라 언론은 전문적이다 is highly overall correlated with 우리나라 언론은 공정하다High correlation
우리나라 언론은 정확하다 is highly overall correlated with 우리나라 언론은 공정하다 and 1 other fieldsHigh correlation
우리나라 언론은 신뢰할 수 있다 is highly overall correlated with 우리나라 언론은 공정하다 and 1 other fieldsHigh correlation
구분 has unique valuesUnique

Reproduction

Analysis started2024-03-14 12:36:34.430799
Analysis finished2024-03-14 12:36:46.973899
Duration12.54 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Text

UNIQUE 

Distinct55
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size568.0 B
2024-03-14T21:36:47.792276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.3818182
Min length2

Characters and Unicode

Total characters241
Distinct characters29
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

Unique55 ?
Unique (%)100.0%

Sample

1st row전체
2nd row성별1
3rd row성별2
4th row연령1
5th row연령2
ValueCountFrequency (%)
전체 1
 
1.8%
소속부서4 1
 
1.8%
소속부서6 1
 
1.8%
소속부서7 1
 
1.8%
소속부서8 1
 
1.8%
소속부서9 1
 
1.8%
소속부서10 1
 
1.8%
소속부서11 1
 
1.8%
소속부서12 1
 
1.8%
소속부서13 1
 
1.8%
Other values (45) 45
81.8%
2024-03-14T21:36:49.245238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
소 29
12.0%
속 29
12.0%
1 21
 
8.7%
서 18
 
7.5%
부 18
 
7.5%
체 16
 
6.6%
매 15
 
6.2%
2 9
 
3.7%
3 7
 
2.9%
연 7
 
2.9%
Other values (19) 72
29.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 176
73.0%
Decimal Number 65
 
27.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
소 29
16.5%
속 29
16.5%
서 18
10.2%
부 18
10.2%
체 16
9.1%
매 15
8.5%
연 7
 
4.0%
령 7
 
4.0%
경 5
 
2.8%
위 5
 
2.8%
Other values (9) 27
15.3%
Decimal Number
ValueCountFrequency (%)
1 21
32.3%
2 9
13.8%
3 7
 
10.8%
4 7
 
10.8%
5 6
 
9.2%
7 4
 
6.2%
6 4
 
6.2%
8 3
 
4.6%
0 2
 
3.1%
9 2
 
3.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 176
73.0%
Common 65
 
27.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
소 29
16.5%
속 29
16.5%
서 18
10.2%
부 18
10.2%
체 16
9.1%
매 15
8.5%
연 7
 
4.0%
령 7
 
4.0%
경 5
 
2.8%
위 5
 
2.8%
Other values (9) 27
15.3%
Common
ValueCountFrequency (%)
1 21
32.3%
2 9
13.8%
3 7
 
10.8%
4 7
 
10.8%
5 6
 
9.2%
7 4
 
6.2%
6 4
 
6.2%
8 3
 
4.6%
0 2
 
3.1%
9 2
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 176
73.0%
ASCII 65
 
27.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
소 29
16.5%
속 29
16.5%
서 18
10.2%
부 18
10.2%
체 16
9.1%
매 15
8.5%
연 7
 
4.0%
령 7
 
4.0%
경 5
 
2.8%
위 5
 
2.8%
Other values (9) 27
15.3%
ASCII
ValueCountFrequency (%)
1 21
32.3%
2 9
13.8%
3 7
 
10.8%
4 7
 
10.8%
5 6
 
9.2%
7 4
 
6.2%
6 4
 
6.2%
8 3
 
4.6%
0 2
 
3.1%
9 2
 
3.1%

중분류
Text

Distinct53
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Memory size568.0 B
2024-03-14T21:36:50.194700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length5.5090909
Min length2

Characters and Unicode

Total characters303
Distinct characters105
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

Unique51 ?
Unique (%)92.7%

Sample

1st row전체1
2nd row남자
3rd row여자
4th row20대
5th row30~34세
ValueCountFrequency (%)
인터넷언론사 2
 
3.4%
이상 2
 
3.4%
뉴스통신사 2
 
3.4%
기타 1
 
1.7%
영상부 1
 
1.7%
국장/국장대우 1
 
1.7%
국방/통일/북한 1
 
1.7%
편집(편성)/교열부 1
 
1.7%
여론/독자/심의부 1
 
1.7%
사진 1
 
1.7%
Other values (46) 46
78.0%
2024-03-14T21:36:51.559159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 20
 
6.6%
부 14
 
4.6%
사 11
 
3.6%
국 10
 
3.3%
4 8
 
2.6%
~ 8
 
2.6%
장 8
 
2.6%
일 7
 
2.3%
대 7
 
2.3%
0 7
 
2.3%
Other values (95) 203
67.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 225
74.3%
Decimal Number 37
 
12.2%
Other Punctuation 20
 
6.6%
Math Symbol 8
 
2.6%
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 (%)
부 14
 
6.2%
사 11
 
4.9%
국 10
 
4.4%
장 8
 
3.6%
일 7
 
3.1%
대 7
 
3.1%
지 6
 
2.7%
전 5
 
2.2%
스 5
 
2.2%
년 5
 
2.2%
Other values (80) 147
65.3%
Decimal Number
ValueCountFrequency (%)
4 8
21.6%
0 7
18.9%
1 6
16.2%
5 5
13.5%
9 4
10.8%
3 4
10.8%
2 2
 
5.4%
6 1
 
2.7%
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 225
74.3%
Common 73
 
24.1%
Latin 5
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 14
 
6.2%
사 11
 
4.9%
국 10
 
4.4%
장 8
 
3.6%
일 7
 
3.1%
대 7
 
3.1%
지 6
 
2.7%
전 5
 
2.2%
스 5
 
2.2%
년 5
 
2.2%
Other values (80) 147
65.3%
Common
ValueCountFrequency (%)
/ 20
27.4%
4 8
 
11.0%
~ 8
 
11.0%
0 7
 
9.6%
1 6
 
8.2%
5 5
 
6.8%
9 4
 
5.5%
4
 
5.5%
3 4
 
5.5%
) 2
 
2.7%
Other values (3) 5
 
6.8%
Latin
ValueCountFrequency (%)
I 4
80.0%
T 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 225
74.3%
ASCII 78
 
25.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 20
25.6%
4 8
 
10.3%
~ 8
 
10.3%
0 7
 
9.0%
1 6
 
7.7%
5 5
 
6.4%
I 4
 
5.1%
9 4
 
5.1%
4
 
5.1%
3 4
 
5.1%
Other values (5) 8
 
10.3%
Hangul
ValueCountFrequency (%)
부 14
 
6.2%
사 11
 
4.9%
국 10
 
4.4%
장 8
 
3.6%
일 7
 
3.1%
대 7
 
3.1%
지 6
 
2.7%
전 5
 
2.2%
스 5
 
2.2%
년 5
 
2.2%
Other values (80) 147
65.3%

사례수
Real number (ℝ)

Distinct51
Distinct (%)92.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean329.07273
Minimum8
Maximum2011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size623.0 B
2024-03-14T21:36:52.180802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile20.3
Q180.5
median209
Q3406
95-th percentile1158.3
Maximum2011
Range2003
Interquartile range (IQR)325.5

Descriptive statistics

Standard deviation386.16931
Coefficient of variation (CV)1.1735075
Kurtosis7.1894785
Mean329.07273
Median Absolute Deviation (MAD)163
Skewness2.4878756
Sum18099
Variance149126.74
MonotonicityNot monotonic
2024-03-14T21:36:52.631738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
457 3
 
5.5%
406 2
 
3.6%
160 2
 
3.6%
71 1
 
1.8%
50 1
 
1.8%
12 1
 
1.8%
87 1
 
1.8%
14 1
 
1.8%
34 1
 
1.8%
52 1
 
1.8%
Other values (41) 41
74.5%
ValueCountFrequency (%)
8 1
1.8%
12 1
1.8%
14 1
1.8%
23 1
1.8%
26 1
1.8%
33 1
1.8%
34 1
1.8%
44 1
1.8%
50 1
1.8%
52 1
1.8%
ValueCountFrequency (%)
2011 1
 
1.8%
1392 1
 
1.8%
1376 1
 
1.8%
1065 1
 
1.8%
1018 1
 
1.8%
635 1
 
1.8%
619 1
 
1.8%
457 3
5.5%
449 1
 
1.8%
432 1
 
1.8%

우리나라 언론은 공정하다
Real number (ℝ)

HIGH CORRELATION 

Distinct31
Distinct (%)56.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.5758182
Minimum2.19
Maximum3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size623.0 B
2024-03-14T21:36:52.913627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.19
5-th percentile2.415
Q12.51
median2.58
Q32.64
95-th percentile2.759
Maximum3
Range0.81
Interquartile range (IQR)0.13

Descriptive statistics

Standard deviation0.12305811
Coefficient of variation (CV)0.047774379
Kurtosis2.8487368
Mean2.5758182
Median Absolute Deviation (MAD)0.06
Skewness0.24766321
Sum141.67
Variance0.0151433
MonotonicityNot monotonic
2024-03-14T21:36:53.330610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
2.58 8
 
14.5%
2.49 3
 
5.5%
2.52 3
 
5.5%
2.53 3
 
5.5%
2.64 3
 
5.5%
2.46 2
 
3.6%
2.59 2
 
3.6%
2.54 2
 
3.6%
2.48 2
 
3.6%
2.44 2
 
3.6%
Other values (21) 25
45.5%
ValueCountFrequency (%)
2.19 1
 
1.8%
2.36 1
 
1.8%
2.38 1
 
1.8%
2.43 1
 
1.8%
2.44 2
3.6%
2.46 2
3.6%
2.48 2
3.6%
2.49 3
5.5%
2.5 1
 
1.8%
2.52 3
5.5%
ValueCountFrequency (%)
3.0 1
1.8%
2.79 1
1.8%
2.78 1
1.8%
2.75 1
1.8%
2.74 1
1.8%
2.71 1
1.8%
2.7 1
1.8%
2.69 1
1.8%
2.68 1
1.8%
2.67 2
3.6%

우리나라 언론은 전문적이다
Real number (ℝ)

HIGH CORRELATION 

Distinct28
Distinct (%)50.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.7490909
Minimum2.57
Maximum3.24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size623.0 B
2024-03-14T21:36:53.714236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.57
5-th percentile2.644
Q12.68
median2.72
Q32.795
95-th percentile2.963
Maximum3.24
Range0.67
Interquartile range (IQR)0.115

Descriptive statistics

Standard deviation0.11020642
Coefficient of variation (CV)0.040088313
Kurtosis6.5731994
Mean2.7490909
Median Absolute Deviation (MAD)0.04
Skewness2.0871151
Sum151.2
Variance0.012145455
MonotonicityNot monotonic
2024-03-14T21:36:54.113801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
2.68 5
 
9.1%
2.69 4
 
7.3%
2.72 4
 
7.3%
2.67 4
 
7.3%
2.7 4
 
7.3%
2.71 4
 
7.3%
2.73 3
 
5.5%
2.8 2
 
3.6%
2.88 2
 
3.6%
2.81 2
 
3.6%
Other values (18) 21
38.2%
ValueCountFrequency (%)
2.57 1
 
1.8%
2.62 1
 
1.8%
2.63 1
 
1.8%
2.65 2
 
3.6%
2.66 1
 
1.8%
2.67 4
7.3%
2.68 5
9.1%
2.69 4
7.3%
2.7 4
7.3%
2.71 4
7.3%
ValueCountFrequency (%)
3.24 1
1.8%
3.0 1
1.8%
2.97 1
1.8%
2.96 1
1.8%
2.88 2
3.6%
2.86 1
1.8%
2.85 1
1.8%
2.83 1
1.8%
2.82 1
1.8%
2.81 2
3.6%

우리나라 언론은 정확하다
Real number (ℝ)

HIGH CORRELATION 

Distinct30
Distinct (%)54.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.8896364
Minimum2.57
Maximum3.16
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size623.0 B
2024-03-14T21:36:54.489019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.57
5-th percentile2.71
Q12.83
median2.91
Q32.955
95-th percentile3.102
Maximum3.16
Range0.59
Interquartile range (IQR)0.125

Descriptive statistics

Standard deviation0.11872726
Coefficient of variation (CV)0.041087266
Kurtosis0.71301015
Mean2.8896364
Median Absolute Deviation (MAD)0.06
Skewness-0.27137618
Sum158.93
Variance0.014096162
MonotonicityNot monotonic
2024-03-14T21:36:54.878472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
2.97 5
 
9.1%
2.95 4
 
7.3%
2.92 4
 
7.3%
2.89 3
 
5.5%
2.88 3
 
5.5%
2.71 3
 
5.5%
2.94 3
 
5.5%
2.98 2
 
3.6%
2.73 2
 
3.6%
2.93 2
 
3.6%
Other values (20) 24
43.6%
ValueCountFrequency (%)
2.57 1
 
1.8%
2.62 1
 
1.8%
2.71 3
5.5%
2.72 1
 
1.8%
2.73 2
3.6%
2.75 1
 
1.8%
2.76 1
 
1.8%
2.79 1
 
1.8%
2.8 1
 
1.8%
2.82 1
 
1.8%
ValueCountFrequency (%)
3.16 1
 
1.8%
3.15 1
 
1.8%
3.13 1
 
1.8%
3.09 1
 
1.8%
2.99 1
 
1.8%
2.98 2
 
3.6%
2.97 5
9.1%
2.96 2
 
3.6%
2.95 4
7.3%
2.94 3
5.5%

우리나라 언론은 신뢰할 수 있다
Real number (ℝ)

HIGH CORRELATION 

Distinct27
Distinct (%)49.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.9087273
Minimum2.43
Maximum3.18
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size623.0 B
2024-03-14T21:36:55.264622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.43
5-th percentile2.72
Q12.86
median2.92
Q32.975
95-th percentile3.095
Maximum3.18
Range0.75
Interquartile range (IQR)0.115

Descriptive statistics

Standard deviation0.12665284
Coefficient of variation (CV)0.043542358
Kurtosis2.7296824
Mean2.9087273
Median Absolute Deviation (MAD)0.06
Skewness-0.8720836
Sum159.98
Variance0.016040943
MonotonicityNot monotonic
2024-03-14T21:36:55.679368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
2.93 5
 
9.1%
2.92 4
 
7.3%
2.97 4
 
7.3%
2.77 4
 
7.3%
2.99 4
 
7.3%
2.91 3
 
5.5%
2.72 3
 
5.5%
2.88 3
 
5.5%
3.13 2
 
3.6%
2.95 2
 
3.6%
Other values (17) 21
38.2%
ValueCountFrequency (%)
2.43 1
 
1.8%
2.72 3
5.5%
2.74 1
 
1.8%
2.75 2
3.6%
2.77 4
7.3%
2.79 1
 
1.8%
2.84 1
 
1.8%
2.85 1
 
1.8%
2.87 1
 
1.8%
2.88 3
5.5%
ValueCountFrequency (%)
3.18 1
 
1.8%
3.13 2
3.6%
3.08 2
3.6%
3.06 1
 
1.8%
3.04 1
 
1.8%
3.02 1
 
1.8%
3.01 1
 
1.8%
2.99 4
7.3%
2.98 1
 
1.8%
2.97 4
7.3%

우리나라 언론은 영향력 있다
Real number (ℝ)

Distinct26
Distinct (%)47.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.5594545
Minimum3.17
Maximum3.71
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size623.0 B
2024-03-14T21:36:56.068694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.17
5-th percentile3.347
Q13.52
median3.58
Q33.615
95-th percentile3.7
Maximum3.71
Range0.54
Interquartile range (IQR)0.095

Descriptive statistics

Standard deviation0.10346619
Coefficient of variation (CV)0.02906799
Kurtosis2.9582452
Mean3.5594545
Median Absolute Deviation (MAD)0.05
Skewness-1.3344357
Sum195.77
Variance0.010705253
MonotonicityNot monotonic
2024-03-14T21:36:56.462391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
3.6 5
 
9.1%
3.58 4
 
7.3%
3.59 3
 
5.5%
3.56 3
 
5.5%
3.48 3
 
5.5%
3.55 3
 
5.5%
3.5 3
 
5.5%
3.61 2
 
3.6%
3.71 2
 
3.6%
3.68 2
 
3.6%
Other values (16) 25
45.5%
ValueCountFrequency (%)
3.17 1
 
1.8%
3.34 2
3.6%
3.35 1
 
1.8%
3.4 2
3.6%
3.48 3
5.5%
3.5 3
5.5%
3.51 1
 
1.8%
3.52 2
3.6%
3.53 2
3.6%
3.54 2
3.6%
ValueCountFrequency (%)
3.71 2
3.6%
3.7 2
3.6%
3.69 1
1.8%
3.68 2
3.6%
3.66 2
3.6%
3.65 1
1.8%
3.64 1
1.8%
3.63 2
3.6%
3.62 1
1.8%
3.61 2
3.6%

우리나라는 언론활동이 자유롭다
Real number (ℝ)

Distinct28
Distinct (%)50.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1623636
Minimum2.86
Maximum3.44
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size623.0 B
2024-03-14T21:36:56.824766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.86
5-th percentile3.014
Q13.105
median3.16
Q33.205
95-th percentile3.366
Maximum3.44
Range0.58
Interquartile range (IQR)0.1

Descriptive statistics

Standard deviation0.10374405
Coefficient of variation (CV)0.032805858
Kurtosis1.6729365
Mean3.1623636
Median Absolute Deviation (MAD)0.05
Skewness0.29184667
Sum173.93
Variance0.010762828
MonotonicityNot monotonic
2024-03-14T21:36:57.202689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
3.16 5
 
9.1%
3.08 5
 
9.1%
3.12 5
 
9.1%
3.14 4
 
7.3%
3.18 3
 
5.5%
3.09 3
 
5.5%
3.21 3
 
5.5%
3.17 3
 
5.5%
3.2 2
 
3.6%
3.1 2
 
3.6%
Other values (18) 20
36.4%
ValueCountFrequency (%)
2.86 1
 
1.8%
2.95 1
 
1.8%
3.0 1
 
1.8%
3.02 1
 
1.8%
3.08 5
9.1%
3.09 3
5.5%
3.1 2
 
3.6%
3.11 2
 
3.6%
3.12 5
9.1%
3.14 4
7.3%
ValueCountFrequency (%)
3.44 1
1.8%
3.42 1
1.8%
3.38 1
1.8%
3.36 1
1.8%
3.3 1
1.8%
3.29 1
1.8%
3.28 1
1.8%
3.27 1
1.8%
3.26 1
1.8%
3.25 1
1.8%

Interactions

2024-03-14T21:36:44.457700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:34.806302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:36.287464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:37.794910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:39.553499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:41.342634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:43.016402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:44.716323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:35.074228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:36.459580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:38.025089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:39.817531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:41.620096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:43.175148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:44.983476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:35.345889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:36.633826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:38.291811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:40.080485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:41.897418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:43.340320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:45.228386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:35.624219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:36.883577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:38.543078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:40.338053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:42.161938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:43.490853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:45.473093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:35.800454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:37.237987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:38.790636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:40.582922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:42.416209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:43.705120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:45.735384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:35.977230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:37.411307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:39.055893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:40.848474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:42.703240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:43.971954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:45.981137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:36.131335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:37.574876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:39.302911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:41.094737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:42.858847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:36:44.214449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T21:36:57.463592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분중분류사례수우리나라 언론은 공정하다우리나라 언론은 전문적이다우리나라 언론은 정확하다우리나라 언론은 신뢰할 수 있다우리나라 언론은 영향력 있다우리나라는 언론활동이 자유롭다
구분1.0001.0001.0001.0001.0001.0001.0001.0001.000
중분류1.0001.0001.0001.0001.0001.0001.0001.0001.000
사례수1.0001.0001.0000.0000.0000.0000.0000.0000.000
우리나라 언론은 공정하다1.0001.0000.0001.0000.9300.6460.7910.7030.505
우리나라 언론은 전문적이다1.0001.0000.0000.9301.0000.2660.5940.5640.421
우리나라 언론은 정확하다1.0001.0000.0000.6460.2661.0000.8060.5630.358
우리나라 언론은 신뢰할 수 있다1.0001.0000.0000.7910.5940.8061.0000.6470.532
우리나라 언론은 영향력 있다1.0001.0000.0000.7030.5640.5630.6471.0000.526
우리나라는 언론활동이 자유롭다1.0001.0000.0000.5050.4210.3580.5320.5261.000
2024-03-14T21:36:57.794874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사례수우리나라 언론은 공정하다우리나라 언론은 전문적이다우리나라 언론은 정확하다우리나라 언론은 신뢰할 수 있다우리나라 언론은 영향력 있다우리나라는 언론활동이 자유롭다
사례수1.0000.089-0.137-0.0140.034-0.012-0.044
우리나라 언론은 공정하다0.0891.0000.5120.5900.656-0.1190.317
우리나라 언론은 전문적이다-0.1370.5121.0000.2290.2530.0910.285
우리나라 언론은 정확하다-0.0140.5900.2291.0000.781-0.0260.135
우리나라 언론은 신뢰할 수 있다0.0340.6560.2530.7811.0000.0760.189
우리나라 언론은 영향력 있다-0.012-0.1190.091-0.0260.0761.0000.116
우리나라는 언론활동이 자유롭다-0.0440.3170.2850.1350.1890.1161.000

Missing values

2024-03-14T21:36:46.325735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T21:36:46.786561image/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

구분중분류사례수우리나라 언론은 공정하다우리나라 언론은 전문적이다우리나라 언론은 정확하다우리나라 언론은 신뢰할 수 있다우리나라 언론은 영향력 있다우리나라는 언론활동이 자유롭다
0전체전체120112.582.732.892.923.573.16
1성별1남자13762.582.722.92.923.593.18
2성별2여자6352.582.762.882.913.533.11
3연령120대2172.72.852.972.973.563.12
4연령230~34세3912.62.722.983.013.593.14
5연령335~39세3822.552.682.973.083.573.17
6연령440~44세3172.562.712.922.913.643.1
7연령545~49세2252.552.682.792.773.483.12
8연령650대3722.522.762.712.723.553.18
9연령760대 이상1072.672.772.892.933.523.42
구분중분류사례수우리나라 언론은 공정하다우리나라 언론은 전문적이다우리나라 언론은 정확하다우리나라 언론은 신뢰할 수 있다우리나라 언론은 영향력 있다우리나라는 언론활동이 자유롭다
45직위3부장/부장대우2092.492.812.732.773.53.08
46직위4차장/차장대우4572.582.712.882.893.583.2
47직위5평기자10182.592.712.952.993.583.11
48경력11~4년4262.692.862.962.953.613.15
49경력25~9년4572.62.672.953.023.583.14
50경력310~14년3992.532.672.912.933.543.1
51경력415~19년2722.582.792.942.973.623.26
52경력520년 이상4572.492.682.732.743.513.17
53권역1서울13922.542.692.882.913.553.16
54권역2그 외 지역6192.682.822.922.943.613.16