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 "언론보도에 의한 인격권 침해 주 요인"에 관한 자료입니다. (언론사 간의 특종 및 속보 경쟁, 선정적이거나 흥미 위주의 보도, 취재윤리에 대한 인식 부족 등)
Author한국언론진흥재단
URLhttps://www.data.go.kr/data/15050478/fileData.do

Alerts

별로 심각하지 않다 is highly overall correlated with 대체로 심각하다 and 2 other fieldsHigh correlation
보통이다 is highly overall correlated with 대체로 심각하다High correlation
대체로 심각하다 is highly overall correlated with 별로 심각하지 않다 and 2 other fieldsHigh correlation
매우 심각하다 is highly overall correlated with 별로 심각하지 않다 and 1 other fieldsHigh correlation
5점평균 is highly overall correlated with 별로 심각하지 않다 and 2 other fieldsHigh correlation
대분류 has unique valuesUnique
전혀 심각하지 않다 has 14 (25.5%) zerosZeros
별로 심각하지 않다 has 2 (3.6%) zerosZeros
매우 심각하다 has 4 (7.3%) zerosZeros

Reproduction

Analysis started2024-03-14 12:39:57.043656
Analysis finished2024-03-14 12:40:08.626820
Duration11.58 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대분류
Text

UNIQUE 

Distinct55
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size568.0 B
2024-03-14T21:40:09.430292image/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%
2024-03-14T21:40:10.882316image/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
2024-03-14T21:40:11.808693image/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%
2024-03-14T21:40:13.144347image/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
2024-03-14T21:40:13.561739image/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
2024-03-14T21:40:14.012822image/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%

전혀 심각하지 않다
Real number (ℝ)

ZEROS 

Distinct20
Distinct (%)36.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.83272727
Minimum0
Maximum5.9
Zeros14
Zeros (%)25.5%
Negative0
Negative (%)0.0%
Memory size623.0 B
2024-03-14T21:40:14.393115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.1
median0.6
Q31.15
95-th percentile2.23
Maximum5.9
Range5.9
Interquartile range (IQR)1.05

Descriptive statistics

Standard deviation0.94438978
Coefficient of variation (CV)1.1340925
Kurtosis14.607135
Mean0.83272727
Median Absolute Deviation (MAD)0.6
Skewness3.0575138
Sum45.8
Variance0.89187205
MonotonicityNot monotonic
2024-03-14T21:40:14.774278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0.0 14
25.5%
0.5 6
10.9%
1.3 5
 
9.1%
0.6 4
 
7.3%
1.1 3
 
5.5%
0.9 3
 
5.5%
0.8 3
 
5.5%
1.0 3
 
5.5%
0.4 2
 
3.6%
1.2 2
 
3.6%
Other values (10) 10
18.2%
ValueCountFrequency (%)
0.0 14
25.5%
0.2 1
 
1.8%
0.3 1
 
1.8%
0.4 2
 
3.6%
0.5 6
10.9%
0.6 4
 
7.3%
0.7 1
 
1.8%
0.8 3
 
5.5%
0.9 3
 
5.5%
1.0 3
 
5.5%
ValueCountFrequency (%)
5.9 1
 
1.8%
2.4 1
 
1.8%
2.3 1
 
1.8%
2.2 1
 
1.8%
1.9 1
 
1.8%
1.8 1
 
1.8%
1.6 1
 
1.8%
1.3 5
9.1%
1.2 2
 
3.6%
1.1 3
5.5%

별로 심각하지 않다
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct45
Distinct (%)81.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.758182
Minimum0
Maximum30.4
Zeros2
Zeros (%)3.6%
Negative0
Negative (%)0.0%
Memory size623.0 B
2024-03-14T21:40:15.165039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5.54
Q110.15
median13
Q314.7
95-th percentile21.23
Maximum30.4
Range30.4
Interquartile range (IQR)4.55

Descriptive statistics

Standard deviation5.1312655
Coefficient of variation (CV)0.4021941
Kurtosis2.4922834
Mean12.758182
Median Absolute Deviation (MAD)2
Skewness0.3395767
Sum701.7
Variance26.329886
MonotonicityNot monotonic
2024-03-14T21:40:15.791649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
13.3 3
 
5.5%
14.0 3
 
5.5%
0.0 2
 
3.6%
14.2 2
 
3.6%
12.7 2
 
3.6%
11.9 2
 
3.6%
12.1 2
 
3.6%
17.3 2
 
3.6%
16.5 1
 
1.8%
14.4 1
 
1.8%
Other values (35) 35
63.6%
ValueCountFrequency (%)
0.0 2
3.6%
4.0 1
1.8%
6.2 1
1.8%
7.0 1
1.8%
7.1 1
1.8%
7.3 1
1.8%
7.7 1
1.8%
7.9 1
1.8%
8.0 1
1.8%
8.3 1
1.8%
ValueCountFrequency (%)
30.4 1
1.8%
23.5 1
1.8%
21.3 1
1.8%
21.2 1
1.8%
17.9 1
1.8%
17.5 1
1.8%
17.3 2
3.6%
17.0 1
1.8%
16.5 1
1.8%
16.4 1
1.8%

보통이다
Real number (ℝ)

HIGH CORRELATION 

Distinct43
Distinct (%)78.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49.036364
Minimum25
Maximum57.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size623.0 B
2024-03-14T21:40:16.185771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum25
5-th percentile41.01
Q147.1
median50
Q351.4
95-th percentile54.92
Maximum57.7
Range32.7
Interquartile range (IQR)4.3

Descriptive statistics

Standard deviation4.9932682
Coefficient of variation (CV)0.10182786
Kurtosis9.2681852
Mean49.036364
Median Absolute Deviation (MAD)1.9
Skewness-2.2793501
Sum2697
Variance24.932727
MonotonicityNot monotonic
2024-03-14T21:40:16.592818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
48.8 4
 
7.3%
50.6 3
 
5.5%
47.1 2
 
3.6%
46.0 2
 
3.6%
50.5 2
 
3.6%
49.5 2
 
3.6%
45.6 2
 
3.6%
51.4 2
 
3.6%
50.0 2
 
3.6%
53.6 1
 
1.8%
Other values (33) 33
60.0%
ValueCountFrequency (%)
25.0 1
1.8%
38.6 1
1.8%
39.4 1
1.8%
41.7 1
1.8%
42.9 1
1.8%
44.3 1
1.8%
45.4 1
1.8%
45.6 2
3.6%
46.0 2
3.6%
46.4 1
1.8%
ValueCountFrequency (%)
57.7 1
1.8%
56.5 1
1.8%
55.9 1
1.8%
54.5 1
1.8%
53.6 1
1.8%
53.5 1
1.8%
53.3 1
1.8%
53.1 1
1.8%
52.5 1
1.8%
52.4 1
1.8%

대체로 심각하다
Real number (ℝ)

HIGH CORRELATION 

Distinct46
Distinct (%)83.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.676364
Minimum13
Maximum62.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size623.0 B
2024-03-14T21:40:17.002870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum13
5-th percentile26.48
Q130.25
median32.8
Q336.6
95-th percentile43.83
Maximum62.5
Range49.5
Interquartile range (IQR)6.35

Descriptive statistics

Standard deviation7.2551888
Coefficient of variation (CV)0.2154386
Kurtosis5.0785893
Mean33.676364
Median Absolute Deviation (MAD)2.7
Skewness0.71673505
Sum1852.2
Variance52.637764
MonotonicityNot monotonic
2024-03-14T21:40:17.423873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
32.9 2
 
3.6%
32.7 2
 
3.6%
33.3 2
 
3.6%
30.1 2
 
3.6%
34.6 2
 
3.6%
28.2 2
 
3.6%
32.8 2
 
3.6%
37.5 2
 
3.6%
30.2 2
 
3.6%
32.1 1
 
1.8%
Other values (36) 36
65.5%
ValueCountFrequency (%)
13.0 1
1.8%
14.7 1
1.8%
26.2 1
1.8%
26.6 1
1.8%
26.9 1
1.8%
27.9 1
1.8%
28.1 1
1.8%
28.2 2
3.6%
29.6 1
1.8%
30.1 2
3.6%
ValueCountFrequency (%)
62.5 1
1.8%
47.7 1
1.8%
46.0 1
1.8%
42.9 1
1.8%
42.7 1
1.8%
42.0 1
1.8%
41.7 1
1.8%
40.3 1
1.8%
40.0 1
1.8%
38.4 1
1.8%

매우 심각하다
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct36
Distinct (%)65.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.7127273
Minimum0
Maximum12.5
Zeros4
Zeros (%)7.3%
Negative0
Negative (%)0.0%
Memory size623.0 B
2024-03-14T21:40:17.763538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.4
median3.3
Q34.5
95-th percentile8.54
Maximum12.5
Range12.5
Interquartile range (IQR)2.1

Descriptive statistics

Standard deviation2.4352393
Coefficient of variation (CV)0.65591657
Kurtosis2.7567973
Mean3.7127273
Median Absolute Deviation (MAD)1
Skewness1.3328953
Sum204.2
Variance5.9303906
MonotonicityNot monotonic
2024-03-14T21:40:18.080482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
3.3 4
 
7.3%
0.0 4
 
7.3%
2.6 3
 
5.5%
2.4 3
 
5.5%
3.8 3
 
5.5%
3.5 2
 
3.6%
2.3 2
 
3.6%
3.7 2
 
3.6%
2.7 2
 
3.6%
4.5 2
 
3.6%
Other values (26) 28
50.9%
ValueCountFrequency (%)
0.0 4
7.3%
0.6 1
 
1.8%
1.1 1
 
1.8%
1.4 1
 
1.8%
1.9 1
 
1.8%
2.0 1
 
1.8%
2.1 1
 
1.8%
2.3 2
3.6%
2.4 3
5.5%
2.6 3
5.5%
ValueCountFrequency (%)
12.5 1
1.8%
9.8 1
1.8%
9.1 1
1.8%
8.3 1
1.8%
7.7 1
1.8%
7.1 1
1.8%
6.4 1
1.8%
5.6 1
1.8%
5.4 2
3.6%
5.3 1
1.8%

5점평균
Real number (ℝ)

HIGH CORRELATION 

Distinct32
Distinct (%)58.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.2674545
Minimum2.79
Maximum3.88
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size623.0 B
2024-03-14T21:40:18.480209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.79
5-th percentile3.057
Q13.19
median3.26
Q33.325
95-th percentile3.5
Maximum3.88
Range1.09
Interquartile range (IQR)0.135

Descriptive statistics

Standard deviation0.16043019
Coefficient of variation (CV)0.04909944
Kurtosis4.6109647
Mean3.2674545
Median Absolute Deviation (MAD)0.07
Skewness0.34337997
Sum179.71
Variance0.025737845
MonotonicityNot monotonic
2024-03-14T21:40:18.891969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
3.24 4
 
7.3%
3.19 4
 
7.3%
3.26 4
 
7.3%
3.31 4
 
7.3%
3.3 3
 
5.5%
3.5 3
 
5.5%
3.27 2
 
3.6%
3.22 2
 
3.6%
3.2 2
 
3.6%
3.16 2
 
3.6%
Other values (22) 25
45.5%
ValueCountFrequency (%)
2.79 1
 
1.8%
2.83 1
 
1.8%
3.05 1
 
1.8%
3.06 1
 
1.8%
3.12 1
 
1.8%
3.13 1
 
1.8%
3.16 2
3.6%
3.17 2
3.6%
3.18 1
 
1.8%
3.19 4
7.3%
ValueCountFrequency (%)
3.88 1
 
1.8%
3.5 3
5.5%
3.48 1
 
1.8%
3.46 1
 
1.8%
3.42 2
3.6%
3.41 1
 
1.8%
3.39 1
 
1.8%
3.37 1
 
1.8%
3.36 1
 
1.8%
3.35 1
 
1.8%

Interactions

2024-03-14T21:40:06.998204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:39:57.402634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:39:59.195170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:40:00.947724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:40:02.956982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:40:04.689115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:40:05.878205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:40:07.154550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:39:57.667949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:39:59.459531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:40:01.210390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:40:03.216018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:40:04.948524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:40:06.038628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:40:07.302501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:39:57.927244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:39:59.707606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:40:01.725858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:40:03.465581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:40:05.172176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:40:06.222638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:40:07.535995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:39:58.187123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:39:59.956817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:40:01.972582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:40:03.712825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:40:05.314418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:40:06.420247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:40:07.697639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:39:58.443889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:40:00.211952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:40:02.219507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:40:03.963520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:40:05.455951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:40:06.566579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:40:07.833777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:39:58.687572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:40:00.452654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:40:02.456006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:40:04.197822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:40:05.597835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:40:06.704149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:40:07.982652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:39:58.943830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:40:00.700431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:40:02.710816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:40:04.446746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:40:05.740154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:40:06.849796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T21:40:19.156003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대분류중분류사례수전혀 심각하지 않다별로 심각하지 않다보통이다대체로 심각하다매우 심각하다5점평균
대분류1.0001.0001.0001.0001.0001.0001.0001.0001.000
중분류1.0001.0001.0001.0001.0001.0001.0001.0001.000
사례수1.0001.0001.0000.0000.0000.0000.0000.0000.000
전혀 심각하지 않다1.0001.0000.0001.0000.3980.1770.3080.0000.456
별로 심각하지 않다1.0001.0000.0000.3981.0000.5490.7610.8010.848
보통이다1.0001.0000.0000.1770.5491.0000.8030.7250.887
대체로 심각하다1.0001.0000.0000.3080.7610.8031.0000.7190.896
매우 심각하다1.0001.0000.0000.0000.8010.7250.7191.0000.806
5점평균1.0001.0000.0000.4560.8480.8870.8960.8061.000
2024-03-14T21:40:19.466939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사례수전혀 심각하지 않다별로 심각하지 않다보통이다대체로 심각하다매우 심각하다5점평균
사례수1.0000.4060.179-0.025-0.135-0.111-0.280
전혀 심각하지 않다0.4061.0000.279-0.119-0.213-0.234-0.460
별로 심각하지 않다0.1790.2791.0000.226-0.757-0.556-0.898
보통이다-0.025-0.1190.2261.000-0.656-0.352-0.423
대체로 심각하다-0.135-0.213-0.757-0.6561.0000.3720.836
매우 심각하다-0.111-0.234-0.556-0.3520.3721.0000.691
5점평균-0.280-0.460-0.898-0.4230.8360.6911.000

Missing values

2024-03-14T21:40:08.175508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T21:40:08.448982image/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

대분류중분류사례수전혀 심각하지 않다별로 심각하지 않다보통이다대체로 심각하다매우 심각하다5점평균
0전체전체120110.913.349.632.93.33.24
1성별1남자13761.213.249.233.33.13.24
2성별2여자6350.313.450.632.03.83.26
3연령120대2170.517.552.528.11.43.12
4연령230~34세3911.017.946.031.53.63.19
5연령335~39세3820.817.353.126.22.63.13
6연령440~44세3171.911.751.132.23.23.23
7연령545~49세2250.48.051.636.04.03.35
8연령650대3720.56.245.442.75.13.46
9연령760대 이상1070.914.050.532.71.93.21
대분류중분류사례수전혀 심각하지 않다별로 심각하지 않다보통이다대체로 심각하다매우 심각하다5점평균
45직위3부장/부장대우2090.57.754.532.15.33.34
46직위4차장/차장대우4571.312.748.834.62.63.25
47직위5평기자10180.916.550.029.63.03.17
48경력11~4년4260.216.450.530.32.63.19
49경력25~9년4571.317.349.528.23.73.16
50경력310~14년3990.814.052.430.12.83.2
51경력415~19년2722.211.047.136.82.93.27
52경력520년 이상4570.47.048.140.04.43.41
53권역1서울13921.112.949.333.03.73.26
54권역2그 외 지역6190.514.250.432.52.43.22