Overview

Dataset statistics

Number of variables9
Number of observations54
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.3 KiB
Average record size in memory81.4 B

Variable types

Text2
Numeric7

Dataset

Description기사작성 시 취재환경에 대한 평가에 대한 언론인 조사 통계 파일데이터 입니다. 자세한 내용은 한국언론진흥재단 홈페이지에서 자세히 확인하실 수 있습니다.
Author한국언론진흥재단
URLhttps://www.data.go.kr/data/15060157/fileData.do

Alerts

타 부서와의 협력이 잘 이뤄진다 is highly overall correlated with 기사 작성 및 송고 시스템이 잘 갖추어져 있다High correlation
기사 작성 및 송고 시스템이 잘 갖추어져 있다 is highly overall correlated with 타 부서와의 협력이 잘 이뤄진다 and 2 other fieldsHigh correlation
사내 아카이브 등 취재 기초 자료가 잘 축적되어 있다 is highly overall correlated with 기사 작성 및 송고 시스템이 잘 갖추어져 있다 and 1 other fieldsHigh correlation
취재 지원이 잘 된다 is highly overall correlated with 기사 작성 및 송고 시스템이 잘 갖추어져 있다 and 1 other fieldsHigh correlation
구분 has unique valuesUnique

Reproduction

Analysis started2024-03-15 00:37:19.754626
Analysis finished2024-03-15 00:37:34.693429
Duration14.94 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
2024-03-15T09:37:35.541070image/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%
2024-03-15T09:37:36.939848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
소 29
12.1%
속 29
12.1%
1 21
 
8.8%
부 18
 
7.5%
서 18
 
7.5%
매 15
 
6.3%
체 15
 
6.3%
2 9
 
3.8%
령 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 (%)
소 29
16.7%
속 29
16.7%
부 18
10.3%
서 18
10.3%
매 15
8.6%
체 15
8.6%
령 7
 
4.0%
연 7
 
4.0%
경 5
 
2.9%
위 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 (%)
소 29
16.7%
속 29
16.7%
부 18
10.3%
서 18
10.3%
매 15
8.6%
체 15
8.6%
령 7
 
4.0%
연 7
 
4.0%
경 5
 
2.9%
위 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 (%)
소 29
16.7%
속 29
16.7%
부 18
10.3%
서 18
10.3%
매 15
8.6%
체 15
8.6%
령 7
 
4.0%
연 7
 
4.0%
경 5
 
2.9%
위 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%

중분류
Text

Distinct52
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Memory size560.0 B
2024-03-15T09:37:37.835937image/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%
그 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%
2024-03-15T09:37:39.221497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 20
 
6.7%
부 14
 
4.7%
사 11
 
3.7%
국 10
 
3.3%
4 8
 
2.7%
~ 8
 
2.7%
장 8
 
2.7%
대 7
 
2.3%
일 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 (%)
부 14
 
6.3%
사 11
 
4.9%
국 10
 
4.5%
장 8
 
3.6%
대 7
 
3.1%
일 7
 
3.1%
지 6
 
2.7%
년 5
 
2.2%
간 5
 
2.2%
스 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 (%)
부 14
 
6.3%
사 11
 
4.9%
국 10
 
4.5%
장 8
 
3.6%
대 7
 
3.1%
일 7
 
3.1%
지 6
 
2.7%
년 5
 
2.2%
간 5
 
2.2%
스 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 (%)
부 14
 
6.3%
사 11
 
4.9%
국 10
 
4.5%
장 8
 
3.6%
대 7
 
3.1%
일 7
 
3.1%
지 6
 
2.7%
년 5
 
2.2%
간 5
 
2.2%
스 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
2024-03-15T09:37:39.621051image/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
2024-03-15T09:37:40.068076image/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%

취재원_정보원에 대한 접촉이 쉽다
Real number (ℝ)

Distinct22
Distinct (%)40.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.3909259
Minimum3
Maximum3.74
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-15T09:37:40.472697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile3.17
Q13.35
median3.38
Q33.4375
95-th percentile3.655
Maximum3.74
Range0.74
Interquartile range (IQR)0.0875

Descriptive statistics

Standard deviation0.1363025
Coefficient of variation (CV)0.040196248
Kurtosis1.8298353
Mean3.3909259
Median Absolute Deviation (MAD)0.04
Skewness0.16699017
Sum183.11
Variance0.018578372
MonotonicityNot monotonic
2024-03-15T09:37:40.879454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
3.38 10
18.5%
3.48 4
 
7.4%
3.34 4
 
7.4%
3.36 4
 
7.4%
3.35 4
 
7.4%
3.39 3
 
5.6%
3.46 3
 
5.6%
3.4 2
 
3.7%
3.17 2
 
3.7%
3.18 2
 
3.7%
Other values (12) 16
29.6%
ValueCountFrequency (%)
3.0 1
 
1.9%
3.15 1
 
1.9%
3.17 2
 
3.7%
3.18 2
 
3.7%
3.19 1
 
1.9%
3.31 1
 
1.9%
3.34 4
 
7.4%
3.35 4
 
7.4%
3.36 4
 
7.4%
3.38 10
18.5%
ValueCountFrequency (%)
3.74 1
 
1.9%
3.72 2
3.7%
3.62 2
3.7%
3.54 1
 
1.9%
3.48 4
7.4%
3.46 3
5.6%
3.44 1
 
1.9%
3.43 1
 
1.9%
3.42 2
3.7%
3.41 2
3.7%

정보가 잘 공개되어 있다
Real number (ℝ)

Distinct28
Distinct (%)51.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.2233333
Minimum2.91
Maximum3.75
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-15T09:37:41.280570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.91
5-th percentile3.076
Q13.16
median3.21
Q33.2675
95-th percentile3.43
Maximum3.75
Range0.84
Interquartile range (IQR)0.1075

Descriptive statistics

Standard deviation0.12506602
Coefficient of variation (CV)0.038800213
Kurtosis5.4627122
Mean3.2233333
Median Absolute Deviation (MAD)0.055
Skewness1.2185128
Sum174.06
Variance0.015641509
MonotonicityNot monotonic
2024-03-15T09:37:41.656501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
3.15 4
 
7.4%
3.21 4
 
7.4%
3.25 4
 
7.4%
3.18 3
 
5.6%
3.22 3
 
5.6%
3.33 3
 
5.6%
3.2 3
 
5.6%
3.16 3
 
5.6%
3.26 2
 
3.7%
3.43 2
 
3.7%
Other values (18) 23
42.6%
ValueCountFrequency (%)
2.91 1
 
1.9%
2.97 1
 
1.9%
3.05 1
 
1.9%
3.09 1
 
1.9%
3.1 1
 
1.9%
3.11 2
3.7%
3.13 1
 
1.9%
3.14 1
 
1.9%
3.15 4
7.4%
3.16 3
5.6%
ValueCountFrequency (%)
3.75 1
 
1.9%
3.44 1
 
1.9%
3.43 2
3.7%
3.38 1
 
1.9%
3.35 1
 
1.9%
3.33 3
5.6%
3.31 2
3.7%
3.29 1
 
1.9%
3.27 2
3.7%
3.26 2
3.7%

타 부서와의 협력이 잘 이뤄진다
Real number (ℝ)

HIGH CORRELATION 

Distinct38
Distinct (%)70.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0492593
Minimum2.5
Maximum3.53
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-15T09:37:42.242322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.5
5-th percentile2.7995
Q12.9
median2.99
Q33.21
95-th percentile3.4445
Maximum3.53
Range1.03
Interquartile range (IQR)0.31

Descriptive statistics

Standard deviation0.22988801
Coefficient of variation (CV)0.075391428
Kurtosis-0.15151064
Mean3.0492593
Median Absolute Deviation (MAD)0.13
Skewness0.29891317
Sum164.66
Variance0.052848498
MonotonicityNot monotonic
2024-03-15T09:37:42.660150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
2.82 3
 
5.6%
2.92 3
 
5.6%
2.99 3
 
5.6%
3.41 2
 
3.7%
3.0 2
 
3.7%
3.18 2
 
3.7%
2.97 2
 
3.7%
2.85 2
 
3.7%
3.38 2
 
3.7%
2.89 2
 
3.7%
Other values (28) 31
57.4%
ValueCountFrequency (%)
2.5 1
 
1.9%
2.57 1
 
1.9%
2.78 1
 
1.9%
2.81 1
 
1.9%
2.82 3
5.6%
2.85 2
3.7%
2.87 2
3.7%
2.89 2
3.7%
2.9 2
3.7%
2.91 1
 
1.9%
ValueCountFrequency (%)
3.53 1
1.9%
3.51 1
1.9%
3.49 1
1.9%
3.42 1
1.9%
3.41 2
3.7%
3.38 2
3.7%
3.33 1
1.9%
3.29 1
1.9%
3.28 1
1.9%
3.26 1
1.9%

기사 작성 및 송고 시스템이 잘 갖추어져 있다
Real number (ℝ)

HIGH CORRELATION 

Distinct34
Distinct (%)63.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.7227778
Minimum3.36
Maximum3.98
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-15T09:37:43.048398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.36
5-th percentile3.56
Q13.6325
median3.71
Q33.82
95-th percentile3.9035
Maximum3.98
Range0.62
Interquartile range (IQR)0.1875

Descriptive statistics

Standard deviation0.12314153
Coefficient of variation (CV)0.033077862
Kurtosis0.050938236
Mean3.7227778
Median Absolute Deviation (MAD)0.1
Skewness-0.19995012
Sum201.03
Variance0.015163836
MonotonicityNot monotonic
2024-03-15T09:37:43.472664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
3.7 4
 
7.4%
3.71 4
 
7.4%
3.86 3
 
5.6%
3.61 3
 
5.6%
3.58 2
 
3.7%
3.75 2
 
3.7%
3.56 2
 
3.7%
3.88 2
 
3.7%
3.81 2
 
3.7%
3.82 2
 
3.7%
Other values (24) 28
51.9%
ValueCountFrequency (%)
3.36 1
 
1.9%
3.53 1
 
1.9%
3.56 2
3.7%
3.57 1
 
1.9%
3.58 2
3.7%
3.59 1
 
1.9%
3.6 1
 
1.9%
3.61 3
5.6%
3.62 1
 
1.9%
3.63 1
 
1.9%
ValueCountFrequency (%)
3.98 1
 
1.9%
3.92 1
 
1.9%
3.91 1
 
1.9%
3.9 2
3.7%
3.88 2
3.7%
3.86 3
5.6%
3.85 1
 
1.9%
3.84 1
 
1.9%
3.83 1
 
1.9%
3.82 2
3.7%

사내 아카이브 등 취재 기초 자료가 잘 축적되어 있다
Real number (ℝ)

HIGH CORRELATION 

Distinct41
Distinct (%)75.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0068519
Minimum2.38
Maximum3.61
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-15T09:37:43.885190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.38
5-th percentile2.6305
Q12.8325
median3.01
Q33.15
95-th percentile3.354
Maximum3.61
Range1.23
Interquartile range (IQR)0.3175

Descriptive statistics

Standard deviation0.25062054
Coefficient of variation (CV)0.083349814
Kurtosis0.10066498
Mean3.0068519
Median Absolute Deviation (MAD)0.17
Skewness-0.12437174
Sum162.37
Variance0.062810657
MonotonicityNot monotonic
2024-03-15T09:37:44.332565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
3.01 5
 
9.3%
3.15 3
 
5.6%
2.84 2
 
3.7%
2.78 2
 
3.7%
3.13 2
 
3.7%
2.8 2
 
3.7%
3.14 2
 
3.7%
3.27 2
 
3.7%
2.69 2
 
3.7%
3.34 1
 
1.9%
Other values (31) 31
57.4%
ValueCountFrequency (%)
2.38 1
1.9%
2.48 1
1.9%
2.52 1
1.9%
2.69 2
3.7%
2.7 1
1.9%
2.74 1
1.9%
2.76 1
1.9%
2.77 1
1.9%
2.78 2
3.7%
2.8 2
3.7%
ValueCountFrequency (%)
3.61 1
1.9%
3.5 1
1.9%
3.38 1
1.9%
3.34 1
1.9%
3.33 1
1.9%
3.32 1
1.9%
3.28 1
1.9%
3.27 2
3.7%
3.26 1
1.9%
3.25 1
1.9%

취재 지원이 잘 된다
Real number (ℝ)

HIGH CORRELATION 

Distinct39
Distinct (%)72.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0353704
Minimum2.23
Maximum3.64
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-15T09:37:44.728648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.23
5-th percentile2.7765
Q12.89
median3.045
Q33.16
95-th percentile3.3815
Maximum3.64
Range1.41
Interquartile range (IQR)0.27

Descriptive statistics

Standard deviation0.22839649
Coefficient of variation (CV)0.075245014
Kurtosis2.3923395
Mean3.0353704
Median Absolute Deviation (MAD)0.13
Skewness-0.34434256
Sum163.91
Variance0.052164955
MonotonicityNot monotonic
2024-03-15T09:37:45.224079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
3.06 3
 
5.6%
3.15 3
 
5.6%
3.16 3
 
5.6%
3.17 3
 
5.6%
3.13 2
 
3.7%
2.84 2
 
3.7%
2.79 2
 
3.7%
2.88 2
 
3.7%
3.24 2
 
3.7%
2.97 2
 
3.7%
Other values (29) 30
55.6%
ValueCountFrequency (%)
2.23 1
1.9%
2.61 1
1.9%
2.77 1
1.9%
2.78 1
1.9%
2.79 2
3.7%
2.83 1
1.9%
2.84 2
3.7%
2.85 1
1.9%
2.86 1
1.9%
2.88 2
3.7%
ValueCountFrequency (%)
3.64 1
 
1.9%
3.5 1
 
1.9%
3.44 1
 
1.9%
3.35 1
 
1.9%
3.33 1
 
1.9%
3.29 1
 
1.9%
3.26 1
 
1.9%
3.24 2
3.7%
3.18 1
 
1.9%
3.17 3
5.6%

Interactions

2024-03-15T09:37:32.181337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:20.212422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:21.701425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:23.501616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:25.461626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:28.389694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:30.688400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:32.457649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:20.466760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:21.927701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:23.752575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:25.732242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:29.029209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:31.010783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:32.730045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:20.732677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:22.199330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:24.007304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:26.065758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:29.288498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:31.281305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:32.968797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:20.975323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:22.440933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:24.236658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:26.460777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:29.531984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:31.422217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:33.219542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:21.213386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:22.695846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:24.468682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:26.990123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:29.855866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:31.569099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:33.502850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:21.373316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:22.963380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:24.925336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:27.458954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:30.132592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:31.733106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:33.764926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:21.535184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:23.231879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:25.169484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:27.905664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:30.399672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:37:31.888697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T09:37:45.583851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분중분류사례수취재원_정보원에 대한 접촉이 쉽다정보가 잘 공개되어 있다타 부서와의 협력이 잘 이뤄진다기사 작성 및 송고 시스템이 잘 갖추어져 있다사내 아카이브 등 취재 기초 자료가 잘 축적되어 있다취재 지원이 잘 된다
구분1.0001.0001.0001.0001.0001.0001.0001.0001.000
중분류1.0001.0001.0001.0001.0001.0001.0001.0001.000
사례수1.0001.0001.0000.0000.0000.0000.1230.0000.000
취재원_정보원에 대한 접촉이 쉽다1.0001.0000.0001.0000.6540.2560.0000.3480.410
정보가 잘 공개되어 있다1.0001.0000.0000.6541.0000.4910.0000.3830.245
타 부서와의 협력이 잘 이뤄진다1.0001.0000.0000.2560.4911.0000.8320.6490.708
기사 작성 및 송고 시스템이 잘 갖추어져 있다1.0001.0000.1230.0000.0000.8321.0000.7330.859
사내 아카이브 등 취재 기초 자료가 잘 축적되어 있다1.0001.0000.0000.3480.3830.6490.7331.0000.839
취재 지원이 잘 된다1.0001.0000.0000.4100.2450.7080.8590.8391.000
2024-03-15T09:37:45.934324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사례수취재원_정보원에 대한 접촉이 쉽다정보가 잘 공개되어 있다타 부서와의 협력이 잘 이뤄진다기사 작성 및 송고 시스템이 잘 갖추어져 있다사내 아카이브 등 취재 기초 자료가 잘 축적되어 있다취재 지원이 잘 된다
사례수1.000-0.048-0.3150.133-0.074-0.321-0.325
취재원_정보원에 대한 접촉이 쉽다-0.0481.0000.2220.1800.2230.084-0.076
정보가 잘 공개되어 있다-0.3150.2221.000-0.0540.2640.0510.206
타 부서와의 협력이 잘 이뤄진다0.1330.180-0.0541.0000.7380.4500.466
기사 작성 및 송고 시스템이 잘 갖추어져 있다-0.0740.2230.2640.7381.0000.6780.743
사내 아카이브 등 취재 기초 자료가 잘 축적되어 있다-0.3210.0840.0510.4500.6781.0000.827
취재 지원이 잘 된다-0.325-0.0760.2060.4660.7430.8271.000

Missing values

2024-03-15T09:37:34.133935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T09:37:34.587079image/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

구분중분류사례수취재원_정보원에 대한 접촉이 쉽다정보가 잘 공개되어 있다타 부서와의 협력이 잘 이뤄진다기사 작성 및 송고 시스템이 잘 갖추어져 있다사내 아카이브 등 취재 기초 자료가 잘 축적되어 있다취재 지원이 잘 된다
0성별1남자13763.393.183.113.733.023.06
1성별2여자6353.383.252.933.672.82.84
2연령120대2173.483.332.963.783.012.92
3연령230~34세3913.383.152.93.532.72.78
4연령335~39세3823.343.22.893.622.772.89
5연령440~44세3173.433.192.983.682.953.02
6연령545~49세2253.343.163.133.772.933.09
7연령650대3723.393.23.333.913.253.17
8연령760대 이상1073.363.213.493.853.383.26
9매체유형1신문사10653.383.173.03.642.782.84
구분중분류사례수취재원_정보원에 대한 접촉이 쉽다정보가 잘 공개되어 있다타 부서와의 협력이 잘 이뤄진다기사 작성 및 송고 시스템이 잘 갖추어져 있다사내 아카이브 등 취재 기초 자료가 잘 축적되어 있다취재 지원이 잘 된다
44직위3부장/부장대우2093.363.153.283.843.133.07
45직위4차장/차장대우4573.343.172.993.652.842.97
46직위5평기자10183.43.222.93.632.832.88
47경력11~4년4263.463.293.143.763.012.94
48경력25~9년4573.353.112.853.582.692.79
49경력310~14년3993.363.182.993.652.882.96
50경력415~19년2723.393.263.023.73.073.16
51경력520년 이상4573.383.183.243.863.143.15
52권역1서울13923.383.232.993.712.93.03
53권역2그 외 지역6193.423.133.183.723.052.9