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

Description언론인 의식조사 관련 "편집국 내 최근 1~2년 사이 기자의 사기 변화"에 관한 자료입니다. (사기 저하, 변화없음, 사기 상승)
Author한국언론진흥재단
URLhttps://www.data.go.kr/data/15050484/fileData.do

Alerts

매우 저하됐다 is highly overall correlated with 변화없다 and 2 other fieldsHigh correlation
저하된 편이다 is highly overall correlated with 변화없다 and 2 other fieldsHigh correlation
변화없다 is highly overall correlated with 매우 저하됐다 and 3 other fieldsHigh correlation
상승한 편이다 is highly overall correlated with 매우 저하됐다 and 2 other fieldsHigh correlation
매우 상승했다 is highly overall correlated with 변화없다 and 1 other fieldsHigh correlation
5점 평균 is highly overall correlated with 매우 저하됐다 and 4 other fieldsHigh correlation
대분류 has unique valuesUnique
매우 저하됐다 has 1 (1.9%) zerosZeros
변화없다 has 1 (1.9%) zerosZeros
상승한 편이다 has 1 (1.9%) zerosZeros
매우 상승했다 has 10 (18.5%) zerosZeros

Reproduction

Analysis started2024-03-15 00:27:19.396743
Analysis finished2024-03-15 00:27:33.563116
Duration14.17 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대분류
Text

UNIQUE 

Distinct54
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size560.0 B
2024-03-15T09:27:34.330724image/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%
2024-03-15T09:27:35.618132image/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
2024-03-15T09:27:36.430392image/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%
2024-03-15T09:27:37.483988image/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
2024-03-15T09:27:37.891271image/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
2024-03-15T09:27:38.334943image/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%

매우 저하됐다
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct48
Distinct (%)88.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.609259
Minimum0
Maximum37.5
Zeros1
Zeros (%)1.9%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-15T09:27:38.959776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7.69
Q115.725
median20.2
Q324.25
95-th percentile31.155
Maximum37.5
Range37.5
Interquartile range (IQR)8.525

Descriptive statistics

Standard deviation7.6083437
Coefficient of variation (CV)0.38799751
Kurtosis0.35985514
Mean19.609259
Median Absolute Deviation (MAD)4.4
Skewness-0.23146141
Sum1058.9
Variance57.886894
MonotonicityNot monotonic
2024-03-15T09:27:39.519754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
14.3 2
 
3.7%
26.3 2
 
3.7%
20.9 2
 
3.7%
17.3 2
 
3.7%
17.5 2
 
3.7%
8.6 2
 
3.7%
18.7 1
 
1.9%
37.5 1
 
1.9%
24.1 1
 
1.9%
8.8 1
 
1.9%
Other values (38) 38
70.4%
ValueCountFrequency (%)
0.0 1
1.9%
2.8 1
1.9%
7.3 1
1.9%
7.9 1
1.9%
8.6 2
3.7%
8.8 1
1.9%
9.1 1
1.9%
12.4 1
1.9%
14.3 2
3.7%
15.1 1
1.9%
ValueCountFrequency (%)
37.5 1
1.9%
34.9 1
1.9%
33.3 1
1.9%
30.0 1
1.9%
28.7 1
1.9%
27.9 1
1.9%
27.3 1
1.9%
26.5 1
1.9%
26.3 2
3.7%
26.0 1
1.9%

저하된 편이다
Real number (ℝ)

HIGH CORRELATION 

Distinct50
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43.662963
Minimum28
Maximum64.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-15T09:27:40.002352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum28
5-th percentile29.53
Q140.05
median43.65
Q347.475
95-th percentile53.935
Maximum64.3
Range36.3
Interquartile range (IQR)7.425

Descriptive statistics

Standard deviation7.196574
Coefficient of variation (CV)0.16482102
Kurtosis0.7055154
Mean43.662963
Median Absolute Deviation (MAD)3.8
Skewness0.0094943496
Sum2357.8
Variance51.790678
MonotonicityNot monotonic
2024-03-15T09:27:40.510749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
45.0 3
 
5.6%
47.1 2
 
3.7%
28.1 2
 
3.7%
40.7 1
 
1.9%
42.7 1
 
1.9%
41.4 1
 
1.9%
64.3 1
 
1.9%
55.8 1
 
1.9%
38.5 1
 
1.9%
51.6 1
 
1.9%
Other values (40) 40
74.1%
ValueCountFrequency (%)
28.0 1
1.9%
28.1 2
3.7%
30.3 1
1.9%
34.0 1
1.9%
35.2 1
1.9%
36.1 1
1.9%
37.5 1
1.9%
37.6 1
1.9%
38.1 1
1.9%
38.5 1
1.9%
ValueCountFrequency (%)
64.3 1
1.9%
55.8 1
1.9%
55.3 1
1.9%
53.2 1
1.9%
52.3 1
1.9%
52.1 1
1.9%
52.0 1
1.9%
51.8 1
1.9%
51.6 1
1.9%
50.7 1
1.9%

변화없다
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct43
Distinct (%)79.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.059259
Minimum0
Maximum32.7
Zeros1
Zeros (%)1.9%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-15T09:27:41.028393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile13.545
Q118.05
median21.8
Q323.4
95-th percentile29.65
Maximum32.7
Range32.7
Interquartile range (IQR)5.35

Descriptive statistics

Standard deviation5.5585229
Coefficient of variation (CV)0.26394674
Kurtosis2.9664927
Mean21.059259
Median Absolute Deviation (MAD)3.35
Skewness-0.84019742
Sum1137.2
Variance30.897177
MonotonicityNot monotonic
2024-03-15T09:27:41.508603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
21.8 5
 
9.3%
22.5 3
 
5.6%
23.4 3
 
5.6%
16.7 2
 
3.7%
20.7 2
 
3.7%
29.3 2
 
3.7%
21.9 1
 
1.9%
23.5 1
 
1.9%
15.4 1
 
1.9%
26.9 1
 
1.9%
Other values (33) 33
61.1%
ValueCountFrequency (%)
0.0 1
1.9%
9.6 1
1.9%
12.7 1
1.9%
14.0 1
1.9%
14.3 1
1.9%
15.4 1
1.9%
15.8 1
1.9%
16.0 1
1.9%
16.7 2
3.7%
17.0 1
1.9%
ValueCountFrequency (%)
32.7 1
1.9%
30.4 1
1.9%
30.3 1
1.9%
29.3 2
3.7%
28.4 1
1.9%
27.1 1
1.9%
26.9 1
1.9%
26.8 1
1.9%
25.7 1
1.9%
25.6 1
1.9%

상승한 편이다
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct48
Distinct (%)88.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.235185
Minimum0
Maximum36.4
Zeros1
Zeros (%)1.9%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-15T09:27:41.948353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4.885
Q18.5
median12.65
Q317.675
95-th percentile30.5
Maximum36.4
Range36.4
Interquartile range (IQR)9.175

Descriptive statistics

Standard deviation7.9019023
Coefficient of variation (CV)0.55509656
Kurtosis0.71451128
Mean14.235185
Median Absolute Deviation (MAD)4.75
Skewness0.94714962
Sum768.7
Variance62.440059
MonotonicityNot monotonic
2024-03-15T09:27:42.431875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
8.3 2
 
3.7%
18.5 2
 
3.7%
12.6 2
 
3.7%
7.1 2
 
3.7%
12.5 2
 
3.7%
30.5 2
 
3.7%
20.6 1
 
1.9%
9.6 1
 
1.9%
7.7 1
 
1.9%
7.2 1
 
1.9%
Other values (38) 38
70.4%
ValueCountFrequency (%)
0.0 1
1.9%
2.3 1
1.9%
4.3 1
1.9%
5.2 1
1.9%
6.1 1
1.9%
6.3 1
1.9%
6.4 1
1.9%
7.0 1
1.9%
7.1 2
3.7%
7.2 1
1.9%
ValueCountFrequency (%)
36.4 1
1.9%
33.6 1
1.9%
30.5 2
3.7%
28.6 1
1.9%
25.8 1
1.9%
25.0 1
1.9%
24.6 1
1.9%
20.6 1
1.9%
19.1 1
1.9%
18.8 1
1.9%

매우 상승했다
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct25
Distinct (%)46.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4277778
Minimum0
Maximum5.1
Zeros10
Zeros (%)18.5%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-15T09:27:42.874778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.625
median1.3
Q31.975
95-th percentile3.54
Maximum5.1
Range5.1
Interquartile range (IQR)1.35

Descriptive statistics

Standard deviation1.2003799
Coefficient of variation (CV)0.84073302
Kurtosis0.87829633
Mean1.4277778
Median Absolute Deviation (MAD)0.7
Skewness0.97525962
Sum77.1
Variance1.4409119
MonotonicityNot monotonic
2024-03-15T09:27:43.120197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0.0 10
18.5%
1.3 5
 
9.3%
0.8 4
 
7.4%
1.4 3
 
5.6%
2.5 3
 
5.6%
1.6 2
 
3.7%
0.7 2
 
3.7%
2.0 2
 
3.7%
0.4 2
 
3.7%
3.4 2
 
3.7%
Other values (15) 19
35.2%
ValueCountFrequency (%)
0.0 10
18.5%
0.3 1
 
1.9%
0.4 2
 
3.7%
0.6 1
 
1.9%
0.7 2
 
3.7%
0.8 4
 
7.4%
0.9 2
 
3.7%
1.0 1
 
1.9%
1.1 1
 
1.9%
1.3 5
9.3%
ValueCountFrequency (%)
5.1 1
 
1.9%
4.5 1
 
1.9%
3.8 1
 
1.9%
3.4 2
3.7%
3.0 1
 
1.9%
2.8 2
3.7%
2.5 3
5.6%
2.4 1
 
1.9%
2.0 2
3.7%
1.9 2
3.7%

5점 평균
Real number (ℝ)

HIGH CORRELATION 

Distinct39
Distinct (%)72.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3422222
Minimum1.94
Maximum3.12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-15T09:27:43.518951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.94
5-th percentile1.976
Q12.1775
median2.29
Q32.4675
95-th percentile2.92
Maximum3.12
Range1.18
Interquartile range (IQR)0.29

Descriptive statistics

Standard deviation0.2718814
Coefficient of variation (CV)0.1160784
Kurtosis1.0486817
Mean2.3422222
Median Absolute Deviation (MAD)0.155
Skewness1.0066185
Sum126.48
Variance0.073919497
MonotonicityNot monotonic
2024-03-15T09:27:43.866585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
2.23 4
 
7.4%
2.31 3
 
5.6%
2.21 3
 
5.6%
2.38 2
 
3.7%
2.0 2
 
3.7%
1.95 2
 
3.7%
2.48 2
 
3.7%
2.13 2
 
3.7%
2.92 2
 
3.7%
2.27 2
 
3.7%
Other values (29) 30
55.6%
ValueCountFrequency (%)
1.94 1
1.9%
1.95 2
3.7%
1.99 1
1.9%
2.0 2
3.7%
2.01 1
1.9%
2.1 1
1.9%
2.11 1
1.9%
2.13 2
3.7%
2.14 1
1.9%
2.15 1
1.9%
ValueCountFrequency (%)
3.12 1
1.9%
3.06 1
1.9%
2.92 2
3.7%
2.84 1
1.9%
2.7 1
1.9%
2.64 1
1.9%
2.57 1
1.9%
2.56 1
1.9%
2.52 1
1.9%
2.49 1
1.9%

Interactions

2024-03-15T09:27:30.879030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:19.851800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:21.786556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:23.578554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:25.445504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:27.289515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:29.242259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:31.136807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:20.046582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:22.047329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:23.905122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:25.714207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:27.569058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:29.506476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:31.394273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:20.311644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:22.309834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:24.121790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:25.981596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:27.870602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:29.780431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:31.652323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:20.577123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:22.575623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:24.282369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:26.251748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:28.162761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:29.933871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:31.902524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:21.031481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:22.821115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:24.639175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:26.505150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:28.392110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:30.124955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:32.157096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:21.291029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:23.078833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:24.919784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:26.769590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:28.642845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:30.376054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:32.395615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:21.540520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:23.328839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:25.183050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:27.034366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:28.895480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:27:30.636654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T09:27:44.116751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대분류중분류사례수매우 저하됐다저하된 편이다변화없다상승한 편이다매우 상승했다5점 평균
대분류1.0001.0001.0001.0001.0001.0001.0001.0001.000
중분류1.0001.0001.0001.0001.0001.0001.0001.0001.000
사례수1.0001.0001.0000.0000.0000.0000.1620.4020.168
매우 저하됐다1.0001.0000.0001.0000.5440.7220.8600.7560.936
저하된 편이다1.0001.0000.0000.5441.0000.7780.6890.5610.671
변화없다1.0001.0000.0000.7220.7781.0000.6790.4820.667
상승한 편이다1.0001.0000.1620.8600.6890.6791.0000.8270.960
매우 상승했다1.0001.0000.4020.7560.5610.4820.8271.0000.872
5점 평균1.0001.0000.1680.9360.6710.6670.9600.8721.000
2024-03-15T09:27:44.430687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사례수매우 저하됐다저하된 편이다변화없다상승한 편이다매우 상승했다5점 평균
사례수1.000-0.138-0.1320.1360.2260.1360.250
매우 저하됐다-0.1381.0000.209-0.635-0.661-0.450-0.861
저하된 편이다-0.1320.2091.000-0.589-0.669-0.446-0.601
변화없다0.136-0.635-0.5891.0000.4920.5300.769
상승한 편이다0.226-0.661-0.6690.4921.0000.3200.853
매우 상승했다0.136-0.450-0.4460.5300.3201.0000.593
5점 평균0.250-0.861-0.6010.7690.8530.5931.000

Missing values

2024-03-15T09:27:32.935888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T09:27:33.389305image/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

대분류중분류사례수매우 저하됐다저하된 편이다변화없다상승한 편이다매우 상승했다5점 평균
0성별1남자137618.740.721.917.21.62.42
1성별2여자63520.947.621.19.11.32.22
2연령120대21714.345.224.411.15.12.47
3연령230~34세39126.339.420.712.01.52.23
4연령335~39세38225.441.619.913.10.02.21
5연령440~44세31720.547.018.612.90.92.27
6연령545~49세22515.148.422.213.30.92.36
7연령650대37215.343.821.817.71.32.46
8연령760대 이상1072.828.032.733.62.83.06
9매체유형1신문사106520.046.720.711.80.82.27
대분류중분류사례수매우 저하됐다저하된 편이다변화없다상승한 편이다매우 상승했다5점 평균
44직위3부장/부장대우20917.740.226.814.41.02.41
45직위4차장/차장대우45721.249.716.012.70.42.21
46직위5평기자101822.742.121.811.42.02.28
47경력11~4년42612.438.725.618.84.52.64
48경력25~9년45726.338.123.410.91.32.23
49경력310~14년39924.644.417.013.80.32.21
50경력415~19년27217.350.717.314.00.72.3
51경력520년 이상45715.845.522.815.50.42.39
52권역1서울139220.443.921.812.61.32.31
53권역2그 외 지역61917.140.521.319.11.92.48