Overview

Dataset statistics

Number of variables11
Number of observations54
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.2 KiB
Average record size in memory99.4 B

Variable types

Text2
Numeric9

Dataset

Description언론사내 주52시간 근무제 도입을 위해 필요한 노력 평가에 대한 언론조사통계 데이터입니다. 자세한 내용은 한국언론진흥재단 홈페이지에서 확인하시기 바랍니다.
Author한국언론진흥재단
URLhttps://www.data.go.kr/data/15060167/fileData.do

Alerts

인력 충원 is highly overall correlated with 업무량 조정High correlation
업무량 조정 is highly overall correlated with 인력 충원High correlation
구분 has unique valuesUnique
연장 근무 제한 has 4 (7.4%) zerosZeros
포괄임금제(수당을 급여에 미리 포함하는 계약) 폐지 has 2 (3.7%) zerosZeros
연차대체휴가 부여 및 사용에 대한 보장 has 6 (11.1%) zerosZeros
기타 has 12 (22.2%) zerosZeros

Reproduction

Analysis started2024-03-15 01:25:18.268871
Analysis finished2024-03-15 01:25:39.873811
Duration21.6 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
2024-03-15T10:25:40.695754image/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%
2024-03-15T10:25:41.830140image/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
2024-03-15T10:25:42.717462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length8
Mean length5.0740741
Min length2

Characters and Unicode

Total characters274
Distinct characters103
Distinct categories7 ?
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
 
3.3%
이상 2
 
3.3%
기타 2
 
3.3%
인터넷언론사 2
 
3.3%
15-19년 1
 
1.7%
지역전국 1
 
1.7%
취재(보도)일반 1
 
1.7%
남자 1
 
1.7%
국방통일북한 1
 
1.7%
편집(편성)교열부 1
 
1.7%
Other values (46) 46
76.7%
2024-03-15T10:25:43.812485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
부 14
 
5.1%
사 11
 
4.0%
국 9
 
3.3%
4 8
 
2.9%
장 8
 
2.9%
- 8
 
2.9%
0 7
 
2.6%
대 7
 
2.6%
일 7
 
2.6%
6
 
2.2%
Other values (93) 189
69.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 217
79.2%
Decimal Number 37
 
13.5%
Dash Punctuation 8
 
2.9%
Space Separator 6
 
2.2%
Close Punctuation 2
 
0.7%
Open Punctuation 2
 
0.7%
Uppercase Letter 2
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 14
 
6.5%
사 11
 
5.1%
국 9
 
4.1%
장 8
 
3.7%
대 7
 
3.2%
일 7
 
3.2%
지 6
 
2.8%
스 5
 
2.3%
년 5
 
2.3%
간 5
 
2.3%
Other values (79) 140
64.5%
Decimal Number
ValueCountFrequency (%)
4 8
21.6%
0 7
18.9%
3 5
13.5%
5 5
13.5%
1 5
13.5%
9 4
10.8%
2 2
 
5.4%
6 1
 
2.7%
Uppercase Letter
ValueCountFrequency (%)
T 1
50.0%
I 1
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 217
79.2%
Common 55
 
20.1%
Latin 2
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 14
 
6.5%
사 11
 
5.1%
국 9
 
4.1%
장 8
 
3.7%
대 7
 
3.2%
일 7
 
3.2%
지 6
 
2.8%
스 5
 
2.3%
년 5
 
2.3%
간 5
 
2.3%
Other values (79) 140
64.5%
Common
ValueCountFrequency (%)
4 8
14.5%
- 8
14.5%
0 7
12.7%
6
10.9%
3 5
9.1%
5 5
9.1%
1 5
9.1%
9 4
7.3%
) 2
 
3.6%
( 2
 
3.6%
Other values (2) 3
 
5.5%
Latin
ValueCountFrequency (%)
T 1
50.0%
I 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 217
79.2%
ASCII 57
 
20.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
부 14
 
6.5%
사 11
 
5.1%
국 9
 
4.1%
장 8
 
3.7%
대 7
 
3.2%
일 7
 
3.2%
지 6
 
2.8%
스 5
 
2.3%
년 5
 
2.3%
간 5
 
2.3%
Other values (79) 140
64.5%
ASCII
ValueCountFrequency (%)
4 8
14.0%
- 8
14.0%
0 7
12.3%
6
10.5%
3 5
8.8%
5 5
8.8%
1 5
8.8%
9 4
7.0%
) 2
 
3.5%
( 2
 
3.5%
Other values (4) 5
8.8%

사례수
Real number (ℝ)

Distinct50
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean298.37037
Minimum8
Maximum1441
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-15T10:25:44.163476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile28.65
Q181.75
median195.5
Q3407
95-th percentile1033.45
Maximum1441
Range1433
Interquartile range (IQR)325.25

Descriptive statistics

Standard deviation315.83255
Coefficient of variation (CV)1.0585252
Kurtosis4.8058914
Mean298.37037
Median Absolute Deviation (MAD)143
Skewness2.0986396
Sum16112
Variance99750.2
MonotonicityNot monotonic
2024-03-15T10:25:44.615051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
136 3
 
5.6%
491 2
 
3.7%
29 2
 
3.7%
1370 1
 
1.9%
149 1
 
1.9%
140 1
 
1.9%
28 1
 
1.9%
53 1
 
1.9%
58 1
 
1.9%
147 1
 
1.9%
Other values (40) 40
74.1%
ValueCountFrequency (%)
8 1
1.9%
16 1
1.9%
28 1
1.9%
29 2
3.7%
30 1
1.9%
50 1
1.9%
52 1
1.9%
53 1
1.9%
58 1
1.9%
66 1
1.9%
ValueCountFrequency (%)
1441 1
1.9%
1370 1
1.9%
1090 1
1.9%
1003 1
1.9%
644 1
1.9%
573 1
1.9%
508 1
1.9%
491 2
3.7%
446 1
1.9%
440 1
1.9%

인력 충원
Real number (ℝ)

HIGH CORRELATION 

Distinct48
Distinct (%)88.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46.531481
Minimum28.6
Maximum68
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-15T10:25:45.104096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum28.6
5-th percentile33.365
Q142.35
median46.65
Q350.95
95-th percentile56.04
Maximum68
Range39.4
Interquartile range (IQR)8.6

Descriptive statistics

Standard deviation7.3025409
Coefficient of variation (CV)0.15693764
Kurtosis0.81807919
Mean46.531481
Median Absolute Deviation (MAD)4.4
Skewness0.00084857984
Sum2512.7
Variance53.327103
MonotonicityNot monotonic
2024-03-15T10:25:45.530644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
51.7 2
 
3.7%
46.7 2
 
3.7%
50.8 2
 
3.7%
50.2 2
 
3.7%
46.3 2
 
3.7%
33.4 2
 
3.7%
28.6 1
 
1.9%
39.6 1
 
1.9%
44.8 1
 
1.9%
42.2 1
 
1.9%
Other values (38) 38
70.4%
ValueCountFrequency (%)
28.6 1
1.9%
32.7 1
1.9%
33.3 1
1.9%
33.4 2
3.7%
37.5 1
1.9%
38.9 1
1.9%
39.6 1
1.9%
40.0 1
1.9%
41.1 1
1.9%
41.7 1
1.9%
ValueCountFrequency (%)
68.0 1
1.9%
60.0 1
1.9%
57.6 1
1.9%
55.2 1
1.9%
55.0 1
1.9%
54.8 1
1.9%
54.4 1
1.9%
53.9 1
1.9%
53.0 1
1.9%
52.9 1
1.9%

유연근무제 도입
Real number (ℝ)

Distinct42
Distinct (%)77.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.257407
Minimum8.7
Maximum36
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-15T10:25:45.848412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8.7
5-th percentile9.895
Q113.95
median16.7
Q319.2
95-th percentile28.755
Maximum36
Range27.3
Interquartile range (IQR)5.25

Descriptive statistics

Standard deviation5.5637507
Coefficient of variation (CV)0.32239783
Kurtosis2.3623676
Mean17.257407
Median Absolute Deviation (MAD)2.6
Skewness1.2949216
Sum931.9
Variance30.955321
MonotonicityNot monotonic
2024-03-15T10:25:46.088858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
15.4 2
 
3.7%
20.7 2
 
3.7%
17.7 2
 
3.7%
18.6 2
 
3.7%
12.5 2
 
3.7%
15.0 2
 
3.7%
17.5 2
 
3.7%
14.1 2
 
3.7%
16.9 2
 
3.7%
16.2 2
 
3.7%
Other values (32) 34
63.0%
ValueCountFrequency (%)
8.7 1
1.9%
9.0 1
1.9%
9.7 1
1.9%
10.0 1
1.9%
10.1 1
1.9%
11.1 1
1.9%
12.0 1
1.9%
12.3 1
1.9%
12.5 2
3.7%
12.7 1
1.9%
ValueCountFrequency (%)
36.0 1
1.9%
32.1 1
1.9%
30.9 1
1.9%
27.6 1
1.9%
25.8 1
1.9%
24.3 1
1.9%
22.3 1
1.9%
21.8 1
1.9%
20.7 2
3.7%
20.6 1
1.9%

업무량 조정
Real number (ℝ)

HIGH CORRELATION 

Distinct44
Distinct (%)81.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.522222
Minimum3.4
Maximum25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-15T10:25:46.339581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.4
5-th percentile6.93
Q19.925
median12.3
Q314.75
95-th percentile19.1
Maximum25
Range21.6
Interquartile range (IQR)4.825

Descriptive statistics

Standard deviation4.0429611
Coefficient of variation (CV)0.32286291
Kurtosis1.015184
Mean12.522222
Median Absolute Deviation (MAD)2.45
Skewness0.54675597
Sum676.2
Variance16.345535
MonotonicityNot monotonic
2024-03-15T10:25:46.592581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
13.8 4
 
7.4%
15.7 3
 
5.6%
10.3 2
 
3.7%
9.4 2
 
3.7%
19.1 2
 
3.7%
15.5 2
 
3.7%
10.9 2
 
3.7%
25.0 1
 
1.9%
8.6 1
 
1.9%
14.3 1
 
1.9%
Other values (34) 34
63.0%
ValueCountFrequency (%)
3.4 1
1.9%
5.3 1
1.9%
6.8 1
1.9%
7.0 1
1.9%
7.5 1
1.9%
7.6 1
1.9%
8.3 1
1.9%
8.6 1
1.9%
9.1 1
1.9%
9.2 1
1.9%
ValueCountFrequency (%)
25.0 1
 
1.9%
22.0 1
 
1.9%
19.1 2
3.7%
18.8 1
 
1.9%
17.3 1
 
1.9%
15.9 1
 
1.9%
15.7 3
5.6%
15.5 2
3.7%
15.2 1
 
1.9%
14.8 1
 
1.9%

연장 근무 제한
Real number (ℝ)

ZEROS 

Distinct39
Distinct (%)72.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.4777778
Minimum0
Maximum15.4
Zeros4
Zeros (%)7.4%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-15T10:25:47.002975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14.45
median6.05
Q38.5
95-th percentile12.955
Maximum15.4
Range15.4
Interquartile range (IQR)4.05

Descriptive statistics

Standard deviation3.5183973
Coefficient of variation (CV)0.54314881
Kurtosis0.44110588
Mean6.4777778
Median Absolute Deviation (MAD)2
Skewness0.41272563
Sum349.8
Variance12.379119
MonotonicityNot monotonic
2024-03-15T10:25:47.340866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
0.0 4
 
7.4%
4.4 3
 
5.6%
11.4 2
 
3.7%
9.1 2
 
3.7%
9.0 2
 
3.7%
6.6 2
 
3.7%
4.6 2
 
3.7%
5.1 2
 
3.7%
6.0 2
 
3.7%
5.3 2
 
3.7%
Other values (29) 31
57.4%
ValueCountFrequency (%)
0.0 4
7.4%
1.5 1
 
1.9%
2.7 1
 
1.9%
2.9 1
 
1.9%
3.1 1
 
1.9%
3.4 2
3.7%
4.1 1
 
1.9%
4.4 3
5.6%
4.6 2
3.7%
4.9 1
 
1.9%
ValueCountFrequency (%)
15.4 1
1.9%
15.1 1
1.9%
13.8 1
1.9%
12.5 1
1.9%
11.4 2
3.7%
10.2 1
1.9%
9.5 1
1.9%
9.1 2
3.7%
9.0 2
3.7%
8.9 1
1.9%

포괄임금제(수당을 급여에 미리 포함하는 계약) 폐지
Real number (ℝ)

ZEROS 

Distinct35
Distinct (%)64.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.1518519
Minimum0
Maximum11.7
Zeros2
Zeros (%)3.7%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-15T10:25:47.810717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.9
Q13.8
median6.6
Q37.9
95-th percentile9.905
Maximum11.7
Range11.7
Interquartile range (IQR)4.1

Descriptive statistics

Standard deviation2.5644699
Coefficient of variation (CV)0.41686146
Kurtosis-0.16408457
Mean6.1518519
Median Absolute Deviation (MAD)1.75
Skewness-0.23622258
Sum332.2
Variance6.5765059
MonotonicityNot monotonic
2024-03-15T10:25:48.065499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
7.8 4
 
7.4%
7.9 4
 
7.4%
3.7 3
 
5.6%
7.7 3
 
5.6%
3.8 3
 
5.6%
8.5 2
 
3.7%
2.9 2
 
3.7%
0.0 2
 
3.7%
3.4 2
 
3.7%
6.3 2
 
3.7%
Other values (25) 27
50.0%
ValueCountFrequency (%)
0.0 2
3.7%
2.9 2
3.7%
3.0 1
 
1.9%
3.3 1
 
1.9%
3.4 2
3.7%
3.5 1
 
1.9%
3.6 1
 
1.9%
3.7 3
5.6%
3.8 3
5.6%
4.0 1
 
1.9%
ValueCountFrequency (%)
11.7 1
 
1.9%
11.5 1
 
1.9%
10.1 1
 
1.9%
9.8 1
 
1.9%
8.8 1
 
1.9%
8.5 2
3.7%
8.4 1
 
1.9%
8.3 2
3.7%
8.0 1
 
1.9%
7.9 4
7.4%

임금 감소에 대비한 대책 마련
Real number (ℝ)

Distinct35
Distinct (%)64.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.9240741
Minimum3.3
Maximum12.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-15T10:25:48.465187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.3
5-th percentile4.16
Q15.7
median6.65
Q38.2
95-th percentile10.31
Maximum12.5
Range9.2
Interquartile range (IQR)2.5

Descriptive statistics

Standard deviation1.9751222
Coefficient of variation (CV)0.28525434
Kurtosis0.54646041
Mean6.9240741
Median Absolute Deviation (MAD)1.15
Skewness0.77964818
Sum373.9
Variance3.9011076
MonotonicityNot monotonic
2024-03-15T10:25:48.883481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
5.7 4
 
7.4%
6.9 3
 
5.6%
6.3 3
 
5.6%
6.7 3
 
5.6%
5.9 3
 
5.6%
5.5 3
 
5.6%
9.1 3
 
5.6%
7.4 2
 
3.7%
5.2 2
 
3.7%
7.1 2
 
3.7%
Other values (25) 26
48.1%
ValueCountFrequency (%)
3.3 1
 
1.9%
3.8 1
 
1.9%
3.9 1
 
1.9%
4.3 1
 
1.9%
4.6 1
 
1.9%
4.9 1
 
1.9%
5.1 1
 
1.9%
5.2 2
3.7%
5.4 1
 
1.9%
5.5 3
5.6%
ValueCountFrequency (%)
12.5 1
 
1.9%
12.0 1
 
1.9%
10.7 1
 
1.9%
10.1 1
 
1.9%
9.8 1
 
1.9%
9.5 1
 
1.9%
9.4 1
 
1.9%
9.1 3
5.6%
8.6 1
 
1.9%
8.5 1
 
1.9%

연차대체휴가 부여 및 사용에 대한 보장
Real number (ℝ)

ZEROS 

Distinct34
Distinct (%)63.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.6351852
Minimum0
Maximum12.5
Zeros6
Zeros (%)11.1%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-15T10:25:49.269845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.3
median2.55
Q33.675
95-th percentile4.94
Maximum12.5
Range12.5
Interquartile range (IQR)2.375

Descriptive statistics

Standard deviation2.0943912
Coefficient of variation (CV)0.79477951
Kurtosis8.2230792
Mean2.6351852
Median Absolute Deviation (MAD)1.25
Skewness2.0155668
Sum142.3
Variance4.3864745
MonotonicityNot monotonic
2024-03-15T10:25:49.582229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
0.0 6
 
11.1%
3.6 3
 
5.6%
1.3 3
 
5.6%
4.1 3
 
5.6%
2.9 2
 
3.7%
2.6 2
 
3.7%
0.8 2
 
3.7%
3.4 2
 
3.7%
1.2 2
 
3.7%
3.8 2
 
3.7%
Other values (24) 27
50.0%
ValueCountFrequency (%)
0.0 6
11.1%
0.4 1
 
1.9%
0.6 1
 
1.9%
0.7 1
 
1.9%
0.8 2
 
3.7%
1.2 2
 
3.7%
1.3 3
5.6%
1.4 1
 
1.9%
1.5 1
 
1.9%
1.7 2
 
3.7%
ValueCountFrequency (%)
12.5 1
 
1.9%
7.1 1
 
1.9%
5.2 1
 
1.9%
4.8 1
 
1.9%
4.5 2
3.7%
4.2 1
 
1.9%
4.1 3
5.6%
4.0 1
 
1.9%
3.8 2
3.7%
3.7 1
 
1.9%

기타
Real number (ℝ)

ZEROS 

Distinct23
Distinct (%)42.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.487037
Minimum0
Maximum6.3
Zeros12
Zeros (%)22.2%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-15T10:25:49.820846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.625
median1.4
Q32
95-th percentile3.6
Maximum6.3
Range6.3
Interquartile range (IQR)1.375

Descriptive statistics

Standard deviation1.2846035
Coefficient of variation (CV)0.86386786
Kurtosis2.3510747
Mean1.487037
Median Absolute Deviation (MAD)0.75
Skewness1.1731281
Sum80.3
Variance1.6502061
MonotonicityNot monotonic
2024-03-15T10:25:50.083027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0.0 12
22.2%
1.0 5
 
9.3%
1.5 4
 
7.4%
1.2 3
 
5.6%
2.5 3
 
5.6%
1.4 3
 
5.6%
1.7 3
 
5.6%
1.6 2
 
3.7%
2.9 2
 
3.7%
2.0 2
 
3.7%
Other values (13) 15
27.8%
ValueCountFrequency (%)
0.0 12
22.2%
0.3 1
 
1.9%
0.6 1
 
1.9%
0.7 1
 
1.9%
0.8 1
 
1.9%
0.9 1
 
1.9%
1.0 5
9.3%
1.2 3
 
5.6%
1.3 1
 
1.9%
1.4 3
 
5.6%
ValueCountFrequency (%)
6.3 1
 
1.9%
3.8 1
 
1.9%
3.6 2
3.7%
3.4 2
3.7%
3.1 1
 
1.9%
2.9 2
3.7%
2.5 3
5.6%
2.2 1
 
1.9%
2.0 2
3.7%
1.9 1
 
1.9%

Interactions

2024-03-15T10:25:37.056109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:18.837539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:20.724427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:23.064214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:25.119176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:27.468017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:29.991263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:32.316539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:34.238836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:37.312345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:19.035623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:20.989301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:23.325226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:25.361348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:27.775096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:30.253553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:32.570918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:34.473109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:37.603622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:19.197759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:21.253155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:23.587999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:25.617620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:28.103341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:30.520012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:32.840752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:35.047377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:37.866251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:19.348308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:21.504783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:23.828107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:25.927856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:28.365149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:30.771202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:33.080283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:35.336876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:38.033476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:19.505157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:21.750670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:24.065689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:26.190215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:28.619292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:31.011885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:33.310203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:35.584726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:38.416919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:19.754215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:22.227843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:24.289982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:26.527016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:28.895853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:31.281001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:33.576041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:35.871165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:38.635116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:20.010639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:22.405748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:24.547458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:26.813401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:29.161428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:31.535867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:33.726454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:36.136080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:38.810014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:20.251693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:22.555247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:24.766469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:27.011036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:29.443424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:31.795197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:33.883470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:36.428946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:39.015778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:20.506968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:22.805027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:24.963521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:27.198181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:29.729352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:32.057285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:34.090264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:25:36.777920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T10:25:50.354282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분중분류사례수인력 충원유연근무제 도입업무량 조정연장 근무 제한포괄임금제(수당을 급여에 미리 포함하는 계약) 폐지임금 감소에 대비한 대책 마련연차대체휴가 부여 및 사용에 대한 보장기타
구분1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
중분류1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
사례수1.0001.0001.0000.0000.0000.0000.1030.6240.0000.0000.339
인력 충원1.0001.0000.0001.0000.4860.5760.5280.0000.6650.7060.513
유연근무제 도입1.0001.0000.0000.4861.0000.2820.0000.4060.6150.3400.271
업무량 조정1.0001.0000.0000.5760.2821.0000.6720.6310.7310.6540.453
연장 근무 제한1.0001.0000.1030.5280.0000.6721.0000.3250.3050.4180.754
포괄임금제(수당을 급여에 미리 포함하는 계약) 폐지1.0001.0000.6240.0000.4060.6310.3251.0000.0000.5790.000
임금 감소에 대비한 대책 마련1.0001.0000.0000.6650.6150.7310.3050.0001.0000.6860.000
연차대체휴가 부여 및 사용에 대한 보장1.0001.0000.0000.7060.3400.6540.4180.5790.6861.0000.067
기타1.0001.0000.3390.5130.2710.4530.7540.0000.0000.0671.000
2024-03-15T10:25:50.699740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사례수인력 충원유연근무제 도입업무량 조정연장 근무 제한포괄임금제(수당을 급여에 미리 포함하는 계약) 폐지임금 감소에 대비한 대책 마련연차대체휴가 부여 및 사용에 대한 보장기타
사례수1.0000.001-0.1950.1590.1760.441-0.1990.1470.240
인력 충원0.0011.000-0.164-0.509-0.390-0.2550.053-0.463-0.390
유연근무제 도입-0.195-0.1641.000-0.411-0.206-0.4660.203-0.212-0.174
업무량 조정0.159-0.509-0.4111.0000.1200.320-0.4470.4000.442
연장 근무 제한0.176-0.390-0.2060.1201.0000.403-0.3380.3580.212
포괄임금제(수당을 급여에 미리 포함하는 계약) 폐지0.441-0.255-0.4660.3200.4031.000-0.2800.1660.202
임금 감소에 대비한 대책 마련-0.1990.0530.203-0.447-0.338-0.2801.000-0.239-0.133
연차대체휴가 부여 및 사용에 대한 보장0.147-0.463-0.2120.4000.3580.166-0.2391.0000.089
기타0.240-0.390-0.1740.4420.2120.202-0.1330.0891.000

Missing values

2024-03-15T10:25:39.249293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T10:25:39.656308image/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

구분중분류사례수인력 충원유연근무제 도입업무량 조정연장 근무 제한포괄임금제(수당을 급여에 미리 포함하는 계약) 폐지임금 감소에 대비한 대책 마련연차대체휴가 부여 및 사용에 대한 보장기타
0성별1남자137048.816.611.56.85.57.41.81.6
1성별2여자64441.114.815.77.39.85.14.51.7
2연령120대26743.110.115.79.010.15.25.21.5
3연령230-34세44041.812.715.99.57.75.23.63.4
4연령335-39세34949.012.012.68.08.35.73.40.9
5연령440-44세29550.218.612.25.15.45.42.01.0
6연령545-49세24255.013.210.72.96.67.91.22.5
7연령650대34645.424.310.45.83.59.50.60.6
8연령760대 이상7533.336.05.35.36.712.01.30.0
9매체유형1신문사100348.414.112.06.57.87.72.11.6
구분중분류사례수인력 충원유연근무제 도입업무량 조정연장 근무 제한포괄임금제(수당을 급여에 미리 포함하는 계약) 폐지임금 감소에 대비한 대책 마련연차대체휴가 부여 및 사용에 대한 보장기타
44직위3부장부장대우24350.218.99.14.96.68.60.41.2
45직위4차장차장대우41449.518.611.65.67.74.61.21.2
46직위5평기자109044.712.314.88.37.36.34.22.0
47경력11-4년50841.913.415.79.17.95.74.12.2
48경력25-9년44641.714.114.19.07.86.74.02.5
49경력310-14년38647.215.013.06.08.56.72.61.0
50경력415-19년23954.815.59.24.66.37.10.81.7
51경력520년 이상43550.822.39.94.63.77.40.70.7
52권역1서울144145.015.413.88.56.55.73.21.9
53권역2그 외 지역57349.617.610.33.17.99.11.41.0