Overview

Dataset statistics

Number of variables5
Number of observations54
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 KiB
Average record size in memory45.4 B

Variable types

Text2
Numeric3

Dataset

Description현재 소속 언론사에서 주52시간 근무제를 실시하고있는지 여부를 알 수 있는 파일데이터입니다. 자세한 사항은 한국언론진흥재단 홈페이지에서 자세히 확인바랍니다.
Author한국언론진흥재단
URLhttps://www.data.go.kr/data/15060166/fileData.do

Alerts

현재 주 52시간 근무제를 시행하고 있다 is highly overall correlated with 아직 주 52시간 근무제를 시행하지 않고 있다High correlation
아직 주 52시간 근무제를 시행하지 않고 있다 is highly overall correlated with 현재 주 52시간 근무제를 시행하고 있다High correlation
구분1 has unique valuesUnique
아직 주 52시간 근무제를 시행하지 않고 있다 has 2 (3.7%) zerosZeros

Reproduction

Analysis started2024-03-14 20:33:53.043892
Analysis finished2024-03-14 20:33:55.790378
Duration2.75 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분1
Text

UNIQUE 

Distinct54
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size560.0 B
2024-03-15T05:33:56.694501image/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%
2024-03-15T05:33:58.093141image/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
2024-03-15T05:33:58.986726image/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%
2024-03-15T05:34:00.159233image/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
2024-03-15T05:34:00.575445image/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
2024-03-15T05:34:01.294457image/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%

현재 주 52시간 근무제를 시행하고 있다
Real number (ℝ)

HIGH CORRELATION 

Distinct45
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean88.466667
Minimum68.1
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-15T05:34:01.650294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum68.1
5-th percentile78.21
Q183.35
median88
Q394.1
95-th percentile98.57
Maximum100
Range31.9
Interquartile range (IQR)10.75

Descriptive statistics

Standard deviation7.1716423
Coefficient of variation (CV)0.081066039
Kurtosis-0.036311105
Mean88.466667
Median Absolute Deviation (MAD)5.65
Skewness-0.47404845
Sum4777.2
Variance51.432453
MonotonicityNot monotonic
2024-03-15T05:34:02.027721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
88.0 2
 
3.7%
100.0 2
 
3.7%
86.2 2
 
3.7%
93.4 2
 
3.7%
86.6 2
 
3.7%
96.6 2
 
3.7%
94.1 2
 
3.7%
79.2 2
 
3.7%
90.2 2
 
3.7%
91.5 1
 
1.9%
Other values (35) 35
64.8%
ValueCountFrequency (%)
68.1 1
1.9%
72.4 1
1.9%
77.3 1
1.9%
78.7 1
1.9%
79.2 2
3.7%
80.0 1
1.9%
80.8 1
1.9%
80.9 1
1.9%
81.5 1
1.9%
82.3 1
1.9%
ValueCountFrequency (%)
100.0 2
3.7%
98.7 1
1.9%
98.5 1
1.9%
97.7 1
1.9%
96.7 1
1.9%
96.6 2
3.7%
96.5 1
1.9%
96.2 1
1.9%
95.9 1
1.9%
94.8 1
1.9%

아직 주 52시간 근무제를 시행하지 않고 있다
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct45
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.533333
Minimum0
Maximum31.9
Zeros2
Zeros (%)3.7%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-15T05:34:02.435708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.43
Q15.9
median12
Q316.65
95-th percentile21.79
Maximum31.9
Range31.9
Interquartile range (IQR)10.75

Descriptive statistics

Standard deviation7.1716423
Coefficient of variation (CV)0.62181869
Kurtosis-0.036311105
Mean11.533333
Median Absolute Deviation (MAD)5.65
Skewness0.47404845
Sum622.8
Variance51.432453
MonotonicityNot monotonic
2024-03-15T05:34:02.789078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
12.0 2
 
3.7%
0.0 2
 
3.7%
13.8 2
 
3.7%
6.6 2
 
3.7%
13.4 2
 
3.7%
3.4 2
 
3.7%
5.9 2
 
3.7%
20.8 2
 
3.7%
9.8 2
 
3.7%
8.5 1
 
1.9%
Other values (35) 35
64.8%
ValueCountFrequency (%)
0.0 2
3.7%
1.3 1
1.9%
1.5 1
1.9%
2.3 1
1.9%
3.3 1
1.9%
3.4 2
3.7%
3.5 1
1.9%
3.8 1
1.9%
4.1 1
1.9%
5.2 1
1.9%
ValueCountFrequency (%)
31.9 1
1.9%
27.6 1
1.9%
22.7 1
1.9%
21.3 1
1.9%
20.8 2
3.7%
20.0 1
1.9%
19.2 1
1.9%
19.1 1
1.9%
18.5 1
1.9%
17.7 1
1.9%

Interactions

2024-03-15T05:33:54.873105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:33:53.294297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:33:54.095227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:33:55.040812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:33:53.563530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:33:54.361921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:33:55.200599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:33:53.825392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:33:54.614871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T05:34:03.013783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분1중분류사례수현재 주 52시간 근무제를 시행하고 있다아직 주 52시간 근무제를 시행하지 않고 있다
구분11.0001.0001.0001.0001.000
중분류1.0001.0001.0001.0001.000
사례수1.0001.0001.0000.2840.284
현재 주 52시간 근무제를 시행하고 있다1.0001.0000.2841.0001.000
아직 주 52시간 근무제를 시행하지 않고 있다1.0001.0000.2841.0001.000
2024-03-15T05:34:03.458429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사례수현재 주 52시간 근무제를 시행하고 있다아직 주 52시간 근무제를 시행하지 않고 있다
사례수1.000-0.3090.309
현재 주 52시간 근무제를 시행하고 있다-0.3091.000-1.000
아직 주 52시간 근무제를 시행하지 않고 있다0.309-1.0001.000

Missing values

2024-03-15T05:33:55.417821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T05:33:55.657149image/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

구분1중분류사례수현재 주 52시간 근무제를 시행하고 있다아직 주 52시간 근무제를 시행하지 않고 있다
0성별1남자137088.012.0
1성별2여자64485.614.4
2연령120대26780.919.1
3연령230-34세44083.216.8
4연령335-39세34987.712.3
5연령440-44세29587.812.2
6연령545-49세24293.46.6
7연령650대34693.66.4
8연령760대 이상7580.020.0
9매체유형1신문사100386.613.4
구분1중분류사례수현재 주 52시간 근무제를 시행하고 있다아직 주 52시간 근무제를 시행하지 않고 있다
44직위3부장부장대우24393.46.6
45직위4차장차장대우41486.213.8
46직위5평기자109085.914.1
47경력11-4년50882.317.7
48경력25-9년44683.616.4
49경력310-14년38688.911.1
50경력415-19년23990.010.0
51경력520년 이상43593.86.2
52권역1서울144189.510.5
53권역2그 외 지역57381.518.5