Overview

Dataset statistics

Number of variables8
Number of observations24
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.8 KiB
Average record size in memory75.5 B

Variable types

Categorical2
Text1
Numeric5

Dataset

Description상시근로자 수 300인 이상 사업장의 전체 근로자 수 및 55세 이상 남녀 고령자 수 (업종별, 규모별) *2022년 기준
URLhttps://www.data.go.kr/data/15117724/fileData.do

Alerts

연도 has constant value ""Constant
사업장 (개) is highly overall correlated with 전체 근로자 (명) and 4 other fieldsHigh correlation
전체 근로자 (명) is highly overall correlated with 사업장 (개) and 4 other fieldsHigh correlation
55세 이상 근로자 (명) is highly overall correlated with 사업장 (개) and 4 other fieldsHigh correlation
55세 이상 남성근로자 (명) is highly overall correlated with 사업장 (개) and 4 other fieldsHigh correlation
55세 이상 여성근로자 (명) is highly overall correlated with 사업장 (개) and 4 other fieldsHigh correlation
구분별(1) is highly overall correlated with 사업장 (개) and 4 other fieldsHigh correlation
구분별(2) has unique valuesUnique
사업장 (개) has unique valuesUnique
전체 근로자 (명) has unique valuesUnique
55세 이상 근로자 (명) has unique valuesUnique
55세 이상 남성근로자 (명) has unique valuesUnique
55세 이상 여성근로자 (명) has unique valuesUnique
사업장 (개) has 1 (4.2%) zerosZeros
전체 근로자 (명) has 1 (4.2%) zerosZeros
55세 이상 근로자 (명) has 1 (4.2%) zerosZeros
55세 이상 남성근로자 (명) has 1 (4.2%) zerosZeros
55세 이상 여성근로자 (명) has 1 (4.2%) zerosZeros

Reproduction

Analysis started2023-12-12 01:10:04.512358
Analysis finished2023-12-12 01:10:07.949210
Duration3.44 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
2022
24 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2022 24
100.0%

Length

2023-12-12T10:10:08.054874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:10:08.176647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 24
100.0%

구분별(1)
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size324.0 B
업종별
21 
규모별
3 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row업종별
2nd row업종별
3rd row업종별
4th row업종별
5th row업종별

Common Values

ValueCountFrequency (%)
업종별 21
87.5%
규모별 3
 
12.5%

Length

2023-12-12T10:10:08.297162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:10:08.422625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
업종별 21
87.5%
규모별 3
 
12.5%

구분별(2)
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-12T10:10:08.699025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length19
Mean length12.166667
Min length2

Characters and Unicode

Total characters292
Distinct characters102
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)100.0%

Sample

1st row농업, 임업 및 어업
2nd row광업
3rd row제조업
4th row전기, 가스, 증기 및 공기조절 공급업
5th row수도, 하수 및 폐기물 처리, 원료 재생업
ValueCountFrequency (%)
및 16
 
18.8%
서비스업 6
 
7.1%
농업 1
 
1.2%
보건업 1
 
1.2%
협회 1
 
1.2%
여가관련 1
 
1.2%
스포츠 1
 
1.2%
예술 1
 
1.2%
사회복지 1
 
1.2%
행정 1
 
1.2%
Other values (55) 55
64.7%
2023-12-12T10:10:09.223746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
61
20.9%
업 23
 
7.9%
및 16
 
5.5%
, 10
 
3.4%
스 8
 
2.7%
비 7
 
2.4%
0 7
 
2.4%
기 7
 
2.4%
서 6
 
2.1%
9 5
 
1.7%
Other values (92) 142
48.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 203
69.5%
Space Separator 61
 
20.9%
Decimal Number 16
 
5.5%
Other Punctuation 10
 
3.4%
Math Symbol 2
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 23
 
11.3%
및 16
 
7.9%
스 8
 
3.9%
비 7
 
3.4%
기 7
 
3.4%
서 6
 
3.0%
수 4
 
2.0%
공 4
 
2.0%
사 4
 
2.0%
리 4
 
2.0%
Other values (83) 120
59.1%
Decimal Number
ValueCountFrequency (%)
0 7
43.8%
9 5
31.2%
1 1
 
6.2%
5 1
 
6.2%
4 1
 
6.2%
3 1
 
6.2%
Space Separator
ValueCountFrequency (%)
61
100.0%
Other Punctuation
ValueCountFrequency (%)
, 10
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 203
69.5%
Common 89
30.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 23
 
11.3%
및 16
 
7.9%
스 8
 
3.9%
비 7
 
3.4%
기 7
 
3.4%
서 6
 
3.0%
수 4
 
2.0%
공 4
 
2.0%
사 4
 
2.0%
리 4
 
2.0%
Other values (83) 120
59.1%
Common
ValueCountFrequency (%)
61
68.5%
, 10
 
11.2%
0 7
 
7.9%
9 5
 
5.6%
~ 2
 
2.2%
1 1
 
1.1%
5 1
 
1.1%
4 1
 
1.1%
3 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 203
69.5%
ASCII 89
30.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
61
68.5%
, 10
 
11.2%
0 7
 
7.9%
9 5
 
5.6%
~ 2
 
2.2%
1 1
 
1.1%
5 1
 
1.1%
4 1
 
1.1%
3 1
 
1.1%
Hangul
ValueCountFrequency (%)
업 23
 
11.3%
및 16
 
7.9%
스 8
 
3.9%
비 7
 
3.4%
기 7
 
3.4%
서 6
 
3.0%
수 4
 
2.0%
공 4
 
2.0%
사 4
 
2.0%
리 4
 
2.0%
Other values (83) 120
59.1%

사업장 (개)
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean323.91667
Minimum0
Maximum1765
Zeros1
Zeros (%)4.2%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T10:10:09.381521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.15
Q146.75
median160.5
Q3309.75
95-th percentile1206.55
Maximum1765
Range1765
Interquartile range (IQR)263

Descriptive statistics

Standard deviation452.2828
Coefficient of variation (CV)1.3962937
Kurtosis3.823422
Mean323.91667
Median Absolute Deviation (MAD)137.5
Skewness2.0120971
Sum7774
Variance204559.73
MonotonicityNot monotonic
2023-12-12T10:10:09.523234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
3 1
 
4.2%
619 1
 
4.2%
867 1
 
4.2%
1255 1
 
4.2%
1765 1
 
4.2%
4 1
 
4.2%
0 1
 
4.2%
34 1
 
4.2%
51 1
 
4.2%
324 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
0 1
4.2%
2 1
4.2%
3 1
4.2%
4 1
4.2%
20 1
4.2%
34 1
4.2%
51 1
4.2%
54 1
4.2%
61 1
4.2%
66 1
4.2%
ValueCountFrequency (%)
1765 1
4.2%
1255 1
4.2%
932 1
4.2%
867 1
4.2%
619 1
4.2%
324 1
4.2%
305 1
4.2%
295 1
4.2%
256 1
4.2%
246 1
4.2%

전체 근로자 (명)
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean351433.5
Minimum0
Maximum2671044
Zeros1
Zeros (%)4.2%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T10:10:09.661908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1199.85
Q135021.75
median162618.5
Q3319162.5
95-th percentile1117238
Maximum2671044
Range2671044
Interquartile range (IQR)284140.75

Descriptive statistics

Standard deviation578835.19
Coefficient of variation (CV)1.6470689
Kurtosis11.448237
Mean351433.5
Median Absolute Deviation (MAD)138116.5
Skewness3.1380246
Sum8434404
Variance3.3505017 × 1011
MonotonicityNot monotonic
2023-12-12T10:10:09.817445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1188 1
 
4.2%
631011 1
 
4.2%
2671044 1
 
4.2%
872070 1
 
4.2%
674088 1
 
4.2%
11358 1
 
4.2%
0 1
 
4.2%
28202 1
 
4.2%
37295 1
 
4.2%
208451 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
0 1
4.2%
1188 1
4.2%
1267 1
4.2%
11358 1
4.2%
20802 1
4.2%
28202 1
4.2%
37295 1
4.2%
49285 1
4.2%
59401 1
4.2%
78561 1
4.2%
ValueCountFrequency (%)
2671044 1
4.2%
1160503 1
4.2%
872070 1
4.2%
674088 1
4.2%
631011 1
4.2%
337734 1
4.2%
312972 1
4.2%
291152 1
4.2%
280509 1
4.2%
252897 1
4.2%

55세 이상 근로자 (명)
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean62698.167
Minimum0
Maximum409869
Zeros1
Zeros (%)4.2%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T10:10:09.949088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile594.8
Q15776.75
median19828
Q364282
95-th percentile252546.25
Maximum409869
Range409869
Interquartile range (IQR)58505.25

Descriptive statistics

Standard deviation100626.3
Coefficient of variation (CV)1.6049322
Kurtosis5.7327964
Mean62698.167
Median Absolute Deviation (MAD)15850
Skewness2.3612199
Sum1504756
Variance1.0125653 × 1010
MonotonicityNot monotonic
2023-12-12T10:10:10.075723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
775 1
 
4.2%
261079 1
 
4.2%
409869 1
 
4.2%
204194 1
 
4.2%
138315 1
 
4.2%
4234 1
 
4.2%
0 1
 
4.2%
3982 1
 
4.2%
6291 1
 
4.2%
30824 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
0 1
4.2%
563 1
4.2%
775 1
4.2%
3974 1
4.2%
3982 1
4.2%
4234 1
4.2%
6291 1
4.2%
6509 1
4.2%
11795 1
4.2%
12158 1
4.2%
ValueCountFrequency (%)
409869 1
4.2%
261079 1
4.2%
204194 1
4.2%
138315 1
4.2%
110302 1
4.2%
99910 1
4.2%
52406 1
4.2%
37858 1
4.2%
30824 1
4.2%
29155 1
4.2%

55세 이상 남성근로자 (명)
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39465.5
Minimum0
Maximum263172
Zeros1
Zeros (%)4.2%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T10:10:10.235473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile332.55
Q13283.5
median10278.5
Q345328.5
95-th percentile135777.9
Maximum263172
Range263172
Interquartile range (IQR)42045

Descriptive statistics

Standard deviation62898.467
Coefficient of variation (CV)1.5937583
Kurtosis6.2778971
Mean39465.5
Median Absolute Deviation (MAD)8114.5
Skewness2.3777762
Sum947172
Variance3.9562172 × 109
MonotonicityNot monotonic
2023-12-12T10:10:10.367953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
294 1
 
4.2%
137433 1
 
4.2%
263172 1
 
4.2%
126399 1
 
4.2%
84015 1
 
4.2%
3336 1
 
4.2%
0 1
 
4.2%
2235 1
 
4.2%
3582 1
 
4.2%
8972 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
0 1
4.2%
294 1
4.2%
551 1
4.2%
2093 1
4.2%
2235 1
4.2%
3126 1
4.2%
3336 1
4.2%
3582 1
4.2%
4391 1
4.2%
6086 1
4.2%
ValueCountFrequency (%)
263172 1
4.2%
137433 1
4.2%
126399 1
4.2%
98982 1
4.2%
84015 1
4.2%
57510 1
4.2%
41268 1
4.2%
34387 1
4.2%
17628 1
4.2%
16749 1
4.2%

55세 이상 여성근로자 (명)
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23232.667
Minimum0
Maximum146697
Zeros1
Zeros (%)4.2%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T10:10:10.517837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile73.65
Q1885.5
median5261
Q322580
95-th percentile116768.35
Maximum146697
Range146697
Interquartile range (IQR)21694.5

Descriptive statistics

Standard deviation39712.133
Coefficient of variation (CV)1.709323
Kurtosis4.4403656
Mean23232.667
Median Absolute Deviation (MAD)4809
Skewness2.2387252
Sum557584
Variance1.5770535 × 109
MonotonicityNot monotonic
2023-12-12T10:10:10.646316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
481 1
 
4.2%
123646 1
 
4.2%
146697 1
 
4.2%
77795 1
 
4.2%
54300 1
 
4.2%
898 1
 
4.2%
0 1
 
4.2%
1747 1
 
4.2%
2709 1
 
4.2%
21852 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
0 1
4.2%
12 1
4.2%
423 1
4.2%
481 1
4.2%
573 1
4.2%
848 1
4.2%
898 1
4.2%
1747 1
4.2%
2538 1
4.2%
2709 1
4.2%
ValueCountFrequency (%)
146697 1
4.2%
123646 1
4.2%
77795 1
4.2%
54300 1
4.2%
42400 1
4.2%
24764 1
4.2%
21852 1
4.2%
11320 1
4.2%
11138 1
4.2%
9748 1
4.2%

Interactions

2023-12-12T10:10:07.038548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:10:04.812900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:10:05.336687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:10:05.922820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:10:06.510911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:10:07.137078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:10:04.919259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:10:05.455273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:10:06.055099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:10:06.626850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:10:07.263680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:10:05.021531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:10:05.565598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:10:06.185075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:10:06.734332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:10:07.384089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:10:05.130536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:10:05.683409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:10:06.279171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:10:06.821439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:10:07.506404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:10:05.226908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:10:05.792785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:10:06.396301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:10:06.925220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T10:10:10.768543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분별(1)구분별(2)사업장 (개)전체 근로자 (명)55세 이상 근로자 (명)55세 이상 남성근로자 (명)55세 이상 여성근로자 (명)
구분별(1)1.0001.0001.0000.9791.0000.7961.000
구분별(2)1.0001.0001.0001.0001.0001.0001.000
사업장 (개)1.0001.0001.0000.9600.9890.9820.983
전체 근로자 (명)0.9791.0000.9601.0000.8970.8860.868
55세 이상 근로자 (명)1.0001.0000.9890.8971.0000.9910.986
55세 이상 남성근로자 (명)0.7961.0000.9820.8860.9911.0000.986
55세 이상 여성근로자 (명)1.0001.0000.9830.8680.9860.9861.000
2023-12-12T10:10:10.911958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업장 (개)전체 근로자 (명)55세 이상 근로자 (명)55세 이상 남성근로자 (명)55세 이상 여성근로자 (명)구분별(1)
사업장 (개)1.0000.9490.9480.8890.8580.879
전체 근로자 (명)0.9491.0000.9300.8800.8540.787
55세 이상 근로자 (명)0.9480.9301.0000.9500.9200.879
55세 이상 남성근로자 (명)0.8890.8800.9501.0000.7960.757
55세 이상 여성근로자 (명)0.8580.8540.9200.7961.0000.879
구분별(1)0.8790.7870.8790.7570.8791.000

Missing values

2023-12-12T10:10:07.670655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T10:10:07.860019image/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

연도구분별(1)구분별(2)사업장 (개)전체 근로자 (명)55세 이상 근로자 (명)55세 이상 남성근로자 (명)55세 이상 여성근로자 (명)
02022업종별농업, 임업 및 어업31188775294481
12022업종별광업2126756355112
22022업종별제조업93211605031103029898211320
32022업종별전기, 가스, 증기 및 공기조절 공급업615940165096086423
42022업종별수도, 하수 및 폐기물 처리, 원료 재생업202080239743126848
52022업종별건설업941076571215811585573
62022업종별도매 및 소매업24633773429155439124764
72022업종별운수 및 창고업200252897524064126811138
82022업종별숙박 및 음식점업661167861179520939702
92022업종별정보통신업25628050917516149782538
연도구분별(1)구분별(2)사업장 (개)전체 근로자 (명)55세 이상 근로자 (명)55세 이상 남성근로자 (명)55세 이상 여성근로자 (명)
142022업종별공공행정, 국방 및 사회보장 행정305291152999105751042400
152022업종별교육 서비스업124785611441084006010
162022업종별보건업 및 사회복지 서비스업32420845130824897221852
172022업종별예술, 스포츠 및 여가관련 서비스업5137295629135822709
182022업종별협회 및 단체, 수리 및 기타 개인 서비스업3428202398222351747
192022업종별가구 내 고용활동 및 달리 분류되지 않은 자가소비 생산활동00000
202022업종별국제 및 외국기관41135842343336898
212022규모별300~499인17656740881383158401554300
222022규모별500~999인125587207020419412639977795
232022규모별1000인이상8672671044409869263172146697