Overview

Dataset statistics

Number of variables12
Number of observations126
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.3 KiB
Average record size in memory108.0 B

Variable types

Numeric11
Categorical1

Dataset

Description한국산업안전보건공단에서 실시하는 작업환경측정 사업에 대한 업종별 측정 실시 결과보고서 데이터로 실시 및 초과 사업장 현황에 대한 데이터를 제공합니다.
URLhttps://www.data.go.kr/data/15091873/fileData.do

Alerts

상반기_실시사업장수 is highly overall correlated with 상반기_실시사업장비율 and 7 other fieldsHigh correlation
상반기_실시사업장비율 is highly overall correlated with 상반기_실시사업장수 and 7 other fieldsHigh correlation
상반기_초과사업장수 is highly overall correlated with 상반기_실시사업장수 and 8 other fieldsHigh correlation
상반기_초과사업장비율 is highly overall correlated with 상반기_실시사업장수 and 7 other fieldsHigh correlation
상반기_초과율 is highly overall correlated with 상반기_초과사업장수 and 1 other fieldsHigh correlation
하반기_실시사업장수 is highly overall correlated with 상반기_실시사업장수 and 6 other fieldsHigh correlation
하반기_실시사업장비율 is highly overall correlated with 상반기_실시사업장수 and 7 other fieldsHigh correlation
하반기_초과사업장수 is highly overall correlated with 상반기_실시사업장수 and 7 other fieldsHigh correlation
하반기_초과사업장비율 is highly overall correlated with 상반기_실시사업장수 and 7 other fieldsHigh correlation
상반기_초과율.1 is highly overall correlated with 상반기_초과율High correlation
업종구분 is highly overall correlated with 상반기_실시사업장수 and 6 other fieldsHigh correlation
상반기_실시사업장비율 has 19 (15.1%) zerosZeros
상반기_초과사업장수 has 25 (19.8%) zerosZeros
상반기_초과사업장비율 has 51 (40.5%) zerosZeros
상반기_초과율 has 27 (21.4%) zerosZeros
하반기_실시사업장비율 has 20 (15.9%) zerosZeros
하반기_초과사업장수 has 16 (12.7%) zerosZeros
하반기_초과사업장비율 has 44 (34.9%) zerosZeros
상반기_초과율.1 has 16 (12.7%) zerosZeros

Reproduction

Analysis started2023-12-12 05:08:17.912077
Analysis finished2023-12-12 05:08:34.299258
Duration16.39 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

Distinct6
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2018.5
Minimum2016
Maximum2021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T14:08:34.368261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2016
5-th percentile2016
Q12017
median2018.5
Q32020
95-th percentile2021
Maximum2021
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.7146428
Coefficient of variation (CV)0.00084946387
Kurtosis-1.271215
Mean2018.5
Median Absolute Deviation (MAD)1.5
Skewness0
Sum254331
Variance2.94
MonotonicityIncreasing
2023-12-12T14:08:34.493165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2016 21
16.7%
2017 21
16.7%
2018 21
16.7%
2019 21
16.7%
2020 21
16.7%
2021 21
16.7%
ValueCountFrequency (%)
2016 21
16.7%
2017 21
16.7%
2018 21
16.7%
2019 21
16.7%
2020 21
16.7%
2021 21
16.7%
ValueCountFrequency (%)
2021 21
16.7%
2020 21
16.7%
2019 21
16.7%
2018 21
16.7%
2017 21
16.7%
2016 21
16.7%

업종구분
Categorical

HIGH CORRELATION 

Distinct28
Distinct (%)22.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
농업
 
6
보건업 및 사회복지 서비스업
 
6
교육 서비스업
 
6
사업시설관리 및 사업지원 서비스업
 
6
임업
 
6
Other values (23)
96 

Length

Max length21
Median length18
Mean length10.261905
Min length2

Unique

Unique7 ?
Unique (%)5.6%

Sample

1st row농업
2nd row임업
3rd row어업
4th row광업
5th row제조업

Common Values

ValueCountFrequency (%)
농업 6
 
4.8%
보건업 및 사회복지 서비스업 6
 
4.8%
교육 서비스업 6
 
4.8%
사업시설관리 및 사업지원 서비스업 6
 
4.8%
임업 6
 
4.8%
부동산업 및 임대업 6
 
4.8%
금융 및 보험업 6
 
4.8%
숙박 및 음식점업 6
 
4.8%
운수업 6
 
4.8%
도매 및 소매업 6
 
4.8%
Other values (18) 66
52.4%

Length

2023-12-12T14:08:34.647729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
및 78
 
21.7%
서비스업 36
 
10.0%
농업 6
 
1.7%
국방 6
 
1.7%
방송통신 6
 
1.7%
정보서비스업 6
 
1.7%
수도사업 6
 
1.7%
환경복원업 6
 
1.7%
기타 6
 
1.7%
개인 6
 
1.7%
Other values (36) 198
55.0%

상반기_실시사업장수
Real number (ℝ)

HIGH CORRELATION 

Distinct109
Distinct (%)86.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2637.6111
Minimum3
Maximum47145
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T14:08:34.791060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile6
Q159.25
median164.5
Q3771.25
95-th percentile4007
Maximum47145
Range47142
Interquartile range (IQR)712

Descriptive statistics

Standard deviation9262.5823
Coefficient of variation (CV)3.5117316
Kurtosis16.761517
Mean2637.6111
Median Absolute Deviation (MAD)154
Skewness4.263083
Sum332339
Variance85795431
MonotonicityNot monotonic
2023-12-12T14:08:34.927409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7 4
 
3.2%
94 3
 
2.4%
10 3
 
2.4%
3 3
 
2.4%
60 2
 
1.6%
103 2
 
1.6%
88 2
 
1.6%
6 2
 
1.6%
3770 2
 
1.6%
4 2
 
1.6%
Other values (99) 101
80.2%
ValueCountFrequency (%)
3 3
2.4%
4 2
1.6%
5 1
 
0.8%
6 2
1.6%
7 4
3.2%
8 1
 
0.8%
10 3
2.4%
12 1
 
0.8%
14 1
 
0.8%
16 1
 
0.8%
ValueCountFrequency (%)
47145 1
0.8%
46811 1
0.8%
44988 1
0.8%
42583 1
0.8%
40974 1
0.8%
38940 1
0.8%
4086 1
0.8%
3770 2
1.6%
3520 1
0.8%
3502 1
0.8%

상반기_실시사업장비율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct37
Distinct (%)29.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.7640476
Minimum0
Maximum81.2
Zeros19
Zeros (%)15.1%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T14:08:35.344281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.1
median0.3
Q31.4
95-th percentile6.575
Maximum81.2
Range81.2
Interquartile range (IQR)1.3

Descriptive statistics

Standard deviation16.705196
Coefficient of variation (CV)3.5065132
Kurtosis16.392427
Mean4.7640476
Median Absolute Deviation (MAD)0.3
Skewness4.233168
Sum600.27
Variance279.06357
MonotonicityNot monotonic
2023-12-12T14:08:35.467434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
0.0 19
15.1%
0.1 17
13.5%
0.2 17
13.5%
0.3 11
 
8.7%
0.4 6
 
4.8%
1.4 4
 
3.2%
0.5 4
 
3.2%
1.2 4
 
3.2%
1.3 3
 
2.4%
1.5 3
 
2.4%
Other values (27) 38
30.2%
ValueCountFrequency (%)
0.0 19
15.1%
0.01 2
 
1.6%
0.02 1
 
0.8%
0.03 1
 
0.8%
0.1 17
13.5%
0.2 17
13.5%
0.3 11
8.7%
0.4 6
 
4.8%
0.5 4
 
3.2%
0.6 2
 
1.6%
ValueCountFrequency (%)
81.2 1
0.8%
80.1 1
0.8%
78.7 1
0.8%
78.2 1
0.8%
78.1 1
0.8%
76.4 1
0.8%
6.7 1
0.8%
6.2 2
1.6%
6.1 2
1.6%
5.9 1
0.8%

상반기_초과사업장수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct43
Distinct (%)34.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean311.00794
Minimum0
Maximum6482
Zeros25
Zeros (%)19.8%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T14:08:35.600211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median6
Q317.75
95-th percentile133
Maximum6482
Range6482
Interquartile range (IQR)16.75

Descriptive statistics

Standard deviation1326.9441
Coefficient of variation (CV)4.2665925
Kurtosis16.834479
Mean311.00794
Median Absolute Deviation (MAD)6
Skewness4.3051638
Sum39187
Variance1760780.8
MonotonicityNot monotonic
2023-12-12T14:08:35.729781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
0 25
19.8%
1 12
 
9.5%
6 10
 
7.9%
3 7
 
5.6%
2 7
 
5.6%
9 6
 
4.8%
5 6
 
4.8%
7 5
 
4.0%
8 3
 
2.4%
13 3
 
2.4%
Other values (33) 42
33.3%
ValueCountFrequency (%)
0 25
19.8%
1 12
9.5%
2 7
 
5.6%
3 7
 
5.6%
4 3
 
2.4%
5 6
 
4.8%
6 10
 
7.9%
7 5
 
4.0%
8 3
 
2.4%
9 6
 
4.8%
ValueCountFrequency (%)
6482 1
0.8%
6424 1
0.8%
6318 1
0.8%
6105 1
0.8%
6020 1
0.8%
5955 1
0.8%
140 1
0.8%
112 1
0.8%
88 1
0.8%
87 1
0.8%

상반기_초과사업장비율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct29
Distinct (%)23.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.437381
Minimum0
Maximum95.7
Zeros51
Zeros (%)40.5%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T14:08:35.845543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.1
Q30.3
95-th percentile7.6875
Maximum95.7
Range95.7
Interquartile range (IQR)0.3

Descriptive statistics

Standard deviation19.010241
Coefficient of variation (CV)4.2841129
Kurtosis18.906238
Mean4.437381
Median Absolute Deviation (MAD)0.1
Skewness4.5004207
Sum559.11
Variance361.38926
MonotonicityNot monotonic
2023-12-12T14:08:35.968269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0.0 51
40.5%
0.1 26
20.6%
0.2 6
 
4.8%
0.5 5
 
4.0%
0.3 4
 
3.2%
0.01 4
 
3.2%
1.2 3
 
2.4%
0.8 2
 
1.6%
95.2 2
 
1.6%
0.02 2
 
1.6%
Other values (19) 21
16.7%
ValueCountFrequency (%)
0.0 51
40.5%
0.01 4
 
3.2%
0.02 2
 
1.6%
0.03 1
 
0.8%
0.04 1
 
0.8%
0.1 26
20.6%
0.12 1
 
0.8%
0.14 1
 
0.8%
0.2 6
 
4.8%
0.3 4
 
3.2%
ValueCountFrequency (%)
95.7 1
0.8%
95.2 2
1.6%
95.0 1
0.8%
94.6 1
0.8%
47.75 1
0.8%
9.55 1
0.8%
2.1 1
0.8%
1.8 1
0.8%
1.4 1
0.8%
1.3 1
0.8%

상반기_초과율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct82
Distinct (%)65.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.955635
Minimum0
Maximum750
Zeros27
Zeros (%)21.4%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T14:08:36.114505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.425
median3.505
Q38.95
95-th percentile36.96
Maximum750
Range750
Interquartile range (IQR)8.525

Descriptive statistics

Standard deviation88.985132
Coefficient of variation (CV)4.0529519
Kurtosis46.580272
Mean21.955635
Median Absolute Deviation (MAD)3.505
Skewness6.5999573
Sum2766.41
Variance7918.3538
MonotonicityNot monotonic
2023-12-12T14:08:36.284024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 27
 
21.4%
1.9 4
 
3.2%
2.6 3
 
2.4%
5.6 3
 
2.4%
9.0 2
 
1.6%
3.51 2
 
1.6%
4.5 2
 
1.6%
4.2 2
 
1.6%
33.3 2
 
1.6%
2.8 2
 
1.6%
Other values (72) 77
61.1%
ValueCountFrequency (%)
0.0 27
21.4%
0.1 1
 
0.8%
0.2 1
 
0.8%
0.3 1
 
0.8%
0.4 2
 
1.6%
0.5 1
 
0.8%
0.6 1
 
0.8%
0.8 1
 
0.8%
0.86 1
 
0.8%
1.1 1
 
0.8%
ValueCountFrequency (%)
750.0 1
0.8%
555.0 1
0.8%
288.6 1
0.8%
276.0 1
0.8%
60.68 1
0.8%
49.4 1
0.8%
37.5 1
0.8%
35.34 1
0.8%
33.3 2
1.6%
31.08 1
0.8%

하반기_실시사업장수
Real number (ℝ)

HIGH CORRELATION 

Distinct109
Distinct (%)86.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2518.0556
Minimum1
Maximum44005
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T14:08:36.494768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.25
Q158.5
median177.5
Q3764
95-th percentile4235.5
Maximum44005
Range44004
Interquartile range (IQR)705.5

Descriptive statistics

Standard deviation8733.4197
Coefficient of variation (CV)3.4683189
Kurtosis16.497112
Mean2518.0556
Median Absolute Deviation (MAD)165
Skewness4.2377759
Sum317275
Variance76272620
MonotonicityNot monotonic
2023-12-12T14:08:36.679937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 4
 
3.2%
11 3
 
2.4%
69 3
 
2.4%
52 3
 
2.4%
60 2
 
1.6%
9 2
 
1.6%
48 2
 
1.6%
67 2
 
1.6%
181 2
 
1.6%
7 2
 
1.6%
Other values (99) 101
80.2%
ValueCountFrequency (%)
1 1
 
0.8%
2 4
3.2%
4 2
1.6%
5 2
1.6%
6 1
 
0.8%
7 2
1.6%
9 2
1.6%
11 3
2.4%
14 1
 
0.8%
18 1
 
0.8%
ValueCountFrequency (%)
44005 1
0.8%
42695 1
0.8%
41721 1
0.8%
40688 1
0.8%
39067 1
0.8%
38755 1
0.8%
4430 1
0.8%
3652 1
0.8%
3528 1
0.8%
3358 1
0.8%

하반기_실시사업장비율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct40
Distinct (%)31.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.7560317
Minimum0
Maximum81.8
Zeros20
Zeros (%)15.9%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T14:08:36.837537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.1
median0.3
Q31.4
95-th percentile7.75
Maximum81.8
Range81.8
Interquartile range (IQR)1.3

Descriptive statistics

Standard deviation16.527689
Coefficient of variation (CV)3.4751006
Kurtosis16.408689
Mean4.7560317
Median Absolute Deviation (MAD)0.3
Skewness4.2314698
Sum599.26
Variance273.1645
MonotonicityNot monotonic
2023-12-12T14:08:36.995041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
0.1 22
17.5%
0.0 20
15.9%
0.3 11
 
8.7%
0.2 10
 
7.9%
0.4 8
 
6.3%
1.3 5
 
4.0%
1.4 4
 
3.2%
0.7 4
 
3.2%
3.3 3
 
2.4%
0.5 3
 
2.4%
Other values (30) 36
28.6%
ValueCountFrequency (%)
0.0 20
15.9%
0.01 2
 
1.6%
0.04 1
 
0.8%
0.1 22
17.5%
0.2 10
7.9%
0.3 11
8.7%
0.4 8
 
6.3%
0.5 3
 
2.4%
0.6 2
 
1.6%
0.7 4
 
3.2%
ValueCountFrequency (%)
81.8 1
0.8%
79.3 1
0.8%
78.5 1
0.8%
77.7 1
0.8%
76.1 1
0.8%
74.2 1
0.8%
8.1 1
0.8%
6.7 1
0.8%
6.2 1
0.8%
6.1 1
0.8%

하반기_초과사업장수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct44
Distinct (%)34.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean307.11905
Minimum0
Maximum6418
Zeros16
Zeros (%)12.7%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T14:08:37.165696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median5.5
Q317.75
95-th percentile120.25
Maximum6418
Range6418
Interquartile range (IQR)16.75

Descriptive statistics

Standard deviation1310.915
Coefficient of variation (CV)4.2684263
Kurtosis16.811429
Mean307.11905
Median Absolute Deviation (MAD)4.5
Skewness4.3033092
Sum38697
Variance1718498.2
MonotonicityNot monotonic
2023-12-12T14:08:37.348801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
1 26
20.6%
0 16
 
12.7%
6 9
 
7.1%
9 7
 
5.6%
2 7
 
5.6%
5 6
 
4.8%
7 4
 
3.2%
4 4
 
3.2%
3 4
 
3.2%
40 3
 
2.4%
Other values (34) 40
31.7%
ValueCountFrequency (%)
0 16
12.7%
1 26
20.6%
2 7
 
5.6%
3 4
 
3.2%
4 4
 
3.2%
5 6
 
4.8%
6 9
 
7.1%
7 4
 
3.2%
8 3
 
2.4%
9 7
 
5.6%
ValueCountFrequency (%)
6418 1
0.8%
6274 1
0.8%
6186 1
0.8%
6074 1
0.8%
6000 1
0.8%
5906 1
0.8%
127 1
0.8%
100 1
0.8%
99 1
0.8%
79 1
0.8%

하반기_초과사업장비율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)18.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.7584921
Minimum0
Maximum95.5
Zeros44
Zeros (%)34.9%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T14:08:37.491894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.1
Q30.3
95-th percentile1.825
Maximum95.5
Range95.5
Interquartile range (IQR)0.3

Descriptive statistics

Standard deviation20.318915
Coefficient of variation (CV)4.2700324
Kurtosis16.741781
Mean4.7584921
Median Absolute Deviation (MAD)0.1
Skewness4.2974819
Sum599.57
Variance412.85832
MonotonicityNot monotonic
2023-12-12T14:08:37.636604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0.0 44
34.9%
0.1 33
26.2%
0.6 5
 
4.0%
0.2 5
 
4.0%
0.8 4
 
3.2%
0.02 4
 
3.2%
0.3 4
 
3.2%
1.1 4
 
3.2%
0.5 3
 
2.4%
0.03 3
 
2.4%
Other values (13) 17
 
13.5%
ValueCountFrequency (%)
0.0 44
34.9%
0.02 4
 
3.2%
0.03 3
 
2.4%
0.05 2
 
1.6%
0.1 33
26.2%
0.2 5
 
4.0%
0.3 4
 
3.2%
0.4 2
 
1.6%
0.5 3
 
2.4%
0.6 5
 
4.0%
ValueCountFrequency (%)
95.5 2
1.6%
95.3 2
1.6%
95.2 1
 
0.8%
94.7 1
 
0.8%
1.9 1
 
0.8%
1.6 1
 
0.8%
1.5 1
 
0.8%
1.3 1
 
0.8%
1.2 1
 
0.8%
1.1 4
3.2%

상반기_초과율.1
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct70
Distinct (%)55.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.8309524
Minimum0
Maximum50
Zeros16
Zeros (%)12.7%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T14:08:37.776078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.425
median2.9
Q37.65
95-th percentile26.55
Maximum50
Range50
Interquartile range (IQR)6.225

Descriptive statistics

Standard deviation9.8470175
Coefficient of variation (CV)1.4415292
Kurtosis7.5686413
Mean6.8309524
Median Absolute Deviation (MAD)2.75
Skewness2.5855928
Sum860.7
Variance96.963754
MonotonicityNot monotonic
2023-12-12T14:08:37.934777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 16
 
12.7%
0.1 5
 
4.0%
2.0 5
 
4.0%
1.7 4
 
3.2%
1.9 3
 
2.4%
2.8 3
 
2.4%
50.0 3
 
2.4%
1.4 3
 
2.4%
2.5 3
 
2.4%
6.0 3
 
2.4%
Other values (60) 78
61.9%
ValueCountFrequency (%)
0.0 16
12.7%
0.1 5
 
4.0%
0.2 1
 
0.8%
0.3 3
 
2.4%
0.5 1
 
0.8%
0.7 2
 
1.6%
1.1 1
 
0.8%
1.4 3
 
2.4%
1.5 1
 
0.8%
1.6 2
 
1.6%
ValueCountFrequency (%)
50.0 3
2.4%
30.9 1
 
0.8%
28.6 1
 
0.8%
27.0 1
 
0.8%
26.7 1
 
0.8%
26.1 1
 
0.8%
25.0 1
 
0.8%
23.4 1
 
0.8%
22.6 1
 
0.8%
22.2 1
 
0.8%

Interactions

2023-12-12T14:08:32.640414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:18.444676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:20.096406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:21.320382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:22.848817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:24.295202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:25.561423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:26.729360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:28.469646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:29.973243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:31.306597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:32.758301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:18.568830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:20.205193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:21.432093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:22.978543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:24.405724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:25.675638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:26.858581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:28.607772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:30.106682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:31.425456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:32.861803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:18.682357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:20.301469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:21.553181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:23.090581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:24.496246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:25.772636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:26.969641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:28.733189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:30.237570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:31.527566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:33.011075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:18.833280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:20.448167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:21.707370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:23.234432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:24.624386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:25.877476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:27.097955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:28.878636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:30.367476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:31.689363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:33.142007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:18.962846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:20.548280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:21.860680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:23.363224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:24.751771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:25.979968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:27.251040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:29.014068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:30.496090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:31.816138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:33.245856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:19.068262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:20.657093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:21.973303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:23.476531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:24.879242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:26.068242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:27.381864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:29.144067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:30.631251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:31.934402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:33.371972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:19.214305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:20.779087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:22.161261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:23.614286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:24.991674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:26.183754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:27.830418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:29.276589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:30.772489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:32.071011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:33.490864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:19.334326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:20.879970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:22.285890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:23.728367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:25.088282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:26.271893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:27.955349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:29.419562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:30.874377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:32.191582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:33.616790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:19.460753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:21.002573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:22.437585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:23.905125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:25.214152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:26.427308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:28.152947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:29.562474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:30.986172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:32.328809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:33.730069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:19.574169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:21.128485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:22.586064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:24.042884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:25.321867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:26.519645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:28.267573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:29.694130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:31.098034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:32.442569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:33.854279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:19.674248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:21.235814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:22.722988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:24.173738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:25.433633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:26.617787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:28.371427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:29.819025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:31.198018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:08:32.542352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:08:38.073602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도업종구분상반기_실시사업장수상반기_실시사업장비율상반기_초과사업장수상반기_초과사업장비율상반기_초과율하반기_실시사업장수하반기_실시사업장비율하반기_초과사업장수하반기_초과사업장비율상반기_초과율.1
연도1.0000.0000.0000.0000.0000.0000.1510.0000.0000.0000.0000.000
업종구분0.0001.0000.8041.0001.0000.8040.0000.7631.0001.0001.0000.782
상반기_실시사업장수0.0000.8041.0001.0001.0000.9540.1971.0001.0001.0001.0000.827
상반기_실시사업장비율0.0001.0001.0001.0000.9901.0000.3371.0000.9900.9900.9900.915
상반기_초과사업장수0.0001.0001.0000.9901.0001.0000.3371.0000.9900.9900.9900.915
상반기_초과사업장비율0.0000.8040.9541.0001.0001.0000.4820.6981.0001.0001.0000.656
상반기_초과율0.1510.0000.1970.3370.3370.4821.0000.3050.3370.3370.3370.760
하반기_실시사업장수0.0000.7631.0001.0001.0000.6980.3051.0001.0001.0001.0000.906
하반기_실시사업장비율0.0001.0001.0000.9900.9901.0000.3371.0001.0000.9900.9900.915
하반기_초과사업장수0.0001.0001.0000.9900.9901.0000.3371.0000.9901.0000.9900.915
하반기_초과사업장비율0.0001.0001.0000.9900.9901.0000.3371.0000.9900.9901.0000.915
상반기_초과율.10.0000.7820.8270.9150.9150.6560.7600.9060.9150.9150.9151.000
2023-12-12T14:08:38.275740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도상반기_실시사업장수상반기_실시사업장비율상반기_초과사업장수상반기_초과사업장비율상반기_초과율하반기_실시사업장수하반기_실시사업장비율하반기_초과사업장수하반기_초과사업장비율상반기_초과율.1업종구분
연도1.0000.0820.0180.057-0.0810.1890.0890.0370.0520.020-0.0300.000
상반기_실시사업장수0.0821.0000.9910.7280.7230.0500.9960.9880.7410.738-0.0570.537
상반기_실시사업장비율0.0180.9911.0000.7210.7310.0430.9890.9930.7370.739-0.0430.889
상반기_초과사업장수0.0570.7280.7211.0000.9220.5650.7350.7350.9440.9440.4080.889
상반기_초과사업장비율-0.0810.7230.7310.9221.0000.4450.7310.7450.8900.9230.3550.537
상반기_초과율0.1890.0500.0430.5650.4451.0000.0670.0640.4720.4570.6550.000
하반기_실시사업장수0.0890.9960.9890.7350.7310.0671.0000.9910.7520.747-0.0400.418
하반기_실시사업장비율0.0370.9880.9930.7350.7450.0640.9911.0000.7530.756-0.0250.889
하반기_초과사업장수0.0520.7410.7370.9440.8900.4720.7520.7531.0000.9620.4990.889
하반기_초과사업장비율0.0200.7380.7390.9440.9230.4570.7470.7560.9621.0000.4310.889
상반기_초과율.1-0.030-0.057-0.0430.4080.3550.655-0.040-0.0250.4990.4311.0000.395
업종구분0.0000.5370.8890.8890.5370.0000.4180.8890.8890.8890.3951.000

Missing values

2023-12-12T14:08:33.993641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:08:34.204164image/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

연도업종구분상반기_실시사업장수상반기_실시사업장비율상반기_초과사업장수상반기_초과사업장비율상반기_초과율하반기_실시사업장수하반기_실시사업장비율하반기_초과사업장수하반기_초과사업장비율상반기_초과율.1
02016농업670.160.19.0700.190.112.9
12016임업70.010.014.370.010.014.3
22016어업70.000.00.010.000.00.0
32016광업1810.4500.727.61810.4560.830.9
42016제조업3894081.2642495.716.53906781.8641895.316.4
52016전기가스증기 및 수도사업1900.460.13.21930.460.13.1
62016하수.폐기물처리원료재생 및 환경복원업6611.4560.88.56861.4530.87.7
72016건설업13862.9861.36.216763.51001.56.0
82016도매 및 소매업6491.4340.55.26071.3420.66.9
92016운수업3000.690.13.03060.680.12.6
연도업종구분상반기_실시사업장수상반기_실시사업장비율상반기_초과사업장수상반기_초과사업장비율상반기_초과율하반기_실시사업장수하반기_실시사업장비율하반기_초과사업장수하반기_초과사업장비율상반기_초과율.1
1162021출판, 영상, 방송통신 및 정보서비스업1180.250.00.01330.280.16.0
1172021금융 및 보험업270.020.031.08260.010.03.8
1182021부동산업 및 임대업610.150.060.68670.140.16.0
1192021전문, 과학 및 기술 서비스업9861.6130.0210.6610241.9170.31.7
1202021사업시설관리 및 사업지원 서비스업2570.470.023.512400.460.12.5
1212021공공행정, 국방 및 사회보장 행정3180.540.013.513260.690.12.8
1222021교육 서비스업750.110.01.69480.100.00.0
1232021보건업 및 사회복지 서비스업18533.000.00.018073.300.00.0
1242021예술, 스포츠 및 여가관련 서비스업940.240.00.0930.220.02.2
1252021협회및단체,수리 및 기타 개인 서비스업37706.260.010.8632986.090.10.3