Overview

Dataset statistics

Number of variables11
Number of observations42
Missing cells14
Missing cells (%)3.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.1 KiB
Average record size in memory101.0 B

Variable types

Categorical1
Numeric10

Dataset

Description한국산업안전보건공단에서 제공하는 특수건강진단 사후관리 조치에 대한 통계 분석자료로 대상자별 직업병,일반질병,작업관련질병에 대한 작업자들의 데이터를 나타냅니다.
Author공공데이터포털
URLhttps://www.data.go.kr/data/15091897/fileData.do

Alerts

정상근무 is highly overall correlated with 건강상담 and 4 other fieldsHigh correlation
건강상담 is highly overall correlated with 정상근무 and 4 other fieldsHigh correlation
보호구착용 is highly overall correlated with 정상근무 and 6 other fieldsHigh correlation
추적검사 is highly overall correlated with 정상근무 and 6 other fieldsHigh correlation
근무중치료 is highly overall correlated with 건강관리구분High correlation
근로시간단축 is highly overall correlated with 작업전환High correlation
작업전환 is highly overall correlated with 정상근무 and 6 other fieldsHigh correlation
근로금지제한 is highly overall correlated with 정상근무 and 3 other fieldsHigh correlation
기타 is highly overall correlated with 건강상담 and 3 other fieldsHigh correlation
건강관리구분 is highly overall correlated with 보호구착용 and 2 other fieldsHigh correlation
보호구착용 has 14 (33.3%) missing valuesMissing
정상근무 has unique valuesUnique
건강상담 has unique valuesUnique
추적검사 has unique valuesUnique
근무중치료 has unique valuesUnique
기타 has unique valuesUnique
근로금지제한 has 1 (2.4%) zerosZeros

Reproduction

Analysis started2024-04-20 14:04:44.302315
Analysis finished2024-04-20 14:05:08.055494
Duration23.75 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

건강관리구분
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size464.0 B
직업병_유소견자_D1
7 
직업병_요관찰자_C1
7 
일반질병_유소견자_D2
7 
일반질병_요관찰자_C2
7 
작업관련질병야간작업_유소견자_Dn
7 

Length

Max length18
Median length12
Mean length13.666667
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row직업병_유소견자_D1
2nd row직업병_유소견자_D1
3rd row직업병_유소견자_D1
4th row직업병_유소견자_D1
5th row직업병_유소견자_D1

Common Values

ValueCountFrequency (%)
직업병_유소견자_D1 7
16.7%
직업병_요관찰자_C1 7
16.7%
일반질병_유소견자_D2 7
16.7%
일반질병_요관찰자_C2 7
16.7%
작업관련질병야간작업_유소견자_Dn 7
16.7%
작업관련질병야간작업_요관찰자_Cn 7
16.7%

Length

2024-04-20T23:05:08.297535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-20T23:05:08.752263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
직업병_유소견자_d1 7
16.7%
직업병_요관찰자_c1 7
16.7%
일반질병_유소견자_d2 7
16.7%
일반질병_요관찰자_c2 7
16.7%
작업관련질병야간작업_유소견자_dn 7
16.7%
작업관련질병야간작업_요관찰자_cn 7
16.7%

연도
Real number (ℝ)

Distinct7
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2018
Minimum2015
Maximum2021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size506.0 B
2024-04-20T23:05:09.111823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2015
5-th percentile2015
Q12016
median2018
Q32020
95-th percentile2021
Maximum2021
Range6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.0242433
Coefficient of variation (CV)0.0010030938
Kurtosis-1.2549679
Mean2018
Median Absolute Deviation (MAD)2
Skewness0
Sum84756
Variance4.097561
MonotonicityNot monotonic
2024-04-20T23:05:09.481524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2015 6
14.3%
2016 6
14.3%
2017 6
14.3%
2018 6
14.3%
2019 6
14.3%
2020 6
14.3%
2021 6
14.3%
ValueCountFrequency (%)
2015 6
14.3%
2016 6
14.3%
2017 6
14.3%
2018 6
14.3%
2019 6
14.3%
2020 6
14.3%
2021 6
14.3%
ValueCountFrequency (%)
2021 6
14.3%
2020 6
14.3%
2019 6
14.3%
2018 6
14.3%
2017 6
14.3%
2016 6
14.3%
2015 6
14.3%

정상근무
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6168.881
Minimum73
Maximum14061
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size506.0 B
2024-04-20T23:05:09.878618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum73
5-th percentile1105.1
Q12041.5
median5911
Q39448
95-th percentile13132.1
Maximum14061
Range13988
Interquartile range (IQR)7406.5

Descriptive statistics

Standard deviation4113.2752
Coefficient of variation (CV)0.66677818
Kurtosis-1.1270462
Mean6168.881
Median Absolute Deviation (MAD)3833
Skewness0.28650848
Sum259093
Variance16919033
MonotonicityNot monotonic
2024-04-20T23:05:10.305843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
1101 1
 
2.4%
5904 1
 
2.4%
14061 1
 
2.4%
9418 1
 
2.4%
6789 1
 
2.4%
4582 1
 
2.4%
4407 1
 
2.4%
5918 1
 
2.4%
6755 1
 
2.4%
7763 1
 
2.4%
Other values (32) 32
76.2%
ValueCountFrequency (%)
73 1
2.4%
283 1
2.4%
1101 1
2.4%
1183 1
2.4%
1225 1
2.4%
1405 1
2.4%
1972 1
2.4%
1978 1
2.4%
1989 1
2.4%
1998 1
2.4%
ValueCountFrequency (%)
14061 1
2.4%
13434 1
2.4%
13180 1
2.4%
12222 1
2.4%
12182 1
2.4%
11398 1
2.4%
11033 1
2.4%
10471 1
2.4%
10331 1
2.4%
10089 1
2.4%

건강상담
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37367.5
Minimum6
Maximum178275
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size506.0 B
2024-04-20T23:05:10.767485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile8.5
Q1758.5
median3092
Q381710.5
95-th percentile150071.4
Maximum178275
Range178269
Interquartile range (IQR)80952

Descriptive statistics

Standard deviation55122.352
Coefficient of variation (CV)1.4751415
Kurtosis0.12085786
Mean37367.5
Median Absolute Deviation (MAD)3055
Skewness1.2243612
Sum1569435
Variance3.0384737 × 109
MonotonicityNot monotonic
2024-04-20T23:05:11.243915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
45 1
 
2.4%
4921 1
 
2.4%
85405 1
 
2.4%
104522 1
 
2.4%
87346 1
 
2.4%
88191 1
 
2.4%
4063 1
 
2.4%
2864 1
 
2.4%
5160 1
 
2.4%
5121 1
 
2.4%
Other values (32) 32
76.2%
ValueCountFrequency (%)
6 1
2.4%
7 1
2.4%
8 1
2.4%
18 1
2.4%
28 1
2.4%
29 1
2.4%
45 1
2.4%
304 1
2.4%
343 1
2.4%
433 1
2.4%
ValueCountFrequency (%)
178275 1
2.4%
162016 1
2.4%
150795 1
2.4%
136323 1
2.4%
128033 1
2.4%
116457 1
2.4%
104522 1
2.4%
88599 1
2.4%
88191 1
2.4%
87346 1
2.4%

보호구착용
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct28
Distinct (%)100.0%
Missing14
Missing (%)33.3%
Infinite0
Infinite (%)0.0%
Mean72148.429
Minimum4410
Maximum224221
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size506.0 B
2024-04-20T23:05:11.657120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4410
5-th percentile5100.95
Q16879
median55451
Q3113446
95-th percentile205878.05
Maximum224221
Range219811
Interquartile range (IQR)106567

Descriptive statistics

Standard deviation73532.809
Coefficient of variation (CV)1.0191879
Kurtosis-0.88414487
Mean72148.429
Median Absolute Deviation (MAD)49812.5
Skewness0.6117057
Sum2020156
Variance5.4070739 × 109
MonotonicityNot monotonic
2024-04-20T23:05:12.037260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
7002 1
 
2.4%
203189 1
 
2.4%
207326 1
 
2.4%
224221 1
 
2.4%
174394 1
 
2.4%
130097 1
 
2.4%
127621 1
 
2.4%
105251 1
 
2.4%
6922 1
 
2.4%
7150 1
 
2.4%
Other values (18) 18
42.9%
(Missing) 14
33.3%
ValueCountFrequency (%)
4410 1
2.4%
4899 1
2.4%
5476 1
2.4%
5626 1
2.4%
6237 1
2.4%
6410 1
2.4%
6750 1
2.4%
6922 1
2.4%
7002 1
2.4%
7097 1
2.4%
ValueCountFrequency (%)
224221 1
2.4%
207326 1
2.4%
203189 1
2.4%
174394 1
2.4%
130097 1
2.4%
127621 1
2.4%
116626 1
2.4%
112386 1
2.4%
110735 1
2.4%
108116 1
2.4%

추적검사
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49336.429
Minimum2339
Maximum179171
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size506.0 B
2024-04-20T23:05:12.612443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2339
5-th percentile2789.05
Q13725.75
median15766.5
Q3113943.25
95-th percentile150300.35
Maximum179171
Range176832
Interquartile range (IQR)110217.5

Descriptive statistics

Standard deviation58560.304
Coefficient of variation (CV)1.1869587
Kurtosis-0.94766447
Mean49336.429
Median Absolute Deviation (MAD)12821.5
Skewness0.85432661
Sum2072130
Variance3.4293092 × 109
MonotonicityNot monotonic
2024-04-20T23:05:13.035609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
2518 1
 
2.4%
5119 1
 
2.4%
150511 1
 
2.4%
179171 1
 
2.4%
159629 1
 
2.4%
146298 1
 
2.4%
3824 1
 
2.4%
6685 1
 
2.4%
7337 1
 
2.4%
5122 1
 
2.4%
Other values (32) 32
76.2%
ValueCountFrequency (%)
2339 1
2.4%
2518 1
2.4%
2785 1
2.4%
2866 1
2.4%
2944 1
2.4%
2947 1
2.4%
3031 1
2.4%
3464 1
2.4%
3568 1
2.4%
3659 1
2.4%
ValueCountFrequency (%)
179171 1
2.4%
159629 1
2.4%
150511 1
2.4%
146298 1
2.4%
135219 1
2.4%
131300 1
2.4%
123724 1
2.4%
118046 1
2.4%
117333 1
2.4%
116759 1
2.4%

근무중치료
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34347.571
Minimum88
Maximum179853
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size506.0 B
2024-04-20T23:05:13.370602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum88
5-th percentile196.55
Q1616.75
median11773
Q341908.25
95-th percentile165534.85
Maximum179853
Range179765
Interquartile range (IQR)41291.5

Descriptive statistics

Standard deviation50292.239
Coefficient of variation (CV)1.4642153
Kurtosis2.5003667
Mean34347.571
Median Absolute Deviation (MAD)11355.5
Skewness1.860209
Sum1442598
Variance2.5293093 × 109
MonotonicityNot monotonic
2024-04-20T23:05:13.666409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
88 1
 
2.4%
167009 1
 
2.4%
11386 1
 
2.4%
11619 1
 
2.4%
11168 1
 
2.4%
11927 1
 
2.4%
64386 1
 
2.4%
97942 1
 
2.4%
120381 1
 
2.4%
137526 1
 
2.4%
Other values (32) 32
76.2%
ValueCountFrequency (%)
88 1
2.4%
135 1
2.4%
195 1
2.4%
226 1
2.4%
230 1
2.4%
285 1
2.4%
350 1
2.4%
485 1
2.4%
523 1
2.4%
552 1
2.4%
ValueCountFrequency (%)
179853 1
2.4%
169479 1
2.4%
167009 1
2.4%
137526 1
2.4%
120381 1
2.4%
97942 1
2.4%
64386 1
2.4%
57694 1
2.4%
52778 1
2.4%
50497 1
2.4%

근로시간단축
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)69.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47.785714
Minimum2
Maximum238
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size506.0 B
2024-04-20T23:05:14.010763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile4.1
Q110.25
median22
Q367.25
95-th percentile159.55
Maximum238
Range236
Interquartile range (IQR)57

Descriptive statistics

Standard deviation57.978354
Coefficient of variation (CV)1.2132989
Kurtosis2.918982
Mean47.785714
Median Absolute Deviation (MAD)16
Skewness1.8121894
Sum2007
Variance3361.4895
MonotonicityNot monotonic
2024-04-20T23:05:14.217742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
6 4
 
9.5%
12 3
 
7.1%
16 3
 
7.1%
28 2
 
4.8%
4 2
 
4.8%
8 2
 
4.8%
22 2
 
4.8%
47 2
 
4.8%
10 2
 
4.8%
129 1
 
2.4%
Other values (19) 19
45.2%
ValueCountFrequency (%)
2 1
 
2.4%
4 2
4.8%
6 4
9.5%
8 2
4.8%
10 2
4.8%
11 1
 
2.4%
12 3
7.1%
13 1
 
2.4%
16 3
7.1%
20 1
 
2.4%
ValueCountFrequency (%)
238 1
2.4%
216 1
2.4%
161 1
2.4%
132 1
2.4%
129 1
2.4%
116 1
2.4%
112 1
2.4%
95 1
2.4%
86 1
2.4%
79 1
2.4%

작업전환
Real number (ℝ)

HIGH CORRELATION 

Distinct37
Distinct (%)88.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean261.45238
Minimum3
Maximum1548
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size506.0 B
2024-04-20T23:05:14.427654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile4.05
Q111.25
median100.5
Q3195.5
95-th percentile1351.55
Maximum1548
Range1545
Interquartile range (IQR)184.25

Descriptive statistics

Standard deviation419.26191
Coefficient of variation (CV)1.603588
Kurtosis2.872035
Mean261.45238
Median Absolute Deviation (MAD)89.5
Skewness2.0114641
Sum10981
Variance175780.55
MonotonicityNot monotonic
2024-04-20T23:05:14.909986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
6 2
 
4.8%
11 2
 
4.8%
126 2
 
4.8%
9 2
 
4.8%
4 2
 
4.8%
1548 1
 
2.4%
293 1
 
2.4%
8 1
 
2.4%
12 1
 
2.4%
5 1
 
2.4%
Other values (27) 27
64.3%
ValueCountFrequency (%)
3 1
2.4%
4 2
4.8%
5 1
2.4%
6 2
4.8%
8 1
2.4%
9 2
4.8%
11 2
4.8%
12 1
2.4%
19 1
2.4%
26 1
2.4%
ValueCountFrequency (%)
1548 1
2.4%
1375 1
2.4%
1369 1
2.4%
1020 1
2.4%
959 1
2.4%
880 1
2.4%
845 1
2.4%
293 1
2.4%
234 1
2.4%
232 1
2.4%

근로금지제한
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct33
Distinct (%)78.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean58.071429
Minimum0
Maximum215
Zeros1
Zeros (%)2.4%
Negative0
Negative (%)0.0%
Memory size506.0 B
2024-04-20T23:05:15.333033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q18.25
median33.5
Q3104.75
95-th percentile154.95
Maximum215
Range215
Interquartile range (IQR)96.5

Descriptive statistics

Standard deviation58.652092
Coefficient of variation (CV)1.0099991
Kurtosis-0.29513913
Mean58.071429
Median Absolute Deviation (MAD)29
Skewness0.87764129
Sum2439
Variance3440.0679
MonotonicityNot monotonic
2024-04-20T23:05:15.740218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
5 3
 
7.1%
14 3
 
7.1%
2 3
 
7.1%
20 2
 
4.8%
49 2
 
4.8%
4 2
 
4.8%
0 1
 
2.4%
215 1
 
2.4%
94 1
 
2.4%
16 1
 
2.4%
Other values (23) 23
54.8%
ValueCountFrequency (%)
0 1
 
2.4%
2 3
7.1%
4 2
4.8%
5 3
7.1%
6 1
 
2.4%
8 1
 
2.4%
9 1
 
2.4%
10 1
 
2.4%
14 3
7.1%
16 1
 
2.4%
ValueCountFrequency (%)
215 1
2.4%
171 1
2.4%
155 1
2.4%
154 1
2.4%
143 1
2.4%
142 1
2.4%
130 1
2.4%
112 1
2.4%
108 1
2.4%
107 1
2.4%

기타
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24617.024
Minimum396
Maximum105622
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size506.0 B
2024-04-20T23:05:16.165560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum396
5-th percentile497.45
Q11058
median3584
Q347455.75
95-th percentile96043.7
Maximum105622
Range105226
Interquartile range (IQR)46397.75

Descriptive statistics

Standard deviation34248.401
Coefficient of variation (CV)1.3912486
Kurtosis-0.18665686
Mean24617.024
Median Absolute Deviation (MAD)3019.5
Skewness1.1619087
Sum1033915
Variance1.1729529 × 109
MonotonicityNot monotonic
2024-04-20T23:05:16.624376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
490 1
 
2.4%
5552 1
 
2.4%
51329 1
 
2.4%
69628 1
 
2.4%
74267 1
 
2.4%
78961 1
 
2.4%
5163 1
 
2.4%
8338 1
 
2.4%
7760 1
 
2.4%
8012 1
 
2.4%
Other values (32) 32
76.2%
ValueCountFrequency (%)
396 1
2.4%
421 1
2.4%
490 1
2.4%
639 1
2.4%
859 1
2.4%
890 1
2.4%
912 1
2.4%
944 1
2.4%
961 1
2.4%
972 1
2.4%
ValueCountFrequency (%)
105622 1
2.4%
97801 1
2.4%
96603 1
2.4%
85417 1
2.4%
78961 1
2.4%
74267 1
2.4%
71733 1
2.4%
69876 1
2.4%
69628 1
2.4%
51329 1
2.4%

Interactions

2024-04-20T23:05:04.504853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:44.851625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:47.360433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:49.693246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:52.264345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:54.135459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:55.717672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:57.276752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:59.289633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:05:02.064121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:05:04.757550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:45.099418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:47.693156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:49.951381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:52.509915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:54.300204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:55.875607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:57.439362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:59.556785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:05:02.310683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:05:05.008163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:45.355064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:47.946123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:50.212424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:52.764761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:54.463873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:56.035341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:57.668686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:59.822904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:05:02.560049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:05:05.262728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:45.615670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:48.163356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:50.472774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:52.899849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:54.637354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:56.192980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:57.872794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:05:00.083573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:05:02.813676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:05:05.506461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:45.851710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:48.412826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:50.704777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:53.026124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:54.776255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:56.338315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:58.011297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:05:00.325377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:05:03.054586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:05:05.761403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:46.110743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:48.681318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:51.009123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:53.178341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:54.938153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:56.502916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:58.156437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:05:00.586407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:05:03.303645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:05:06.015150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:46.371318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:48.905704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:51.212912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:53.382290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:55.093958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:56.657016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:58.316706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:05:01.058564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:05:03.556350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:05:06.249347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:46.610561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:49.046124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:51.488625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:53.564038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:55.244275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:56.816982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:58.569082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:05:01.300065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:05:03.788570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:05:06.507387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:46.875533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:49.217456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:51.716175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:53.828065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:55.411218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:56.981891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:58.828625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:05:01.568544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:05:04.042061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:05:06.743478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:47.112132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:49.443491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:52.061392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:53.981580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:55.556239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:57.121281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:04:59.054890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:05:01.816225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T23:05:04.269912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-20T23:05:16.921876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
건강관리구분연도정상근무건강상담보호구착용추적검사근무중치료근로시간단축작업전환근로금지제한기타
건강관리구분1.0000.0000.7200.7160.7220.8460.7390.4610.8440.5270.658
연도0.0001.0000.0000.0000.0000.0000.0000.1980.0000.0000.000
정상근무0.7200.0001.0000.5030.8560.5600.3710.0000.2600.0000.513
건강상담0.7160.0000.5031.0000.9190.9160.0000.0000.0000.0000.918
보호구착용0.7220.0000.8560.9191.0000.8580.0000.0000.0000.2510.964
추적검사0.8460.0000.5600.9160.8581.0000.0000.0000.0000.2550.898
근무중치료0.7390.0000.3710.0000.0000.0001.0000.8450.0000.7560.000
근로시간단축0.4610.1980.0000.0000.0000.0000.8451.0000.7300.5520.000
작업전환0.8440.0000.2600.0000.0000.0000.0000.7301.0000.5910.000
근로금지제한0.5270.0000.0000.0000.2510.2550.7560.5520.5911.0000.219
기타0.6580.0000.5130.9180.9640.8980.0000.0000.0000.2191.000
2024-04-20T23:05:17.280509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도정상근무건강상담보호구착용추적검사근무중치료근로시간단축작업전환근로금지제한기타건강관리구분
연도1.000-0.2230.0190.3230.1820.118-0.436-0.198-0.1100.2290.000
정상근무-0.2231.0000.5900.7150.7220.055-0.050-0.612-0.5160.3780.453
건강상담0.0190.5901.0000.6680.7370.482-0.344-0.777-0.4600.8850.430
보호구착용0.3230.7150.6681.0000.9420.228-0.491-0.862-0.6560.5680.648
추적검사0.1820.7220.7370.9421.000-0.027-0.406-0.828-0.6950.6660.661
근무중치료0.1180.0550.4820.228-0.0271.000-0.094-0.1380.2670.4660.512
근로시간단축-0.436-0.050-0.344-0.491-0.406-0.0941.0000.6140.274-0.4520.262
작업전환-0.198-0.612-0.777-0.862-0.828-0.1380.6141.0000.661-0.7030.460
근로금지제한-0.110-0.516-0.460-0.656-0.6950.2670.2740.6611.000-0.4250.311
기타0.2290.3780.8850.5680.6660.466-0.452-0.703-0.4251.0000.461
건강관리구분0.0000.4530.4300.6480.6610.5120.2620.4600.3110.4611.000

Missing values

2024-04-20T23:05:07.092515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-20T23:05:07.688863image/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

건강관리구분연도정상근무건강상담보호구착용추적검사근무중치료근로시간단축작업전환근로금지제한기타
0직업병_유소견자_D120151101454410251888471548130490
1직업병_유소견자_D120161405184899294719513210201551039
2직업병_유소견자_D120171989285476233913571959154972
3직업병_유소견자_D120181972756262944226112137544890
4직업병_유소견자_D120191225867504116230116136914859
5직업병_유소견자_D12020283297486451228510880201115
6직업병_유소견자_D120217368907522635016845201183
7직업병_요관찰자_C1201510471332010199527592760287410396
8직업병_요관찰자_C120161139825291032242858765812912234421
9직업병_요관찰자_C12017134343041031092419676622118107639
건강관리구분연도정상근무건강상담보호구착용추적검사근무중치료근로시간단축작업전환근로금지제한기타
32작업관련질병야간작업_유소견자_Dn201959044921<NA>51191670092162321715552
33작업관련질병야간작업_유소견자_Dn202049484580<NA>467116947948201945977
34작업관련질병야간작업_유소견자_Dn2021215110505<NA>5381179853281262158905
35작업관련질병야간작업_요관찰자_Cn2015945888599<NA>86200101899511550318
36작업관련질병야간작업_요관찰자_Cn201610089116457<NA>1045061857623819069876
37작업관련질병야간작업_요관찰자_Cn201710331136323<NA>10582014076166471733
38작업관련질병야간작업_요관찰자_Cn201811033128033<NA>1180461667343285417
39작업관련질병야간작업_요관찰자_Cn201913180150795<NA>11675916322129297801
40작업관련질병야간작업_요관찰자_Cn20208577162016<NA>1237241909186296603
41작업관련질병야간작업_요관찰자_Cn20215370178275<NA>11733319174444105622