Overview

Dataset statistics

Number of variables9
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory830.1 KiB
Average record size in memory85.0 B

Variable types

Numeric5
Categorical3
DateTime1

Dataset

Description고용노동부에서 제공하는 순번, 과태료부과유형, 과태료징수요청일자, 과태료징수요청결과, 과태료징수결정금액, 가산금금액, 합계금액, 과태료부과상태 순으로 나열된 과태료 부과내역 데이터파일입니다.
Author고용노동부
URLhttps://www.data.go.kr/data/15071628/fileData.do

Alerts

과태료징수요청결과 has constant value ""Constant
과태료징수결정금액 is highly overall correlated with 합계금액High correlation
가산금금액 is highly overall correlated with 가산횟수High correlation
가산횟수 is highly overall correlated with 가산금금액High correlation
합계금액 is highly overall correlated with 과태료징수결정금액High correlation
과태료부과유형 is highly overall correlated with 과태료부과상태High correlation
과태료부과상태 is highly overall correlated with 과태료부과유형High correlation
과태료징수결정금액 is highly skewed (γ1 = 24.46003228)Skewed
가산금금액 is highly skewed (γ1 = 30.7349579)Skewed
합계금액 is highly skewed (γ1 = 23.17143546)Skewed
순번 has unique valuesUnique
가산금금액 has 8152 (81.5%) zerosZeros
가산횟수 has 8101 (81.0%) zerosZeros

Reproduction

Analysis started2023-12-12 09:22:34.087690
Analysis finished2023-12-12 09:22:38.805966
Duration4.72 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49889.577
Minimum4
Maximum99952
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T18:22:38.905357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile5278.75
Q124853.25
median49801
Q374723.5
95-th percentile94914.8
Maximum99952
Range99948
Interquartile range (IQR)49870.25

Descriptive statistics

Standard deviation28835.957
Coefficient of variation (CV)0.57799563
Kurtosis-1.2045036
Mean49889.577
Median Absolute Deviation (MAD)24929.5
Skewness0.0098685528
Sum4.9889577 × 108
Variance8.3151244 × 108
MonotonicityNot monotonic
2023-12-12T18:22:39.492503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10327 1
 
< 0.1%
21359 1
 
< 0.1%
91367 1
 
< 0.1%
85620 1
 
< 0.1%
26565 1
 
< 0.1%
62913 1
 
< 0.1%
56588 1
 
< 0.1%
10005 1
 
< 0.1%
40126 1
 
< 0.1%
21795 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
4 1
< 0.1%
8 1
< 0.1%
20 1
< 0.1%
25 1
< 0.1%
26 1
< 0.1%
32 1
< 0.1%
42 1
< 0.1%
51 1
< 0.1%
69 1
< 0.1%
70 1
< 0.1%
ValueCountFrequency (%)
99952 1
< 0.1%
99943 1
< 0.1%
99928 1
< 0.1%
99926 1
< 0.1%
99918 1
< 0.1%
99901 1
< 0.1%
99885 1
< 0.1%
99884 1
< 0.1%
99874 1
< 0.1%
99857 1
< 0.1%

과태료부과유형
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
자진납부 부과
6340 
정식납부 부과
1692 
중가산금납부 부과
1109 
가산금납부 부과
740 
<NA>
 
119

Length

Max length9
Median length7
Mean length7.2601
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row자진납부 부과
2nd row자진납부 부과
3rd row<NA>
4th row자진납부 부과
5th row자진납부 부과

Common Values

ValueCountFrequency (%)
자진납부 부과 6340
63.4%
정식납부 부과 1692
 
16.9%
중가산금납부 부과 1109
 
11.1%
가산금납부 부과 740
 
7.4%
<NA> 119
 
1.2%

Length

2023-12-12T18:22:39.681209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:22:39.828165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부과 9881
49.7%
자진납부 6340
31.9%
정식납부 1692
 
8.5%
중가산금납부 1109
 
5.6%
가산금납부 740
 
3.7%
na 119
 
0.6%

과태료징수요청일자
Date

Distinct219
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2022-01-03 00:00:00
Maximum2022-09-27 00:00:00
2023-12-12T18:22:39.956836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:22:40.110484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

과태료징수요청결과
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
성공
10000 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
성공 10000
100.0%

Length

2023-12-12T18:22:40.269379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:22:40.395028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
성공 10000
100.0%

과태료징수결정금액
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct269
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean398751.05
Minimum0
Maximum1.28 × 108
Zeros9
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T18:22:40.528216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile12000
Q124000
median40000
Q360000
95-th percentile1000000
Maximum1.28 × 108
Range1.28 × 108
Interquartile range (IQR)36000

Descriptive statistics

Standard deviation2627766.3
Coefficient of variation (CV)6.5899921
Kurtosis916.48541
Mean398751.05
Median Absolute Deviation (MAD)16000
Skewness24.460032
Sum3.9875105 × 109
Variance6.9051556 × 1012
MonotonicityNot monotonic
2023-12-12T18:22:40.738286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24000 1823
18.2%
12000 1323
13.2%
40000 1256
12.6%
30000 938
9.4%
50000 635
 
6.3%
15000 628
 
6.3%
48000 552
 
5.5%
60000 303
 
3.0%
80000 209
 
2.1%
72000 160
 
1.6%
Other values (259) 2173
21.7%
ValueCountFrequency (%)
0 9
 
0.1%
12000 1323
13.2%
15000 628
 
6.3%
20000 6
 
0.1%
24000 1823
18.2%
25000 16
 
0.2%
30000 938
9.4%
36000 68
 
0.7%
40000 1256
12.6%
45000 36
 
0.4%
ValueCountFrequency (%)
128000000 1
< 0.1%
104000000 1
< 0.1%
72500000 1
< 0.1%
57500000 1
< 0.1%
49440000 1
< 0.1%
38700000 1
< 0.1%
38400000 1
< 0.1%
37500000 1
< 0.1%
35000000 1
< 0.1%
27344530 1
< 0.1%

가산금금액
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct456
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19775.188
Minimum0
Maximum14094000
Zeros8152
Zeros (%)81.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T18:22:40.925058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile23100
Maximum14094000
Range14094000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation265917.72
Coefficient of variation (CV)13.447039
Kurtosis1225.8742
Mean19775.188
Median Absolute Deviation (MAD)0
Skewness30.734958
Sum1.9775188 × 108
Variance7.0712236 × 1010
MonotonicityNot monotonic
2023-12-12T18:22:41.117619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 8152
81.5%
900 217
 
2.2%
450 138
 
1.4%
1500 135
 
1.4%
1800 50
 
0.5%
2700 45
 
0.4%
38500 45
 
0.4%
1260 35
 
0.4%
30000 32
 
0.3%
4500 26
 
0.3%
Other values (446) 1125
 
11.2%
ValueCountFrequency (%)
0 8152
81.5%
450 138
 
1.4%
630 23
 
0.2%
810 12
 
0.1%
900 217
 
2.2%
990 11
 
0.1%
1170 8
 
0.1%
1260 35
 
0.4%
1350 15
 
0.1%
1500 135
 
1.4%
ValueCountFrequency (%)
14094000 1
< 0.1%
10458000 1
< 0.1%
7484400 1
< 0.1%
6930000 1
< 0.1%
5490000 1
< 0.1%
5262600 1
< 0.1%
5202000 1
< 0.1%
4851000 1
< 0.1%
4620000 2
< 0.1%
4158000 1
< 0.1%

가산횟수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct62
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.5648
Minimum0
Maximum61
Zeros8101
Zeros (%)81.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T18:22:41.308394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile17
Maximum61
Range61
Interquartile range (IQR)0

Descriptive statistics

Standard deviation9.7953048
Coefficient of variation (CV)3.8191301
Kurtosis22.027563
Mean2.5648
Median Absolute Deviation (MAD)0
Skewness4.6680749
Sum25648
Variance95.947996
MonotonicityNot monotonic
2023-12-12T18:22:41.486639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 8101
81.0%
1 766
 
7.7%
2 135
 
1.4%
61 135
 
1.4%
3 88
 
0.9%
4 63
 
0.6%
5 63
 
0.6%
10 40
 
0.4%
7 40
 
0.4%
6 39
 
0.4%
Other values (52) 530
 
5.3%
ValueCountFrequency (%)
0 8101
81.0%
1 766
 
7.7%
2 135
 
1.4%
3 88
 
0.9%
4 63
 
0.6%
5 63
 
0.6%
6 39
 
0.4%
7 40
 
0.4%
8 16
 
0.2%
9 28
 
0.3%
ValueCountFrequency (%)
61 135
1.4%
60 10
 
0.1%
59 4
 
< 0.1%
58 6
 
0.1%
57 2
 
< 0.1%
56 3
 
< 0.1%
55 3
 
< 0.1%
54 2
 
< 0.1%
53 4
 
< 0.1%
52 1
 
< 0.1%

합계금액
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct780
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean418526.24
Minimum0
Maximum1.28 × 108
Zeros9
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T18:22:41.729421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile12000
Q124000
median40000
Q364000
95-th percentile1200000
Maximum1.28 × 108
Range1.28 × 108
Interquartile range (IQR)40000

Descriptive statistics

Standard deviation2697694.3
Coefficient of variation (CV)6.4456993
Kurtosis831.82149
Mean418526.24
Median Absolute Deviation (MAD)16000
Skewness23.171435
Sum4.1852624 × 109
Variance7.2775545 × 1012
MonotonicityNot monotonic
2023-12-12T18:22:41.923781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24000 1823
18.2%
12000 1323
 
13.2%
40000 1256
 
12.6%
48000 552
 
5.5%
30000 492
 
4.9%
15000 360
 
3.6%
50000 284
 
2.8%
30900 217
 
2.2%
60000 189
 
1.9%
80000 172
 
1.7%
Other values (770) 3332
33.3%
ValueCountFrequency (%)
0 9
 
0.1%
12000 1323
13.2%
15000 360
 
3.6%
15450 138
 
1.4%
15630 23
 
0.2%
15810 12
 
0.1%
15990 11
 
0.1%
16170 8
 
0.1%
16350 5
 
0.1%
16530 5
 
0.1%
ValueCountFrequency (%)
128000000 1
< 0.1%
104000000 1
< 0.1%
72500000 1
< 0.1%
57500000 1
< 0.1%
49440000 1
< 0.1%
41094000 1
< 0.1%
39861000 1
< 0.1%
38400000 1
< 0.1%
37500000 1
< 0.1%
35000000 1
< 0.1%

과태료부과상태
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
수납 완료
5605 
자진납부 부과
1918 
중가산금납부 요청
1124 
가산금납부 요청
867 
중가산금납부 부과
 
159
Other values (7)
 
327

Length

Max length9
Median length5
Mean length6.2097
Min length4

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row수납 완료
2nd row수납 완료
3rd row수납 완료
4th row수납 완료
5th row자진납부 부과

Common Values

ValueCountFrequency (%)
수납 완료 5605
56.0%
자진납부 부과 1918
 
19.2%
중가산금납부 요청 1124
 
11.2%
가산금납부 요청 867
 
8.7%
중가산금납부 부과 159
 
1.6%
정식납부 부과 147
 
1.5%
가산금납부 부과 76
 
0.8%
<NA> 74
 
0.7%
과태료 부과취소 19
 
0.2%
이의제기 요청 9
 
0.1%
Other values (2) 2
 
< 0.1%

Length

2023-12-12T18:22:42.114649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수납 5605
28.1%
완료 5605
28.1%
부과 2301
11.5%
요청 2000
 
10.0%
자진납부 1918
 
9.6%
중가산금납부 1283
 
6.4%
가산금납부 943
 
4.7%
정식납부 147
 
0.7%
na 74
 
0.4%
과태료 20
 
0.1%
Other values (4) 30
 
0.2%

Interactions

2023-12-12T18:22:37.996688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:22:35.459781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:22:36.193111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:22:36.813355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:22:37.410179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:22:38.101755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:22:35.578332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:22:36.329242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:22:36.924621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:22:37.533704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:22:38.208146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:22:35.710184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:22:36.467414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:22:37.048961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:22:37.655609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:22:38.325770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:22:35.879686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:22:36.584690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:22:37.174591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:22:37.762998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:22:38.442160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:22:36.053218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:22:36.700693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:22:37.281289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:22:37.892075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:22:42.229086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번과태료부과유형과태료징수결정금액가산금금액가산횟수합계금액과태료부과상태
순번1.0000.1510.0000.0000.1980.0090.108
과태료부과유형0.1511.0000.0410.1630.6620.0710.833
과태료징수결정금액0.0000.0411.0000.4880.0000.9990.000
가산금금액0.0000.1630.4881.0000.2320.7020.324
가산횟수0.1980.6620.0000.2321.0000.0570.490
합계금액0.0090.0710.9990.7020.0571.0000.026
과태료부과상태0.1080.8330.0000.3240.4900.0261.000
2023-12-12T18:22:42.377600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과태료부과유형과태료부과상태
과태료부과유형1.0000.681
과태료부과상태0.6811.000
2023-12-12T18:22:42.483825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번과태료징수결정금액가산금금액가산횟수합계금액과태료부과유형과태료부과상태
순번1.000-0.035-0.008-0.009-0.0380.0910.046
과태료징수결정금액-0.0351.0000.2370.2290.9970.0160.000
가산금금액-0.0080.2371.0000.9820.2780.0740.159
가산횟수-0.0090.2290.9821.0000.2730.4630.233
합계금액-0.0380.9970.2780.2731.0000.0280.016
과태료부과유형0.0910.0160.0740.4630.0281.0000.681
과태료부과상태0.0460.0000.1590.2330.0160.6811.000

Missing values

2023-12-12T18:22:38.597753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:22:38.739297image/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

순번과태료부과유형과태료징수요청일자과태료징수요청결과과태료징수결정금액가산금금액가산횟수합계금액과태료부과상태
1032610327자진납부 부과2022-02-07성공16800000168000수납 완료
76087609자진납부 부과2022-01-24성공240000024000수납 완료
7613676137<NA>2022-07-25성공6240000006240000수납 완료
7742577426자진납부 부과2022-07-27성공240000024000수납 완료
9355993560자진납부 부과2022-09-13성공120000012000자진납부 부과
86918692정식납부 부과2022-01-26성공150000015000수납 완료
2458724588가산금납부 부과2022-03-17성공12000036001123600중가산금납부 요청
2157121572자진납부 부과2022-03-08성공240000024000자진납부 부과
9872798728중가산금납부 부과2022-09-23성공300001260231260중가산금납부 요청
9817698177중가산금납부 부과2022-09-22성공4000007920015479200중가산금납부 부과
순번과태료부과유형과태료징수요청일자과태료징수요청결과과태료징수결정금액가산금금액가산횟수합계금액과태료부과상태
1850918510자진납부 부과2022-03-02성공240000024000자진납부 부과
5334353344정식납부 부과2022-05-31성공150000015000가산금납부 요청
88508851중가산금납부 부과2022-01-27성공50000385006188500중가산금납부 요청
2151121512중가산금납부 부과2022-03-08성공300002340532340수납 완료
5655756558자진납부 부과2022-06-08성공400000040000수납 완료
6592565926자진납부 부과2022-07-01성공400000040000자진납부 부과
7702877029자진납부 부과2022-07-27성공120000012000수납 완료
40984099자진납부 부과2022-01-13성공400000040000수납 완료
7224872249자진납부 부과2022-07-15성공240000024000자진납부 부과
48054806자진납부 부과2022-01-17성공720000072000수납 완료