Overview

Dataset statistics

Number of variables4
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory410.2 KiB
Average record size in memory42.0 B

Variable types

DateTime1
Numeric2
Categorical1

Dataset

Description2013년부터 2018년까지의 시간별 공급량 자료로 연/월/일/시간 단위로 구분하여 제공하고 있습니다. "구분"은 공급사이지만 영업 비밀에 해당하여 비식별화 처리된 데이터이고, "공급량"은 영업비밀에 해당하여 원데이터와 유사한 패턴을 갖도록 처리된 데이터입니다.
URLhttps://www.data.go.kr/data/15091497/fileData.do

Reproduction

Analysis started2023-12-12 17:04:32.598841
Analysis finished2023-12-12 17:04:33.352756
Duration0.75 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연월일
Date

Distinct730
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2013-01-01 00:00:00
Maximum2014-12-31 00:00:00
2023-12-13T02:04:33.432387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:33.605173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

시간
Real number (ℝ)

Distinct24
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.4167
Minimum1
Maximum24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T02:04:33.764221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q16
median12
Q318
95-th percentile23
Maximum24
Range23
Interquartile range (IQR)12

Descriptive statistics

Standard deviation6.9364597
Coefficient of variation (CV)0.55863955
Kurtosis-1.2042125
Mean12.4167
Median Absolute Deviation (MAD)6
Skewness0.0072462189
Sum124167
Variance48.114473
MonotonicityNot monotonic
2023-12-13T02:04:33.913213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1 464
 
4.6%
11 452
 
4.5%
12 442
 
4.4%
5 441
 
4.4%
19 438
 
4.4%
15 438
 
4.4%
20 435
 
4.3%
14 431
 
4.3%
4 425
 
4.2%
23 424
 
4.2%
Other values (14) 5610
56.1%
ValueCountFrequency (%)
1 464
4.6%
2 394
3.9%
3 421
4.2%
4 425
4.2%
5 441
4.4%
6 417
4.2%
7 422
4.2%
8 385
3.9%
9 410
4.1%
10 382
3.8%
ValueCountFrequency (%)
24 399
4.0%
23 424
4.2%
22 408
4.1%
21 393
3.9%
20 435
4.3%
19 438
4.4%
18 386
3.9%
17 403
4.0%
16 391
3.9%
15 438
4.4%

구분
Categorical

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
D
1782 
C
1781 
B
1745 
A
1724 
E
1236 
Other values (2)
1732 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowD
2nd rowC
3rd rowB
4th rowB
5th rowC

Common Values

ValueCountFrequency (%)
D 1782
17.8%
C 1781
17.8%
B 1745
17.4%
A 1724
17.2%
E 1236
12.4%
H 869
8.7%
G 863
8.6%

Length

2023-12-13T02:04:34.056075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:04:34.177103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
d 1782
17.8%
c 1781
17.8%
b 1745
17.4%
a 1724
17.2%
e 1236
12.4%
h 869
8.7%
g 863
8.6%

공급량(톤)
Real number (ℝ)

Distinct8261
Distinct (%)82.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean920.49238
Minimum1.378
Maximum5741.557
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T02:04:34.362252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.378
5-th percentile95.7573
Q1219.69325
median627.579
Q31358.6502
95-th percentile2762.2842
Maximum5741.557
Range5740.179
Interquartile range (IQR)1138.957

Descriptive statistics

Standard deviation879.24477
Coefficient of variation (CV)0.95518963
Kurtosis1.8197728
Mean920.49238
Median Absolute Deviation (MAD)461.135
Skewness1.4231965
Sum9204923.8
Variance773071.37
MonotonicityNot monotonic
2023-12-13T02:04:34.554297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.378 105
 
1.1%
135.778 18
 
0.2%
134.178 18
 
0.2%
136.578 17
 
0.2%
134.978 16
 
0.2%
127.778 15
 
0.1%
154.978 15
 
0.1%
130.178 15
 
0.1%
147.778 15
 
0.1%
130.978 14
 
0.1%
Other values (8251) 9752
97.5%
ValueCountFrequency (%)
1.378 105
1.1%
14.916 1
 
< 0.1%
15.076 1
 
< 0.1%
15.956 1
 
< 0.1%
16.916 1
 
< 0.1%
17.716 1
 
< 0.1%
18.116 1
 
< 0.1%
19.796 1
 
< 0.1%
21.556 1
 
< 0.1%
22.036 1
 
< 0.1%
ValueCountFrequency (%)
5741.557 1
< 0.1%
5307.157 1
< 0.1%
5183.237 1
< 0.1%
5151.789 1
< 0.1%
5048.221 1
< 0.1%
5004.437 1
< 0.1%
4955.205 1
< 0.1%
4916.037 1
< 0.1%
4855.557 1
< 0.1%
4783.621 1
< 0.1%

Interactions

2023-12-13T02:04:33.012009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:32.817586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:33.103889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:32.911035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:04:34.648200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시간구분공급량(톤)
시간1.0000.0000.241
구분0.0001.0000.558
공급량(톤)0.2410.5581.000
2023-12-13T02:04:34.748839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시간공급량(톤)구분
시간1.0000.1170.000
공급량(톤)0.1171.0000.324
구분0.0000.3241.000

Missing values

2023-12-13T02:04:33.226119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:04:33.314574image/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

연월일시간구분공급량(톤)
345062013-12-0919D1373.156
867182014-11-257C155.778
705302014-01-1919B2220.053
728672014-04-274B264.933
796252014-02-0218C202.978
773952014-11-0120B742.453
197332013-04-036C160.578
602682013-11-185H290.54
279462013-03-1111D1084.196
461152013-04-0712G2024.981
연월일시간구분공급량(톤)
340002013-11-1817D952.596
940742014-09-2719D350.653
591422013-10-027H116.724
510452013-10-2922G2338.605
278202013-03-065D949.396
827152014-06-1112C140.578
416542013-10-0315E688.405
87022013-12-2915A1971.201
266922013-01-185D1411.636
948132014-10-2814D489.917