Overview

Dataset statistics

Number of variables7
Number of observations213
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.6 KiB
Average record size in memory60.6 B

Variable types

DateTime1
Categorical3
Numeric3

Dataset

Description년월,업종코드,업종,난방 판매량,냉방 판매량,총 판매량,작업일시
Author서울에너지공사
URLhttps://data.seoul.go.kr/dataList/OA-20441/S/1/datasetView.do

Alerts

작업일시 has constant value ""Constant
업종 is highly overall correlated with 난방 판매량 and 2 other fieldsHigh correlation
업종코드 is highly overall correlated with 난방 판매량 and 2 other fieldsHigh correlation
난방 판매량 is highly overall correlated with 냉방 판매량 and 3 other fieldsHigh correlation
냉방 판매량 is highly overall correlated with 난방 판매량High correlation
총 판매량 is highly overall correlated with 난방 판매량 and 2 other fieldsHigh correlation
난방 판매량 has unique valuesUnique
총 판매량 has unique valuesUnique
냉방 판매량 has 93 (43.7%) zerosZeros

Reproduction

Analysis started2024-05-18 07:07:25.819354
Analysis finished2024-05-18 07:07:30.614923
Duration4.8 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년월
Date

Distinct71
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
Minimum2016-12-01 00:00:00
Maximum2022-10-01 00:00:00
2024-05-18T16:07:30.810952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T16:07:31.280749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업종코드
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
3
71 
2
71 
1
71 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row2
3rd row1
4th row3
5th row2

Common Values

ValueCountFrequency (%)
3 71
33.3%
2 71
33.3%
1 71
33.3%

Length

2024-05-18T16:07:31.761877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T16:07:32.165720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 71
33.3%
2 71
33.3%
1 71
33.3%

업종
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
공공용
71 
업무용
71 
주택용
71 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row공공용
2nd row업무용
3rd row주택용
4th row공공용
5th row업무용

Common Values

ValueCountFrequency (%)
공공용 71
33.3%
업무용 71
33.3%
주택용 71
33.3%

Length

2024-05-18T16:07:32.405546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T16:07:32.669319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공용 71
33.3%
업무용 71
33.3%
주택용 71
33.3%

난방 판매량
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct213
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59437.794
Minimum507.5
Maximum403956.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-05-18T16:07:33.003368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum507.5
5-th percentile950.72
Q14319.7
median11930.2
Q351117.3
95-th percentile326240.84
Maximum403956.4
Range403448.9
Interquartile range (IQR)46797.6

Descriptive statistics

Standard deviation98849.703
Coefficient of variation (CV)1.6630783
Kurtosis3.3727813
Mean59437.794
Median Absolute Deviation (MAD)10976
Skewness2.1139577
Sum12660250
Variance9.7712639 × 109
MonotonicityNot monotonic
2024-05-18T16:07:33.336398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2666.3 1
 
0.5%
9520.0 1
 
0.5%
11930.2 1
 
0.5%
52859.6 1
 
0.5%
11318.6 1
 
0.5%
48953.4 1
 
0.5%
342210.3 1
 
0.5%
191841.9 1
 
0.5%
22273.2 1
 
0.5%
6048.6 1
 
0.5%
Other values (203) 203
95.3%
ValueCountFrequency (%)
507.5 1
0.5%
721.2 1
0.5%
741.4 1
0.5%
759.3 1
0.5%
776.1 1
0.5%
810.7 1
0.5%
854.5 1
0.5%
855.1 1
0.5%
884.9 1
0.5%
921.9 1
0.5%
ValueCountFrequency (%)
403956.4 1
0.5%
401822.3 1
0.5%
388121.1 1
0.5%
370119.9 1
0.5%
357264.5 1
0.5%
354651.1 1
0.5%
346060.5 1
0.5%
342210.3 1
0.5%
337241.2 1
0.5%
333131.6 1
0.5%

냉방 판매량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct117
Distinct (%)54.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3598.6817
Minimum0
Maximum42293.6
Zeros93
Zeros (%)43.7%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-05-18T16:07:33.784740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median52.5
Q32872.3
95-th percentile22624.28
Maximum42293.6
Range42293.6
Interquartile range (IQR)2872.3

Descriptive statistics

Standard deviation8297.6965
Coefficient of variation (CV)2.30576
Kurtosis9.1465667
Mean3598.6817
Median Absolute Deviation (MAD)52.5
Skewness3.0410355
Sum766519.2
Variance68851767
MonotonicityNot monotonic
2024-05-18T16:07:34.210279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 93
43.7%
0.1 5
 
2.3%
886.0 1
 
0.5%
447.1 1
 
0.5%
5089.7 1
 
0.5%
1383.4 1
 
0.5%
15021.3 1
 
0.5%
2936.4 1
 
0.5%
36.0 1
 
0.5%
685.9 1
 
0.5%
Other values (107) 107
50.2%
ValueCountFrequency (%)
0.0 93
43.7%
0.1 5
 
2.3%
0.2 1
 
0.5%
1.4 1
 
0.5%
3.5 1
 
0.5%
9.8 1
 
0.5%
15.6 1
 
0.5%
30.8 1
 
0.5%
36.0 1
 
0.5%
41.7 1
 
0.5%
ValueCountFrequency (%)
42293.6 1
0.5%
41405.6 1
0.5%
40184.6 1
0.5%
39716.6 1
0.5%
35257.5 1
0.5%
34873.9 1
0.5%
30704.0 1
0.5%
28270.8 1
0.5%
27109.6 1
0.5%
25942.8 1
0.5%

총 판매량
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct213
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean63036.476
Minimum1424.3
Maximum403956.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-05-18T16:07:34.601952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1424.3
5-th percentile2846.9
Q18380.2
median24328.6
Q351473.4
95-th percentile326240.84
Maximum403956.4
Range402532.1
Interquartile range (IQR)43093.2

Descriptive statistics

Standard deviation97185.664
Coefficient of variation (CV)1.541737
Kurtosis3.4766961
Mean63036.476
Median Absolute Deviation (MAD)18272.2
Skewness2.1360759
Sum13426769
Variance9.4450533 × 109
MonotonicityNot monotonic
2024-05-18T16:07:35.318370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3552.3 1
 
0.5%
9520.0 1
 
0.5%
11930.2 1
 
0.5%
53008.9 1
 
0.5%
11318.6 1
 
0.5%
49562.7 1
 
0.5%
342210.3 1
 
0.5%
191841.9 1
 
0.5%
22959.1 1
 
0.5%
6048.7 1
 
0.5%
Other values (203) 203
95.3%
ValueCountFrequency (%)
1424.3 1
0.5%
1512.3 1
0.5%
1721.4 1
0.5%
2069.4 1
0.5%
2194.4 1
0.5%
2203.4 1
0.5%
2238.5 1
0.5%
2723.2 1
0.5%
2740.1 1
0.5%
2755.5 1
0.5%
ValueCountFrequency (%)
403956.4 1
0.5%
401822.3 1
0.5%
388121.1 1
0.5%
370119.9 1
0.5%
357264.5 1
0.5%
354651.1 1
0.5%
346060.5 1
0.5%
342210.3 1
0.5%
337241.2 1
0.5%
333131.6 1
0.5%

작업일시
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-05-10 20:46:50.0
213 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-05-10 20:46:50.0
2nd row2024-05-10 20:46:50.0
3rd row2024-05-10 20:46:50.0
4th row2024-05-10 20:46:50.0
5th row2024-05-10 20:46:50.0

Common Values

ValueCountFrequency (%)
2024-05-10 20:46:50.0 213
100.0%

Length

2024-05-18T16:07:35.972941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T16:07:36.328457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-05-10 213
50.0%
20:46:50.0 213
50.0%

Interactions

2024-05-18T16:07:28.650052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T16:07:26.366965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T16:07:27.598454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T16:07:29.106905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T16:07:26.793494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T16:07:28.008783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T16:07:29.394848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T16:07:27.120439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T16:07:28.282744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T16:07:36.630662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년월업종코드업종난방 판매량냉방 판매량총 판매량
년월1.0000.0000.0000.0000.0000.000
업종코드0.0001.0001.0000.8020.4840.805
업종0.0001.0001.0000.8020.4840.805
난방 판매량0.0000.8020.8021.0000.0001.000
냉방 판매량0.0000.4840.4840.0001.0000.000
총 판매량0.0000.8050.8051.0000.0001.000
2024-05-18T16:07:37.034980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종업종코드
업종1.0001.000
업종코드1.0001.000
2024-05-18T16:07:37.326755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
난방 판매량냉방 판매량총 판매량업종코드업종
난방 판매량1.000-0.7150.8960.5020.502
냉방 판매량-0.7151.000-0.4380.3270.327
총 판매량0.896-0.4381.0000.5050.505
업종코드0.5020.3270.5051.0001.000
업종0.5020.3270.5051.0001.000

Missing values

2024-05-18T16:07:29.896384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T16:07:30.468202image/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

년월업종코드업종난방 판매량냉방 판매량총 판매량작업일시
02022-103공공용2666.3886.03552.32024-05-10 20:46:50.0
12022-102업무용9928.03349.913277.92024-05-10 20:46:50.0
22022-101주택용100927.30.0100927.32024-05-10 20:46:50.0
32022-093공공용1286.44565.45851.82024-05-10 20:46:50.0
42022-092업무용4856.920412.425269.32024-05-10 20:46:50.0
52022-091주택용39891.00.039891.02024-05-10 20:46:50.0
62022-083공공용1085.29629.910715.12024-05-10 20:46:50.0
72022-082업무용5257.039716.644973.62024-05-10 20:46:50.0
82022-081주택용30800.70.030800.72024-05-10 20:46:50.0
92022-073공공용1037.59365.910403.42024-05-10 20:46:50.0
년월업종코드업종난방 판매량냉방 판매량총 판매량작업일시
2032017-033공공용5904.60.05904.62024-05-10 20:46:50.0
2042017-023공공용8273.30.08273.32024-05-10 20:46:50.0
2052017-022업무용23961.130.823991.92024-05-10 20:46:50.0
2062017-021주택용304119.50.0304119.52024-05-10 20:46:50.0
2072017-013공공용9174.80.09174.82024-05-10 20:46:50.0
2082017-012업무용26647.50.026647.52024-05-10 20:46:50.0
2092017-011주택용354651.10.0354651.12024-05-10 20:46:50.0
2102016-123공공용8187.00.08187.02024-05-10 20:46:50.0
2112016-122업무용21565.89.821575.62024-05-10 20:46:50.0
2122016-121주택용303310.20.0303310.22024-05-10 20:46:50.0