Overview

Dataset statistics

Number of variables8
Number of observations288
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory19.0 KiB
Average record size in memory67.5 B

Variable types

DateTime2
Categorical5
Numeric1

Dataset

Description년월,지사코드,지사명,지역코드,지역명,열공급량,단위,작업일시
Author서울에너지공사
URLhttps://data.seoul.go.kr/dataList/OA-20443/S/1/datasetView.do

Alerts

단위 has constant value ""Constant
작업일시 has constant value ""Constant
지사코드 is highly overall correlated with 지사명 and 1 other fieldsHigh correlation
지사명 is highly overall correlated with 지사코드 and 1 other fieldsHigh correlation
지역명 is highly overall correlated with 지사코드 and 2 other fieldsHigh correlation
지역코드 is highly overall correlated with 지역명High correlation
열공급량 has unique valuesUnique

Reproduction

Analysis started2024-05-11 06:54:51.946009
Analysis finished2024-05-11 06:54:52.984339
Duration1.04 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년월
Date

Distinct72
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
Minimum2016-12-01 00:00:00
Maximum2022-11-01 00:00:00
2024-05-11T15:54:53.099790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:54:53.312775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

지사코드
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2
144 
1
144 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 144
50.0%
1 144
50.0%

Length

2024-05-11T15:54:53.560868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:54:53.720528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 144
50.0%
1 144
50.0%

지사명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
동부지사
144 
서부지사
144 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row동부지사
2nd row동부지사
3rd row서부지사
4th row서부지사
5th row동부지사

Common Values

ValueCountFrequency (%)
동부지사 144
50.0%
서부지사 144
50.0%

Length

2024-05-11T15:54:53.887573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:54:54.051517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
동부지사 144
50.0%
서부지사 144
50.0%

지역코드
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
1
144 
2
144 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 144
50.0%
2 144
50.0%

Length

2024-05-11T15:54:54.227155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:54:54.401835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 144
50.0%
2 144
50.0%

지역명
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
남단
72 
북단
72 
강서
72 
목동
72 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row남단
2nd row북단
3rd row강서
4th row목동
5th row북단

Common Values

ValueCountFrequency (%)
남단 72
25.0%
북단 72
25.0%
강서 72
25.0%
목동 72
25.0%

Length

2024-05-11T15:54:54.585882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:54:54.779716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남단 72
25.0%
북단 72
25.0%
강서 72
25.0%
목동 72
25.0%

열공급량
Real number (ℝ)

UNIQUE 

Distinct288
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40553.126
Minimum2743.26
Maximum135662.96
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-05-11T15:54:55.102846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2743.26
5-th percentile7439.759
Q114451.583
median32928.1
Q357738.445
95-th percentile109453.3
Maximum135662.96
Range132919.7
Interquartile range (IQR)43286.863

Descriptive statistics

Standard deviation31594.542
Coefficient of variation (CV)0.77909018
Kurtosis0.37190696
Mean40553.126
Median Absolute Deviation (MAD)20424.415
Skewness1.0446816
Sum11679300
Variance9.9821511 × 108
MonotonicityNot monotonic
2024-05-11T15:54:55.398416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36378.18 1
 
0.3%
34649.11 1
 
0.3%
13258.89 1
 
0.3%
34183.94 1
 
0.3%
56539.58 1
 
0.3%
7049.02 1
 
0.3%
26432.03 1
 
0.3%
49366.49 1
 
0.3%
61567.62 1
 
0.3%
106143.55 1
 
0.3%
Other values (278) 278
96.5%
ValueCountFrequency (%)
2743.26 1
0.3%
3559.11 1
0.3%
5192.54 1
0.3%
5924.28 1
0.3%
6203.38 1
0.3%
6233.99 1
0.3%
6322.96 1
0.3%
6522.89 1
0.3%
6855.56 1
0.3%
6866.56 1
0.3%
ValueCountFrequency (%)
135662.96 1
0.3%
134944.85 1
0.3%
131620.91 1
0.3%
128267.23 1
0.3%
123422.11 1
0.3%
123142.94 1
0.3%
119015.69 1
0.3%
116343.32 1
0.3%
114782.43 1
0.3%
114446.81 1
0.3%

단위
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
GCAL
288 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
GCAL 288
100.0%

Length

2024-05-11T15:54:55.686759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:54:55.916190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
gcal 288
100.0%

작업일시
Date

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
Minimum2024-05-03 20:36:49
Maximum2024-05-03 20:36:49
2024-05-11T15:54:56.152152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:54:56.391132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-05-11T15:54:52.340670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T15:54:56.530881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년월지사코드지사명지역코드지역명열공급량
년월1.0000.0000.0000.0000.0000.732
지사코드0.0001.0001.0000.0001.0000.591
지사명0.0001.0001.0000.0001.0000.591
지역코드0.0000.0000.0001.0001.0000.233
지역명0.0001.0001.0001.0001.0000.459
열공급량0.7320.5910.5910.2330.4591.000
2024-05-11T15:54:56.724389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지사코드지사명지역명지역코드
지사코드1.0000.9930.9960.000
지사명0.9931.0000.9960.000
지역명0.9960.9961.0000.996
지역코드0.0000.0000.9961.000
2024-05-11T15:54:56.899663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
열공급량지사코드지사명지역코드지역명
열공급량1.0000.4530.4530.1770.289
지사코드0.4531.0000.9930.0000.996
지사명0.4530.9931.0000.0000.996
지역코드0.1770.0000.0001.0000.996
지역명0.2890.9960.9960.9961.000

Missing values

2024-05-11T15:54:52.645736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T15:54:52.914123image/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

년월지사코드지사명지역코드지역명열공급량단위작업일시
02022-112동부지사1남단36378.18GCAL2024-05-03 20:36:49.0
12022-112동부지사2북단24775.0GCAL2024-05-03 20:36:49.0
22022-111서부지사2강서56091.48GCAL2024-05-03 20:36:49.0
32022-111서부지사1목동57722.28GCAL2024-05-03 20:36:49.0
42022-102동부지사2북단15532.42GCAL2024-05-03 20:36:49.0
52022-101서부지사2강서37019.86GCAL2024-05-03 20:36:49.0
62022-102동부지사1남단23212.96GCAL2024-05-03 20:36:49.0
72022-101서부지사1목동38220.75GCAL2024-05-03 20:36:49.0
82022-092동부지사2북단6203.38GCAL2024-05-03 20:36:49.0
92022-091서부지사2강서33531.65GCAL2024-05-03 20:36:49.0
년월지사코드지사명지역코드지역명열공급량단위작업일시
2782017-021서부지사2강서67860.32GCAL2024-05-03 20:36:49.0
2792017-022동부지사2북단48816.16GCAL2024-05-03 20:36:49.0
2802017-012동부지사2북단56794.89GCAL2024-05-03 20:36:49.0
2812017-011서부지사1목동114782.43GCAL2024-05-03 20:36:49.0
2822017-011서부지사2강서78930.72GCAL2024-05-03 20:36:49.0
2832017-012동부지사1남단64418.32GCAL2024-05-03 20:36:49.0
2842016-122동부지사1남단53038.79GCAL2024-05-03 20:36:49.0
2852016-121서부지사2강서67643.37GCAL2024-05-03 20:36:49.0
2862016-121서부지사1목동98927.99GCAL2024-05-03 20:36:49.0
2872016-122동부지사2북단46238.23GCAL2024-05-03 20:36:49.0