Overview

Dataset statistics

Number of variables10
Number of observations82
Missing cells52
Missing cells (%)6.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.9 KiB
Average record size in memory86.6 B

Variable types

Categorical1
DateTime4
Numeric5

Dataset

Description한국지역난방공사 열원별 무재해 현황자료(지사, 무재해 개시일, 목표 예정일, 목표배수, 목표일수, 달성목표일수, 경과일수, 최근달성배수, 최근배수 달성일)
URLhttps://www.data.go.kr/data/15069256/fileData.do

Alerts

목표배수 is highly overall correlated with 목표일수 and 4 other fieldsHigh correlation
목표일수 is highly overall correlated with 목표배수 and 2 other fieldsHigh correlation
달성목표일수 is highly overall correlated with 목표배수 and 3 other fieldsHigh correlation
경과일수 is highly overall correlated with 목표배수 and 3 other fieldsHigh correlation
최근달성배수 is highly overall correlated with 목표배수 and 4 other fieldsHigh correlation
지사 is highly overall correlated with 목표배수 and 4 other fieldsHigh correlation
목표일수 has 16 (19.5%) missing valuesMissing
달성목표일수 has 16 (19.5%) missing valuesMissing
경과일수 has 16 (19.5%) missing valuesMissing
최근달성배수 has 2 (2.4%) missing valuesMissing
최근배수 달성일 has 2 (2.4%) missing valuesMissing
최근달성배수 has 3 (3.7%) zerosZeros

Reproduction

Analysis started2023-12-12 18:55:15.473699
Analysis finished2023-12-12 18:55:20.344023
Duration4.87 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지사
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Memory size788.0 B
청주지사
 
5
파주지사
 
5
세종지사
 
5
김해사업소
 
5
화성지사
 
5
Other values (13)
57 

Length

Max length6
Median length4
Mean length4.304878
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row동탄지사
2nd row동탄지사
3rd row동탄지사
4th row동탄지사
5th row중앙지사

Common Values

ValueCountFrequency (%)
청주지사 5
 
6.1%
파주지사 5
 
6.1%
세종지사 5
 
6.1%
김해사업소 5
 
6.1%
화성지사 5
 
6.1%
중앙지사 5
 
6.1%
삼송지사 5
 
6.1%
광교지사 5
 
6.1%
대구지사 5
 
6.1%
강남지사 5
 
6.1%
Other values (8) 32
39.0%

Length

2023-12-13T03:55:20.485564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
청주지사 5
 
6.1%
삼송지사 5
 
6.1%
파주지사 5
 
6.1%
대구지사 5
 
6.1%
광교지사 5
 
6.1%
강남지사 5
 
6.1%
중앙지사 5
 
6.1%
화성지사 5
 
6.1%
김해사업소 5
 
6.1%
세종지사 5
 
6.1%
Other values (8) 32
39.0%

무재해 개시일
Date

Distinct17
Distinct (%)20.7%
Missing0
Missing (%)0.0%
Memory size788.0 B
Minimum1999-01-01 00:00:00
Maximum2021-10-14 00:00:00
2023-12-13T03:55:20.699364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:55:20.908836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)

현황기준일
Date

Distinct5
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size788.0 B
Minimum2014-12-31 00:00:00
Maximum2022-06-21 00:00:00
2023-12-13T03:55:21.673651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:55:21.829583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)

목표 예정일
Date

Distinct40
Distinct (%)48.8%
Missing0
Missing (%)0.0%
Memory size788.0 B
Minimum2015-01-06 00:00:00
Maximum2030-07-01 00:00:00
2023-12-13T03:55:22.008955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:55:22.231662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)

목표배수
Real number (ℝ)

HIGH CORRELATION 

Distinct7
Distinct (%)8.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.634146
Minimum1
Maximum20
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-12-13T03:55:22.407806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.05
Q15
median10
Q315
95-th percentile20
Maximum20
Range19
Interquartile range (IQR)10

Descriptive statistics

Standard deviation6.6155675
Coefficient of variation (CV)0.62210612
Kurtosis-1.414249
Mean10.634146
Median Absolute Deviation (MAD)5
Skewness0.094967817
Sum872
Variance43.765733
MonotonicityNot monotonic
2023-12-13T03:55:22.631677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
15 18
22.0%
20 17
20.7%
10 15
18.3%
5 15
18.3%
3 8
9.8%
1 5
 
6.1%
2 4
 
4.9%
ValueCountFrequency (%)
1 5
 
6.1%
2 4
 
4.9%
3 8
9.8%
5 15
18.3%
10 15
18.3%
15 18
22.0%
20 17
20.7%
ValueCountFrequency (%)
20 17
20.7%
15 18
22.0%
10 15
18.3%
5 15
18.3%
3 8
9.8%
2 4
 
4.9%
1 5
 
6.1%

목표일수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct8
Distinct (%)12.1%
Missing16
Missing (%)19.5%
Infinite0
Infinite (%)0.0%
Mean2521.6061
Minimum546
Maximum3120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-12-13T03:55:22.853151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum546
5-th percentile1053
Q12730
median2730
Q32730
95-th percentile3120
Maximum3120
Range2574
Interquartile range (IQR)0

Descriptive statistics

Standard deviation613.36762
Coefficient of variation (CV)0.24324482
Kurtosis3.9297703
Mean2521.6061
Median Absolute Deviation (MAD)0
Skewness-2.1760213
Sum166426
Variance376219.84
MonotonicityNot monotonic
2023-12-13T03:55:23.058489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
2730 46
56.1%
3120 6
 
7.3%
2600 4
 
4.9%
1560 3
 
3.7%
546 3
 
3.7%
1638 2
 
2.4%
1040 1
 
1.2%
1092 1
 
1.2%
(Missing) 16
 
19.5%
ValueCountFrequency (%)
546 3
 
3.7%
1040 1
 
1.2%
1092 1
 
1.2%
1560 3
 
3.7%
1638 2
 
2.4%
2600 4
 
4.9%
2730 46
56.1%
3120 6
 
7.3%
ValueCountFrequency (%)
3120 6
 
7.3%
2730 46
56.1%
2600 4
 
4.9%
1638 2
 
2.4%
1560 3
 
3.7%
1092 1
 
1.2%
1040 1
 
1.2%
546 3
 
3.7%

달성목표일수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct16
Distinct (%)24.2%
Missing16
Missing (%)19.5%
Infinite0
Infinite (%)0.0%
Mean5399.0606
Minimum546
Maximum9660
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-12-13T03:55:23.273400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum546
5-th percentile1189.5
Q14368
median5460
Q36240
95-th percentile9595
Maximum9660
Range9114
Interquartile range (IQR)1872

Descriptive statistics

Standard deviation2333.3494
Coefficient of variation (CV)0.43217692
Kurtosis-0.09245468
Mean5399.0606
Median Absolute Deviation (MAD)1092
Skewness0.034255519
Sum356338
Variance5444519.4
MonotonicityNot monotonic
2023-12-13T03:55:23.595342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
5460 19
23.2%
4368 14
17.1%
8190 4
 
4.9%
9660 4
 
4.9%
9400 4
 
4.9%
546 3
 
3.7%
2600 3
 
3.7%
6240 2
 
2.4%
7320 2
 
2.4%
5082 2
 
2.4%
Other values (6) 9
11.0%
(Missing) 16
19.5%
ValueCountFrequency (%)
546 3
 
3.7%
1040 1
 
1.2%
1638 2
 
2.4%
2600 3
 
3.7%
2730 2
 
2.4%
4368 14
17.1%
5082 2
 
2.4%
5460 19
23.2%
5850 2
 
2.4%
6240 2
 
2.4%
ValueCountFrequency (%)
9660 4
 
4.9%
9400 4
 
4.9%
8190 4
 
4.9%
7320 2
 
2.4%
7319 1
 
1.2%
6929 1
 
1.2%
6240 2
 
2.4%
5850 2
 
2.4%
5460 19
23.2%
5082 2
 
2.4%

경과일수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct59
Distinct (%)89.4%
Missing16
Missing (%)19.5%
Infinite0
Infinite (%)0.0%
Mean4589.2424
Minimum137
Maximum8573
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-12-13T03:55:23.842265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum137
5-th percentile644.75
Q12634
median3906
Q37371.25
95-th percentile8373.5
Maximum8573
Range8436
Interquartile range (IQR)4737.25

Descriptive statistics

Standard deviation2576.9746
Coefficient of variation (CV)0.56152505
Kurtosis-1.3400434
Mean4589.2424
Median Absolute Deviation (MAD)2321
Skewness0.092845644
Sum302890
Variance6640797.9
MonotonicityNot monotonic
2023-12-13T03:55:24.166270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8573 2
 
2.4%
8459 2
 
2.4%
8036 2
 
2.4%
7495 2
 
2.4%
7509 2
 
2.4%
7395 2
 
2.4%
6431 2
 
2.4%
3533 1
 
1.2%
3856 1
 
1.2%
2992 1
 
1.2%
Other values (49) 49
59.8%
(Missing) 16
 
19.5%
ValueCountFrequency (%)
137 1
1.2%
251 1
1.2%
346 1
1.2%
564 1
1.2%
887 1
1.2%
1105 1
1.2%
1316 1
1.2%
1528 1
1.2%
1642 1
1.2%
1857 1
1.2%
ValueCountFrequency (%)
8573 2
2.4%
8459 2
2.4%
8117 1
1.2%
8036 2
2.4%
8003 1
1.2%
7903 1
1.2%
7789 1
1.2%
7509 2
2.4%
7495 2
2.4%
7395 2
2.4%

최근달성배수
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct7
Distinct (%)8.8%
Missing2
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean7.1875
Minimum0
Maximum15
Zeros3
Zeros (%)3.7%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-12-13T03:55:24.467227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13
median5
Q310
95-th percentile15
Maximum15
Range15
Interquartile range (IQR)7

Descriptive statistics

Standard deviation5.0793545
Coefficient of variation (CV)0.7066928
Kurtosis-1.28978
Mean7.1875
Median Absolute Deviation (MAD)4
Skewness0.40321465
Sum575
Variance25.799842
MonotonicityNot monotonic
2023-12-13T03:55:24.737104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
10 18
22.0%
15 17
20.7%
5 15
18.3%
3 15
18.3%
2 8
9.8%
1 4
 
4.9%
0 3
 
3.7%
(Missing) 2
 
2.4%
ValueCountFrequency (%)
0 3
 
3.7%
1 4
 
4.9%
2 8
9.8%
3 15
18.3%
5 15
18.3%
10 18
22.0%
15 17
20.7%
ValueCountFrequency (%)
15 17
20.7%
10 18
22.0%
5 15
18.3%
3 15
18.3%
2 8
9.8%
1 4
 
4.9%
0 3
 
3.7%

최근배수 달성일
Date

MISSING 

Distinct34
Distinct (%)42.5%
Missing2
Missing (%)2.4%
Memory size788.0 B
Minimum2010-07-01 00:00:00
Maximum2021-12-14 00:00:00
2023-12-13T03:55:25.050096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:55:25.389311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)

Interactions

2023-12-13T03:55:18.955774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:55:15.969311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:55:16.785707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:55:17.546811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:55:18.319452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:55:19.103240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:55:16.158530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:55:16.955878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:55:17.704520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:55:18.466796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:55:19.248044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:55:16.341862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:55:17.104046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:55:17.870352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:55:18.606237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:55:19.405781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:55:16.484079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:55:17.257710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:55:18.021406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:55:18.724227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:55:19.548957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:55:16.617582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:55:17.389915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:55:18.157290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:55:18.832653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T03:55:25.624796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지사무재해 개시일현황기준일목표 예정일목표배수목표일수달성목표일수경과일수최근달성배수최근배수 달성일
지사1.0000.9960.0000.9950.9050.9270.9610.8530.9180.994
무재해 개시일0.9961.0000.0000.9990.8550.8890.9060.8560.8691.000
현황기준일0.0000.0001.0000.0000.1990.0000.0000.1320.1670.000
목표 예정일0.9950.9990.0001.0001.0000.9960.9920.9471.0001.000
목표배수0.9050.8550.1991.0001.0000.8040.9420.9211.0001.000
목표일수0.9270.8890.0000.9960.8041.0000.8670.7890.8040.996
달성목표일수0.9610.9060.0000.9920.9420.8671.0000.7870.9420.990
경과일수0.8530.8560.1320.9470.9210.7890.7871.0000.9210.948
최근달성배수0.9180.8690.1671.0001.0000.8040.9420.9211.0001.000
최근배수 달성일0.9941.0000.0001.0001.0000.9960.9900.9481.0001.000
2023-12-13T03:55:25.902416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
목표배수목표일수달성목표일수경과일수최근달성배수지사
목표배수1.0000.5090.9110.9361.0000.557
목표일수0.5091.0000.4660.4580.5090.607
달성목표일수0.9110.4661.0000.8890.9110.642
경과일수0.9360.4580.8891.0000.9360.508
최근달성배수1.0000.5090.9110.9361.0000.618
지사0.5570.6070.6420.5080.6181.000

Missing values

2023-12-13T03:55:19.756376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:55:19.996007image/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.
2023-12-13T03:55:20.212363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

지사무재해 개시일현황기준일목표 예정일목표배수목표일수달성목표일수경과일수최근달성배수최근배수 달성일
0동탄지사2017-12-232022-06-212025-02-04315602600164222020-10-27
1동탄지사2017-12-232022-02-282025-02-04315602600152822020-10-27
2동탄지사2017-12-232021-12-312025-02-04315602600110522020-10-27
3동탄지사2017-12-232019-05-262020-10-2721040104056412019-05-26
4중앙지사1999-01-012022-06-212025-06-1320273096608573152017-12-21
5중앙지사1999-01-012022-02-282025-06-1320273096608459152017-12-21
6중앙지사1999-01-012021-12-312025-06-1320273096608036152017-12-21
7중앙지사1999-01-012019-05-262025-06-1320273096607495152017-12-21
8중앙지사1999-01-012014-12-312017-12-2115<NA><NA><NA>102010-07-01
9강남지사1999-01-012022-06-212024-09-2520260094008573152017-08-13
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