Overview

Dataset statistics

Number of variables6
Number of observations34
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 KiB
Average record size in memory56.9 B

Variable types

Numeric5
Text1

Dataset

Description전국 34개 도시가스사별 가스공급 현황 정보(수요자 수(개), 공급열량(MJ), 공급량(M3) 및 배관길이(m))를 제공하여 도시가스 업계 현황 파악이 가능하도록 하기 위한 데이터입니다.
Author한국가스안전공사
URLhttps://www.data.go.kr/data/15020493/fileData.do

Alerts

번호 is highly overall correlated with 수요자 수(개) and 3 other fieldsHigh correlation
수요자 수(개) is highly overall correlated with 번호 and 3 other fieldsHigh correlation
공급열량(천MJ) is highly overall correlated with 번호 and 3 other fieldsHigh correlation
공급량(천m3) is highly overall correlated with 번호 and 3 other fieldsHigh correlation
배관(m) is highly overall correlated with 번호 and 3 other fieldsHigh correlation
번호 has unique valuesUnique
도시가스사업자 has unique valuesUnique
수요자 수(개) has unique valuesUnique
공급열량(천MJ) has unique valuesUnique
공급량(천m3) has unique valuesUnique
배관(m) has unique valuesUnique

Reproduction

Analysis started2023-12-12 21:53:51.681358
Analysis finished2023-12-12 21:53:54.735622
Duration3.05 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.5
Minimum1
Maximum34
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-13T06:53:55.105860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.65
Q19.25
median17.5
Q325.75
95-th percentile32.35
Maximum34
Range33
Interquartile range (IQR)16.5

Descriptive statistics

Standard deviation9.9582462
Coefficient of variation (CV)0.56904264
Kurtosis-1.2
Mean17.5
Median Absolute Deviation (MAD)8.5
Skewness0
Sum595
Variance99.166667
MonotonicityStrictly increasing
2023-12-13T06:53:55.250143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
1 1
 
2.9%
27 1
 
2.9%
21 1
 
2.9%
22 1
 
2.9%
23 1
 
2.9%
24 1
 
2.9%
25 1
 
2.9%
26 1
 
2.9%
28 1
 
2.9%
19 1
 
2.9%
Other values (24) 24
70.6%
ValueCountFrequency (%)
1 1
2.9%
2 1
2.9%
3 1
2.9%
4 1
2.9%
5 1
2.9%
6 1
2.9%
7 1
2.9%
8 1
2.9%
9 1
2.9%
10 1
2.9%
ValueCountFrequency (%)
34 1
2.9%
33 1
2.9%
32 1
2.9%
31 1
2.9%
30 1
2.9%
29 1
2.9%
28 1
2.9%
27 1
2.9%
26 1
2.9%
25 1
2.9%

도시가스사업자
Text

UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size404.0 B
2023-12-13T06:53:55.483268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.6470588
Min length3

Characters and Unicode

Total characters124
Distinct characters58
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)100.0%

Sample

1st row코원ES
2nd row예스코
3rd row서 울
4th row귀뚜라미
5th row대 륜
ValueCountFrequency (%)
대 3
 
5.7%
성 2
 
3.8%
전 2
 
3.8%
서 2
 
3.8%
해 2
 
3.8%
경 2
 
3.8%
산 2
 
3.8%
남 2
 
3.8%
지에스이 1
 
1.9%
서라벌 1
 
1.9%
Other values (34) 34
64.2%
2023-12-13T06:53:55.817354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19
 
15.3%
E 5
 
4.0%
S 5
 
4.0%
남 4
 
3.2%
대 4
 
3.2%
참 4
 
3.2%
빛 4
 
3.2%
성 3
 
2.4%
원 3
 
2.4%
서 3
 
2.4%
Other values (48) 70
56.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 83
66.9%
Space Separator 19
 
15.3%
Uppercase Letter 18
 
14.5%
Open Punctuation 2
 
1.6%
Close Punctuation 2
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 4
 
4.8%
대 4
 
4.8%
참 4
 
4.8%
빛 4
 
4.8%
성 3
 
3.6%
원 3
 
3.6%
서 3
 
3.6%
영 3
 
3.6%
북 3
 
3.6%
전 3
 
3.6%
Other values (36) 49
59.0%
Uppercase Letter
ValueCountFrequency (%)
E 5
27.8%
S 5
27.8%
C 2
 
11.1%
J 1
 
5.6%
B 1
 
5.6%
Y 1
 
5.6%
T 1
 
5.6%
I 1
 
5.6%
N 1
 
5.6%
Space Separator
ValueCountFrequency (%)
19
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 83
66.9%
Common 23
 
18.5%
Latin 18
 
14.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 4
 
4.8%
대 4
 
4.8%
참 4
 
4.8%
빛 4
 
4.8%
성 3
 
3.6%
원 3
 
3.6%
서 3
 
3.6%
영 3
 
3.6%
북 3
 
3.6%
전 3
 
3.6%
Other values (36) 49
59.0%
Latin
ValueCountFrequency (%)
E 5
27.8%
S 5
27.8%
C 2
 
11.1%
J 1
 
5.6%
B 1
 
5.6%
Y 1
 
5.6%
T 1
 
5.6%
I 1
 
5.6%
N 1
 
5.6%
Common
ValueCountFrequency (%)
19
82.6%
( 2
 
8.7%
) 2
 
8.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 83
66.9%
ASCII 41
33.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19
46.3%
E 5
 
12.2%
S 5
 
12.2%
( 2
 
4.9%
) 2
 
4.9%
C 2
 
4.9%
J 1
 
2.4%
B 1
 
2.4%
Y 1
 
2.4%
T 1
 
2.4%
Other values (2) 2
 
4.9%
Hangul
ValueCountFrequency (%)
남 4
 
4.8%
대 4
 
4.8%
참 4
 
4.8%
빛 4
 
4.8%
성 3
 
3.6%
원 3
 
3.6%
서 3
 
3.6%
영 3
 
3.6%
북 3
 
3.6%
전 3
 
3.6%
Other values (36) 49
59.0%

수요자 수(개)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean614119.94
Minimum1649
Maximum3345898
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-13T06:53:55.990036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1649
5-th percentile43304.15
Q1129733.75
median263480
Q3799498.5
95-th percentile1944684.3
Maximum3345898
Range3344249
Interquartile range (IQR)669764.75

Descriptive statistics

Standard deviation758599.37
Coefficient of variation (CV)1.2352626
Kurtosis4.9755905
Mean614119.94
Median Absolute Deviation (MAD)198868.5
Skewness2.1356415
Sum20880078
Variance5.75473 × 1011
MonotonicityNot monotonic
2023-12-13T06:53:56.142806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
1572917 1
 
2.9%
105138 1
 
2.9%
195579 1
 
2.9%
391982 1
 
2.9%
126625 1
 
2.9%
128604 1
 
2.9%
152127 1
 
2.9%
178096 1
 
2.9%
307936 1
 
2.9%
82018 1
 
2.9%
Other values (24) 24
70.6%
ValueCountFrequency (%)
1649 1
2.9%
38461 1
2.9%
45912 1
2.9%
77356 1
2.9%
82018 1
2.9%
101803 1
2.9%
105138 1
2.9%
126625 1
2.9%
128604 1
2.9%
133123 1
2.9%
ValueCountFrequency (%)
3345898 1
2.9%
2621647 1
2.9%
1580166 1
2.9%
1572917 1
2.9%
1432652 1
2.9%
1210792 1
2.9%
972379 1
2.9%
883872 1
2.9%
807484 1
2.9%
775542 1
2.9%

공급열량(천MJ)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean745380.14
Minimum11622.324
Maximum4211995.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-13T06:53:56.292779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11622.324
5-th percentile34065.618
Q1189215.69
median467364.5
Q3950320.59
95-th percentile2161584.4
Maximum4211995.1
Range4200372.8
Interquartile range (IQR)761104.9

Descriptive statistics

Standard deviation847786.51
Coefficient of variation (CV)1.1373881
Kurtosis7.7029757
Mean745380.14
Median Absolute Deviation (MAD)339721
Skewness2.424347
Sum25342925
Variance7.1874197 × 1011
MonotonicityNot monotonic
2023-12-13T06:53:56.452835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
1668383.0 1
 
2.9%
333596.4782 1
 
2.9%
640105.0 1
 
2.9%
505556.0 1
 
2.9%
303510.5534 1
 
2.9%
194676.4065 1
 
2.9%
135097.0 1
 
2.9%
283922.0 1
 
2.9%
587281.6942 1
 
2.9%
154597.1889 1
 
2.9%
Other values (24) 24
70.6%
ValueCountFrequency (%)
11622.324 1
2.9%
33675.0 1
2.9%
34275.95 1
2.9%
89555.62 1
2.9%
135097.0 1
2.9%
154597.1889 1
2.9%
165723.5 1
2.9%
174458.0 1
2.9%
188999.0 1
2.9%
189865.7606 1
2.9%
ValueCountFrequency (%)
4211995.144 1
2.9%
2261464.247 1
2.9%
2107803.0 1
2.9%
1668383.0 1
2.9%
1439558.823 1
2.9%
1368587.709 1
2.9%
1124756.34 1
2.9%
1005284.0 1
2.9%
958212.6734 1
2.9%
926644.3519 1
2.9%

공급량(천m3)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean97793.843
Minimum1829.246
Maximum580994.06
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-13T06:53:56.588760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1829.246
5-th percentile5585.563
Q125462.324
median66040.5
Q3120445
95-th percentile277403.5
Maximum580994.06
Range579164.81
Interquartile range (IQR)94982.676

Descriptive statistics

Standard deviation115949.75
Coefficient of variation (CV)1.1856549
Kurtosis8.4256905
Mean97793.843
Median Absolute Deviation (MAD)48445.942
Skewness2.5417298
Sum3324990.7
Variance1.3444344 × 1010
MonotonicityNot monotonic
2023-12-13T06:53:56.717070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
260936.0 1
 
2.9%
27344.97458 1
 
2.9%
74154.0 1
 
2.9%
71911.0 1
 
2.9%
32694.48258 1
 
2.9%
25353.76515 1
 
2.9%
19743.0 1
 
2.9%
34967.0 1
 
2.9%
73997.09033 1
 
2.9%
13613.10971 1
 
2.9%
Other values (24) 24
70.6%
ValueCountFrequency (%)
1829.246 1
2.9%
5555.0 1
2.9%
5602.02 1
2.9%
12814.0 1
2.9%
13613.10971 1
2.9%
17293.11564 1
2.9%
17896.0 1
2.9%
19743.0 1
2.9%
25353.76515 1
2.9%
25788.0 1
2.9%
ValueCountFrequency (%)
580994.0593 1
2.9%
307986.0 1
2.9%
260936.0 1
2.9%
229953.0137 1
2.9%
199755.9627 1
2.9%
177120.0456 1
2.9%
168365.4806 1
2.9%
125470.0 1
2.9%
120723.0 1
2.9%
119611.0 1
2.9%

배관(m)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1508951.6
Minimum14276.7
Maximum6922111.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-13T06:53:56.891145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum14276.7
5-th percentile133435.95
Q1523442.81
median869023.1
Q32404845
95-th percentile3850954.2
Maximum6922111.8
Range6907835.1
Interquartile range (IQR)1881402.2

Descriptive statistics

Standard deviation1499927.4
Coefficient of variation (CV)0.99401956
Kurtosis4.0004259
Mean1508951.6
Median Absolute Deviation (MAD)614106.5
Skewness1.7903925
Sum51304355
Variance2.2497823 × 1012
MonotonicityNot monotonic
2023-12-13T06:53:57.062413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
3340545.0 1
 
2.9%
459503.3 1
 
2.9%
1006073.0 1
 
2.9%
1477697.0 1
 
2.9%
530381.4 1
 
2.9%
407907.0 1
 
2.9%
583847.1 1
 
2.9%
570257.0 1
 
2.9%
923092.2 1
 
2.9%
347574.75 1
 
2.9%
Other values (24) 24
70.6%
ValueCountFrequency (%)
14276.7 1
2.9%
95812.0 1
2.9%
153695.0 1
2.9%
249484.0 1
2.9%
347574.75 1
2.9%
402992.0 1
2.9%
407907.0 1
2.9%
459503.3 1
2.9%
522838.6 1
2.9%
525255.43 1
2.9%
ValueCountFrequency (%)
6922111.8 1
2.9%
4609824.0 1
2.9%
3442331.928 1
2.9%
3340545.0 1
2.9%
3081957.85 1
2.9%
2769646.0 1
2.9%
2520334.0 1
2.9%
2500031.0 1
2.9%
2491644.0 1
2.9%
2144448.0 1
2.9%

Interactions

2023-12-13T06:53:53.950770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:53:51.864172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:53:52.323353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:53:52.804049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:53:53.412318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:53:54.064042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:53:51.946224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:53:52.428537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:53:52.896916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:53:53.510782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:53:54.180153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:53:52.034111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:53:52.511583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:53:53.067683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:53:53.629779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:53:54.286031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:53:52.122872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:53:52.598645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:53:53.203299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:53:53.739004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:53:54.402952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:53:52.231900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:53:52.703693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:53:53.304227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:53:53.838901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:53:57.224955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호도시가스사업자수요자 수(개)공급열량(천MJ)공급량(천m3)배관(m)
번호1.0001.0000.5240.3650.0000.505
도시가스사업자1.0001.0001.0001.0001.0001.000
수요자 수(개)0.5241.0001.0000.9770.9700.967
공급열량(천MJ)0.3651.0000.9771.0000.9780.962
공급량(천m3)0.0001.0000.9700.9781.0000.960
배관(m)0.5051.0000.9670.9620.9601.000
2023-12-13T06:53:57.369182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호수요자 수(개)공급열량(천MJ)공급량(천m3)배관(m)
번호1.000-0.611-0.549-0.589-0.538
수요자 수(개)-0.6111.0000.9290.9400.974
공급열량(천MJ)-0.5490.9291.0000.9740.949
공급량(천m3)-0.5890.9400.9741.0000.956
배관(m)-0.5380.9740.9490.9561.000

Missing values

2023-12-13T06:53:54.555164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:53:54.694484image/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

번호도시가스사업자수요자 수(개)공급열량(천MJ)공급량(천m3)배관(m)
01코원ES15729171668383.0260936.03340545.0
12예스코14326521368587.709177120.04563442331.928
23서 울26216472107803.0307986.04609824.0
34귀뚜라미411113341166.060170.0586715.0
45대 륜972379958212.6734168365.48061809416.1
56삼천리33458984211995.144580994.05936922111.8
67인 천807484837200.091146.01605753.41
78부 산15801661439558.823199755.96272769646.0
89대 성12107921124756.34106009.3573081957.85
910해 양775542814539.0120723.02491644.0
번호도시가스사업자수요자 수(개)공급열량(천MJ)공급량(천m3)배관(m)
2425목 포152127135097.019743.0583847.1
2526전 남178096283922.034967.0570257.0
2627대 화105138333596.478227344.97458459503.3
2728영남ES(구미)307936587281.694273997.09033923092.2
2829영남ES(포항)219024429173.050867.0814954.0
2930대성청정101803174458.017896.0402992.0
3031서라벌133123211333.028639.0555925.0
3132경 남883872926644.351991609.2992520334.0
3233지에스이205542188999.025788.0732562.0
3334제 주4591234275.955602.02153695.0