Overview

Dataset statistics

Number of variables8
Number of observations438
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory30.5 KiB
Average record size in memory71.3 B

Variable types

Numeric6
Categorical1
Text1

Dataset

Description고유번호,기준연도,행정동코드,행정동명,2005년사용량,2006년사용량,X 좌표,Y 좌표
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-323/S/1/datasetView.do

Alerts

기준연도 has constant value ""Constant
고유번호 is highly overall correlated with 행정동코드 and 1 other fieldsHigh correlation
행정동코드 is highly overall correlated with 고유번호 and 1 other fieldsHigh correlation
2005년사용량 is highly overall correlated with 2006년사용량High correlation
2006년사용량 is highly overall correlated with 2005년사용량High correlation
Y 좌표 is highly overall correlated with 고유번호 and 1 other fieldsHigh correlation
고유번호 has unique valuesUnique
행정동코드 has unique valuesUnique
X 좌표 has unique valuesUnique
Y 좌표 has unique valuesUnique

Reproduction

Analysis started2023-12-11 09:56:44.284261
Analysis finished2023-12-11 09:56:48.760091
Duration4.48 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

고유번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct438
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean219.5
Minimum1
Maximum438
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2023-12-11T18:56:48.838449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile22.85
Q1110.25
median219.5
Q3328.75
95-th percentile416.15
Maximum438
Range437
Interquartile range (IQR)218.5

Descriptive statistics

Standard deviation126.58396
Coefficient of variation (CV)0.57669232
Kurtosis-1.2
Mean219.5
Median Absolute Deviation (MAD)109.5
Skewness0
Sum96141
Variance16023.5
MonotonicityNot monotonic
2023-12-11T18:56:48.987522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
55 1
 
0.2%
320 1
 
0.2%
341 1
 
0.2%
331 1
 
0.2%
323 1
 
0.2%
353 1
 
0.2%
312 1
 
0.2%
315 1
 
0.2%
270 1
 
0.2%
269 1
 
0.2%
Other values (428) 428
97.7%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
438 1
0.2%
437 1
0.2%
436 1
0.2%
435 1
0.2%
434 1
0.2%
433 1
0.2%
432 1
0.2%
431 1
0.2%
430 1
0.2%
429 1
0.2%

기준연도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
2008
438 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2008
2nd row2008
3rd row2008
4th row2008
5th row2008

Common Values

ValueCountFrequency (%)
2008 438
100.0%

Length

2023-12-11T18:56:49.102776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T18:56:49.195392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2008 438
100.0%

행정동코드
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct438
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1113545.7
Minimum1101053
Maximum1125074
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2023-12-11T18:56:49.324241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1101053
5-th percentile1102057.9
Q11107061.2
median1114060.5
Q31120072.8
95-th percentile1124075.3
Maximum1125074
Range24021
Interquartile range (IQR)13011.5

Descriptive statistics

Standard deviation7427.8897
Coefficient of variation (CV)0.0066704851
Kurtosis-1.2748023
Mean1113545.7
Median Absolute Deviation (MAD)6996
Skewness-0.052988859
Sum4.87733 × 108
Variance55173546
MonotonicityNot monotonic
2023-12-11T18:56:49.487545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1104066 1
 
0.2%
1120055 1
 
0.2%
1121066 1
 
0.2%
1120063 1
 
0.2%
1118058 1
 
0.2%
1122052 1
 
0.2%
1119072 1
 
0.2%
1119075 1
 
0.2%
1116067 1
 
0.2%
1114072 1
 
0.2%
Other values (428) 428
97.7%
ValueCountFrequency (%)
1101053 1
0.2%
1101054 1
0.2%
1101055 1
0.2%
1101056 1
0.2%
1101057 1
0.2%
1101058 1
0.2%
1101060 1
0.2%
1101061 1
0.2%
1101063 1
0.2%
1101064 1
0.2%
ValueCountFrequency (%)
1125074 1
0.2%
1125073 1
0.2%
1125072 1
0.2%
1125071 1
0.2%
1125070 1
0.2%
1125067 1
0.2%
1125066 1
0.2%
1125065 1
0.2%
1125063 1
0.2%
1125061 1
0.2%

행정동명
Text

Distinct437
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
2023-12-11T18:56:49.846064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length4
Mean length3.8287671
Min length2

Characters and Unicode

Total characters1677
Distinct characters187
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique436 ?
Unique (%)99.5%

Sample

1st row성수1가2동
2nd row창신2동
3rd row회현동
4th row자양3동
5th row행당1동
ValueCountFrequency (%)
신사동 2
 
0.5%
가산동 1
 
0.2%
사당1동 1
 
0.2%
시흥2동 1
 
0.2%
서초2동 1
 
0.2%
대림3동 1
 
0.2%
도림동 1
 
0.2%
발산1동 1
 
0.2%
성산1동 1
 
0.2%
가리봉동 1
 
0.2%
Other values (427) 427
97.5%
2023-12-11T18:56:50.304842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 439
26.2%
1 101
 
6.0%
2 101
 
6.0%
3 52
 
3.1%
신 42
 
2.5%
4 30
 
1.8%
가 24
 
1.4%
계 19
 
1.1%
곡 18
 
1.1%
성 16
 
1.0%
Other values (177) 835
49.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1354
80.7%
Decimal Number 314
 
18.7%
Other Punctuation 9
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 439
32.4%
신 42
 
3.1%
가 24
 
1.8%
계 19
 
1.4%
곡 18
 
1.3%
성 16
 
1.2%
화 16
 
1.2%
정 16
 
1.2%
방 16
 
1.2%
상 16
 
1.2%
Other values (166) 732
54.1%
Decimal Number
ValueCountFrequency (%)
1 101
32.2%
2 101
32.2%
3 52
16.6%
4 30
 
9.6%
5 11
 
3.5%
6 8
 
2.5%
7 6
 
1.9%
8 3
 
1.0%
0 1
 
0.3%
9 1
 
0.3%
Other Punctuation
ValueCountFrequency (%)
. 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1354
80.7%
Common 323
 
19.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 439
32.4%
신 42
 
3.1%
가 24
 
1.8%
계 19
 
1.4%
곡 18
 
1.3%
성 16
 
1.2%
화 16
 
1.2%
정 16
 
1.2%
방 16
 
1.2%
상 16
 
1.2%
Other values (166) 732
54.1%
Common
ValueCountFrequency (%)
1 101
31.3%
2 101
31.3%
3 52
16.1%
4 30
 
9.3%
5 11
 
3.4%
. 9
 
2.8%
6 8
 
2.5%
7 6
 
1.9%
8 3
 
0.9%
0 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1354
80.7%
ASCII 323
 
19.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 439
32.4%
신 42
 
3.1%
가 24
 
1.8%
계 19
 
1.4%
곡 18
 
1.3%
성 16
 
1.2%
화 16
 
1.2%
정 16
 
1.2%
방 16
 
1.2%
상 16
 
1.2%
Other values (166) 732
54.1%
ASCII
ValueCountFrequency (%)
1 101
31.3%
2 101
31.3%
3 52
16.1%
4 30
 
9.3%
5 11
 
3.4%
. 9
 
2.8%
6 8
 
2.5%
7 6
 
1.9%
8 3
 
0.9%
0 1
 
0.3%

2005년사용량
Real number (ℝ)

HIGH CORRELATION 

Distinct437
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3037.3943
Minimum195.699
Maximum12229.231
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2023-12-11T18:56:50.525967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum195.699
5-th percentile1376.4597
Q12240.8293
median2853.7995
Q33656.1688
95-th percentile5363.1867
Maximum12229.231
Range12033.532
Interquartile range (IQR)1415.3395

Descriptive statistics

Standard deviation1314.3355
Coefficient of variation (CV)0.4327181
Kurtosis6.5387581
Mean3037.3943
Median Absolute Deviation (MAD)701.9715
Skewness1.6129735
Sum1330378.7
Variance1727477.8
MonotonicityNot monotonic
2023-12-11T18:56:50.668298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2848.357 2
 
0.5%
2429.858 1
 
0.2%
2954.55 1
 
0.2%
2956.236 1
 
0.2%
2156.933 1
 
0.2%
3955.001 1
 
0.2%
4050.706 1
 
0.2%
2111.056 1
 
0.2%
2160.748 1
 
0.2%
2803.076 1
 
0.2%
Other values (427) 427
97.5%
ValueCountFrequency (%)
195.699 1
0.2%
443.816 1
0.2%
597.968 1
0.2%
602.259 1
0.2%
670.722 1
0.2%
701.065 1
0.2%
702.162 1
0.2%
898.988 1
0.2%
1031.067 1
0.2%
1077.191 1
0.2%
ValueCountFrequency (%)
12229.231 1
0.2%
8664.508 1
0.2%
8028.832 1
0.2%
7587.432 1
0.2%
7381.551 1
0.2%
7316.592 1
0.2%
7019.27 1
0.2%
6877.485 1
0.2%
6471.145 1
0.2%
6250.918 1
0.2%

2006년사용량
Real number (ℝ)

HIGH CORRELATION 

Distinct437
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3031.3256
Minimum107.722
Maximum12380.618
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2023-12-11T18:56:50.838558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum107.722
5-th percentile1345.013
Q12214.7195
median2837.5545
Q33663.9597
95-th percentile5354.0804
Maximum12380.618
Range12272.896
Interquartile range (IQR)1449.2403

Descriptive statistics

Standard deviation1325.2546
Coefficient of variation (CV)0.43718649
Kurtosis6.7620194
Mean3031.3256
Median Absolute Deviation (MAD)712.9085
Skewness1.6299965
Sum1327720.6
Variance1756299.8
MonotonicityNot monotonic
2023-12-11T18:56:50.976456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2814.014 2
 
0.5%
2370.667 1
 
0.2%
3027.88 1
 
0.2%
2941.452 1
 
0.2%
2161.771 1
 
0.2%
4091.877 1
 
0.2%
3961.839 1
 
0.2%
2122.224 1
 
0.2%
2190.7 1
 
0.2%
2809.276 1
 
0.2%
Other values (427) 427
97.5%
ValueCountFrequency (%)
107.722 1
0.2%
424.463 1
0.2%
571.511 1
0.2%
616.414 1
0.2%
633.343 1
0.2%
672.904 1
0.2%
725.012 1
0.2%
904.084 1
0.2%
928.069 1
0.2%
1006.103 1
0.2%
ValueCountFrequency (%)
12380.618 1
0.2%
8841.838 1
0.2%
7817.496 1
0.2%
7694.399 1
0.2%
7517.131 1
0.2%
7307.985 1
0.2%
7066.892 1
0.2%
6848.068 1
0.2%
6449.422 1
0.2%
6395.768 1
0.2%

X 좌표
Real number (ℝ)

UNIQUE 

Distinct438
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean199615.65
Minimum181863.61
Maximum215247.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2023-12-11T18:56:51.141974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum181863.61
5-th percentile186582.34
Q1193301.75
median200928.42
Q3205491.4
95-th percentile211311.35
Maximum215247.6
Range33383.994
Interquartile range (IQR)12189.656

Descriptive statistics

Standard deviation7515.4609
Coefficient of variation (CV)0.037649658
Kurtosis-0.84397398
Mean199615.65
Median Absolute Deviation (MAD)5611.313
Skewness-0.20514805
Sum87431654
Variance56482152
MonotonicityNot monotonic
2023-12-11T18:56:51.291530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
203702.617 1
 
0.2%
194251.717 1
 
0.2%
194525.99 1
 
0.2%
197890.478 1
 
0.2%
192968.314 1
 
0.2%
202461.729 1
 
0.2%
191028.681 1
 
0.2%
191304.339 1
 
0.2%
184607.027 1
 
0.2%
192119.502 1
 
0.2%
Other values (428) 428
97.7%
ValueCountFrequency (%)
181863.605 1
0.2%
182826.453 1
0.2%
183479.251 1
0.2%
183694.055 1
0.2%
184558.927 1
0.2%
184607.027 1
0.2%
184818.062 1
0.2%
184974.596 1
0.2%
185086.826 1
0.2%
185371.643 1
0.2%
ValueCountFrequency (%)
215247.599 1
0.2%
214585.692 1
0.2%
214335.251 1
0.2%
213768.099 1
0.2%
213665.901 1
0.2%
213409.003 1
0.2%
213176.714 1
0.2%
213171.669 1
0.2%
213127.875 1
0.2%
213023.986 1
0.2%

Y 좌표
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct438
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean450117.74
Minimum437916.66
Maximum465070.19
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2023-12-11T18:56:51.425101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum437916.66
5-th percentile441670.65
Q1445271.95
median450016.76
Q3453913.19
95-th percentile460794.65
Maximum465070.19
Range27153.533
Interquartile range (IQR)8641.2373

Descriptive statistics

Standard deviation5850.6624
Coefficient of variation (CV)0.012998071
Kurtosis-0.55467903
Mean450117.74
Median Absolute Deviation (MAD)4332.767
Skewness0.32397248
Sum1.9715157 × 108
Variance34230250
MonotonicityNot monotonic
2023-12-11T18:56:51.567945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
449912.407 1
 
0.2%
444227.442 1
 
0.2%
441596.917 1
 
0.2%
442327.237 1
 
0.2%
439034.702 1
 
0.2%
443293.446 1
 
0.2%
444520.256 1
 
0.2%
445500.911 1
 
0.2%
450101.154 1
 
0.2%
451429.174 1
 
0.2%
Other values (428) 428
97.7%
ValueCountFrequency (%)
437916.657 1
0.2%
438847.03 1
0.2%
439034.702 1
0.2%
439211.042 1
0.2%
439328.644 1
0.2%
439411.965 1
0.2%
439440.063 1
0.2%
440019.112 1
0.2%
440227.137 1
0.2%
440254.738 1
0.2%
ValueCountFrequency (%)
465070.19 1
0.2%
464874.245 1
0.2%
464652.49 1
0.2%
464065.786 1
0.2%
463217.382 1
0.2%
463107.98 1
0.2%
462951.716 1
0.2%
462834.562 1
0.2%
462635.878 1
0.2%
462552.518 1
0.2%

Interactions

2023-12-11T18:56:47.987882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:56:44.622283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:56:45.155874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:56:45.772691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:56:46.449510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:56:47.402870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:56:48.081579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:56:44.693523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:56:45.240633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:56:45.907574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:56:46.557066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:56:47.493663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:56:48.195686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:56:44.775720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:56:45.337880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:56:46.004372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:56:46.660349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:56:47.576473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:56:48.298160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:56:44.868892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:56:45.445084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:56:46.105274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:56:46.748819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:56:47.665341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:56:48.376666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:56:44.971382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:56:45.545107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:56:46.212302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:56:47.169401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:56:47.797495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:56:48.468632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:56:45.069696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:56:45.678265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:56:46.336600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:56:47.288329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:56:47.883643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T18:56:51.663032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
고유번호행정동코드2005년사용량2006년사용량X 좌표Y 좌표
고유번호1.0000.9490.3150.3130.8430.806
행정동코드0.9491.0000.3240.3030.8940.878
2005년사용량0.3150.3241.0000.9990.1260.231
2006년사용량0.3130.3030.9991.0000.1310.177
X 좌표0.8430.8940.1260.1311.0000.454
Y 좌표0.8060.8780.2310.1770.4541.000
2023-12-11T18:56:51.764326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
고유번호행정동코드2005년사용량2006년사용량X 좌표Y 좌표
고유번호1.0000.9790.2960.303-0.009-0.626
행정동코드0.9791.0000.3020.3070.009-0.630
2005년사용량0.2960.3021.0000.995-0.003-0.078
2006년사용량0.3030.3070.9951.000-0.017-0.084
X 좌표-0.0090.009-0.003-0.0171.0000.215
Y 좌표-0.626-0.630-0.078-0.0840.2151.000

Missing values

2023-12-11T18:56:48.585302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T18:56:48.714245image/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

고유번호기준연도행정동코드행정동명2005년사용량2006년사용량X 좌표Y 좌표
05520081104066성수1가2동2429.8582370.667203702.617449912.407
11220081101068창신2동1388.5721373.445200920.962452936.545
21820081102054회현동4952.5754838.064197965.536450859.005
34620081105066자양3동2976.8493051.446206296.331448042.291
45020081104056행당1동2396.1672365.388203101.577451136.531
55720081104068성수2가3동3234.3893249.287205174.84449557.35
65820081104069송정동1371.8171305.38205562.916450474.779
76420081105055중곡1동1987.7641982.025206869.179451378.271
86620081105057중곡3동2226.3032270.692207191.668452012.858
97420081105067자양4동3470.3783445.408205621.339448266.35
고유번호기준연도행정동코드행정동명2005년사용량2006년사용량X 좌표Y 좌표
42832120081120056상도4동3489.9033454.443194705.213444247.615
42936520081120070신대방2동3670.3643564.309193121.754443841.773
43043820081125074길동7019.277066.892213023.986448939.589
43141220081122068내곡동1302.5381379.414206165.612439211.042
43241620081123055압구정2동3082.513063.982203495.035447743.0
43341720081124070장지동2518.2422481.972212098.948442416.229
43441920081124077잠실6동2987.5873186.472208776.964446524.327
43542120081124079잠실2동443.816424.463207032.194446477.204
43642220081124080잠실3동3211.8242964.627208380.132446309.836
43742320081125051강일동195.699107.722215247.599451535.363