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,2007년사용량,2008년사용량,X 좌표,Y 좌표
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-329/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
2007년사용량 is highly overall correlated with 2008년사용량High correlation
2008년사용량 is highly overall correlated with 2007년사용량High 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 09:21:24.184221
Analysis finished2023-12-11 09:21:28.769139
Duration4.58 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
2023-12-11T18:21:28.875855image/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
2023-12-11T18:21:29.015046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
46 1
 
0.2%
316 1
 
0.2%
269 1
 
0.2%
300 1
 
0.2%
299 1
 
0.2%
297 1
 
0.2%
295 1
 
0.2%
294 1
 
0.2%
292 1
 
0.2%
322 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

2023-12-11T18:21:29.149620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T18:21:29.303380image/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
2023-12-11T18:21:29.445336image/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
2023-12-11T18:21:29.590148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1105066 1
 
0.2%
1119076 1
 
0.2%
1114072 1
 
0.2%
1123060 1
 
0.2%
1123054 1
 
0.2%
1122062 1
 
0.2%
1121081 1
 
0.2%
1121065 1
 
0.2%
1117070 1
 
0.2%
1118057 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
2023-12-11T18:21:29.904334image/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 row자양3동
2nd row답십리1동
3rd row창신2동
4th row구의1동
5th row응봉동
ValueCountFrequency (%)
신사동 2
 
0.5%
서초1동 1
 
0.2%
양평2동 1
 
0.2%
대치1동 1
 
0.2%
압구정1동 1
 
0.2%
방배1동 1
 
0.2%
난곡동 1
 
0.2%
신원동 1
 
0.2%
가리봉동 1
 
0.2%
시흥1동 1
 
0.2%
Other values (427) 427
97.5%
2023-12-11T18:21:30.384427image/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%
화 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%
화 16
 
1.2%
성 16
 
1.2%
상 16
 
1.2%
정 16
 
1.2%
방 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%
화 16
 
1.2%
성 16
 
1.2%
상 16
 
1.2%
정 16
 
1.2%
방 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%
화 16
 
1.2%
성 16
 
1.2%
상 16
 
1.2%
정 16
 
1.2%
방 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%

2007년사용량
Real number (ℝ)

HIGH CORRELATION 

Distinct437
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean97.806861
Minimum7.689708
Maximum831.76975
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2023-12-11T18:21:30.535534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.689708
5-th percentile29.565866
Q150.59604
median68.728149
Q3105.82203
95-th percentile257.35967
Maximum831.76975
Range824.08005
Interquartile range (IQR)55.225989

Descriptive statistics

Standard deviation94.714691
Coefficient of variation (CV)0.96838493
Kurtosis19.452535
Mean97.806861
Median Absolute Deviation (MAD)22.90389
Skewness3.746478
Sum42839.405
Variance8970.8726
MonotonicityNot monotonic
2023-12-11T18:21:30.682498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
57.489527 2
 
0.5%
181.929695 1
 
0.2%
185.888596 1
 
0.2%
83.873355 1
 
0.2%
130.655621 1
 
0.2%
70.275494 1
 
0.2%
51.527064 1
 
0.2%
39.847821 1
 
0.2%
44.60397 1
 
0.2%
119.654957 1
 
0.2%
Other values (427) 427
97.5%
ValueCountFrequency (%)
7.689708 1
0.2%
8.222036 1
0.2%
12.637248 1
0.2%
13.391452 1
0.2%
13.518065 1
0.2%
14.357689 1
0.2%
16.753378 1
0.2%
17.042226 1
0.2%
18.183449 1
0.2%
20.814328 1
0.2%
ValueCountFrequency (%)
831.769753 1
0.2%
811.389233 1
0.2%
548.405825 1
0.2%
547.700436 1
0.2%
494.563072 1
0.2%
494.54089 1
0.2%
467.512156 1
0.2%
458.031508 1
0.2%
434.279556 1
0.2%
423.513379 1
0.2%

2008년사용량
Real number (ℝ)

HIGH CORRELATION 

Distinct437
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean100.37198
Minimum7.425011
Maximum862.38961
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2023-12-11T18:21:30.818604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.425011
5-th percentile30.730494
Q151.001925
median70.178257
Q3107.37879
95-th percentile267.52692
Maximum862.38961
Range854.9646
Interquartile range (IQR)56.376867

Descriptive statistics

Standard deviation97.057949
Coefficient of variation (CV)0.96698255
Kurtosis19.821936
Mean100.37198
Median Absolute Deviation (MAD)23.534489
Skewness3.7555051
Sum43962.925
Variance9420.2454
MonotonicityNot monotonic
2023-12-11T18:21:30.998111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
59.389609 2
 
0.5%
195.52611 1
 
0.2%
185.371236 1
 
0.2%
88.578803 1
 
0.2%
133.605558 1
 
0.2%
70.368563 1
 
0.2%
50.931373 1
 
0.2%
41.182472 1
 
0.2%
46.063641 1
 
0.2%
119.542269 1
 
0.2%
Other values (427) 427
97.5%
ValueCountFrequency (%)
7.425011 1
0.2%
8.429381 1
0.2%
14.025424 1
0.2%
14.903593 1
0.2%
15.349535 1
0.2%
16.982302 1
0.2%
17.382672 1
0.2%
17.516867 1
0.2%
19.178458 1
0.2%
21.459975 1
0.2%
ValueCountFrequency (%)
862.389607 1
0.2%
839.363475 1
0.2%
571.652817 1
0.2%
532.941004 1
0.2%
498.36079 1
0.2%
493.660601 1
0.2%
473.315272 1
0.2%
451.500206 1
0.2%
447.570895 1
0.2%
424.742285 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
2023-12-11T18:21:31.142528image/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
2023-12-11T18:21:31.283380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
206296.331 1
 
0.2%
190430.571 1
 
0.2%
192119.502 1
 
0.2%
205236.16 1
 
0.2%
203181.696 1
 
0.2%
199637.863 1
 
0.2%
192971.616 1
 
0.2%
193520.82 1
 
0.2%
190112.471 1
 
0.2%
191120.599 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
2023-12-11T18:21:31.424871image/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
2023-12-11T18:21:31.611301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
448042.291 1
 
0.2%
446242.902 1
 
0.2%
451429.174 1
 
0.2%
443760.327 1
 
0.2%
446188.395 1
 
0.2%
442845.689 1
 
0.2%
441212.867 1
 
0.2%
442191.517 1
 
0.2%
442613.672 1
 
0.2%
439328.644 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

2023-12-11T18:21:27.558242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:21:24.533519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:21:25.061986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:21:25.667989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:21:26.220472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:21:26.866233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:21:27.670090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:21:24.606895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:21:25.156859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:21:25.744017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:21:26.325851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:21:26.965425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:21:27.780614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:21:24.688355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:21:25.272482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:21:25.839770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:21:26.435833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:21:27.106791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:21:27.881505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:21:24.783967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:21:25.375918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:21:25.917589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:21:26.523238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:21:27.199922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:21:27.976854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:21:24.877239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:21:25.471204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:21:26.008161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:21:26.641500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:21:27.329556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:21:28.095680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:21:24.960991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:21:25.562593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:21:26.113726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:21:26.755432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:21:27.453773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T18:21:31.703415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
고유번호행정동코드2007년사용량2008년사용량X 좌표Y 좌표
고유번호1.0000.9490.1420.1370.8470.807
행정동코드0.9491.0000.0430.0000.8930.872
2007년사용량0.1420.0431.0000.9970.0000.000
2008년사용량0.1370.0000.9971.0000.0000.000
X 좌표0.8470.8930.0000.0001.0000.454
Y 좌표0.8070.8720.0000.0000.4541.000
2023-12-11T18:21:31.832921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
고유번호행정동코드2007년사용량2008년사용량X 좌표Y 좌표
고유번호1.0000.9790.1250.131-0.011-0.626
행정동코드0.9791.0000.1230.1300.011-0.629
2007년사용량0.1250.1231.0000.9970.012-0.148
2008년사용량0.1310.1300.9971.0000.012-0.154
X 좌표-0.0110.0110.0120.0121.0000.215
Y 좌표-0.626-0.629-0.148-0.1540.2151.000

Missing values

2023-12-11T18:21:28.252563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T18:21:28.709438image/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

고유번호기준연도행정동코드행정동명2007년사용량2008년사용량X 좌표Y 좌표
04620081105066자양3동181.929695195.52611206296.331448042.291
18020081106060답십리1동22.71127522.774185204828.138452466.809
21220081101068창신2동39.37118540.275563200920.962452936.545
34520081105060구의1동467.512156447.570895207597.569449054.352
45220081104058응봉동16.75337816.982302203056.58450117.053
55820081104069송정동30.94326632.125956205562.916450474.779
65920081104070용답동62.36044464.027549205120.555451313.517
76020081104071왕십리도선동90.0282286.348238202645.626451886.773
86820081105059능동40.65917141.626176207245.626450183.437
97820081106056전농1동34.33390133.884137204414.826452922.966
고유번호기준연도행정동코드행정동명2007년사용량2008년사용량X 좌표Y 좌표
42832320081118058시흥2동42.63093339.78739192968.314439034.702
42939120081124068문정1동53.52508855.243119208003.497444695.558
43041320081123051신사동57.48952759.389609201783.985447372.759
43142220081124080잠실3동188.013635214.449989208380.132446309.836
43242320081125051강일동12.63724815.349535215247.599451535.363
43342420081125052상일동65.7770466.072943214585.692450155.145
43442720081125056고덕2동40.61262641.410712214335.251451907.084
43542920081125059암사3동135.190887141.3095212230.801451450.658
43643020081125061천호1동62.42099666.6182212156.58449683.208
43743220081125066성내2동73.90453476.036348211294.978448323.149