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-334/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 07:33:50.162871
Analysis finished2023-12-11 07:33:55.445770
Duration5.28 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
2023-12-11T16:33:55.578245image/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
2023-12-11T16:33:55.730227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
55 1
 
0.2%
321 1
 
0.2%
384 1
 
0.2%
313 1
 
0.2%
306 1
 
0.2%
355 1
 
0.2%
299 1
 
0.2%
296 1
 
0.2%
295 1
 
0.2%
293 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

2023-12-11T16:33:55.856133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T16:33:55.962031image/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
2023-12-11T16:33:56.083552image/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
2023-12-11T16:33:56.256816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1104066 1
 
0.2%
1120055 1
 
0.2%
1123074 1
 
0.2%
1119071 1
 
0.2%
1124058 1
 
0.2%
1122055 1
 
0.2%
1123051 1
 
0.2%
1122054 1
 
0.2%
1121081 1
 
0.2%
1121054 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
2023-12-11T16:33:56.599797image/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%
오류1동 1
 
0.2%
상도2동 1
 
0.2%
대림2동 1
 
0.2%
방이2동 1
 
0.2%
잠원동 1
 
0.2%
서초4동 1
 
0.2%
난곡동 1
 
0.2%
청림동 1
 
0.2%
시흥4동 1
 
0.2%
Other values (427) 427
97.5%
2023-12-11T16:33:57.055491image/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%
방 16
 
1.2%
상 16
 
1.2%
정 16
 
1.2%
화 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%
9 1
 
0.3%
0 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%
방 16
 
1.2%
상 16
 
1.2%
정 16
 
1.2%
화 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%
9 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%
방 16
 
1.2%
상 16
 
1.2%
정 16
 
1.2%
화 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%
9 1
 
0.3%

2007년사용량
Real number (ℝ)

HIGH CORRELATION 

Distinct437
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.272784
Minimum0.105726
Maximum96.543881
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2023-12-11T16:33:57.233925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.105726
5-th percentile2.2810962
Q16.5731015
median8.9292195
Q312.411614
95-th percentile21.06466
Maximum96.543881
Range96.438155
Interquartile range (IQR)5.8385123

Descriptive statistics

Standard deviation7.9528354
Coefficient of variation (CV)0.77416551
Kurtosis46.755084
Mean10.272784
Median Absolute Deviation (MAD)2.8772371
Skewness5.3880508
Sum4499.4796
Variance63.247591
MonotonicityNot monotonic
2023-12-11T16:33:57.486597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9.726021 2
 
0.5%
7.726222 1
 
0.2%
10.780839 1
 
0.2%
8.011355 1
 
0.2%
14.959138 1
 
0.2%
8.668007 1
 
0.2%
9.206964 1
 
0.2%
11.28092 1
 
0.2%
9.135405 1
 
0.2%
9.66928483 1
 
0.2%
Other values (427) 427
97.5%
ValueCountFrequency (%)
0.105726 1
0.2%
0.41099 1
0.2%
0.469326 1
0.2%
0.54488 1
0.2%
0.944227 1
0.2%
0.962463 1
0.2%
1.117913 1
0.2%
1.16327 1
0.2%
1.171394 1
0.2%
1.237687 1
0.2%
ValueCountFrequency (%)
96.543881 1
0.2%
76.960833 1
0.2%
60.090084 1
0.2%
52.622083 1
0.2%
29.046991 1
0.2%
28.756018 1
0.2%
27.777639 1
0.2%
26.390219 1
0.2%
25.891209 1
0.2%
25.867369 1
0.2%

2008년사용량
Real number (ℝ)

HIGH CORRELATION 

Distinct437
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.394986
Minimum0.116264
Maximum102.61198
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2023-12-11T16:33:57.649025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.116264
5-th percentile2.3951543
Q16.5274815
median8.9874745
Q312.383406
95-th percentile21.377385
Maximum102.61198
Range102.49572
Interquartile range (IQR)5.855924

Descriptive statistics

Standard deviation8.3808803
Coefficient of variation (CV)0.80624257
Kurtosis57.31522
Mean10.394986
Median Absolute Deviation (MAD)2.802458
Skewness6.0566653
Sum4553.0039
Variance70.239155
MonotonicityNot monotonic
2023-12-11T16:33:57.833441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9.727387 2
 
0.5%
8.65027 1
 
0.2%
11.797069 1
 
0.2%
8.187848 1
 
0.2%
15.03456 1
 
0.2%
8.549712 1
 
0.2%
9.260281 1
 
0.2%
11.003274 1
 
0.2%
9.19833 1
 
0.2%
9.75467319 1
 
0.2%
Other values (427) 427
97.5%
ValueCountFrequency (%)
0.116264 1
0.2%
0.410427 1
0.2%
0.434542 1
0.2%
0.537682 1
0.2%
0.810669 1
0.2%
0.902703 1
0.2%
1.015512 1
0.2%
1.055612 1
0.2%
1.154264 1
0.2%
1.170693 1
0.2%
ValueCountFrequency (%)
102.61198 1
0.2%
93.720453 1
0.2%
59.307558 1
0.2%
36.221153 1
0.2%
32.57433 1
0.2%
29.750465 1
0.2%
28.173288 1
0.2%
28.041599 1
0.2%
27.556485 1
0.2%
26.96501 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
2023-12-11T16:33:58.027324image/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
2023-12-11T16:33:58.217948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
203702.617 1
 
0.2%
194705.213 1
 
0.2%
208979.314 1
 
0.2%
191028.681 1
 
0.2%
191569.02 1
 
0.2%
198881.227 1
 
0.2%
201783.985 1
 
0.2%
201770.899 1
 
0.2%
192971.616 1
 
0.2%
195695.918 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
2023-12-11T16:33:58.402495image/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
2023-12-11T16:33:58.565041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
449912.407 1
 
0.2%
444247.615 1
 
0.2%
442894.292 1
 
0.2%
444520.256 1
 
0.2%
445270.601 1
 
0.2%
445209.663 1
 
0.2%
447372.759 1
 
0.2%
444405.416 1
 
0.2%
441212.867 1
 
0.2%
442742.949 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

2023-12-11T16:33:54.369975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:33:50.538316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:33:51.231307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:33:52.006760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:33:52.774190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:33:53.583419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:33:54.459742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:33:50.633348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:33:51.353422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:33:52.130614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:33:52.891529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:33:53.717978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:33:54.556000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:33:50.753615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:33:51.468957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:33:52.245560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:33:53.028353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:33:53.844258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:33:54.650352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:33:50.881601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:33:51.602628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:33:52.372817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:33:53.174937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:33:53.969368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:33:55.035933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:33:50.993399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:33:51.714388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:33:52.502430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:33:53.326324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:33:54.092855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:33:55.132594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:33:51.122320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:33:51.858208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:33:52.663215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:33:53.457592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:33:54.251457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T16:33:58.676144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
고유번호행정동코드2007년사용량2008년사용량X 좌표Y 좌표
고유번호1.0000.9490.1650.1300.8440.810
행정동코드0.9491.0000.1190.1370.8760.865
2007년사용량0.1650.1191.0000.9610.0000.000
2008년사용량0.1300.1370.9611.0000.0820.000
X 좌표0.8440.8760.0000.0821.0000.454
Y 좌표0.8100.8650.0000.0000.4541.000
2023-12-11T16:33:58.809358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
고유번호행정동코드2007년사용량2008년사용량X 좌표Y 좌표
고유번호1.0000.9780.1680.128-0.012-0.627
행정동코드0.9781.0000.1470.1070.005-0.623
2007년사용량0.1680.1471.0000.972-0.140-0.093
2008년사용량0.1280.1070.9721.000-0.108-0.074
X 좌표-0.0120.005-0.140-0.1081.0000.215
Y 좌표-0.627-0.623-0.093-0.0740.2151.000

Missing values

2023-12-11T16:33:55.249559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T16:33:55.387687image/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
05520081104066성수1가2동7.7262228.65027203702.617449912.407
11220081101068창신2동4.2833164.548497200920.962452936.545
21820081102054회현동14.4410115.065532197965.536450859.005
34620081105066자양3동12.36734214.242936206296.331448042.291
45020081104056행당1동8.0239298.582296203101.577451136.531
55720081104068성수2가3동15.70542515.271613205174.84449557.35
65820081104069송정동5.4389864.931568205562.916450474.779
76420081105055중곡1동6.3331666.564086206869.179451378.271
86620081105057중곡3동8.4082958.61405207191.668452012.858
97420081105067자양4동2.0964781.880025205621.339448266.35
고유번호기준연도행정동코드행정동명2007년사용량2008년사용량X 좌표Y 좌표
42839520081124063석촌동15.18021614.91921210816.916445619.643
42943820081125074길동17.60003317.597098213023.986448939.589
43041720081124070장지동24.02331136.221153212098.948442416.229
43142220081124080잠실3동9.8165989.296283208380.132446309.836
43242320081125051강일동13.04174514.206382215247.599451535.363
43342520081125054명일2동4.7458914.439935213768.099449897.966
43442720081125056고덕2동8.1139098.241782214335.251451907.084
43542920081125059암사3동1.7815131.788522212230.801451450.658
43643020081125061천호1동10.21239910.259278212156.58449683.208
43743120081125063천호3동9.4367379.392293211849.088448880.5