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-327/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 started2024-04-21 08:02:52.442137
Analysis finished2024-04-21 08:03:02.200717
Duration9.76 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
2024-04-21T17:03:02.332351image/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
2024-04-21T17:03:02.570584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
70 1
 
0.2%
290 1
 
0.2%
296 1
 
0.2%
295 1
 
0.2%
294 1
 
0.2%
293 1
 
0.2%
291 1
 
0.2%
382 1
 
0.2%
373 1
 
0.2%
364 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 size3.5 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

2024-04-21T17:03:02.788150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T17:03:02.952179image/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
2024-04-21T17:03:03.153068image/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
2024-04-21T17:03:03.427235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1105062 1
 
0.2%
1117068 1
 
0.2%
1122054 1
 
0.2%
1121081 1
 
0.2%
1121065 1
 
0.2%
1121061 1
 
0.2%
1117069 1
 
0.2%
1123072 1
 
0.2%
1123062 1
 
0.2%
1120069 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 size3.5 KiB
2024-04-21T17:03:04.579278image/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 row구의3동
2nd row창신2동
3rd row무악동
4th row자양3동
5th row전농1동
ValueCountFrequency (%)
신사동 2
 
0.5%
시흥4동 1
 
0.2%
오류1동 1
 
0.2%
난곡동 1
 
0.2%
신원동 1
 
0.2%
중앙동 1
 
0.2%
수궁동 1
 
0.2%
일원본동 1
 
0.2%
대치3동 1
 
0.2%
신대방1동 1
 
0.2%
Other values (427) 427
97.5%
2024-04-21T17:03:05.919064image/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%
방 16
 
1.2%
성 16
 
1.2%
상 16
 
1.2%
정 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%
화 16
 
1.2%
방 16
 
1.2%
성 16
 
1.2%
상 16
 
1.2%
정 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%
화 16
 
1.2%
방 16
 
1.2%
성 16
 
1.2%
상 16
 
1.2%
정 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%

2005년사용량
Real number (ℝ)

HIGH CORRELATION 

Distinct437
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean88.116144
Minimum7.021582
Maximum745.59215
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-04-21T17:03:06.160833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.021582
5-th percentile27.825696
Q145.13542
median61.319471
Q392.485717
95-th percentile237.73866
Maximum745.59215
Range738.57057
Interquartile range (IQR)47.350297

Descriptive statistics

Standard deviation86.159803
Coefficient of variation (CV)0.97779816
Kurtosis18.111776
Mean88.116144
Median Absolute Deviation (MAD)21.11911
Skewness3.6640708
Sum38594.871
Variance7423.5117
MonotonicityNot monotonic
2024-04-21T17:03:06.414053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
53.871981 2
 
0.5%
152.193076 1
 
0.2%
51.338002 1
 
0.2%
50.801434 1
 
0.2%
38.75203 1
 
0.2%
36.542143 1
 
0.2%
56.887105 1
 
0.2%
103.246562 1
 
0.2%
178.864892 1
 
0.2%
49.872045 1
 
0.2%
Other values (427) 427
97.5%
ValueCountFrequency (%)
7.021582 1
0.2%
9.793491 1
0.2%
10.162799 1
0.2%
14.611261 1
0.2%
15.01936 1
0.2%
15.551121 1
0.2%
15.761751 1
0.2%
17.612789 1
0.2%
17.878851 1
0.2%
19.210865 1
0.2%
ValueCountFrequency (%)
745.59215 1
0.2%
710.758701 1
0.2%
510.695359 1
0.2%
481.094198 1
0.2%
464.848832 1
0.2%
447.644492 1
0.2%
435.101217 1
0.2%
416.37423 1
0.2%
408.913542 1
0.2%
357.56073 1
0.2%

2006년사용량
Real number (ℝ)

HIGH CORRELATION 

Distinct437
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean92.136764
Minimum8.12449
Maximum785.55754
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-04-21T17:03:06.672580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8.12449
5-th percentile28.837305
Q147.760129
median63.823172
Q397.258358
95-th percentile247.60642
Maximum785.55754
Range777.43305
Interquartile range (IQR)49.498229

Descriptive statistics

Standard deviation89.972957
Coefficient of variation (CV)0.97651527
Kurtosis18.46165
Mean92.136764
Median Absolute Deviation (MAD)21.556883
Skewness3.6803716
Sum40355.903
Variance8095.133
MonotonicityNot monotonic
2024-04-21T17:03:06.948194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
56.153428 2
 
0.5%
157.496824 1
 
0.2%
55.788854 1
 
0.2%
51.340878 1
 
0.2%
38.663838 1
 
0.2%
41.288263 1
 
0.2%
58.02913 1
 
0.2%
106.48295 1
 
0.2%
189.047475 1
 
0.2%
52.94749 1
 
0.2%
Other values (427) 427
97.5%
ValueCountFrequency (%)
8.12449 1
0.2%
9.676906 1
0.2%
10.939988 1
0.2%
14.685397 1
0.2%
15.801553 1
0.2%
18.321737 1
0.2%
20.88436 1
0.2%
20.915793 1
0.2%
21.184328 1
0.2%
21.186319 1
0.2%
ValueCountFrequency (%)
785.557543 1
0.2%
750.761009 1
0.2%
526.338071 1
0.2%
487.605265 1
0.2%
468.130495 1
0.2%
461.263275 1
0.2%
457.54841 1
0.2%
436.947854 1
0.2%
432.249003 1
0.2%
396.668101 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
2024-04-21T17:03:07.203880image/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
2024-04-21T17:03:07.644205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
208497.268 1
 
0.2%
185378.999 1
 
0.2%
201770.899 1
 
0.2%
192971.616 1
 
0.2%
193520.82 1
 
0.2%
195695.918 1
 
0.2%
184558.927 1
 
0.2%
207425.076 1
 
0.2%
205845.671 1
 
0.2%
192006.103 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
2024-04-21T17:03:07.895825image/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
2024-04-21T17:03:08.148486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
448474.65 1
 
0.2%
442796.642 1
 
0.2%
444405.416 1
 
0.2%
441212.867 1
 
0.2%
442191.517 1
 
0.2%
442742.949 1
 
0.2%
444384.536 1
 
0.2%
442627.816 1
 
0.2%
444693.458 1
 
0.2%
443485.022 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

2024-04-21T17:03:00.769006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T17:02:52.858422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T17:02:54.359716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T17:02:55.905037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T17:02:57.655540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T17:02:59.226078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T17:03:01.007527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T17:02:53.091330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T17:02:54.601669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T17:02:56.157039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T17:02:57.902265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T17:02:59.470748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T17:03:01.214549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T17:02:53.343232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T17:02:54.854847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T17:02:56.419974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T17:02:58.165083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T17:02:59.725688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T17:03:01.375162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T17:02:53.598565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T17:02:55.116267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T17:02:56.682562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T17:02:58.433519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T17:02:59.990992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T17:03:01.542026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T17:02:53.862507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T17:02:55.390141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T17:02:56.954991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T17:02:58.704071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T17:03:00.262031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T17:03:01.696169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T17:02:54.113299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T17:02:55.647739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T17:02:57.214623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T17:02:58.970169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T17:03:00.516266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T17:03:08.313243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
고유번호행정동코드2005년사용량2006년사용량X 좌표Y 좌표
고유번호1.0000.9480.1800.2160.8470.807
행정동코드0.9481.0000.1800.1740.8940.878
2005년사용량0.1800.1801.0000.9930.0480.000
2006년사용량0.2160.1740.9931.0000.1460.000
X 좌표0.8470.8940.0480.1461.0000.454
Y 좌표0.8070.8780.0000.0000.4541.000
2024-04-21T17:03:08.492453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
고유번호행정동코드2005년사용량2006년사용량X 좌표Y 좌표
고유번호1.0000.9790.1600.159-0.011-0.626
행정동코드0.9791.0000.1580.1560.009-0.630
2005년사용량0.1600.1581.0000.9960.022-0.148
2006년사용량0.1590.1560.9961.0000.018-0.148
X 좌표-0.0110.0090.0220.0181.0000.215
Y 좌표-0.626-0.630-0.148-0.1480.2151.000

Missing values

2024-04-21T17:03:01.897712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T17:03:02.116282image/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
07020081105062구의3동152.193076157.496824208497.268448474.65
11220081101068창신2동33.43654534.349623200920.962452936.545
23720081101057무악동14.61126114.685397196314.58453087.528
34620081105066자양3동49.2954760.870064206296.331448042.291
47820081106056전농1동27.71718728.541684204414.826452922.966
55620081104067성수2가1동92.17037294.296648204945.831448533.352
65920081104070용답동322.564854280.648117205120.555451313.517
76020081104071왕십리도선동86.74000888.951934202645.626451886.773
86820081105059능동34.9165536.699909207245.626450183.437
915720081110054쌍문4동36.04896236.216353202650.172461752.57
고유번호기준연도행정동코드행정동명2005년사용량2006년사용량X 좌표Y 좌표
42818320081112051녹번동90.63228192.5545194306.655456073.987
42921620081113072북가좌2동60.5141763.531337192397.613453509.328
43034720081121079성현동59.50504660.432441195639.647443380.734
43141120081122066양재1동164.6301170.6103202096.054441227.636
43241220081122068내곡동69.86758174.436983206165.612439211.042
43341420081123052논현1동211.050108219.20894202364.22445842.604
43441720081124070장지동48.77300453.448314212098.948442416.229
43541920081124077잠실6동127.886566157.812053208776.964446524.327
43642120081124079잠실2동15.0193624.237208207032.194446477.204
43742220081124080잠실3동160.593047173.411804208380.132446309.836