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-335/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
2005년사용량 has 326 (74.4%) zerosZeros
2006년사용량 has 325 (74.2%) zerosZeros

Reproduction

Analysis started2023-12-11 07:19:07.758786
Analysis finished2023-12-11 07:19:13.499599
Duration5.74 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
2023-12-11T16:19:13.616553image/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
2023-12-11T16:19:13.816295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
70 1
 
0.2%
387 1
 
0.2%
354 1
 
0.2%
298 1
 
0.2%
295 1
 
0.2%
294 1
 
0.2%
383 1
 
0.2%
377 1
 
0.2%
371 1
 
0.2%
406 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

2023-12-11T16:19:14.001137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T16:19:14.124647image/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
2023-12-11T16:19:14.289042image/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
2023-12-11T16:19:14.473041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1105062 1
 
0.2%
1124052 1
 
0.2%
1122053 1
 
0.2%
1123051 1
 
0.2%
1122052 1
 
0.2%
1117071 1
 
0.2%
1123074 1
 
0.2%
1123066 1
 
0.2%
1123059 1
 
0.2%
1124068 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
2023-12-11T16:19:14.912784image/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 row이촌1동
3rd row소공동
4th row성수1가2동
5th row사근동
ValueCountFrequency (%)
신사동 2
 
0.5%
화곡6동 1
 
0.2%
사당3동 1
 
0.2%
서초2동 1
 
0.2%
구로2동 1
 
0.2%
일원2동 1
 
0.2%
도곡1동 1
 
0.2%
삼성2동 1
 
0.2%
문정1동 1
 
0.2%
석촌동 1
 
0.2%
Other values (427) 427
97.5%
2023-12-11T16:19:15.490784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 439
26.2%
2 101
 
6.0%
1 101
 
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%
정 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%
정 16
 
1.2%
성 16
 
1.2%
화 16
 
1.2%
상 16
 
1.2%
방 16
 
1.2%
Other values (166) 732
54.1%
Decimal Number
ValueCountFrequency (%)
2 101
32.2%
1 101
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%
정 16
 
1.2%
성 16
 
1.2%
화 16
 
1.2%
상 16
 
1.2%
방 16
 
1.2%
Other values (166) 732
54.1%
Common
ValueCountFrequency (%)
2 101
31.3%
1 101
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%
정 16
 
1.2%
성 16
 
1.2%
화 16
 
1.2%
상 16
 
1.2%
방 16
 
1.2%
Other values (166) 732
54.1%
ASCII
ValueCountFrequency (%)
2 101
31.3%
1 101
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  ZEROS 

Distinct113
Distinct (%)25.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11565.648
Minimum0
Maximum299852.16
Zeros326
Zeros (%)74.4%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2023-12-11T16:19:15.717141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3334.21
95-th percentile73337.627
Maximum299852.16
Range299852.16
Interquartile range (IQR)334.21

Descriptive statistics

Standard deviation30676.595
Coefficient of variation (CV)2.6523887
Kurtosis25.631933
Mean11565.648
Median Absolute Deviation (MAD)0
Skewness4.2956773
Sum5065754
Variance9.4105347 × 108
MonotonicityNot monotonic
2023-12-11T16:19:15.955296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 326
74.4%
10743.1 1
 
0.2%
16174.53 1
 
0.2%
83943.91 1
 
0.2%
27192.9 1
 
0.2%
33559.5 1
 
0.2%
76568.86 1
 
0.2%
20705.99 1
 
0.2%
16711.2 1
 
0.2%
350.08 1
 
0.2%
Other values (103) 103
 
23.5%
ValueCountFrequency (%)
0.0 326
74.4%
142.8 1
 
0.2%
286.6 1
 
0.2%
350.08 1
 
0.2%
367.6 1
 
0.2%
374.1 1
 
0.2%
563.02 1
 
0.2%
805.0 1
 
0.2%
2035.0 1
 
0.2%
2401.5 1
 
0.2%
ValueCountFrequency (%)
299852.16 1
0.2%
198098.9 1
0.2%
180946.18 1
0.2%
172459.0099 1
0.2%
143993.0001 1
0.2%
115285.3 1
0.2%
113897.3 1
0.2%
112021.3 1
0.2%
111990.0 1
0.2%
104380.2 1
0.2%

2006년사용량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct114
Distinct (%)26.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10576.106
Minimum0
Maximum262022.67
Zeros325
Zeros (%)74.2%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2023-12-11T16:19:16.169013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3347.35
95-th percentile65001.734
Maximum262022.67
Range262022.67
Interquartile range (IQR)347.35

Descriptive statistics

Standard deviation28031.928
Coefficient of variation (CV)2.6504961
Kurtosis24.875471
Mean10576.106
Median Absolute Deviation (MAD)0
Skewness4.2913354
Sum4632334.6
Variance7.8578901 × 108
MonotonicityNot monotonic
2023-12-11T16:19:16.417063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 325
74.2%
9702.1 1
 
0.2%
14459.54 1
 
0.2%
75452.02 1
 
0.2%
22664.0 1
 
0.2%
29737.3 1
 
0.2%
54592.11 1
 
0.2%
25295.96 1
 
0.2%
15090.0 1
 
0.2%
572.26 1
 
0.2%
Other values (104) 104
 
23.7%
ValueCountFrequency (%)
0.0 325
74.2%
141.0 1
 
0.2%
222.2 1
 
0.2%
280.3 1
 
0.2%
369.7 1
 
0.2%
403.04 1
 
0.2%
572.26 1
 
0.2%
667.8 1
 
0.2%
1499.7 1
 
0.2%
1525.7 1
 
0.2%
ValueCountFrequency (%)
262022.67 1
0.2%
200547.7 1
0.2%
175677.5 1
0.2%
163398.46 1
0.2%
124751.7 1
0.2%
105319.5 1
0.2%
103321.2 1
0.2%
98582.1 1
0.2%
97807.0 1
0.2%
97337.9 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
2023-12-11T16:19:16.602559image/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
2023-12-11T16:19:16.800005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
208497.268 1
 
0.2%
209733.947 1
 
0.2%
200863.446 1
 
0.2%
201783.986 1
 
0.2%
202461.729 1
 
0.2%
189244.268 1
 
0.2%
207178.152 1
 
0.2%
203602.87 1
 
0.2%
204331.585 1
 
0.2%
211261.036 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
2023-12-11T16:19:17.028298image/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-0.55467902
Mean450117.74
Median Absolute Deviation (MAD)4332.767
Skewness0.32397248
Sum1.9715157 × 108
Variance34230250
MonotonicityNot monotonic
2023-12-11T16:19:17.260813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
448474.65 1
 
0.2%
447836.425 1
 
0.2%
442912.533 1
 
0.2%
447372.759 1
 
0.2%
443293.446 1
 
0.2%
444144.064 1
 
0.2%
443859.614 1
 
0.2%
443332.918 1
 
0.2%
445802.96 1
 
0.2%
443157.816 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

2023-12-11T16:19:12.078294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:19:08.146130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:19:08.910918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:19:09.735219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:19:10.577555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:19:11.283341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:19:12.216365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:19:08.276997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:19:09.045617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:19:09.872182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:19:10.734003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:19:11.399534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:19:12.332328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:19:08.410506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:19:09.175950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:19:10.007079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:19:10.868770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:19:11.523354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:19:12.459568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:19:08.549213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:19:09.315938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:19:10.146506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:19:10.995522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:19:11.672136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:19:12.569016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:19:08.678048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:19:09.457986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:19:10.278815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:19:11.097489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:19:11.800866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:19:12.704691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:19:08.791582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:19:09.602202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:19:10.435024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:19:11.190260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T16:19:11.942364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T16:19:17.421793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
고유번호행정동코드2005년사용량2006년사용량X 좌표Y 좌표
고유번호1.0000.9480.2310.2380.8540.814
행정동코드0.9481.0000.2450.2600.8940.878
2005년사용량0.2310.2451.0000.9980.1760.143
2006년사용량0.2380.2600.9981.0000.2090.170
X 좌표0.8540.8940.1760.2091.0000.454
Y 좌표0.8140.8780.1430.1700.4541.000
2023-12-11T16:19:17.595724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
고유번호행정동코드2005년사용량2006년사용량X 좌표Y 좌표
고유번호1.0000.9800.2620.256-0.011-0.629
행정동코드0.9801.0000.2940.2870.009-0.630
2005년사용량0.2620.2941.0000.9960.169-0.119
2006년사용량0.2560.2870.9961.0000.168-0.119
X 좌표-0.0110.0090.1690.1681.0000.215
Y 좌표-0.629-0.630-0.119-0.1190.2151.000

Missing values

2023-12-11T16:19:12.882069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T16:19:13.438900image/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
07020081105062구의3동0.00.0208497.268448474.65
14120081103063이촌1동180946.18163398.46197366.442446451.673
21720081102052소공동2035.01499.7197763.058451662.285
34320081104066성수1가2동0.00.0203702.617449912.407
44920081104055사근동0.00.0204007.697451051.69
55620081104067성수2가1동0.00.0204945.831448533.352
66520081105056중곡2동0.00.0207430.635451029.495
77420081105067자양4동0.00.0205621.339448266.35
84220081104054마장동0.00.0203559.413451994.594
9720081101061종로1.2.3.4가동0.00.0199052.485453135.715
고유번호기준연도행정동코드행정동명2005년사용량2006년사용량X 좌표Y 좌표
42816720081111054월계4동22853.320165.5205047.708459107.823
42921520081113072북가좌2동0.00.0192397.613453509.328
43029320081117070가리봉동0.00.0190112.471442613.672
43127120081114076서강동0.00.0193295.628449646.73
43231020081119069신길7동0.00.0192883.061445343.677
43335020081121081난곡동0.00.0192971.616441212.867
43438520081123076세곡동0.00.0209153.533441450.913
43542320081125051강일동0.00.0215247.599451535.363
43642620081125054명일2동0.00.0213768.099449897.966
43742720081125056고덕2동0.00.0214335.251451907.084