Overview

Dataset statistics

Number of variables11
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.5 KiB
Average record size in memory97.3 B

Variable types

Categorical5
Numeric6

Alerts

배출년도 has constant value ""Constant
배출월 has constant value ""Constant
지자체 시도명 has constant value ""Constant
지자체 시군구명 is highly overall correlated with 배출량(g) and 2 other fieldsHigh correlation
지자체코드 is highly overall correlated with 배출량(g) and 2 other fieldsHigh correlation
배출량(g) is highly overall correlated with 배출횟수 and 2 other fieldsHigh correlation
배출량비율(%) is highly overall correlated with 배출횟수비율(%)High correlation
배출횟수 is highly overall correlated with 배출량(g) and 2 other fieldsHigh correlation
배출횟수비율(%) is highly overall correlated with 배출량비율(%)High correlation
배출량(g) has unique valuesUnique

Reproduction

Analysis started2023-12-10 10:44:30.661763
Analysis finished2023-12-10 10:44:38.098805
Duration7.44 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

배출년도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2020
100 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020
2nd row2020
3rd row2020
4th row2020
5th row2020

Common Values

ValueCountFrequency (%)
2020 100
100.0%

Length

2023-12-10T19:44:38.230898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:44:38.470249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 100
100.0%

배출월
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
1
100 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 100
100.0%

Length

2023-12-10T19:44:38.646826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:44:38.821264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 100
100.0%

배출일
Real number (ℝ)

Distinct31
Distinct (%)31.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.16
Minimum1
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:44:39.007652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q17
median15
Q323
95-th percentile30
Maximum31
Range30
Interquartile range (IQR)16

Descriptive statistics

Standard deviation9.214306
Coefficient of variation (CV)0.60780382
Kurtosis-1.2602055
Mean15.16
Median Absolute Deviation (MAD)8
Skewness0.10720476
Sum1516
Variance84.903434
MonotonicityNot monotonic
2023-12-10T19:44:39.244859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
2 4
 
4.0%
4 4
 
4.0%
5 4
 
4.0%
6 4
 
4.0%
7 4
 
4.0%
1 4
 
4.0%
3 4
 
4.0%
26 3
 
3.0%
23 3
 
3.0%
24 3
 
3.0%
Other values (21) 63
63.0%
ValueCountFrequency (%)
1 4
4.0%
2 4
4.0%
3 4
4.0%
4 4
4.0%
5 4
4.0%
6 4
4.0%
7 4
4.0%
8 3
3.0%
9 3
3.0%
10 3
3.0%
ValueCountFrequency (%)
31 3
3.0%
30 3
3.0%
29 3
3.0%
28 3
3.0%
27 3
3.0%
26 3
3.0%
25 3
3.0%
24 3
3.0%
23 3
3.0%
22 3
3.0%

배출요일
Real number (ℝ)

Distinct7
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.09
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:44:39.499195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q36
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation1.9545079
Coefficient of variation (CV)0.47787478
Kurtosis-1.175345
Mean4.09
Median Absolute Deviation (MAD)2
Skewness-0.10378941
Sum409
Variance3.820101
MonotonicityNot monotonic
2023-12-10T19:44:39.688851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
5 16
16.0%
6 16
16.0%
4 16
16.0%
7 13
13.0%
1 13
13.0%
2 13
13.0%
3 13
13.0%
ValueCountFrequency (%)
1 13
13.0%
2 13
13.0%
3 13
13.0%
4 16
16.0%
5 16
16.0%
6 16
16.0%
7 13
13.0%
ValueCountFrequency (%)
7 13
13.0%
6 16
16.0%
5 16
16.0%
4 16
16.0%
3 13
13.0%
2 13
13.0%
1 13
13.0%

지자체코드
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
W01
31 
W02
31 
W03
31 
W04
7 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowW01
2nd rowW01
3rd rowW01
4th rowW01
5th rowW01

Common Values

ValueCountFrequency (%)
W01 31
31.0%
W02 31
31.0%
W03 31
31.0%
W04 7
 
7.0%

Length

2023-12-10T19:44:39.935061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:44:40.152837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
w01 31
31.0%
w02 31
31.0%
w03 31
31.0%
w04 7
 
7.0%

지자체 시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
서울특별시
100 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울특별시 100
100.0%

Length

2023-12-10T19:44:40.354725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:44:40.514510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 100
100.0%

지자체 시군구명
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
종로구
31 
중구
31 
용산구
31 
성동구
7 

Length

Max length3
Median length3
Mean length2.69
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
종로구 31
31.0%
중구 31
31.0%
용산구 31
31.0%
성동구 7
 
7.0%

Length

2023-12-10T19:44:40.700862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:44:40.889688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
종로구 31
31.0%
중구 31
31.0%
용산구 31
31.0%
성동구 7
 
7.0%

배출량(g)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4321811.5
Minimum359350
Maximum18437050
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:44:41.135194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum359350
5-th percentile457235
Q1557312.5
median3552225
Q36028850
95-th percentile13196823
Maximum18437050
Range18077700
Interquartile range (IQR)5471537.5

Descriptive statistics

Standard deviation3832576.7
Coefficient of variation (CV)0.88679868
Kurtosis2.4258898
Mean4321811.5
Median Absolute Deviation (MAD)2930650
Skewness1.4124589
Sum4.3218115 × 108
Variance1.4688644 × 1013
MonotonicityNot monotonic
2023-12-10T19:44:41.418081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3548600 1
 
1.0%
492350 1
 
1.0%
528500 1
 
1.0%
452400 1
 
1.0%
553300 1
 
1.0%
457250 1
 
1.0%
462750 1
 
1.0%
456950 1
 
1.0%
520100 1
 
1.0%
440500 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
359350 1
1.0%
420800 1
1.0%
440500 1
1.0%
452400 1
1.0%
456950 1
1.0%
457250 1
1.0%
462750 1
1.0%
465050 1
1.0%
471300 1
1.0%
473100 1
1.0%
ValueCountFrequency (%)
18437050 1
1.0%
15670750 1
1.0%
15482800 1
1.0%
15212400 1
1.0%
13446200 1
1.0%
13183698 1
1.0%
11557450 1
1.0%
10319050 1
1.0%
8252350 1
1.0%
8233250 1
1.0%

배출량비율(%)
Real number (ℝ)

HIGH CORRELATION 

Distinct68
Distinct (%)68.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.2151
Minimum2.24
Maximum5.08
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:44:41.702382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.24
5-th percentile2.6395
Q12.865
median3.195
Q33.385
95-th percentile4.062
Maximum5.08
Range2.84
Interquartile range (IQR)0.52

Descriptive statistics

Standard deviation0.49359636
Coefficient of variation (CV)0.15352442
Kurtosis2.405878
Mean3.2151
Median Absolute Deviation (MAD)0.275
Skewness1.24885
Sum321.51
Variance0.24363736
MonotonicityNot monotonic
2023-12-10T19:44:41.938455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.75 5
 
5.0%
2.77 4
 
4.0%
3.23 3
 
3.0%
2.95 3
 
3.0%
3.1 3
 
3.0%
3.35 3
 
3.0%
3.21 2
 
2.0%
3.2 2
 
2.0%
2.96 2
 
2.0%
2.87 2
 
2.0%
Other values (58) 71
71.0%
ValueCountFrequency (%)
2.24 1
 
1.0%
2.4 1
 
1.0%
2.41 1
 
1.0%
2.63 2
 
2.0%
2.64 1
 
1.0%
2.68 1
 
1.0%
2.72 2
 
2.0%
2.75 5
5.0%
2.77 4
4.0%
2.79 2
 
2.0%
ValueCountFrequency (%)
5.08 1
1.0%
4.76 1
1.0%
4.74 1
1.0%
4.12 1
1.0%
4.1 1
1.0%
4.06 1
1.0%
4.05 1
1.0%
4.03 1
1.0%
3.99 2
2.0%
3.94 1
1.0%

배출횟수
Real number (ℝ)

HIGH CORRELATION 

Distinct97
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2945.01
Minimum251
Maximum11911
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:44:42.179700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum251
5-th percentile331.65
Q1395.25
median2363.5
Q34382.5
95-th percentile8869.95
Maximum11911
Range11660
Interquartile range (IQR)3987.25

Descriptive statistics

Standard deviation2566.1639
Coefficient of variation (CV)0.87135999
Kurtosis1.734334
Mean2945.01
Median Absolute Deviation (MAD)1976
Skewness1.2542607
Sum294501
Variance6585197.1
MonotonicityNot monotonic
2023-12-10T19:44:42.429912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
380 3
 
3.0%
373 2
 
2.0%
333 1
 
1.0%
336 1
 
1.0%
351 1
 
1.0%
332 1
 
1.0%
383 1
 
1.0%
322 1
 
1.0%
434 1
 
1.0%
352 1
 
1.0%
Other values (87) 87
87.0%
ValueCountFrequency (%)
251 1
1.0%
314 1
1.0%
320 1
1.0%
322 1
1.0%
325 1
1.0%
332 1
1.0%
333 1
1.0%
336 1
1.0%
342 1
1.0%
351 1
1.0%
ValueCountFrequency (%)
11911 1
1.0%
10265 1
1.0%
10071 1
1.0%
10004 1
1.0%
9078 1
1.0%
8859 1
1.0%
7805 1
1.0%
6507 1
1.0%
5823 1
1.0%
5770 1
1.0%

배출횟수비율(%)
Real number (ℝ)

HIGH CORRELATION 

Distinct74
Distinct (%)74.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.2164
Minimum2.19
Maximum4.53
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:44:42.699132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.19
5-th percentile2.7345
Q12.93
median3.2
Q33.3625
95-th percentile4.0215
Maximum4.53
Range2.34
Interquartile range (IQR)0.4325

Descriptive statistics

Standard deviation0.40886519
Coefficient of variation (CV)0.12711889
Kurtosis1.3323864
Mean3.2164
Median Absolute Deviation (MAD)0.24
Skewness0.83850089
Sum321.64
Variance0.16717075
MonotonicityNot monotonic
2023-12-10T19:44:42.953416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.31 5
 
5.0%
3.21 3
 
3.0%
2.89 3
 
3.0%
2.9 3
 
3.0%
3.03 3
 
3.0%
3.32 2
 
2.0%
2.85 2
 
2.0%
3.2 2
 
2.0%
2.93 2
 
2.0%
3.78 2
 
2.0%
Other values (64) 73
73.0%
ValueCountFrequency (%)
2.19 1
1.0%
2.46 1
1.0%
2.49 1
1.0%
2.62 1
1.0%
2.63 1
1.0%
2.74 1
1.0%
2.76 1
1.0%
2.79 1
1.0%
2.81 1
1.0%
2.82 1
1.0%
ValueCountFrequency (%)
4.53 1
1.0%
4.41 1
1.0%
4.27 1
1.0%
4.13 1
1.0%
4.05 1
1.0%
4.02 1
1.0%
4.0 1
1.0%
3.91 1
1.0%
3.89 1
1.0%
3.8 1
1.0%

Interactions

2023-12-10T19:44:36.228861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:31.130609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:32.142329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:33.249632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:34.278773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:35.244068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:36.384098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:31.287304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:32.293787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:33.417665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:34.427713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:35.423403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:36.559138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:31.443473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:32.497980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:33.607397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:34.582132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:35.607003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:37.109991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:31.661219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:32.709065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:33.797578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:34.756263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:35.769396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:37.262407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:31.815926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:32.854532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:33.950017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:34.924958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:35.938047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:37.453793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:31.985972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:33.050703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:34.119278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:35.078448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:44:36.086499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:44:43.142261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
배출일배출요일지자체코드지자체 시군구명배출량(g)배출량비율(%)배출횟수배출횟수비율(%)
배출일1.0000.6110.0000.0000.0000.4340.0000.662
배출요일0.6111.0000.0000.0000.0410.4910.0000.506
지자체코드0.0000.0001.0001.0000.9940.0001.0000.000
지자체 시군구명0.0000.0001.0001.0000.9940.0001.0000.000
배출량(g)0.0000.0410.9940.9941.0000.8090.9980.734
배출량비율(%)0.4340.4910.0000.0000.8091.0000.7940.872
배출횟수0.0000.0001.0001.0000.9980.7941.0000.738
배출횟수비율(%)0.6620.5060.0000.0000.7340.8720.7381.000
2023-12-10T19:44:43.341435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지자체 시군구명지자체코드
지자체 시군구명1.0001.000
지자체코드1.0001.000
2023-12-10T19:44:43.511676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
배출일배출요일배출량(g)배출량비율(%)배출횟수배출횟수비율(%)지자체코드지자체 시군구명
배출일1.000-0.031-0.0590.327-0.0760.2840.0000.000
배출요일-0.0311.000-0.117-0.412-0.110-0.3630.0000.000
배출량(g)-0.059-0.1171.0000.2050.9890.1670.9320.932
배출량비율(%)0.327-0.4120.2051.0000.1700.8870.0000.000
배출횟수-0.076-0.1100.9890.1701.0000.1970.9600.960
배출횟수비율(%)0.284-0.3630.1670.8870.1971.0000.0000.000
지자체코드0.0000.0000.9320.0000.9600.0001.0001.000
지자체 시군구명0.0000.0000.9320.0000.9600.0001.0001.000

Missing values

2023-12-10T19:44:37.684202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:44:37.985977image/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

배출년도배출월배출일배출요일지자체코드지자체 시도명지자체 시군구명배출량(g)배출량비율(%)배출횟수배출횟수비율(%)
02020125W01서울특별시종로구35486003.2323063.23
12020136W01서울특별시종로구31519002.8721092.95
22020147W01서울특별시종로구32463502.9521152.96
32020151W01서울특별시종로구38792003.5324623.45
42020162W01서울특별시종로구37663503.4224323.41
52020173W01서울특별시종로구29925502.7219682.76
62020184W01서울특별시종로구35402003.2224043.37
72020195W01서울특별시종로구29952002.7220652.89
820201106W01서울특별시종로구30428502.7720812.91
920201117W01서울특별시종로구31007502.8220722.9
배출년도배출월배출일배출요일지자체코드지자체 시도명지자체 시군구명배출량(g)배출량비율(%)배출횟수배출횟수비율(%)
9020201305W03서울특별시용산구4731002.953803.31
9120201316W03서울특별시용산구5586503.493793.3
922020114W04서울특별시성동구156707503.27100043.19
932020125W04서울특별시성동구154828003.23102653.27
942020136W04서울특별시성동구131836982.7590782.89
952020147W04서울특별시성동구134462002.8188592.82
962020151W04서울특별시성동구184370503.85119113.79
972020162W04서울특별시성동구152124003.18100713.21
982020173W04서울특별시성동구115574502.4178052.49
992020114W01서울특별시종로구33241503.0221242.97