Overview

Dataset statistics

Number of variables18
Number of observations49
Missing cells70
Missing cells (%)7.9%
Duplicate rows3
Duplicate rows (%)6.1%
Total size in memory7.2 KiB
Average record size in memory150.7 B

Variable types

Text1
Categorical2
Unsupported11
Numeric4

Dataset

Description강원도 원주시의 2020년 월별 CO측정결과입니다. (EX> 1월 중앙동, 반곡동, 문막읍, 도시평균의 CO관련 다양한 측정결과)
Author강원도 원주시
URLhttps://www.data.go.kr/data/15092040/fileData.do

Alerts

Dataset has 3 (6.1%) duplicate rowsDuplicates
도시명 is highly overall correlated with 유효 측정 일수 and 4 other fieldsHigh correlation
측정소명 is highly overall correlated with 유효 측정 일수 and 2 other fieldsHigh correlation
유효 측정 일수 is highly overall correlated with 유효 측정 횟수 and 3 other fieldsHigh correlation
유효 측정 횟수 is highly overall correlated with 유효 측정 일수 and 2 other fieldsHigh correlation
유효 측정 시간 is highly overall correlated with 유효 측정 일수 and 3 other fieldsHigh correlation
월평균 (ppm) is highly overall correlated with 도시명High correlation
시,도명 has 37 (75.5%) missing valuesMissing
유효자료 획득율 (%) has 1 (2.0%) missing valuesMissing
유효 측정 일수 has 3 (6.1%) missing valuesMissing
유효 측정 횟수 has 3 (6.1%) missing valuesMissing
유효 측정 시간 has 3 (6.1%) missing valuesMissing
월평균 (ppm) has 3 (6.1%) missing valuesMissing
1시간치 has 2 (4.1%) missing valuesMissing
Unnamed: 9 has 2 (4.1%) missing valuesMissing
Unnamed: 10 has 2 (4.1%) missing valuesMissing
Unnamed: 11 has 2 (4.1%) missing valuesMissing
Unnamed: 12 has 2 (4.1%) missing valuesMissing
8시간치 has 2 (4.1%) missing valuesMissing
Unnamed: 14 has 2 (4.1%) missing valuesMissing
Unnamed: 15 has 2 (4.1%) missing valuesMissing
Unnamed: 16 has 2 (4.1%) missing valuesMissing
Unnamed: 17 has 2 (4.1%) missing valuesMissing
유효자료 획득율 (%) is an unsupported type, check if it needs cleaning or further analysisUnsupported
1시간치 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 11 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 12 is an unsupported type, check if it needs cleaning or further analysisUnsupported
8시간치 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 14 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 15 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 16 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 17 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 00:20:35.394870
Analysis finished2023-12-12 00:20:38.759665
Duration3.36 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시,도명
Text

MISSING 

Distinct12
Distinct (%)100.0%
Missing37
Missing (%)75.5%
Memory size524.0 B
2023-12-12T09:20:38.892853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.25
Min length2

Characters and Unicode

Total characters27
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)100.0%

Sample

1st row1월
2nd row2월
3rd row3월
4th row4월
5th row5월
ValueCountFrequency (%)
1월 1
8.3%
2월 1
8.3%
3월 1
8.3%
4월 1
8.3%
5월 1
8.3%
6월 1
8.3%
7월 1
8.3%
8월 1
8.3%
9월 1
8.3%
10월 1
8.3%
Other values (2) 2
16.7%
2023-12-12T09:20:39.242952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
월 12
44.4%
1 5
18.5%
2 2
 
7.4%
3 1
 
3.7%
4 1
 
3.7%
5 1
 
3.7%
6 1
 
3.7%
7 1
 
3.7%
8 1
 
3.7%
9 1
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15
55.6%
Other Letter 12
44.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 5
33.3%
2 2
 
13.3%
3 1
 
6.7%
4 1
 
6.7%
5 1
 
6.7%
6 1
 
6.7%
7 1
 
6.7%
8 1
 
6.7%
9 1
 
6.7%
0 1
 
6.7%
Other Letter
ValueCountFrequency (%)
월 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15
55.6%
Hangul 12
44.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1 5
33.3%
2 2
 
13.3%
3 1
 
6.7%
4 1
 
6.7%
5 1
 
6.7%
6 1
 
6.7%
7 1
 
6.7%
8 1
 
6.7%
9 1
 
6.7%
0 1
 
6.7%
Hangul
ValueCountFrequency (%)
월 12
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15
55.6%
Hangul 12
44.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
월 12
100.0%
ASCII
ValueCountFrequency (%)
1 5
33.3%
2 2
 
13.3%
3 1
 
6.7%
4 1
 
6.7%
5 1
 
6.7%
6 1
 
6.7%
7 1
 
6.7%
8 1
 
6.7%
9 1
 
6.7%
0 1
 
6.7%

도시명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size524.0 B
<NA>
37 
원주시
12 

Length

Max length4
Median length4
Mean length3.755102
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row원주시
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 37
75.5%
원주시 12
 
24.5%

Length

2023-12-12T09:20:39.409675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:20:39.558536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 37
75.5%
원주시 12
 
24.5%

측정소명
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)10.2%
Missing0
Missing (%)0.0%
Memory size524.0 B
중앙동
12 
반곡동
12 
문막읍
12 
도시평균
12 
<NA>
 
1

Length

Max length4
Median length3
Mean length3.2653061
Min length3

Unique

Unique1 ?
Unique (%)2.0%

Sample

1st row<NA>
2nd row중앙동
3rd row반곡동
4th row문막읍
5th row도시평균

Common Values

ValueCountFrequency (%)
중앙동 12
24.5%
반곡동 12
24.5%
문막읍 12
24.5%
도시평균 12
24.5%
<NA> 1
 
2.0%

Length

2023-12-12T09:20:39.677374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:20:39.870225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중앙동 12
24.5%
반곡동 12
24.5%
문막읍 12
24.5%
도시평균 12
24.5%
na 1
 
2.0%

유효자료 획득율 (%)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1
Missing (%)2.0%
Memory size524.0 B

유효 측정 일수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct14
Distinct (%)30.4%
Missing3
Missing (%)6.1%
Infinite0
Infinite (%)0.0%
Mean44.043478
Minimum16
Maximum93
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-12T09:20:39.994438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum16
5-th percentile28.25
Q130
median31
Q352
95-th percentile92.75
Maximum93
Range77
Interquartile range (IQR)22

Descriptive statistics

Standard deviation25.080277
Coefficient of variation (CV)0.5694436
Kurtosis-0.24906486
Mean44.043478
Median Absolute Deviation (MAD)1
Skewness1.2506308
Sum2026
Variance629.02029
MonotonicityNot monotonic
2023-12-12T09:20:40.131790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
31 16
32.7%
30 11
22.4%
29 4
 
8.2%
93 3
 
6.1%
90 3
 
6.1%
28 1
 
2.0%
86 1
 
2.0%
27 1
 
2.0%
89 1
 
2.0%
16 1
 
2.0%
Other values (4) 4
 
8.2%
(Missing) 3
 
6.1%
ValueCountFrequency (%)
16 1
 
2.0%
27 1
 
2.0%
28 1
 
2.0%
29 4
 
8.2%
30 11
22.4%
31 16
32.7%
59 1
 
2.0%
62 1
 
2.0%
76 1
 
2.0%
86 1
 
2.0%
ValueCountFrequency (%)
93 3
 
6.1%
92 1
 
2.0%
90 3
 
6.1%
89 1
 
2.0%
86 1
 
2.0%
76 1
 
2.0%
62 1
 
2.0%
59 1
 
2.0%
31 16
32.7%
30 11
22.4%

유효 측정 횟수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct24
Distinct (%)52.2%
Missing3
Missing (%)6.1%
Infinite0
Infinite (%)0.0%
Mean919.08696
Minimum272
Maximum2232
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-12T09:20:40.286157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum272
5-th percentile488.5
Q1527
median723
Q3945.75
95-th percentile2214.5
Maximum2232
Range1960
Interquartile range (IQR)418.75

Descriptive statistics

Standard deviation570.54071
Coefficient of variation (CV)0.62076902
Kurtosis0.9032424
Mean919.08696
Median Absolute Deviation (MAD)196
Skewness1.4905707
Sum42278
Variance325516.7
MonotonicityNot monotonic
2023-12-12T09:20:40.421428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
744 9
18.4%
527 7
14.3%
720 5
 
10.2%
510 3
 
6.1%
493 2
 
4.1%
2232 2
 
4.1%
486 1
 
2.0%
1540 1
 
2.0%
2225 1
 
2.0%
737 1
 
2.0%
Other values (14) 14
28.6%
(Missing) 3
 
6.1%
ValueCountFrequency (%)
272 1
 
2.0%
486 1
 
2.0%
487 1
 
2.0%
493 2
 
4.1%
503 1
 
2.0%
510 3
6.1%
527 7
14.3%
713 1
 
2.0%
714 1
 
2.0%
720 5
10.2%
ValueCountFrequency (%)
2232 2
4.1%
2225 1
2.0%
2183 1
2.0%
2160 1
2.0%
2154 1
2.0%
1581 1
2.0%
1540 1
2.0%
1473 1
2.0%
1292 1
2.0%
1054 1
2.0%

유효 측정 시간
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct26
Distinct (%)56.5%
Missing3
Missing (%)6.1%
Infinite0
Infinite (%)0.0%
Mean1058.1739
Minimum383
Maximum2223
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-12T09:20:40.583220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum383
5-th percentile692.25
Q1716
median740
Q31259.5
95-th percentile2219.5
Maximum2223
Range1840
Interquartile range (IQR)543.5

Descriptive statistics

Standard deviation602.26153
Coefficient of variation (CV)0.56915174
Kurtosis-0.25136651
Mean1058.1739
Median Absolute Deviation (MAD)24
Skewness1.2512391
Sum48676
Variance362718.95
MonotonicityNot monotonic
2023-12-12T09:20:40.748898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
740 10
20.4%
741 5
 
10.2%
715 3
 
6.1%
717 3
 
6.1%
716 3
 
6.1%
2220 2
 
4.1%
2076 1
 
2.0%
729 1
 
2.0%
2218 1
 
2.0%
737 1
 
2.0%
Other values (16) 16
32.7%
(Missing) 3
 
6.1%
ValueCountFrequency (%)
383 1
 
2.0%
691 1
 
2.0%
692 1
 
2.0%
693 1
 
2.0%
695 1
 
2.0%
713 1
 
2.0%
714 1
 
2.0%
715 3
6.1%
716 3
6.1%
717 3
6.1%
ValueCountFrequency (%)
2223 1
2.0%
2220 2
4.1%
2218 1
2.0%
2183 1
2.0%
2176 1
2.0%
2148 1
2.0%
2145 1
2.0%
2076 1
2.0%
1816 1
2.0%
1481 1
2.0%

월평균 (ppm)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct8
Distinct (%)17.4%
Missing3
Missing (%)6.1%
Infinite0
Infinite (%)0.0%
Mean0.47173913
Minimum0.2
Maximum0.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-12T09:20:40.913826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.2
5-th percentile0.3
Q10.325
median0.4
Q30.6
95-th percentile0.7
Maximum0.9
Range0.7
Interquartile range (IQR)0.275

Descriptive statistics

Standard deviation0.16008754
Coefficient of variation (CV)0.33935607
Kurtosis-0.25868292
Mean0.47173913
Median Absolute Deviation (MAD)0.1
Skewness0.62184298
Sum21.7
Variance0.025628019
MonotonicityNot monotonic
2023-12-12T09:20:41.077618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0.4 13
26.5%
0.3 11
22.4%
0.6 8
16.3%
0.5 6
12.2%
0.7 5
 
10.2%
0.8 1
 
2.0%
0.9 1
 
2.0%
0.2 1
 
2.0%
(Missing) 3
 
6.1%
ValueCountFrequency (%)
0.2 1
 
2.0%
0.3 11
22.4%
0.4 13
26.5%
0.5 6
12.2%
0.6 8
16.3%
0.7 5
 
10.2%
0.8 1
 
2.0%
0.9 1
 
2.0%
ValueCountFrequency (%)
0.9 1
 
2.0%
0.8 1
 
2.0%
0.7 5
 
10.2%
0.6 8
16.3%
0.5 6
12.2%
0.4 13
26.5%
0.3 11
22.4%
0.2 1
 
2.0%

1시간치
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2
Missing (%)4.1%
Memory size524.0 B

Unnamed: 9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2
Missing (%)4.1%
Memory size524.0 B

Unnamed: 10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2
Missing (%)4.1%
Memory size524.0 B

Unnamed: 11
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2
Missing (%)4.1%
Memory size524.0 B

Unnamed: 12
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2
Missing (%)4.1%
Memory size524.0 B

8시간치
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2
Missing (%)4.1%
Memory size524.0 B

Unnamed: 14
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2
Missing (%)4.1%
Memory size524.0 B

Unnamed: 15
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2
Missing (%)4.1%
Memory size524.0 B

Unnamed: 16
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2
Missing (%)4.1%
Memory size524.0 B

Unnamed: 17
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2
Missing (%)4.1%
Memory size524.0 B

Interactions

2023-12-12T09:20:37.205938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:20:35.649434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:20:36.015839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:20:36.751608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:20:37.322647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:20:35.740891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:20:36.127031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:20:36.866137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:20:37.474877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:20:35.831580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:20:36.243247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:20:36.981645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:20:37.625418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:20:35.923865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:20:36.643407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:20:37.102362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T09:20:41.191828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시,도명측정소명유효 측정 일수유효 측정 횟수유효 측정 시간월평균 (ppm)
시,도명1.000NaNNaN1.000NaN1.000
측정소명NaN1.0000.6160.6780.8700.000
유효\n측정\n일수NaN0.6161.0001.0001.0000.638
유효\n측정\n횟수1.0000.6781.0001.0001.0000.400
유효\n측정\n시간NaN0.8701.0001.0001.0000.000
월평균\n(ppm)1.0000.0000.6380.4000.0001.000
2023-12-12T09:20:41.316877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
도시명측정소명
도시명1.0001.000
측정소명1.0001.000
2023-12-12T09:20:41.412405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유효 측정 일수유효 측정 횟수유효 측정 시간월평균 (ppm)도시명측정소명
유효\n측정\n일수1.0000.8570.974-0.0401.0000.537
유효\n측정\n횟수0.8571.0000.848-0.2471.0000.498
유효\n측정\n시간0.9740.8481.000-0.0601.0000.537
월평균\n(ppm)-0.040-0.247-0.0601.0001.0000.000
도시명1.0001.0001.0001.0001.0001.000
측정소명0.5370.4980.5370.0001.0001.000

Missing values

2023-12-12T09:20:37.829797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:20:38.138969image/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.
2023-12-12T09:20:38.436991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

시,도명도시명측정소명유효자료 획득율 (%)유효 측정 일수유효 측정 횟수유효 측정 시간월평균 (ppm)1시간치Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 128시간치Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17
0<NA><NA><NA>NaN<NA><NA><NA><NA>최저\n(ppm)최고\n(ppm)최고일시\n(년월일시)기준\n초과\n(회)초과율\n(%)최저\n(ppm)최고\n(ppm)최고일\n(년월일)기준\n초과\n(회)초과율\n(%)
11월원주시중앙동99.46315277400.50.11.62020010224000.21.120200120020900
2<NA><NA>반곡동99.46315277400.70.11.52020010310000.41.420200106091600
3<NA><NA>문막읍99.46315277400.60.31.22020011510000.3120200120041100
4<NA><NA>도시평균99.4693158122200.60.11.62020010224000.21.420200106091600
52월원주시중앙동99.57294936930.70.11.92020021301000.21.420200212172400
6<NA><NA>반곡동99.43294936920.70.222020022109000.51.520200221071400
7<NA><NA>문막읍99.28284876910.50.31.12020020201000.40.920200201172400
8<NA><NA>도시평균99.4386147320760.60.122020022109000.21.520200221071400
93월원주시중앙동99.46315277400.60.31.32020030723000.60.820200302172400
시,도명도시명측정소명유효자료 획득율 (%)유효 측정 일수유효 측정 횟수유효 측정 시간월평균 (ppm)1시간치Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 128시간치Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17
39<NA><NA>문막읍99.46317447400.40.30.92020102809000.30.820201028020900
40<NA><NA>도시평균99.4693223222200.40.10.92020102809000.30.820201027162300
4111월원주시중앙동99.44307207160.60.11.92020111702000.51.720201116190200
42<NA><NA>반곡동99.31307147150.40.10.92020110704000.10.820201113031000
43<NA><NA>문막읍99.58307207170.50.20.92020111621000.40.820201116162300
44<NA><NA>도시평균99.4490215421480.50.11.92020111702000.11.720201116190200
4512월원주시중앙동99.6317447410.70.22.52020122321000.4220201223172400
46<NA><NA>반곡동99.46317447400.60.31.32020121109000.51.220201211031000
47<NA><NA>문막읍99.06307377370.60.31.32020122620000.51.120201223190200
48<NA><NA>도시평균99.3792222522180.70.22.52020122321000.4220201223172400

Duplicate rows

Most frequently occurring

시,도명도시명측정소명유효 측정 일수유효 측정 횟수유효 측정 시간월평균 (ppm)# duplicates
0<NA><NA>문막읍305107170.42
1<NA><NA>문막읍317447410.32
2<NA><NA>반곡동<NA><NA><NA><NA>2