Overview

Dataset statistics

Number of variables18
Number of observations49
Missing cells70
Missing cells (%)7.9%
Duplicate rows1
Duplicate rows (%)2.0%
Total size in memory7.2 KiB
Average record size in memory150.7 B

Variable types

Text1
Categorical2
Unsupported11
Numeric4

Dataset

Description강원도 원주시의 2020년 월별 O3측정 결과입니다. EX)1월 중앙동, 반곡동, 문막읍, 도시평균의 O3관련 다양한 측정결과)
Author강원도 원주시
URLhttps://www.data.go.kr/data/15092041/fileData.do

Alerts

Dataset has 1 (2.0%) duplicate rowsDuplicates
측정소명 is highly overall correlated with 유효 측정 일수 and 2 other fieldsHigh correlation
도시명 is highly overall correlated with 유효 측정 일수 and 4 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 측정시간 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
유효자료획득율 (%) 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 측정시간 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
24시간치 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
유효자료획득율 (%) 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
24시간치 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 17:56:54.533974
Analysis finished2023-12-12 17:56:57.465329
Duration2.93 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
2023-12-13T02:56:57.589960image/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%
2023-12-13T02:56:57.909370image/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

2023-12-13T02:56:58.048405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:56:58.147000image/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

2023-12-13T02:56:58.258038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:56:58.369010image/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%

유효자료획득율 (%)
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
2023-12-13T02:56:58.484220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum16
5-th percentile27.5
Q130
median31
Q352
95-th percentile92.75
Maximum93
Range77
Interquartile range (IQR)22

Descriptive statistics

Standard deviation25.097106
Coefficient of variation (CV)0.56982571
Kurtosis-0.23789161
Mean44.043478
Median Absolute Deviation (MAD)1
Skewness1.2518218
Sum2026
Variance629.86473
MonotonicityNot monotonic
2023-12-13T02:56:58.631086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
31 18
36.7%
30 9
18.4%
29 4
 
8.2%
93 3
 
6.1%
90 2
 
4.1%
92 2
 
4.1%
26 1
 
2.0%
84 1
 
2.0%
27 1
 
2.0%
89 1
 
2.0%
Other values (4) 4
 
8.2%
(Missing) 3
 
6.1%
ValueCountFrequency (%)
16 1
 
2.0%
26 1
 
2.0%
27 1
 
2.0%
29 4
 
8.2%
30 9
18.4%
31 18
36.7%
59 1
 
2.0%
62 1
 
2.0%
76 1
 
2.0%
84 1
 
2.0%
ValueCountFrequency (%)
93 3
 
6.1%
92 2
 
4.1%
90 2
 
4.1%
89 1
 
2.0%
84 1
 
2.0%
76 1
 
2.0%
62 1
 
2.0%
59 1
 
2.0%
31 18
36.7%
30 9
18.4%

유효 측정 횟수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct22
Distinct (%)47.8%
Missing3
Missing (%)6.1%
Infinite0
Infinite (%)0.0%
Mean921.26087
Minimum272
Maximum2232
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-13T02:56:58.795787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum272
5-th percentile487.75
Q1527
median740.5
Q3945.75
95-th percentile2225
Maximum2232
Range1960
Interquartile range (IQR)418.75

Descriptive statistics

Standard deviation573.43667
Coefficient of variation (CV)0.62244766
Kurtosis0.93082127
Mean921.26087
Median Absolute Deviation (MAD)213.5
Skewness1.4957053
Sum42378
Variance328829.62
MonotonicityNot monotonic
2023-12-13T02:56:58.934758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
744 11
22.4%
527 7
14.3%
510 3
 
6.1%
720 3
 
6.1%
2232 2
 
4.1%
493 2
 
4.1%
2225 2
 
4.1%
737 2
 
4.1%
486 1
 
2.0%
1540 1
 
2.0%
Other values (12) 12
24.5%
(Missing) 3
 
6.1%
ValueCountFrequency (%)
272 1
 
2.0%
466 1
 
2.0%
486 1
 
2.0%
493 2
 
4.1%
503 1
 
2.0%
510 3
6.1%
527 7
14.3%
713 1
 
2.0%
720 3
6.1%
726 1
 
2.0%
ValueCountFrequency (%)
2232 2
4.1%
2225 2
4.1%
2183 1
2.0%
2160 1
2.0%
1581 1
2.0%
1540 1
2.0%
1452 1
2.0%
1292 1
2.0%
1054 1
2.0%
1013 1
2.0%

유효 측정시간
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct26
Distinct (%)56.5%
Missing3
Missing (%)6.1%
Infinite0
Infinite (%)0.0%
Mean1060.3478
Minimum383
Maximum2220
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-13T02:56:59.095701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum383
5-th percentile692.25
Q1717
median740
Q31259.5
95-th percentile2219.75
Maximum2220
Range1837
Interquartile range (IQR)542.5

Descriptive statistics

Standard deviation603.82467
Coefficient of variation (CV)0.56945905
Kurtosis-0.24320291
Mean1060.3478
Median Absolute Deviation (MAD)23.5
Skewness1.2531936
Sum48776
Variance364604.23
MonotonicityNot monotonic
2023-12-13T02:56:59.259725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
740 12
24.5%
741 5
 
10.2%
2220 3
 
6.1%
716 2
 
4.1%
717 2
 
4.1%
715 2
 
4.1%
673 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%
673 1
2.0%
692 1
2.0%
693 1
2.0%
695 1
2.0%
713 1
2.0%
714 1
2.0%
715 2
4.1%
716 2
4.1%
717 2
4.1%
ValueCountFrequency (%)
2220 3
6.1%
2219 1
 
2.0%
2218 1
 
2.0%
2183 1
 
2.0%
2176 1
 
2.0%
2145 1
 
2.0%
2058 1
 
2.0%
1816 1
 
2.0%
1481 1
 
2.0%
1432 1
 
2.0%

월평균 (ppm)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct29
Distinct (%)63.0%
Missing3
Missing (%)6.1%
Infinite0
Infinite (%)0.0%
Mean0.059043478
Minimum0.009
Maximum0.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-13T02:56:59.409773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.009
5-th percentile0.01225
Q10.01925
median0.026
Q30.03875
95-th percentile0.4
Maximum0.4
Range0.391
Interquartile range (IQR)0.0195

Descriptive statistics

Standard deviation0.10693299
Coefficient of variation (CV)1.811089
Kurtosis7.3027096
Mean0.059043478
Median Absolute Deviation (MAD)0.01
Skewness2.97597
Sum2.716
Variance0.011434665
MonotonicityNot monotonic
2023-12-13T02:56:59.623302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0.4 4
 
8.2%
0.022 3
 
6.1%
0.023 3
 
6.1%
0.015 2
 
4.1%
0.012 2
 
4.1%
0.02 2
 
4.1%
0.027 2
 
4.1%
0.021 2
 
4.1%
0.016 2
 
4.1%
0.029 2
 
4.1%
Other values (19) 22
44.9%
(Missing) 3
 
6.1%
ValueCountFrequency (%)
0.009 1
2.0%
0.012 2
4.1%
0.013 1
2.0%
0.014 2
4.1%
0.015 2
4.1%
0.016 2
4.1%
0.018 1
2.0%
0.019 1
2.0%
0.02 2
4.1%
0.021 2
4.1%
ValueCountFrequency (%)
0.4 4
8.2%
0.051 1
 
2.0%
0.049 1
 
2.0%
0.048 1
 
2.0%
0.047 1
 
2.0%
0.042 2
4.1%
0.04 1
 
2.0%
0.039 1
 
2.0%
0.038 1
 
2.0%
0.036 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

24시간치
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

2023-12-13T02:56:56.292841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:56:54.828256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:56:55.225666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:56:55.628361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:56:56.376700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:56:54.931167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:56:55.325349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:56:55.724974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:56:56.460522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:56:55.036701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:56:55.429489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:56:55.829445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:56:56.554112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:56:55.126713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:56:55.525841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:56:55.933639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:56:59.778344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시,도명측정소명유효 측정 일수유효 측정 횟수유효 측정시간월평균 (ppm)
시,도명1.000NaNNaN1.000NaN1.000
측정소명NaN1.0000.6970.6480.8700.000
유효\n측정\n일수NaN0.6971.0000.9211.0000.275
유효\n측정\n횟수1.0000.6480.9211.0001.0000.275
유효\n측정시간NaN0.8701.0001.0001.0000.245
월평균\n(ppm)1.0000.0000.2750.2750.2451.000
2023-12-13T02:56:59.939044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
측정소명도시명
측정소명1.0001.000
도시명1.0001.000
2023-12-13T02:57:00.059210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유효 측정 일수유효 측정 횟수유효 측정시간월평균 (ppm)도시명측정소명
유효\n측정\n일수1.0000.8790.973-0.1101.0000.514
유효\n측정\n횟수0.8791.0000.867-0.1521.0000.483
유효\n측정시간0.9730.8671.000-0.1181.0000.537
월평균\n(ppm)-0.110-0.152-0.1181.0001.0000.000
도시명1.0001.0001.0001.0001.0001.000
측정소명0.5140.4830.5370.0001.0001.000

Missing values

2023-12-13T02:56:56.700134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:56:56.941978image/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.
2023-12-13T02:56:57.177365image/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,도명도시명측정소명유효자료획득율 (%)유효 측정 일수유효 측정 횟수유효 측정시간월평균 (ppm)1시간치Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 1224시간치Unnamed: 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(%)
11월원주시중앙동99.46315277400.0160.0040.0462020012416000.0080.04120200127051200
2<NA><NA>반곡동99.46315277400.0150.0020.0472020012416000.0040.04620200127041100
3<NA><NA>문막읍99.46315277400.0140.0010.0522020013116000.0040.0420200127091600
4<NA><NA>도시평균99.4693158122200.0150.0010.0522020013116000.0040.04620200127041100
52월원주시중앙동99.57294936930.0220.0040.0542020022017000.0090.04620200215142100
6<NA><NA>반곡동99.43294936920.0230.0020.0622020022116000.0060.05620200215142100
7<NA><NA>문막읍96.7264666730.0220.0010.0532020022116000.0150.04520200222132000
8<NA><NA>도시평균98.5684145220580.0230.0010.0622020022116000.0060.05620200215142100
93월원주시중앙동99.46315277400.0310.0040.0792020032517000.0330.0720200325121930.57
시,도명도시명측정소명유효자료획득율 (%)유효 측정 일수유효 측정 횟수유효 측정시간월평균 (ppm)1시간치Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 1224시간치Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17
39<NA><NA>문막읍99.46317447400.0210.0010.0792020102716000.0220.05820201019111800
40<NA><NA>도시평균99.4693223222200.0190.0010.0792020102716000.010.05820201019111800
4111월원주시중앙동99.46317447400.40.10.92020102719000.30.820201027162300
42<NA><NA>반곡동99.46317447400.40.30.92020102809000.30.820201027180100
43<NA><NA>문막읍99.46317447400.40.30.92020102809000.30.820201028020900
44<NA><NA>도시평균99.4693223222200.40.10.92020102809000.30.820201027162300
4512월원주시중앙동99.6317447410.0130.0030.0442020122815000.0090.03720201212121900
46<NA><NA>반곡동99.46317447400.0090.0020.0312020122404000.0060.02320201212111800
47<NA><NA>문막읍99.06307377370.0120.0010.0532020122815000.0070.03620201207142100
48<NA><NA>도시평균99.3792222522180.0120.0010.0532020122815000.0060.03720201212121900

Duplicate rows

Most frequently occurring

시,도명도시명측정소명유효 측정 일수유효 측정 횟수유효 측정시간월평균 (ppm)# duplicates
0<NA><NA>반곡동<NA><NA><NA><NA>2