Overview

Dataset statistics

Number of variables7
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory693.4 KiB
Average record size in memory71.0 B

Variable types

Numeric5
Categorical2

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15526/S/1/datasetView.do

Alerts

평균값 is highly overall correlated with 측정기 상태High correlation
측정기 상태 is highly overall correlated with 평균값High correlation
국가 기준초과 구분 is highly overall correlated with 지자체 기준초과 구분High correlation
지자체 기준초과 구분 is highly overall correlated with 국가 기준초과 구분High correlation
국가 기준초과 구분 is highly imbalanced (89.4%)Imbalance
지자체 기준초과 구분 is highly imbalanced (84.0%)Imbalance
평균값 has 232 (2.3%) zerosZeros
측정기 상태 has 7272 (72.7%) zerosZeros

Reproduction

Analysis started2024-05-04 04:00:54.450908
Analysis finished2024-05-04 04:01:03.427774
Duration8.98 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

측정일시
Real number (ℝ)

Distinct667
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0010114 × 109
Minimum2.0010101 × 109
Maximum2.0010128 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T04:01:03.643674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0010101 × 109
5-th percentile2.0010102 × 109
Q12.0010107 × 109
median2.0010114 × 109
Q32.0010121 × 109
95-th percentile2.0010127 × 109
Maximum2.0010128 × 109
Range2718
Interquartile range (IQR)1397

Descriptive statistics

Standard deviation800.93825
Coefficient of variation (CV)4.002667 × 10-7
Kurtosis-1.2004567
Mean2.0010114 × 109
Median Absolute Deviation (MAD)699
Skewness-0.00114414
Sum2.0010114 × 1013
Variance641502.08
MonotonicityNot monotonic
2024-05-04T04:01:04.251183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2001012416 28
 
0.3%
2001012518 28
 
0.3%
2001011706 25
 
0.2%
2001010514 25
 
0.2%
2001012308 25
 
0.2%
2001010806 25
 
0.2%
2001011501 24
 
0.2%
2001012506 24
 
0.2%
2001010623 24
 
0.2%
2001010109 24
 
0.2%
Other values (657) 9748
97.5%
ValueCountFrequency (%)
2001010100 16
0.2%
2001010101 16
0.2%
2001010102 15
0.1%
2001010103 15
0.1%
2001010104 17
0.2%
2001010105 13
0.1%
2001010106 19
0.2%
2001010107 8
 
0.1%
2001010108 16
0.2%
2001010109 24
0.2%
ValueCountFrequency (%)
2001012818 3
 
< 0.1%
2001012817 17
0.2%
2001012816 17
0.2%
2001012815 10
0.1%
2001012814 12
0.1%
2001012813 13
0.1%
2001012812 11
0.1%
2001012811 12
0.1%
2001012810 10
0.1%
2001012809 14
0.1%

측정소 코드
Real number (ℝ)

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean112.936
Minimum101
Maximum125
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T04:01:04.671776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile102
Q1107
median113
Q3119
95-th percentile124
Maximum125
Range24
Interquartile range (IQR)12

Descriptive statistics

Standard deviation7.1690616
Coefficient of variation (CV)0.063478975
Kurtosis-1.1934948
Mean112.936
Median Absolute Deviation (MAD)6
Skewness0.013939591
Sum1129360
Variance51.395444
MonotonicityNot monotonic
2024-05-04T04:01:05.172553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
106 443
 
4.4%
118 436
 
4.4%
111 434
 
4.3%
102 432
 
4.3%
110 412
 
4.1%
122 410
 
4.1%
124 408
 
4.1%
108 407
 
4.1%
107 407
 
4.1%
115 405
 
4.0%
Other values (15) 5806
58.1%
ValueCountFrequency (%)
101 387
3.9%
102 432
4.3%
103 370
3.7%
104 368
3.7%
105 404
4.0%
106 443
4.4%
107 407
4.1%
108 407
4.1%
109 400
4.0%
110 412
4.1%
ValueCountFrequency (%)
125 371
3.7%
124 408
4.1%
123 384
3.8%
122 410
4.1%
121 376
3.8%
120 394
3.9%
119 391
3.9%
118 436
4.4%
117 397
4.0%
116 377
3.8%

측정항목
Real number (ℝ)

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.432
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T04:01:05.505268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q38
95-th percentile9
Maximum9
Range8
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.7467309
Coefficient of variation (CV)0.50565738
Kurtosis-1.1958416
Mean5.432
Median Absolute Deviation (MAD)3
Skewness-0.23951616
Sum54320
Variance7.5445305
MonotonicityNot monotonic
2024-05-04T04:01:05.834377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
9 1789
17.9%
8 1715
17.2%
5 1694
16.9%
3 1651
16.5%
6 1585
15.8%
1 1566
15.7%
ValueCountFrequency (%)
1 1566
15.7%
3 1651
16.5%
5 1694
16.9%
6 1585
15.8%
8 1715
17.2%
9 1789
17.9%
ValueCountFrequency (%)
9 1789
17.9%
8 1715
17.2%
6 1585
15.8%
5 1694
16.9%
3 1651
16.5%
1 1566
15.7%

평균값
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct387
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-1828.1401
Minimum-9999
Maximum941
Zeros232
Zeros (%)2.3%
Negative2419
Negative (%)24.2%
Memory size166.0 KiB
2024-05-04T04:01:06.371099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-9999
5-th percentile-9999
Q10
median0.015
Q31
95-th percentile77
Maximum941
Range10940
Interquartile range (IQR)1

Descriptive statistics

Standard deviation3861.0667
Coefficient of variation (CV)-2.1120191
Kurtosis0.69966428
Mean-1828.1401
Median Absolute Deviation (MAD)0.885
Skewness-1.6407694
Sum-18281401
Variance14907836
MonotonicityNot monotonic
2024-05-04T04:01:06.820217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-9999.0 1823
 
18.2%
-9.999 411
 
4.1%
0.005 236
 
2.4%
0.004 235
 
2.4%
0.0 232
 
2.3%
0.002 230
 
2.3%
0.006 208
 
2.1%
0.001 204
 
2.0%
0.003 192
 
1.9%
0.007 162
 
1.6%
Other values (377) 6067
60.7%
ValueCountFrequency (%)
-9999.0 1823
18.2%
-3276.8 5
 
0.1%
-999.9 149
 
1.5%
-32.768 25
 
0.2%
-9.999 411
 
4.1%
-8.9 1
 
< 0.1%
-4.4 1
 
< 0.1%
-1.2 4
 
< 0.1%
0.0 232
 
2.3%
0.001 204
 
2.0%
ValueCountFrequency (%)
941.0 1
< 0.1%
903.0 1
< 0.1%
860.0 1
< 0.1%
829.0 1
< 0.1%
819.0 1
< 0.1%
780.0 1
< 0.1%
757.0 1
< 0.1%
701.0 1
< 0.1%
651.0 1
< 0.1%
598.0 1
< 0.1%

측정기 상태
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.0447
Minimum0
Maximum9
Zeros7272
Zeros (%)72.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T04:01:07.153398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile4
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.7731374
Coefficient of variation (CV)1.6972695
Kurtosis0.42588548
Mean1.0447
Median Absolute Deviation (MAD)0
Skewness1.3030879
Sum10447
Variance3.1440163
MonotonicityNot monotonic
2024-05-04T04:01:07.536345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 7272
72.7%
4 2364
 
23.6%
2 280
 
2.8%
1 38
 
0.4%
9 25
 
0.2%
8 21
 
0.2%
ValueCountFrequency (%)
0 7272
72.7%
1 38
 
0.4%
2 280
 
2.8%
4 2364
 
23.6%
8 21
 
0.2%
9 25
 
0.2%
ValueCountFrequency (%)
9 25
 
0.2%
8 21
 
0.2%
4 2364
 
23.6%
2 280
 
2.8%
1 38
 
0.4%
0 7272
72.7%

국가 기준초과 구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9860 
1
 
140

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 9860
98.6%
1 140
 
1.4%

Length

2024-05-04T04:01:07.935449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T04:01:08.234258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 9860
98.6%
1 140
 
1.4%

지자체 기준초과 구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9767 
1
 
233

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 9767
97.7%
1 233
 
2.3%

Length

2024-05-04T04:01:08.788247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T04:01:09.103978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 9767
97.7%
1 233
 
2.3%

Interactions

2024-05-04T04:01:00.716948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:00:56.025756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:00:57.137770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:00:58.230934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:00:59.441828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:01:01.034386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:00:56.251615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:00:57.407310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:00:58.454977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:00:59.727859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:01:01.317354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:00:56.467946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:00:57.670695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:00:58.727759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:00:59.990120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:01:01.655381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:00:56.660987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:00:57.900944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:00:58.968714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:01:00.280746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:01:02.015872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:00:56.880559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:00:58.070253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:00:59.173715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:01:00.489702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-04T04:01:09.315200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
측정일시측정소 코드측정항목평균값측정기 상태국가 기준초과 구분지자체 기준초과 구분
측정일시1.0000.0000.0150.1890.2100.2570.300
측정소 코드0.0001.0000.0180.1730.3200.0700.077
측정항목0.0150.0181.0000.4170.7250.3120.432
평균값0.1890.1730.4171.0000.6540.0060.011
측정기 상태0.2100.3200.7250.6541.0000.1470.139
국가 기준초과 구분0.2570.0700.3120.0060.1471.0000.931
지자체 기준초과 구분0.3000.0770.4320.0110.1390.9311.000
2024-05-04T04:01:09.646670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지자체 기준초과 구분국가 기준초과 구분
지자체 기준초과 구분1.0000.763
국가 기준초과 구분0.7631.000
2024-05-04T04:01:09.892591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
측정일시측정소 코드측정항목평균값측정기 상태국가 기준초과 구분지자체 기준초과 구분
측정일시1.000-0.012-0.0220.114-0.1260.1970.230
측정소 코드-0.0121.000-0.020-0.016-0.0090.0540.059
측정항목-0.022-0.0201.000-0.1310.4970.2240.311
평균값0.114-0.016-0.1311.000-0.7230.0570.075
측정기 상태-0.126-0.0090.497-0.7231.0000.1060.100
국가 기준초과 구분0.1970.0540.2240.0570.1061.0000.763
지자체 기준초과 구분0.2300.0590.3110.0750.1000.7631.000

Missing values

2024-05-04T04:01:02.632157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-04T04:01:03.135243image/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

측정일시측정소 코드측정항목평균값측정기 상태국가 기준초과 구분지자체 기준초과 구분
19998200101061310910.003000
84984200101241411510.006000
224442001010705116821.0000
21614200101070010350.6000
1467520010105011219-9999.0400
42307200101121810230.028000
3947920010111231059-9999.0400
28603200101082211830.035000
2618320010108061149-9999.0400
79435200101230111530.038000
측정일시측정소 코드측정항목평균값측정기 상태국가 기준초과 구분지자체 기준초과 구분
67278200101191611410.022000
22884200101070811510.001000
4567200101020611230.052000
691720010102221039-9999.0400
91334200101260812351.9000
6772620010119191138103.0000
637002001011816117894.0000
50466200101150011210.003000
42207200101121711060.011000
1491120010105031113-9.999400