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 (98.6%)Imbalance
지자체 기준초과 구분 is highly imbalanced (96.7%)Imbalance
평균값 has 353 (3.5%) zerosZeros
측정기 상태 has 6781 (67.8%) zerosZeros

Reproduction

Analysis started2024-05-04 04:01:55.121855
Analysis finished2024-05-04 04:02:05.607904
Duration10.49 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

측정일시
Real number (ℝ)

Distinct583
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0000113 × 109
Minimum2.0000101 × 109
Maximum2.0000125 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T04:02:05.830815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0000101 × 109
5-th percentile2.0000102 × 109
Q12.0000107 × 109
median2.0000112 × 109
Q32.0000119 × 109
95-th percentile2.0000124 × 109
Maximum2.0000125 × 109
Range2406
Interquartile range (IQR)1203

Descriptive statistics

Standard deviation700.52126
Coefficient of variation (CV)3.5025866 × 10-7
Kurtosis-1.199604
Mean2.0000113 × 109
Median Absolute Deviation (MAD)602
Skewness0.021984439
Sum2.0000113 × 1013
Variance490730.03
MonotonicityNot monotonic
2024-05-04T04:02:06.234785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2000010705 30
 
0.3%
2000010414 28
 
0.3%
2000010706 28
 
0.3%
2000012315 27
 
0.3%
2000011216 27
 
0.3%
2000011313 27
 
0.3%
2000010914 26
 
0.3%
2000010313 26
 
0.3%
2000011618 26
 
0.3%
2000011205 25
 
0.2%
Other values (573) 9730
97.3%
ValueCountFrequency (%)
2000010100 18
0.2%
2000010101 14
0.1%
2000010102 21
0.2%
2000010103 20
0.2%
2000010104 15
0.1%
2000010105 17
0.2%
2000010106 18
0.2%
2000010107 14
0.1%
2000010108 19
0.2%
2000010109 17
0.2%
ValueCountFrequency (%)
2000012506 12
0.1%
2000012505 17
0.2%
2000012504 14
0.1%
2000012503 13
0.1%
2000012502 14
0.1%
2000012501 18
0.2%
2000012500 18
0.2%
2000012423 18
0.2%
2000012422 13
0.1%
2000012421 22
0.2%

측정소 코드
Real number (ℝ)

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean112.7874
Minimum101
Maximum125
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T04:02:06.660543image/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 deviation7.1973454
Coefficient of variation (CV)0.063813382
Kurtosis-1.2066641
Mean112.7874
Median Absolute Deviation (MAD)6
Skewness0.041144931
Sum1127874
Variance51.801781
MonotonicityNot monotonic
2024-05-04T04:02:07.054182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
103 463
 
4.6%
117 440
 
4.4%
107 437
 
4.4%
122 420
 
4.2%
108 420
 
4.2%
102 415
 
4.2%
106 414
 
4.1%
110 413
 
4.1%
112 412
 
4.1%
118 411
 
4.1%
Other values (15) 5755
57.6%
ValueCountFrequency (%)
101 385
3.9%
102 415
4.2%
103 463
4.6%
104 402
4.0%
105 401
4.0%
106 414
4.1%
107 437
4.4%
108 420
4.2%
109 384
3.8%
110 413
4.1%
ValueCountFrequency (%)
125 377
3.8%
124 388
3.9%
123 357
3.6%
122 420
4.2%
121 381
3.8%
120 396
4.0%
119 348
3.5%
118 411
4.1%
117 440
4.4%
116 378
3.8%

측정항목
Real number (ℝ)

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.319
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T04:02:07.399779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median5
Q38
95-th percentile9
Maximum9
Range8
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.7420049
Coefficient of variation (CV)0.51551136
Kurtosis-1.2026796
Mean5.319
Median Absolute Deviation (MAD)2
Skewness-0.19884851
Sum53190
Variance7.5185909
MonotonicityNot monotonic
2024-05-04T04:02:07.754623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
5 1745
17.4%
8 1680
16.8%
1 1670
16.7%
3 1657
16.6%
9 1632
16.3%
6 1616
16.2%
ValueCountFrequency (%)
1 1670
16.7%
3 1657
16.6%
5 1745
17.4%
6 1616
16.2%
8 1680
16.8%
9 1632
16.3%
ValueCountFrequency (%)
9 1632
16.3%
8 1680
16.8%
6 1616
16.2%
5 1745
17.4%
3 1657
16.6%
1 1670
16.7%

평균값
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct259
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-2036.5449
Minimum-9999
Maximum194
Zeros353
Zeros (%)3.5%
Negative2990
Negative (%)29.9%
Memory size166.0 KiB
2024-05-04T04:02:08.180136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-9999
5-th percentile-9999
Q1-9.999
median0.008
Q30.1
95-th percentile42
Maximum194
Range10193
Interquartile range (IQR)10.099

Descriptive statistics

Standard deviation4004.396
Coefficient of variation (CV)-1.9662695
Kurtosis0.20536988
Mean-2036.5449
Median Absolute Deviation (MAD)0.292
Skewness-1.4824024
Sum-20365449
Variance16035188
MonotonicityNot monotonic
2024-05-04T04:02:08.654337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-9999.0 2016
 
20.2%
-9.999 725
 
7.2%
0.0 353
 
3.5%
0.1 291
 
2.9%
0.004 263
 
2.6%
-999.9 248
 
2.5%
0.003 231
 
2.3%
0.002 228
 
2.3%
0.005 223
 
2.2%
0.006 216
 
2.2%
Other values (249) 5206
52.1%
ValueCountFrequency (%)
-9999.0 2016
20.2%
-999.9 248
 
2.5%
-9.999 725
 
7.2%
-0.286 1
 
< 0.1%
0.0 353
 
3.5%
0.001 144
 
1.4%
0.002 228
 
2.3%
0.003 231
 
2.3%
0.004 263
 
2.6%
0.005 223
 
2.2%
ValueCountFrequency (%)
194.0 1
< 0.1%
187.0 1
< 0.1%
176.0 1
< 0.1%
172.0 1
< 0.1%
171.0 1
< 0.1%
169.0 1
< 0.1%
168.0 1
< 0.1%
162.0 1
< 0.1%
155.0 1
< 0.1%
152.0 1
< 0.1%

측정기 상태
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2708
Minimum0
Maximum9
Zeros6781
Zeros (%)67.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T04:02:09.013949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34
95-th percentile4
Maximum9
Range9
Interquartile range (IQR)4

Descriptive statistics

Standard deviation1.8784622
Coefficient of variation (CV)1.478173
Kurtosis-0.88324923
Mean1.2708
Median Absolute Deviation (MAD)0
Skewness0.89106979
Sum12708
Variance3.5286202
MonotonicityNot monotonic
2024-05-04T04:02:09.489953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 6781
67.8%
4 3046
30.5%
2 114
 
1.1%
8 27
 
0.3%
1 26
 
0.3%
9 6
 
0.1%
ValueCountFrequency (%)
0 6781
67.8%
1 26
 
0.3%
2 114
 
1.1%
4 3046
30.5%
8 27
 
0.3%
9 6
 
0.1%
ValueCountFrequency (%)
9 6
 
0.1%
8 27
 
0.3%
4 3046
30.5%
2 114
 
1.1%
1 26
 
0.3%
0 6781
67.8%

국가 기준초과 구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9987 
1
 
13

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 9987
99.9%
1 13
 
0.1%

Length

2024-05-04T04:02:09.908532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T04:02:10.232275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 9987
99.9%
1 13
 
0.1%

지자체 기준초과 구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9966 
1
 
34

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 9966
99.7%
1 34
 
0.3%

Length

2024-05-04T04:02:10.525654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T04:02:10.832387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 9966
99.7%
1 34
 
0.3%

Interactions

2024-05-04T04:02:03.261922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:01:57.100186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:01:58.662649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:02:00.108968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:02:01.731531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:02:03.794353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:01:57.365704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:01:58.924580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:02:00.433946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:02:02.010615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:02:04.135170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:01:57.636367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:01:59.186171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:02:00.730058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:02:02.376085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:02:04.471994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:01:58.147656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:01:59.488142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:02:01.065837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:02:02.660156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:02:04.728009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:01:58.405557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:01:59.768045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:02:01.389798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T04:02:02.964041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-04T04:02:11.035653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
측정일시측정소 코드측정항목평균값측정기 상태국가 기준초과 구분지자체 기준초과 구분
측정일시1.0000.0000.0000.0500.1360.0510.084
측정소 코드0.0001.0000.0000.4240.3390.0510.080
측정항목0.0000.0001.0000.2770.6790.0970.172
평균값0.0500.4240.2771.0000.6220.0000.000
측정기 상태0.1360.3390.6790.6221.0000.0720.061
국가 기준초과 구분0.0510.0510.0970.0000.0721.0000.803
지자체 기준초과 구분0.0840.0800.1720.0000.0610.8031.000
2024-05-04T04:02:11.383141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지자체 기준초과 구분국가 기준초과 구분
지자체 기준초과 구분1.0000.594
국가 기준초과 구분0.5941.000
2024-05-04T04:02:11.689457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
측정일시측정소 코드측정항목평균값측정기 상태국가 기준초과 구분지자체 기준초과 구분
측정일시1.0000.0030.0200.028-0.0140.0390.062
측정소 코드0.0031.0000.0020.156-0.2220.0390.061
측정항목0.0200.0021.000-0.2560.4740.0700.123
평균값0.0280.156-0.2561.000-0.7960.0130.028
측정기 상태-0.014-0.2220.474-0.7961.0000.0520.044
국가 기준초과 구분0.0390.0390.0700.0130.0521.0000.594
지자체 기준초과 구분0.0620.0610.1230.0280.0440.5941.000

Missing values

2024-05-04T04:02:05.065419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-04T04:02:05.465676image/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
1945720000106091189-9999.0400
23184200001071011510.001000
81744200001231612510.001000
8663920000125011159-9999.0400
28249200001082010930.042000
3395920000110101109-9999.0400
23354200001071111850.8000
69260200001200511950.0000
2173200001011411330.023000
52830200001151610610.005000
측정일시측정소 코드측정항목평균값측정기 상태국가 기준초과 구분지자체 기준초과 구분
56526200001161612210.006000
70102200001201110983.0000
55584200001161011510.012000
2702320000108121049-9999.0400
818920000103061159-9999.0400
6786520000119201119-9999.0400
376182000011110120876.0000
35414200001102010351.1000
8553520000124181069-9999.0400
43662200001130310310.004000