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 (95.9%)Imbalance
지자체 기준초과 구분 is highly imbalanced (90.7%)Imbalance
평균값 has 310 (3.1%) zerosZeros
측정기 상태 has 6022 (60.2%) zerosZeros

Reproduction

Analysis started2024-04-27 12:08:14.056485
Analysis finished2024-04-27 12:08:22.106176
Duration8.05 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

측정일시
Real number (ℝ)

Distinct570
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9990112 × 109
Minimum1.9990101 × 109
Maximum1.9990124 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-27T12:08:22.263012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990101 × 109
5-th percentile1.9990102 × 109
Q11.9990107 × 109
median1.9990112 × 109
Q31.9990118 × 109
95-th percentile1.9990123 × 109
Maximum1.9990124 × 109
Range2317
Interquartile range (IQR)1115

Descriptive statistics

Standard deviation679.9902
Coefficient of variation (CV)3.4016327 × 10-7
Kurtosis-1.1813133
Mean1.9990112 × 109
Median Absolute Deviation (MAD)595
Skewness-0.00086168503
Sum1.9990112 × 1013
Variance462386.68
MonotonicityNot monotonic
2024-04-27T12:08:22.541759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1999011621 29
 
0.3%
1999011401 28
 
0.3%
1999010603 28
 
0.3%
1999010214 27
 
0.3%
1999011315 27
 
0.3%
1999011205 27
 
0.3%
1999011714 27
 
0.3%
1999010202 26
 
0.3%
1999011921 26
 
0.3%
1999011312 26
 
0.3%
Other values (560) 9729
97.3%
ValueCountFrequency (%)
1999010100 10
0.1%
1999010101 18
0.2%
1999010102 15
0.1%
1999010103 24
0.2%
1999010104 21
0.2%
1999010105 13
0.1%
1999010106 21
0.2%
1999010107 17
0.2%
1999010108 20
0.2%
1999010109 24
0.2%
ValueCountFrequency (%)
1999012417 9
0.1%
1999012416 16
0.2%
1999012415 15
0.1%
1999012414 15
0.1%
1999012413 16
0.2%
1999012412 19
0.2%
1999012411 21
0.2%
1999012410 20
0.2%
1999012409 15
0.1%
1999012408 19
0.2%

측정소 코드
Real number (ℝ)

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean113.0235
Minimum101
Maximum125
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-27T12:08:22.802671image/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 deviation7.2236948
Coefficient of variation (CV)0.063913211
Kurtosis-1.2107436
Mean113.0235
Median Absolute Deviation (MAD)6
Skewness-0.0097533089
Sum1130235
Variance52.181766
MonotonicityNot monotonic
2024-04-27T12:08:23.206640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
122 436
 
4.4%
115 428
 
4.3%
120 420
 
4.2%
117 415
 
4.2%
103 415
 
4.2%
106 414
 
4.1%
102 414
 
4.1%
111 411
 
4.1%
116 410
 
4.1%
107 408
 
4.1%
Other values (15) 5829
58.3%
ValueCountFrequency (%)
101 395
4.0%
102 414
4.1%
103 415
4.2%
104 386
3.9%
105 377
3.8%
106 414
4.1%
107 408
4.1%
108 383
3.8%
109 401
4.0%
110 401
4.0%
ValueCountFrequency (%)
125 398
4.0%
124 403
4.0%
123 384
3.8%
122 436
4.4%
121 378
3.8%
120 420
4.2%
119 406
4.1%
118 388
3.9%
117 415
4.2%
116 410
4.1%

측정항목
Real number (ℝ)

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.3189
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-27T12:08:23.570237image/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 deviation2.7650619
Coefficient of variation (CV)0.51985597
Kurtosis-1.2372694
Mean5.3189
Median Absolute Deviation (MAD)3
Skewness-0.18916866
Sum53189
Variance7.6455673
MonotonicityNot monotonic
2024-04-27T12:08:23.912881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3 1735
17.3%
8 1691
16.9%
9 1680
16.8%
1 1678
16.8%
5 1638
16.4%
6 1578
15.8%
ValueCountFrequency (%)
1 1678
16.8%
3 1735
17.3%
5 1638
16.4%
6 1578
15.8%
8 1691
16.9%
9 1680
16.8%
ValueCountFrequency (%)
9 1680
16.8%
8 1691
16.9%
6 1578
15.8%
5 1638
16.4%
3 1735
17.3%
1 1678
16.8%

평균값
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct342
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-2248.914
Minimum-9999
Maximum1746
Zeros310
Zeros (%)3.1%
Negative3695
Negative (%)37.0%
Memory size166.0 KiB
2024-04-27T12:08:24.541294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-9999
5-th percentile-9999
Q1-999.9
median0.006
Q30.054
95-th percentile61
Maximum1746
Range11745
Interquartile range (IQR)999.954

Descriptive statistics

Standard deviation4143.5648
Coefficient of variation (CV)-1.8424737
Kurtosis-0.21721077
Mean-2248.914
Median Absolute Deviation (MAD)2.094
Skewness-1.3311283
Sum-22489140
Variance17169129
MonotonicityNot monotonic
2024-04-27T12:08:24.948667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-9999.0 2219
22.2%
-9.999 1101
 
11.0%
-999.9 372
 
3.7%
0.0 310
 
3.1%
0.001 225
 
2.2%
0.004 172
 
1.7%
0.002 166
 
1.7%
0.005 160
 
1.6%
0.009 158
 
1.6%
0.008 156
 
1.6%
Other values (332) 4961
49.6%
ValueCountFrequency (%)
-9999.0 2219
22.2%
-999.9 372
 
3.7%
-9.999 1101
11.0%
-0.438 1
 
< 0.1%
-0.432 1
 
< 0.1%
-0.236 1
 
< 0.1%
0.0 310
 
3.1%
0.001 225
 
2.2%
0.002 166
 
1.7%
0.003 147
 
1.5%
ValueCountFrequency (%)
1746.0 1
< 0.1%
1711.0 1
< 0.1%
1503.0 1
< 0.1%
1431.0 1
< 0.1%
1406.0 1
< 0.1%
1272.0 1
< 0.1%
1140.0 1
< 0.1%
872.0 1
< 0.1%
604.0 1
< 0.1%
457.0 1
< 0.1%

측정기 상태
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5774
Minimum0
Maximum9
Zeros6022
Zeros (%)60.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-27T12:08:25.221418image/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 deviation1.9729162
Coefficient of variation (CV)1.2507393
Kurtosis-1.4241996
Mean1.5774
Median Absolute Deviation (MAD)0
Skewness0.53342752
Sum15774
Variance3.8923985
MonotonicityNot monotonic
2024-04-27T12:08:25.575742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 6022
60.2%
4 3809
38.1%
2 116
 
1.2%
8 27
 
0.3%
1 18
 
0.2%
9 8
 
0.1%
ValueCountFrequency (%)
0 6022
60.2%
1 18
 
0.2%
2 116
 
1.2%
4 3809
38.1%
8 27
 
0.3%
9 8
 
0.1%
ValueCountFrequency (%)
9 8
 
0.1%
8 27
 
0.3%
4 3809
38.1%
2 116
 
1.2%
1 18
 
0.2%
0 6022
60.2%

국가 기준초과 구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9956 
1
 
44

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 9956
99.6%
1 44
 
0.4%

Length

2024-04-27T12:08:25.888475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-27T12:08:26.253954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 9956
99.6%
1 44
 
0.4%

지자체 기준초과 구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9882 
1
 
118

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 9882
98.8%
1 118
 
1.2%

Length

2024-04-27T12:08:26.597311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-27T12:08:27.020693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 9882
98.8%
1 118
 
1.2%

Interactions

2024-04-27T12:08:20.478259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:08:15.753471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:08:17.172078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:08:18.463344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:08:19.533533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:08:20.646926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:08:16.042197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:08:17.443486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:08:18.738908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:08:19.710239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:08:20.839988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:08:16.323937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:08:17.729025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:08:18.935173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:08:19.891060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:08:21.108088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:08:16.618425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:08:17.949944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:08:19.174463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:08:20.091510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:08:21.325937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:08:16.941654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:08:18.209421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:08:19.359662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:08:20.309790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-27T12:08:27.266980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
측정일시측정소 코드측정항목평균값측정기 상태국가 기준초과 구분지자체 기준초과 구분
측정일시1.0000.0000.0000.0880.1000.0870.114
측정소 코드0.0001.0000.0070.2730.3250.1030.113
측정항목0.0000.0071.0000.3800.6190.2030.335
평균값0.0880.2730.3801.0000.6720.2780.167
측정기 상태0.1000.3250.6190.6721.0000.1920.154
국가 기준초과 구분0.0870.1030.2030.2780.1921.0000.810
지자체 기준초과 구분0.1140.1130.3350.1670.1540.8101.000
2024-04-27T12:08:27.524377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지자체 기준초과 구분국가 기준초과 구분
지자체 기준초과 구분1.0000.601
국가 기준초과 구분0.6011.000
2024-04-27T12:08:27.810513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
측정일시측정소 코드측정항목평균값측정기 상태국가 기준초과 구분지자체 기준초과 구분
측정일시1.0000.003-0.0090.052-0.0660.0670.087
측정소 코드0.0031.0000.0140.041-0.0330.0790.087
측정항목-0.0090.0141.000-0.3510.4470.1460.241
평균값0.0520.041-0.3511.000-0.8360.4520.281
측정기 상태-0.066-0.0330.447-0.8361.0000.1380.111
국가 기준초과 구분0.0670.0790.1460.4520.1381.0000.601
지자체 기준초과 구분0.0870.0870.2410.2810.1110.6011.000

Missing values

2024-04-27T12:08:21.636272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-27T12:08:21.873696image/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
50641199901150111630.053000
40719199901120711260.0000
3267519990110011219-9999.0400
1690819990105161191-9.999400
26096199901080512550.4000
3213119990109221063-9.999400
31061999010120118844.0000
18114199901060012010.027000
35037199901101711560.012000
23517199901071212060.018000
측정일시측정소 코드측정항목평균값측정기 상태국가 기준초과 구분지자체 기준초과 구분
5896819990117091041-9.999400
24079199901071611430.013000
6156419990118021118-9999.0400
3602319990111001049-9999.0400
83545199901240412530.021000
724061999012102118846.0000
1954619990106101088-9999.0400
7503519990121201069-9999.0400
3814419990111141085-999.9400
1310319990104151099-9999.0400