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

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 (70.3%)Imbalance
지자체 기준초과 구분 is highly imbalanced (70.3%)Imbalance
평균값 has 154 (1.5%) zerosZeros
측정기 상태 has 9229 (92.3%) zerosZeros

Reproduction

Analysis started2024-05-11 06:57:42.452154
Analysis finished2024-05-11 06:57:47.742018
Duration5.29 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

측정일시
Real number (ℝ)

Distinct566
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0070112 × 109
Minimum2.0070101 × 109
Maximum2.0070124 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:57:47.841426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0070101 × 109
5-th percentile2.0070102 × 109
Q12.0070106 × 109
median2.0070112 × 109
Q32.0070118 × 109
95-th percentile2.0070123 × 109
Maximum2.0070124 × 109
Range2313
Interquartile range (IQR)1197

Descriptive statistics

Standard deviation686.81627
Coefficient of variation (CV)3.4220848 × 10-7
Kurtosis-1.2065903
Mean2.0070112 × 109
Median Absolute Deviation (MAD)599
Skewness0.0078732948
Sum2.0070112 × 1013
Variance471716.58
MonotonicityNot monotonic
2024-05-11T15:57:48.084840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2007010401 28
 
0.3%
2007012316 28
 
0.3%
2007010302 28
 
0.3%
2007010814 28
 
0.3%
2007010114 27
 
0.3%
2007011517 27
 
0.3%
2007010621 27
 
0.3%
2007011216 27
 
0.3%
2007010106 27
 
0.3%
2007010710 26
 
0.3%
Other values (556) 9727
97.3%
ValueCountFrequency (%)
2007010100 16
0.2%
2007010101 20
0.2%
2007010102 14
0.1%
2007010103 16
0.2%
2007010104 20
0.2%
2007010105 16
0.2%
2007010106 27
0.3%
2007010107 16
0.2%
2007010108 18
0.2%
2007010109 22
0.2%
ValueCountFrequency (%)
2007012413 19
0.2%
2007012412 19
0.2%
2007012411 16
0.2%
2007012410 16
0.2%
2007012409 20
0.2%
2007012408 19
0.2%
2007012407 25
0.2%
2007012406 23
0.2%
2007012405 14
0.1%
2007012404 16
0.2%

측정소 코드
Real number (ℝ)

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean112.8982
Minimum101
Maximum125
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:57:48.301966image/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 deviation7.1846641
Coefficient of variation (CV)0.063638429
Kurtosis-1.1895578
Mean112.8982
Median Absolute Deviation (MAD)6
Skewness-0.0015054535
Sum1128982
Variance51.619399
MonotonicityNot monotonic
2024-05-11T15:57:48.464671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
101 444
 
4.4%
117 421
 
4.2%
111 420
 
4.2%
114 419
 
4.2%
113 418
 
4.2%
121 418
 
4.2%
116 417
 
4.2%
115 415
 
4.2%
118 415
 
4.2%
106 407
 
4.1%
Other values (15) 5806
58.1%
ValueCountFrequency (%)
101 444
4.4%
102 389
3.9%
103 404
4.0%
104 404
4.0%
105 391
3.9%
106 407
4.1%
107 403
4.0%
108 403
4.0%
109 365
3.6%
110 380
3.8%
ValueCountFrequency (%)
125 385
3.9%
124 357
3.6%
123 388
3.9%
122 388
3.9%
121 418
4.2%
120 401
4.0%
119 362
3.6%
118 415
4.2%
117 421
4.2%
116 417
4.2%

측정항목
Real number (ℝ)

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.3213
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:57:48.580668image/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 deviation2.769013
Coefficient of variation (CV)0.52036401
Kurtosis-1.231943
Mean5.3213
Median Absolute Deviation (MAD)3
Skewness-0.19981145
Sum53213
Variance7.6674331
MonotonicityNot monotonic
2024-05-11T15:57:48.693320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 1711
17.1%
8 1705
17.1%
9 1672
16.7%
5 1672
16.7%
3 1662
16.6%
6 1578
15.8%
ValueCountFrequency (%)
1 1711
17.1%
3 1662
16.6%
5 1672
16.7%
6 1578
15.8%
8 1705
17.1%
9 1672
16.7%
ValueCountFrequency (%)
9 1672
16.7%
8 1705
17.1%
6 1578
15.8%
5 1672
16.7%
3 1662
16.6%
1 1711
17.1%

평균값
Real number (ℝ)

ZEROS 

Distinct327
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-299.64771
Minimum-9999
Maximum231
Zeros154
Zeros (%)1.5%
Negative488
Negative (%)4.9%
Memory size166.0 KiB
2024-05-11T15:57:48.857111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-9999
5-th percentile0
Q10.009
median0.057
Q324
95-th percentile83
Maximum231
Range10230
Interquartile range (IQR)23.991

Descriptive statistics

Standard deviation1739.6109
Coefficient of variation (CV)-5.8055203
Kurtosis27.076841
Mean-299.64771
Median Absolute Deviation (MAD)0.443
Skewness-5.3864844
Sum-2996477.1
Variance3026245.9
MonotonicityNot monotonic
2024-05-11T15:57:49.010677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-9999.0 311
 
3.1%
0.007 232
 
2.3%
0.001 224
 
2.2%
0.003 223
 
2.2%
0.002 222
 
2.2%
0.006 214
 
2.1%
0.008 209
 
2.1%
0.009 184
 
1.8%
0.004 183
 
1.8%
0.005 180
 
1.8%
Other values (317) 7818
78.2%
ValueCountFrequency (%)
-9999.0 311
3.1%
-999.9 51
 
0.5%
-9.999 126
1.3%
0.0 154
1.5%
0.001 224
2.2%
0.002 222
2.2%
0.003 223
2.2%
0.004 183
1.8%
0.005 180
1.8%
0.006 214
2.1%
ValueCountFrequency (%)
231.0 2
< 0.1%
222.0 1
< 0.1%
205.0 2
< 0.1%
200.0 1
< 0.1%
199.0 1
< 0.1%
197.0 1
< 0.1%
190.0 1
< 0.1%
188.0 1
< 0.1%
185.0 1
< 0.1%
183.0 1
< 0.1%

측정기 상태
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.308
Minimum0
Maximum9
Zeros9229
Zeros (%)92.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:57:49.119071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile4
Maximum9
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.1828254
Coefficient of variation (CV)3.8403422
Kurtosis22.054152
Mean0.308
Median Absolute Deviation (MAD)0
Skewness4.4287447
Sum3080
Variance1.3990759
MonotonicityNot monotonic
2024-05-11T15:57:49.225888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 9229
92.3%
4 558
 
5.6%
1 75
 
0.8%
2 65
 
0.7%
9 59
 
0.6%
8 14
 
0.1%
ValueCountFrequency (%)
0 9229
92.3%
1 75
 
0.8%
2 65
 
0.7%
4 558
 
5.6%
8 14
 
0.1%
9 59
 
0.6%
ValueCountFrequency (%)
9 59
 
0.6%
8 14
 
0.1%
4 558
 
5.6%
2 65
 
0.7%
1 75
 
0.8%
0 9229
92.3%

국가 기준초과 구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9475 
1
 
525

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 9475
94.8%
1 525
 
5.2%

Length

2024-05-11T15:57:49.339208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:57:49.439845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 9475
94.8%
1 525
 
5.2%

지자체 기준초과 구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9475 
1
 
525

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 9475
94.8%
1 525
 
5.2%

Length

2024-05-11T15:57:49.544508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:57:49.638373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 9475
94.8%
1 525
 
5.2%

Interactions

2024-05-11T15:57:46.898200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:57:43.593885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:57:44.295763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:57:45.012019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:57:46.200546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:57:47.016849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:57:43.726700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:57:44.445152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:57:45.169411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:57:46.338028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:57:47.136048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:57:43.869254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:57:44.581316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:57:45.637317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:57:46.501132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:57:47.253669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:57:44.014369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:57:44.748449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:57:45.901764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:57:46.656242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:57:47.369897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:57:44.146153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:57:44.881091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:57:46.059401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:57:46.794807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T15:57:49.714895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
측정일시측정소 코드측정항목평균값측정기 상태국가 기준초과 구분지자체 기준초과 구분
측정일시1.0000.0000.0000.0590.0920.4140.414
측정소 코드0.0001.0000.0000.2890.4300.0910.091
측정항목0.0000.0001.0000.2190.3550.4550.455
평균값0.0590.2890.2191.0000.5720.0160.016
측정기 상태0.0920.4300.3550.5721.0000.1420.142
국가 기준초과 구분0.4140.0910.4550.0160.1421.0001.000
지자체 기준초과 구분0.4140.0910.4550.0160.1421.0001.000
2024-05-11T15:57:49.856128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
국가 기준초과 구분지자체 기준초과 구분
국가 기준초과 구분1.0000.999
지자체 기준초과 구분0.9991.000
2024-05-11T15:57:49.959015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
측정일시측정소 코드측정항목평균값측정기 상태국가 기준초과 구분지자체 기준초과 구분
측정일시1.000-0.0040.0060.0320.0500.3180.318
측정소 코드-0.0041.0000.0040.031-0.0190.0700.070
측정항목0.0060.0041.0000.4920.1670.3280.328
평균값0.0320.0310.4921.000-0.3240.0430.043
측정기 상태0.050-0.0190.167-0.3241.0000.1020.102
국가 기준초과 구분0.3180.0700.3280.0430.1021.0000.999
지자체 기준초과 구분0.3180.0700.3280.0430.1020.9991.000

Missing values

2024-05-11T15:57:47.527739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T15:57:47.678630image/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
71773200701202211330.06000
8469120070124121163-9.999400
78172007010304103917.0000
27483200701081510660.03000
4029120070112041163-9.999400
64425200701182111360.007000
28495200701082112530.044000
52707200701151511060.006000
83660200701240511950.7000
10551200701032210960.0000
측정일시측정소 코드측정항목평균값측정기 상태국가 기준초과 구분지자체 기준초과 구분
20382007010113115836.0000
292432007010902124922.0000
22567200701070611230.028000
714832007012020114932.0000
47819200701140612097.0200
39373200701112211330.054000
7179120070120221163-9.999400
72338200701210210751.6000
48644200701141210850.9000
26653200701080911830.033000