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

지자체 기준초과 구분 has constant value ""Constant
측정항목 is highly overall correlated with 평균값High correlation
평균값 is highly overall correlated with 측정항목High correlation
국가 기준초과 구분 is highly imbalanced (99.3%)Imbalance
측정기 상태 has 9758 (97.6%) zerosZeros

Reproduction

Analysis started2024-04-27 12:04:29.757506
Analysis finished2024-04-27 12:04:38.981524
Duration9.22 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

측정일시
Real number (ℝ)

Distinct445
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.012011 × 109
Minimum2.0120101 × 109
Maximum2.0120119 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-27T12:04:39.138149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0120101 × 109
5-th percentile2.0120101 × 109
Q12.0120105 × 109
median2.012011 × 109
Q32.0120114 × 109
95-th percentile2.0120118 × 109
Maximum2.0120119 × 109
Range1812
Interquartile range (IQR)906

Descriptive statistics

Standard deviation534.50972
Coefficient of variation (CV)2.6565944 × 10-7
Kurtosis-1.1923553
Mean2.012011 × 109
Median Absolute Deviation (MAD)489.5
Skewness0.0037260393
Sum2.012011 × 1013
Variance285700.64
MonotonicityNot monotonic
2024-04-27T12:04:39.537540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2012011200 39
 
0.4%
2012010117 34
 
0.3%
2012011018 33
 
0.3%
2012010712 33
 
0.3%
2012010901 32
 
0.3%
2012010209 32
 
0.3%
2012011019 32
 
0.3%
2012010500 32
 
0.3%
2012011405 32
 
0.3%
2012011100 31
 
0.3%
Other values (435) 9670
96.7%
ValueCountFrequency (%)
2012010100 16
0.2%
2012010101 21
0.2%
2012010102 24
0.2%
2012010103 27
0.3%
2012010104 25
0.2%
2012010105 18
0.2%
2012010106 24
0.2%
2012010107 25
0.2%
2012010108 23
0.2%
2012010109 14
0.1%
ValueCountFrequency (%)
2012011912 16
0.2%
2012011911 23
0.2%
2012011910 25
0.2%
2012011909 17
0.2%
2012011908 18
0.2%
2012011907 31
0.3%
2012011906 28
0.3%
2012011905 17
0.2%
2012011904 28
0.3%
2012011903 30
0.3%

측정소 코드
Real number (ℝ)

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean112.9952
Minimum101
Maximum125
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-27T12:04:39.905646image/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 deviation7.191102
Coefficient of variation (CV)0.063640774
Kurtosis-1.1847427
Mean112.9952
Median Absolute Deviation (MAD)6
Skewness0.00086664139
Sum1129952
Variance51.711948
MonotonicityNot monotonic
2024-04-27T12:04:40.280038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
110 435
 
4.3%
111 426
 
4.3%
125 423
 
4.2%
120 421
 
4.2%
114 419
 
4.2%
102 418
 
4.2%
122 416
 
4.2%
101 414
 
4.1%
106 409
 
4.1%
116 409
 
4.1%
Other values (15) 5810
58.1%
ValueCountFrequency (%)
101 414
4.1%
102 418
4.2%
103 376
3.8%
104 361
3.6%
105 390
3.9%
106 409
4.1%
107 390
3.9%
108 401
4.0%
109 404
4.0%
110 435
4.3%
ValueCountFrequency (%)
125 423
4.2%
124 371
3.7%
123 385
3.9%
122 416
4.2%
121 372
3.7%
120 421
4.2%
119 398
4.0%
118 395
4.0%
117 383
3.8%
116 409
4.1%

측정항목
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.3208
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-27T12:04:40.624178image/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 deviation2.7336852
Coefficient of variation (CV)0.51377334
Kurtosis-1.1992067
Mean5.3208
Median Absolute Deviation (MAD)2
Skewness-0.18749361
Sum53208
Variance7.4730347
MonotonicityNot monotonic
2024-04-27T12:04:41.002312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3 1732
17.3%
5 1686
16.9%
6 1684
16.8%
9 1669
16.7%
1 1625
16.2%
8 1604
16.0%
ValueCountFrequency (%)
1 1625
16.2%
3 1732
17.3%
5 1686
16.9%
6 1684
16.8%
8 1604
16.0%
9 1669
16.7%
ValueCountFrequency (%)
9 1669
16.7%
8 1604
16.0%
6 1684
16.8%
5 1686
16.9%
3 1732
17.3%
1 1625
16.2%

평균값
Real number (ℝ)

HIGH CORRELATION 

Distinct283
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-22.577191
Minimum-9999
Maximum173
Zeros47
Zeros (%)0.5%
Negative128
Negative (%)1.3%
Memory size166.0 KiB
2024-04-27T12:04:41.437387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-9999
5-th percentile0.002
Q10.011
median0.071
Q335
95-th percentile88
Maximum173
Range10172
Interquartile range (IQR)34.989

Descriptive statistics

Standard deviation627.15421
Coefficient of variation (CV)-27.778222
Kurtosis246.91656
Mean-22.577191
Median Absolute Deviation (MAD)0.229
Skewness-15.711937
Sum-225771.91
Variance393322.41
MonotonicityNot monotonic
2024-04-27T12:04:41.884517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.007 303
 
3.0%
0.008 291
 
2.9%
0.006 267
 
2.7%
0.009 245
 
2.5%
0.002 244
 
2.4%
0.6 210
 
2.1%
0.01 209
 
2.1%
0.8 199
 
2.0%
0.7 195
 
1.9%
0.011 182
 
1.8%
Other values (273) 7655
76.5%
ValueCountFrequency (%)
-9999.0 39
 
0.4%
-999.9 25
 
0.2%
-9.999 64
 
0.6%
0.0 47
 
0.5%
0.001 159
1.6%
0.002 244
2.4%
0.003 174
1.7%
0.004 136
1.4%
0.005 174
1.7%
0.006 267
2.7%
ValueCountFrequency (%)
173.0 1
 
< 0.1%
172.0 1
 
< 0.1%
168.0 1
 
< 0.1%
165.0 1
 
< 0.1%
163.0 1
 
< 0.1%
162.0 1
 
< 0.1%
160.0 1
 
< 0.1%
159.0 1
 
< 0.1%
158.0 3
< 0.1%
157.0 2
< 0.1%

측정기 상태
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1067
Minimum0
Maximum9
Zeros9758
Zeros (%)97.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-27T12:04:42.296929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

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

Descriptive statistics

Standard deviation0.82157325
Coefficient of variation (CV)7.699843
Kurtosis83.727357
Mean0.1067
Median Absolute Deviation (MAD)0
Skewness8.9285928
Sum1067
Variance0.67498261
MonotonicityNot monotonic
2024-04-27T12:04:42.608293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 9758
97.6%
4 75
 
0.8%
1 62
 
0.6%
8 44
 
0.4%
9 33
 
0.3%
2 28
 
0.3%
ValueCountFrequency (%)
0 9758
97.6%
1 62
 
0.6%
2 28
 
0.3%
4 75
 
0.8%
8 44
 
0.4%
9 33
 
0.3%
ValueCountFrequency (%)
9 33
 
0.3%
8 44
 
0.4%
4 75
 
0.8%
2 28
 
0.3%
1 62
 
0.6%
0 9758
97.6%

국가 기준초과 구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9994 
1
 
6

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 9994
99.9%
1 6
 
0.1%

Length

2024-04-27T12:04:43.009551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-27T12:04:43.387641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 9994
99.9%
1 6
 
0.1%

지자체 기준초과 구분
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
10000 

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 10000
100.0%

Length

2024-04-27T12:04:43.710874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-27T12:04:43.998576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 10000
100.0%

Interactions

2024-04-27T12:04:37.108815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:04:31.315162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:04:32.938978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:04:34.530432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:04:35.831390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:04:37.317673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:04:31.634791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:04:33.289789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:04:34.783166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:04:36.118487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:04:37.559116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:04:32.051347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:04:33.763270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:04:35.035640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:04:36.320991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:04:37.998729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:04:32.336779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:04:34.055299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:04:35.331451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:04:36.610801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:04:38.184962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:04:32.642786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:04:34.326074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:04:35.570894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:04:36.868058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-27T12:04:44.327646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
측정일시측정소 코드측정항목평균값측정기 상태국가 기준초과 구분
측정일시1.0000.0000.0000.1280.2020.031
측정소 코드0.0001.0000.0000.1150.2610.030
측정항목0.0000.0001.0000.1510.0750.068
평균값0.1280.1150.1511.0000.7200.000
측정기 상태0.2020.2610.0750.7201.0000.000
국가 기준초과 구분0.0310.0300.0680.0000.0001.000
2024-04-27T12:04:44.618265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
측정일시측정소 코드측정항목평균값측정기 상태국가 기준초과 구분
측정일시1.0000.0010.013-0.0360.1210.024
측정소 코드0.0011.000-0.008-0.0220.0860.023
측정항목0.013-0.0081.0000.643-0.0040.049
평균값-0.036-0.0220.6431.000-0.1620.000
측정기 상태0.1210.086-0.004-0.1621.0000.000
국가 기준초과 구분0.0240.0230.0490.0000.0001.000

Missing values

2024-04-27T12:04:38.487782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-27T12:04:38.867210image/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
55605201201161011860.006000
20790201201061811610.021900
41773201201121411330.038000
26676201201080912210.007000
54144201201160012510.006000
18926201201060610551.1000
397072012011200118935.0000
553242012011608121855.0000
12823201201041311330.013000
436542012011303101841.0000
측정일시측정소 코드측정항목평균값측정기 상태국가 기준초과 구분지자체 기준초과 구분
38157201201111411060.022000
17238201201051812410.006000
41502012010203117882.0000
18456201201060310210.008000
24417201201071812060.003000
28489201201082112430.039000
21735201201070012360.002000
43584201201130211510.011000
60674201201172011350.7000
46886201201140011550.5000