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 has constant value ""Constant
지자체 기준초과 구분 has constant value ""Constant
측정항목 is highly overall correlated with 평균값 and 1 other fieldsHigh correlation
평균값 is highly overall correlated with 측정항목 and 1 other fieldsHigh correlation
측정기 상태 is highly overall correlated with 측정항목 and 1 other fieldsHigh correlation
평균값 has 507 (5.1%) zerosZeros
측정기 상태 has 5950 (59.5%) zerosZeros

Reproduction

Analysis started2024-07-27 00:30:02.799487
Analysis finished2024-07-27 00:30:13.906772
Duration11.11 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

측정일시
Real number (ℝ)

Distinct2076
Distinct (%)20.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9890212 × 109
Minimum1.9890101 × 109
Maximum1.9890328 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-07-27T09:30:14.561495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9890101 × 109
5-th percentile1.9890105 × 109
Q11.9890122 × 109
median1.9890213 × 109
Q31.9890307 × 109
95-th percentile1.9890324 × 109
Maximum1.9890328 × 109
Range22719
Interquartile range (IQR)18489

Descriptive statistics

Standard deviation8200.7491
Coefficient of variation (CV)4.1230075 × 10-6
Kurtosis-1.486408
Mean1.9890212 × 109
Median Absolute Deviation (MAD)9208
Skewness0.067166008
Sum1.9890212 × 1013
Variance67252286
MonotonicityNot monotonic
2024-07-27T09:30:15.092729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1989031016 14
 
0.1%
1989032016 13
 
0.1%
1989031810 12
 
0.1%
1989012111 12
 
0.1%
1989022403 12
 
0.1%
1989012119 11
 
0.1%
1989031607 11
 
0.1%
1989011901 11
 
0.1%
1989010705 11
 
0.1%
1989021220 11
 
0.1%
Other values (2066) 9882
98.8%
ValueCountFrequency (%)
1989010100 7
0.1%
1989010101 6
0.1%
1989010102 3
< 0.1%
1989010103 3
< 0.1%
1989010104 6
0.1%
1989010105 6
0.1%
1989010106 7
0.1%
1989010107 5
0.1%
1989010108 5
0.1%
1989010109 2
 
< 0.1%
ValueCountFrequency (%)
1989032819 2
 
< 0.1%
1989032818 4
 
< 0.1%
1989032817 5
0.1%
1989032816 6
0.1%
1989032815 10
0.1%
1989032814 8
0.1%
1989032813 8
0.1%
1989032812 7
0.1%
1989032811 5
0.1%
1989032810 4
 
< 0.1%

측정소 코드
Real number (ℝ)

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean112.388
Minimum103
Maximum124
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-07-27T09:30:15.688109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum103
5-th percentile103
Q1105
median108
Q3122
95-th percentile124
Maximum124
Range21
Interquartile range (IQR)17

Descriptive statistics

Standard deviation7.4461534
Coefficient of variation (CV)0.06625399
Kurtosis-1.3964105
Mean112.388
Median Absolute Deviation (MAD)5
Skewness0.33006119
Sum1123880
Variance55.445201
MonotonicityNot monotonic
2024-07-27T09:30:16.125176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
122 1293
12.9%
103 1264
12.6%
105 1261
12.6%
107 1256
12.6%
117 1246
12.5%
124 1243
12.4%
108 1230
12.3%
113 1207
12.1%
ValueCountFrequency (%)
103 1264
12.6%
105 1261
12.6%
107 1256
12.6%
108 1230
12.3%
113 1207
12.1%
117 1246
12.5%
122 1293
12.9%
124 1243
12.4%
ValueCountFrequency (%)
124 1243
12.4%
122 1293
12.9%
117 1246
12.5%
113 1207
12.1%
108 1230
12.3%
107 1256
12.6%
105 1261
12.6%
103 1264
12.6%

측정항목
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.3214
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-07-27T09:30:16.480631image/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 deviation2.7535904
Coefficient of variation (CV)0.51745601
Kurtosis-1.2151839
Mean5.3214
Median Absolute Deviation (MAD)2.5
Skewness-0.19625573
Sum53214
Variance7.5822603
MonotonicityNot monotonic
2024-07-27T09:30:16.992273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3 1682
16.8%
1 1678
16.8%
9 1675
16.8%
5 1669
16.7%
6 1649
16.5%
8 1647
16.5%
ValueCountFrequency (%)
1 1678
16.8%
3 1682
16.8%
5 1669
16.7%
6 1649
16.5%
8 1647
16.5%
9 1675
16.8%
ValueCountFrequency (%)
9 1675
16.8%
8 1647
16.5%
6 1649
16.5%
5 1669
16.7%
3 1682
16.8%
1 1678
16.8%

평균값
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct503
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-3338.1404
Minimum-9999
Maximum34.8
Zeros507
Zeros (%)5.1%
Negative4048
Negative (%)40.5%
Memory size166.0 KiB
2024-07-27T09:30:17.722425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-9999
5-th percentile-9999
Q1-9999
median0.006
Q30.067
95-th percentile4.5
Maximum34.8
Range10033.8
Interquartile range (IQR)9999.067

Descriptive statistics

Standard deviation4699.8927
Coefficient of variation (CV)-1.4079374
Kurtosis-1.4928678
Mean-3338.1404
Median Absolute Deviation (MAD)2.394
Skewness-0.71044253
Sum-33381404
Variance22088991
MonotonicityNot monotonic
2024-07-27T09:30:18.258242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-9999.0 3322
33.2%
-9.999 556
 
5.6%
0.0 507
 
5.1%
-999.9 166
 
1.7%
0.001 146
 
1.5%
0.002 93
 
0.9%
0.003 71
 
0.7%
0.005 62
 
0.6%
0.016 61
 
0.6%
0.01 61
 
0.6%
Other values (493) 4955
49.5%
ValueCountFrequency (%)
-9999.0 3322
33.2%
-999.9 166
 
1.7%
-10.051 1
 
< 0.1%
-10.002 1
 
< 0.1%
-9.999 556
 
5.6%
-0.025 1
 
< 0.1%
-0.007 1
 
< 0.1%
0.0 507
 
5.1%
0.001 146
 
1.5%
0.002 93
 
0.9%
ValueCountFrequency (%)
34.8 1
< 0.1%
30.8 1
< 0.1%
29.8 1
< 0.1%
25.1 1
< 0.1%
24.4 1
< 0.1%
23.8 1
< 0.1%
22.9 2
< 0.1%
22.6 1
< 0.1%
22.0 1
< 0.1%
21.6 1
< 0.1%

측정기 상태
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5899
Minimum0
Maximum9
Zeros5950
Zeros (%)59.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-07-27T09:30:18.717880image/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 deviation2.0550281
Coefficient of variation (CV)1.2925518
Kurtosis-0.021434708
Mean1.5899
Median Absolute Deviation (MAD)0
Skewness0.8737231
Sum15899
Variance4.2231403
MonotonicityNot monotonic
2024-07-27T09:30:19.121016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 5950
59.5%
4 3466
34.7%
2 423
 
4.2%
9 118
 
1.2%
1 31
 
0.3%
8 12
 
0.1%
ValueCountFrequency (%)
0 5950
59.5%
1 31
 
0.3%
2 423
 
4.2%
4 3466
34.7%
8 12
 
0.1%
9 118
 
1.2%
ValueCountFrequency (%)
9 118
 
1.2%
8 12
 
0.1%
4 3466
34.7%
2 423
 
4.2%
1 31
 
0.3%
0 5950
59.5%

국가 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

2024-07-27T09:30:19.609421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-07-27T09:30:19.992557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 10000
100.0%

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

2024-07-27T09:30:20.447882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-07-27T09:30:20.947790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 10000
100.0%

Interactions

2024-07-27T09:30:11.338038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-07-27T09:30:05.009526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-07-27T09:30:06.692839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-07-27T09:30:08.055941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-07-27T09:30:09.616637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-07-27T09:30:11.662607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-07-27T09:30:05.365679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-07-27T09:30:06.961666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-07-27T09:30:08.343732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-07-27T09:30:09.944179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-07-27T09:30:12.018088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-07-27T09:30:05.751622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-07-27T09:30:07.214115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-07-27T09:30:08.648663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-07-27T09:30:10.200092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-07-27T09:30:12.369207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-07-27T09:30:06.111729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-07-27T09:30:07.551764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-07-27T09:30:08.985775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-07-27T09:30:10.667332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-07-27T09:30:12.721604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-07-27T09:30:06.411457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-07-27T09:30:07.797725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-07-27T09:30:09.315701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-07-27T09:30:11.027085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-07-27T09:30:21.282653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
측정일시측정소 코드측정항목평균값측정기 상태
측정일시1.0000.0000.0180.1060.141
측정소 코드0.0001.0000.0190.0870.273
측정항목0.0180.0191.0000.4110.823
평균값0.1060.0870.4111.0000.664
측정기 상태0.1410.2730.8230.6641.000
2024-07-27T09:30:21.802829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
측정일시측정소 코드측정항목평균값측정기 상태
측정일시1.0000.009-0.0030.039-0.037
측정소 코드0.0091.000-0.0080.015-0.027
측정항목-0.003-0.0081.000-0.7580.724
평균값0.0390.015-0.7581.000-0.867
측정기 상태-0.037-0.0270.724-0.8671.000

Missing values

2024-07-27T09:30:13.128343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-07-27T09:30:13.663643image/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
23300198901210510853.3000
73099198903051012430.021000
4627719890210041039-9999.0400
69096198903012311310.071000
9412019890323161228-9999.0400
89142198903190910510.254000
99633198903281111760.01000
4562919890209141139-9999.0400
277619890103091228-9999.0400
34914198901310710810.088000
측정일시측정소 코드측정항목평균값측정기 상태국가 기준초과 구분지자체 기준초과 구분
24654198901220911710.136000
13521198901121711760.0000
4849019890212021058-9999.0400
808819890108001131-9.999200
92664198903221011310.038000
64338198902252010810.022000
1666719890115111059-9999.0400
7795719890309161039-9999.0400
86864198903170911753.1000
12303198901111610760.008000