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 518 (5.2%) zerosZeros
측정기 상태 has 6023 (60.2%) zerosZeros

Reproduction

Analysis started2024-04-27 12:07:29.793411
Analysis finished2024-04-27 12:07:37.808839
Duration8.02 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

측정일시
Real number (ℝ)

Distinct2072
Distinct (%)20.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9890213 × 109
Minimum1.9890101 × 109
Maximum1.9890328 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-27T12:07:38.025876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9890101 × 109
5-th percentile1.9890105 × 109
Q11.9890123 × 109
median1.9890213 × 109
Q31.9890307 × 109
95-th percentile1.9890324 × 109
Maximum1.9890328 × 109
Range22719
Interquartile range (IQR)18397

Descriptive statistics

Standard deviation8183.4592
Coefficient of variation (CV)4.1143146 × 10-6
Kurtosis-1.4797767
Mean1.9890213 × 109
Median Absolute Deviation (MAD)9199.5
Skewness0.047959316
Sum1.9890213 × 1013
Variance66969004
MonotonicityNot monotonic
2024-04-27T12:07:38.475324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1989030414 12
 
0.1%
1989031011 11
 
0.1%
1989031216 11
 
0.1%
1989021808 11
 
0.1%
1989011915 11
 
0.1%
1989021604 11
 
0.1%
1989010303 11
 
0.1%
1989021218 11
 
0.1%
1989032300 11
 
0.1%
1989030314 10
 
0.1%
Other values (2062) 9890
98.9%
ValueCountFrequency (%)
1989010100 5
0.1%
1989010101 7
0.1%
1989010102 4
< 0.1%
1989010103 2
 
< 0.1%
1989010104 7
0.1%
1989010105 1
 
< 0.1%
1989010106 7
0.1%
1989010107 6
0.1%
1989010108 3
< 0.1%
1989010109 6
0.1%
ValueCountFrequency (%)
1989032819 1
 
< 0.1%
1989032818 5
0.1%
1989032817 5
0.1%
1989032816 6
0.1%
1989032815 5
0.1%
1989032814 3
 
< 0.1%
1989032813 5
0.1%
1989032811 3
 
< 0.1%
1989032810 10
0.1%
1989032809 4
 
< 0.1%

측정소 코드
Real number (ℝ)

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean112.3116
Minimum103
Maximum124
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-27T12:07:38.778962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum103
5-th percentile103
Q1105
median108
Q3117
95-th percentile124
Maximum124
Range21
Interquartile range (IQR)12

Descriptive statistics

Standard deviation7.389382
Coefficient of variation (CV)0.065793578
Kurtosis-1.3655476
Mean112.3116
Median Absolute Deviation (MAD)5
Skewness0.35252875
Sum1123116
Variance54.602966
MonotonicityNot monotonic
2024-04-27T12:07:38.969920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
107 1288
12.9%
105 1278
12.8%
113 1260
12.6%
122 1244
12.4%
117 1239
12.4%
108 1237
12.4%
103 1233
12.3%
124 1221
12.2%
ValueCountFrequency (%)
103 1233
12.3%
105 1278
12.8%
107 1288
12.9%
108 1237
12.4%
113 1260
12.6%
117 1239
12.4%
122 1244
12.4%
124 1221
12.2%
ValueCountFrequency (%)
124 1221
12.2%
122 1244
12.4%
117 1239
12.4%
113 1260
12.6%
108 1237
12.4%
107 1288
12.9%
105 1278
12.8%
103 1233
12.3%

측정항목
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.307
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-27T12:07:39.149636image/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 deviation2.7475636
Coefficient of variation (CV)0.51772445
Kurtosis-1.2222253
Mean5.307
Median Absolute Deviation (MAD)2
Skewness-0.18305703
Sum53070
Variance7.5491059
MonotonicityNot monotonic
2024-04-27T12:07:39.416991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3 1749
17.5%
8 1679
16.8%
5 1678
16.8%
1 1656
16.6%
9 1639
16.4%
6 1599
16.0%
ValueCountFrequency (%)
1 1656
16.6%
3 1749
17.5%
5 1678
16.8%
6 1599
16.0%
8 1679
16.8%
9 1639
16.4%
ValueCountFrequency (%)
9 1639
16.4%
8 1679
16.8%
6 1599
16.0%
5 1678
16.8%
3 1749
17.5%
1 1656
16.6%

평균값
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct514
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-3334.0823
Minimum-9999
Maximum29.8
Zeros518
Zeros (%)5.2%
Negative3976
Negative (%)39.8%
Memory size166.0 KiB
2024-04-27T12:07:39.806238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-9999
5-th percentile-9999
Q1-9999
median0.008
Q30.068
95-th percentile4.5
Maximum29.8
Range10028.8
Interquartile range (IQR)9999.068

Descriptive statistics

Standard deviation4698.5182
Coefficient of variation (CV)-1.4092388
Kurtosis-1.4901419
Mean-3334.0823
Median Absolute Deviation (MAD)2.292
Skewness-0.71235557
Sum-33340823
Variance22076074
MonotonicityNot monotonic
2024-04-27T12:07:40.258805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-9999.0 3318
33.2%
0.0 518
 
5.2%
-9.999 491
 
4.9%
-999.9 166
 
1.7%
0.001 124
 
1.2%
0.002 96
 
1.0%
0.003 66
 
0.7%
0.035 65
 
0.7%
0.021 62
 
0.6%
0.03 61
 
0.6%
Other values (504) 5033
50.3%
ValueCountFrequency (%)
-9999.0 3318
33.2%
-999.9 166
 
1.7%
-10.011 1
 
< 0.1%
-9.999 491
 
4.9%
0.0 518
 
5.2%
0.001 124
 
1.2%
0.002 96
 
1.0%
0.003 66
 
0.7%
0.004 50
 
0.5%
0.005 51
 
0.5%
ValueCountFrequency (%)
29.8 1
< 0.1%
28.1 1
< 0.1%
26.3 1
< 0.1%
23.9 1
< 0.1%
23.8 1
< 0.1%
22.8 1
< 0.1%
21.1 1
< 0.1%
20.8 1
< 0.1%
20.7 1
< 0.1%
20.6 1
< 0.1%

측정기 상태
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5613
Minimum0
Maximum9
Zeros6023
Zeros (%)60.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-27T12:07:40.736598image/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 deviation2.0332869
Coefficient of variation (CV)1.3023038
Kurtosis-0.17728485
Mean1.5613
Median Absolute Deviation (MAD)0
Skewness0.84900228
Sum15613
Variance4.1342557
MonotonicityNot monotonic
2024-04-27T12:07:41.053826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 6023
60.2%
4 3459
34.6%
2 377
 
3.8%
9 98
 
1.0%
1 29
 
0.3%
8 14
 
0.1%
ValueCountFrequency (%)
0 6023
60.2%
1 29
 
0.3%
2 377
 
3.8%
4 3459
34.6%
8 14
 
0.1%
9 98
 
1.0%
ValueCountFrequency (%)
9 98
 
1.0%
8 14
 
0.1%
4 3459
34.6%
2 377
 
3.8%
1 29
 
0.3%
0 6023
60.2%

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

2024-04-27T12:07:41.331849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-27T12:07:41.684586image/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

2024-04-27T12:07:41.962684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-27T12:07:42.301590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 10000
100.0%

Interactions

2024-04-27T12:07:36.066092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:30.950366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:32.247540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:33.370052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:34.728916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:36.229268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:31.282776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:32.503958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:33.587405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:34.985871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:36.403113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:31.510995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:32.662561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:33.853288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:35.414304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:36.641066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:31.727777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:32.940682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:34.192874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:35.654922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:36.894789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:31.991141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:33.202189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:34.465906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:35.904918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-27T12:07:42.481596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
측정일시측정소 코드측정항목평균값측정기 상태
측정일시1.0000.0080.0000.0830.139
측정소 코드0.0081.0000.0190.0810.246
측정항목0.0000.0191.0000.4090.823
평균값0.0830.0810.4091.0000.685
측정기 상태0.1390.2460.8230.6851.000
2024-04-27T12:07:42.763763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
측정일시측정소 코드측정항목평균값측정기 상태
측정일시1.000-0.013-0.0140.059-0.060
측정소 코드-0.0131.000-0.007-0.009-0.003
측정항목-0.014-0.0071.000-0.7580.734
평균값0.059-0.009-0.7581.000-0.865
측정기 상태-0.060-0.0030.734-0.8651.000

Missing values

2024-04-27T12:07:37.243018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-27T12:07:37.638317image/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
74748198903062110710.068000
87915198903180711360.0000
6950319890302071249-9999.0400
3681719890201231033-9.999200
304219890103151081-9.999400
89124198903190812210.326000
5402919890216211139-9999.0400
185319890102141139-9999.0400
564261989021823113510.5000
2560019890123051078-9999.0400
측정일시측정소 코드측정항목평균값측정기 상태국가 기준초과 구분지자체 기준초과 구분
62481198902240511760.001000
2992319890126231083-9.999900
1415219890113061228-9999.0400
28314198901251312410.052000
14283198901130911360.002000
5804819890220091078-9999.0400
29120198901260611754.0000
64767198902260510760.002000
49159198902121610530.029000
95666198903250110352.4000