Overview

Dataset statistics

Number of variables8
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory742.2 KiB
Average record size in memory76.0 B

Variable types

Categorical3
Numeric4
DateTime1

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15971/S/1/datasetView.do

Alerts

기관 명 has constant value ""Constant
모델명 has constant value ""Constant
초미세먼지(㎍/㎥) is highly overall correlated with 미세먼지(㎍/㎥)High correlation
미세먼지(㎍/㎥) is highly overall correlated with 초미세먼지(㎍/㎥)High correlation

Reproduction

Analysis started2024-05-04 06:51:06.284528
Analysis finished2024-05-04 06:51:13.395918
Duration7.11 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기관 명
Categorical

CONSTANT 

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

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영등포구
2nd row영등포구
3rd row영등포구
4th row영등포구
5th row영등포구

Common Values

ValueCountFrequency (%)
영등포구 10000
100.0%

Length

2024-05-04T06:51:13.524012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T06:51:13.821788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영등포구 10000
100.0%

모델명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
AF-YDP-2018
10000 

Length

Max length11
Median length11
Mean length11
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAF-YDP-2018
2nd rowAF-YDP-2018
3rd rowAF-YDP-2018
4th rowAF-YDP-2018
5th rowAF-YDP-2018

Common Values

ValueCountFrequency (%)
AF-YDP-2018 10000
100.0%

Length

2024-05-04T06:51:14.124874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T06:51:14.425483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
af-ydp-2018 10000
100.0%

시리얼
Categorical

Distinct27
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
240AC425CA98
 
406
240AC4265A9C
 
395
240AC4208BD0
 
390
240AC425E790
 
390
240AC4208BE4
 
386
Other values (22)
8033 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row240AC42651E4
2nd row240AC4208BD0
3rd row240AC425E8F4
4th row240AC4265148
5th row240AC425E79C

Common Values

ValueCountFrequency (%)
240AC425CA98 406
 
4.1%
240AC4265A9C 395
 
4.0%
240AC4208BD0 390
 
3.9%
240AC425E790 390
 
3.9%
240AC4208BE4 386
 
3.9%
240AC42651E4 384
 
3.8%
240AC420739C 384
 
3.8%
240AC4207314 383
 
3.8%
240AC425E76C 381
 
3.8%
240AC4265148 380
 
3.8%
Other values (17) 6121
61.2%

Length

2024-05-04T06:51:14.814809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
240ac425ca98 406
 
4.1%
240ac4265a9c 395
 
4.0%
240ac4208bd0 390
 
3.9%
240ac425e790 390
 
3.9%
240ac4208be4 386
 
3.9%
240ac42651e4 384
 
3.8%
240ac420739c 384
 
3.8%
240ac4207314 383
 
3.8%
240ac425e76c 381
 
3.8%
240ac4265148 380
 
3.8%
Other values (17) 6121
61.2%

온도(℃)
Real number (ℝ)

Distinct27
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.9223
Minimum6
Maximum32
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T06:51:15.159714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile12
Q115
median18
Q323
95-th percentile27
Maximum32
Range26
Interquartile range (IQR)8

Descriptive statistics

Standard deviation4.8052858
Coefficient of variation (CV)0.25394829
Kurtosis-0.82710781
Mean18.9223
Median Absolute Deviation (MAD)4
Skewness0.25846857
Sum189223
Variance23.090772
MonotonicityNot monotonic
2024-05-04T06:51:15.554543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
16 972
 
9.7%
17 958
 
9.6%
15 775
 
7.8%
18 758
 
7.6%
14 692
 
6.9%
25 587
 
5.9%
26 550
 
5.5%
24 550
 
5.5%
19 547
 
5.5%
13 532
 
5.3%
Other values (17) 3079
30.8%
ValueCountFrequency (%)
6 1
 
< 0.1%
7 12
 
0.1%
8 32
 
0.3%
9 34
 
0.3%
10 70
 
0.7%
11 187
 
1.9%
12 354
3.5%
13 532
5.3%
14 692
6.9%
15 775
7.8%
ValueCountFrequency (%)
32 6
 
0.1%
31 36
 
0.4%
30 32
 
0.3%
29 69
 
0.7%
28 148
 
1.5%
27 314
3.1%
26 550
5.5%
25 587
5.9%
24 550
5.5%
23 491
4.9%

습도(%)
Real number (ℝ)

Distinct38
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.701
Minimum2
Maximum40
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T06:51:16.102118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile6
Q19
median12
Q315
95-th percentile20
Maximum40
Range38
Interquartile range (IQR)6

Descriptive statistics

Standard deviation4.9062619
Coefficient of variation (CV)0.38628942
Kurtosis3.6111751
Mean12.701
Median Absolute Deviation (MAD)3
Skewness1.2814583
Sum127010
Variance24.071406
MonotonicityNot monotonic
2024-05-04T06:51:16.545334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
15 952
9.5%
13 853
 
8.5%
14 827
 
8.3%
12 803
 
8.0%
11 797
 
8.0%
16 787
 
7.9%
9 758
 
7.6%
10 744
 
7.4%
8 726
 
7.3%
7 543
 
5.4%
Other values (28) 2210
22.1%
ValueCountFrequency (%)
2 5
 
0.1%
3 45
 
0.4%
4 60
 
0.6%
5 228
 
2.3%
6 338
3.4%
7 543
5.4%
8 726
7.3%
9 758
7.6%
10 744
7.4%
11 797
8.0%
ValueCountFrequency (%)
40 1
 
< 0.1%
38 3
 
< 0.1%
37 5
 
0.1%
36 14
 
0.1%
35 12
 
0.1%
34 15
 
0.1%
33 15
 
0.1%
32 20
0.2%
31 25
0.2%
30 42
0.4%

초미세먼지(㎍/㎥)
Real number (ℝ)

HIGH CORRELATION 

Distinct63
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.8533
Minimum0
Maximum62
Zeros42
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T06:51:17.012987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q18
median12
Q320
95-th percentile36
Maximum62
Range62
Interquartile range (IQR)12

Descriptive statistics

Standard deviation10.11672
Coefficient of variation (CV)0.68110922
Kurtosis1.6579869
Mean14.8533
Median Absolute Deviation (MAD)6
Skewness1.2458722
Sum148533
Variance102.34801
MonotonicityNot monotonic
2024-05-04T06:51:17.446100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9 589
 
5.9%
6 516
 
5.2%
10 514
 
5.1%
12 487
 
4.9%
11 473
 
4.7%
8 471
 
4.7%
5 469
 
4.7%
7 450
 
4.5%
14 445
 
4.5%
13 430
 
4.3%
Other values (53) 5156
51.6%
ValueCountFrequency (%)
0 42
 
0.4%
1 156
 
1.6%
2 200
 
2.0%
3 271
2.7%
4 374
3.7%
5 469
4.7%
6 516
5.2%
7 450
4.5%
8 471
4.7%
9 589
5.9%
ValueCountFrequency (%)
62 2
 
< 0.1%
61 2
 
< 0.1%
60 3
< 0.1%
59 3
< 0.1%
58 5
0.1%
57 5
0.1%
56 5
0.1%
55 2
 
< 0.1%
54 7
0.1%
53 7
0.1%

미세먼지(㎍/㎥)
Real number (ℝ)

HIGH CORRELATION 

Distinct74
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.6026
Minimum0
Maximum77
Zeros24
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T06:51:17.874190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q19
median15
Q323
95-th percentile42
Maximum77
Range77
Interquartile range (IQR)14

Descriptive statistics

Standard deviation11.74415
Coefficient of variation (CV)0.6671827
Kurtosis1.5531781
Mean17.6026
Median Absolute Deviation (MAD)7
Skewness1.2091039
Sum176026
Variance137.92507
MonotonicityNot monotonic
2024-05-04T06:51:18.305255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10 464
 
4.6%
13 443
 
4.4%
12 431
 
4.3%
11 418
 
4.2%
7 417
 
4.2%
8 413
 
4.1%
16 396
 
4.0%
15 395
 
4.0%
9 386
 
3.9%
14 383
 
3.8%
Other values (64) 5854
58.5%
ValueCountFrequency (%)
0 24
 
0.2%
1 105
 
1.1%
2 171
1.7%
3 198
2.0%
4 264
2.6%
5 318
3.2%
6 362
3.6%
7 417
4.2%
8 413
4.1%
9 386
3.9%
ValueCountFrequency (%)
77 1
 
< 0.1%
73 1
 
< 0.1%
72 1
 
< 0.1%
70 3
< 0.1%
69 1
 
< 0.1%
68 3
< 0.1%
67 3
< 0.1%
66 1
 
< 0.1%
65 3
< 0.1%
64 6
0.1%

등록일시
Date

Distinct4856
Distinct (%)48.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2024-01-22 00:01:05
Maximum2024-01-28 23:51:08
2024-05-04T06:51:18.700769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:51:19.085393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2024-05-04T06:51:11.440015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:51:07.650312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:51:09.143810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:51:10.281546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:51:11.724009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:51:07.998584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:51:09.408360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:51:10.542402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:51:12.027332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:51:08.325247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:51:09.697258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:51:10.865938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:51:12.345473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:51:08.852081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:51:09.983952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:51:11.140766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-04T06:51:19.353214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시리얼온도(℃)습도(%)초미세먼지(㎍/㎥)미세먼지(㎍/㎥)
시리얼1.0000.7360.7620.5330.519
온도(℃)0.7361.0000.5270.2970.298
습도(%)0.7620.5271.0000.4290.411
초미세먼지(㎍/㎥)0.5330.2970.4291.0000.969
미세먼지(㎍/㎥)0.5190.2980.4110.9691.000
2024-05-04T06:51:19.621768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
온도(℃)습도(%)초미세먼지(㎍/㎥)미세먼지(㎍/㎥)시리얼
온도(℃)1.000-0.398-0.187-0.2070.371
습도(%)-0.3981.0000.2540.2590.397
초미세먼지(㎍/㎥)-0.1870.2541.0000.9850.223
미세먼지(㎍/㎥)-0.2070.2590.9851.0000.215
시리얼0.3710.3970.2230.2151.000

Missing values

2024-05-04T06:51:12.748195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-04T06:51:13.173387image/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

기관 명모델명시리얼온도(℃)습도(%)초미세먼지(㎍/㎥)미세먼지(㎍/㎥)등록일시
14881영등포구AF-YDP-2018240AC42651E425129102024-01-25 21:11:10
2947영등포구AF-YDP-2018240AC4208BD021818192024-01-22 18:41:10
8265영등포구AF-YDP-2018240AC425E8F410912162024-01-24 04:11:08
23679영등포구AF-YDP-2018240AC4265148171626312024-01-28 03:32:51
14523영등포구AF-YDP-2018240AC425E79C24620262024-01-25 19:01:08
16729영등포구AF-YDP-2018240AC4208BF423711112024-01-26 08:41:06
18373영등포구AF-YDP-2018240AC4208BA4183023282024-01-26 18:51:06
19228영등포구AF-YDP-2018240AC42651E4211615162024-01-27 00:01:09
11238영등포구AF-YDP-2018240AC42651B4171210132024-01-24 22:41:09
25498영등포구AF-YDP-2018240AC42073B82112662024-01-28 14:51:06
기관 명모델명시리얼온도(℃)습도(%)초미세먼지(㎍/㎥)미세먼지(㎍/㎥)등록일시
22435영등포구AF-YDP-2018240AC425E8F4131632382024-01-27 19:51:08
6114영등포구AF-YDP-2018240AC425E8F4219562024-01-23 14:51:13
24125영등포구AF-YDP-2018240AC4208BE4121514152024-01-28 06:21:48
20096영등포구AF-YDP-2018240AC4207398181620242024-01-27 05:31:05
12724영등포구AF-YDP-2018240AC42651B41610992024-01-25 07:51:09
2465영등포구AF-YDP-2018240AC420731429718192024-01-22 15:41:08
11790영등포구AF-YDP-2018240AC4208BE414913142024-01-25 02:11:44
10497영등포구AF-YDP-2018240AC425C9EC2012682024-01-24 18:11:10
13465영등포구AF-YDP-2018240AC4208BE4239352024-01-25 12:31:10
6047영등포구AF-YDP-2018240AC420739C251212152024-01-23 14:31:08