Overview

Dataset statistics

Number of variables8
Number of observations3964
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory263.4 KiB
Average record size in memory68.0 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
온도(℃) is highly overall correlated with 시리얼High correlation
습도(%) is highly overall correlated with 시리얼High correlation
초미세먼지(㎍/㎥) is highly overall correlated with 미세먼지(㎍/㎥)High correlation
미세먼지(㎍/㎥) is highly overall correlated with 초미세먼지(㎍/㎥)High correlation
시리얼 is highly overall correlated with 온도(℃) and 1 other fieldsHigh correlation

Reproduction

Analysis started2024-05-11 15:53:28.049899
Analysis finished2024-05-11 15:53:31.734783
Duration3.68 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기관 명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size31.1 KiB
영등포구
3964 

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 3964
100.0%

Length

2024-05-12T00:53:31.839179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-12T00:53:32.002476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영등포구 3964
100.0%

모델명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size31.1 KiB
AF-YDP-2018
3964 

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 3964
100.0%

Length

2024-05-12T00:53:32.168217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-12T00:53:32.331674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
af-ydp-2018 3964
100.0%

시리얼
Categorical

HIGH CORRELATION 

Distinct29
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size31.1 KiB
240AC4207314
 
144
240AC4207398
 
144
240AC420739C
 
144
240AC42073B8
 
144
240AC4207414
 
144
Other values (24)
3244 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row240AC4207314
2nd row240AC4207398
3rd row240AC420739C
4th row240AC42073B8
5th row240AC4207414

Common Values

ValueCountFrequency (%)
240AC4207314 144
 
3.6%
240AC4207398 144
 
3.6%
240AC420739C 144
 
3.6%
240AC42073B8 144
 
3.6%
240AC4207414 144
 
3.6%
240AC4208BA4 144
 
3.6%
240AC4208BD0 144
 
3.6%
240AC4208BE4 144
 
3.6%
240AC4208C00 144
 
3.6%
240AC425C9EC 144
 
3.6%
Other values (19) 2524
63.7%

Length

2024-05-12T00:53:32.497607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
240ac4207314 144
 
3.6%
240ac4207398 144
 
3.6%
240ac4265a9c 144
 
3.6%
240ac42651e4 144
 
3.6%
240ac42651cc 144
 
3.6%
240ac42651b4 144
 
3.6%
240ac42651ac 144
 
3.6%
240ac4265148 144
 
3.6%
240ac42620f0 144
 
3.6%
240ac425e8f4 144
 
3.6%
Other values (19) 2524
63.7%

온도(℃)
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.152624
Minimum11
Maximum28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size35.0 KiB
2024-05-12T00:53:32.671740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile13
Q116
median18
Q320
95-th percentile25
Maximum28
Range17
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.3800659
Coefficient of variation (CV)0.18620261
Kurtosis0.11814352
Mean18.152624
Median Absolute Deviation (MAD)2
Skewness0.64358964
Sum71957
Variance11.424845
MonotonicityNot monotonic
2024-05-12T00:53:32.871015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
18 739
18.6%
19 494
12.5%
17 467
11.8%
16 377
9.5%
15 320
8.1%
14 319
8.0%
20 279
 
7.0%
24 156
 
3.9%
13 155
 
3.9%
23 120
 
3.0%
Other values (8) 538
13.6%
ValueCountFrequency (%)
11 7
 
0.2%
12 70
 
1.8%
13 155
 
3.9%
14 319
8.0%
15 320
8.1%
16 377
9.5%
17 467
11.8%
18 739
18.6%
19 494
12.5%
20 279
 
7.0%
ValueCountFrequency (%)
28 12
 
0.3%
27 38
 
1.0%
26 112
 
2.8%
25 89
 
2.2%
24 156
 
3.9%
23 120
 
3.0%
22 107
 
2.7%
21 103
 
2.6%
20 279
7.0%
19 494
12.5%

습도(%)
Real number (ℝ)

HIGH CORRELATION 

Distinct35
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.175832
Minimum4
Maximum39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size35.0 KiB
2024-05-12T00:53:33.121044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile8
Q112
median13
Q316
95-th percentile20
Maximum39
Range35
Interquartile range (IQR)4

Descriptive statistics

Standard deviation4.8185979
Coefficient of variation (CV)0.3399164
Kurtosis7.9119238
Mean14.175832
Median Absolute Deviation (MAD)2
Skewness2.2243489
Sum56193
Variance23.218886
MonotonicityNot monotonic
2024-05-12T00:53:33.359231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
13 708
17.9%
12 445
11.2%
15 426
10.7%
14 386
9.7%
16 341
8.6%
17 283
 
7.1%
10 237
 
6.0%
9 205
 
5.2%
11 197
 
5.0%
18 197
 
5.0%
Other values (25) 539
13.6%
ValueCountFrequency (%)
4 12
 
0.3%
5 9
 
0.2%
6 25
 
0.6%
7 87
 
2.2%
8 96
 
2.4%
9 205
 
5.2%
10 237
 
6.0%
11 197
 
5.0%
12 445
11.2%
13 708
17.9%
ValueCountFrequency (%)
39 3
 
0.1%
38 5
 
0.1%
37 12
0.3%
36 13
0.3%
35 18
0.5%
34 27
0.7%
33 21
0.5%
32 12
0.3%
31 17
0.4%
30 2
 
0.1%

초미세먼지(㎍/㎥)
Real number (ℝ)

HIGH CORRELATION 

Distinct32
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.3940464
Minimum0
Maximum31
Zeros36
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size35.0 KiB
2024-05-12T00:53:33.593193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q16
median8
Q311
95-th percentile20
Maximum31
Range31
Interquartile range (IQR)5

Descriptive statistics

Standard deviation4.9352737
Coefficient of variation (CV)0.52536186
Kurtosis2.0326088
Mean9.3940464
Median Absolute Deviation (MAD)2
Skewness1.1970902
Sum37238
Variance24.356926
MonotonicityNot monotonic
2024-05-12T00:53:33.811453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
8 468
11.8%
7 422
10.6%
6 381
9.6%
9 375
9.5%
10 371
9.4%
5 312
 
7.9%
11 312
 
7.9%
12 203
 
5.1%
4 157
 
4.0%
13 117
 
3.0%
Other values (22) 846
21.3%
ValueCountFrequency (%)
0 36
 
0.9%
1 67
 
1.7%
2 71
 
1.8%
3 69
 
1.7%
4 157
 
4.0%
5 312
7.9%
6 381
9.6%
7 422
10.6%
8 468
11.8%
9 375
9.5%
ValueCountFrequency (%)
31 4
 
0.1%
30 6
 
0.2%
29 3
 
0.1%
28 6
 
0.2%
27 5
 
0.1%
26 10
 
0.3%
25 17
0.4%
24 23
0.6%
23 29
0.7%
22 32
0.8%

미세먼지(㎍/㎥)
Real number (ℝ)

HIGH CORRELATION 

Distinct40
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.30222
Minimum0
Maximum42
Zeros21
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size35.0 KiB
2024-05-12T00:53:34.174130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q17
median10
Q314
95-th percentile23
Maximum42
Range42
Interquartile range (IQR)7

Descriptive statistics

Standard deviation5.8522894
Coefficient of variation (CV)0.51779999
Kurtosis1.9905669
Mean11.30222
Median Absolute Deviation (MAD)3
Skewness1.1229926
Sum44802
Variance34.249291
MonotonicityNot monotonic
2024-05-12T00:53:34.406420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
10 350
 
8.8%
9 344
 
8.7%
8 334
 
8.4%
11 323
 
8.1%
12 307
 
7.7%
7 296
 
7.5%
13 281
 
7.1%
6 229
 
5.8%
5 174
 
4.4%
14 173
 
4.4%
Other values (30) 1153
29.1%
ValueCountFrequency (%)
0 21
 
0.5%
1 57
 
1.4%
2 58
 
1.5%
3 70
 
1.8%
4 89
 
2.2%
5 174
4.4%
6 229
5.8%
7 296
7.5%
8 334
8.4%
9 344
8.7%
ValueCountFrequency (%)
42 1
 
< 0.1%
40 2
 
0.1%
38 1
 
< 0.1%
37 1
 
< 0.1%
35 4
 
0.1%
34 3
 
0.1%
33 8
0.2%
32 8
0.2%
31 11
0.3%
30 8
0.2%

등록일시
Date

Distinct836
Distinct (%)21.1%
Missing0
Missing (%)0.0%
Memory size31.1 KiB
Minimum2024-01-13 00:01:04
Maximum2024-01-13 23:51:09
2024-05-12T00:53:34.645844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-12T00:53:34.885285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2024-05-12T00:53:30.739980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-12T00:53:28.578511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-12T00:53:29.363378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-12T00:53:30.038682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-12T00:53:30.897961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-12T00:53:28.741993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-12T00:53:29.539926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-12T00:53:30.204707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-12T00:53:31.063305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-12T00:53:28.917669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-12T00:53:29.713314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-12T00:53:30.383954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-12T00:53:31.220893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-12T00:53:29.085362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-12T00:53:29.881063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-12T00:53:30.573021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-12T00:53:35.038935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시리얼온도(℃)습도(%)초미세먼지(㎍/㎥)미세먼지(㎍/㎥)
시리얼1.0000.8900.8860.7660.730
온도(℃)0.8901.0000.6830.6050.550
습도(%)0.8860.6831.0000.5750.556
초미세먼지(㎍/㎥)0.7660.6050.5751.0000.953
미세먼지(㎍/㎥)0.7300.5500.5560.9531.000
2024-05-12T00:53:35.207811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
온도(℃)습도(%)초미세먼지(㎍/㎥)미세먼지(㎍/㎥)시리얼
온도(℃)1.000-0.239-0.301-0.3010.577
습도(%)-0.2391.000-0.395-0.3620.543
초미세먼지(㎍/㎥)-0.301-0.3951.0000.9520.395
미세먼지(㎍/㎥)-0.301-0.3620.9521.0000.357
시리얼0.5770.5430.3950.3571.000

Missing values

2024-05-12T00:53:31.419313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-12T00:53:31.644716image/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
0영등포구AF-YDP-2018240AC42073141813892024-01-13 00:01:04
1영등포구AF-YDP-2018240AC4207398132012152024-01-13 00:01:04
2영등포구AF-YDP-2018240AC420739C1918782024-01-13 00:01:05
3영등포구AF-YDP-2018240AC42073B82018442024-01-13 00:01:05
4영등포구AF-YDP-2018240AC42074141712662024-01-13 00:01:05
5영등포구AF-YDP-2018240AC4208BA4173613182024-01-13 00:01:05
6영등포구AF-YDP-2018240AC4208BD01910772024-01-13 00:01:05
7영등포구AF-YDP-2018240AC4208BE41812882024-01-13 00:01:05
8영등포구AF-YDP-2018240AC4208C002314682024-01-13 00:01:06
9영등포구AF-YDP-2018240AC425C9EC1813662024-01-13 00:01:06
기관 명모델명시리얼온도(℃)습도(%)초미세먼지(㎍/㎥)미세먼지(㎍/㎥)등록일시
3954영등포구AF-YDP-2018240AC425E790191412152024-01-13 23:51:08
3955영등포구AF-YDP-2018240AC425E7F4131520222024-01-13 23:51:08
3956영등포구AF-YDP-2018240AC425E8F4131324252024-01-13 23:51:08
3957영등포구AF-YDP-2018240AC42620F0141325352024-01-13 23:51:08
3958영등포구AF-YDP-2018240AC4265148181613142024-01-13 23:51:08
3959영등포구AF-YDP-2018240AC42651AC141521232024-01-13 23:51:08
3960영등포구AF-YDP-2018240AC42651B4161415172024-01-13 23:51:08
3961영등포구AF-YDP-2018240AC42651CC2689102024-01-13 23:51:09
3962영등포구AF-YDP-2018240AC42651E4191611112024-01-13 23:51:09
3963영등포구AF-YDP-2018240AC4265A9C181614142024-01-13 23:51:09