Overview

Dataset statistics

Number of variables30
Number of observations500
Missing cells5496
Missing cells (%)36.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory130.5 KiB
Average record size in memory267.3 B

Variable types

Categorical2
Text1
Numeric26
DateTime1

Dataset

Description샘플 데이터
AuthorIoT 도시데이터 시스템
URLhttps://bigdata.seoul.go.kr/data/selectSampleData.do?sample_data_seq=328

Alerts

모델명(MODEL) has constant value ""Constant
암모니아(ppm)(AMMONIA) is highly imbalanced (74.9%)Imbalance
풍향(°)(WIND_DIRE) has 478 (95.6%) missing valuesMissing
풍속(m/s)(WIND_SPEED) has 473 (94.6%) missing valuesMissing
돌풍풍향(°)(GUST_DIRE) has 464 (92.8%) missing valuesMissing
돌풍풍속(m/s)(GUST_SPEED) has 477 (95.4%) missing valuesMissing
조도(lux)(INTE_ILLU) has 81 (16.2%) missing valuesMissing
자외선(UVI)(ULTRA_RAYS) has 92 (18.4%) missing valuesMissing
진동(x)(g)(VIBR_X) has 89 (17.8%) missing valuesMissing
진동(y)(g)(VIBR_Y) has 77 (15.4%) missing valuesMissing
진동(z)(g)(VIBR_Z) has 104 (20.8%) missing valuesMissing
진동(x)최대(g)(VIBR_X_MAX) has 85 (17.0%) missing valuesMissing
진동(y)최대(g)(VIBR_Y_MAX) has 100 (20.0%) missing valuesMissing
진동(z)최대(g)(VIBR_Z_MAX) has 98 (19.6%) missing valuesMissing
흑구온도(℃)(EFFE_TEMP) has 486 (97.2%) missing valuesMissing
일산화탄소(ppm)(CARBON_MONO) has 480 (96.0%) missing valuesMissing
이산화질소(ppm)(NITROGEN_DIO) has 477 (95.4%) missing valuesMissing
이산화황(ppm)(SULFUR_DIO) has 475 (95.0%) missing valuesMissing
황화수소(ppm)(HYDROGEN_SULF) has 475 (95.0%) missing valuesMissing
오존(ppm)(OZONE) has 483 (96.6%) missing valuesMissing
측정시간(REG_DATE) has unique valuesUnique
등록일시(DB_DATE) has unique valuesUnique
조도(lux)(INTE_ILLU) has 106 (21.2%) zerosZeros
자외선(UVI)(ULTRA_RAYS) has 252 (50.4%) zerosZeros
황화수소(ppm)(HYDROGEN_SULF) has 18 (3.6%) zerosZeros

Reproduction

Analysis started2024-01-14 06:49:22.603005
Analysis finished2024-01-14 06:49:23.254339
Duration0.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

모델명(MODEL)
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
SDOT001
500 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSDOT001
2nd rowSDOT001
3rd rowSDOT001
4th rowSDOT001
5th rowSDOT001

Common Values

ValueCountFrequency (%)
SDOT001 500
100.0%

Length

2024-01-14T15:49:23.321264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-14T15:49:23.402866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
sdot001 500
100.0%

시리얼(SERIAL)
Text

Distinct396
Distinct (%)79.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2024-01-14T15:49:23.611688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters5500
Distinct characters15
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique299 ?
Unique (%)59.8%

Sample

1st rowOC3CL200089
2nd rowV02Q1940548
3rd rowV02Q1940521
4th rowOC3CL200060
5th rowOC3CL200036
ValueCountFrequency (%)
v02q1940280 4
 
0.8%
v02q1940537 3
 
0.6%
v02q1940669 3
 
0.6%
v02q1940703 3
 
0.6%
v02q1940070 3
 
0.6%
v02q1940787 3
 
0.6%
oc3cl200113 2
 
0.4%
v02q1940379 2
 
0.4%
v02q1940132 2
 
0.4%
v02q1940267 2
 
0.4%
Other values (386) 473
94.6%
2024-01-14T15:49:23.963422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1173
21.3%
2 649
11.8%
1 594
10.8%
4 541
9.8%
9 520
9.5%
V 400
 
7.3%
Q 400
 
7.3%
3 247
 
4.5%
C 200
 
3.6%
7 167
 
3.0%
Other values (5) 609
11.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4300
78.2%
Uppercase Letter 1200
 
21.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1173
27.3%
2 649
15.1%
1 594
13.8%
4 541
12.6%
9 520
12.1%
3 247
 
5.7%
7 167
 
3.9%
8 142
 
3.3%
6 136
 
3.2%
5 131
 
3.0%
Uppercase Letter
ValueCountFrequency (%)
V 400
33.3%
Q 400
33.3%
C 200
16.7%
O 100
 
8.3%
L 100
 
8.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4300
78.2%
Latin 1200
 
21.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1173
27.3%
2 649
15.1%
1 594
13.8%
4 541
12.6%
9 520
12.1%
3 247
 
5.7%
7 167
 
3.9%
8 142
 
3.3%
6 136
 
3.2%
5 131
 
3.0%
Latin
ValueCountFrequency (%)
V 400
33.3%
Q 400
33.3%
C 200
16.7%
O 100
 
8.3%
L 100
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5500
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1173
21.3%
2 649
11.8%
1 594
10.8%
4 541
9.8%
9 520
9.5%
V 400
 
7.3%
Q 400
 
7.3%
3 247
 
4.5%
C 200
 
3.6%
7 167
 
3.0%
Other values (5) 609
11.1%

초미세먼지(㎍/㎥)(PM25)
Real number (ℝ)

Distinct34
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.988
Minimum0
Maximum81
Zeros5
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-01-14T15:49:24.102761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q16
median9
Q314
95-th percentile22
Maximum81
Range81
Interquartile range (IQR)8

Descriptive statistics

Standard deviation7.5473028
Coefficient of variation (CV)0.68686775
Kurtosis26.038979
Mean10.988
Median Absolute Deviation (MAD)4
Skewness3.5467301
Sum5494
Variance56.96178
MonotonicityNot monotonic
2024-01-14T15:49:24.226156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
7 41
 
8.2%
8 41
 
8.2%
6 38
 
7.6%
9 38
 
7.6%
5 30
 
6.0%
4 29
 
5.8%
10 29
 
5.8%
11 26
 
5.2%
12 23
 
4.6%
14 23
 
4.6%
Other values (24) 182
36.4%
ValueCountFrequency (%)
0 5
 
1.0%
1 4
 
0.8%
2 8
 
1.6%
3 20
4.0%
4 29
5.8%
5 30
6.0%
6 38
7.6%
7 41
8.2%
8 41
8.2%
9 38
7.6%
ValueCountFrequency (%)
81 1
 
0.2%
73 1
 
0.2%
60 1
 
0.2%
35 1
 
0.2%
31 1
 
0.2%
28 1
 
0.2%
27 2
 
0.4%
26 1
 
0.2%
25 4
0.8%
24 6
1.2%

미세먼지(㎍/㎥)(PM10)
Real number (ℝ)

Distinct40
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.01
Minimum0
Maximum85
Zeros2
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-01-14T15:49:24.366506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q18
median12
Q317
95-th percentile26
Maximum85
Range85
Interquartile range (IQR)9

Descriptive statistics

Standard deviation7.8519556
Coefficient of variation (CV)0.60353233
Kurtosis14.530898
Mean13.01
Median Absolute Deviation (MAD)5
Skewness2.2821815
Sum6505
Variance61.653206
MonotonicityNot monotonic
2024-01-14T15:49:24.503767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
9 36
 
7.2%
10 34
 
6.8%
12 32
 
6.4%
8 31
 
6.2%
7 30
 
6.0%
14 27
 
5.4%
11 27
 
5.4%
4 24
 
4.8%
6 24
 
4.8%
16 21
 
4.2%
Other values (30) 214
42.8%
ValueCountFrequency (%)
0 2
 
0.4%
1 4
 
0.8%
2 5
 
1.0%
3 10
 
2.0%
4 24
4.8%
5 21
4.2%
6 24
4.8%
7 30
6.0%
8 31
6.2%
9 36
7.2%
ValueCountFrequency (%)
85 1
 
0.2%
50 1
 
0.2%
38 1
 
0.2%
37 2
0.4%
36 1
 
0.2%
35 1
 
0.2%
34 1
 
0.2%
32 1
 
0.2%
31 3
0.6%
30 3
0.6%

기온(℃)(TEMP)
Real number (ℝ)

Distinct119
Distinct (%)23.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30.6254
Minimum-40
Maximum38.6
Zeros0
Zeros (%)0.0%
Negative1
Negative (%)0.2%
Memory size4.5 KiB
2024-01-14T15:49:24.651905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-40
5-th percentile26.295
Q128.6
median30.5
Q333
95-th percentile35.7
Maximum38.6
Range78.6
Interquartile range (IQR)4.4

Descriptive statistics

Standard deviation4.3225205
Coefficient of variation (CV)0.14114168
Kurtosis142.02173
Mean30.6254
Median Absolute Deviation (MAD)2.1
Skewness-8.6855944
Sum15312.7
Variance18.684183
MonotonicityNot monotonic
2024-01-14T15:49:24.813328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30.0 11
 
2.2%
29.9 11
 
2.2%
35.0 11
 
2.2%
30.2 10
 
2.0%
30.4 10
 
2.0%
28.5 9
 
1.8%
29.0 8
 
1.6%
30.9 8
 
1.6%
28.8 8
 
1.6%
30.5 8
 
1.6%
Other values (109) 406
81.2%
ValueCountFrequency (%)
-40.0 1
 
0.2%
24.1 1
 
0.2%
24.9 1
 
0.2%
25.0 3
0.6%
25.2 2
0.4%
25.3 1
 
0.2%
25.5 1
 
0.2%
25.7 1
 
0.2%
25.8 2
0.4%
25.9 3
0.6%
ValueCountFrequency (%)
38.6 1
0.2%
37.9 1
0.2%
37.5 1
0.2%
36.8 1
0.2%
36.6 2
0.4%
36.4 1
0.2%
36.3 2
0.4%
36.2 1
0.2%
36.1 1
0.2%
36.0 2
0.4%

상대습도(%)(HUMI)
Real number (ℝ)

Distinct55
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean67.486
Minimum45
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-01-14T15:49:25.013917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum45
5-th percentile49
Q156
median64
Q378
95-th percentile96
Maximum100
Range55
Interquartile range (IQR)22

Descriptive statistics

Standard deviation15.007874
Coefficient of variation (CV)0.222385
Kurtosis-0.61460465
Mean67.486
Median Absolute Deviation (MAD)10
Skewness0.66587135
Sum33743
Variance225.23628
MonotonicityNot monotonic
2024-01-14T15:49:25.160696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
56 23
 
4.6%
58 20
 
4.0%
100 19
 
3.8%
54 18
 
3.6%
55 17
 
3.4%
59 15
 
3.0%
63 15
 
3.0%
64 15
 
3.0%
49 14
 
2.8%
53 14
 
2.8%
Other values (45) 330
66.0%
ValueCountFrequency (%)
45 3
 
0.6%
46 4
 
0.8%
47 9
1.8%
48 7
 
1.4%
49 14
2.8%
50 12
2.4%
51 13
2.6%
52 12
2.4%
53 14
2.8%
54 18
3.6%
ValueCountFrequency (%)
100 19
3.8%
99 2
 
0.4%
97 2
 
0.4%
96 9
1.8%
95 5
 
1.0%
94 8
1.6%
93 8
1.6%
92 4
 
0.8%
91 2
 
0.4%
90 5
 
1.0%

풍향(°)(WIND_DIRE)
Real number (ℝ)

MISSING 

Distinct22
Distinct (%)100.0%
Missing478
Missing (%)95.6%
Infinite0
Infinite (%)0.0%
Mean209.22727
Minimum3
Maximum328
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-01-14T15:49:25.282726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile45.43
Q1183.25
median208.5
Q3287
95-th percentile315.65
Maximum328
Range325
Interquartile range (IQR)103.75

Descriptive statistics

Standard deviation89.444301
Coefficient of variation (CV)0.42749829
Kurtosis0.29059186
Mean209.22727
Median Absolute Deviation (MAD)56.5
Skewness-0.83354427
Sum4603
Variance8000.283
MonotonicityNot monotonic
2024-01-14T15:49:25.400590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
190.0 1
 
0.2%
198.0 1
 
0.2%
3.0 1
 
0.2%
49.8 1
 
0.2%
291.0 1
 
0.2%
309.0 1
 
0.2%
164.0 1
 
0.2%
234.0 1
 
0.2%
290.0 1
 
0.2%
316.0 1
 
0.2%
Other values (12) 12
 
2.4%
(Missing) 478
95.6%
ValueCountFrequency (%)
3.0 1
0.2%
45.2 1
0.2%
49.8 1
0.2%
151.0 1
0.2%
164.0 1
0.2%
182.0 1
0.2%
187.0 1
0.2%
188.0 1
0.2%
190.0 1
0.2%
195.0 1
0.2%
ValueCountFrequency (%)
328.0 1
0.2%
316.0 1
0.2%
309.0 1
0.2%
299.0 1
0.2%
291.0 1
0.2%
290.0 1
0.2%
278.0 1
0.2%
264.0 1
0.2%
234.0 1
0.2%
222.0 1
0.2%

풍속(m/s)(WIND_SPEED)
Real number (ℝ)

MISSING 

Distinct15
Distinct (%)55.6%
Missing473
Missing (%)94.6%
Infinite0
Infinite (%)0.0%
Mean0.9037037
Minimum0.1
Maximum2.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-01-14T15:49:25.514739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile0.1
Q10.25
median0.6
Q31.3
95-th percentile2.34
Maximum2.9
Range2.8
Interquartile range (IQR)1.05

Descriptive statistics

Standard deviation0.82670871
Coefficient of variation (CV)0.91480062
Kurtosis-0.15171376
Mean0.9037037
Median Absolute Deviation (MAD)0.5
Skewness0.96349262
Sum24.4
Variance0.68344729
MonotonicityNot monotonic
2024-01-14T15:49:25.631202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0.1 5
 
1.0%
0.3 3
 
0.6%
1.2 3
 
0.6%
0.5 2
 
0.4%
2.2 2
 
0.4%
0.2 2
 
0.4%
0.8 2
 
0.4%
0.7 1
 
0.2%
2.9 1
 
0.2%
1.7 1
 
0.2%
Other values (5) 5
 
1.0%
(Missing) 473
94.6%
ValueCountFrequency (%)
0.1 5
1.0%
0.2 2
 
0.4%
0.3 3
0.6%
0.4 1
 
0.2%
0.5 2
 
0.4%
0.6 1
 
0.2%
0.7 1
 
0.2%
0.8 2
 
0.4%
1.2 3
0.6%
1.4 1
 
0.2%
ValueCountFrequency (%)
2.9 1
 
0.2%
2.4 1
 
0.2%
2.2 2
0.4%
1.9 1
 
0.2%
1.7 1
 
0.2%
1.4 1
 
0.2%
1.2 3
0.6%
0.8 2
0.4%
0.7 1
 
0.2%
0.6 1
 
0.2%

돌풍풍향(°)(GUST_DIRE)
Real number (ℝ)

MISSING 

Distinct30
Distinct (%)83.3%
Missing464
Missing (%)92.8%
Infinite0
Infinite (%)0.0%
Mean197.99167
Minimum5.6
Maximum357
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-01-14T15:49:25.786904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5.6
5-th percentile20.4
Q1131.25
median230
Q3241.75
95-th percentile354
Maximum357
Range351.4
Interquartile range (IQR)110.5

Descriptive statistics

Standard deviation103.419
Coefficient of variation (CV)0.52234017
Kurtosis-0.66426575
Mean197.99167
Median Absolute Deviation (MAD)50.5
Skewness-0.45385762
Sum7127.7
Variance10695.49
MonotonicityNot monotonic
2024-01-14T15:49:25.921174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
241.0 3
 
0.6%
230.0 3
 
0.6%
233.0 2
 
0.4%
354.0 2
 
0.4%
244.0 1
 
0.2%
194.0 1
 
0.2%
264.0 1
 
0.2%
22.5 1
 
0.2%
326.0 1
 
0.2%
239.0 1
 
0.2%
Other values (20) 20
 
4.0%
(Missing) 464
92.8%
ValueCountFrequency (%)
5.6 1
0.2%
14.1 1
0.2%
22.5 1
0.2%
28.1 1
0.2%
36.6 1
0.2%
47.8 1
0.2%
53.4 1
0.2%
95.6 1
0.2%
129.0 1
0.2%
132.0 1
0.2%
ValueCountFrequency (%)
357.0 1
 
0.2%
354.0 2
0.4%
331.0 1
 
0.2%
326.0 1
 
0.2%
323.0 1
 
0.2%
275.0 1
 
0.2%
264.0 1
 
0.2%
244.0 1
 
0.2%
241.0 3
0.6%
239.0 1
 
0.2%

돌풍풍속(m/s)(GUST_SPEED)
Real number (ℝ)

MISSING 

Distinct16
Distinct (%)69.6%
Missing477
Missing (%)95.4%
Infinite0
Infinite (%)0.0%
Mean1.5956522
Minimum0
Maximum3.2
Zeros2
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-01-14T15:49:26.029589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.04
Q10.95
median1.6
Q32.1
95-th percentile2.99
Maximum3.2
Range3.2
Interquartile range (IQR)1.15

Descriptive statistics

Standard deviation0.92366772
Coefficient of variation (CV)0.57886533
Kurtosis-0.66681505
Mean1.5956522
Median Absolute Deviation (MAD)0.5
Skewness-0.0092346336
Sum36.7
Variance0.85316206
MonotonicityNot monotonic
2024-01-14T15:49:26.126070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
1.6 4
 
0.8%
0.0 2
 
0.4%
0.7 2
 
0.4%
2.1 2
 
0.4%
1.5 2
 
0.4%
0.4 1
 
0.2%
1.7 1
 
0.2%
1.3 1
 
0.2%
2.9 1
 
0.2%
0.6 1
 
0.2%
Other values (6) 6
 
1.2%
(Missing) 477
95.4%
ValueCountFrequency (%)
0.0 2
0.4%
0.4 1
 
0.2%
0.6 1
 
0.2%
0.7 2
0.4%
1.2 1
 
0.2%
1.3 1
 
0.2%
1.5 2
0.4%
1.6 4
0.8%
1.7 1
 
0.2%
2.0 1
 
0.2%
ValueCountFrequency (%)
3.2 1
 
0.2%
3.0 1
 
0.2%
2.9 1
 
0.2%
2.8 1
 
0.2%
2.6 1
 
0.2%
2.1 2
0.4%
2.0 1
 
0.2%
1.7 1
 
0.2%
1.6 4
0.8%
1.5 2
0.4%

조도(lux)(INTE_ILLU)
Real number (ℝ)

MISSING  ZEROS 

Distinct267
Distinct (%)63.7%
Missing81
Missing (%)16.2%
Infinite0
Infinite (%)0.0%
Mean5644.6539
Minimum0
Maximum84313
Zeros106
Zeros (%)21.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-01-14T15:49:26.263896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median927
Q37294.5
95-th percentile23361.7
Maximum84313
Range84313
Interquartile range (IQR)7294.5

Descriptive statistics

Standard deviation10370.936
Coefficient of variation (CV)1.8373024
Kurtosis15.371768
Mean5644.6539
Median Absolute Deviation (MAD)927
Skewness3.3800589
Sum2365110
Variance1.0755632 × 108
MonotonicityNot monotonic
2024-01-14T15:49:26.395218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 106
21.2%
2 10
 
2.0%
1 9
 
1.8%
6 8
 
1.6%
10 6
 
1.2%
5 6
 
1.2%
3 4
 
0.8%
79 2
 
0.4%
22 2
 
0.4%
262 2
 
0.4%
Other values (257) 264
52.8%
(Missing) 81
 
16.2%
ValueCountFrequency (%)
0 106
21.2%
1 9
 
1.8%
2 10
 
2.0%
3 4
 
0.8%
4 2
 
0.4%
5 6
 
1.2%
6 8
 
1.6%
7 2
 
0.4%
8 1
 
0.2%
9 2
 
0.4%
ValueCountFrequency (%)
84313 1
0.2%
72036 1
0.2%
57712 1
0.2%
51408 1
0.2%
48421 1
0.2%
41664 1
0.2%
41373 1
0.2%
41173 1
0.2%
38357 1
0.2%
38200 1
0.2%

자외선(UVI)(ULTRA_RAYS)
Real number (ℝ)

MISSING  ZEROS 

Distinct29
Distinct (%)7.1%
Missing92
Missing (%)18.4%
Infinite0
Infinite (%)0.0%
Mean0.27598039
Minimum0
Maximum8.3
Zeros252
Zeros (%)50.4%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-01-14T15:49:26.522787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.2
95-th percentile1.165
Maximum8.3
Range8.3
Interquartile range (IQR)0.2

Descriptive statistics

Standard deviation0.86078161
Coefficient of variation (CV)3.1189955
Kurtosis39.564174
Mean0.27598039
Median Absolute Deviation (MAD)0
Skewness5.7672676
Sum112.6
Variance0.74094498
MonotonicityNot monotonic
2024-01-14T15:49:26.670691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0.0 252
50.4%
0.1 41
 
8.2%
0.2 29
 
5.8%
0.3 22
 
4.4%
0.4 18
 
3.6%
0.8 7
 
1.4%
0.5 5
 
1.0%
0.7 4
 
0.8%
0.6 3
 
0.6%
1.1 3
 
0.6%
Other values (19) 24
 
4.8%
(Missing) 92
 
18.4%
ValueCountFrequency (%)
0.0 252
50.4%
0.1 41
 
8.2%
0.2 29
 
5.8%
0.3 22
 
4.4%
0.4 18
 
3.6%
0.5 5
 
1.0%
0.6 3
 
0.6%
0.7 4
 
0.8%
0.8 7
 
1.4%
0.9 2
 
0.4%
ValueCountFrequency (%)
8.3 1
0.2%
7.0 1
0.2%
6.6 1
0.2%
5.5 1
0.2%
4.1 2
0.4%
3.3 1
0.2%
3.0 2
0.4%
2.9 1
0.2%
2.8 2
0.4%
2.7 1
0.2%

소음(dB)(NOISE)
Real number (ℝ)

Distinct38
Distinct (%)7.6%
Missing2
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean51.118474
Minimum35
Maximum73
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-01-14T15:49:26.833535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35
5-th percentile40
Q144
median50
Q357
95-th percentile65.15
Maximum73
Range38
Interquartile range (IQR)13

Descriptive statistics

Standard deviation8.2181046
Coefficient of variation (CV)0.16076584
Kurtosis-0.57476012
Mean51.118474
Median Absolute Deviation (MAD)6
Skewness0.36423405
Sum25457
Variance67.537244
MonotonicityNot monotonic
2024-01-14T15:49:26.985180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
48 35
 
7.0%
44 34
 
6.8%
52 29
 
5.8%
40 25
 
5.0%
56 23
 
4.6%
60 23
 
4.6%
49 22
 
4.4%
55 20
 
4.0%
43 20
 
4.0%
47 19
 
3.8%
Other values (28) 248
49.6%
ValueCountFrequency (%)
35 2
 
0.4%
36 5
 
1.0%
37 5
 
1.0%
38 1
 
0.2%
39 9
 
1.8%
40 25
5.0%
41 18
3.6%
42 13
 
2.6%
43 20
4.0%
44 34
6.8%
ValueCountFrequency (%)
73 1
 
0.2%
72 4
 
0.8%
70 1
 
0.2%
69 2
 
0.4%
68 9
1.8%
67 7
1.4%
66 1
 
0.2%
65 7
1.4%
64 12
2.4%
63 12
2.4%

진동(x)(g)(VIBR_X)
Real number (ℝ)

MISSING 

Distinct15
Distinct (%)3.6%
Missing89
Missing (%)17.8%
Infinite0
Infinite (%)0.0%
Mean0.028442822
Minimum0
Maximum0.14
Zeros1
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-01-14T15:49:27.110956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.01
Q10.01
median0.02
Q30.04
95-th percentile0.07
Maximum0.14
Range0.14
Interquartile range (IQR)0.03

Descriptive statistics

Standard deviation0.021034432
Coefficient of variation (CV)0.73953392
Kurtosis4.5003285
Mean0.028442822
Median Absolute Deviation (MAD)0.01
Skewness1.782122
Sum11.69
Variance0.00044244733
MonotonicityNot monotonic
2024-01-14T15:49:27.405491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0.01 126
25.2%
0.02 113
22.6%
0.04 47
 
9.4%
0.03 46
 
9.2%
0.05 39
 
7.8%
0.06 17
 
3.4%
0.07 8
 
1.6%
0.08 6
 
1.2%
0.1 2
 
0.4%
0.11 2
 
0.4%
Other values (5) 5
 
1.0%
(Missing) 89
17.8%
ValueCountFrequency (%)
0.0 1
 
0.2%
0.01 126
25.2%
0.02 113
22.6%
0.03 46
 
9.2%
0.04 47
 
9.4%
0.05 39
 
7.8%
0.06 17
 
3.4%
0.07 8
 
1.6%
0.08 6
 
1.2%
0.09 1
 
0.2%
ValueCountFrequency (%)
0.14 1
 
0.2%
0.13 1
 
0.2%
0.12 1
 
0.2%
0.11 2
 
0.4%
0.1 2
 
0.4%
0.09 1
 
0.2%
0.08 6
 
1.2%
0.07 8
 
1.6%
0.06 17
3.4%
0.05 39
7.8%

진동(y)(g)(VIBR_Y)
Real number (ℝ)

MISSING 

Distinct17
Distinct (%)4.0%
Missing77
Missing (%)15.4%
Infinite0
Infinite (%)0.0%
Mean0.061583924
Minimum0.01
Maximum0.17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-01-14T15:49:27.524693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile0.02
Q10.03
median0.05
Q30.09
95-th percentile0.13
Maximum0.17
Range0.16
Interquartile range (IQR)0.06

Descriptive statistics

Standard deviation0.038207427
Coefficient of variation (CV)0.62041235
Kurtosis-0.49680012
Mean0.061583924
Median Absolute Deviation (MAD)0.03
Skewness0.64518323
Sum26.05
Variance0.0014598075
MonotonicityNot monotonic
2024-01-14T15:49:27.681453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0.02 74
14.8%
0.03 46
9.2%
0.04 42
8.4%
0.05 39
7.8%
0.08 31
6.2%
0.07 30
 
6.0%
0.09 29
 
5.8%
0.06 28
 
5.6%
0.1 23
 
4.6%
0.01 17
 
3.4%
Other values (7) 64
12.8%
(Missing) 77
15.4%
ValueCountFrequency (%)
0.01 17
 
3.4%
0.02 74
14.8%
0.03 46
9.2%
0.04 42
8.4%
0.05 39
7.8%
0.06 28
 
5.6%
0.07 30
6.0%
0.08 31
6.2%
0.09 29
 
5.8%
0.1 23
 
4.6%
ValueCountFrequency (%)
0.17 2
 
0.4%
0.16 3
 
0.6%
0.15 3
 
0.6%
0.14 13
2.6%
0.13 13
2.6%
0.12 14
2.8%
0.11 16
3.2%
0.1 23
4.6%
0.09 29
5.8%
0.08 31
6.2%

진동(z)(g)(VIBR_Z)
Real number (ℝ)

MISSING 

Distinct20
Distinct (%)5.1%
Missing104
Missing (%)20.8%
Infinite0
Infinite (%)0.0%
Mean1.0218939
Minimum0.94
Maximum1.14
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-01-14T15:49:27.831504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.94
5-th percentile0.97
Q11
median1.02
Q31.04
95-th percentile1.07
Maximum1.14
Range0.2
Interquartile range (IQR)0.04

Descriptive statistics

Standard deviation0.032618995
Coefficient of variation (CV)0.031920138
Kurtosis0.018420908
Mean1.0218939
Median Absolute Deviation (MAD)0.02
Skewness0.025979579
Sum404.67
Variance0.0010639988
MonotonicityNot monotonic
2024-01-14T15:49:27.962896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
1.01 48
9.6%
1.02 47
9.4%
1.04 47
9.4%
1.03 40
 
8.0%
1.05 40
 
8.0%
1.0 32
 
6.4%
0.99 27
 
5.4%
0.98 26
 
5.2%
1.06 24
 
4.8%
1.07 19
 
3.8%
Other values (10) 46
9.2%
(Missing) 104
20.8%
ValueCountFrequency (%)
0.94 3
 
0.6%
0.95 4
 
0.8%
0.96 10
 
2.0%
0.97 14
 
2.8%
0.98 26
5.2%
0.99 27
5.4%
1.0 32
6.4%
1.01 48
9.6%
1.02 47
9.4%
1.03 40
8.0%
ValueCountFrequency (%)
1.14 1
 
0.2%
1.12 1
 
0.2%
1.11 1
 
0.2%
1.1 1
 
0.2%
1.09 4
 
0.8%
1.08 7
 
1.4%
1.07 19
3.8%
1.06 24
4.8%
1.05 40
8.0%
1.04 47
9.4%

진동(x)최대(g)(VIBR_X_MAX)
Real number (ℝ)

MISSING 

Distinct11
Distinct (%)2.7%
Missing85
Missing (%)17.0%
Infinite0
Infinite (%)0.0%
Mean0.076771084
Minimum0.04
Maximum0.18
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-01-14T15:49:28.079121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.04
5-th percentile0.05
Q10.06
median0.08
Q30.09
95-th percentile0.11
Maximum0.18
Range0.14
Interquartile range (IQR)0.03

Descriptive statistics

Standard deviation0.024150957
Coefficient of variation (CV)0.31458403
Kurtosis1.9972073
Mean0.076771084
Median Absolute Deviation (MAD)0.02
Skewness1.0574385
Sum31.86
Variance0.00058326873
MonotonicityNot monotonic
2024-01-14T15:49:28.187633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0.08 101
20.2%
0.06 100
20.0%
0.05 67
13.4%
0.09 57
11.4%
0.1 33
 
6.6%
0.11 25
 
5.0%
0.04 13
 
2.6%
0.13 9
 
1.8%
0.14 5
 
1.0%
0.18 3
 
0.6%
(Missing) 85
17.0%
ValueCountFrequency (%)
0.04 13
 
2.6%
0.05 67
13.4%
0.06 100
20.0%
0.08 101
20.2%
0.09 57
11.4%
0.1 33
 
6.6%
0.11 25
 
5.0%
0.13 9
 
1.8%
0.14 5
 
1.0%
0.16 2
 
0.4%
ValueCountFrequency (%)
0.18 3
 
0.6%
0.16 2
 
0.4%
0.14 5
 
1.0%
0.13 9
 
1.8%
0.11 25
 
5.0%
0.1 33
 
6.6%
0.09 57
11.4%
0.08 101
20.2%
0.06 100
20.0%
0.05 67
13.4%

진동(y)최대(g)(VIBR_Y_MAX)
Real number (ℝ)

MISSING 

Distinct15
Distinct (%)3.8%
Missing100
Missing (%)20.0%
Infinite0
Infinite (%)0.0%
Mean0.137525
Minimum0.05
Maximum0.23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-01-14T15:49:28.335880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.05
5-th percentile0.08
Q10.1
median0.14
Q30.16
95-th percentile0.2
Maximum0.23
Range0.18
Interquartile range (IQR)0.06

Descriptive statistics

Standard deviation0.039547876
Coefficient of variation (CV)0.28756863
Kurtosis-0.91599435
Mean0.137525
Median Absolute Deviation (MAD)0.04
Skewness-0.0056753431
Sum55.01
Variance0.0015640345
MonotonicityNot monotonic
2024-01-14T15:49:28.525947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0.14 46
9.2%
0.13 45
9.0%
0.11 38
 
7.6%
0.16 38
 
7.6%
0.1 37
 
7.4%
0.09 35
 
7.0%
0.18 33
 
6.6%
0.2 32
 
6.4%
0.15 31
 
6.2%
0.19 29
 
5.8%
Other values (5) 36
 
7.2%
(Missing) 100
20.0%
ValueCountFrequency (%)
0.05 3
 
0.6%
0.06 11
 
2.2%
0.08 18
 
3.6%
0.09 35
7.0%
0.1 37
7.4%
0.11 38
7.6%
0.13 45
9.0%
0.14 46
9.2%
0.15 31
6.2%
0.16 38
7.6%
ValueCountFrequency (%)
0.23 1
 
0.2%
0.21 3
 
0.6%
0.2 32
6.4%
0.19 29
5.8%
0.18 33
6.6%
0.16 38
7.6%
0.15 31
6.2%
0.14 46
9.2%
0.13 45
9.0%
0.11 38
7.6%

진동(z)최대(g)(VIBR_Z_MAX)
Real number (ℝ)

MISSING 

Distinct18
Distinct (%)4.5%
Missing98
Missing (%)19.6%
Infinite0
Infinite (%)0.0%
Mean1.101592
Minimum0.99
Maximum1.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-01-14T15:49:28.649662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.99
5-th percentile1.03
Q11.08
median1.1
Q31.13
95-th percentile1.17
Maximum1.2
Range0.21
Interquartile range (IQR)0.05

Descriptive statistics

Standard deviation0.042195989
Coefficient of variation (CV)0.038304551
Kurtosis-0.28180401
Mean1.101592
Median Absolute Deviation (MAD)0.03
Skewness0.05004858
Sum442.84
Variance0.0017805015
MonotonicityNot monotonic
2024-01-14T15:49:28.794311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
1.1 53
10.6%
1.09 46
9.2%
1.08 44
8.8%
1.11 41
8.2%
1.13 39
 
7.8%
1.14 30
 
6.0%
1.06 29
 
5.8%
1.05 20
 
4.0%
1.15 19
 
3.8%
1.04 17
 
3.4%
Other values (8) 64
12.8%
(Missing) 98
19.6%
ValueCountFrequency (%)
0.99 1
 
0.2%
1.0 2
 
0.4%
1.01 7
 
1.4%
1.03 12
 
2.4%
1.04 17
 
3.4%
1.05 20
 
4.0%
1.06 29
5.8%
1.08 44
8.8%
1.09 46
9.2%
1.1 53
10.6%
ValueCountFrequency (%)
1.2 2
 
0.4%
1.19 16
 
3.2%
1.17 13
 
2.6%
1.16 11
 
2.2%
1.15 19
 
3.8%
1.14 30
6.0%
1.13 39
7.8%
1.11 41
8.2%
1.1 53
10.6%
1.09 46
9.2%

흑구온도(℃)(EFFE_TEMP)
Real number (ℝ)

MISSING 

Distinct14
Distinct (%)100.0%
Missing486
Missing (%)97.2%
Infinite0
Infinite (%)0.0%
Mean26.671429
Minimum21.5
Maximum29.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-01-14T15:49:28.907860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21.5
5-th percentile23.71
Q125.45
median26.5
Q328.25
95-th percentile29.475
Maximum29.8
Range8.3
Interquartile range (IQR)2.8

Descriptive statistics

Standard deviation2.1938475
Coefficient of variation (CV)0.082254594
Kurtosis1.0161797
Mean26.671429
Median Absolute Deviation (MAD)1.5
Skewness-0.70026441
Sum373.4
Variance4.812967
MonotonicityNot monotonic
2024-01-14T15:49:29.023948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
25.4 1
 
0.2%
26.2 1
 
0.2%
28.1 1
 
0.2%
26.3 1
 
0.2%
25.1 1
 
0.2%
25.6 1
 
0.2%
28.3 1
 
0.2%
26.7 1
 
0.2%
29.0 1
 
0.2%
29.8 1
 
0.2%
Other values (4) 4
 
0.8%
(Missing) 486
97.2%
ValueCountFrequency (%)
21.5 1
0.2%
24.9 1
0.2%
25.1 1
0.2%
25.4 1
0.2%
25.6 1
0.2%
26.2 1
0.2%
26.3 1
0.2%
26.7 1
0.2%
27.2 1
0.2%
28.1 1
0.2%
ValueCountFrequency (%)
29.8 1
0.2%
29.3 1
0.2%
29.0 1
0.2%
28.3 1
0.2%
28.1 1
0.2%
27.2 1
0.2%
26.7 1
0.2%
26.3 1
0.2%
26.2 1
0.2%
25.6 1
0.2%

초미세먼지보정(㎍/㎥)(PM25_STD)
Real number (ℝ)

Distinct31
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.744
Minimum0
Maximum210
Zeros1
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-01-14T15:49:29.193465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5
Q19
median11
Q315
95-th percentile22
Maximum210
Range210
Interquartile range (IQR)6

Descriptive statistics

Standard deviation10.687324
Coefficient of variation (CV)0.83861616
Kurtosis236.3218
Mean12.744
Median Absolute Deviation (MAD)3
Skewness13.256108
Sum6372
Variance114.2189
MonotonicityNot monotonic
2024-01-14T15:49:29.332634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
11 51
 
10.2%
10 50
 
10.0%
12 37
 
7.4%
9 37
 
7.4%
7 33
 
6.6%
13 32
 
6.4%
14 30
 
6.0%
8 30
 
6.0%
15 25
 
5.0%
17 24
 
4.8%
Other values (21) 151
30.2%
ValueCountFrequency (%)
0 1
 
0.2%
2 5
 
1.0%
3 4
 
0.8%
4 12
 
2.4%
5 16
 
3.2%
6 15
 
3.0%
7 33
6.6%
8 30
6.0%
9 37
7.4%
10 50
10.0%
ValueCountFrequency (%)
210 1
 
0.2%
83 1
 
0.2%
33 1
 
0.2%
29 1
 
0.2%
27 2
 
0.4%
26 4
0.8%
25 2
 
0.4%
24 4
0.8%
23 5
1.0%
22 6
1.2%

미세먼지보정(㎍/㎥)(PM10_STD)
Real number (ℝ)

Distinct38
Distinct (%)7.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.544
Minimum0
Maximum40
Zeros1
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-01-14T15:49:29.451351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5
Q111
median15
Q320
95-th percentile29
Maximum40
Range40
Interquartile range (IQR)9

Descriptive statistics

Standard deviation6.7235762
Coefficient of variation (CV)0.43255122
Kurtosis0.27426988
Mean15.544
Median Absolute Deviation (MAD)4
Skewness0.53020452
Sum7772
Variance45.206477
MonotonicityNot monotonic
2024-01-14T15:49:29.575996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
13 40
 
8.0%
14 34
 
6.8%
11 32
 
6.4%
16 31
 
6.2%
17 29
 
5.8%
18 28
 
5.6%
12 25
 
5.0%
15 24
 
4.8%
10 22
 
4.4%
19 20
 
4.0%
Other values (28) 215
43.0%
ValueCountFrequency (%)
0 1
 
0.2%
1 1
 
0.2%
2 1
 
0.2%
3 4
 
0.8%
4 6
 
1.2%
5 18
3.6%
6 9
1.8%
7 14
2.8%
8 16
3.2%
9 19
3.8%
ValueCountFrequency (%)
40 1
 
0.2%
36 1
 
0.2%
35 2
 
0.4%
34 2
 
0.4%
33 2
 
0.4%
32 2
 
0.4%
31 1
 
0.2%
30 8
1.6%
29 8
1.6%
28 4
0.8%

측정시간(REG_DATE)
Real number (ℝ)

UNIQUE 

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0209264 × 1011
Minimum2.0201112 × 1011
Maximum2.021112 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-01-14T15:49:29.766853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0201112 × 1011
5-th percentile2.0201198 × 1011
Q12.0210224 × 1011
median2.0210522 × 1011
Q32.0210822 × 1011
95-th percentile2.0211107 × 1011
Maximum2.021112 × 1011
Range1.0008184 × 108
Interquartile range (IQR)5980274.2

Descriptive statistics

Standard deviation33292262
Coefficient of variation (CV)0.00016473763
Kurtosis2.082135
Mean2.0209264 × 1011
Median Absolute Deviation (MAD)3009671
Skewness-2.0044173
Sum1.0104632 × 1014
Variance1.1083747 × 1015
MonotonicityNot monotonic
2024-01-14T15:49:29.953640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
202102091152 1
 
0.2%
202102282031 1
 
0.2%
202109071046 1
 
0.2%
202111202227 1
 
0.2%
202011271536 1
 
0.2%
202103212127 1
 
0.2%
202111130526 1
 
0.2%
202108050923 1
 
0.2%
202011300443 1
 
0.2%
202103071033 1
 
0.2%
Other values (490) 490
98.0%
ValueCountFrequency (%)
202011120400 1
0.2%
202011131238 1
0.2%
202011132332 1
0.2%
202011150043 1
0.2%
202011151801 1
0.2%
202011162054 1
0.2%
202011180633 1
0.2%
202011180922 1
0.2%
202011191819 1
0.2%
202011210557 1
0.2%
ValueCountFrequency (%)
202111202235 1
0.2%
202111202227 1
0.2%
202111201300 1
0.2%
202111191134 1
0.2%
202111190753 1
0.2%
202111181825 1
0.2%
202111180843 1
0.2%
202111180400 1
0.2%
202111172040 1
0.2%
202111171632 1
0.2%

일산화탄소(ppm)(CARBON_MONO)
Real number (ℝ)

MISSING 

Distinct20
Distinct (%)100.0%
Missing480
Missing (%)96.0%
Infinite0
Infinite (%)0.0%
Mean0.83425
Minimum0.529
Maximum1.234
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-01-14T15:49:30.101627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.529
5-th percentile0.54895
Q10.635
median0.8205
Q31.001
95-th percentile1.1789
Maximum1.234
Range0.705
Interquartile range (IQR)0.366

Descriptive statistics

Standard deviation0.22860075
Coefficient of variation (CV)0.27401948
Kurtosis-1.0710529
Mean0.83425
Median Absolute Deviation (MAD)0.1865
Skewness0.45717084
Sum16.685
Variance0.052258303
MonotonicityNot monotonic
2024-01-14T15:49:30.248405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0.529 1
 
0.2%
0.63 1
 
0.2%
0.835 1
 
0.2%
1.234 1
 
0.2%
0.591 1
 
0.2%
0.834 1
 
0.2%
0.55 1
 
0.2%
0.632 1
 
0.2%
0.689 1
 
0.2%
1.174 1
 
0.2%
Other values (10) 10
 
2.0%
(Missing) 480
96.0%
ValueCountFrequency (%)
0.529 1
0.2%
0.55 1
0.2%
0.591 1
0.2%
0.63 1
0.2%
0.632 1
0.2%
0.636 1
0.2%
0.638 1
0.2%
0.689 1
0.2%
0.805 1
0.2%
0.807 1
0.2%
ValueCountFrequency (%)
1.234 1
0.2%
1.176 1
0.2%
1.174 1
0.2%
1.165 1
0.2%
1.064 1
0.2%
0.98 1
0.2%
0.863 1
0.2%
0.853 1
0.2%
0.835 1
0.2%
0.834 1
0.2%

이산화질소(ppm)(NITROGEN_DIO)
Real number (ℝ)

MISSING 

Distinct17
Distinct (%)73.9%
Missing477
Missing (%)95.4%
Infinite0
Infinite (%)0.0%
Mean0.11617391
Minimum0.019
Maximum2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-01-14T15:49:30.378276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.019
5-th percentile0.02
Q10.0225
median0.03
Q30.0355
95-th percentile0.0597
Maximum2
Range1.981
Interquartile range (IQR)0.013

Descriptive statistics

Standard deviation0.41078502
Coefficient of variation (CV)3.5359489
Kurtosis22.96791
Mean0.11617391
Median Absolute Deviation (MAD)0.007
Skewness4.7910453
Sum2.672
Variance0.16874433
MonotonicityNot monotonic
2024-01-14T15:49:30.499121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0.022 3
 
0.6%
0.02 2
 
0.4%
0.031 2
 
0.4%
0.041 2
 
0.4%
0.023 2
 
0.4%
0.027 1
 
0.2%
0.061 1
 
0.2%
2.0 1
 
0.2%
0.029 1
 
0.2%
0.019 1
 
0.2%
Other values (7) 7
 
1.4%
(Missing) 477
95.4%
ValueCountFrequency (%)
0.019 1
 
0.2%
0.02 2
0.4%
0.022 3
0.6%
0.023 2
0.4%
0.024 1
 
0.2%
0.027 1
 
0.2%
0.029 1
 
0.2%
0.03 1
 
0.2%
0.031 2
0.4%
0.033 1
 
0.2%
ValueCountFrequency (%)
2.0 1
0.2%
0.061 1
0.2%
0.048 1
0.2%
0.041 2
0.4%
0.036 1
0.2%
0.035 1
0.2%
0.034 1
0.2%
0.033 1
0.2%
0.031 2
0.4%
0.03 1
0.2%

이산화황(ppm)(SULFUR_DIO)
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)24.0%
Missing475
Missing (%)95.0%
Infinite0
Infinite (%)0.0%
Mean0.00504
Minimum0.004
Maximum0.013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-01-14T15:49:30.612629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.004
5-th percentile0.004
Q10.004
median0.004
Q30.004
95-th percentile0.0112
Maximum0.013
Range0.009
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.002474537
Coefficient of variation (CV)0.49097956
Kurtosis5.8309637
Mean0.00504
Median Absolute Deviation (MAD)0
Skewness2.5506625
Sum0.126
Variance6.1233333 × 10-6
MonotonicityNot monotonic
2024-01-14T15:49:30.712185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0.004 20
 
4.0%
0.012 1
 
0.2%
0.006 1
 
0.2%
0.008 1
 
0.2%
0.007 1
 
0.2%
0.013 1
 
0.2%
(Missing) 475
95.0%
ValueCountFrequency (%)
0.004 20
4.0%
0.006 1
 
0.2%
0.007 1
 
0.2%
0.008 1
 
0.2%
0.012 1
 
0.2%
0.013 1
 
0.2%
ValueCountFrequency (%)
0.013 1
 
0.2%
0.012 1
 
0.2%
0.008 1
 
0.2%
0.007 1
 
0.2%
0.006 1
 
0.2%
0.004 20
4.0%

암모니아(ppm)(AMMONIA)
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
479 
0
 
21

Length

Max length4
Median length4
Mean length3.874
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 479
95.8%
0 21
 
4.2%

Length

2024-01-14T15:49:30.837636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-14T15:49:30.943248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 479
95.8%
0 21
 
4.2%

황화수소(ppm)(HYDROGEN_SULF)
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)28.0%
Missing475
Missing (%)95.0%
Infinite0
Infinite (%)0.0%
Mean0.00324
Minimum0
Maximum0.033
Zeros18
Zeros (%)3.6%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-01-14T15:49:31.025053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.001
95-th percentile0.015
Maximum0.033
Range0.033
Interquartile range (IQR)0.001

Descriptive statistics

Standard deviation0.0076173049
Coefficient of variation (CV)2.35102
Kurtosis9.7130415
Mean0.00324
Median Absolute Deviation (MAD)0
Skewness2.9903844
Sum0.081
Variance5.8023333 × 10-5
MonotonicityNot monotonic
2024-01-14T15:49:31.119552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0.0 18
 
3.6%
0.015 2
 
0.4%
0.005 1
 
0.2%
0.033 1
 
0.2%
0.003 1
 
0.2%
0.009 1
 
0.2%
0.001 1
 
0.2%
(Missing) 475
95.0%
ValueCountFrequency (%)
0.0 18
3.6%
0.001 1
 
0.2%
0.003 1
 
0.2%
0.005 1
 
0.2%
0.009 1
 
0.2%
0.015 2
 
0.4%
0.033 1
 
0.2%
ValueCountFrequency (%)
0.033 1
 
0.2%
0.015 2
 
0.4%
0.009 1
 
0.2%
0.005 1
 
0.2%
0.003 1
 
0.2%
0.001 1
 
0.2%
0.0 18
3.6%

오존(ppm)(OZONE)
Real number (ℝ)

MISSING 

Distinct17
Distinct (%)100.0%
Missing483
Missing (%)96.6%
Infinite0
Infinite (%)0.0%
Mean0.61547059
Minimum0.003
Maximum1.108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-01-14T15:49:31.230515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.003
5-th percentile0.0262
Q10.105
median0.858
Q30.97
95-th percentile1.1064
Maximum1.108
Range1.105
Interquartile range (IQR)0.865

Descriptive statistics

Standard deviation0.46659915
Coefficient of variation (CV)0.7581177
Kurtosis-1.9932067
Mean0.61547059
Median Absolute Deviation (MAD)0.248
Skewness-0.31921647
Sum10.463
Variance0.21771476
MonotonicityNot monotonic
2024-01-14T15:49:31.369296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0.032 1
 
0.2%
1.106 1
 
0.2%
0.858 1
 
0.2%
0.092 1
 
0.2%
1.078 1
 
0.2%
0.955 1
 
0.2%
0.159 1
 
0.2%
1.105 1
 
0.2%
0.97 1
 
0.2%
0.105 1
 
0.2%
Other values (7) 7
 
1.4%
(Missing) 483
96.6%
ValueCountFrequency (%)
0.003 1
0.2%
0.032 1
0.2%
0.064 1
0.2%
0.092 1
0.2%
0.105 1
0.2%
0.129 1
0.2%
0.159 1
0.2%
0.843 1
0.2%
0.858 1
0.2%
0.913 1
0.2%
ValueCountFrequency (%)
1.108 1
0.2%
1.106 1
0.2%
1.105 1
0.2%
1.078 1
0.2%
0.97 1
0.2%
0.955 1
0.2%
0.943 1
0.2%
0.913 1
0.2%
0.858 1
0.2%
0.843 1
0.2%

등록일시(DB_DATE)
Date

UNIQUE 

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
Minimum2020-11-12 03:22:08
Maximum2021-11-20 22:38:35
2024-01-14T15:49:31.518844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T15:49:31.660617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Sample

모델명(MODEL)시리얼(SERIAL)초미세먼지(㎍/㎥)(PM25)미세먼지(㎍/㎥)(PM10)기온(℃)(TEMP)상대습도(%)(HUMI)풍향(°)(WIND_DIRE)풍속(m/s)(WIND_SPEED)돌풍풍향(°)(GUST_DIRE)돌풍풍속(m/s)(GUST_SPEED)조도(lux)(INTE_ILLU)자외선(UVI)(ULTRA_RAYS)소음(dB)(NOISE)진동(x)(g)(VIBR_X)진동(y)(g)(VIBR_Y)진동(z)(g)(VIBR_Z)진동(x)최대(g)(VIBR_X_MAX)진동(y)최대(g)(VIBR_Y_MAX)진동(z)최대(g)(VIBR_Z_MAX)흑구온도(℃)(EFFE_TEMP)초미세먼지보정(㎍/㎥)(PM25_STD)미세먼지보정(㎍/㎥)(PM10_STD)측정시간(REG_DATE)일산화탄소(ppm)(CARBON_MONO)이산화질소(ppm)(NITROGEN_DIO)이산화황(ppm)(SULFUR_DIO)암모니아(ppm)(AMMONIA)황화수소(ppm)(HYDROGEN_SULF)오존(ppm)(OZONE)등록일시(DB_DATE)
0SDOT001OC3CL200089241534.897<NA><NA><NA><NA>00.0510.05<NA><NA>0.10.21.03<NA>1213202102091152<NA><NA><NA><NA><NA><NA>2021-02-09 13:11:41
1SDOT001V02Q1940548151829.192<NA><NA><NA><NA>199330.0550.120.061.040.050.111.13<NA>1123202109250310<NA><NA><NA><NA><NA><NA>2021-09-25 02:21:59
2SDOT001V02Q19405217531.158<NA><NA>53.4<NA><NA>2.0490.03<NA>1.010.06<NA>1.06<NA>1716202101221351<NA><NA><NA><NA><NA><NA>2021-01-22 01:30:42
3SDOT001OC3CL20006071234.752<NA><NA><NA><NA>186050.061<NA>0.031.030.080.11<NA><NA>1215202012032345<NA><NA><NA><NA><NA><NA>2020-12-03 09:50:38
4SDOT001OC3CL200036131233.179<NA>0.3<NA><NA>00.2470.050.051.030.180.131.14<NA>1121202109232143<NA><NA><NA><NA><NA><NA>2021-09-23 07:24:45
5SDOT001V02Q19401337434.149<NA><NA>331.0<NA>0<NA>470.020.010.980.060.131.03<NA>2415202109101200<NA><NA><NA><NA><NA><NA>2021-09-10 07:47:50
6SDOT001V02Q194035151428.079<NA><NA><NA><NA>126250.1440.010.1<NA>0.05<NA>1.08<NA>1313202102050633<NA><NA><NA><NA><NA><NA>2021-02-05 16:37:30
7SDOT001V02Q194029718928.555<NA><NA><NA><NA>48800.0600.01<NA>0.980.06<NA><NA><NA>1035202107191332<NA><NA><NA><NA><NA><NA>2021-07-19 20:33:50
8SDOT001V02Q1940440241726.553<NA><NA><NA><NA>218340.0450.020.021.040.080.081.13<NA>1728202104040024<NA><NA><NA><NA><NA>0.972021-04-04 21:10:57
9SDOT001V02Q194081211928.061<NA><NA><NA><NA><NA>0.0360.03<NA>0.970.060.11.17<NA>103202105242148<NA><NA><NA><NA><NA><NA>2021-05-24 13:57:44
모델명(MODEL)시리얼(SERIAL)초미세먼지(㎍/㎥)(PM25)미세먼지(㎍/㎥)(PM10)기온(℃)(TEMP)상대습도(%)(HUMI)풍향(°)(WIND_DIRE)풍속(m/s)(WIND_SPEED)돌풍풍향(°)(GUST_DIRE)돌풍풍속(m/s)(GUST_SPEED)조도(lux)(INTE_ILLU)자외선(UVI)(ULTRA_RAYS)소음(dB)(NOISE)진동(x)(g)(VIBR_X)진동(y)(g)(VIBR_Y)진동(z)(g)(VIBR_Z)진동(x)최대(g)(VIBR_X_MAX)진동(y)최대(g)(VIBR_Y_MAX)진동(z)최대(g)(VIBR_Z_MAX)흑구온도(℃)(EFFE_TEMP)초미세먼지보정(㎍/㎥)(PM25_STD)미세먼지보정(㎍/㎥)(PM10_STD)측정시간(REG_DATE)일산화탄소(ppm)(CARBON_MONO)이산화질소(ppm)(NITROGEN_DIO)이산화황(ppm)(SULFUR_DIO)암모니아(ppm)(AMMONIA)황화수소(ppm)(HYDROGEN_SULF)오존(ppm)(OZONE)등록일시(DB_DATE)
490SDOT001V02Q194007061630.149<NA><NA><NA>0.0127310.5410.010.06<NA>0.080.151.08<NA>720202101232117<NA><NA><NA><NA><NA><NA>2021-01-23 12:47:30
491SDOT001V02Q194035614331.865<NA><NA><NA><NA>20.0520.02<NA>1.02<NA><NA><NA><NA>1810202108112229<NA><NA>0.004<NA><NA><NA>2021-08-11 16:16:25
492SDOT001V02Q194048821427.156<NA><NA>47.8<NA>00.0530.030.021.00.060.16<NA><NA>89202012271945<NA><NA><NA><NA><NA><NA>2020-12-27 07:51:33
493SDOT001V02Q194024116930.663<NA><NA><NA><NA>358210.0520.040.140.960.090.131.03<NA>1118202103091953<NA>0.031<NA><NA><NA><NA>2021-03-09 08:35:37
494SDOT001V02Q194076993430.275<NA><NA>323.0<NA>00.348<NA>0.041.040.090.111.13<NA>1318202109121927<NA><NA><NA><NA><NA><NA>2021-09-12 02:54:02
495SDOT001V02Q19402806429.764<NA><NA><NA><NA><NA>0.2420.00.041.010.060.091.09<NA>1916202012172220<NA><NA><NA><NA><NA><NA>2020-12-17 03:39:35
496SDOT001V02Q19408187827.7100<NA><NA><NA><NA>69800.3450.050.020.970.110.191.13<NA>124202101121246<NA><NA><NA><NA><NA><NA>2021-01-12 03:16:36
497SDOT001V02Q194025971131.954<NA><NA><NA><NA>00.040<NA><NA>1.060.110.111.04<NA>1710202011231457<NA><NA><NA><NA><NA><NA>2020-11-23 18:58:36
498SDOT001OC3CL200200181428.884<NA><NA><NA><NA>92020.042<NA>0.021.030.050.141.14<NA>1117202101202102<NA>0.03<NA><NA><NA><NA>2021-01-20 18:18:26
499SDOT001V02Q1940697141028.993<NA><NA><NA><NA>1700.047<NA>0.071.030.06<NA>1.05<NA>2219202105042250<NA><NA><NA><NA><NA><NA>2021-05-04 23:24:46