Overview

Dataset statistics

Number of variables6
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory576.2 KiB
Average record size in memory59.0 B

Variable types

DateTime1
Numeric3
Categorical2

Dataset

Description부산광역시 도시열섬 통합관리시스템의 열섬관측 지점 정보(날짜 및 시간, 센서항목코드, 센서 항목, 센서 코드, 센서명, 센서 값)입니다.
Author부산광역시
URLhttps://www.data.go.kr/data/15120945/fileData.do

Alerts

센서항목코드 is highly overall correlated with 센서값 and 1 other fieldsHigh correlation
센서 코드 is highly overall correlated with 센서명High correlation
센서값 is highly overall correlated with 센서항목코드 and 1 other fieldsHigh correlation
센서항목 is highly overall correlated with 센서항목코드 and 1 other fieldsHigh correlation
센서명 is highly overall correlated with 센서 코드High correlation

Reproduction

Analysis started2024-03-14 17:55:29.497259
Analysis finished2024-03-14 17:55:33.200369
Duration3.7 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

날짜 및 시간
Date

Distinct1042
Distinct (%)10.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2024-02-01 00:00:00
Maximum2024-02-04 14:45:00
2024-03-15T02:55:33.402247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:55:33.849553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

센서항목코드
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27560.346
Minimum8192
Maximum61440
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T02:55:34.256051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8192
5-th percentile8192
Q18448
median28928
Q329696
95-th percentile61440
Maximum61440
Range53248
Interquartile range (IQR)21248

Descriptive statistics

Standard deviation17670.947
Coefficient of variation (CV)0.64117291
Kurtosis-0.31359698
Mean27560.346
Median Absolute Deviation (MAD)768
Skewness0.73310529
Sum2.7560346 × 108
Variance3.1226237 × 108
MonotonicityNot monotonic
2024-03-15T02:55:34.638579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
29696 1738
17.4%
28928 1677
16.8%
8448 1675
16.8%
61440 1644
16.4%
28672 1639
16.4%
8192 1627
16.3%
ValueCountFrequency (%)
8192 1627
16.3%
8448 1675
16.8%
28672 1639
16.4%
28928 1677
16.8%
29696 1738
17.4%
61440 1644
16.4%
ValueCountFrequency (%)
61440 1644
16.4%
29696 1738
17.4%
28928 1677
16.8%
28672 1639
16.4%
8448 1675
16.8%
8192 1627
16.3%

센서항목
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
기압
1738 
풍속
1677 
습도
1675 
기타
1644 
풍향
1639 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row습도
2nd row풍속
3rd row기압
4th row기압
5th row온도

Common Values

ValueCountFrequency (%)
기압 1738
17.4%
풍속 1677
16.8%
습도 1675
16.8%
기타 1644
16.4%
풍향 1639
16.4%
온도 1627
16.3%

Length

2024-03-15T02:55:35.059521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T02:55:35.441017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기압 1738
17.4%
풍속 1677
16.8%
습도 1675
16.8%
기타 1644
16.4%
풍향 1639
16.4%
온도 1627
16.3%

센서 코드
Real number (ℝ)

HIGH CORRELATION 

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.4438
Minimum1
Maximum16
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T02:55:35.822620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median8
Q312
95-th percentile16
Maximum16
Range15
Interquartile range (IQR)8

Descriptive statistics

Standard deviation4.6196294
Coefficient of variation (CV)0.54710313
Kurtosis-1.2119307
Mean8.4438
Median Absolute Deviation (MAD)4
Skewness0.017308176
Sum84438
Variance21.340976
MonotonicityNot monotonic
2024-03-15T02:55:36.147220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
4 664
 
6.6%
10 663
 
6.6%
1 655
 
6.6%
7 640
 
6.4%
5 635
 
6.3%
3 626
 
6.3%
16 625
 
6.2%
8 624
 
6.2%
14 623
 
6.2%
13 621
 
6.2%
Other values (6) 3624
36.2%
ValueCountFrequency (%)
1 655
6.6%
2 612
6.1%
3 626
6.3%
4 664
6.6%
5 635
6.3%
6 610
6.1%
7 640
6.4%
8 624
6.2%
9 585
5.9%
10 663
6.6%
ValueCountFrequency (%)
16 625
6.2%
15 611
6.1%
14 623
6.2%
13 621
6.2%
12 597
6.0%
11 609
6.1%
10 663
6.6%
9 585
5.9%
8 624
6.2%
7 640
6.4%

센서명
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
영도구
 
664
금정구
 
663
중구
 
655
북구
 
640
부산진구
 
635
Other values (11)
6743 

Length

Max length4
Median length3
Mean length2.8116
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row수영구
2nd row부산진구
3rd row북구
4th row중구
5th row북구

Common Values

ValueCountFrequency (%)
영도구 664
 
6.6%
금정구 663
 
6.6%
중구 655
 
6.6%
북구 640
 
6.4%
부산진구 635
 
6.3%
동구 626
 
6.3%
동래구 625
 
6.2%
해운대구 624
 
6.2%
사상구 623
 
6.2%
수영구 621
 
6.2%
Other values (6) 3624
36.2%

Length

2024-03-15T02:55:36.549452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
영도구 664
 
6.6%
금정구 663
 
6.6%
중구 655
 
6.6%
북구 640
 
6.4%
부산진구 635
 
6.3%
동구 626
 
6.3%
동래구 625
 
6.2%
해운대구 624
 
6.2%
사상구 623
 
6.2%
수영구 621
 
6.2%
Other values (6) 3624
36.2%

센서값
Real number (ℝ)

HIGH CORRELATION 

Distinct9904
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3748992.6
Minimum-99.956392
Maximum30769050
Zeros43
Zeros (%)0.4%
Negative94
Negative (%)0.9%
Memory size166.0 KiB
2024-03-15T02:55:36.961751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-99.956392
5-th percentile0.38618978
Q16.8381636
median90.043849
Q31025.3
95-th percentile30508645
Maximum30769050
Range30769150
Interquartile range (IQR)1018.4618

Descriptive statistics

Standard deviation9554632.1
Coefficient of variation (CV)2.5485866
Kurtosis3.2763949
Mean3748992.6
Median Absolute Deviation (MAD)89.78819
Skewness2.2652435
Sum3.7489926 × 1010
Variance9.1290994 × 1013
MonotonicityNot monotonic
2024-03-15T02:55:37.548176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 43
 
0.4%
100.0 13
 
0.1%
357.4110107 2
 
< 0.1%
355.6419983 2
 
< 0.1%
346.7009888 2
 
< 0.1%
358.0270081 2
 
< 0.1%
1026.015991 2
 
< 0.1%
1025.11866 2
 
< 0.1%
359.1759949 2
 
< 0.1%
350.7739868 2
 
< 0.1%
Other values (9894) 9928
99.3%
ValueCountFrequency (%)
-99.95639228 1
< 0.1%
-99.95610295 1
< 0.1%
-99.95600753 1
< 0.1%
-99.95569822 1
< 0.1%
-99.95545978 1
< 0.1%
-99.95518492 1
< 0.1%
-99.95472965 1
< 0.1%
-99.9546971 1
< 0.1%
-99.95435503 1
< 0.1%
-99.94974276 1
< 0.1%
ValueCountFrequency (%)
30769050.0 1
< 0.1%
30768450.0 1
< 0.1%
30767550.0 1
< 0.1%
30766250.0 1
< 0.1%
30765750.0 1
< 0.1%
30764250.0 1
< 0.1%
30763831.25 1
< 0.1%
30763650.0 1
< 0.1%
30763050.0 1
< 0.1%
30762650.0 1
< 0.1%

Interactions

2024-03-15T02:55:31.602072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:55:29.939237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:55:30.774301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:55:31.869101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:55:30.222059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:55:31.047170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:55:32.269410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:55:30.500695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:55:31.324968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T02:55:37.820650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
센서항목코드센서항목센서 코드센서명센서값
센서항목코드1.0001.0000.0000.0000.857
센서항목1.0001.0000.0000.0000.686
센서 코드0.0000.0001.0001.0000.390
센서명0.0000.0001.0001.0000.649
센서값0.8570.6860.3900.6491.000
2024-03-15T02:55:38.064950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
센서명센서항목
센서명1.0000.000
센서항목0.0001.000
2024-03-15T02:55:38.276270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
센서항목코드센서 코드센서값센서항목센서명
센서항목코드1.0000.0010.6581.0000.000
센서 코드0.0011.000-0.0530.0001.000
센서값0.658-0.0531.0000.5160.358
센서항목1.0000.0000.5161.0000.000
센서명0.0001.0000.3580.0001.000

Missing values

2024-03-15T02:55:32.650111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T02:55:33.043467image/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

날짜 및 시간센서항목코드센서항목센서 코드센서명센서값
440932024-02-02 14:15:008448습도13수영구69.7145
571872024-02-03 01:35:0028928풍속5부산진구0.68726
244642024-02-01 21:10:0029696기압7북구1025.362651
969622024-02-04 12:10:0029696기압1중구1025.61187
134262024-02-01 11:35:008192온도7북구8.970732
745672024-02-03 16:40:008448습도5부산진구70.788287
519882024-02-02 21:05:008192온도2서구7.603201
328972024-02-02 04:30:008448습도4영도구82.720053
866922024-02-04 03:15:008192온도1중구6.848647
654202024-02-03 08:45:0029696기압16동래구1029.743994
날짜 및 시간센서항목코드센서항목센서 코드센서명센서값
223702024-02-01 19:25:0029696기압1중구1025.457479
401932024-02-02 10:50:008448습도4영도구75.953447
194232024-02-01 16:50:0028928풍속14사상구0.825214
593752024-02-03 03:30:008448습도16동래구0.674296
778032024-02-03 19:30:0028928풍속16동래구0.281226
694942024-02-03 12:15:0029696기압8해운대구1027.57535
734462024-02-03 15:45:0028672풍향10금정구339.100006
115262024-02-01 10:00:0028672풍향10금정구78.000702
559092024-02-03 00:30:0028928풍속15기장군0.026069
72442024-02-01 06:15:0029696기압16동래구1022.857788