Overview

Dataset statistics

Number of variables4
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory419.9 KiB
Average record size in memory43.0 B

Variable types

DateTime1
Numeric2
Categorical1

Dataset

Description부산광역시_열섬관측지점정보_20230925
Author부산광역시
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15120945

Reproduction

Analysis started2024-03-13 13:15:45.156974
Analysis finished2024-03-13 13:15:46.043268
Duration0.89 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

날짜 및 시간
Date

Distinct5009
Distinct (%)50.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-09-01 00:00:00
Maximum2023-09-25 11:30:00
2024-03-13T22:15:46.123224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:15:46.291260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

센서항목코드
Real number (ℝ)

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27570.355
Minimum8192
Maximum61440
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T22:15:46.412779image/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 deviation17869.121
Coefficient of variation (CV)0.64812807
Kurtosis-0.36988377
Mean27570.355
Median Absolute Deviation (MAD)20480
Skewness0.72829006
Sum2.7570355 × 108
Variance3.1930549 × 108
MonotonicityNot monotonic
2024-03-13T22:15:46.586661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
29696 1690
16.9%
61440 1686
16.9%
8192 1686
16.9%
28928 1683
16.8%
8448 1676
16.8%
28672 1579
15.8%
ValueCountFrequency (%)
8192 1686
16.9%
8448 1676
16.8%
28672 1579
15.8%
28928 1683
16.8%
29696 1690
16.9%
61440 1686
16.9%
ValueCountFrequency (%)
61440 1686
16.9%
29696 1690
16.9%
28928 1683
16.8%
28672 1579
15.8%
8448 1676
16.8%
8192 1686
16.9%

센서 코드
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
10
3656 
1
3651 
11
2693 

Length

Max length2
Median length2
Mean length1.6349
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row10
4th row10
5th row10

Common Values

ValueCountFrequency (%)
10 3656
36.6%
1 3651
36.5%
11 2693
26.9%

Length

2024-03-13T22:15:46.791826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T22:15:46.902460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10 3656
36.6%
1 3651
36.5%
11 2693
26.9%

센서 값
Real number (ℝ)

Distinct9900
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2933374
Minimum0
Maximum19349740
Zeros4
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T22:15:47.027857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.37502493
Q1351.24799
median5359.2596
Q312550.929
95-th percentile18391313
Maximum19349740
Range19349740
Interquartile range (IQR)12199.681

Descriptive statistics

Standard deviation6530673.5
Coefficient of variation (CV)2.2263351
Kurtosis1.2933572
Mean2933374
Median Absolute Deviation (MAD)5357.9741
Skewness1.8011428
Sum2.933374 × 1010
Variance4.2649696 × 1013
MonotonicityNot monotonic
2024-03-13T22:15:47.189042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10000.0 43
 
0.4%
0.0 4
 
< 0.1%
359.3450012207031 3
 
< 0.1%
354.2929992675781 2
 
< 0.1%
358.9330139160156 2
 
< 0.1%
1012.2446614583332 2
 
< 0.1%
1013.902001953125 2
 
< 0.1%
355.10400390625 2
 
< 0.1%
356.1319885253906 2
 
< 0.1%
12461.5 2
 
< 0.1%
Other values (9890) 9936
99.4%
ValueCountFrequency (%)
0.0 4
< 0.1%
0.0102157334486643 1
 
< 0.1%
0.0105205665032068 1
 
< 0.1%
0.0108907997608184 1
 
< 0.1%
0.0109347999095916 1
 
< 0.1%
0.0115505665540695 1
 
< 0.1%
0.0190361003081003 1
 
< 0.1%
0.0203681329886118 1
 
< 0.1%
0.0209819336732228 1
 
< 0.1%
0.021419600645701 1
 
< 0.1%
ValueCountFrequency (%)
19349740.0 1
< 0.1%
19347940.0 1
< 0.1%
19344940.0 1
< 0.1%
19332922.222222224 1
< 0.1%
19111540.0 1
< 0.1%
19104010.0 1
< 0.1%
19103740.0 1
< 0.1%
19099206.666666668 1
< 0.1%
19097440.0 1
< 0.1%
19097140.0 1
< 0.1%

Interactions

2024-03-13T22:15:45.653750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:15:45.424330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:15:45.763765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:15:45.542645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T22:15:47.298027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
센서항목코드센서 코드센서 값
센서항목코드1.0000.0000.895
센서 코드0.0001.0000.277
센서 값0.8950.2771.000
2024-03-13T22:15:47.397262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
센서항목코드센서 값센서 코드
센서항목코드1.0000.0330.000
센서 값0.0331.0000.265
센서 코드0.0000.2651.000

Missing values

2024-03-13T22:15:45.913662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T22:15:46.005742image/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 시간센서항목코드센서 코드센서 값
101962023-09-06 21:35:002969611012.985999
100292023-09-06 19:15:0061440117726710.0
662932023-09-18 17:30:008448107396.188883
385262023-09-02 00:35:002867210341.653992
432542023-09-04 18:15:002867210357.920013
762272023-09-02 13:40:00614401114685810.0
802432023-09-04 21:25:008448118072.89388
18142023-09-02 01:10:002969611011.941329
840362023-09-07 02:10:002867211352.640991
101342023-09-06 20:45:00286721352.540985
날짜 및 시간센서항목코드센서 코드센서 값
515592023-09-09 13:35:0028928101.130701
928312023-09-12 04:15:008448118901.473828
999622023-09-16 22:40:0029696111011.821342
939362023-09-12 19:40:002867211355.552002
371322023-09-01 05:10:0081921012331.006576
242742023-09-15 16:25:008192112667.466634
282142023-09-17 23:10:002969611012.19801
717582023-09-21 21:25:0081921012054.473438
423122023-09-04 05:10:002867210359.661011
781032023-09-03 15:45:0028928110.753757