Overview

Dataset statistics

Number of variables8
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.9 KiB
Average record size in memory70.3 B

Variable types

Categorical4
Numeric4

Alerts

지점 has constant value ""Constant
주소 has constant value ""Constant
측정시간 is highly overall correlated with 온도(℃) and 1 other fieldsHigh correlation
온도(℃) is highly overall correlated with 측정시간 and 1 other fieldsHigh correlation
습도(%) is highly overall correlated with 측정시간 and 4 other fieldsHigh correlation
풍속(m/s) is highly overall correlated with 습도(%) and 1 other fieldsHigh correlation
측정일 is highly overall correlated with 습도(%) and 2 other fieldsHigh correlation
풍향 is highly overall correlated with 습도(%) and 1 other fieldsHigh correlation
측정일 is highly imbalanced (75.8%)Imbalance
측정시간 has 2 (2.0%) zerosZeros
풍속(m/s) has 16 (16.0%) zerosZeros

Reproduction

Analysis started2023-12-10 12:41:51.989106
Analysis finished2023-12-10 12:41:53.983115
Duration1.99 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지점
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
A-0010-0083E-6
100 

Length

Max length14
Median length14
Mean length14
Min length14

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowA-0010-0083E-6
2nd rowA-0010-0083E-6
3rd rowA-0010-0083E-6
4th rowA-0010-0083E-6
5th rowA-0010-0083E-6

Common Values

ValueCountFrequency (%)
A-0010-0083E-6 100
100.0%

Length

2023-12-10T21:41:54.052056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:41:54.147909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
a-0010-0083e-6 100
100.0%

측정일
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20200301
96 
20200302
 
4

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20200301
2nd row20200301
3rd row20200301
4th row20200301
5th row20200301

Common Values

ValueCountFrequency (%)
20200301 96
96.0%
20200302 4
 
4.0%

Length

2023-12-10T21:41:54.236364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:41:54.324508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20200301 96
96.0%
20200302 4
 
4.0%

측정시간
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct96
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1146.75
Minimum0
Maximum2345
Zeros2
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:41:54.437835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile97.25
Q1541.25
median1122.5
Q31733.75
95-th percentile2230.75
Maximum2345
Range2345
Interquartile range (IQR)1192.5

Descriptive statistics

Standard deviation700.21836
Coefficient of variation (CV)0.61061117
Kurtosis-1.1835169
Mean1146.75
Median Absolute Deviation (MAD)600
Skewness0.026925197
Sum114675
Variance490305.74
MonotonicityNot monotonic
2023-12-10T21:41:54.648760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2
 
2.0%
1000 2
 
2.0%
1015 2
 
2.0%
100 2
 
2.0%
2315 1
 
1.0%
400 1
 
1.0%
345 1
 
1.0%
330 1
 
1.0%
315 1
 
1.0%
300 1
 
1.0%
Other values (86) 86
86.0%
ValueCountFrequency (%)
0 2
2.0%
15 1
1.0%
30 1
1.0%
45 1
1.0%
100 2
2.0%
115 1
1.0%
130 1
1.0%
145 1
1.0%
200 1
1.0%
215 1
1.0%
ValueCountFrequency (%)
2345 1
1.0%
2330 1
1.0%
2315 1
1.0%
2300 1
1.0%
2245 1
1.0%
2230 1
1.0%
2215 1
1.0%
2200 1
1.0%
2145 1
1.0%
2130 1
1.0%

온도(℃)
Real number (ℝ)

HIGH CORRELATION 

Distinct59
Distinct (%)59.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.896
Minimum5
Maximum16.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:41:54.789716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile5.89
Q16.3
median10.2
Q312.65
95-th percentile15.305
Maximum16.1
Range11.1
Interquartile range (IQR)6.35

Descriptive statistics

Standard deviation3.2856566
Coefficient of variation (CV)0.33201866
Kurtosis-1.2703945
Mean9.896
Median Absolute Deviation (MAD)3.5
Skewness0.13340411
Sum989.6
Variance10.795539
MonotonicityNot monotonic
2023-12-10T21:41:54.950536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.3 5
 
5.0%
6.1 5
 
5.0%
6.0 5
 
5.0%
6.2 5
 
5.0%
5.9 4
 
4.0%
10.1 4
 
4.0%
10.3 4
 
4.0%
6.4 3
 
3.0%
10.9 3
 
3.0%
9.7 3
 
3.0%
Other values (49) 59
59.0%
ValueCountFrequency (%)
5.0 1
 
1.0%
5.4 1
 
1.0%
5.5 1
 
1.0%
5.7 2
 
2.0%
5.9 4
4.0%
6.0 5
5.0%
6.1 5
5.0%
6.2 5
5.0%
6.3 5
5.0%
6.4 3
3.0%
ValueCountFrequency (%)
16.1 2
2.0%
15.8 1
1.0%
15.5 1
1.0%
15.4 1
1.0%
15.3 1
1.0%
15.0 1
1.0%
14.9 1
1.0%
14.5 1
1.0%
14.3 2
2.0%
14.1 2
2.0%

습도(%)
Real number (ℝ)

HIGH CORRELATION 

Distinct87
Distinct (%)87.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean73.034
Minimum37
Maximum95.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:41:55.095673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37
5-th percentile49.28
Q160.325
median73.5
Q389.125
95-th percentile92.41
Maximum95.8
Range58.8
Interquartile range (IQR)28.8

Descriptive statistics

Standard deviation15.823357
Coefficient of variation (CV)0.21665741
Kurtosis-1.1373297
Mean73.034
Median Absolute Deviation (MAD)15.25
Skewness-0.26270787
Sum7303.4
Variance250.37863
MonotonicityNot monotonic
2023-12-10T21:41:55.231054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
77.7 2
 
2.0%
90.1 2
 
2.0%
66.9 2
 
2.0%
92.2 2
 
2.0%
91.6 2
 
2.0%
89.0 2
 
2.0%
62.7 2
 
2.0%
50.7 2
 
2.0%
54.0 2
 
2.0%
88.2 2
 
2.0%
Other values (77) 80
80.0%
ValueCountFrequency (%)
37.0 1
1.0%
38.7 1
1.0%
46.3 1
1.0%
46.4 1
1.0%
47.0 1
1.0%
49.4 1
1.0%
49.5 1
1.0%
50.2 1
1.0%
50.7 2
2.0%
51.3 1
1.0%
ValueCountFrequency (%)
95.8 1
1.0%
94.7 1
1.0%
94.5 1
1.0%
93.6 1
1.0%
92.6 1
1.0%
92.4 1
1.0%
92.2 2
2.0%
92.1 1
1.0%
92.0 1
1.0%
91.7 1
1.0%

풍향
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
남동
23 
동
17 
북
16 
북동
15 
남서
14 
Other values (3)
15 

Length

Max length2
Median length2
Mean length1.57
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row북동
2nd row북동
3rd row북동
4th row북동
5th row동

Common Values

ValueCountFrequency (%)
남동 23
23.0%
동 17
17.0%
북 16
16.0%
북동 15
15.0%
남서 14
14.0%
남 7
 
7.0%
북서 5
 
5.0%
서 3
 
3.0%

Length

2023-12-10T21:41:55.363102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:41:55.503635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남동 23
23.0%
동 17
17.0%
북 16
16.0%
북동 15
15.0%
남서 14
14.0%
남 7
 
7.0%
북서 5
 
5.0%
서 3
 
3.0%

풍속(m/s)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct34
Distinct (%)34.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.542
Minimum0
Maximum4.6
Zeros16
Zeros (%)16.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:41:55.628127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.6
median1.65
Q32.5
95-th percentile3.21
Maximum4.6
Range4.6
Interquartile range (IQR)1.9

Descriptive statistics

Standard deviation1.1274518
Coefficient of variation (CV)0.73116197
Kurtosis-0.82534873
Mean1.542
Median Absolute Deviation (MAD)1
Skewness0.205015
Sum154.2
Variance1.2711475
MonotonicityNot monotonic
2023-12-10T21:41:55.776884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
0.0 16
 
16.0%
1.8 8
 
8.0%
0.6 6
 
6.0%
1.9 4
 
4.0%
2.5 4
 
4.0%
2.7 4
 
4.0%
2.0 4
 
4.0%
2.8 4
 
4.0%
1.0 4
 
4.0%
3.1 3
 
3.0%
Other values (24) 43
43.0%
ValueCountFrequency (%)
0.0 16
16.0%
0.1 2
 
2.0%
0.2 2
 
2.0%
0.4 3
 
3.0%
0.5 1
 
1.0%
0.6 6
 
6.0%
0.7 1
 
1.0%
0.8 3
 
3.0%
1.0 4
 
4.0%
1.1 2
 
2.0%
ValueCountFrequency (%)
4.6 1
 
1.0%
3.9 1
 
1.0%
3.5 2
2.0%
3.4 1
 
1.0%
3.2 1
 
1.0%
3.1 3
3.0%
3.0 2
2.0%
2.9 1
 
1.0%
2.8 4
4.0%
2.7 4
4.0%

주소
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
경남 양산시 동면
100 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경남 양산시 동면
2nd row경남 양산시 동면
3rd row경남 양산시 동면
4th row경남 양산시 동면
5th row경남 양산시 동면

Common Values

ValueCountFrequency (%)
경남 양산시 동면 100
100.0%

Length

2023-12-10T21:41:55.922541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:41:56.022729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경남 100
33.3%
양산시 100
33.3%
동면 100
33.3%

Interactions

2023-12-10T21:41:53.421749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:41:52.300280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:41:52.586794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:41:53.103467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:41:53.497619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:41:52.367419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:41:52.658134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:41:53.173429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:41:53.585508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:41:52.443206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:41:52.934016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:41:53.247359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:41:53.680733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:41:52.518031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:41:53.018323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:41:53.322943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T21:41:56.094064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
측정일측정시간온도(℃)습도(%)풍향풍속(m/s)
측정일1.0000.2840.5350.9680.7510.744
측정시간0.2841.0000.9270.9430.7420.632
온도(℃)0.5350.9271.0000.9710.7600.729
습도(%)0.9680.9430.9711.0000.7870.843
풍향0.7510.7420.7600.7871.0000.638
풍속(m/s)0.7440.6320.7290.8430.6381.000
2023-12-10T21:41:56.221472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
풍향측정일
풍향1.0000.559
측정일0.5591.000
2023-12-10T21:41:56.316776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
측정시간온도(℃)습도(%)풍속(m/s)측정일풍향
측정시간1.0000.595-0.524-0.0360.2070.469
온도(℃)0.5951.000-0.9350.4230.3940.491
습도(%)-0.524-0.9351.000-0.5160.8100.526
풍속(m/s)-0.0360.423-0.5161.0000.5590.369
측정일0.2070.3940.8100.5591.0000.559
풍향0.4690.4910.5260.3690.5591.000

Missing values

2023-12-10T21:41:53.792606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T21:41:53.935098image/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

지점측정일측정시간온도(℃)습도(%)풍향풍속(m/s)주소
0A-0010-0083E-62020030106.388.9북동1.3경남 양산시 동면
1A-0010-0083E-6202003011006.188.2북동2.9경남 양산시 동면
2A-0010-0083E-620200301100011.759.1북동2.6경남 양산시 동면
3A-0010-0083E-620200301101511.960.1북동2.4경남 양산시 동면
4A-0010-0083E-620200301103012.859.1동1.8경남 양산시 동면
5A-0010-0083E-620200301104512.960.4동2.5경남 양산시 동면
6A-0010-0083E-620200301110014.355.8남동2.7경남 양산시 동면
7A-0010-0083E-620200301111514.154.0동3.4경남 양산시 동면
8A-0010-0083E-620200301113014.152.6동1.8경남 양산시 동면
9A-0010-0083E-620200301114513.754.0동2.1경남 양산시 동면
지점측정일측정시간온도(℃)습도(%)풍향풍속(m/s)주소
90A-0010-0083E-6202003018307.188.2남0.4경남 양산시 동면
91A-0010-0083E-6202003018457.684.1북서0.2경남 양산시 동면
92A-0010-0083E-6202003019008.380.3북0.5경남 양산시 동면
93A-0010-0083E-6202003019159.176.8서0.0경남 양산시 동면
94A-0010-0083E-6202003019309.772.3북0.6경남 양산시 동면
95A-0010-0083E-62020030194510.969.8남0.8경남 양산시 동면
96A-0010-0083E-62020030209.781.0남서0.6경남 양산시 동면
97A-0010-0083E-6202003021009.779.5남서0.6경남 양산시 동면
98A-0010-0083E-62020030210008.038.7서3.5경남 양산시 동면
99A-0010-0083E-62020030210158.537.0서4.6경남 양산시 동면