Overview

Dataset statistics

Number of variables6
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory585.9 KiB
Average record size in memory60.0 B

Variable types

DateTime2
Numeric3
Categorical1

Dataset

Description송파구 전역의 야간 조도 데이터로 송파구 관내 도로 조도 DB 입니다. 관측 연월일, 관측 시간, 위도, 경도, 조도, S-Dot 여부 데이터로 구성되어 있습니다. 1차 전반 측정 : 2021. 8. 25. 21:00 기준 1차 후반 측정: 2021. 8. 25. 23:00 기준 2차 전반 측정: 2021. 10. 7. 21:00 기준 2차 후반 측정: 2021. 10. 7. 23:00 기준 3차 전반 측정: 2021. 11.22. 21:00 기준 3차 후반 측정: 2021. 11.22. 23:00 기준
Author서울특별시 송파구
URLhttps://www.data.go.kr/data/15097745/fileData.do

Alerts

SDOT여부(S-DoT여부) is highly imbalanced (92.7%)Imbalance

Reproduction

Analysis started2023-12-12 21:49:08.923076
Analysis finished2023-12-12 21:49:10.410741
Duration1.49 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관측연월일(DATE)
Date

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2021-08-25 00:00:00
Maximum2021-11-22 00:00:00
2023-12-13T06:49:10.449738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:49:10.544307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=3)

관측시간(TIME)
Date

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-12-13 21:00:00
Maximum2023-12-13 23:00:00
2023-12-13T06:49:10.620007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:49:10.704566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)

위도(LATITUDE)
Real number (ℝ)

Distinct521
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.50333
Minimum37.466878
Maximum37.541809
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T06:49:10.823770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.466878
5-th percentile37.476315
Q137.492315
median37.503515
Q337.514715
95-th percentile37.528315
Maximum37.541809
Range0.07493024
Interquartile range (IQR)0.0224

Descriptive statistics

Standard deviation0.015563896
Coefficient of variation (CV)0.00041500037
Kurtosis-0.50510315
Mean37.50333
Median Absolute Deviation (MAD)0.0112
Skewness-0.057881642
Sum375033.3
Variance0.00024223485
MonotonicityNot monotonic
2023-12-13T06:49:10.950475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.5011154 198
 
2.0%
37.5019154 193
 
1.9%
37.5003154 192
 
1.9%
37.5179154 190
 
1.9%
37.5163154 188
 
1.9%
37.5099154 187
 
1.9%
37.5107154 187
 
1.9%
37.5171154 185
 
1.8%
37.5035154 184
 
1.8%
37.5131154 181
 
1.8%
Other values (511) 8115
81.2%
ValueCountFrequency (%)
37.46687839 1
 
< 0.1%
37.46695993 1
 
< 0.1%
37.46752027 2
< 0.1%
37.46754216 2
< 0.1%
37.46783609 4
< 0.1%
37.4678613 2
< 0.1%
37.46788548 3
< 0.1%
37.46831119 1
 
< 0.1%
37.4683154 4
< 0.1%
37.46832078 2
< 0.1%
ValueCountFrequency (%)
37.54180863 3
< 0.1%
37.54156449 3
< 0.1%
37.54151915 1
 
< 0.1%
37.5411154 4
< 0.1%
37.5410761 3
< 0.1%
37.54101747 2
 
< 0.1%
37.54096138 3
< 0.1%
37.54081612 3
< 0.1%
37.5403154 7
0.1%
37.54031503 2
 
< 0.1%

경도(LONGITUDE)
Real number (ℝ)

Distinct543
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.11737
Minimum127.06809
Maximum127.16134
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T06:49:11.430271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.06809
5-th percentile127.07687
Q1127.10407
median127.11927
Q3127.13287
95-th percentile127.15047
Maximum127.16134
Range0.0932448
Interquartile range (IQR)0.0288

Descriptive statistics

Standard deviation0.021266989
Coefficient of variation (CV)0.00016730199
Kurtosis-0.48685284
Mean127.11737
Median Absolute Deviation (MAD)0.0144
Skewness-0.33306725
Sum1271173.7
Variance0.00045228482
MonotonicityNot monotonic
2023-12-13T06:49:11.569919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.1160674 165
 
1.7%
127.1176674 163
 
1.6%
127.1224674 156
 
1.6%
127.1192674 154
 
1.5%
127.1184674 154
 
1.5%
127.1288674 151
 
1.5%
127.1232674 151
 
1.5%
127.1144674 149
 
1.5%
127.1152674 149
 
1.5%
127.1200674 147
 
1.5%
Other values (533) 8461
84.6%
ValueCountFrequency (%)
127.0680925 2
< 0.1%
127.0680997 4
< 0.1%
127.0681698 1
 
< 0.1%
127.0682057 2
< 0.1%
127.0682561 3
< 0.1%
127.0683077 3
< 0.1%
127.0683588 1
 
< 0.1%
127.0684075 1
 
< 0.1%
127.0684464 2
< 0.1%
127.0688496 2
< 0.1%
ValueCountFrequency (%)
127.1613373 2
 
< 0.1%
127.1613269 5
0.1%
127.1608442 1
 
< 0.1%
127.1608326 2
 
< 0.1%
127.1606097 1
 
< 0.1%
127.1605312 1
 
< 0.1%
127.1604922 1
 
< 0.1%
127.1600674 6
0.1%
127.1600408 2
 
< 0.1%
127.1598371 2
 
< 0.1%

조도(ILLUMINATION_lx)
Real number (ℝ)

Distinct2690
Distinct (%)26.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.079263
Minimum2.54
Maximum84.46
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T06:49:11.715464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.54
5-th percentile6.2095
Q110.19
median13.72
Q318.13
95-th percentile29.5505
Maximum84.46
Range81.92
Interquartile range (IQR)7.94

Descriptive statistics

Standard deviation7.4164926
Coefficient of variation (CV)0.49183389
Kurtosis5.1989917
Mean15.079263
Median Absolute Deviation (MAD)3.84
Skewness1.7202368
Sum150792.63
Variance55.004363
MonotonicityNot monotonic
2023-12-13T06:49:11.866068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10.27 16
 
0.2%
13.73 15
 
0.1%
13.34 14
 
0.1%
10.78 14
 
0.1%
14.18 14
 
0.1%
13.4 14
 
0.1%
11.96 14
 
0.1%
11.31 14
 
0.1%
13.28 14
 
0.1%
10.97 14
 
0.1%
Other values (2680) 9857
98.6%
ValueCountFrequency (%)
2.54 1
< 0.1%
2.67 1
< 0.1%
2.68 1
< 0.1%
2.75 1
< 0.1%
2.76 1
< 0.1%
2.84 1
< 0.1%
2.85 1
< 0.1%
2.87 1
< 0.1%
2.88 1
< 0.1%
3.03 1
< 0.1%
ValueCountFrequency (%)
84.46 1
< 0.1%
69.82 1
< 0.1%
64.91 1
< 0.1%
61.68 1
< 0.1%
60.66 1
< 0.1%
58.85 1
< 0.1%
58.68 1
< 0.1%
57.36 1
< 0.1%
57.29 1
< 0.1%
57.22 1
< 0.1%

SDOT여부(S-DoT여부)
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9912 
1
 
88

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 9912
99.1%
1 88
 
0.9%

Length

2023-12-13T06:49:12.028467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:49:12.186387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 9912
99.1%
1 88
 
0.9%

Interactions

2023-12-13T06:49:09.995119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:49:09.385050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:49:09.740861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:49:10.080765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:49:09.525150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:49:09.844397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:49:10.157467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:49:09.617381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:49:09.923250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:49:12.250417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관측연월일(DATE)관측시간(TIME)위도(LATITUDE)경도(LONGITUDE)조도(ILLUMINATION_lx)SDOT여부(S-DoT여부)
관측연월일(DATE)1.0000.0090.0000.0250.2990.000
관측시간(TIME)0.0091.0000.0000.0000.1910.000
위도(LATITUDE)0.0000.0001.0000.6570.3790.048
경도(LONGITUDE)0.0250.0000.6571.0000.3020.051
조도(ILLUMINATION_lx)0.2990.1910.3790.3021.0000.038
SDOT여부(S-DoT여부)0.0000.0000.0480.0510.0381.000
2023-12-13T06:49:12.357682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도(LATITUDE)경도(LONGITUDE)조도(ILLUMINATION_lx)SDOT여부(S-DoT여부)
위도(LATITUDE)1.000-0.432-0.1640.037
경도(LONGITUDE)-0.4321.0000.0160.039
조도(ILLUMINATION_lx)-0.1640.0161.0000.029
SDOT여부(S-DoT여부)0.0370.0390.0291.000

Missing values

2023-12-13T06:49:10.264905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:49:10.370576image/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

관측연월일(DATE)관측시간(TIME)위도(LATITUDE)경도(LONGITUDE)조도(ILLUMINATION_lx)SDOT여부(S-DoT여부)
239572021-11-2221:0037.520315127.1288676.730
37632021-08-2521:0037.502715127.13206710.930
132021-08-2521:0037.517115127.0688676.950
232082021-11-2221:0037.525115127.1208676.390
189052021-10-0723:0037.518715127.12966711.180
143362021-10-0721:0037.492315127.13606711.760
159902021-10-0723:0037.501115127.08886752.50
285002021-11-2223:0037.519515127.1224677.650
89212021-08-2523:0037.475515127.13206714.380
188582021-10-0723:0037.500315127.12886713.740
관측연월일(DATE)관측시간(TIME)위도(LATITUDE)경도(LONGITUDE)조도(ILLUMINATION_lx)SDOT여부(S-DoT여부)
41252021-08-2521:0037.509915127.13686710.320
225042021-11-2221:0037.494715127.11366724.190
108652021-10-0721:0037.501915127.08886758.680
132672021-10-0721:0037.469115127.12326717.30
114172021-10-0721:0037.520315127.1024677.270
65592021-08-2523:0037.493115127.10646713.470
120862021-10-0721:0037.513115127.11206721.060
264792021-11-2223:0037.498715127.09526718.170
56962021-08-2523:0037.516315127.0880677.310
34882021-08-2521:0037.498715127.12886713.030