Overview

Dataset statistics

Number of variables7
Number of observations10000
Missing cells3
Missing cells (%)< 0.1%
Duplicate rows39
Duplicate rows (%)0.4%
Total size in memory673.8 KiB
Average record size in memory69.0 B

Variable types

DateTime2
Numeric5

Dataset

Description경기도 성남시 도로의 조도,휘도 데이터입니다. 날짜, 시간, 위도, 경도, 조도, 휘도, 달 위상 데이터를 제공합니다.
Author경기도 성남시
URLhttps://www.data.go.kr/data/15110579/fileData.do

Alerts

Dataset has 39 (0.4%) duplicate rowsDuplicates
조도(ILLUMINATION) is highly overall correlated with 휘도(BRIGHTNESS)High correlation
휘도(BRIGHTNESS) is highly overall correlated with 조도(ILLUMINATION)High correlation
위도(LATITUDE) is highly skewed (γ1 = 99.99999999)Skewed
경도(LONGITUDE) is highly skewed (γ1 = 95.94234984)Skewed
조도(ILLUMINATION) is highly skewed (γ1 = 32.35611236)Skewed
휘도(BRIGHTNESS) is highly skewed (γ1 = 29.50964126)Skewed

Reproduction

Analysis started2023-12-12 16:13:09.561194
Analysis finished2023-12-12 16:13:14.547291
Duration4.99 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

날짜(DATE)
Date

Distinct34
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2022-08-11 00:00:00
Maximum2022-10-22 00:00:00
2023-12-13T01:13:14.633288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:14.828445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)

시간(TIME)
Date

Distinct268
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-12-13 18:31:00
Maximum2023-12-13 23:01:00
2023-12-13T01:13:14.991792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:15.182459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

위도(LATITUDE)
Real number (ℝ)

SKEWED 

Distinct9693
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3781.4914
Minimum37.334088
Maximum37440405
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T01:13:15.435093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.334088
5-th percentile37.361235
Q137.402559
median37.432119
Q337.443144
95-th percentile37.456079
Maximum37440405
Range37440368
Interquartile range (IQR)0.04058525

Descriptive statistics

Standard deviation374403.68
Coefficient of variation (CV)99.009527
Kurtosis10000
Mean3781.4914
Median Absolute Deviation (MAD)0.01677767
Skewness100
Sum37814914
Variance1.4017811 × 1011
MonotonicityNot monotonic
2023-12-13T01:13:15.659037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.441736 4
 
< 0.1%
37.410407 3
 
< 0.1%
37.44221952 3
 
< 0.1%
37.41684486 3
 
< 0.1%
37.435801 3
 
< 0.1%
37.412021 3
 
< 0.1%
37.367394 3
 
< 0.1%
37.443897 3
 
< 0.1%
37.444848 3
 
< 0.1%
37.442165 3
 
< 0.1%
Other values (9683) 9969
99.7%
ValueCountFrequency (%)
37.33408849 1
< 0.1%
37.334332 1
< 0.1%
37.334481 1
< 0.1%
37.334543 1
< 0.1%
37.3345663 1
< 0.1%
37.33477979 1
< 0.1%
37.334813 1
< 0.1%
37.334913 1
< 0.1%
37.33528809 1
< 0.1%
37.335435 1
< 0.1%
ValueCountFrequency (%)
37440405.0 1
< 0.1%
378.434221 1
< 0.1%
37.47340256 1
< 0.1%
37.473329 1
< 0.1%
37.472896 1
< 0.1%
37.4723853 1
< 0.1%
37.47236236 1
< 0.1%
37.47230435 1
< 0.1%
37.47205111 1
< 0.1%
37.47190445 1
< 0.1%

경도(LONGITUDE)
Real number (ℝ)

SKEWED 

Distinct9632
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean165282.87
Minimum127.05167
Maximum1.2701446 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T01:13:15.864709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.05167
5-th percentile127.09945
Q1127.12196
median127.13398
Q3127.14501
95-th percentile127.16597
Maximum1.2701446 × 109
Range1.2701444 × 109
Interquartile range (IQR)0.0230562

Descriptive statistics

Standard deviation12890507
Coefficient of variation (CV)77.990579
Kurtosis9427.6305
Mean165282.87
Median Absolute Deviation (MAD)0.0113088
Skewness95.94235
Sum1.6528287 × 109
Variance1.6616516 × 1014
MonotonicityNot monotonic
2023-12-13T01:13:16.073608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.107046 3
 
< 0.1%
127.144819 3
 
< 0.1%
127.123303 3
 
< 0.1%
127.159985 3
 
< 0.1%
127.15513 3
 
< 0.1%
127.139724 3
 
< 0.1%
127.109833 3
 
< 0.1%
127.144509 3
 
< 0.1%
127.109834 3
 
< 0.1%
127.125553 3
 
< 0.1%
Other values (9622) 9970
99.7%
ValueCountFrequency (%)
127.051667 1
< 0.1%
127.051818 1
< 0.1%
127.05194 1
< 0.1%
127.052325 1
< 0.1%
127.054474 1
< 0.1%
127.0555104 1
< 0.1%
127.0557086 1
< 0.1%
127.056461 1
< 0.1%
127.057272 1
< 0.1%
127.057455 1
< 0.1%
ValueCountFrequency (%)
1270144552.0 1
< 0.1%
127160611.0 1
< 0.1%
127135487.0 1
< 0.1%
127114919.0 1
< 0.1%
1277.116997 1
< 0.1%
1272.138593 1
< 0.1%
127.181257 1
< 0.1%
127.1808163 1
< 0.1%
127.180676 1
< 0.1%
127.1806235 1
< 0.1%

조도(ILLUMINATION)
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct2095
Distinct (%)21.0%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean21.433886
Minimum0.01
Maximum2823
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T01:13:16.264936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile0.4
Q12.96
median10.2
Q326.4
95-th percentile81.115
Maximum2823
Range2822.99
Interquartile range (IQR)23.44

Descriptive statistics

Standard deviation41.414556
Coefficient of variation (CV)1.9322001
Kurtosis2100.3198
Mean21.433886
Median Absolute Deviation (MAD)8.6
Skewness32.356112
Sum214295.99
Variance1715.1655
MonotonicityNot monotonic
2023-12-13T01:13:16.442930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.4 121
 
1.2%
0.2 106
 
1.1%
0.5 105
 
1.1%
0.6 100
 
1.0%
0.3 100
 
1.0%
0.8 89
 
0.9%
0.1 83
 
0.8%
1.2 78
 
0.8%
0.7 73
 
0.7%
1.4 69
 
0.7%
Other values (2085) 9074
90.7%
ValueCountFrequency (%)
0.01 2
 
< 0.1%
0.02 3
 
< 0.1%
0.04 5
 
0.1%
0.05 3
 
< 0.1%
0.06 2
 
< 0.1%
0.07 1
 
< 0.1%
0.08 2
 
< 0.1%
0.09 2
 
< 0.1%
0.1 83
0.8%
0.11 4
 
< 0.1%
ValueCountFrequency (%)
2823.0 1
< 0.1%
527.0 1
< 0.1%
435.0 1
< 0.1%
333.9 1
< 0.1%
322.0 1
< 0.1%
305.0 1
< 0.1%
245.0 1
< 0.1%
233.4 1
< 0.1%
221.9 1
< 0.1%
209.3 1
< 0.1%

휘도(BRIGHTNESS)
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct683
Distinct (%)6.8%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.98740314
Minimum0.01
Maximum149
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T01:13:16.595398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile0.02
Q10.13
median0.39
Q31.05
95-th percentile3.51
Maximum149
Range148.99
Interquartile range (IQR)0.92

Descriptive statistics

Standard deviation3.0081554
Coefficient of variation (CV)3.0465321
Kurtosis1256.8137
Mean0.98740314
Median Absolute Deviation (MAD)0.32
Skewness29.509641
Sum9873.044
Variance9.0489987
MonotonicityNot monotonic
2023-12-13T01:13:16.761369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.02 298
 
3.0%
0.01 259
 
2.6%
0.03 252
 
2.5%
0.04 225
 
2.2%
0.05 218
 
2.2%
0.06 192
 
1.9%
0.1 174
 
1.7%
0.12 171
 
1.7%
0.07 164
 
1.6%
0.09 159
 
1.6%
Other values (673) 7887
78.9%
ValueCountFrequency (%)
0.01 259
2.6%
0.013 1
 
< 0.1%
0.018 1
 
< 0.1%
0.02 298
3.0%
0.03 252
2.5%
0.04 225
2.2%
0.05 218
2.2%
0.06 192
1.9%
0.07 164
1.6%
0.08 152
1.5%
ValueCountFrequency (%)
149.0 1
< 0.1%
137.7 1
< 0.1%
114.5 1
< 0.1%
72.5 1
< 0.1%
38.5 1
< 0.1%
33.9 1
< 0.1%
33.67 1
< 0.1%
32.5 1
< 0.1%
28.77 1
< 0.1%
27.3 1
< 0.1%

달 위상(LUNAR_PHASE)
Real number (ℝ)

Distinct30
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59.1492
Minimum8
Maximum98.666667
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T01:13:16.921562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile14.666667
Q138.666667
median64
Q377.333333
95-th percentile98.666667
Maximum98.666667
Range90.666667
Interquartile range (IQR)38.666667

Descriptive statistics

Standard deviation24.783237
Coefficient of variation (CV)0.41899531
Kurtosis-1.0054713
Mean59.1492
Median Absolute Deviation (MAD)18.666667
Skewness-0.27901683
Sum591492
Variance614.20885
MonotonicityNot monotonic
2023-12-13T01:13:17.053237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
28.0 722
 
7.2%
76.0 578
 
5.8%
49.33333333 556
 
5.6%
98.66666667 547
 
5.5%
89.33333333 533
 
5.3%
74.66666667 532
 
5.3%
64.0 491
 
4.9%
14.66666667 485
 
4.9%
57.33333333 458
 
4.6%
21.33333333 449
 
4.5%
Other values (20) 4649
46.5%
ValueCountFrequency (%)
8.0 143
 
1.4%
14.66666667 485
4.9%
21.33333333 449
4.5%
22.66666667 66
 
0.7%
28.0 722
7.2%
34.66666667 300
3.0%
36.0 333
3.3%
38.66666667 82
 
0.8%
41.33333333 171
 
1.7%
42.66666667 321
3.2%
ValueCountFrequency (%)
98.66666667 547
5.5%
96.0 224
 
2.2%
92.0 62
 
0.6%
89.33333333 533
5.3%
85.33333333 121
 
1.2%
82.66666667 404
4.0%
81.33333333 109
 
1.1%
78.66666667 411
4.1%
77.33333333 391
3.9%
76.0 578
5.8%

Interactions

2023-12-13T01:13:13.342283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:10.384958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:10.982320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:11.649124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:12.507517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:13.480186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:10.499818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:11.105039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:11.862433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:12.688058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:13.619596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:10.606277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:11.219301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:12.041987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:12.853656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:13.768312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:10.734203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:11.336144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:12.193846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:13.002186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:13.919950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:10.865105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:11.494633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:12.369070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:13.167408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:13:17.527484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
날짜(DATE)위도(LATITUDE)경도(LONGITUDE)조도(ILLUMINATION)휘도(BRIGHTNESS)달 위상(LUNAR_PHASE)
날짜(DATE)1.0000.0000.0000.0000.1311.000
위도(LATITUDE)0.0001.0000.0000.0000.0000.040
경도(LONGITUDE)0.0000.0001.0000.0000.0000.000
조도(ILLUMINATION)0.0000.0000.0001.0000.0000.000
휘도(BRIGHTNESS)0.1310.0000.0000.0001.0000.038
달 위상(LUNAR_PHASE)1.0000.0400.0000.0000.0381.000
2023-12-13T01:13:17.667194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도(LATITUDE)경도(LONGITUDE)조도(ILLUMINATION)휘도(BRIGHTNESS)달 위상(LUNAR_PHASE)
위도(LATITUDE)1.0000.475-0.042-0.067-0.223
경도(LONGITUDE)0.4751.0000.008-0.047-0.117
조도(ILLUMINATION)-0.0420.0081.0000.784-0.001
휘도(BRIGHTNESS)-0.067-0.0470.7841.000-0.027
달 위상(LUNAR_PHASE)-0.223-0.117-0.001-0.0271.000

Missing values

2023-12-13T01:13:14.115128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:13:14.312728image/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.
2023-12-13T01:13:14.470929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

날짜(DATE)시간(TIME)위도(LATITUDE)경도(LONGITUDE)조도(ILLUMINATION)휘도(BRIGHTNESS)달 위상(LUNAR_PHASE)
306352022-10-1320:0837.400598127.1236728.70.4382.666667
66882022-08-2320:5537.437623127.14255315.00.0528.0
310422022-10-1319:3837.420284127.1060240.20.0482.666667
70352022-08-2320:2037.441529127.14580876.91.4728.0
233822022-10-0520:1737.361134127.11408219.01.7864.0
102632022-08-2520:5737.441435127.1380534.290.5114.666667
270712022-10-1121:4937.43382127.08474117.80.896.0
52102022-08-1821:4237.433203127.1416862.80.1561.333333
371452022-10-1820:4637.444806127.10350922.52.2249.333333
99922022-08-2521:2537.44561127.1461822.420.2114.666667
날짜(DATE)시간(TIME)위도(LATITUDE)경도(LONGITUDE)조도(ILLUMINATION)휘도(BRIGHTNESS)달 위상(LUNAR_PHASE)
21612022-08-1221:1737.428866127.1434710.90.0498.666667
79672022-08-2420:0637.44614127.13788267.90.3721.333333
69232022-08-2322:3337.441469127.1500016.00.1728.0
239492022-10-0520:1337.380896127.1282857.80.4564.0
27272022-08-1621:1037.440884127.134518128.37.8974.666667
602022-08-1120:4337.448058127.12866714.820.9792.0
2092022-08-1122:3137.444561127.1307273.930.3592.0
190972022-09-1920:5237.439702127.1203811.90.8345.333333
393912022-10-2021:0637.403361127.0987955.80.3736.0
387472022-10-1922:0737.426386127.11648310.20.4342.666667

Duplicate rows

Most frequently occurring

날짜(DATE)시간(TIME)위도(LATITUDE)경도(LONGITUDE)조도(ILLUMINATION)휘도(BRIGHTNESS)달 위상(LUNAR_PHASE)# duplicates
02022-08-2319:4637.442898127.13895860.54.3928.02
12022-08-2320:0937.444025127.1447743.320.128.02
22022-08-2320:1037.443858127.145011.10.0228.02
32022-08-2320:1137.443651127.1451964.860.2428.02
42022-08-2320:1237.443077127.14563811.431.128.02
52022-08-2320:1637.441762127.14648338.892.9128.02
62022-08-2320:1737.440895127.14641729.551.2428.02
72022-08-2320:2537.440118127.144855169.717.128.02
82022-08-2320:5537.44222127.1457511.160.0328.02
92022-08-2321:0137.441309127.1436498.61.1528.02