Overview

Dataset statistics

Number of variables13
Number of observations54
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.2 KiB
Average record size in memory118.4 B

Variable types

DateTime1
Numeric12

Dataset

Description평화누리길 월별 이용자 현황
Author경기관광공사
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=7CN7VHML3ZBWOFVD00IQ34555671&infSeq=1

Alerts

1코스(대명항입구) is highly overall correlated with 9코스(율곡습지공원) and 2 other fieldsHigh correlation
2코스(문수산성) is highly overall correlated with 8코스(반구정)High correlation
3코스(애기봉) is highly overall correlated with 5코스(노래하는분수대) and 1 other fieldsHigh correlation
4코스(행주산성) is highly overall correlated with 5코스(노래하는분수대) and 1 other fieldsHigh correlation
5코스(노래하는분수대) is highly overall correlated with 3코스(애기봉) and 2 other fieldsHigh correlation
7코스(헤이리) is highly overall correlated with 11코스(숭의전)High correlation
8코스(반구정) is highly overall correlated with 2코스(문수산성) and 1 other fieldsHigh correlation
9코스(율곡습지공원) is highly overall correlated with 1코스(대명항입구) and 2 other fieldsHigh correlation
10코스(장남교) is highly overall correlated with 8코스(반구정) and 2 other fieldsHigh correlation
11코스(숭의전) is highly overall correlated with 1코스(대명항입구) and 3 other fieldsHigh correlation
12코스(신탄리역) is highly overall correlated with 1코스(대명항입구) and 3 other fieldsHigh correlation
구분 has unique valuesUnique
1코스(대명항입구) has unique valuesUnique
2코스(문수산성) has unique valuesUnique
4코스(행주산성) has unique valuesUnique
5코스(노래하는분수대) has unique valuesUnique
7코스(헤이리) has unique valuesUnique
9코스(율곡습지공원) has unique valuesUnique
10코스(장남교) has unique valuesUnique
11코스(숭의전) has 3 (5.6%) zerosZeros

Reproduction

Analysis started2023-12-10 21:36:54.147741
Analysis finished2023-12-10 21:37:08.286058
Duration14.14 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Date

UNIQUE 

Distinct54
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size564.0 B
Minimum2019-01-01 00:00:00
Maximum2023-06-01 00:00:00
2023-12-11T06:37:08.366152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:08.521274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

1코스(대명항입구)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct54
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12073.426
Minimum769
Maximum45915
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-11T06:37:08.672911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum769
5-th percentile2122.55
Q18810.75
median11415
Q314203.25
95-th percentile20994.45
Maximum45915
Range45146
Interquartile range (IQR)5392.5

Descriptive statistics

Standard deviation7421.4131
Coefficient of variation (CV)0.61468991
Kurtosis8.052049
Mean12073.426
Median Absolute Deviation (MAD)2766.5
Skewness2.1279904
Sum651965
Variance55077373
MonotonicityNot monotonic
2023-12-11T06:37:08.803217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
803 1
 
1.9%
13573 1
 
1.9%
9048 1
 
1.9%
12106 1
 
1.9%
19128 1
 
1.9%
15870 1
 
1.9%
12447 1
 
1.9%
8969 1
 
1.9%
11486 1
 
1.9%
10111 1
 
1.9%
Other values (44) 44
81.5%
ValueCountFrequency (%)
769 1
1.9%
803 1
1.9%
1949 1
1.9%
2216 1
1.9%
4758 1
1.9%
4856 1
1.9%
4881 1
1.9%
4982 1
1.9%
5007 1
1.9%
6619 1
1.9%
ValueCountFrequency (%)
45915 1
1.9%
33210 1
1.9%
24262 1
1.9%
19235 1
1.9%
19128 1
1.9%
18446 1
1.9%
18249 1
1.9%
18248 1
1.9%
16256 1
1.9%
16212 1
1.9%

2코스(문수산성)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct54
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4166.1852
Minimum610
Maximum20081
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-11T06:37:08.927238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum610
5-th percentile1763.05
Q13132
median3639.5
Q34335.5
95-th percentile7711.9
Maximum20081
Range19471
Interquartile range (IQR)1203.5

Descriptive statistics

Standard deviation2738.6892
Coefficient of variation (CV)0.65736136
Kurtosis21.654514
Mean4166.1852
Median Absolute Deviation (MAD)592.5
Skewness3.9974924
Sum224974
Variance7500418.3
MonotonicityNot monotonic
2023-12-11T06:37:09.088606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
695 1
 
1.9%
3050 1
 
1.9%
2598 1
 
1.9%
4167 1
 
1.9%
3192 1
 
1.9%
2311 1
 
1.9%
4370 1
 
1.9%
2905 1
 
1.9%
4513 1
 
1.9%
3755 1
 
1.9%
Other values (44) 44
81.5%
ValueCountFrequency (%)
610 1
1.9%
695 1
1.9%
1674 1
1.9%
1811 1
1.9%
2278 1
1.9%
2308 1
1.9%
2311 1
1.9%
2407 1
1.9%
2598 1
1.9%
2741 1
1.9%
ValueCountFrequency (%)
20081 1
1.9%
9812 1
1.9%
8475 1
1.9%
7301 1
1.9%
6438 1
1.9%
6397 1
1.9%
5607 1
1.9%
5440 1
1.9%
5149 1
1.9%
4741 1
1.9%

3코스(애기봉)
Real number (ℝ)

HIGH CORRELATION 

Distinct53
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean712.62963
Minimum28
Maximum3372
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-11T06:37:09.220731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum28
5-th percentile44.75
Q1244
median585
Q3946
95-th percentile1581.45
Maximum3372
Range3344
Interquartile range (IQR)702

Descriptive statistics

Standard deviation626.93532
Coefficient of variation (CV)0.87974917
Kurtosis4.719291
Mean712.62963
Median Absolute Deviation (MAD)354.5
Skewness1.7091181
Sum38482
Variance393047.9
MonotonicityNot monotonic
2023-12-11T06:37:09.353464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1522 2
 
3.7%
829 1
 
1.9%
1056 1
 
1.9%
417 1
 
1.9%
427 1
 
1.9%
901 1
 
1.9%
919 1
 
1.9%
736 1
 
1.9%
560 1
 
1.9%
646 1
 
1.9%
Other values (43) 43
79.6%
ValueCountFrequency (%)
28 1
1.9%
33 1
1.9%
35 1
1.9%
50 1
1.9%
58 1
1.9%
84 1
1.9%
100 1
1.9%
124 1
1.9%
127 1
1.9%
151 1
1.9%
ValueCountFrequency (%)
3372 1
1.9%
1878 1
1.9%
1612 1
1.9%
1565 1
1.9%
1554 1
1.9%
1527 1
1.9%
1525 1
1.9%
1522 2
3.7%
1439 1
1.9%
1199 1
1.9%

4코스(행주산성)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct54
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4746.6111
Minimum226
Maximum19829
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-11T06:37:09.484143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum226
5-th percentile456.45
Q1844.25
median1447
Q38181.75
95-th percentile16228
Maximum19829
Range19603
Interquartile range (IQR)7337.5

Descriptive statistics

Standard deviation5317.6294
Coefficient of variation (CV)1.1203002
Kurtosis0.76689696
Mean4746.6111
Median Absolute Deviation (MAD)838
Skewness1.2730998
Sum256317
Variance28277183
MonotonicityNot monotonic
2023-12-11T06:37:09.623098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
882 1
 
1.9%
6879 1
 
1.9%
959 1
 
1.9%
9704 1
 
1.9%
12300 1
 
1.9%
4188 1
 
1.9%
8306 1
 
1.9%
5654 1
 
1.9%
9809 1
 
1.9%
8064 1
 
1.9%
Other values (44) 44
81.5%
ValueCountFrequency (%)
226 1
1.9%
231 1
1.9%
279 1
1.9%
552 1
1.9%
666 1
1.9%
729 1
1.9%
738 1
1.9%
740 1
1.9%
746 1
1.9%
748 1
1.9%
ValueCountFrequency (%)
19829 1
1.9%
18705 1
1.9%
16501 1
1.9%
16081 1
1.9%
14458 1
1.9%
12300 1
1.9%
11758 1
1.9%
9809 1
1.9%
9704 1
1.9%
8773 1
1.9%

5코스(노래하는분수대)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct54
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9158.2778
Minimum1006
Maximum29021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-11T06:37:09.761427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1006
5-th percentile1222.35
Q11667.75
median3803.5
Q316473.25
95-th percentile27046.75
Maximum29021
Range28015
Interquartile range (IQR)14805.5

Descriptive statistics

Standard deviation8747.6126
Coefficient of variation (CV)0.95515913
Kurtosis-0.66719602
Mean9158.2778
Median Absolute Deviation (MAD)2605
Skewness0.82158215
Sum494547
Variance76520726
MonotonicityNot monotonic
2023-12-11T06:37:09.879595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4644 1
 
1.9%
18580 1
 
1.9%
27824 1
 
1.9%
27557 1
 
1.9%
26772 1
 
1.9%
20049 1
 
1.9%
13377 1
 
1.9%
11127 1
 
1.9%
11114 1
 
1.9%
9076 1
 
1.9%
Other values (44) 44
81.5%
ValueCountFrequency (%)
1006 1
1.9%
1112 1
1.9%
1119 1
1.9%
1278 1
1.9%
1283 1
1.9%
1344 1
1.9%
1352 1
1.9%
1369 1
1.9%
1377 1
1.9%
1421 1
1.9%
ValueCountFrequency (%)
29021 1
1.9%
27824 1
1.9%
27557 1
1.9%
26772 1
1.9%
21985 1
1.9%
21562 1
1.9%
20259 1
1.9%
20189 1
1.9%
20049 1
1.9%
19923 1
1.9%

6코스(출판도시)
Real number (ℝ)

Distinct53
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1499.7037
Minimum408
Maximum2656
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-11T06:37:10.284947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum408
5-th percentile834.05
Q11295
median1459.5
Q31698.5
95-th percentile2291.9
Maximum2656
Range2248
Interquartile range (IQR)403.5

Descriptive statistics

Standard deviation445.79781
Coefficient of variation (CV)0.29725726
Kurtosis0.99651285
Mean1499.7037
Median Absolute Deviation (MAD)227
Skewness0.23905217
Sum80984
Variance198735.68
MonotonicityNot monotonic
2023-12-11T06:37:10.418426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1304 2
 
3.7%
449 1
 
1.9%
1039 1
 
1.9%
1424 1
 
1.9%
1699 1
 
1.9%
1955 1
 
1.9%
1115 1
 
1.9%
1028 1
 
1.9%
1343 1
 
1.9%
1246 1
 
1.9%
Other values (43) 43
79.6%
ValueCountFrequency (%)
408 1
1.9%
449 1
1.9%
784 1
1.9%
861 1
1.9%
1028 1
1.9%
1039 1
1.9%
1043 1
1.9%
1109 1
1.9%
1115 1
1.9%
1128 1
1.9%
ValueCountFrequency (%)
2656 1
1.9%
2607 1
1.9%
2301 1
1.9%
2287 1
1.9%
2103 1
1.9%
2089 1
1.9%
1978 1
1.9%
1955 1
1.9%
1922 1
1.9%
1880 1
1.9%

7코스(헤이리)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct54
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2659.0741
Minimum277
Maximum4680
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-11T06:37:10.543194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum277
5-th percentile637.95
Q12070
median2754
Q33366.75
95-th percentile4191.05
Maximum4680
Range4403
Interquartile range (IQR)1296.75

Descriptive statistics

Standard deviation1009.8604
Coefficient of variation (CV)0.37977895
Kurtosis0.15687919
Mean2659.0741
Median Absolute Deviation (MAD)666
Skewness-0.46442444
Sum143590
Variance1019818
MonotonicityNot monotonic
2023-12-11T06:37:10.657894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
277 1
 
1.9%
3087 1
 
1.9%
2127 1
 
1.9%
2134 1
 
1.9%
2821 1
 
1.9%
2740 1
 
1.9%
2130 1
 
1.9%
1818 1
 
1.9%
2018 1
 
1.9%
1865 1
 
1.9%
Other values (44) 44
81.5%
ValueCountFrequency (%)
277 1
1.9%
293 1
1.9%
350 1
1.9%
793 1
1.9%
1210 1
1.9%
1379 1
1.9%
1574 1
1.9%
1661 1
1.9%
1818 1
1.9%
1865 1
1.9%
ValueCountFrequency (%)
4680 1
1.9%
4377 1
1.9%
4349 1
1.9%
4106 1
1.9%
3998 1
1.9%
3748 1
1.9%
3665 1
1.9%
3629 1
1.9%
3558 1
1.9%
3553 1
1.9%

8코스(반구정)
Real number (ℝ)

HIGH CORRELATION 

Distinct52
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1713.463
Minimum258
Maximum3854
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-11T06:37:10.779840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum258
5-th percentile775.35
Q11291.75
median1727.5
Q32071.75
95-th percentile2712
Maximum3854
Range3596
Interquartile range (IQR)780

Descriptive statistics

Standard deviation651.63471
Coefficient of variation (CV)0.38030277
Kurtosis1.4334311
Mean1713.463
Median Absolute Deviation (MAD)379.5
Skewness0.36675283
Sum92527
Variance424627.8
MonotonicityNot monotonic
2023-12-11T06:37:10.909663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2232 2
 
3.7%
1583 2
 
3.7%
294 1
 
1.9%
1174 1
 
1.9%
1279 1
 
1.9%
1718 1
 
1.9%
1999 1
 
1.9%
2089 1
 
1.9%
1879 1
 
1.9%
1220 1
 
1.9%
Other values (42) 42
77.8%
ValueCountFrequency (%)
258 1
1.9%
294 1
1.9%
724 1
1.9%
803 1
1.9%
844 1
1.9%
886 1
1.9%
907 1
1.9%
978 1
1.9%
1142 1
1.9%
1174 1
1.9%
ValueCountFrequency (%)
3854 1
1.9%
2960 1
1.9%
2855 1
1.9%
2635 1
1.9%
2442 1
1.9%
2417 1
1.9%
2351 1
1.9%
2234 1
1.9%
2232 2
3.7%
2226 1
1.9%

9코스(율곡습지공원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct54
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6731.5
Minimum84
Maximum22498
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-11T06:37:11.060077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum84
5-th percentile1234.5
Q12636.75
median5067.5
Q39617.25
95-th percentile17852.5
Maximum22498
Range22414
Interquartile range (IQR)6980.5

Descriptive statistics

Standard deviation5357.6876
Coefficient of variation (CV)0.79591289
Kurtosis1.5860575
Mean6731.5
Median Absolute Deviation (MAD)2944
Skewness1.3317522
Sum363501
Variance28704816
MonotonicityNot monotonic
2023-12-11T06:37:11.193764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
84 1
 
1.9%
8019 1
 
1.9%
2202 1
 
1.9%
6970 1
 
1.9%
11607 1
 
1.9%
6834 1
 
1.9%
4700 1
 
1.9%
2122 1
 
1.9%
2128 1
 
1.9%
2142 1
 
1.9%
Other values (44) 44
81.5%
ValueCountFrequency (%)
84 1
1.9%
98 1
1.9%
1059 1
1.9%
1329 1
1.9%
1743 1
1.9%
1768 1
1.9%
1898 1
1.9%
2054 1
1.9%
2122 1
1.9%
2125 1
1.9%
ValueCountFrequency (%)
22498 1
1.9%
21744 1
1.9%
21330 1
1.9%
15980 1
1.9%
14381 1
1.9%
13269 1
1.9%
12758 1
1.9%
11775 1
1.9%
11607 1
1.9%
10939 1
1.9%

10코스(장남교)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct54
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean838.92593
Minimum270
Maximum2974
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-11T06:37:11.370749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum270
5-th percentile362.55
Q1509.25
median755.5
Q3958.75
95-th percentile1938.4
Maximum2974
Range2704
Interquartile range (IQR)449.5

Descriptive statistics

Standard deviation492.70826
Coefficient of variation (CV)0.58730842
Kurtosis6.5159727
Mean838.92593
Median Absolute Deviation (MAD)220.5
Skewness2.2452155
Sum45302
Variance242761.43
MonotonicityNot monotonic
2023-12-11T06:37:11.542237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
312 1
 
1.9%
882 1
 
1.9%
604 1
 
1.9%
730 1
 
1.9%
556 1
 
1.9%
426 1
 
1.9%
424 1
 
1.9%
531 1
 
1.9%
464 1
 
1.9%
434 1
 
1.9%
Other values (44) 44
81.5%
ValueCountFrequency (%)
270 1
1.9%
312 1
1.9%
332 1
1.9%
379 1
1.9%
424 1
1.9%
426 1
1.9%
434 1
1.9%
459 1
1.9%
463 1
1.9%
464 1
1.9%
ValueCountFrequency (%)
2974 1
1.9%
2090 1
1.9%
1954 1
1.9%
1930 1
1.9%
1482 1
1.9%
1386 1
1.9%
1241 1
1.9%
1121 1
1.9%
1097 1
1.9%
1094 1
1.9%

11코스(숭의전)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct52
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2217.2222
Minimum0
Maximum28070
Zeros3
Zeros (%)5.6%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-11T06:37:11.717697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile295.75
Q11110
median1636.5
Q32115.75
95-th percentile3697.15
Maximum28070
Range28070
Interquartile range (IQR)1005.75

Descriptive statistics

Standard deviation3763.1274
Coefficient of variation (CV)1.6972261
Kurtosis43.980278
Mean2217.2222
Median Absolute Deviation (MAD)516.5
Skewness6.3818536
Sum119730
Variance14161128
MonotonicityNot monotonic
2023-12-11T06:37:11.906404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3
 
5.6%
1537 1
 
1.9%
2132 1
 
1.9%
2581 1
 
1.9%
2469 1
 
1.9%
1658 1
 
1.9%
764 1
 
1.9%
994 1
 
1.9%
869 1
 
1.9%
1655 1
 
1.9%
Other values (42) 42
77.8%
ValueCountFrequency (%)
0 3
5.6%
455 1
 
1.9%
723 1
 
1.9%
764 1
 
1.9%
833 1
 
1.9%
848 1
 
1.9%
869 1
 
1.9%
981 1
 
1.9%
994 1
 
1.9%
1071 1
 
1.9%
ValueCountFrequency (%)
28070 1
1.9%
7333 1
1.9%
4548 1
1.9%
3239 1
1.9%
3101 1
1.9%
2936 1
1.9%
2809 1
1.9%
2801 1
1.9%
2581 1
1.9%
2469 1
1.9%

12코스(신탄리역)
Real number (ℝ)

HIGH CORRELATION 

Distinct53
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean798.12963
Minimum128
Maximum2346
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-11T06:37:12.105832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128
5-th percentile165.65
Q1382
median698
Q31054.75
95-th percentile1880.05
Maximum2346
Range2218
Interquartile range (IQR)672.75

Descriptive statistics

Standard deviation544.31695
Coefficient of variation (CV)0.68199066
Kurtosis0.27421367
Mean798.12963
Median Absolute Deviation (MAD)349.5
Skewness0.95456853
Sum43099
Variance296280.95
MonotonicityNot monotonic
2023-12-11T06:37:12.280470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
906 2
 
3.7%
311 1
 
1.9%
1417 1
 
1.9%
1029 1
 
1.9%
2346 1
 
1.9%
1830 1
 
1.9%
1997 1
 
1.9%
1104 1
 
1.9%
752 1
 
1.9%
1109 1
 
1.9%
Other values (43) 43
79.6%
ValueCountFrequency (%)
128 1
1.9%
139 1
1.9%
165 1
1.9%
166 1
1.9%
204 1
1.9%
225 1
1.9%
273 1
1.9%
274 1
1.9%
276 1
1.9%
277 1
1.9%
ValueCountFrequency (%)
2346 1
1.9%
1997 1
1.9%
1973 1
1.9%
1830 1
1.9%
1699 1
1.9%
1592 1
1.9%
1565 1
1.9%
1439 1
1.9%
1417 1
1.9%
1411 1
1.9%

Interactions

2023-12-11T06:37:06.965047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:54.519878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:55.535141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:56.379398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:57.326228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:58.310017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:59.662380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:00.802939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:01.971423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:03.258502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:04.519380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:05.909014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:07.051048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:54.602424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:55.600988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:56.444860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:57.405779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:58.383610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:59.761836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:00.892298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:02.062613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:03.353336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:04.609904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:05.998974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:07.145836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:54.703667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:55.674711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:56.521933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:57.494450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:58.712589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:59.866154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:01.004425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:02.161135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:03.462367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:04.722769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:06.102155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:07.224172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:54.811431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:55.746491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:56.596291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:57.582835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:58.792571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:59.975979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:01.133780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:02.259106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:03.565766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:04.807626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:06.190262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:07.328465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:54.888895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:55.820323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:56.680563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:57.673961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:58.890846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:00.082914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:01.224943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:02.354261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:03.696955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:04.915010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:06.294341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:07.459408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:54.977955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:55.891914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:56.752552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:57.754592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:58.986778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:00.196758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:01.306691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:02.468697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:03.819715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:05.015908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:06.373934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:07.537441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:55.058192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:55.960680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:56.815719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:57.827782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:59.066515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:00.290545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:01.386671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:02.578468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:03.946885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:05.105364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:06.451726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:07.600674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:55.122692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:56.025541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:56.885972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:57.909823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:59.141281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:00.369038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:01.471568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:02.660492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:04.048910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:05.450036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:06.531312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:07.681301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:55.219622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:56.112581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:56.967624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:57.997976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:59.232010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:00.464522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:01.568781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:02.812436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:04.162921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:05.557614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:06.631880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:07.765920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:55.303861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:56.176729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:57.040695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:58.073897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:59.332809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:00.537223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:01.665187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:02.923998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:04.254693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:05.646056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:06.719820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:07.850514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:55.389012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:56.245943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:57.130203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:58.164618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:59.465826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:00.629328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:01.784315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:03.051245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:04.352239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:05.740659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:06.816453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:07.935977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:55.472447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:56.317280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:57.254250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:58.237614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:59.565265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:00.716347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:01.888654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:03.162163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:04.444132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:05.831516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:06.894670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:37:12.386636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분1코스(대명항입구)2코스(문수산성)3코스(애기봉)4코스(행주산성)5코스(노래하는분수대)6코스(출판도시)7코스(헤이리)8코스(반구정)9코스(율곡습지공원)10코스(장남교)11코스(숭의전)12코스(신탄리역)
구분1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
1코스(대명항입구)1.0001.0000.0000.4260.4180.0000.5410.0000.2220.7340.2060.7020.483
2코스(문수산성)1.0000.0001.0000.0000.0000.0000.0000.0000.0510.5830.5820.6780.000
3코스(애기봉)1.0000.4260.0001.0000.6140.5940.0000.0000.0000.0000.4620.0000.690
4코스(행주산성)1.0000.4180.0000.6141.0000.8260.0000.0000.0000.1560.0000.0000.648
5코스(노래하는분수대)1.0000.0000.0000.5940.8261.0000.1760.3370.0000.0000.0000.0000.744
6코스(출판도시)1.0000.5410.0000.0000.0000.1761.0000.6250.6770.0000.3300.0000.000
7코스(헤이리)1.0000.0000.0000.0000.0000.3370.6251.0000.6140.3970.1330.3710.251
8코스(반구정)1.0000.2220.0510.0000.0000.0000.6770.6141.0000.1820.3950.3230.000
9코스(율곡습지공원)1.0000.7340.5830.0000.1560.0000.0000.3970.1821.0000.6170.8410.341
10코스(장남교)1.0000.2060.5820.4620.0000.0000.3300.1330.3950.6171.0000.7840.000
11코스(숭의전)1.0000.7020.6780.0000.0000.0000.0000.3710.3230.8410.7841.0000.000
12코스(신탄리역)1.0000.4830.0000.6900.6480.7440.0000.2510.0000.3410.0000.0001.000
2023-12-11T06:37:12.587407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
1코스(대명항입구)2코스(문수산성)3코스(애기봉)4코스(행주산성)5코스(노래하는분수대)6코스(출판도시)7코스(헤이리)8코스(반구정)9코스(율곡습지공원)10코스(장남교)11코스(숭의전)12코스(신탄리역)
1코스(대명항입구)1.0000.2900.2390.4980.2720.4760.2300.1560.6340.2650.6150.522
2코스(문수산성)0.2901.000-0.280-0.098-0.3440.3890.3340.5420.3900.4960.461-0.043
3코스(애기봉)0.239-0.2801.0000.4440.653-0.193-0.126-0.3360.146-0.021-0.1510.631
4코스(행주산성)0.498-0.0980.4441.0000.6430.054-0.138-0.3280.076-0.221-0.0620.690
5코스(노래하는분수대)0.272-0.3440.6530.6431.000-0.211-0.054-0.448-0.026-0.341-0.0990.694
6코스(출판도시)0.4760.389-0.1930.054-0.2111.0000.1230.4440.3460.3540.4760.138
7코스(헤이리)0.2300.334-0.126-0.138-0.0540.1231.0000.2770.4940.4290.558-0.016
8코스(반구정)0.1560.542-0.336-0.328-0.4480.4440.2771.0000.3240.5580.459-0.142
9코스(율곡습지공원)0.6340.3900.1460.076-0.0260.3460.4940.3241.0000.5560.7490.270
10코스(장남교)0.2650.496-0.021-0.221-0.3410.3540.4290.5580.5561.0000.513-0.114
11코스(숭의전)0.6150.461-0.151-0.062-0.0990.4760.5580.4590.7490.5131.0000.077
12코스(신탄리역)0.522-0.0430.6310.6900.6940.138-0.016-0.1420.270-0.1140.0771.000

Missing values

2023-12-11T06:37:08.040667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:37:08.218610image/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

구분1코스(대명항입구)2코스(문수산성)3코스(애기봉)4코스(행주산성)5코스(노래하는분수대)6코스(출판도시)7코스(헤이리)8코스(반구정)9코스(율곡습지공원)10코스(장남교)11코스(숭의전)12코스(신탄리역)
02019-01-018036958298824644449277294843120311
12019-02-017696107276663125408293258982700277
22019-03-0119491674755746301910431210114213294740406
32019-04-0111344981278322632241109260522321081920902801276
42019-05-01126231811955231363413043540218722498297428070204
52019-06-0198024741433279354013684680179399319314548225
62019-07-0147583482339552257114753220158333486031567488
72019-08-015007362184738294214083272223445146691306478
82019-09-0166193450151814314417713318180151067181404319
92019-10-01891141014181410355619224349285520549722278534
구분1코스(대명항입구)2코스(문수산성)3코스(애기봉)4코스(행주산성)5코스(노래하는분수대)6코스(출판도시)7코스(헤이리)8코스(반구정)9코스(율곡습지공원)10코스(장남교)11코스(숭의전)12코스(신탄리역)
442022-09-0114030353916128221202591308289716842174478218421973
452022-10-01182483479156514458161621672314014992133083318501439
462022-11-01182495440337216081201891725374817379402109420761592
472022-12-019087293418788427152111509281213303281721848919
482023-01-018870227815274608580086116618031059622723411
492023-02-01127353405425877368691327189284418987511071577
502023-03-0114565365868916501937613512524126145466851113724
512023-04-0114138325374019829134641455248688655875021381909
522023-05-01122223112706187052156213822458907662237917311026
532023-06-01115093285610117581724815372375724580646318181062