Overview

Dataset statistics

Number of variables14
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 MiB
Average record size in memory132.0 B

Variable types

Categorical1
Numeric12
DateTime1

Dataset

Description주차장 이름,총 건수,총 금액,장애인 할인 건수,장애인 할인 금액,국가유공자 할인 건수,국가유공자 할인 금액,경차 할인 건수,경차 할인 금액,저공해 할인 건수,저공해 할인 금액,무료차량 건수,무료차량 금액,입차 시간
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-21087/S/1/datasetView.do

Alerts

총 건수 is highly overall correlated with 총 금액 and 8 other fieldsHigh correlation
총 금액 is highly overall correlated with 총 건수 and 8 other fieldsHigh correlation
장애인 할인 건수 is highly overall correlated with 총 건수 and 8 other fieldsHigh correlation
장애인 할인 금액 is highly overall correlated with 총 건수 and 8 other fieldsHigh correlation
국가유공자 할인 건수 is highly overall correlated with 총 건수 and 8 other fieldsHigh correlation
국가유공자 할인 금액 is highly overall correlated with 총 건수 and 8 other fieldsHigh correlation
경차 할인 건수 is highly overall correlated with 총 건수 and 8 other fieldsHigh correlation
경차 할인 금액 is highly overall correlated with 총 건수 and 8 other fieldsHigh correlation
저공해 할인 건수 is highly overall correlated with 총 건수 and 8 other fieldsHigh correlation
저공해 할인 금액 is highly overall correlated with 총 건수 and 8 other fieldsHigh correlation
무료차량 건수 is highly overall correlated with 무료차량 금액High correlation
무료차량 금액 is highly overall correlated with 무료차량 건수High correlation
무료차량 건수 is highly skewed (γ1 = 52.69220566)Skewed
무료차량 금액 is highly skewed (γ1 = 95.81703206)Skewed
장애인 할인 건수 has 1050 (10.5%) zerosZeros
장애인 할인 금액 has 1050 (10.5%) zerosZeros
국가유공자 할인 건수 has 3596 (36.0%) zerosZeros
국가유공자 할인 금액 has 3596 (36.0%) zerosZeros
경차 할인 건수 has 324 (3.2%) zerosZeros
경차 할인 금액 has 324 (3.2%) zerosZeros
무료차량 건수 has 9901 (99.0%) zerosZeros
무료차량 금액 has 9902 (99.0%) zerosZeros

Reproduction

Analysis started2024-05-11 06:39:25.976768
Analysis finished2024-05-11 06:40:03.024362
Duration37.05 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

주차장 이름
Categorical

Distinct28
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
광나루1,2주차장
 
417
잠실1주차장
 
408
뚝섬1주차장
 
408
반포2,3주차장
 
407
뚝섬2주차장
 
407
Other values (23)
7953 

Length

Max length10
Median length6
Mean length6.8287
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row여의도1주차장
2nd row양화2주차장
3rd row광나루1,2주차장
4th row강서1주차장
5th row이촌1주차장

Common Values

ValueCountFrequency (%)
광나루1,2주차장 417
 
4.2%
잠실1주차장 408
 
4.1%
뚝섬1주차장 408
 
4.1%
반포2,3주차장 407
 
4.1%
뚝섬2주차장 407
 
4.1%
여의도5주차장 402
 
4.0%
잠원2-6주차장 398
 
4.0%
여의도4주차장 397
 
4.0%
여의도1주차장 396
 
4.0%
난지1,2,3주차장 396
 
4.0%
Other values (18) 5964
59.6%

Length

2024-05-11T15:40:03.140603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
광나루1,2주차장 417
 
4.2%
잠실1주차장 408
 
4.1%
뚝섬1주차장 408
 
4.1%
반포2,3주차장 407
 
4.1%
뚝섬2주차장 407
 
4.1%
여의도5주차장 402
 
4.0%
잠원2-6주차장 398
 
4.0%
여의도4주차장 397
 
4.0%
여의도1주차장 396
 
4.0%
난지1,2,3주차장 396
 
4.0%
Other values (18) 5964
59.6%

총 건수
Real number (ℝ)

HIGH CORRELATION 

Distinct532
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean104.0336
Minimum1
Maximum902
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:40:03.318072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6
Q130
median69
Q3143
95-th percentile311
Maximum902
Range901
Interquartile range (IQR)113

Descriptive statistics

Standard deviation105.96615
Coefficient of variation (CV)1.0185762
Kurtosis6.0989776
Mean104.0336
Median Absolute Deviation (MAD)48
Skewness2.0411741
Sum1040336
Variance11228.824
MonotonicityNot monotonic
2024-05-11T15:40:03.537718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10 114
 
1.1%
12 109
 
1.1%
8 106
 
1.1%
5 106
 
1.1%
13 104
 
1.0%
6 103
 
1.0%
9 103
 
1.0%
11 100
 
1.0%
4 99
 
1.0%
7 96
 
1.0%
Other values (522) 8960
89.6%
ValueCountFrequency (%)
1 55
0.5%
2 64
0.6%
3 89
0.9%
4 99
1.0%
5 106
1.1%
6 103
1.0%
7 96
1.0%
8 106
1.1%
9 103
1.0%
10 114
1.1%
ValueCountFrequency (%)
902 1
< 0.1%
874 1
< 0.1%
861 1
< 0.1%
840 1
< 0.1%
833 1
< 0.1%
822 1
< 0.1%
819 1
< 0.1%
806 1
< 0.1%
776 1
< 0.1%
757 1
< 0.1%

총 금액
Real number (ℝ)

HIGH CORRELATION 

Distinct5200
Distinct (%)52.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean220678.11
Minimum500
Maximum2655900
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:40:03.797727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum500
5-th percentile11000
Q153175
median117600
Q3269225
95-th percentile851405
Maximum2655900
Range2655400
Interquartile range (IQR)216050

Descriptive statistics

Standard deviation276770.33
Coefficient of variation (CV)1.2541811
Kurtosis7.7281937
Mean220678.11
Median Absolute Deviation (MAD)80850
Skewness2.5022347
Sum2.2067811 × 109
Variance7.6601815 × 1010
MonotonicityNot monotonic
2024-05-11T15:40:04.056393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
68700 11
 
0.1%
61800 11
 
0.1%
72600 11
 
0.1%
7500 11
 
0.1%
57300 11
 
0.1%
54200 10
 
0.1%
49000 10
 
0.1%
1000 10
 
0.1%
9500 10
 
0.1%
23100 10
 
0.1%
Other values (5190) 9895
99.0%
ValueCountFrequency (%)
500 5
0.1%
600 1
 
< 0.1%
700 1
 
< 0.1%
800 3
 
< 0.1%
900 1
 
< 0.1%
1000 10
0.1%
1100 5
0.1%
1200 3
 
< 0.1%
1300 5
0.1%
1400 5
0.1%
ValueCountFrequency (%)
2655900 1
< 0.1%
2437600 1
< 0.1%
2353200 1
< 0.1%
2278100 1
< 0.1%
2166200 1
< 0.1%
2054600 1
< 0.1%
1993100 1
< 0.1%
1957800 1
< 0.1%
1955000 1
< 0.1%
1920300 1
< 0.1%

장애인 할인 건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct94
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.091
Minimum0
Maximum103
Zeros1050
Zeros (%)10.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:40:04.343267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median7
Q318
95-th percentile40
Maximum103
Range103
Interquartile range (IQR)16

Descriptive statistics

Standard deviation13.916871
Coefficient of variation (CV)1.1510107
Kurtosis4.0146407
Mean12.091
Median Absolute Deviation (MAD)6
Skewness1.80566
Sum120910
Variance193.67929
MonotonicityNot monotonic
2024-05-11T15:40:04.606133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1050
 
10.5%
1 972
 
9.7%
2 853
 
8.5%
3 679
 
6.8%
4 562
 
5.6%
5 484
 
4.8%
6 396
 
4.0%
7 339
 
3.4%
8 309
 
3.1%
9 277
 
2.8%
Other values (84) 4079
40.8%
ValueCountFrequency (%)
0 1050
10.5%
1 972
9.7%
2 853
8.5%
3 679
6.8%
4 562
5.6%
5 484
4.8%
6 396
 
4.0%
7 339
 
3.4%
8 309
 
3.1%
9 277
 
2.8%
ValueCountFrequency (%)
103 1
 
< 0.1%
97 1
 
< 0.1%
96 2
< 0.1%
95 1
 
< 0.1%
94 1
 
< 0.1%
92 1
 
< 0.1%
91 2
< 0.1%
90 1
 
< 0.1%
89 1
 
< 0.1%
87 4
< 0.1%

장애인 할인 금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct2252
Distinct (%)22.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42448.483
Minimum0
Maximum584800
Zeros1050
Zeros (%)10.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:40:04.888397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15400
median19500
Q353800
95-th percentile169720
Maximum584800
Range584800
Interquartile range (IQR)48400

Descriptive statistics

Standard deviation59502.39
Coefficient of variation (CV)1.4017554
Kurtosis8.7915282
Mean42448.483
Median Absolute Deviation (MAD)17500
Skewness2.6102878
Sum4.2448483 × 108
Variance3.5405344 × 109
MonotonicityNot monotonic
2024-05-11T15:40:05.106289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1050
 
10.5%
800 88
 
0.9%
1600 82
 
0.8%
8000 71
 
0.7%
1500 58
 
0.6%
12000 56
 
0.6%
2000 52
 
0.5%
1800 52
 
0.5%
1200 49
 
0.5%
2800 45
 
0.4%
Other values (2242) 8397
84.0%
ValueCountFrequency (%)
0 1050
10.5%
800 88
 
0.9%
900 4
 
< 0.1%
960 12
 
0.1%
1000 38
 
0.4%
1100 6
 
0.1%
1120 6
 
0.1%
1200 49
 
0.5%
1280 5
 
0.1%
1300 38
 
0.4%
ValueCountFrequency (%)
584800 1
< 0.1%
553000 1
< 0.1%
517900 1
< 0.1%
472500 1
< 0.1%
458500 1
< 0.1%
457900 1
< 0.1%
443700 1
< 0.1%
434700 1
< 0.1%
427700 1
< 0.1%
415200 1
< 0.1%

국가유공자 할인 건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct27
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.949
Minimum0
Maximum38
Zeros3596
Zeros (%)36.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:40:05.304517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile7
Maximum38
Range38
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.6156994
Coefficient of variation (CV)1.3420725
Kurtosis14.562047
Mean1.949
Median Absolute Deviation (MAD)1
Skewness2.7390195
Sum19490
Variance6.8418832
MonotonicityNot monotonic
2024-05-11T15:40:05.490596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 3596
36.0%
1 2255
22.6%
2 1379
 
13.8%
3 892
 
8.9%
4 586
 
5.9%
5 393
 
3.9%
6 275
 
2.8%
7 199
 
2.0%
8 122
 
1.2%
9 98
 
1.0%
Other values (17) 205
 
2.1%
ValueCountFrequency (%)
0 3596
36.0%
1 2255
22.6%
2 1379
 
13.8%
3 892
 
8.9%
4 586
 
5.9%
5 393
 
3.9%
6 275
 
2.8%
7 199
 
2.0%
8 122
 
1.2%
9 98
 
1.0%
ValueCountFrequency (%)
38 1
 
< 0.1%
33 1
 
< 0.1%
31 1
 
< 0.1%
29 1
 
< 0.1%
23 2
 
< 0.1%
22 3
< 0.1%
20 2
 
< 0.1%
19 1
 
< 0.1%
18 6
0.1%
17 3
< 0.1%

국가유공자 할인 금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct691
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6671.192
Minimum0
Maximum172800
Zeros3596
Zeros (%)36.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:40:05.691923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2400
Q38400
95-th percentile28305
Maximum172800
Range172800
Interquartile range (IQR)8400

Descriptive statistics

Standard deviation11263.418
Coefficient of variation (CV)1.6883667
Kurtosis23.049075
Mean6671.192
Median Absolute Deviation (MAD)2400
Skewness3.7022858
Sum66711920
Variance1.2686459 × 108
MonotonicityNot monotonic
2024-05-11T15:40:05.901568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3596
36.0%
800 247
 
2.5%
1600 155
 
1.6%
8000 139
 
1.4%
2400 104
 
1.0%
2000 103
 
1.0%
1000 103
 
1.0%
2800 100
 
1.0%
1500 97
 
1.0%
1800 96
 
1.0%
Other values (681) 5260
52.6%
ValueCountFrequency (%)
0 3596
36.0%
800 247
 
2.5%
900 6
 
0.1%
960 23
 
0.2%
1000 103
 
1.0%
1100 10
 
0.1%
1120 18
 
0.2%
1200 95
 
0.9%
1280 18
 
0.2%
1300 92
 
0.9%
ValueCountFrequency (%)
172800 1
< 0.1%
145200 1
< 0.1%
144480 1
< 0.1%
129800 1
< 0.1%
122100 1
< 0.1%
108100 1
< 0.1%
105300 1
< 0.1%
100000 1
< 0.1%
99100 1
< 0.1%
98900 1
< 0.1%

경차 할인 건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct145
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.283
Minimum0
Maximum224
Zeros324
Zeros (%)3.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:40:06.130625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q16
median16
Q331
95-th percentile67
Maximum224
Range224
Interquartile range (IQR)25

Descriptive statistics

Standard deviation21.687783
Coefficient of variation (CV)0.97328831
Kurtosis4.8881508
Mean22.283
Median Absolute Deviation (MAD)11
Skewness1.8126517
Sum222830
Variance470.35995
MonotonicityNot monotonic
2024-05-11T15:40:06.351421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 400
 
4.0%
1 379
 
3.8%
3 377
 
3.8%
4 346
 
3.5%
5 341
 
3.4%
6 338
 
3.4%
0 324
 
3.2%
8 309
 
3.1%
7 308
 
3.1%
10 286
 
2.9%
Other values (135) 6592
65.9%
ValueCountFrequency (%)
0 324
3.2%
1 379
3.8%
2 400
4.0%
3 377
3.8%
4 346
3.5%
5 341
3.4%
6 338
3.4%
7 308
3.1%
8 309
3.1%
9 266
2.7%
ValueCountFrequency (%)
224 1
< 0.1%
193 1
< 0.1%
183 1
< 0.1%
162 1
< 0.1%
159 1
< 0.1%
156 1
< 0.1%
154 1
< 0.1%
151 1
< 0.1%
147 1
< 0.1%
146 1
< 0.1%

경차 할인 금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct1727
Distinct (%)17.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41809.45
Minimum0
Maximum706600
Zeros324
Zeros (%)3.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:40:06.581645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1100
Q19900
median23900
Q353000
95-th percentile149705
Maximum706600
Range706600
Interquartile range (IQR)43100

Descriptive statistics

Standard deviation51269.684
Coefficient of variation (CV)1.2262702
Kurtosis11.398015
Mean41809.45
Median Absolute Deviation (MAD)17300
Skewness2.724092
Sum4.180945 × 108
Variance2.6285805 × 109
MonotonicityNot monotonic
2024-05-11T15:40:06.838048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 324
 
3.2%
7500 58
 
0.6%
500 52
 
0.5%
1000 46
 
0.5%
15000 41
 
0.4%
5000 38
 
0.4%
5600 35
 
0.4%
7400 35
 
0.4%
5700 33
 
0.3%
14200 31
 
0.3%
Other values (1717) 9307
93.1%
ValueCountFrequency (%)
0 324
3.2%
500 52
 
0.5%
600 25
 
0.2%
700 14
 
0.1%
800 17
 
0.2%
900 14
 
0.1%
1000 46
 
0.5%
1100 27
 
0.3%
1200 21
 
0.2%
1300 28
 
0.3%
ValueCountFrequency (%)
706600 1
< 0.1%
517800 1
< 0.1%
452600 1
< 0.1%
431600 1
< 0.1%
427900 1
< 0.1%
426100 1
< 0.1%
414600 1
< 0.1%
410700 1
< 0.1%
409000 1
< 0.1%
387500 1
< 0.1%

저공해 할인 건수
Real number (ℝ)

HIGH CORRELATION 

Distinct403
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean67.6871
Minimum0
Maximum705
Zeros45
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:40:07.087559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q119
median43
Q392
95-th percentile208
Maximum705
Range705
Interquartile range (IQR)73

Descriptive statistics

Standard deviation72.342987
Coefficient of variation (CV)1.0687854
Kurtosis8.5055216
Mean67.6871
Median Absolute Deviation (MAD)30
Skewness2.324877
Sum676871
Variance5233.5077
MonotonicityNot monotonic
2024-05-11T15:40:07.310839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6 172
 
1.7%
4 172
 
1.7%
5 161
 
1.6%
7 159
 
1.6%
2 155
 
1.6%
3 148
 
1.5%
11 147
 
1.5%
22 133
 
1.3%
8 132
 
1.3%
13 132
 
1.3%
Other values (393) 8489
84.9%
ValueCountFrequency (%)
0 45
 
0.4%
1 116
1.2%
2 155
1.6%
3 148
1.5%
4 172
1.7%
5 161
1.6%
6 172
1.7%
7 159
1.6%
8 132
1.3%
9 125
1.2%
ValueCountFrequency (%)
705 1
< 0.1%
670 1
< 0.1%
657 1
< 0.1%
642 1
< 0.1%
638 1
< 0.1%
590 1
< 0.1%
582 1
< 0.1%
563 1
< 0.1%
558 1
< 0.1%
540 1
< 0.1%

저공해 할인 금액
Real number (ℝ)

HIGH CORRELATION 

Distinct3383
Distinct (%)33.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129538.03
Minimum0
Maximum2042300
Zeros45
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:40:07.509062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5497.5
Q128900
median65500
Q3157500
95-th percentile499925
Maximum2042300
Range2042300
Interquartile range (IQR)128600

Descriptive statistics

Standard deviation171716.84
Coefficient of variation (CV)1.3256095
Kurtosis11.144816
Mean129538.03
Median Absolute Deviation (MAD)46300
Skewness2.8415312
Sum1.2953803 × 109
Variance2.9486673 × 1010
MonotonicityNot monotonic
2024-05-11T15:40:07.717184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 45
 
0.4%
5000 22
 
0.2%
30600 18
 
0.2%
8700 17
 
0.2%
6500 17
 
0.2%
1000 16
 
0.2%
26700 16
 
0.2%
1400 15
 
0.1%
13200 15
 
0.1%
1200 15
 
0.1%
Other values (3373) 9804
98.0%
ValueCountFrequency (%)
0 45
0.4%
100 1
 
< 0.1%
500 13
 
0.1%
600 6
 
0.1%
700 3
 
< 0.1%
800 8
 
0.1%
900 2
 
< 0.1%
1000 16
 
0.2%
1100 9
 
0.1%
1200 15
 
0.1%
ValueCountFrequency (%)
2042300 1
< 0.1%
1686300 1
< 0.1%
1625700 1
< 0.1%
1597700 1
< 0.1%
1582800 1
< 0.1%
1469400 1
< 0.1%
1456900 1
< 0.1%
1346700 1
< 0.1%
1291100 1
< 0.1%
1249000 1
< 0.1%

무료차량 건수
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0235
Minimum0
Maximum37
Zeros9901
Zeros (%)99.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:40:07.892945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum37
Range37
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.47788135
Coefficient of variation (CV)20.335377
Kurtosis3702.1997
Mean0.0235
Median Absolute Deviation (MAD)0
Skewness52.692206
Sum235
Variance0.22837059
MonotonicityNot monotonic
2024-05-11T15:40:08.377563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 9901
99.0%
1 73
 
0.7%
2 6
 
0.1%
4 5
 
0.1%
3 5
 
0.1%
9 3
 
< 0.1%
7 2
 
< 0.1%
10 2
 
< 0.1%
37 1
 
< 0.1%
6 1
 
< 0.1%
ValueCountFrequency (%)
0 9901
99.0%
1 73
 
0.7%
2 6
 
0.1%
3 5
 
0.1%
4 5
 
0.1%
6 1
 
< 0.1%
7 2
 
< 0.1%
9 3
 
< 0.1%
10 2
 
< 0.1%
11 1
 
< 0.1%
ValueCountFrequency (%)
37 1
 
< 0.1%
11 1
 
< 0.1%
10 2
 
< 0.1%
9 3
 
< 0.1%
7 2
 
< 0.1%
6 1
 
< 0.1%
4 5
 
0.1%
3 5
 
0.1%
2 6
 
0.1%
1 73
0.7%

무료차량 금액
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct51
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean210.96
Minimum0
Maximum1182300
Zeros9902
Zeros (%)99.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:40:08.616459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1182300
Range1182300
Interquartile range (IQR)0

Descriptive statistics

Standard deviation12000.732
Coefficient of variation (CV)56.886292
Kurtosis9419.4391
Mean210.96
Median Absolute Deviation (MAD)0
Skewness95.817032
Sum2109600
Variance1.4401757 × 108
MonotonicityNot monotonic
2024-05-11T15:40:08.876287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9902
99.0%
2000 14
 
0.1%
1000 10
 
0.1%
15000 8
 
0.1%
4000 4
 
< 0.1%
2300 4
 
< 0.1%
1400 3
 
< 0.1%
3000 3
 
< 0.1%
2900 3
 
< 0.1%
6400 2
 
< 0.1%
Other values (41) 47
 
0.5%
ValueCountFrequency (%)
0 9902
99.0%
500 1
 
< 0.1%
800 2
 
< 0.1%
900 2
 
< 0.1%
1000 10
 
0.1%
1200 1
 
< 0.1%
1300 1
 
< 0.1%
1400 3
 
< 0.1%
1500 1
 
< 0.1%
1600 2
 
< 0.1%
ValueCountFrequency (%)
1182300 1
< 0.1%
125800 1
< 0.1%
106700 1
< 0.1%
56000 1
< 0.1%
51200 1
< 0.1%
47000 1
< 0.1%
36400 1
< 0.1%
33000 1
< 0.1%
21800 1
< 0.1%
20800 1
< 0.1%
Distinct1558
Distinct (%)15.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2019-11-01 00:00:00
Maximum2024-05-11 00:00:00
2024-05-11T15:40:09.117632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:40:09.346772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2024-05-11T15:39:59.874223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:33.881162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:36.091295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:38.442011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:40.536101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:42.854495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:45.029116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:47.324469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:49.437351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:53.243096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:55.639894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:57.883550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:40:00.054518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:34.037894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:36.238594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:38.603709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:40.723876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:43.012067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:45.163444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:47.466685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:49.582154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:53.415347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:55.795496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:58.018822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:40:00.224621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:34.273839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:36.439270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:38.775572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:40.926438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:43.194133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:45.347452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:47.620627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:49.756751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:53.604191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:56.000233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:58.173097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:40:00.401138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:34.459824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:36.763259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:38.944077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:41.125310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:43.348953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:45.529634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:47.779141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:49.919828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:53.774045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:56.198559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:58.336555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:40:00.564476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:34.628652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:36.950116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:39.100724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:41.361630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:43.564640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:45.688217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:47.919401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:50.085353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:53.961253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:56.354600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:58.507478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:40:00.725358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:34.840607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:37.149722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:39.267047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:41.552191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:43.792334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:45.944268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:48.164737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:51.725592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:54.157534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:56.530062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:58.670156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:40:00.911601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:35.019703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:37.334800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:39.410446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:41.722796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:43.965390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:46.141992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:48.368651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:51.907617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:54.384248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:56.713552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:58.829306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:40:01.053394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:35.184802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:37.500566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:39.549366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:41.871400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:44.119487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:46.337964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:48.516109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:52.091745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:54.563356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:56.910574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:58.986539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:40:01.209832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:35.362733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:37.685981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:39.760670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:42.061170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:44.310768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:46.570630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:48.708296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:52.308517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:54.751487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:57.100306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:59.175395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:40:01.373988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:35.536844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:37.891124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:39.941179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:42.253863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:44.499894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:46.775985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:48.887057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:52.615744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:54.959889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:57.315085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:59.338066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:40:01.989111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:35.733196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:38.101506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:40.141530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:42.472979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:44.663442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:46.966298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:49.080852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:52.874579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:55.255258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:57.545798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:59.523795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:40:02.206218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:35.910870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:38.269886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:40.340704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:42.663185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:44.840672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:47.151817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:49.269582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:53.041714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:55.454349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:57.738978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:59.705835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T15:40:09.576629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주차장 이름총 건수총 금액장애인 할인 건수장애인 할인 금액국가유공자 할인 건수국가유공자 할인 금액경차 할인 건수경차 할인 금액저공해 할인 건수저공해 할인 금액무료차량 건수무료차량 금액
주차장 이름1.0000.6390.6680.6550.6550.4570.4550.5950.6050.6020.6440.0330.000
총 건수0.6391.0000.8730.8610.6980.6400.4950.8940.6620.9690.8460.0000.000
총 금액0.6680.8731.0000.7810.8490.5690.6120.8220.7990.8420.9560.0000.070
장애인 할인 건수0.6550.8610.7811.0000.7970.6920.5310.8340.5720.8140.6990.0000.000
장애인 할인 금액0.6550.6980.8490.7971.0000.5910.6600.6780.6350.6400.7630.0000.000
국가유공자 할인 건수0.4570.6400.5690.6920.5911.0000.8570.6210.3810.6380.4950.0000.000
국가유공자 할인 금액0.4550.4950.6120.5310.6600.8571.0000.5040.4250.5010.5560.0000.000
경차 할인 건수0.5950.8940.8220.8340.6780.6210.5041.0000.8060.8430.7800.0000.000
경차 할인 금액0.6050.6620.7990.5720.6350.3810.4250.8061.0000.6000.7330.0000.000
저공해 할인 건수0.6020.9690.8420.8140.6400.6380.5010.8430.6001.0000.8320.0000.000
저공해 할인 금액0.6440.8460.9560.6990.7630.4950.5560.7800.7330.8321.0000.0000.000
무료차량 건수0.0330.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.676
무료차량 금액0.0000.0000.0700.0000.0000.0000.0000.0000.0000.0000.0000.6761.000
2024-05-11T15:40:09.820400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
총 건수총 금액장애인 할인 건수장애인 할인 금액국가유공자 할인 건수국가유공자 할인 금액경차 할인 건수경차 할인 금액저공해 할인 건수저공해 할인 금액무료차량 건수무료차량 금액주차장 이름
총 건수1.0000.9380.8630.7890.6960.6670.9510.8940.9900.9320.0230.0230.288
총 금액0.9381.0000.8460.8700.6710.6900.8770.9240.9270.9750.0380.0390.310
장애인 할인 건수0.8630.8461.0000.9290.7030.6650.7980.7600.8150.7820.0290.0290.300
장애인 할인 금액0.7890.8700.9291.0000.6450.6500.7220.7560.7450.7840.0380.0370.300
국가유공자 할인 건수0.6960.6710.7030.6451.0000.9430.6480.6040.6540.6210.0290.0300.181
국가유공자 할인 금액0.6670.6900.6650.6500.9431.0000.6190.6180.6300.6390.0370.0380.181
경차 할인 건수0.9510.8770.7980.7220.6480.6191.0000.9260.9150.8490.0140.0150.258
경차 할인 금액0.8940.9240.7600.7560.6040.6180.9261.0000.8640.8830.0190.0210.274
저공해 할인 건수0.9900.9270.8150.7450.6540.6300.9150.8641.0000.9430.0170.0170.263
저공해 할인 금액0.9320.9750.7820.7840.6210.6390.8490.8830.9431.0000.0290.0290.292
무료차량 건수0.0230.0380.0290.0380.0290.0370.0140.0190.0170.0291.0000.9950.016
무료차량 금액0.0230.0390.0290.0370.0300.0380.0150.0210.0170.0290.9951.0000.000
주차장 이름0.2880.3100.3000.3000.1810.1810.2580.2740.2630.2920.0160.0001.000

Missing values

2024-05-11T15:40:02.529708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T15:40:02.891575image/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

주차장 이름총 건수총 금액장애인 할인 건수장애인 할인 금액국가유공자 할인 건수국가유공자 할인 금액경차 할인 건수경차 할인 금액저공해 할인 건수저공해 할인 금액무료차량 건수무료차량 금액입차 시간
24245여의도1주차장2145756003316930052300053119900123263400002020/07/01
21501양화2주차장121560000004790087700002022/09/08
2312광나루1,2주차장11517390030586001120022265006287600002023/10/05
1432강서1주차장24261001260012100662001615200002023/03/07
30864이촌1주차장91200000005790044100002021/07/31
6283난지1,2,3주차장142262200267450023800345970080124200002023/09/12
12340뚝섬4주차장63102700113001100027409003459500002021/11/22
20494양화2주차장6750000001100056500002020/08/22
1854광나루1,2주차장123159800182920061120040498005969600002021/06/01
7369뚝섬1주차장21302000000765001423700002020/08/31
주차장 이름총 건수총 금액장애인 할인 건수장애인 할인 금액국가유공자 할인 건수국가유공자 할인 금액경차 할인 건수경차 할인 금액저공해 할인 건수저공해 할인 금액무료차량 건수무료차량 금액입차 시간
5570난지1,2,3주차장4460100923680410720756002420100002020/12/30
16898반포1주차장19195601336000653001210900002020/07/13
10586뚝섬3주차장59980005128000021359003349300002021/05/30
30924이촌1주차장121560011600004410079900002021/11/17
16374반포1주차장7479100553000012111005762700002024/03/15
6120난지1,2,3주차장2705168803694560124672065104900157270700002020/09/13
1058강서1주차장18304402624013200451001115900002020/06/08
38706잠원2-6주차장33049120041890009137006894500212294000002021/07/13
22888양화3주차장36356000000864002829200002021/08/26
32076이촌1주차장22238002560000428001615400002024/05/05