Overview

Dataset statistics

Number of variables5
Number of observations47
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.1 KiB
Average record size in memory45.8 B

Variable types

DateTime1
Numeric3
Categorical1

Dataset

Description울산시설공단 울산대공원에 소재하는 장미원 입장객 현황 정보를 년월, 입장객, 유료, 무료 항목으로 데이터를 제공합니다.
URLhttps://www.data.go.kr/data/15089184/fileData.do

Alerts

기준일자 has constant value ""Constant
입장객 is highly overall correlated with 유료 and 1 other fieldsHigh correlation
유료 is highly overall correlated with 입장객 and 1 other fieldsHigh correlation
무료 is highly overall correlated with 입장객 and 1 other fieldsHigh correlation
년월 has unique valuesUnique
입장객 has 2 (4.3%) zerosZeros
유료 has 2 (4.3%) zerosZeros
무료 has 2 (4.3%) zerosZeros

Reproduction

Analysis started2023-12-12 08:20:13.451237
Analysis finished2023-12-12 08:20:14.958918
Duration1.51 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년월
Date

UNIQUE 

Distinct47
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size508.0 B
Minimum2019-01-01 00:00:00
Maximum2022-11-01 00:00:00
2023-12-12T17:20:15.067487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:20:15.259245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)

입장객
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct46
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21909.681
Minimum0
Maximum192657
Zeros2
Zeros (%)4.3%
Negative0
Negative (%)0.0%
Memory size555.0 B
2023-12-12T17:20:15.447107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2104.6
Q15057
median12270
Q322531.5
95-th percentile57672.1
Maximum192657
Range192657
Interquartile range (IQR)17474.5

Descriptive statistics

Standard deviation37599.31
Coefficient of variation (CV)1.7161049
Kurtosis15.764377
Mean21909.681
Median Absolute Deviation (MAD)8055
Skewness3.9004442
Sum1029755
Variance1.4137081 × 109
MonotonicityNot monotonic
2023-12-12T17:20:15.611427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
0 2
 
4.3%
28406 1
 
2.1%
12270 1
 
2.1%
20174 1
 
2.1%
62050 1
 
2.1%
24097 1
 
2.1%
4215 1
 
2.1%
5608 1
 
2.1%
16007 1
 
2.1%
20966 1
 
2.1%
Other values (36) 36
76.6%
ValueCountFrequency (%)
0 2
4.3%
2041 1
2.1%
2253 1
2.1%
2280 1
2.1%
2844 1
2.1%
2916 1
2.1%
3855 1
2.1%
3936 1
2.1%
3994 1
2.1%
4215 1
2.1%
ValueCountFrequency (%)
192657 1
2.1%
183120 1
2.1%
62050 1
2.1%
47457 1
2.1%
32719 1
2.1%
31638 1
2.1%
31546 1
2.1%
29720 1
2.1%
29488 1
2.1%
28406 1
2.1%

유료
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct46
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17490.851
Minimum0
Maximum154363
Zeros2
Zeros (%)4.3%
Negative0
Negative (%)0.0%
Memory size555.0 B
2023-12-12T17:20:15.782591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1697.4
Q14012.5
median10125
Q318093.5
95-th percentile45878.1
Maximum154363
Range154363
Interquartile range (IQR)14081

Descriptive statistics

Standard deviation29619.979
Coefficient of variation (CV)1.6934556
Kurtosis15.731675
Mean17490.851
Median Absolute Deviation (MAD)6707
Skewness3.8852297
Sum822070
Variance8.7734318 × 108
MonotonicityNot monotonic
2023-12-12T17:20:15.956249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
0 2
 
4.3%
24868 1
 
2.1%
9754 1
 
2.1%
14916 1
 
2.1%
49485 1
 
2.1%
18927 1
 
2.1%
3418 1
 
2.1%
4529 1
 
2.1%
12824 1
 
2.1%
17260 1
 
2.1%
Other values (36) 36
76.6%
ValueCountFrequency (%)
0 2
4.3%
1611 1
2.1%
1899 1
2.1%
1901 1
2.1%
2238 1
2.1%
2424 1
2.1%
3293 1
2.1%
3325 1
2.1%
3361 1
2.1%
3418 1
2.1%
ValueCountFrequency (%)
154363 1
2.1%
141362 1
2.1%
49485 1
2.1%
37462 1
2.1%
26752 1
2.1%
25005 1
2.1%
24868 1
2.1%
24436 1
2.1%
24198 1
2.1%
23854 1
2.1%

무료
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct46
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4418.8298
Minimum0
Maximum41758
Zeros2
Zeros (%)4.3%
Negative0
Negative (%)0.0%
Memory size555.0 B
2023-12-12T17:20:16.486718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile360.7
Q11009.5
median2516
Q34029.5
95-th percentile11794
Maximum41758
Range41758
Interquartile range (IQR)3020

Descriptive statistics

Standard deviation8034.8398
Coefficient of variation (CV)1.8183185
Kurtosis16.228762
Mean4418.8298
Median Absolute Deviation (MAD)1516
Skewness3.9677948
Sum207685
Variance64558650
MonotonicityNot monotonic
2023-12-12T17:20:16.718405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
0 2
 
4.3%
3538 1
 
2.1%
2516 1
 
2.1%
5258 1
 
2.1%
12565 1
 
2.1%
5170 1
 
2.1%
797 1
 
2.1%
1079 1
 
2.1%
3183 1
 
2.1%
3706 1
 
2.1%
Other values (36) 36
76.6%
ValueCountFrequency (%)
0 2
4.3%
352 1
2.1%
381 1
2.1%
430 1
2.1%
492 1
2.1%
530 1
2.1%
575 1
2.1%
606 1
2.1%
701 1
2.1%
797 1
2.1%
ValueCountFrequency (%)
41758 1
2.1%
38294 1
2.1%
12565 1
2.1%
9995 1
2.1%
7714 1
2.1%
7692 1
2.1%
5522 1
2.1%
5258 1
2.1%
5170 1
2.1%
5052 1
2.1%

기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size508.0 B
2023-07-17
47 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-07-17
2nd row2023-07-17
3rd row2023-07-17
4th row2023-07-17
5th row2023-07-17

Common Values

ValueCountFrequency (%)
2023-07-17 47
100.0%

Length

2023-12-12T17:20:16.880405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:20:16.987556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-07-17 47
100.0%

Interactions

2023-12-12T17:20:14.382505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:20:13.575348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:20:13.970086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:20:14.512888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:20:13.720688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:20:14.112075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:20:14.637811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:20:13.861729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:20:14.242110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:20:17.062302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년월입장객유료무료
년월1.0001.0001.0001.000
입장객1.0001.0001.0000.999
유료1.0001.0001.0000.998
무료1.0000.9990.9981.000
2023-12-12T17:20:17.174232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
입장객유료무료
입장객1.0000.9980.985
유료0.9981.0000.978
무료0.9850.9781.000

Missing values

2023-12-12T17:20:14.777719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:20:14.907784image/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

년월입장객유료무료기준일자
02019-01284062486835382023-07-17
12019-026394522411702023-07-17
22019-03162971359727002023-07-17
32019-04294882443650522023-07-17
42019-05192657154363382942023-07-17
52019-06297202419855222023-07-17
62019-074976395710192023-07-17
72019-085138406810702023-07-17
82019-0910365852118442023-07-17
92019-10316382675248862023-07-17
년월입장객유료무료기준일자
372022-027871654713242023-07-17
382022-03149361230326332023-07-17
392022-04327192500577142023-07-17
402022-05183120141362417582023-07-17
412022-06315462385476922023-07-17
422022-07399432937012023-07-17
432022-085554455410002023-07-17
442022-09130941073623582023-07-17
452022-10252542119440602023-07-17
462022-11141681088632822023-07-17