Overview

Dataset statistics

Number of variables6
Number of observations730
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory35.8 KiB
Average record size in memory50.2 B

Variable types

DateTime1
Numeric2
Categorical3

Dataset

Description경기도 화성시서신면제부리위치한 제부도를 방문한 2021년 ,2022년 기준이용관광객 현황을 나타내는 데이터 입니다
Author화성도시공사
URLhttps://www.data.go.kr/data/15096681/fileData.do

Alerts

관리자 연락처 has constant value ""Constant
데이터기준일자 has constant value ""Constant
입차대수 is highly overall correlated with 이용객High correlation
이용객 is highly overall correlated with 입차대수High correlation
일자 has unique valuesUnique

Reproduction

Analysis started2023-12-12 04:24:58.637280
Analysis finished2023-12-12 04:24:59.377946
Duration0.74 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일자
Date

UNIQUE 

Distinct730
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
Minimum2021-01-01 00:00:00
Maximum2022-12-31 00:00:00
2023-12-12T13:24:59.444485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:24:59.582712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

입차대수
Real number (ℝ)

HIGH CORRELATION 

Distinct618
Distinct (%)84.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2435.6274
Minimum680
Maximum8337
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.5 KiB
2023-12-12T13:24:59.725929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum680
5-th percentile1061
Q11432.5
median1762.5
Q33400.75
95-th percentile5352.9
Maximum8337
Range7657
Interquartile range (IQR)1968.25

Descriptive statistics

Standard deviation1456.0946
Coefficient of variation (CV)0.59783144
Kurtosis0.77581978
Mean2435.6274
Median Absolute Deviation (MAD)491
Skewness1.2648204
Sum1778008
Variance2120211.6
MonotonicityNot monotonic
2023-12-12T13:24:59.927993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1439 4
 
0.5%
1475 4
 
0.5%
1538 4
 
0.5%
1247 3
 
0.4%
1376 3
 
0.4%
2549 3
 
0.4%
1991 3
 
0.4%
1950 3
 
0.4%
1440 3
 
0.4%
1174 3
 
0.4%
Other values (608) 697
95.5%
ValueCountFrequency (%)
680 1
0.1%
688 1
0.1%
755 1
0.1%
759 1
0.1%
801 1
0.1%
899 1
0.1%
915 1
0.1%
920 1
0.1%
930 1
0.1%
931 1
0.1%
ValueCountFrequency (%)
8337 2
0.3%
7184 1
0.1%
7085 1
0.1%
7017 1
0.1%
7007 1
0.1%
6808 1
0.1%
6747 1
0.1%
6401 2
0.3%
6328 1
0.1%
6240 1
0.1%

이용객
Real number (ℝ)

HIGH CORRELATION 

Distinct618
Distinct (%)84.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6089.3164
Minimum1700
Maximum20843
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.5 KiB
2023-12-12T13:25:00.111199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1700
5-th percentile2653
Q13581.25
median4406.5
Q38502.25
95-th percentile13382.25
Maximum20843
Range19143
Interquartile range (IQR)4921

Descriptive statistics

Standard deviation3640.2508
Coefficient of variation (CV)0.59780943
Kurtosis0.77584314
Mean6089.3164
Median Absolute Deviation (MAD)1227.5
Skewness1.2648239
Sum4445201
Variance13251426
MonotonicityNot monotonic
2023-12-12T13:25:00.278253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3598 4
 
0.5%
3688 4
 
0.5%
3845 4
 
0.5%
3118 3
 
0.4%
3440 3
 
0.4%
6373 3
 
0.4%
4978 3
 
0.4%
4875 3
 
0.4%
3600 3
 
0.4%
2935 3
 
0.4%
Other values (608) 697
95.5%
ValueCountFrequency (%)
1700 1
0.1%
1720 1
0.1%
1888 1
0.1%
1898 1
0.1%
2003 1
0.1%
2248 1
0.1%
2288 1
0.1%
2300 1
0.1%
2325 1
0.1%
2328 1
0.1%
ValueCountFrequency (%)
20843 2
0.3%
17960 1
0.1%
17713 1
0.1%
17543 1
0.1%
17518 1
0.1%
17020 1
0.1%
16868 1
0.1%
16003 2
0.3%
15820 1
0.1%
15600 1
0.1%

관리기관
Categorical

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
제부도관리팀
545 
제부도관리부
184 
제부도관리부
 
1

Length

Max length8
Median length6
Mean length6.5041096
Min length6

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row제부도관리부
2nd row제부도관리팀
3rd row제부도관리팀
4th row제부도관리팀
5th row제부도관리팀

Common Values

ValueCountFrequency (%)
제부도관리팀 545
74.7%
제부도관리부 184
 
25.2%
제부도관리부 1
 
0.1%

Length

2023-12-12T13:25:00.458149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:25:00.586337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제부도관리팀 545
74.7%
제부도관리부 185
 
25.3%

관리자 연락처
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
031-355-3624
730 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row031-355-3624
2nd row031-355-3624
3rd row031-355-3624
4th row031-355-3624
5th row031-355-3624

Common Values

ValueCountFrequency (%)
031-355-3624 730
100.0%

Length

2023-12-12T13:25:00.722184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:25:00.852855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
031-355-3624 730
100.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
2022-12-31
730 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-12-31
2nd row2022-12-31
3rd row2022-12-31
4th row2022-12-31
5th row2022-12-31

Common Values

ValueCountFrequency (%)
2022-12-31 730
100.0%

Length

2023-12-12T13:25:00.970891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:25:01.073896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-12-31 730
100.0%

Interactions

2023-12-12T13:24:59.000911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:24:58.758167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:24:59.116519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:24:58.871180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:25:01.158953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
입차대수이용객관리기관
입차대수1.0001.0000.458
이용객1.0001.0000.458
관리기관0.4580.4581.000
2023-12-12T13:25:01.269835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
입차대수이용객관리기관
입차대수1.0001.0000.309
이용객1.0001.0000.309
관리기관0.3090.3091.000

Missing values

2023-12-12T13:24:59.226942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:24:59.333038image/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

일자입차대수이용객관리기관관리자 연락처데이터기준일자
02021-01-01680817020제부도관리부031-355-36242022-12-31
12021-01-02564514113제부도관리팀031-355-36242022-12-31
22021-01-0331097773제부도관리팀031-355-36242022-12-31
32021-01-0414873718제부도관리팀031-355-36242022-12-31
42021-01-0515373843제부도관리팀031-355-36242022-12-31
52021-01-0617624405제부도관리팀031-355-36242022-12-31
62021-01-0716674168제부도관리팀031-355-36242022-12-31
72021-01-0819244810제부도관리팀031-355-36242022-12-31
82021-01-0930547635제부도관리팀031-355-36242022-12-31
92021-01-1029847460제부도관리팀031-355-36242022-12-31
일자입차대수이용객관리기관관리자 연락처데이터기준일자
7202022-12-227551888제부도관리부031-355-36242022-12-31
7212022-12-2310442610제부도관리부031-355-36242022-12-31
7222022-12-2424586145제부도관리부031-355-36242022-12-31
7232022-12-2524616153제부도관리부031-355-36242022-12-31
7242022-12-2611312828제부도관리부031-355-36242022-12-31
7252022-12-2712303075제부도관리부031-355-36242022-12-31
7262022-12-2813613403제부도관리부031-355-36242022-12-31
7272022-12-2914513628제부도관리부031-355-36242022-12-31
7282022-12-3021005250제부도관리부031-355-36242022-12-31
7292022-12-31542913573제부도관리부031-355-36242022-12-31