Overview

Dataset statistics

Number of variables9
Number of observations63
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.7 KiB
Average record size in memory77.0 B

Variable types

Numeric3
Categorical6

Dataset

Description부산광역시 7개 해수욕장(송도, 해운대, 송정, 광안리, 다대포, 일광, 임랑)의 규모, 방문객 현황, 개장일 및 폐장일 항목을 제공합니다.
Author부산광역시
URLhttps://www.data.go.kr/data/15043252/fileData.do

Alerts

시도 has constant value ""Constant
구군 is highly overall correlated with 규모(제곱미터) and 2 other fieldsHigh correlation
해수욕장명 is highly overall correlated with 규모(제곱미터) and 2 other fieldsHigh correlation
비고 is highly overall correlated with 연도별 and 1 other fieldsHigh correlation
폐장일 is highly overall correlated with 연도별 and 2 other fieldsHigh correlation
연도별 is highly overall correlated with 폐장일 and 1 other fieldsHigh correlation
규모(제곱미터) is highly overall correlated with 방문자수(천명) and 2 other fieldsHigh correlation
방문자수(천명) is highly overall correlated with 규모(제곱미터) and 1 other fieldsHigh correlation
개장일 is highly overall correlated with 구군 and 1 other fieldsHigh correlation
비고 is highly imbalanced (50.6%)Imbalance
방문자수(천명) has unique valuesUnique

Reproduction

Analysis started2024-03-14 15:03:56.069592
Analysis finished2024-03-14 15:03:58.800306
Duration2.73 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도별
Real number (ℝ)

HIGH CORRELATION 

Distinct9
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2019
Minimum2015
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size695.0 B
2024-03-15T00:03:58.886806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2015
5-th percentile2015
Q12017
median2019
Q32021
95-th percentile2023
Maximum2023
Range8
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.6027281
Coefficient of variation (CV)0.0012891174
Kurtosis-1.2318689
Mean2019
Median Absolute Deviation (MAD)2
Skewness0
Sum127197
Variance6.7741935
MonotonicityIncreasing
2024-03-15T00:03:59.093893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
2015 7
11.1%
2016 7
11.1%
2017 7
11.1%
2018 7
11.1%
2019 7
11.1%
2020 7
11.1%
2021 7
11.1%
2022 7
11.1%
2023 7
11.1%
ValueCountFrequency (%)
2015 7
11.1%
2016 7
11.1%
2017 7
11.1%
2018 7
11.1%
2019 7
11.1%
2020 7
11.1%
2021 7
11.1%
2022 7
11.1%
2023 7
11.1%
ValueCountFrequency (%)
2023 7
11.1%
2022 7
11.1%
2021 7
11.1%
2020 7
11.1%
2019 7
11.1%
2018 7
11.1%
2017 7
11.1%
2016 7
11.1%
2015 7
11.1%

시도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size632.0 B
부산광역시
63 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row부산광역시
2nd row부산광역시
3rd row부산광역시
4th row부산광역시
5th row부산광역시

Common Values

ValueCountFrequency (%)
부산광역시 63
100.0%

Length

2024-03-15T00:03:59.323640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T00:03:59.552116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 63
100.0%

구군
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size632.0 B
기장군
18 
서구
9 
해운대구
9 
해운대구
9 
수영구
9 

Length

Max length5
Median length4
Mean length3.4285714
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서구
2nd row해운대구
3rd row해운대구
4th row수영구
5th row사하구

Common Values

ValueCountFrequency (%)
기장군 18
28.6%
서구 9
14.3%
해운대구 9
14.3%
해운대구 9
14.3%
수영구 9
14.3%
사하구 9
14.3%

Length

2024-03-15T00:03:59.759611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T00:03:59.964091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기장군 18
28.6%
해운대구 18
28.6%
서구 9
14.3%
수영구 9
14.3%
사하구 9
14.3%

해수욕장명
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size632.0 B
송도해수욕장
9 
해운대해수욕장
9 
송정해수욕장
9 
광안리해수욕장
9 
다대포해수욕장
9 
Other values (2)
18 

Length

Max length7
Median length7
Mean length6.5714286
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row송도해수욕장
2nd row해운대해수욕장
3rd row송정해수욕장
4th row광안리해수욕장
5th row다대포해수욕장

Common Values

ValueCountFrequency (%)
송도해수욕장 9
14.3%
해운대해수욕장 9
14.3%
송정해수욕장 9
14.3%
광안리해수욕장 9
14.3%
다대포해수욕장 9
14.3%
일광해수욕장 9
14.3%
임랑해수욕장 9
14.3%

Length

2024-03-15T00:04:00.206121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T00:04:00.414670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
송도해수욕장 9
14.3%
해운대해수욕장 9
14.3%
송정해수욕장 9
14.3%
광안리해수욕장 9
14.3%
다대포해수욕장 9
14.3%
일광해수욕장 9
14.3%
임랑해수욕장 9
14.3%

규모(제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct9
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean67351.587
Minimum10650
Maximum128000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size695.0 B
2024-03-15T00:04:00.621741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10650
5-th percentile10650
Q148000
median54000
Q3120000
95-th percentile128000
Maximum128000
Range117350
Interquartile range (IQR)72000

Descriptive statistics

Standard deviation42051.9
Coefficient of variation (CV)0.6243639
Kurtosis-1.3075034
Mean67351.587
Median Absolute Deviation (MAD)38250
Skewness0.21923201
Sum4243150
Variance1.7683623 × 109
MonotonicityNot monotonic
2024-03-15T00:04:00.893872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
48000 12
19.0%
128000 9
14.3%
15750 9
14.3%
120000 8
12.7%
54000 8
12.7%
82000 7
11.1%
10650 6
9.5%
72000 3
 
4.8%
127500 1
 
1.6%
ValueCountFrequency (%)
10650 6
9.5%
15750 9
14.3%
48000 12
19.0%
54000 8
12.7%
72000 3
 
4.8%
82000 7
11.1%
120000 8
12.7%
127500 1
 
1.6%
128000 9
14.3%
ValueCountFrequency (%)
128000 9
14.3%
127500 1
 
1.6%
120000 8
12.7%
82000 7
11.1%
72000 3
 
4.8%
54000 8
12.7%
48000 12
19.0%
15750 9
14.3%
10650 6
9.5%

방문자수(천명)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4496.4805
Minimum29
Maximum16085
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size695.0 B
2024-03-15T00:04:01.113251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum29
5-th percentile78.7
Q1297.75
median3635
Q37425
95-th percentile13010
Maximum16085
Range16056
Interquartile range (IQR)7127.25

Descriptive statistics

Standard deviation4453.0028
Coefficient of variation (CV)0.99033072
Kurtosis-0.3174658
Mean4496.4805
Median Absolute Deviation (MAD)3357
Skewness0.85528632
Sum283278.27
Variance19829234
MonotonicityNot monotonic
2024-03-15T00:04:01.375740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7530.0 1
 
1.6%
16085.0 1
 
1.6%
195.0 1
 
1.6%
1820.0 1
 
1.6%
6893.0 1
 
1.6%
1580.0 1
 
1.6%
2760.0 1
 
1.6%
1397.0 1
 
1.6%
151.0 1
 
1.6%
139.0 1
 
1.6%
Other values (53) 53
84.1%
ValueCountFrequency (%)
29.0 1
1.6%
45.0 1
1.6%
46.0 1
1.6%
72.0 1
1.6%
139.0 1
1.6%
143.0 1
1.6%
151.0 1
1.6%
195.0 1
1.6%
196.1 1
1.6%
209.0 1
1.6%
ValueCountFrequency (%)
16085.0 1
1.6%
14587.0 1
1.6%
13709.0 1
1.6%
13108.0 1
1.6%
12128.0 1
1.6%
11956.0 1
1.6%
11260.0 1
1.6%
11202.0 1
1.6%
10551.0 1
1.6%
9480.0 1
1.6%

개장일
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size632.0 B
07월 01일
40 
06월 01일
21 
06월 02일
 
2

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row06월 01일
2nd row06월 01일
3rd row06월 01일
4th row07월 01일
5th row07월 01일

Common Values

ValueCountFrequency (%)
07월 01일 40
63.5%
06월 01일 21
33.3%
06월 02일 2
 
3.2%

Length

2024-03-15T00:04:01.615661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T00:04:01.790649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
01일 61
48.4%
07월 40
31.7%
06월 23
 
18.3%
02일 2
 
1.6%

폐장일
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size632.0 B
08월 31일
53 
09월 10일
10 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row09월 10일
2nd row09월 10일
3rd row09월 10일
4th row09월 10일
5th row08월 31일

Common Values

ValueCountFrequency (%)
08월 31일 53
84.1%
09월 10일 10
 
15.9%

Length

2024-03-15T00:04:02.066708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T00:04:02.236706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
08월 53
42.1%
31일 53
42.1%
09월 10
 
7.9%
10일 10
 
7.9%

비고
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct7
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size632.0 B
<NA>
46 
08-21 대여시설 조기철거
7 
08-10 대여시설 조기철거
6 
야간개장 07-25 ~ 08-08
 
1
야간개장 07-27 ~ 08-12
 
1
Other values (2)
 
2

Length

Max length18
Median length4
Mean length7.1111111
Min length4

Unique

Unique4 ?
Unique (%)6.3%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 46
73.0%
08-21 대여시설 조기철거 7
 
11.1%
08-10 대여시설 조기철거 6
 
9.5%
야간개장 07-25 ~ 08-08 1
 
1.6%
야간개장 07-27 ~ 08-12 1
 
1.6%
야간개장 07-26 ~ 08-11 1
 
1.6%
08-09 대여시설 조기철거 1
 
1.6%

Length

2024-03-15T00:04:02.430998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T00:04:02.638005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 46
46.0%
대여시설 14
 
14.0%
조기철거 14
 
14.0%
08-21 7
 
7.0%
08-10 6
 
6.0%
야간개장 3
 
3.0%
3
 
3.0%
07-25 1
 
1.0%
08-08 1
 
1.0%
07-27 1
 
1.0%
Other values (4) 4
 
4.0%

Interactions

2024-03-15T00:03:57.825637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:03:56.577128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:03:57.337572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:03:58.002736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:03:56.849243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:03:57.502152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:03:58.157276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:03:57.114271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:03:57.645386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T00:04:02.822707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도별구군해수욕장명규모(제곱미터)방문자수(천명)개장일폐장일비고
연도별1.0000.0000.0000.0000.0000.2960.7471.000
구군0.0001.0001.0000.8610.7150.8990.3970.000
해수욕장명0.0001.0001.0000.8940.6540.6970.2400.000
규모(제곱미터)0.0000.8610.8941.0000.7060.3560.1640.000
방문자수(천명)0.0000.7150.6540.7061.0000.5260.7950.867
개장일0.2960.8990.6970.3560.5261.0000.1790.310
폐장일0.7470.3970.2400.1640.7950.1791.000NaN
비고1.0000.0000.0000.0000.8670.310NaN1.000
2024-03-15T00:04:03.049504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구군해수욕장명개장일비고폐장일
구군1.0000.9910.6030.0000.274
해수욕장명0.9911.0000.5890.0000.243
개장일0.6030.5891.0000.1340.291
비고0.0000.0000.1341.0001.000
폐장일0.2740.2430.2911.0001.000
2024-03-15T00:04:03.285144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도별규모(제곱미터)방문자수(천명)구군해수욕장명개장일폐장일비고
연도별1.0000.040-0.3790.0000.0000.1730.5460.957
규모(제곱미터)0.0401.0000.6320.7850.7840.3290.2490.000
방문자수(천명)-0.3790.6321.0000.4610.3920.3460.5850.476
구군0.0000.7850.4611.0000.9910.6030.2740.000
해수욕장명0.0000.7840.3920.9911.0000.5890.2430.000
개장일0.1730.3290.3460.6030.5891.0000.2910.134
폐장일0.5460.2490.5850.2740.2430.2911.0001.000
비고0.9570.0000.4760.0000.0000.1341.0001.000

Missing values

2024-03-15T00:03:58.469347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T00:03:58.708666image/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

연도별시도구군해수욕장명규모(제곱미터)방문자수(천명)개장일폐장일비고
02015부산광역시서구송도해수욕장480007530.006월 01일09월 10일<NA>
12015부산광역시해운대구해운대해수욕장12750016085.006월 01일09월 10일<NA>
22015부산광역시해운대구송정해수욕장720004702.006월 01일09월 10일<NA>
32015부산광역시수영구광안리해수욕장8200013108.007월 01일09월 10일<NA>
42015부산광역시사하구다대포해수욕장1280004332.307월 01일08월 31일<NA>
52015부산광역시기장군일광해수욕장15750249.207월 01일08월 31일<NA>
62015부산광역시기장군임랑해수욕장10650196.107월 01일08월 31일<NA>
72016부산광역시서구송도해수욕장480009480.006월 01일09월 10일<NA>
82016부산광역시해운대구해운대해수욕장12000014587.006월 01일09월 10일<NA>
92016부산광역시해운대구송정해수욕장540004467.006월 01일09월 10일<NA>
연도별시도구군해수욕장명규모(제곱미터)방문자수(천명)개장일폐장일비고
532022부산광역시사하구다대포해수욕장1280002001.007월 01일08월 31일<NA>
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572023부산광역시해운대구해운대해수욕장1200008219.006월 01일08월 31일<NA>
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622023부산광역시기장군임랑해수욕장4800029.007월 01일08월 31일<NA>