Overview

Dataset statistics

Number of variables9
Number of observations56
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.2 KiB
Average record size in memory77.4 B

Variable types

Numeric3
Categorical6

Dataset

Description부산광역시_해수욕장방문현황_20221231
Author부산광역시
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15043252

Alerts

시도 has constant value ""Constant
폐장일 is highly overall correlated with 연도별 and 2 other fieldsHigh correlation
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
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
방문자수(천명) has unique valuesUnique

Reproduction

Analysis started2024-03-13 13:16:13.560115
Analysis finished2024-03-13 13:16:15.259188
Duration1.7 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도별
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2018.5
Minimum2015
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size636.0 B
2024-03-13T22:16:15.310382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2015
5-th percentile2015
Q12016.75
median2018.5
Q32020.25
95-th percentile2022
Maximum2022
Range7
Interquartile range (IQR)3.5

Descriptive statistics

Standard deviation2.3120239
Coefficient of variation (CV)0.0011454168
Kurtosis-1.2408905
Mean2018.5
Median Absolute Deviation (MAD)2
Skewness0
Sum113036
Variance5.3454545
MonotonicityIncreasing
2024-03-13T22:16:15.437153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
2015 7
12.5%
2016 7
12.5%
2017 7
12.5%
2018 7
12.5%
2019 7
12.5%
2020 7
12.5%
2021 7
12.5%
2022 7
12.5%
ValueCountFrequency (%)
2015 7
12.5%
2016 7
12.5%
2017 7
12.5%
2018 7
12.5%
2019 7
12.5%
2020 7
12.5%
2021 7
12.5%
2022 7
12.5%
ValueCountFrequency (%)
2022 7
12.5%
2021 7
12.5%
2020 7
12.5%
2019 7
12.5%
2018 7
12.5%
2017 7
12.5%
2016 7
12.5%
2015 7
12.5%

시도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size580.0 B
부산광역시
56 

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 56
100.0%

Length

2024-03-13T22:16:15.573694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T22:16:15.678368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 56
100.0%

구군
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size580.0 B
기장군
16 
서구
8 
해운대구
8 
해운대구
8 
수영구
8 

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 16
28.6%
서구 8
14.3%
해운대구 8
14.3%
해운대구 8
14.3%
수영구 8
14.3%
사하구 8
14.3%

Length

2024-03-13T22:16:15.813926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T22:16:16.002433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기장군 16
28.6%
해운대구 16
28.6%
서구 8
14.3%
수영구 8
14.3%
사하구 8
14.3%

해수욕장명
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size580.0 B
송도해수욕장
8 
해운대해수욕장
8 
송정해수욕장
8 
광안리해수욕장
8 
다대포해수욕장
8 
Other values (2)
16 

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 8
14.3%
해운대해수욕장 8
14.3%
송정해수욕장 8
14.3%
광안리해수욕장 8
14.3%
다대포해수욕장 8
14.3%
일광해수욕장 8
14.3%
임랑해수욕장 8
14.3%

Length

2024-03-13T22:16:16.176601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T22:16:16.326391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
송도해수욕장 8
14.3%
해운대해수욕장 8
14.3%
송정해수욕장 8
14.3%
광안리해수욕장 8
14.3%
다대포해수욕장 8
14.3%
일광해수욕장 8
14.3%
임랑해수욕장 8
14.3%

규모(제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct9
Distinct (%)16.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean66917.857
Minimum10650
Maximum128000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size636.0 B
2024-03-13T22:16:16.443199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10650
5-th percentile10650
Q139937.5
median54000
Q3120000
95-th percentile128000
Maximum128000
Range117350
Interquartile range (IQR)80062.5

Descriptive statistics

Standard deviation42506.322
Coefficient of variation (CV)0.63520148
Kurtosis-1.3248323
Mean66917.857
Median Absolute Deviation (MAD)38250
Skewness0.21853167
Sum3747400
Variance1.8067874 × 109
MonotonicityNot monotonic
2024-03-13T22:16:16.560197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
48000 10
17.9%
128000 8
14.3%
15750 8
14.3%
120000 7
12.5%
54000 7
12.5%
82000 6
10.7%
10650 6
10.7%
72000 3
 
5.4%
127500 1
 
1.8%
ValueCountFrequency (%)
10650 6
10.7%
15750 8
14.3%
48000 10
17.9%
54000 7
12.5%
72000 3
 
5.4%
82000 6
10.7%
120000 7
12.5%
127500 1
 
1.8%
128000 8
14.3%
ValueCountFrequency (%)
128000 8
14.3%
127500 1
 
1.8%
120000 7
12.5%
82000 6
10.7%
72000 3
 
5.4%
54000 7
12.5%
48000 10
17.9%
15750 8
14.3%
10650 6
10.7%

방문자수(천명)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct56
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4738.0941
Minimum46
Maximum16085
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size636.0 B
2024-03-13T22:16:16.724672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46
5-th percentile142
Q1301.375
median4174
Q37760
95-th percentile13258.25
Maximum16085
Range16039
Interquartile range (IQR)7458.625

Descriptive statistics

Standard deviation4572.1157
Coefficient of variation (CV)0.96496937
Kurtosis-0.50898141
Mean4738.0941
Median Absolute Deviation (MAD)3876.25
Skewness0.76750497
Sum265333.27
Variance20904242
MonotonicityNot monotonic
2024-03-13T22:16:16.885995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7530.0 1
 
1.8%
11202.0 1
 
1.8%
8450.0 1
 
1.8%
5950.0 1
 
1.8%
209.0 1
 
1.8%
195.0 1
 
1.8%
1820.0 1
 
1.8%
6893.0 1
 
1.8%
1580.0 1
 
1.8%
2760.0 1
 
1.8%
Other values (46) 46
82.1%
ValueCountFrequency (%)
46.0 1
1.8%
72.0 1
1.8%
139.0 1
1.8%
143.0 1
1.8%
151.0 1
1.8%
195.0 1
1.8%
196.1 1
1.8%
209.0 1
1.8%
233.0 1
1.8%
249.2 1
1.8%
ValueCountFrequency (%)
16085.0 1
1.8%
14587.0 1
1.8%
13709.0 1
1.8%
13108.0 1
1.8%
12128.0 1
1.8%
11956.0 1
1.8%
11260.0 1
1.8%
11202.0 1
1.8%
10551.0 1
1.8%
9480.0 1
1.8%

개장일
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size580.0 B
07월 01일
35 
06월 01일
19 
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 35
62.5%
06월 01일 19
33.9%
06월 02일 2
 
3.6%

Length

2024-03-13T22:16:17.042225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T22:16:17.148607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
01일 54
48.2%
07월 35
31.2%
06월 21
 
18.8%
02일 2
 
1.8%

폐장일
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size580.0 B
08월 31일
46 
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 46
82.1%
09월 10일 10
 
17.9%

Length

2024-03-13T22:16:17.256015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T22:16:17.349131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
08월 46
41.1%
31일 46
41.1%
09월 10
 
8.9%
10일 10
 
8.9%

비고
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size580.0 B
<NA>
39 
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 length7.5
Min length4

Unique

Unique4 ?
Unique (%)7.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 39
69.6%
08-21 대여시설 조기철거 7
 
12.5%
08-10 대여시설 조기철거 6
 
10.7%
야간개장 07-25 ~ 08-08 1
 
1.8%
야간개장 07-27 ~ 08-12 1
 
1.8%
야간개장 07-26 ~ 08-11 1
 
1.8%
08-09 대여시설 조기철거 1
 
1.8%

Length

2024-03-13T22:16:17.478978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T22:16:17.607439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 39
41.9%
대여시설 14
 
15.1%
조기철거 14
 
15.1%
08-21 7
 
7.5%
08-10 6
 
6.5%
야간개장 3
 
3.2%
3
 
3.2%
07-25 1
 
1.1%
08-08 1
 
1.1%
07-27 1
 
1.1%
Other values (4) 4
 
4.3%

Interactions

2024-03-13T22:16:14.649720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:16:14.019272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:16:14.332581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:16:14.754705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:16:14.138422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:16:14.436012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:16:14.879154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:16:14.238196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:16:14.541230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T22:16:17.718997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도별구군해수욕장명규모(제곱미터)방문자수(천명)개장일폐장일비고
연도별1.0000.0000.0000.0000.0000.2930.5271.000
구군0.0001.0001.0000.8650.7290.8990.4340.000
해수욕장명0.0001.0001.0000.8910.6650.6970.2640.000
규모(제곱미터)0.0000.8650.8911.0000.7280.3740.1870.000
방문자수(천명)0.0000.7290.6650.7281.0000.5740.7820.867
개장일0.2930.8990.6970.3740.5741.0000.1880.310
폐장일0.5270.4340.2640.1870.7820.1881.000NaN
비고1.0000.0000.0000.0000.8670.310NaN1.000
2024-03-13T22:16:18.167769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
폐장일개장일구군해수욕장명비고
폐장일1.0000.3050.2980.2651.000
개장일0.3051.0000.6020.5860.134
구군0.2980.6021.0000.9900.000
해수욕장명0.2650.5860.9901.0000.000
비고1.0000.1340.0000.0001.000
2024-03-13T22:16:18.336194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도별규모(제곱미터)방문자수(천명)구군해수욕장명개장일폐장일비고
연도별1.0000.027-0.3730.0000.0000.1800.5350.957
규모(제곱미터)0.0271.0000.6480.7900.7830.3490.2820.000
방문자수(천명)-0.3730.6481.0000.4740.4000.3860.5680.476
구군0.0000.7900.4741.0000.9900.6020.2980.000
해수욕장명0.0000.7830.4000.9901.0000.5860.2650.000
개장일0.1800.3490.3860.6020.5861.0000.3050.134
폐장일0.5350.2820.5680.2980.2650.3051.0001.000
비고0.9570.0000.4760.0000.0000.1341.0001.000

Missing values

2024-03-13T22:16:15.035582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T22:16:15.197071image/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
462021부산광역시사하구다대포해수욕장1280001185.007월 01일08월 31일08-10 대여시설 조기철거
472021부산광역시기장군일광해수욕장1575072.007월 01일08월 31일08-10 대여시설 조기철거
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