Overview

Dataset statistics

Number of variables9
Number of observations29
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 KiB
Average record size in memory84.6 B

Variable types

Text1
Numeric4
Categorical4

Dataset

Description인천 광역시 내 해수욕장 총 면적, 백사장 면적 등에 대한 정보와 이용, 부대시설에 대한 해수욕장별 통계 정보입니다 . * 항목명 : 백사장면적(제곱미터) 백사장길이(미터) 탈의장 (개소) 샤워장 (개소) 화장실 (개소) 망루대 (개소) 공동수도 (개소) 이용객수 (명)
URLhttps://www.data.go.kr/data/15066567/fileData.do

Alerts

백사장면적 (제곱미터) is highly overall correlated with 백사장길이 (미터)High correlation
백사장길이 (미터) is highly overall correlated with 백사장면적 (제곱미터)High correlation
화장실 (개소) is highly overall correlated with 이용객수 (명)High correlation
이용객수 (명) is highly overall correlated with 화장실 (개소) and 1 other fieldsHigh correlation
탈의장 (개소) is highly overall correlated with 이용객수 (명)High correlation
샤워장 (개소) is highly imbalanced (53.7%)Imbalance
망루대 (개소) is highly imbalanced (63.8%)Imbalance
해수욕장별 has unique valuesUnique
이용객수 (명) has unique valuesUnique
백사장길이 (미터) has 1 (3.4%) zerosZeros
화장실 (개소) has 1 (3.4%) zerosZeros

Reproduction

Analysis started2023-12-12 15:21:03.111796
Analysis finished2023-12-12 15:21:05.133278
Duration2.02 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

해수욕장별
Text

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
2023-12-13T00:21:05.290367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length15
Mean length14.827586
Min length10

Characters and Unicode

Total characters430
Distinct characters88
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)100.0%

Sample

1st row왕산(중구 을왕동)
2nd row을왕(중구 을왕동)
3rd row실미(중구 무의동)
4th row하나개(중구 무의동)
5th row동막(강화군 화도면 동막리)
ValueCountFrequency (%)
자월면 7
 
8.4%
덕적면 5
 
6.0%
이작리 4
 
4.8%
북도면 4
 
4.8%
장봉리 3
 
3.6%
대청면 3
 
3.6%
대청리 2
 
2.4%
자월리 2
 
2.4%
을왕동 2
 
2.4%
무의동 2
 
2.4%
Other values (47) 49
59.0%
2023-12-13T00:21:05.666690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
54
 
12.6%
) 30
 
7.0%
( 30
 
7.0%
리 30
 
7.0%
진 26
 
6.0%
군 25
 
5.8%
면 25
 
5.8%
옹 24
 
5.6%
동 9
 
2.1%
월 9
 
2.1%
Other values (78) 168
39.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 316
73.5%
Space Separator 54
 
12.6%
Close Punctuation 30
 
7.0%
Open Punctuation 30
 
7.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 30
 
9.5%
진 26
 
8.2%
군 25
 
7.9%
면 25
 
7.9%
옹 24
 
7.6%
동 9
 
2.8%
월 9
 
2.8%
자 9
 
2.8%
청 7
 
2.2%
도 6
 
1.9%
Other values (75) 146
46.2%
Space Separator
ValueCountFrequency (%)
54
100.0%
Close Punctuation
ValueCountFrequency (%)
) 30
100.0%
Open Punctuation
ValueCountFrequency (%)
( 30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 316
73.5%
Common 114
 
26.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 30
 
9.5%
진 26
 
8.2%
군 25
 
7.9%
면 25
 
7.9%
옹 24
 
7.6%
동 9
 
2.8%
월 9
 
2.8%
자 9
 
2.8%
청 7
 
2.2%
도 6
 
1.9%
Other values (75) 146
46.2%
Common
ValueCountFrequency (%)
54
47.4%
) 30
26.3%
( 30
26.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 316
73.5%
ASCII 114
 
26.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
54
47.4%
) 30
26.3%
( 30
26.3%
Hangul
ValueCountFrequency (%)
리 30
 
9.5%
진 26
 
8.2%
군 25
 
7.9%
면 25
 
7.9%
옹 24
 
7.6%
동 9
 
2.8%
월 9
 
2.8%
자 9
 
2.8%
청 7
 
2.2%
도 6
 
1.9%
Other values (75) 146
46.2%

백사장면적 (제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)82.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean91981.897
Minimum7500
Maximum600000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-13T00:21:05.808214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7500
5-th percentile10800
Q127825
median45500
Q3100000
95-th percentile286800
Maximum600000
Range592500
Interquartile range (IQR)72175

Descriptive statistics

Standard deviation123189.65
Coefficient of variation (CV)1.3392815
Kurtosis10.090906
Mean91981.897
Median Absolute Deviation (MAD)30500
Skewness2.919222
Sum2667475
Variance1.5175691 × 1010
MonotonicityNot monotonic
2023-12-13T00:21:05.957279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
33000 4
 
13.8%
30000 2
 
6.9%
100000 2
 
6.9%
27825 1
 
3.4%
10000 1
 
3.4%
20000 1
 
3.4%
49000 1
 
3.4%
168000 1
 
3.4%
134000 1
 
3.4%
25000 1
 
3.4%
Other values (14) 14
48.3%
ValueCountFrequency (%)
7500 1
 
3.4%
10000 1
 
3.4%
12000 1
 
3.4%
15000 1
 
3.4%
20000 1
 
3.4%
24000 1
 
3.4%
25000 1
 
3.4%
27825 1
 
3.4%
30000 2
6.9%
33000 4
13.8%
ValueCountFrequency (%)
600000 1
3.4%
300000 1
3.4%
267000 1
3.4%
200000 1
3.4%
168000 1
3.4%
134000 1
3.4%
100000 2
6.9%
99000 1
3.4%
89000 1
3.4%
78000 1
3.4%

백사장길이 (미터)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct28
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean603.37931
Minimum0
Maximum1679
Zeros1
Zeros (%)3.4%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-13T00:21:06.108560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile95.8
Q1354
median585
Q3709
95-th percentile1186.6
Maximum1679
Range1679
Interquartile range (IQR)355

Descriptive statistics

Standard deviation359.37122
Coefficient of variation (CV)0.59559752
Kurtosis1.8205763
Mean603.37931
Median Absolute Deviation (MAD)209
Skewness0.94110357
Sum17498
Variance129147.67
MonotonicityNot monotonic
2023-12-13T00:21:06.253078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
585 2
 
6.9%
795 1
 
3.4%
709 1
 
3.4%
238 1
 
3.4%
262 1
 
3.4%
794 1
 
3.4%
272 1
 
3.4%
352 1
 
3.4%
663 1
 
3.4%
636 1
 
3.4%
Other values (18) 18
62.1%
ValueCountFrequency (%)
0 1
3.4%
1 1
3.4%
238 1
3.4%
262 1
3.4%
272 1
3.4%
326 1
3.4%
352 1
3.4%
354 1
3.4%
415 1
3.4%
454 1
3.4%
ValueCountFrequency (%)
1679 1
3.4%
1261 1
3.4%
1075 1
3.4%
1000 1
3.4%
988 1
3.4%
795 1
3.4%
794 1
3.4%
709 1
3.4%
705 1
3.4%
693 1
3.4%

탈의장 (개소)
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size364.0 B
0
23 
1
6 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
0 23
79.3%
1 6
 
20.7%

Length

2023-12-13T00:21:06.407705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:21:06.528842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 23
79.3%
1 6
 
20.7%

샤워장 (개소)
Categorical

IMBALANCE 

Distinct4
Distinct (%)13.8%
Missing0
Missing (%)0.0%
Memory size364.0 B
1
24 
3
 
2
0
 
2
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)3.4%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 24
82.8%
3 2
 
6.9%
0 2
 
6.9%
2 1
 
3.4%

Length

2023-12-13T00:21:06.650583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:21:06.769860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 24
82.8%
3 2
 
6.9%
0 2
 
6.9%
2 1
 
3.4%

화장실 (개소)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct6
Distinct (%)20.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7931034
Minimum0
Maximum6
Zeros1
Zeros (%)3.4%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-13T00:21:06.890147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q32
95-th percentile4.6
Maximum6
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.4971237
Coefficient of variation (CV)0.83493436
Kurtosis1.3342711
Mean1.7931034
Median Absolute Deviation (MAD)0
Skewness1.5456582
Sum52
Variance2.2413793
MonotonicityNot monotonic
2023-12-13T00:21:07.002068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 19
65.5%
4 4
 
13.8%
2 3
 
10.3%
5 1
 
3.4%
6 1
 
3.4%
0 1
 
3.4%
ValueCountFrequency (%)
0 1
 
3.4%
1 19
65.5%
2 3
 
10.3%
4 4
 
13.8%
5 1
 
3.4%
6 1
 
3.4%
ValueCountFrequency (%)
6 1
 
3.4%
5 1
 
3.4%
4 4
 
13.8%
2 3
 
10.3%
1 19
65.5%
0 1
 
3.4%

망루대 (개소)
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size364.0 B
1
27 
0
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 27
93.1%
0 2
 
6.9%

Length

2023-12-13T00:21:07.133667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:21:07.254673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 27
93.1%
0 2
 
6.9%

공동수도 (개소)
Categorical

Distinct5
Distinct (%)17.2%
Missing0
Missing (%)0.0%
Memory size364.0 B
1
15 
2
6 
4
4 
0
3 
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)3.4%

Sample

1st row1
2nd row4
3rd row2
4th row4
5th row2

Common Values

ValueCountFrequency (%)
1 15
51.7%
2 6
 
20.7%
4 4
 
13.8%
0 3
 
10.3%
3 1
 
3.4%

Length

2023-12-13T00:21:07.344623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:21:07.449990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 15
51.7%
2 6
 
20.7%
4 4
 
13.8%
0 3
 
10.3%
3 1
 
3.4%

이용객수 (명)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28070.586
Minimum40
Maximum255160
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-13T00:21:07.559686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum40
5-th percentile144.8
Q1663
median1878
Q335235
95-th percentile116581.8
Maximum255160
Range255120
Interquartile range (IQR)34572

Descriptive statistics

Standard deviation56267.878
Coefficient of variation (CV)2.0045138
Kurtosis9.0434927
Mean28070.586
Median Absolute Deviation (MAD)1352
Skewness2.797323
Sum814047
Variance3.1660741 × 109
MonotonicityNot monotonic
2023-12-13T00:21:07.692791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
64480 1
 
3.4%
120151 1
 
3.4%
870 1
 
3.4%
544 1
 
3.4%
425 1
 
3.4%
230 1
 
3.4%
251 1
 
3.4%
1203 1
 
3.4%
40 1
 
3.4%
553 1
 
3.4%
Other values (19) 19
65.5%
ValueCountFrequency (%)
40 1
3.4%
88 1
3.4%
230 1
3.4%
251 1
3.4%
425 1
3.4%
544 1
3.4%
553 1
3.4%
663 1
3.4%
750 1
3.4%
870 1
3.4%
ValueCountFrequency (%)
255160 1
3.4%
120151 1
3.4%
111228 1
3.4%
88180 1
3.4%
66234 1
3.4%
64480 1
3.4%
44226 1
3.4%
35235 1
3.4%
4250 1
3.4%
3230 1
3.4%

Interactions

2023-12-13T00:21:04.569151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:21:03.483612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:21:03.855570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:21:04.217854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:21:04.659399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:21:03.570754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:21:03.951698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:21:04.313836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:21:04.745847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:21:03.676985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:21:04.031955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:21:04.399945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:21:04.832569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:21:03.766071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:21:04.121200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:21:04.484914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:21:07.793807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
해수욕장별백사장면적 (제곱미터)백사장길이 (미터)탈의장 (개소)샤워장 (개소)화장실 (개소)망루대 (개소)공동수도 (개소)이용객수 (명)
해수욕장별1.0001.0001.0001.0001.0001.0001.0001.0001.000
백사장면적 (제곱미터)1.0001.0000.7910.0000.6510.0000.3270.0000.000
백사장길이 (미터)1.0000.7911.0000.3640.6080.3550.0000.0000.334
탈의장 (개소)1.0000.0000.3641.0000.0000.4850.0000.4230.977
샤워장 (개소)1.0000.6510.6080.0001.0000.5920.0000.4700.000
화장실 (개소)1.0000.0000.3550.4850.5921.0000.0000.4400.825
망루대 (개소)1.0000.3270.0000.0000.0000.0001.0000.0000.000
공동수도 (개소)1.0000.0000.0000.4230.4700.4400.0001.0000.535
이용객수 (명)1.0000.0000.3340.9770.0000.8250.0000.5351.000
2023-12-13T00:21:08.310425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
탈의장 (개소)공동수도 (개소)망루대 (개소)샤워장 (개소)
탈의장 (개소)1.0000.4810.0000.000
공동수도 (개소)0.4811.0000.0000.386
망루대 (개소)0.0000.0001.0000.000
샤워장 (개소)0.0000.3860.0001.000
2023-12-13T00:21:08.434152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
백사장면적 (제곱미터)백사장길이 (미터)화장실 (개소)이용객수 (명)탈의장 (개소)샤워장 (개소)망루대 (개소)공동수도 (개소)
백사장면적 (제곱미터)1.0000.6110.2090.0100.0000.4600.2180.000
백사장길이 (미터)0.6111.0000.4390.1290.2980.3800.0000.000
화장실 (개소)0.2090.4391.0000.6430.3140.3990.0000.300
이용객수 (명)0.0100.1290.6431.0000.7960.0000.0000.382
탈의장 (개소)0.0000.2980.3140.7961.0000.0000.0000.481
샤워장 (개소)0.4600.3800.3990.0000.0001.0000.0000.386
망루대 (개소)0.2180.0000.0000.0000.0000.0001.0000.000
공동수도 (개소)0.0000.0000.3000.3820.4810.3860.0001.000

Missing values

2023-12-13T00:21:04.936400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:21:05.074733image/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

해수욕장별백사장면적 (제곱미터)백사장길이 (미터)탈의장 (개소)샤워장 (개소)화장실 (개소)망루대 (개소)공동수도 (개소)이용객수 (명)
0왕산(중구 을왕동)278257951141164480
1을왕(중구 을왕동)5265058511214120151
2실미(중구 무의동)4550045511512111228
3하나개(중구 무의동)3000010001141444226
4동막(강화군 화도면 동막리)12000111112255160
5민머루(강화군 삼산면 매음리)1500001111488180
6수기(옹진군 북도면 시도리)1000001075012112240
7옹암(옹진군 북도면 장봉리)267000988016113230
8진촌(옹진군 북도면 장봉리)520005850341266234
9한들(옹진군 북도면 장봉리)780007050341335235
해수욕장별백사장면적 (제곱미터)백사장길이 (미터)탈의장 (개소)샤워장 (개소)화장실 (개소)망루대 (개소)공동수도 (개소)이용객수 (명)
19굴업(옹진군 덕적면 굴업리)3000001261011101070
20장골(옹진군 자월면 자월리)300003260001088
21큰말(옹진군 자월면 자월리)2500049200111553
22이일레(옹진군 자월면 승봉리)1340006360110140
23큰풀안(옹진군 자월면 이작리)168000663011111203
24작은풀안(옹진군 자월면 이작리)4900035201111251
25계남(옹진군 자월면 이작리)3300027201111230
26벌안(옹진군 자월면 이작리)3300079401111425
27십리포(옹진군 영흥면 내리)2000026201101544
28장경리(옹진군 영흥면 내리)3300023801112870