Overview

Dataset statistics

Number of variables8
Number of observations42
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.9 KiB
Average record size in memory71.1 B

Variable types

Categorical4
Text1
Numeric3

Dataset

Description감포해양관광단지, 안동문화관광단지, 보문관광단지의 투자유치 물건 현황
Author경상북도관광공사
URLhttps://www.data.go.kr/data/15045130/fileData.do

Alerts

부지(㎡) is highly overall correlated with 건축(㎡)High correlation
건축(㎡) is highly overall correlated with 부지(㎡) and 1 other fieldsHigh correlation
용적 is highly overall correlated with 시설지구 and 1 other fieldsHigh correlation
관광단지명 is highly overall correlated with 층수 and 1 other fieldsHigh correlation
시설지구 is highly overall correlated with 용적High correlation
층수 is highly overall correlated with 건축(㎡) and 2 other fieldsHigh correlation
건폐 is highly overall correlated with 용적 and 2 other fieldsHigh correlation
물 건 명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 15:11:20.757270
Analysis finished2023-12-12 15:11:22.384990
Duration1.63 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관광단지명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size468.0 B
감포관광단지
34 
안동관광단지
7 
보문관광단지
 
1

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique1 ?
Unique (%)2.4%

Sample

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

Common Values

ValueCountFrequency (%)
감포관광단지 34
81.0%
안동관광단지 7
 
16.7%
보문관광단지 1
 
2.4%

Length

2023-12-13T00:11:22.443143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:11:22.542585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
감포관광단지 34
81.0%
안동관광단지 7
 
16.7%
보문관광단지 1
 
2.4%

시설지구
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size468.0 B
상가시설
16 
숙박시설
15 
휴양문화시설
4 
운동오락시설
4 
공공시설
2 

Length

Max length6
Median length4
Mean length4.3809524
Min length4

Unique

Unique1 ?
Unique (%)2.4%

Sample

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

Common Values

ValueCountFrequency (%)
상가시설 16
38.1%
숙박시설 15
35.7%
휴양문화시설 4
 
9.5%
운동오락시설 4
 
9.5%
공공시설 2
 
4.8%
휴양문화 1
 
2.4%

Length

2023-12-13T00:11:22.716346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:11:22.906061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상가시설 16
38.1%
숙박시설 15
35.7%
휴양문화시설 4
 
9.5%
운동오락시설 4
 
9.5%
공공시설 2
 
4.8%
휴양문화 1
 
2.4%

물 건 명
Text

UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size468.0 B
2023-12-13T00:11:23.186862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length5
Mean length5.952381
Min length3

Characters and Unicode

Total characters250
Distinct characters80
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)100.0%

Sample

1st row관광호텔1
2nd row관광호텔2
3rd row관광호텔3
4th row가족호텔1
5th row가족호텔2
ValueCountFrequency (%)
관광호텔1 1
 
2.2%
복합상가4 1
 
2.2%
복합상가6 1
 
2.2%
휴양콘도3 1
 
2.2%
복합상가7 1
 
2.2%
복합상가8 1
 
2.2%
복합상가9 1
 
2.2%
중심상가1 1
 
2.2%
중심상가2-1 1
 
2.2%
중심상가2-2 1
 
2.2%
Other values (35) 35
77.8%
2023-12-13T00:11:23.586634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
가 18
 
7.2%
상 16
 
6.4%
2 14
 
5.6%
복 9
 
3.6%
1 9
 
3.6%
합 9
 
3.6%
호 7
 
2.8%
텔 7
 
2.8%
수 7
 
2.8%
설 7
 
2.8%
Other values (70) 147
58.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 182
72.8%
Decimal Number 36
 
14.4%
Lowercase Letter 15
 
6.0%
Uppercase Letter 6
 
2.4%
Dash Punctuation 5
 
2.0%
Space Separator 3
 
1.2%
Close Punctuation 1
 
0.4%
Open Punctuation 1
 
0.4%
Other Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
가 18
 
9.9%
상 16
 
8.8%
복 9
 
4.9%
합 9
 
4.9%
호 7
 
3.8%
텔 7
 
3.8%
수 7
 
3.8%
설 7
 
3.8%
시 7
 
3.8%
중 6
 
3.3%
Other values (42) 89
48.9%
Decimal Number
ValueCountFrequency (%)
2 14
38.9%
1 9
25.0%
3 5
 
13.9%
5 2
 
5.6%
4 2
 
5.6%
8 1
 
2.8%
6 1
 
2.8%
7 1
 
2.8%
9 1
 
2.8%
Lowercase Letter
ValueCountFrequency (%)
a 4
26.7%
e 3
20.0%
n 2
13.3%
c 1
 
6.7%
d 1
 
6.7%
i 1
 
6.7%
f 1
 
6.7%
r 1
 
6.7%
k 1
 
6.7%
Uppercase Letter
ValueCountFrequency (%)
L 2
33.3%
A 1
16.7%
O 1
16.7%
S 1
16.7%
P 1
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 182
72.8%
Common 47
 
18.8%
Latin 21
 
8.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
가 18
 
9.9%
상 16
 
8.8%
복 9
 
4.9%
합 9
 
4.9%
호 7
 
3.8%
텔 7
 
3.8%
수 7
 
3.8%
설 7
 
3.8%
시 7
 
3.8%
중 6
 
3.3%
Other values (42) 89
48.9%
Common
ValueCountFrequency (%)
2 14
29.8%
1 9
19.1%
- 5
 
10.6%
3 5
 
10.6%
3
 
6.4%
5 2
 
4.3%
4 2
 
4.3%
8 1
 
2.1%
6 1
 
2.1%
7 1
 
2.1%
Other values (4) 4
 
8.5%
Latin
ValueCountFrequency (%)
a 4
19.0%
e 3
14.3%
n 2
9.5%
L 2
9.5%
A 1
 
4.8%
c 1
 
4.8%
O 1
 
4.8%
d 1
 
4.8%
S 1
 
4.8%
i 1
 
4.8%
Other values (4) 4
19.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 182
72.8%
ASCII 68
 
27.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
가 18
 
9.9%
상 16
 
8.8%
복 9
 
4.9%
합 9
 
4.9%
호 7
 
3.8%
텔 7
 
3.8%
수 7
 
3.8%
설 7
 
3.8%
시 7
 
3.8%
중 6
 
3.3%
Other values (42) 89
48.9%
ASCII
ValueCountFrequency (%)
2 14
20.6%
1 9
13.2%
- 5
 
7.4%
3 5
 
7.4%
a 4
 
5.9%
e 3
 
4.4%
3
 
4.4%
5 2
 
2.9%
n 2
 
2.9%
L 2
 
2.9%
Other values (18) 19
27.9%

부지(㎡)
Real number (ℝ)

HIGH CORRELATION 

Distinct40
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42855.352
Minimum2160.6
Maximum1020196
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-13T00:11:23.746676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2160.6
5-th percentile2608.955
Q13621.35
median12530
Q329970
95-th percentile67728.7
Maximum1020196
Range1018035.4
Interquartile range (IQR)26348.65

Descriptive statistics

Standard deviation155733.53
Coefficient of variation (CV)3.6339342
Kurtosis40.568929
Mean42855.352
Median Absolute Deviation (MAD)9683.3
Skewness6.3216696
Sum1799924.8
Variance2.4252933 × 1010
MonotonicityNot monotonic
2023-12-13T00:11:23.899742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
3610.0 3
 
7.1%
27869.0 1
 
2.4%
2578.1 1
 
2.4%
2160.6 1
 
2.4%
2718.3 1
 
2.4%
2882.6 1
 
2.4%
7023.7 1
 
2.4%
3241.9 1
 
2.4%
3859.0 1
 
2.4%
7131.0 1
 
2.4%
Other values (30) 30
71.4%
ValueCountFrequency (%)
2160.6 1
 
2.4%
2578.1 1
 
2.4%
2603.2 1
 
2.4%
2718.3 1
 
2.4%
2810.8 1
 
2.4%
2882.6 1
 
2.4%
2945.3 1
 
2.4%
3241.9 1
 
2.4%
3610.0 3
7.1%
3655.4 1
 
2.4%
ValueCountFrequency (%)
1020196.0 1
2.4%
87404.0 1
2.4%
68475.0 1
2.4%
53549.0 1
2.4%
50288.8 1
2.4%
38650.0 1
2.4%
38354.0 1
2.4%
37321.0 1
2.4%
36479.4 1
2.4%
32221.0 1
2.4%

건축(㎡)
Real number (ℝ)

HIGH CORRELATION 

Distinct35
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12896.976
Minimum700
Maximum86000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-13T00:11:24.050866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum700
5-th percentile2300
Q13100
median8925
Q315832.5
95-th percentile30824
Maximum86000
Range85300
Interquartile range (IQR)12732.5

Descriptive statistics

Standard deviation14986.6
Coefficient of variation (CV)1.1620243
Kurtosis13.192529
Mean12896.976
Median Absolute Deviation (MAD)6100
Skewness3.0725719
Sum541673
Variance2.2459817 × 108
MonotonicityNot monotonic
2023-12-13T00:11:24.284195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
3100 3
 
7.1%
2300 2
 
4.8%
29000 2
 
4.8%
2600 2
 
4.8%
2500 2
 
4.8%
13000 2
 
4.8%
10563 1
 
2.4%
2800 1
 
2.4%
3800 1
 
2.4%
5600 1
 
2.4%
Other values (25) 25
59.5%
ValueCountFrequency (%)
700 1
 
2.4%
1900 1
 
2.4%
2300 2
4.8%
2400 1
 
2.4%
2500 2
4.8%
2600 2
4.8%
2800 1
 
2.4%
3100 3
7.1%
3300 1
 
2.4%
3500 1
 
2.4%
ValueCountFrequency (%)
86000 1
2.4%
36000 1
2.4%
30920 1
2.4%
29000 2
4.8%
25840 1
2.4%
25000 1
2.4%
22500 1
2.4%
22000 1
2.4%
18540 1
2.4%
16110 1
2.4%

층수
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)19.0%
Missing0
Missing (%)0.0%
Memory size468.0 B
3
19 
6
7 
-
7 
2
5 
4
 
1
Other values (3)
3 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique4 ?
Unique (%)9.5%

Sample

1st row6
2nd row6
3rd row4
4th row6
5th row6

Common Values

ValueCountFrequency (%)
3 19
45.2%
6 7
 
16.7%
- 7
 
16.7%
2 5
 
11.9%
4 1
 
2.4%
5 1
 
2.4%
7 1
 
2.4%
1 1
 
2.4%

Length

2023-12-13T00:11:24.448568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:11:24.594416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 19
45.2%
6 7
 
16.7%
7
 
16.7%
2 5
 
11.9%
4 1
 
2.4%
5 1
 
2.4%
7 1
 
2.4%
1 1
 
2.4%

건폐
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)11.9%
Missing0
Missing (%)0.0%
Memory size468.0 B
40
29 
30
9 
25
 
2
10
 
1
20
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique2 ?
Unique (%)4.8%

Sample

1st row40
2nd row40
3rd row40
4th row40
5th row40

Common Values

ValueCountFrequency (%)
40 29
69.0%
30 9
 
21.4%
25 2
 
4.8%
10 1
 
2.4%
20 1
 
2.4%

Length

2023-12-13T00:11:24.770593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:11:24.940275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
40 29
69.0%
30 9
 
21.4%
25 2
 
4.8%
10 1
 
2.4%
20 1
 
2.4%

용적
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean75.945238
Minimum1
Maximum120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-13T00:11:25.072892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile18.4
Q178
median86
Q390
95-th percentile109.5
Maximum120
Range119
Interquartile range (IQR)12

Descriptive statistics

Standard deviation27.879341
Coefficient of variation (CV)0.36709795
Kurtosis0.99600599
Mean75.945238
Median Absolute Deviation (MAD)7
Skewness-1.2586985
Sum3189.7
Variance777.25766
MonotonicityNot monotonic
2023-12-13T00:11:25.208648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
79.0 5
11.9%
90.0 4
 
9.5%
86.0 4
 
9.5%
88.0 4
 
9.5%
80.0 3
 
7.1%
78.0 2
 
4.8%
98.0 2
 
4.8%
100.0 2
 
4.8%
43.0 2
 
4.8%
110.0 2
 
4.8%
Other values (11) 12
28.6%
ValueCountFrequency (%)
1.0 1
2.4%
5.0 1
2.4%
18.0 1
2.4%
26.0 1
2.4%
37.0 1
2.4%
39.7 1
2.4%
41.0 1
2.4%
43.0 2
4.8%
76.0 1
2.4%
78.0 2
4.8%
ValueCountFrequency (%)
120.0 1
 
2.4%
110.0 2
4.8%
100.0 2
4.8%
99.0 1
 
2.4%
98.0 2
4.8%
90.0 4
9.5%
89.0 2
4.8%
88.0 4
9.5%
86.0 4
9.5%
80.0 3
7.1%

Interactions

2023-12-13T00:11:21.498103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:11:21.099869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:11:21.296861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:11:21.598998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:11:21.166363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:11:21.364668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:11:21.694869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:11:21.231375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:11:21.423070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:11:25.351779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관광단지명시설지구물 건 명부지(㎡)건축(㎡)층수건폐용적
관광단지명1.0000.6181.0000.0000.4530.7910.8500.593
시설지구0.6181.0001.0000.4890.7390.7030.4930.777
물 건 명1.0001.0001.0001.0001.0001.0001.0001.000
부지(㎡)0.0000.4891.0001.0000.0000.0000.0000.797
건축(㎡)0.4530.7391.0000.0001.0000.8730.1560.547
층수0.7910.7031.0000.0000.8731.0000.7630.857
건폐0.8500.4931.0000.0000.1560.7631.0000.709
용적0.5930.7771.0000.7970.5470.8570.7091.000
2023-12-13T00:11:25.501401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설지구건폐층수관광단지명
시설지구1.0000.3530.4710.300
건폐0.3531.0000.5790.865
층수0.4710.5791.0000.663
관광단지명0.3000.8650.6631.000
2023-12-13T00:11:25.627969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부지(㎡)건축(㎡)용적관광단지명시설지구층수건폐
부지(㎡)1.0000.832-0.4230.0000.3350.0000.000
건축(㎡)0.8321.000-0.0180.2070.3250.7020.000
용적-0.423-0.0181.0000.4270.5590.4490.513
관광단지명0.0000.2070.4271.0000.3000.6630.865
시설지구0.3350.3250.5590.3001.0000.4710.353
층수0.0000.7020.4490.6630.4711.0000.579
건폐0.0000.0000.5130.8650.3530.5791.000

Missing values

2023-12-13T00:11:22.206006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:11:22.338766image/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

관광단지명시설지구물 건 명부지(㎡)건축(㎡)층수건폐용적
0감포관광단지숙박시설관광호텔127869.02200064079.0
1감포관광단지숙박시설관광호텔238354.02900064076.0
2감포관광단지숙박시설관광호텔337321.02900044078.0
3감포관광단지숙박시설가족호텔114548.01150064079.0
4감포관광단지숙박시설가족호텔228794.02250064078.0
5감포관광단지숙박시설빌라형콘도36479.43600054099.0
6감포관광단지숙박시설타워형콘도87404.08600074098.0
7감포관광단지숙박시설소형숙박시설18126.0650034080.0
8감포관광단지숙박시설소형숙박시설29794.0770034079.0
9감포관광단지휴양문화시설수목원/산림동물원53549.025001105.0
관광단지명시설지구물 건 명부지(㎡)건축(㎡)층수건폐용적
32감포관광단지공공시설공공시설17131.0560024079.0
33감포관광단지공공시설공공시설25440.0430024079.0
34보문관광단지상가시설보문상가26563.01056322039.7
35안동관광단지숙박시설전통호텔12680.010150-3080.0
36안동관광단지숙박시설휴양콘도(빌라형)14649.016110-30110.0
37안동관광단지숙박시설호텔A23485.025840-30110.0
38안동관광단지숙박시설휴양콘도118540.018540-25100.0
39안동관광단지숙박시설휴양콘도212380.014860-30120.0
40안동관광단지숙박시설휴양콘도314786.014790-25100.0
41안동관광단지휴양문화스파랜드38650.030920-3080.0