Overview

Dataset statistics

Number of variables8
Number of observations35
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 KiB
Average record size in memory70.7 B

Variable types

Text4
Numeric3
DateTime1

Dataset

Description제주특별자치도 서귀포시 관내 휴양콘도미니엄업에 관한 데이터로 상호명, 소재지, 연락처, 위도경도 등 정보를 제공합니다.
Author제주특별자치도 서귀포시
URLhttps://www.data.go.kr/data/15056409/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
상호명 has unique valuesUnique

Reproduction

Analysis started2024-04-13 11:36:11.838074
Analysis finished2024-04-13 11:36:17.442795
Duration5.6 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

상호명
Text

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size408.0 B
2024-04-13T20:36:18.052484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length18
Mean length11.2
Min length6

Characters and Unicode

Total characters392
Distinct characters120
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)100.0%

Sample

1st row㈜이랜드파크 켄싱턴리조트 제주중문
2nd row켄싱턴리조트 서귀포점
3rd row씨제이대한통운㈜ 나인브릿지콘도미니엄
4th row금호리조트(주) 제주
5th row소노캄 제주 웨스트타워
ValueCountFrequency (%)
휴양콘도미니엄 8
 
11.6%
제주 4
 
5.8%
골프&리조트 3
 
4.3%
리조트 3
 
4.3%
켄싱턴리조트 2
 
2.9%
스프링데일 2
 
2.9%
소노캄 2
 
2.9%
백통신원리조트 2
 
2.9%
㈜이랜드파크 1
 
1.4%
제주부영리조트 1
 
1.4%
Other values (41) 41
59.4%
2024-04-13T20:36:19.308619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
35
 
8.9%
트 26
 
6.6%
리 26
 
6.6%
조 23
 
5.9%
주 16
 
4.1%
제 14
 
3.6%
스 10
 
2.6%
미 10
 
2.6%
콘 9
 
2.3%
도 9
 
2.3%
Other values (110) 214
54.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 334
85.2%
Space Separator 35
 
8.9%
Open Punctuation 4
 
1.0%
Close Punctuation 4
 
1.0%
Lowercase Letter 4
 
1.0%
Other Punctuation 3
 
0.8%
Decimal Number 3
 
0.8%
Uppercase Letter 3
 
0.8%
Other Symbol 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
트 26
 
7.8%
리 26
 
7.8%
조 23
 
6.9%
주 16
 
4.8%
제 14
 
4.2%
스 10
 
3.0%
미 10
 
3.0%
콘 9
 
2.7%
도 9
 
2.7%
니 9
 
2.7%
Other values (96) 182
54.5%
Lowercase Letter
ValueCountFrequency (%)
l 1
25.0%
e 1
25.0%
u 1
25.0%
m 1
25.0%
Uppercase Letter
ValueCountFrequency (%)
V 1
33.3%
E 1
33.3%
S 1
33.3%
Decimal Number
ValueCountFrequency (%)
1 2
66.7%
2 1
33.3%
Space Separator
ValueCountFrequency (%)
35
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Other Punctuation
ValueCountFrequency (%)
& 3
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 336
85.7%
Common 49
 
12.5%
Latin 7
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
트 26
 
7.7%
리 26
 
7.7%
조 23
 
6.8%
주 16
 
4.8%
제 14
 
4.2%
스 10
 
3.0%
미 10
 
3.0%
콘 9
 
2.7%
도 9
 
2.7%
니 9
 
2.7%
Other values (97) 184
54.8%
Latin
ValueCountFrequency (%)
l 1
14.3%
V 1
14.3%
e 1
14.3%
u 1
14.3%
E 1
14.3%
S 1
14.3%
m 1
14.3%
Common
ValueCountFrequency (%)
35
71.4%
( 4
 
8.2%
) 4
 
8.2%
& 3
 
6.1%
1 2
 
4.1%
2 1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 334
85.2%
ASCII 56
 
14.3%
None 2
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
35
62.5%
( 4
 
7.1%
) 4
 
7.1%
& 3
 
5.4%
1 2
 
3.6%
l 1
 
1.8%
2 1
 
1.8%
V 1
 
1.8%
e 1
 
1.8%
u 1
 
1.8%
Other values (3) 3
 
5.4%
Hangul
ValueCountFrequency (%)
트 26
 
7.8%
리 26
 
7.8%
조 23
 
6.9%
주 16
 
4.8%
제 14
 
4.2%
스 10
 
3.0%
미 10
 
3.0%
콘 9
 
2.7%
도 9
 
2.7%
니 9
 
2.7%
Other values (96) 182
54.5%
None
ValueCountFrequency (%)
㈜ 2
100.0%

소재지
Text

Distinct32
Distinct (%)91.4%
Missing0
Missing (%)0.0%
Memory size408.0 B
2024-04-13T20:36:20.138206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length28
Mean length24.971429
Min length20

Characters and Unicode

Total characters874
Distinct characters76
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 (%)82.9%

Sample

1st row제주특별자치도 서귀포시 중문관광로72번길 29-29
2nd row제주특별자치도 서귀포시 이어도로 684
3rd row제주특별자치도 서귀포시 안덕면 광평로 34-156
4th row제주특별자치도 서귀포시 남원읍 태위로 522-12
5th row제주특별자치도 서귀포시 표선면 일주동로 6347-17
ValueCountFrequency (%)
제주특별자치도 35
22.3%
서귀포시 35
22.3%
안덕면 6
 
3.8%
남원읍 5
 
3.2%
표선면 4
 
2.5%
서성로 4
 
2.5%
성산읍 2
 
1.3%
이어도로 2
 
1.3%
산록남로 2
 
1.3%
124 2
 
1.3%
Other values (53) 60
38.2%
2024-04-13T20:36:21.362449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
122
 
14.0%
서 41
 
4.7%
주 38
 
4.3%
도 37
 
4.2%
제 35
 
4.0%
로 35
 
4.0%
시 35
 
4.0%
귀 35
 
4.0%
포 35
 
4.0%
치 35
 
4.0%
Other values (66) 426
48.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 590
67.5%
Decimal Number 153
 
17.5%
Space Separator 122
 
14.0%
Dash Punctuation 9
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 41
 
6.9%
주 38
 
6.4%
도 37
 
6.3%
제 35
 
5.9%
로 35
 
5.9%
시 35
 
5.9%
귀 35
 
5.9%
포 35
 
5.9%
치 35
 
5.9%
자 35
 
5.9%
Other values (54) 229
38.8%
Decimal Number
ValueCountFrequency (%)
1 27
17.6%
2 25
16.3%
4 22
14.4%
7 15
9.8%
5 14
9.2%
6 14
9.2%
0 11
7.2%
3 9
 
5.9%
9 9
 
5.9%
8 7
 
4.6%
Space Separator
ValueCountFrequency (%)
122
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 590
67.5%
Common 284
32.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 41
 
6.9%
주 38
 
6.4%
도 37
 
6.3%
제 35
 
5.9%
로 35
 
5.9%
시 35
 
5.9%
귀 35
 
5.9%
포 35
 
5.9%
치 35
 
5.9%
자 35
 
5.9%
Other values (54) 229
38.8%
Common
ValueCountFrequency (%)
122
43.0%
1 27
 
9.5%
2 25
 
8.8%
4 22
 
7.7%
7 15
 
5.3%
5 14
 
4.9%
6 14
 
4.9%
0 11
 
3.9%
- 9
 
3.2%
3 9
 
3.2%
Other values (2) 16
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 590
67.5%
ASCII 284
32.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
122
43.0%
1 27
 
9.5%
2 25
 
8.8%
4 22
 
7.7%
7 15
 
5.3%
5 14
 
4.9%
6 14
 
4.9%
0 11
 
3.9%
- 9
 
3.2%
3 9
 
3.2%
Other values (2) 16
 
5.6%
Hangul
ValueCountFrequency (%)
서 41
 
6.9%
주 38
 
6.4%
도 37
 
6.3%
제 35
 
5.9%
로 35
 
5.9%
시 35
 
5.9%
귀 35
 
5.9%
포 35
 
5.9%
치 35
 
5.9%
자 35
 
5.9%
Other values (54) 229
38.8%

지번주소
Text

Distinct32
Distinct (%)91.4%
Missing0
Missing (%)0.0%
Memory size408.0 B
2024-04-13T20:36:22.165523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length26
Mean length23.285714
Min length20

Characters and Unicode

Total characters815
Distinct characters57
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 (%)82.9%

Sample

1st row제주특별자치도 서귀포시 색달동 2822-5
2nd row제주특별자치도 서귀포시 강정동 2677
3rd row제주특별자치도 서귀포시 안덕면 광평리 산 7
4th row제주특별자치도 서귀포시 남원읍 남원리 2390
5th row제주특별자치도 서귀포시 표선면 토산리 17
ValueCountFrequency (%)
제주특별자치도 35
21.6%
서귀포시 35
21.6%
안덕면 6
 
3.7%
산 5
 
3.1%
남원읍 5
 
3.1%
표선면 4
 
2.5%
위미리 4
 
2.5%
토평동 3
 
1.9%
색달동 3
 
1.9%
상천리 2
 
1.2%
Other values (49) 60
37.0%
2024-04-13T20:36:23.411892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
127
 
15.6%
서 37
 
4.5%
제 35
 
4.3%
특 35
 
4.3%
별 35
 
4.3%
자 35
 
4.3%
치 35
 
4.3%
도 35
 
4.3%
귀 35
 
4.3%
포 35
 
4.3%
Other values (47) 371
45.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 546
67.0%
Space Separator 127
 
15.6%
Decimal Number 127
 
15.6%
Dash Punctuation 15
 
1.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 37
 
6.8%
제 35
 
6.4%
특 35
 
6.4%
별 35
 
6.4%
자 35
 
6.4%
치 35
 
6.4%
도 35
 
6.4%
귀 35
 
6.4%
포 35
 
6.4%
시 35
 
6.4%
Other values (35) 194
35.5%
Decimal Number
ValueCountFrequency (%)
2 21
16.5%
8 18
14.2%
3 17
13.4%
1 14
11.0%
7 14
11.0%
6 10
7.9%
0 10
7.9%
5 9
7.1%
9 8
 
6.3%
4 6
 
4.7%
Space Separator
ValueCountFrequency (%)
127
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 546
67.0%
Common 269
33.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 37
 
6.8%
제 35
 
6.4%
특 35
 
6.4%
별 35
 
6.4%
자 35
 
6.4%
치 35
 
6.4%
도 35
 
6.4%
귀 35
 
6.4%
포 35
 
6.4%
시 35
 
6.4%
Other values (35) 194
35.5%
Common
ValueCountFrequency (%)
127
47.2%
2 21
 
7.8%
8 18
 
6.7%
3 17
 
6.3%
- 15
 
5.6%
1 14
 
5.2%
7 14
 
5.2%
6 10
 
3.7%
0 10
 
3.7%
5 9
 
3.3%
Other values (2) 14
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 546
67.0%
ASCII 269
33.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
127
47.2%
2 21
 
7.8%
8 18
 
6.7%
3 17
 
6.3%
- 15
 
5.6%
1 14
 
5.2%
7 14
 
5.2%
6 10
 
3.7%
0 10
 
3.7%
5 9
 
3.3%
Other values (2) 14
 
5.2%
Hangul
ValueCountFrequency (%)
서 37
 
6.8%
제 35
 
6.4%
특 35
 
6.4%
별 35
 
6.4%
자 35
 
6.4%
치 35
 
6.4%
도 35
 
6.4%
귀 35
 
6.4%
포 35
 
6.4%
시 35
 
6.4%
Other values (35) 194
35.5%

객실수
Real number (ℝ)

Distinct34
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean158.85714
Minimum15
Maximum721
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size443.0 B
2024-04-13T20:36:23.798406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15
5-th percentile28.5
Q172.5
median104
Q3213.5
95-th percentile336
Maximum721
Range706
Interquartile range (IQR)141

Descriptive statistics

Standard deviation135.61258
Coefficient of variation (CV)0.85367634
Kurtosis7.6541281
Mean158.85714
Median Absolute Deviation (MAD)61
Skewness2.288387
Sum5560
Variance18390.773
MonotonicityNot monotonic
2024-04-13T20:36:24.209192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
190 2
 
5.7%
216 1
 
2.9%
102 1
 
2.9%
330 1
 
2.9%
43 1
 
2.9%
187 1
 
2.9%
116 1
 
2.9%
78 1
 
2.9%
721 1
 
2.9%
212 1
 
2.9%
Other values (24) 24
68.6%
ValueCountFrequency (%)
15 1
2.9%
25 1
2.9%
30 1
2.9%
43 1
2.9%
56 1
2.9%
59 1
2.9%
62 1
2.9%
68 1
2.9%
72 1
2.9%
73 1
2.9%
ValueCountFrequency (%)
721 1
2.9%
350 1
2.9%
330 1
2.9%
326 1
2.9%
310 1
2.9%
255 1
2.9%
246 1
2.9%
216 1
2.9%
215 1
2.9%
212 1
2.9%

연락처
Text

Distinct33
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Memory size408.0 B
2024-04-13T20:36:24.976179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.8
Min length9

Characters and Unicode

Total characters413
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)88.6%

Sample

1st row064-738-9101
2nd row064-739-9001
3rd row064-793-9000
4th row064-766-8000
5th row1588-4888
ValueCountFrequency (%)
1588-4888 2
 
5.7%
064-800-8000 2
 
5.7%
064-738-9101 1
 
2.9%
064-738-7871 1
 
2.9%
064-792-5200 1
 
2.9%
064-731-5500 1
 
2.9%
064-773-7800 1
 
2.9%
064-766-6888 1
 
2.9%
064-783-1888 1
 
2.9%
1670-8800 1
 
2.9%
Other values (23) 23
65.7%
2024-04-13T20:36:26.187348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 90
21.8%
- 67
16.2%
6 47
11.4%
7 44
10.7%
8 41
9.9%
4 40
9.7%
1 25
 
6.1%
3 22
 
5.3%
9 16
 
3.9%
5 12
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 346
83.8%
Dash Punctuation 67
 
16.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 90
26.0%
6 47
13.6%
7 44
12.7%
8 41
11.8%
4 40
11.6%
1 25
 
7.2%
3 22
 
6.4%
9 16
 
4.6%
5 12
 
3.5%
2 9
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 67
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 413
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 90
21.8%
- 67
16.2%
6 47
11.4%
7 44
10.7%
8 41
9.9%
4 40
9.7%
1 25
 
6.1%
3 22
 
5.3%
9 16
 
3.9%
5 12
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 413
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 90
21.8%
- 67
16.2%
6 47
11.4%
7 44
10.7%
8 41
9.9%
4 40
9.7%
1 25
 
6.1%
3 22
 
5.3%
9 16
 
3.9%
5 12
 
2.9%

위도
Real number (ℝ)

Distinct32
Distinct (%)91.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.298228
Minimum33.233679
Maximum33.427085
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size443.0 B
2024-04-13T20:36:26.737685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.233679
5-th percentile33.240357
Q133.264863
median33.289904
Q333.322862
95-th percentile33.415589
Maximum33.427085
Range0.19340584
Interquartile range (IQR)0.057999325

Descriptive statistics

Standard deviation0.049606414
Coefficient of variation (CV)0.0014897614
Kurtosis1.3437061
Mean33.298228
Median Absolute Deviation (MAD)0.03277745
Skewness1.1204805
Sum1165.438
Variance0.0024607963
MonotonicityNot monotonic
2024-04-13T20:36:27.152911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
33.28589961 2
 
5.7%
33.30601259 2
 
5.7%
33.3300637 2
 
5.7%
33.24457037 1
 
2.9%
33.42708531 1
 
2.9%
33.30305473 1
 
2.9%
33.2418349 1
 
2.9%
33.29324228 1
 
2.9%
33.32268154 1
 
2.9%
33.2476142 1
 
2.9%
Other values (22) 22
62.9%
ValueCountFrequency (%)
33.23367947 1
2.9%
33.23690795 1
2.9%
33.2418349 1
2.9%
33.24244887 1
2.9%
33.24457037 1
2.9%
33.24462681 1
2.9%
33.2476142 1
2.9%
33.24910501 1
2.9%
33.26467012 1
2.9%
33.2650556 1
2.9%
ValueCountFrequency (%)
33.42708531 1
2.9%
33.42603156 1
2.9%
33.41111391 1
2.9%
33.3403726 1
2.9%
33.33834117 1
2.9%
33.3300637 2
5.7%
33.3246978 1
2.9%
33.32304283 1
2.9%
33.32268154 1
2.9%
33.31987549 1
2.9%

경도
Real number (ℝ)

Distinct32
Distinct (%)91.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.54699
Minimum126.31753
Maximum126.92645
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size443.0 B
2024-04-13T20:36:27.536817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.31753
5-th percentile126.34804
Q1126.40839
median126.51855
Q3126.63956
95-th percentile126.86884
Maximum126.92645
Range0.6089247
Interquartile range (IQR)0.23116555

Descriptive statistics

Standard deviation0.16943276
Coefficient of variation (CV)0.0013388921
Kurtosis-0.27986184
Mean126.54699
Median Absolute Deviation (MAD)0.1210037
Skewness0.75383986
Sum4429.1447
Variance0.028707462
MonotonicityNot monotonic
2024-04-13T20:36:27.931357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
126.5636465 2
 
5.7%
126.7928947 2
 
5.7%
126.6395572 2
 
5.7%
126.5395727 1
 
2.9%
126.9263466 1
 
2.9%
126.392624 1
 
2.9%
126.4224701 1
 
2.9%
126.3464469 1
 
2.9%
126.6390483 1
 
2.9%
126.4125331 1
 
2.9%
Other values (22) 22
62.9%
ValueCountFrequency (%)
126.3175252 1
2.9%
126.3464469 1
2.9%
126.3487166 1
2.9%
126.3726652 1
2.9%
126.37853 1
2.9%
126.3836363 1
2.9%
126.3851692 1
2.9%
126.392624 1
2.9%
126.4042502 1
2.9%
126.4125331 1
2.9%
ValueCountFrequency (%)
126.9264499 1
2.9%
126.9263466 1
2.9%
126.8441927 1
2.9%
126.7928947 2
5.7%
126.7521221 1
2.9%
126.702756 1
2.9%
126.6430554 1
2.9%
126.6395572 2
5.7%
126.6390483 1
2.9%
126.5872802 1
2.9%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size408.0 B
Minimum2024-04-08 00:00:00
Maximum2024-04-08 00:00:00
2024-04-13T20:36:28.280313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:36:28.579729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-04-13T20:36:15.986422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:36:14.399476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:36:15.187085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:36:16.244283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:36:14.663105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:36:15.453009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:36:16.511633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:36:14.932330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:36:15.725577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-13T20:36:28.794222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상호명소재지지번주소객실수연락처위도경도
상호명1.0001.0001.0001.0001.0001.0001.000
소재지1.0001.0001.0000.0001.0001.0001.000
지번주소1.0001.0001.0000.0001.0001.0001.000
객실수1.0000.0000.0001.0000.8500.0000.534
연락처1.0001.0001.0000.8501.0001.0001.000
위도1.0001.0001.0000.0001.0001.0000.714
경도1.0001.0001.0000.5341.0000.7141.000
2024-04-13T20:36:29.063429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
객실수위도경도
객실수1.0000.0400.245
위도0.0401.0000.416
경도0.2450.4161.000

Missing values

2024-04-13T20:36:16.859030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-13T20:36:17.272292image/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

상호명소재지지번주소객실수연락처위도경도데이터기준일자
0㈜이랜드파크 켄싱턴리조트 제주중문제주특별자치도 서귀포시 중문관광로72번길 29-29제주특별자치도 서귀포시 색달동 2822-5216064-738-910133.247614126.4125332024-04-08
1켄싱턴리조트 서귀포점제주특별자치도 서귀포시 이어도로 684제주특별자치도 서귀포시 강정동 2677246064-739-900133.233679126.489042024-04-08
2씨제이대한통운㈜ 나인브릿지콘도미니엄제주특별자치도 서귀포시 안덕면 광평로 34-156제주특별자치도 서귀포시 안덕면 광평리 산 7100064-793-900033.340373126.404252024-04-08
3금호리조트(주) 제주제주특별자치도 서귀포시 남원읍 태위로 522-12제주특별자치도 서귀포시 남원읍 남원리 2390326064-766-800033.273656126.7027562024-04-08
4소노캄 제주 웨스트타워제주특별자치도 서귀포시 표선면 일주동로 6347-17제주특별자치도 서귀포시 표선면 토산리 173101588-488833.306013126.7928952024-04-08
5해비치리조트제주특별자치도 서귀포시 표선면 민속해안로 537제주특별자치도 서귀포시 표선면 표선리 6-3215064-780-800033.323043126.8441932024-04-08
6(주)캐슬렉스제주 휴양콘도미니엄제주특별자치도 서귀포시 안덕면 평화로 1241제주특별자치도 서귀포시 안덕면 광평리 352-983064-793-660033.338341126.3487172024-04-08
7소노캄 제주 이스트타워제주특별자치도 서귀포시 표선면 일주동로 6347-17제주특별자치도 서귀포시 표선면 토산리 171041588-488833.306013126.7928952024-04-08
8사이프러스 골프&리조트 휴양콘도미니엄제주특별자치도 서귀포시 표선면 번영로 2300제주특별자치도 서귀포시 표선면 성읍리 3268-172064-786-241133.411114126.7521222024-04-08
9휘닉스 제주 섭지코지제주특별자치도 서귀포시 성산읍 섭지코지로 107제주특별자치도 서귀포시 성산읍 고성리 87350064-731-700033.426032126.926452024-04-08
상호명소재지지번주소객실수연락처위도경도데이터기준일자
25오레브 리조트제주특별자치도 서귀포시 태평로 156제주특별자치도 서귀포시 호근동 285-178070-4523-800033.24457126.5395732024-04-08
26중문훼미리 휴양콘도미니엄제주특별자치도 서귀포시 소보리당로164번길 83제주특별자치도 서귀포시 상예동 2729-1102064-738-787133.265947126.3836362024-04-08
27제주신화빌라스제주특별자치도 서귀포시 안덕면 신화역사로304번길 139제주특별자치도 서귀포시 안덕면 서광리 25187211670-880033.301386126.3175252024-04-08
28더큐브리조트제주제주특별자치도 서귀포시 솔오름로105번길 24제주특별자치도 서귀포시 토평동 산 30-8255064-717-664233.2859126.5636472024-04-08
29ES제주리조트제주특별자치도 서귀포시 1100로 501제주특별자치도 서귀포시 하원동 1885153070-4548-028533.289904126.4562392024-04-08
30씨사이드아덴제주특별자치도 서귀포시 중문관광로 124제주특별자치도 서귀포시 색달동 3394-3190064-738-963633.249105126.4149192024-04-08
31백통신원리조트 기린제주특별자치도 서귀포시 남원읍 서성로 427-1제주특별자치도 서귀포시 남원읍 위미리 462876064-745-707733.324698126.6430552024-04-08
32스프링데일 골프&리조트 휴양콘도미니엄 1제주특별자치도 서귀포시 남원읍 서성로 459-1제주특별자치도 서귀포시 남원읍 위미리 462656064-800-800033.330064126.6395572024-04-08
33고은관광농원 휴양콘도미니엄제주특별자치도 서귀포시 일주서로 1262제주특별자치도 서귀포시 상예동 3713-115064-738-998733.26467126.378532024-04-08
34더 시에나 리조트제주특별자치도 서귀포시 용흥로66번길 158-8제주특별자치도 서귀포시 강정동 3703-388064-735-710033.265056126.4845962024-04-08