Overview

Dataset statistics

Number of variables8
Number of observations41
Missing cells4
Missing cells (%)1.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.8 KiB
Average record size in memory69.2 B

Variable types

Categorical2
Text4
Numeric2

Dataset

Description전라남도내 골프장정보(시군명, 골프장명, 위치, 면적_제곱미터, 규모 홀, 운영방식, 운영주체, 승인일 등)에 관한 데이터입니다.
Author전라남도
URLhttps://www.data.go.kr/data/15069158/fileData.do

Alerts

면적_제곱미터 is highly overall correlated with 규모_홀High correlation
규모_홀 is highly overall correlated with 면적_제곱미터High correlation
운영 is highly imbalanced (55.3%)Imbalance
운영주체 has 4 (9.8%) missing valuesMissing
골프장명 has unique valuesUnique
면적_제곱미터 has unique valuesUnique

Reproduction

Analysis started2023-12-12 16:23:21.789276
Analysis finished2023-12-12 16:23:22.603710
Duration0.81 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군
Categorical

Distinct16
Distinct (%)39.0%
Missing0
Missing (%)0.0%
Memory size460.0 B
나주
5 
순천
5 
화순
4 
담양
3 
여수
3 
Other values (11)
21 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique3 ?
Unique (%)7.3%

Sample

1st row장성
2nd row장성
3rd row담양
4th row담양
5th row담양

Common Values

ValueCountFrequency (%)
나주 5
12.2%
순천 5
12.2%
화순 4
9.8%
담양 3
 
7.3%
여수 3
 
7.3%
해남 3
 
7.3%
함평 3
 
7.3%
장성 2
 
4.9%
곡성 2
 
4.9%
보성 2
 
4.9%
Other values (6) 9
22.0%

Length

2023-12-13T01:23:22.650490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
나주 5
12.2%
순천 5
12.2%
화순 4
9.8%
담양 3
 
7.3%
여수 3
 
7.3%
해남 3
 
7.3%
함평 3
 
7.3%
장성 2
 
4.9%
곡성 2
 
4.9%
보성 2
 
4.9%
Other values (6) 9
22.0%

골프장명
Text

UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-12-13T01:23:22.830779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length17
Mean length7.097561
Min length4

Characters and Unicode

Total characters291
Distinct characters98
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)100.0%

Sample

1st row푸른솔 골프클럽
2nd row백양우리CC
3rd row창평CC
4th row담양레이나CC
5th row죽향CC
ValueCountFrequency (%)
함평 3
 
5.3%
골프클럽 2
 
3.5%
엘리체cc 2
 
3.5%
광양청 2
 
3.5%
영암cc 1
 
1.8%
부영cc 1
 
1.8%
광양cc 1
 
1.8%
보성cc 1
 
1.8%
보성에덴cc 1
 
1.8%
오시아노 1
 
1.8%
Other values (42) 42
73.7%
2023-12-13T01:23:23.215022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
C 62
 
21.3%
17
 
5.8%
골 9
 
3.1%
리 9
 
3.1%
프 8
 
2.7%
광 7
 
2.4%
양 6
 
2.1%
주 5
 
1.7%
크 4
 
1.4%
) 4
 
1.4%
Other values (88) 160
55.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 198
68.0%
Uppercase Letter 65
 
22.3%
Space Separator 17
 
5.8%
Close Punctuation 4
 
1.4%
Open Punctuation 4
 
1.4%
Other Punctuation 2
 
0.7%
Other Symbol 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
골 9
 
4.5%
리 9
 
4.5%
프 8
 
4.0%
광 7
 
3.5%
양 6
 
3.0%
주 5
 
2.5%
크 4
 
2.0%
아 4
 
2.0%
영 4
 
2.0%
나 4
 
2.0%
Other values (80) 138
69.7%
Uppercase Letter
ValueCountFrequency (%)
C 62
95.4%
J 2
 
3.1%
N 1
 
1.5%
Space Separator
ValueCountFrequency (%)
17
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Other Punctuation
ValueCountFrequency (%)
& 2
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 199
68.4%
Latin 65
 
22.3%
Common 27
 
9.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
골 9
 
4.5%
리 9
 
4.5%
프 8
 
4.0%
광 7
 
3.5%
양 6
 
3.0%
주 5
 
2.5%
크 4
 
2.0%
아 4
 
2.0%
영 4
 
2.0%
나 4
 
2.0%
Other values (81) 139
69.8%
Common
ValueCountFrequency (%)
17
63.0%
) 4
 
14.8%
( 4
 
14.8%
& 2
 
7.4%
Latin
ValueCountFrequency (%)
C 62
95.4%
J 2
 
3.1%
N 1
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 198
68.0%
ASCII 92
31.6%
None 1
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
C 62
67.4%
17
 
18.5%
) 4
 
4.3%
( 4
 
4.3%
& 2
 
2.2%
J 2
 
2.2%
N 1
 
1.1%
Hangul
ValueCountFrequency (%)
골 9
 
4.5%
리 9
 
4.5%
프 8
 
4.0%
광 7
 
3.5%
양 6
 
3.0%
주 5
 
2.5%
크 4
 
2.0%
아 4
 
2.0%
영 4
 
2.0%
나 4
 
2.0%
Other values (80) 138
69.7%
None
ValueCountFrequency (%)
㈜ 1
100.0%

위치
Text

Distinct40
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-12-13T01:23:23.510105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.902439
Min length4

Characters and Unicode

Total characters283
Distinct characters87
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)95.1%

Sample

1st row동화면 남산리
2nd row북이면 사거리
3rd row창평면 오강리
4th row금성면 외추리
5th row창평면 광덕리
ValueCountFrequency (%)
여수시 3
 
3.7%
화원면 2
 
2.5%
도곡면 2
 
2.5%
청계면 2
 
2.5%
주광리 2
 
2.5%
옥과면 2
 
2.5%
대곡리 2
 
2.5%
주암면 2
 
2.5%
창평면 2
 
2.5%
금성면 1
 
1.2%
Other values (61) 61
75.3%
2023-12-13T01:23:23.953835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
41
 
14.5%
리 34
 
12.0%
면 29
 
10.2%
곡 7
 
2.5%
읍 7
 
2.5%
동 6
 
2.1%
산 6
 
2.1%
평 6
 
2.1%
화 5
 
1.8%
수 5
 
1.8%
Other values (77) 137
48.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 239
84.5%
Space Separator 41
 
14.5%
Decimal Number 3
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 34
 
14.2%
면 29
 
12.1%
곡 7
 
2.9%
읍 7
 
2.9%
동 6
 
2.5%
산 6
 
2.5%
평 6
 
2.5%
화 5
 
2.1%
수 5
 
2.1%
시 5
 
2.1%
Other values (74) 129
54.0%
Decimal Number
ValueCountFrequency (%)
0 2
66.7%
2 1
33.3%
Space Separator
ValueCountFrequency (%)
41
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 239
84.5%
Common 44
 
15.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 34
 
14.2%
면 29
 
12.1%
곡 7
 
2.9%
읍 7
 
2.9%
동 6
 
2.5%
산 6
 
2.5%
평 6
 
2.5%
화 5
 
2.1%
수 5
 
2.1%
시 5
 
2.1%
Other values (74) 129
54.0%
Common
ValueCountFrequency (%)
41
93.2%
0 2
 
4.5%
2 1
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 239
84.5%
ASCII 44
 
15.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
41
93.2%
0 2
 
4.5%
2 1
 
2.3%
Hangul
ValueCountFrequency (%)
리 34
 
14.2%
면 29
 
12.1%
곡 7
 
2.9%
읍 7
 
2.9%
동 6
 
2.5%
산 6
 
2.5%
평 6
 
2.5%
화 5
 
2.1%
수 5
 
2.1%
시 5
 
2.1%
Other values (74) 129
54.0%

면적_제곱미터
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean992186.34
Minimum234544
Maximum1969760
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-13T01:23:24.121635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum234544
5-th percentile242563
Q1421962
median951318
Q31525308
95-th percentile1804843
Maximum1969760
Range1735216
Interquartile range (IQR)1103346

Descriptive statistics

Standard deviation557860.63
Coefficient of variation (CV)0.5622539
Kurtosis-1.392266
Mean992186.34
Median Absolute Deviation (MAD)554636
Skewness0.032324546
Sum40679640
Variance3.1120849 × 1011
MonotonicityNot monotonic
2023-12-13T01:23:24.278302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
1312986.0 1
 
2.4%
1804843.0 1
 
2.4%
842238.0 1
 
2.4%
234987.0 1
 
2.4%
911572.0 1
 
2.4%
307437.0 1
 
2.4%
538288.0 1
 
2.4%
834771.0 1
 
2.4%
774903.0 1
 
2.4%
1462477.0 1
 
2.4%
Other values (31) 31
75.6%
ValueCountFrequency (%)
234544.0 1
2.4%
234987.0 1
2.4%
242563.0 1
2.4%
242898.0 1
2.4%
247058.0 1
2.4%
263053.0 1
2.4%
297540.0 1
2.4%
307437.0 1
2.4%
342120.0 1
2.4%
396682.0 1
2.4%
ValueCountFrequency (%)
1969760.0 1
2.4%
1831114.0 1
2.4%
1804843.0 1
2.4%
1791833.0 1
2.4%
1640629.0 1
2.4%
1624510.0 1
2.4%
1599997.0 1
2.4%
1575772.0 1
2.4%
1545440.0 1
2.4%
1541422.0 1
2.4%

규모_홀
Real number (ℝ)

HIGH CORRELATION 

Distinct7
Distinct (%)17.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.341463
Minimum6
Maximum54
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-13T01:23:24.475724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile9
Q19
median18
Q327
95-th percentile36
Maximum54
Range48
Interquartile range (IQR)18

Descriptive statistics

Standard deviation10.743858
Coefficient of variation (CV)0.52817528
Kurtosis1.2089214
Mean20.341463
Median Absolute Deviation (MAD)9
Skewness0.93340575
Sum834
Variance115.43049
MonotonicityNot monotonic
2023-12-13T01:23:24.606409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
27 13
31.7%
9 12
29.3%
18 11
26.8%
36 2
 
4.9%
6 1
 
2.4%
45 1
 
2.4%
54 1
 
2.4%
ValueCountFrequency (%)
6 1
 
2.4%
9 12
29.3%
18 11
26.8%
27 13
31.7%
36 2
 
4.9%
45 1
 
2.4%
54 1
 
2.4%
ValueCountFrequency (%)
54 1
 
2.4%
45 1
 
2.4%
36 2
 
4.9%
27 13
31.7%
18 11
26.8%
9 12
29.3%
6 1
 
2.4%

운영
Categorical

IMBALANCE 

Distinct4
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Memory size460.0 B
비회원
34 
회원
4 
비회원+회원
 
2
간이
 
1

Length

Max length6
Median length3
Mean length3.0243902
Min length2

Unique

Unique1 ?
Unique (%)2.4%

Sample

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

Common Values

ValueCountFrequency (%)
비회원 34
82.9%
회원 4
 
9.8%
비회원+회원 2
 
4.9%
간이 1
 
2.4%

Length

2023-12-13T01:23:24.765131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:23:24.911144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
비회원 34
82.9%
회원 4
 
9.8%
비회원+회원 2
 
4.9%
간이 1
 
2.4%

운영주체
Text

MISSING 

Distinct36
Distinct (%)97.3%
Missing4
Missing (%)9.8%
Memory size460.0 B
2023-12-13T01:23:25.113504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length13
Mean length7
Min length3

Characters and Unicode

Total characters259
Distinct characters98
Distinct categories6 ?
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 (%)94.6%

Sample

1st row동화기업㈜
2nd row덕승개발㈜
3rd row㈜담양골프랜드
4th row㈜에이취에이취레저
5th row죽향산업(주)
ValueCountFrequency (%)
㈜부영주택 2
 
5.1%
보성레저개발㈜ 2
 
5.1%
정남진골프리조트㈜ 1
 
2.6%
대호관광개발㈜ 1
 
2.6%
㈜영산 1
 
2.6%
남화산업㈜ 1
 
2.6%
썬카운티㈜ 1
 
2.6%
㈜보성레저산업 1
 
2.6%
다산베아채컨트리클럽(주 1
 
2.6%
함평엘리체 1
 
2.6%
Other values (27) 27
69.2%
2023-12-13T01:23:25.543838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 32
 
12.4%
발 9
 
3.5%
개 9
 
3.5%
레 9
 
3.5%
주 8
 
3.1%
산 8
 
3.1%
저 8
 
3.1%
광 8
 
3.1%
이 7
 
2.7%
업 7
 
2.7%
Other values (88) 154
59.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 215
83.0%
Other Symbol 32
 
12.4%
Close Punctuation 4
 
1.5%
Open Punctuation 4
 
1.5%
Space Separator 2
 
0.8%
Uppercase Letter 2
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
발 9
 
4.2%
개 9
 
4.2%
레 9
 
4.2%
주 8
 
3.7%
산 8
 
3.7%
저 8
 
3.7%
광 8
 
3.7%
이 7
 
3.3%
업 7
 
3.3%
관 6
 
2.8%
Other values (83) 136
63.3%
Other Symbol
ValueCountFrequency (%)
㈜ 32
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 247
95.4%
Common 10
 
3.9%
Latin 2
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 32
 
13.0%
발 9
 
3.6%
개 9
 
3.6%
레 9
 
3.6%
주 8
 
3.2%
산 8
 
3.2%
저 8
 
3.2%
광 8
 
3.2%
이 7
 
2.8%
업 7
 
2.8%
Other values (84) 142
57.5%
Common
ValueCountFrequency (%)
) 4
40.0%
( 4
40.0%
2
20.0%
Latin
ValueCountFrequency (%)
C 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 215
83.0%
None 32
 
12.4%
ASCII 12
 
4.6%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 32
100.0%
Hangul
ValueCountFrequency (%)
발 9
 
4.2%
개 9
 
4.2%
레 9
 
4.2%
주 8
 
3.7%
산 8
 
3.7%
저 8
 
3.7%
광 8
 
3.7%
이 7
 
3.3%
업 7
 
3.3%
관 6
 
2.8%
Other values (83) 136
63.3%
ASCII
ValueCountFrequency (%)
) 4
33.3%
( 4
33.3%
2
16.7%
C 2
16.7%

승인일
Text

Distinct39
Distinct (%)95.1%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-12-13T01:23:25.808601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.902439
Min length6

Characters and Unicode

Total characters406
Distinct characters17
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

Unique37 ?
Unique (%)90.2%

Sample

1st row2007-05-11
2nd row2005-04-22
3rd row2005-07-29
4th row2005-03-28
5th row2012-09-27
ValueCountFrequency (%)
2006-08-22 2
 
4.8%
1989-08-29 2
 
4.8%
1992-05-07 1
 
2.4%
2003-08-06 1
 
2.4%
2006-11-01 1
 
2.4%
2010-08-20 1
 
2.4%
2006-05-01 1
 
2.4%
2014-06-26 1
 
2.4%
2006-07-23 1
 
2.4%
2006-04-18 1
 
2.4%
Other values (30) 30
71.4%
2023-12-13T01:23:26.208892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 105
25.9%
- 80
19.7%
2 66
16.3%
1 47
11.6%
9 23
 
5.7%
8 18
 
4.4%
5 17
 
4.2%
6 16
 
3.9%
7 12
 
3.0%
3 9
 
2.2%
Other values (7) 13
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 320
78.8%
Dash Punctuation 80
 
19.7%
Other Letter 5
 
1.2%
Space Separator 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 105
32.8%
2 66
20.6%
1 47
14.7%
9 23
 
7.2%
8 18
 
5.6%
5 17
 
5.3%
6 16
 
5.0%
7 12
 
3.8%
3 9
 
2.8%
4 7
 
2.2%
Other Letter
ValueCountFrequency (%)
조 1
20.0%
건 1
20.0%
부 1
20.0%
승 1
20.0%
인 1
20.0%
Dash Punctuation
ValueCountFrequency (%)
- 80
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 401
98.8%
Hangul 5
 
1.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 105
26.2%
- 80
20.0%
2 66
16.5%
1 47
11.7%
9 23
 
5.7%
8 18
 
4.5%
5 17
 
4.2%
6 16
 
4.0%
7 12
 
3.0%
3 9
 
2.2%
Other values (2) 8
 
2.0%
Hangul
ValueCountFrequency (%)
조 1
20.0%
건 1
20.0%
부 1
20.0%
승 1
20.0%
인 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 401
98.8%
Hangul 5
 
1.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 105
26.2%
- 80
20.0%
2 66
16.5%
1 47
11.7%
9 23
 
5.7%
8 18
 
4.5%
5 17
 
4.2%
6 16
 
4.0%
7 12
 
3.0%
3 9
 
2.2%
Other values (2) 8
 
2.0%
Hangul
ValueCountFrequency (%)
조 1
20.0%
건 1
20.0%
부 1
20.0%
승 1
20.0%
인 1
20.0%

Interactions

2023-12-13T01:23:22.317648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:23:22.181826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:23:22.388776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:23:22.253023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:23:26.338125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군골프장명위치면적_제곱미터규모_홀운영운영주체승인일
시군1.0001.0001.0000.0000.0000.8580.9890.956
골프장명1.0001.0001.0001.0001.0001.0001.0001.000
위치1.0001.0001.0000.9320.9591.0000.9940.984
면적_제곱미터0.0001.0000.9321.0000.8530.0000.0000.876
규모_홀0.0001.0000.9590.8531.0000.2021.0000.000
운영0.8581.0001.0000.0000.2021.0001.0001.000
운영주체0.9891.0000.9940.0001.0001.0001.0000.980
승인일0.9561.0000.9840.8760.0001.0000.9801.000
2023-12-13T01:23:26.472271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
운영시군
운영1.0000.464
시군0.4641.000
2023-12-13T01:23:26.574385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
면적_제곱미터규모_홀시군운영
면적_제곱미터1.0000.9570.0000.000
규모_홀0.9571.0000.0000.114
시군0.0000.0001.0000.464
운영0.0000.1140.4641.000

Missing values

2023-12-13T01:23:22.471483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:23:22.566247image/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

시군골프장명위치면적_제곱미터규모_홀운영운영주체승인일
0장성푸른솔 골프클럽동화면 남산리1312986.027비회원동화기업㈜2007-05-11
1장성백양우리CC북이면 사거리297540.09비회원덕승개발㈜2005-04-22
2담양창평CC창평면 오강리263053.09비회원㈜담양골프랜드2005-07-29
3담양담양레이나CC금성면 외추리785210.018비회원㈜에이취에이취레저2005-03-28
4담양죽향CC창평면 광덕리396682.09비회원죽향산업(주)2012-09-27
5화순엘리체CC춘양면 양곡리1067821.018회원엘리체레저(유)1989-08-29
6화순화순CC도곡면 쌍옥리1545440.027회원㈜화순CC1989-08-29
7화순조아밸리CC도곡면 대곡리433394.09비회원조아㈜2005-03-25
8화순무등산CC화순읍 서태리1575772.027비회원동광레저개발㈜2006-05-18
9나주골드레이크CC남평읍 우산리1831114.036비회원+회원나주관광개발㈜2003-09-22
시군골프장명위치면적_제곱미터규모_홀운영운영주체승인일
31영암영암CC삼호읍 난전리1804843.045비회원썬카운티㈜2014-05-14
32무안무안CC청계면 도대리1969760.054비회원남화산업㈜1996-09-14
33무안클린밸리CC청계면 태봉리839686.018비회원㈜영산2006-12-18
34영광대호관광개발㈜백수읍 구수리951318.018비회원대호관광개발㈜2006-08-08
35영광에콜리안 영광골프장영광읍 단주리421962.09비회원<NA>2009-11-28
36장흥JNJ 골프리조트장평면 기동리1450502.027비회원정남진골프리조트㈜2006-08-22
37강진다산베아채 골프&리조트도암면 학장리1420762.027비회원다산베아채컨트리클럽(주)2009-07-07
38함평함평 엘리체CC학교면 곡창리1347715.027비회원함평엘리체1992-05-07
39함평함평 천지CC함평읍 만흥리234544.09비회원㈜지민산업2007-02-12
40함평함평 베르힐 컨트리클럽함평군 대동면1599997.027비회원<NA>조건부 승인