Overview

Dataset statistics

Number of variables7
Number of observations525
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory29.9 KiB
Average record size in memory58.3 B

Variable types

Categorical2
Text3
Numeric2

Dataset

Description전국 골프장 관련 정보 (전국에서 운영 중인 골프장 업소명, 사업자명(대표자), 소재지, 총면적, 홀수, 세부종류 정보 입니다.)
URLhttps://www.data.go.kr/data/15118920/fileData.do

Alerts

총면적(제곱미터) is highly overall correlated with 홀수(홀)High correlation
홀수(홀) is highly overall correlated with 총면적(제곱미터) High correlation
지역 is highly overall correlated with 세부종류High correlation
세부종류 is highly overall correlated with 지역High correlation
총면적(제곱미터) has unique valuesUnique

Reproduction

Analysis started2023-12-12 00:36:47.763118
Analysis finished2023-12-12 00:36:48.942254
Duration1.18 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지역
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
경기
155 
강원
60 
경북
55 
전남
41 
경남
41 
Other values (12)
173 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
경기 155
29.5%
강원 60
 
11.4%
경북 55
 
10.5%
전남 41
 
7.8%
경남 41
 
7.8%
제주 41
 
7.8%
충북 40
 
7.6%
전북 28
 
5.3%
충남 25
 
4.8%
인천 12
 
2.3%
Other values (7) 27
 
5.1%

Length

2023-12-12T09:36:49.013143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기 155
29.5%
강원 60
 
11.4%
경북 55
 
10.5%
전남 41
 
7.8%
경남 41
 
7.8%
제주 41
 
7.8%
충북 40
 
7.6%
전북 28
 
5.3%
충남 25
 
4.8%
인천 12
 
2.3%
Other values (7) 27
 
5.1%

업소명
Text

Distinct491
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
2023-12-12T09:36:49.261422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length15
Mean length7.512381
Min length2

Characters and Unicode

Total characters3944
Distinct characters340
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique457 ?
Unique (%)87.0%

Sample

1st row한양컨트리클럽
2nd row뉴코리아 컨트리클럽
3rd row고양컨트리클럽
4th row1.2.3
5th row올림픽 골프장
ValueCountFrequency (%)
컨트리클럽 18
 
2.8%
골프존카운티 10
 
1.6%
골프클럽 9
 
1.4%
골프장 7
 
1.1%
c.c 4
 
0.6%
엘리시안 4
 
0.6%
소노펠리체 4
 
0.6%
cc 4
 
0.6%
비발디파크 3
 
0.5%
제주cc 3
 
0.5%
Other values (523) 571
89.6%
2023-12-12T09:36:49.661612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
C 346
 
8.8%
리 228
 
5.8%
클 170
 
4.3%
럽 166
 
4.2%
트 163
 
4.1%
스 143
 
3.6%
프 143
 
3.6%
골 134
 
3.4%
123
 
3.1%
컨 109
 
2.8%
Other values (330) 2219
56.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3232
81.9%
Uppercase Letter 413
 
10.5%
Space Separator 124
 
3.1%
Other Punctuation 87
 
2.2%
Decimal Number 33
 
0.8%
Lowercase Letter 28
 
0.7%
Other Symbol 8
 
0.2%
Close Punctuation 8
 
0.2%
Open Punctuation 8
 
0.2%
Letter Number 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 228
 
7.1%
클 170
 
5.3%
럽 166
 
5.1%
트 163
 
5.0%
스 143
 
4.4%
프 143
 
4.4%
골 134
 
4.1%
컨 109
 
3.4%
이 70
 
2.2%
아 40
 
1.2%
Other values (284) 1866
57.7%
Uppercase Letter
ValueCountFrequency (%)
C 346
83.8%
G 25
 
6.1%
K 4
 
1.0%
S 4
 
1.0%
U 4
 
1.0%
O 3
 
0.7%
E 3
 
0.7%
J 3
 
0.7%
B 2
 
0.5%
P 2
 
0.5%
Other values (11) 17
 
4.1%
Decimal Number
ValueCountFrequency (%)
2 10
30.3%
1 6
18.2%
0 5
15.2%
7 4
 
12.1%
3 3
 
9.1%
8 2
 
6.1%
9 1
 
3.0%
5 1
 
3.0%
6 1
 
3.0%
Lowercase Letter
ValueCountFrequency (%)
c 18
64.3%
k 3
 
10.7%
s 3
 
10.7%
l 2
 
7.1%
i 1
 
3.6%
a 1
 
3.6%
Other Punctuation
ValueCountFrequency (%)
. 75
86.2%
& 9
 
10.3%
, 3
 
3.4%
Space Separator
ValueCountFrequency (%)
123
99.2%
  1
 
0.8%
Other Symbol
ValueCountFrequency (%)
㈜ 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3240
82.2%
Latin 443
 
11.2%
Common 261
 
6.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 228
 
7.0%
클 170
 
5.2%
럽 166
 
5.1%
트 163
 
5.0%
스 143
 
4.4%
프 143
 
4.4%
골 134
 
4.1%
컨 109
 
3.4%
이 70
 
2.2%
아 40
 
1.2%
Other values (285) 1874
57.8%
Latin
ValueCountFrequency (%)
C 346
78.1%
G 25
 
5.6%
c 18
 
4.1%
K 4
 
0.9%
S 4
 
0.9%
U 4
 
0.9%
O 3
 
0.7%
E 3
 
0.7%
k 3
 
0.7%
s 3
 
0.7%
Other values (18) 30
 
6.8%
Common
ValueCountFrequency (%)
123
47.1%
. 75
28.7%
2 10
 
3.8%
& 9
 
3.4%
) 8
 
3.1%
( 8
 
3.1%
1 6
 
2.3%
0 5
 
1.9%
7 4
 
1.5%
3 3
 
1.1%
Other values (7) 10
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3232
81.9%
ASCII 701
 
17.8%
None 9
 
0.2%
Number Forms 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
C 346
49.4%
123
 
17.5%
. 75
 
10.7%
G 25
 
3.6%
c 18
 
2.6%
2 10
 
1.4%
& 9
 
1.3%
) 8
 
1.1%
( 8
 
1.1%
1 6
 
0.9%
Other values (33) 73
 
10.4%
Hangul
ValueCountFrequency (%)
리 228
 
7.1%
클 170
 
5.3%
럽 166
 
5.1%
트 163
 
5.0%
스 143
 
4.4%
프 143
 
4.4%
골 134
 
4.1%
컨 109
 
3.4%
이 70
 
2.2%
아 40
 
1.2%
Other values (284) 1866
57.7%
None
ValueCountFrequency (%)
㈜ 8
88.9%
  1
 
11.1%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
100.0%

사업자명(대표자)
Text

Distinct455
Distinct (%)86.7%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
2023-12-12T09:36:50.192464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length24
Mean length11.009524
Min length3

Characters and Unicode

Total characters5780
Distinct characters382
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique392 ?
Unique (%)74.7%

Sample

1st row이승호
2nd row성하현
3rd row김기자
4th row한제걸
5th row이관식
ValueCountFrequency (%)
40
 
5.2%
서상현 6
 
0.8%
주식회사 4
 
0.5%
이승도 4
 
0.5%
유태완 4
 
0.5%
㈜소노인터내셔널(민병소 4
 
0.5%
주)에이치제이매그놀리아 4
 
0.5%
㈜블루원 3
 
0.4%
윤재연 3
 
0.4%
㈜골프존카운티(서상현 3
 
0.4%
Other values (590) 688
90.2%
2023-12-12T09:36:50.606894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 381
 
6.6%
) 314
 
5.4%
( 314
 
5.4%
269
 
4.7%
이 154
 
2.7%
발 112
 
1.9%
개 111
 
1.9%
김 101
 
1.7%
리 100
 
1.7%
주 98
 
1.7%
Other values (372) 3826
66.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4380
75.8%
Other Symbol 381
 
6.6%
Close Punctuation 314
 
5.4%
Open Punctuation 314
 
5.4%
Space Separator 269
 
4.7%
Other Punctuation 76
 
1.3%
Uppercase Letter 35
 
0.6%
Decimal Number 9
 
0.2%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 154
 
3.5%
발 112
 
2.6%
개 111
 
2.5%
김 101
 
2.3%
리 100
 
2.3%
주 98
 
2.2%
트 84
 
1.9%
스 84
 
1.9%
정 71
 
1.6%
레 69
 
1.6%
Other values (354) 3396
77.5%
Uppercase Letter
ValueCountFrequency (%)
C 20
57.1%
S 4
 
11.4%
G 4
 
11.4%
J 3
 
8.6%
K 2
 
5.7%
I 1
 
2.9%
M 1
 
2.9%
Other Punctuation
ValueCountFrequency (%)
/ 41
53.9%
, 32
42.1%
. 2
 
2.6%
․ 1
 
1.3%
Decimal Number
ValueCountFrequency (%)
2 6
66.7%
7 3
33.3%
Other Symbol
ValueCountFrequency (%)
㈜ 381
100.0%
Close Punctuation
ValueCountFrequency (%)
) 314
100.0%
Open Punctuation
ValueCountFrequency (%)
( 314
100.0%
Space Separator
ValueCountFrequency (%)
269
100.0%
Lowercase Letter
ValueCountFrequency (%)
c 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4761
82.4%
Common 982
 
17.0%
Latin 37
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 381
 
8.0%
이 154
 
3.2%
발 112
 
2.4%
개 111
 
2.3%
김 101
 
2.1%
리 100
 
2.1%
주 98
 
2.1%
트 84
 
1.8%
스 84
 
1.8%
정 71
 
1.5%
Other values (355) 3465
72.8%
Common
ValueCountFrequency (%)
) 314
32.0%
( 314
32.0%
269
27.4%
/ 41
 
4.2%
, 32
 
3.3%
2 6
 
0.6%
7 3
 
0.3%
. 2
 
0.2%
․ 1
 
0.1%
Latin
ValueCountFrequency (%)
C 20
54.1%
S 4
 
10.8%
G 4
 
10.8%
J 3
 
8.1%
c 2
 
5.4%
K 2
 
5.4%
I 1
 
2.7%
M 1
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4380
75.8%
ASCII 1018
 
17.6%
None 381
 
6.6%
Punctuation 1
 
< 0.1%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 381
100.0%
ASCII
ValueCountFrequency (%)
) 314
30.8%
( 314
30.8%
269
26.4%
/ 41
 
4.0%
, 32
 
3.1%
C 20
 
2.0%
2 6
 
0.6%
S 4
 
0.4%
G 4
 
0.4%
7 3
 
0.3%
Other values (6) 11
 
1.1%
Hangul
ValueCountFrequency (%)
이 154
 
3.5%
발 112
 
2.6%
개 111
 
2.5%
김 101
 
2.3%
리 100
 
2.3%
주 98
 
2.2%
트 84
 
1.9%
스 84
 
1.9%
정 71
 
1.6%
레 69
 
1.6%
Other values (354) 3396
77.5%
Punctuation
ValueCountFrequency (%)
․ 1
100.0%

소재지
Text

Distinct469
Distinct (%)89.3%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
2023-12-12T09:36:50.965235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length34
Mean length18.752381
Min length10

Characters and Unicode

Total characters9845
Distinct characters317
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique415 ?
Unique (%)79.0%

Sample

1st row고양시 덕양구 고양대로1643번길 164
2nd row고양시 덕양구 신원2로 57
3rd row고양시 덕양구 흥도로 304-23
4th row고양시 덕양구 통일로 43-168
5th row고양시 덕양구 혜음로 301
ValueCountFrequency (%)
강원도 60
 
2.6%
용인시 29
 
1.3%
전라북도 28
 
1.2%
여주시 23
 
1.0%
제주시 21
 
0.9%
서귀포시 20
 
0.9%
처인구 20
 
0.9%
포천시 15
 
0.7%
충주시 14
 
0.6%
경주시 14
 
0.6%
Other values (1331) 2044
89.3%
2023-12-12T09:36:51.460747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1767
 
17.9%
1 399
 
4.1%
시 374
 
3.8%
로 362
 
3.7%
면 342
 
3.5%
2 276
 
2.8%
3 220
 
2.2%
4 196
 
2.0%
길 194
 
2.0%
5 193
 
2.0%
Other values (307) 5522
56.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5723
58.1%
Decimal Number 2098
 
21.3%
Space Separator 1767
 
17.9%
Dash Punctuation 155
 
1.6%
Open Punctuation 47
 
0.5%
Close Punctuation 47
 
0.5%
Other Punctuation 8
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 374
 
6.5%
로 362
 
6.3%
면 342
 
6.0%
길 194
 
3.4%
군 170
 
3.0%
주 164
 
2.9%
산 153
 
2.7%
원 133
 
2.3%
천 128
 
2.2%
도 122
 
2.1%
Other values (290) 3581
62.6%
Decimal Number
ValueCountFrequency (%)
1 399
19.0%
2 276
13.2%
3 220
10.5%
4 196
9.3%
5 193
9.2%
0 182
8.7%
6 165
7.9%
7 165
7.9%
9 160
7.6%
8 142
 
6.8%
Other Punctuation
ValueCountFrequency (%)
/ 4
50.0%
, 2
25.0%
. 2
25.0%
Space Separator
ValueCountFrequency (%)
1767
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 155
100.0%
Open Punctuation
ValueCountFrequency (%)
( 47
100.0%
Close Punctuation
ValueCountFrequency (%)
) 47
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5723
58.1%
Common 4122
41.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 374
 
6.5%
로 362
 
6.3%
면 342
 
6.0%
길 194
 
3.4%
군 170
 
3.0%
주 164
 
2.9%
산 153
 
2.7%
원 133
 
2.3%
천 128
 
2.2%
도 122
 
2.1%
Other values (290) 3581
62.6%
Common
ValueCountFrequency (%)
1767
42.9%
1 399
 
9.7%
2 276
 
6.7%
3 220
 
5.3%
4 196
 
4.8%
5 193
 
4.7%
0 182
 
4.4%
6 165
 
4.0%
7 165
 
4.0%
9 160
 
3.9%
Other values (7) 399
 
9.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5723
58.1%
ASCII 4122
41.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1767
42.9%
1 399
 
9.7%
2 276
 
6.7%
3 220
 
5.3%
4 196
 
4.8%
5 193
 
4.7%
0 182
 
4.4%
6 165
 
4.0%
7 165
 
4.0%
9 160
 
3.9%
Other values (7) 399
 
9.7%
Hangul
ValueCountFrequency (%)
시 374
 
6.5%
로 362
 
6.3%
면 342
 
6.0%
길 194
 
3.4%
군 170
 
3.0%
주 164
 
2.9%
산 153
 
2.7%
원 133
 
2.3%
천 128
 
2.2%
도 122
 
2.1%
Other values (290) 3581
62.6%

총면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct525
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean989691.46
Minimum1157.2
Maximum11700331
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.7 KiB
2023-12-12T09:36:51.606244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1157.2
5-th percentile220795.6
Q1559779
median971759
Q31306750
95-th percentile1787776.4
Maximum11700331
Range11699174
Interquartile range (IQR)746971

Descriptive statistics

Standard deviation702974.78
Coefficient of variation (CV)0.7102969
Kurtosis102.89775
Mean989691.46
Median Absolute Deviation (MAD)347964
Skewness7.1083035
Sum5.1958802 × 108
Variance4.9417354 × 1011
MonotonicityNot monotonic
2023-12-12T09:36:51.763158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1441066.0 1
 
0.2%
1465851.0 1
 
0.2%
972560.0 1
 
0.2%
496811.0 1
 
0.2%
957974.0 1
 
0.2%
891436.0 1
 
0.2%
999080.0 1
 
0.2%
841556.0 1
 
0.2%
1695525.0 1
 
0.2%
1080303.0 1
 
0.2%
Other values (515) 515
98.1%
ValueCountFrequency (%)
1157.2 1
0.2%
74258.0 1
0.2%
103426.0 1
0.2%
116842.0 1
0.2%
125496.0 1
0.2%
139847.0 1
0.2%
147181.0 1
0.2%
152438.0 1
0.2%
153671.0 1
0.2%
156851.0 1
0.2%
ValueCountFrequency (%)
11700330.9 1
0.2%
4240782.0 1
0.2%
3198002.0 1
0.2%
2822471.0 1
0.2%
2814762.0 1
0.2%
2685450.0 1
0.2%
2548234.0 1
0.2%
2437045.0 1
0.2%
2252583.0 1
0.2%
2230679.0 1
0.2%

홀수(홀)
Real number (ℝ)

HIGH CORRELATION 

Distinct14
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.070476
Minimum1
Maximum81
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.7 KiB
2023-12-12T09:36:51.959057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile9
Q118
median18
Q327
95-th percentile36
Maximum81
Range80
Interquartile range (IQR)9

Descriptive statistics

Standard deviation8.5012788
Coefficient of variation (CV)0.4457822
Kurtosis6.2653417
Mean19.070476
Median Absolute Deviation (MAD)9
Skewness1.3547067
Sum10012
Variance72.271741
MonotonicityNot monotonic
2023-12-12T09:36:52.126386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
18 240
45.7%
27 121
23.0%
9 116
22.1%
36 26
 
5.0%
6 8
 
1.5%
10 3
 
0.6%
24 2
 
0.4%
1 2
 
0.4%
45 2
 
0.4%
8 1
 
0.2%
Other values (4) 4
 
0.8%
ValueCountFrequency (%)
1 2
 
0.4%
6 8
 
1.5%
8 1
 
0.2%
9 116
22.1%
10 3
 
0.6%
18 240
45.7%
21 1
 
0.2%
24 2
 
0.4%
27 121
23.0%
36 26
 
5.0%
ValueCountFrequency (%)
81 1
 
0.2%
63 1
 
0.2%
54 1
 
0.2%
45 2
 
0.4%
36 26
 
5.0%
27 121
23.0%
24 2
 
0.4%
21 1
 
0.2%
18 240
45.7%
10 3
 
0.6%

세부종류
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
대중제
336 
회원제
148 
대중제
35 
회원제
 
6

Length

Max length5
Median length3
Mean length3.1561905
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row회원제
2nd row회원제
3rd row대중제
4th row대중제
5th row대중제

Common Values

ValueCountFrequency (%)
대중제 336
64.0%
회원제 148
28.2%
대중제 35
 
6.7%
회원제 6
 
1.1%

Length

2023-12-12T09:36:52.293052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:36:52.398016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대중제 371
70.7%
회원제 154
29.3%

Interactions

2023-12-12T09:36:48.506898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:36:48.331841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:36:48.621634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:36:48.416308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T09:36:52.471668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역총면적(제곱미터)홀수(홀)세부종류
지역1.0000.1360.1660.796
총면적(제곱미터)0.1361.0000.8480.046
홀수(홀)0.1660.8481.0000.346
세부종류0.7960.0460.3461.000
2023-12-12T09:36:52.560904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역세부종류
지역1.0000.578
세부종류0.5781.000
2023-12-12T09:36:52.638011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
총면적(제곱미터)홀수(홀)지역세부종류
총면적(제곱미터)1.0000.8830.0650.038
홀수(홀)0.8831.0000.0720.227
지역0.0650.0721.0000.578
세부종류0.0380.2270.5781.000

Missing values

2023-12-12T09:36:48.752050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:36:48.876227image/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

지역업소명사업자명(대표자)소재지총면적(제곱미터)홀수(홀)세부종류
0경기한양컨트리클럽이승호고양시 덕양구 고양대로1643번길 1641441066.036회원제
1경기뉴코리아 컨트리클럽성하현고양시 덕양구 신원2로 57880053.018회원제
2경기고양컨트리클럽김기자고양시 덕양구 흥도로 304-23295598.09대중제
3경기1.2.3한제걸고양시 덕양구 통일로 43-168334432.06대중제
4경기올림픽 골프장이관식고양시 덕양구 혜음로 301313921.09대중제
5경기일산스프링힐스 컨트리클럽김명두고양시 일산동구 산황로 108230094.09대중제
6경기한양컨트리클럽 대중제 9홀 골프장홍순직,이승호고양시 덕양구 고양대로 1591351587.09대중제
7경기한원CC김인식용인시 처인구 남사읍 전나무골길 2번길 941024961.027회원제
8경기양지파인CC임태주용인시 처인구 양지면 남평로 1121012580.027대중제
9경기수원CC김효석,김우현용인시 기흥구 중부대로 4951480410.036회원제
지역업소명사업자명(대표자)소재지총면적(제곱미터)홀수(홀)세부종류
515제주크라운CC(재)관정이종환 / 안동일제주시 북선로 125961720.027대중제
516제주해비치CC해비치호텔앤드리조트㈜ / 김민수서귀포시 원님로 399번길 319797237.018회원제
517제주해비치CC해비치호텔앤드리조트㈜ / 김민수서귀포시 원님로 399번길 319769915.018대중제
518제주타미우스CC㈜타미우스 / 신진성제주시 화전길 2011164583.027회원제
519제주라헨느라헨느리조트㈜ / 강창원, 박준영제주시 명림로 375807383.018회원제
520제주한라산CC㈜부건 / 김용덕제주시 선돌목동길 56-46643347.018대중제
521제주더클래식CC㈜더클래식CC / 이중근, 이용곤서귀포시 남조로 1105726587.018대중제
522제주스프링데일㈜동국개발 / 강국창서귀포시 서성로 459761919.018대중제
523제주에코랜드㈜더원 / 정우석제주시 번영로 1278-1691317514.027대중제
524제주아덴힐아덴힐리조트앤골프㈜ / 정종인제주시 화전길 82710250.018대중제