Overview

Dataset statistics

Number of variables9
Number of observations156
Missing cells10
Missing cells (%)0.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.9 KiB
Average record size in memory77.8 B

Variable types

Categorical1
Text3
Numeric5

Alerts

골프장면적 is highly overall correlated with 골프장홀수High correlation
골프장홀수 is highly overall correlated with 골프장면적High correlation
정제우편번호 is highly overall correlated with 정제WGS84위도High correlation
정제WGS84위도 is highly overall correlated with 정제우편번호High correlation
정제도로명주소 has 4 (2.6%) missing valuesMissing
정제WGS84경도 has 3 (1.9%) missing valuesMissing
정제WGS84위도 has 3 (1.9%) missing valuesMissing
골프장면적 has unique valuesUnique

Reproduction

Analysis started2024-05-10 20:22:48.829873
Analysis finished2024-05-10 20:22:57.194521
Duration8.36 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종
Categorical

Distinct3
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
비회원(대중형)
83 
회원
68 
비회원
 
5

Length

Max length8
Median length8
Mean length5.224359
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row비회원(대중형)
2nd row회원
3rd row회원
4th row회원
5th row회원

Common Values

ValueCountFrequency (%)
비회원(대중형) 83
53.2%
회원 68
43.6%
비회원 5
 
3.2%

Length

2024-05-10T20:22:57.423244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T20:22:57.789025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
비회원(대중형 83
53.2%
회원 68
43.6%
비회원 5
 
3.2%

사업장명
Text

Distinct137
Distinct (%)87.8%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-05-10T20:22:58.399435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length8
Mean length3.8461538
Min length2

Characters and Unicode

Total characters600
Distinct characters179
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

Unique118 ?
Unique (%)75.6%

Sample

1st row베뉴지
2nd row크리스탈밸리
3rd row가평베네스트
4th row마이다스밸리
5th row프리스틴밸리
ValueCountFrequency (%)
스카이밸리 2
 
1.3%
한림광릉 2
 
1.3%
비에이비스타 2
 
1.3%
포천아도니스 2
 
1.3%
블랙스톤 2
 
1.3%
레이크사이드 2
 
1.3%
블루원용인 2
 
1.3%
지산 2
 
1.3%
발리오스 2
 
1.3%
뉴스프링빌 2
 
1.3%
Other values (127) 136
87.2%
2024-05-10T20:22:59.340605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 42
 
7.0%
리 30
 
5.0%
이 22
 
3.7%
크 14
 
2.3%
아 14
 
2.3%
트 13
 
2.2%
밸 12
 
2.0%
인 11
 
1.8%
베 10
 
1.7%
안 10
 
1.7%
Other values (169) 422
70.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 563
93.8%
Uppercase Letter 20
 
3.3%
Decimal Number 13
 
2.2%
Other Punctuation 2
 
0.3%
Other Symbol 1
 
0.2%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 42
 
7.5%
리 30
 
5.3%
이 22
 
3.9%
크 14
 
2.5%
아 14
 
2.5%
트 13
 
2.3%
밸 12
 
2.1%
인 11
 
2.0%
베 10
 
1.8%
안 10
 
1.8%
Other values (144) 385
68.4%
Uppercase Letter
ValueCountFrequency (%)
U 3
15.0%
C 2
 
10.0%
P 2
 
10.0%
T 2
 
10.0%
O 1
 
5.0%
E 1
 
5.0%
R 1
 
5.0%
W 1
 
5.0%
H 1
 
5.0%
Q 1
 
5.0%
Other values (5) 5
25.0%
Decimal Number
ValueCountFrequency (%)
0 3
23.1%
3 3
23.1%
2 2
15.4%
8 2
15.4%
5 1
 
7.7%
6 1
 
7.7%
1 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
? 2
100.0%
Other Symbol
ValueCountFrequency (%)
° 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 563
93.8%
Latin 20
 
3.3%
Common 17
 
2.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 42
 
7.5%
리 30
 
5.3%
이 22
 
3.9%
크 14
 
2.5%
아 14
 
2.5%
트 13
 
2.3%
밸 12
 
2.1%
인 11
 
2.0%
베 10
 
1.8%
안 10
 
1.8%
Other values (144) 385
68.4%
Latin
ValueCountFrequency (%)
U 3
15.0%
C 2
 
10.0%
P 2
 
10.0%
T 2
 
10.0%
O 1
 
5.0%
E 1
 
5.0%
R 1
 
5.0%
W 1
 
5.0%
H 1
 
5.0%
Q 1
 
5.0%
Other values (5) 5
25.0%
Common
ValueCountFrequency (%)
0 3
17.6%
3 3
17.6%
? 2
11.8%
2 2
11.8%
8 2
11.8%
5 1
 
5.9%
° 1
 
5.9%
6 1
 
5.9%
- 1
 
5.9%
1 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 563
93.8%
ASCII 36
 
6.0%
None 1
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 42
 
7.5%
리 30
 
5.3%
이 22
 
3.9%
크 14
 
2.5%
아 14
 
2.5%
트 13
 
2.3%
밸 12
 
2.1%
인 11
 
2.0%
베 10
 
1.8%
안 10
 
1.8%
Other values (144) 385
68.4%
ASCII
ValueCountFrequency (%)
0 3
 
8.3%
U 3
 
8.3%
3 3
 
8.3%
? 2
 
5.6%
C 2
 
5.6%
2 2
 
5.6%
P 2
 
5.6%
T 2
 
5.6%
8 2
 
5.6%
O 1
 
2.8%
Other values (14) 14
38.9%
None
ValueCountFrequency (%)
° 1
100.0%

골프장면적
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct156
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1087503.7
Minimum139847
Maximum3198002
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-10T20:22:59.677464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum139847
5-th percentile229865.75
Q1809798.25
median1078941.5
Q31438995.8
95-th percentile1957380.5
Maximum3198002
Range3058155
Interquartile range (IQR)629197.5

Descriptive statistics

Standard deviation574123.85
Coefficient of variation (CV)0.52792816
Kurtosis0.97684022
Mean1087503.7
Median Absolute Deviation (MAD)334326.5
Skewness0.59284061
Sum1.6965058 × 108
Variance3.2961819 × 1011
MonotonicityNot monotonic
2024-05-10T20:23:00.074411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1707073 1
 
0.6%
975436 1
 
0.6%
890860 1
 
0.6%
359346 1
 
0.6%
2057831 1
 
0.6%
1160743 1
 
0.6%
1057645 1
 
0.6%
1081010 1
 
0.6%
1771550 1
 
0.6%
495762 1
 
0.6%
Other values (146) 146
93.6%
ValueCountFrequency (%)
139847 1
0.6%
153671 1
0.6%
166549 1
0.6%
184356 1
0.6%
189464 1
0.6%
199267 1
0.6%
221886 1
0.6%
229181 1
0.6%
230094 1
0.6%
241685 1
0.6%
ValueCountFrequency (%)
3198002 1
0.6%
2814762 1
0.6%
2701800 1
0.6%
2548234 1
0.6%
2437045 1
0.6%
2252081 1
0.6%
2230679 1
0.6%
2057831 1
0.6%
1923897 1
0.6%
1901420 1
0.6%

골프장홀수
Real number (ℝ)

HIGH CORRELATION 

Distinct7
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.403846
Minimum6
Maximum45
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-10T20:23:00.439929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile9
Q118
median18
Q327
95-th percentile36
Maximum45
Range39
Interquartile range (IQR)9

Descriptive statistics

Standard deviation8.542704
Coefficient of variation (CV)0.41868106
Kurtosis-0.48267295
Mean20.403846
Median Absolute Deviation (MAD)9
Skewness0.33101515
Sum3183
Variance72.977792
MonotonicityNot monotonic
2024-05-10T20:23:00.807889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
18 63
40.4%
27 41
26.3%
9 31
19.9%
36 16
 
10.3%
6 3
 
1.9%
24 1
 
0.6%
45 1
 
0.6%
ValueCountFrequency (%)
6 3
 
1.9%
9 31
19.9%
18 63
40.4%
24 1
 
0.6%
27 41
26.3%
36 16
 
10.3%
45 1
 
0.6%
ValueCountFrequency (%)
45 1
 
0.6%
36 16
 
10.3%
27 41
26.3%
24 1
 
0.6%
18 63
40.4%
9 31
19.9%
6 3
 
1.9%

정제도로명주소
Text

MISSING 

Distinct131
Distinct (%)86.2%
Missing4
Missing (%)2.6%
Memory size1.3 KiB
2024-05-10T20:23:01.341313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length27
Mean length21.223684
Min length14

Characters and Unicode

Total characters3226
Distinct characters183
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique110 ?
Unique (%)72.4%

Sample

1st row경기도 가평군 가평읍 용추로171번길 100
2nd row경기도 가평군 상면 대보간선로 602-111
3rd row경기도 가평군 상면 둔덕말길 232
4th row경기도 가평군 설악면 다락재로 73-111
5th row경기도 가평군 설악면 유명로 1243-199
ValueCountFrequency (%)
경기도 152
 
19.9%
용인시 29
 
3.8%
여주시 23
 
3.0%
처인구 21
 
2.7%
안성시 14
 
1.8%
이천시 13
 
1.7%
포천시 12
 
1.6%
파주시 9
 
1.2%
가평군 8
 
1.0%
화성시 8
 
1.0%
Other values (318) 475
62.2%
2024-05-10T20:23:02.365497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
612
 
19.0%
기 165
 
5.1%
도 159
 
4.9%
경 154
 
4.8%
시 143
 
4.4%
로 123
 
3.8%
1 107
 
3.3%
면 81
 
2.5%
2 76
 
2.4%
3 62
 
1.9%
Other values (173) 1544
47.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1985
61.5%
Space Separator 612
 
19.0%
Decimal Number 595
 
18.4%
Dash Punctuation 32
 
1.0%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 165
 
8.3%
도 159
 
8.0%
경 154
 
7.8%
시 143
 
7.2%
로 123
 
6.2%
면 81
 
4.1%
길 55
 
2.8%
주 51
 
2.6%
인 51
 
2.6%
구 40
 
2.0%
Other values (160) 963
48.5%
Decimal Number
ValueCountFrequency (%)
1 107
18.0%
2 76
12.8%
3 62
10.4%
6 57
9.6%
0 56
9.4%
5 55
9.2%
4 54
9.1%
7 47
7.9%
9 43
7.2%
8 38
 
6.4%
Space Separator
ValueCountFrequency (%)
612
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1985
61.5%
Common 1241
38.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 165
 
8.3%
도 159
 
8.0%
경 154
 
7.8%
시 143
 
7.2%
로 123
 
6.2%
면 81
 
4.1%
길 55
 
2.8%
주 51
 
2.6%
인 51
 
2.6%
구 40
 
2.0%
Other values (160) 963
48.5%
Common
ValueCountFrequency (%)
612
49.3%
1 107
 
8.6%
2 76
 
6.1%
3 62
 
5.0%
6 57
 
4.6%
0 56
 
4.5%
5 55
 
4.4%
4 54
 
4.4%
7 47
 
3.8%
9 43
 
3.5%
Other values (3) 72
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1985
61.5%
ASCII 1241
38.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
612
49.3%
1 107
 
8.6%
2 76
 
6.1%
3 62
 
5.0%
6 57
 
4.6%
0 56
 
4.5%
5 55
 
4.4%
4 54
 
4.4%
7 47
 
3.8%
9 43
 
3.5%
Other values (3) 72
 
5.8%
Hangul
ValueCountFrequency (%)
기 165
 
8.3%
도 159
 
8.0%
경 154
 
7.8%
시 143
 
7.2%
로 123
 
6.2%
면 81
 
4.1%
길 55
 
2.8%
주 51
 
2.6%
인 51
 
2.6%
구 40
 
2.0%
Other values (160) 963
48.5%

정제지번주소
Text

Distinct135
Distinct (%)86.5%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-05-10T20:23:02.921152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length26
Mean length22.326923
Min length14

Characters and Unicode

Total characters3483
Distinct characters151
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

Unique114 ?
Unique (%)73.1%

Sample

1st row경기도 가평군 가평읍 승안리 산176번지
2nd row경기도 가평군 상면 항사리 31번지
3rd row경기도 가평군 상면 상동리 산52번지
4th row경기도 가평군 설악면 이천리 240번지
5th row경기도 가평군 설악면 이천리 산2-12번지
ValueCountFrequency (%)
경기도 156
 
19.9%
용인시 29
 
3.7%
여주시 23
 
2.9%
처인구 21
 
2.7%
포천시 15
 
1.9%
안성시 15
 
1.9%
이천시 13
 
1.7%
파주시 9
 
1.1%
화성시 8
 
1.0%
광주시 8
 
1.0%
Other values (322) 486
62.1%
2024-05-10T20:23:04.194654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
627
18.0%
기 166
 
4.8%
도 164
 
4.7%
지 164
 
4.7%
경 156
 
4.5%
번 154
 
4.4%
시 147
 
4.2%
1 136
 
3.9%
리 122
 
3.5%
- 102
 
2.9%
Other values (141) 1545
44.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2235
64.2%
Space Separator 627
 
18.0%
Decimal Number 519
 
14.9%
Dash Punctuation 102
 
2.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 166
 
7.4%
도 164
 
7.3%
지 164
 
7.3%
경 156
 
7.0%
번 154
 
6.9%
시 147
 
6.6%
리 122
 
5.5%
면 84
 
3.8%
산 62
 
2.8%
동 55
 
2.5%
Other values (129) 961
43.0%
Decimal Number
ValueCountFrequency (%)
1 136
26.2%
2 68
13.1%
5 56
10.8%
4 52
 
10.0%
3 45
 
8.7%
6 38
 
7.3%
0 36
 
6.9%
7 32
 
6.2%
8 29
 
5.6%
9 27
 
5.2%
Space Separator
ValueCountFrequency (%)
627
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 102
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2235
64.2%
Common 1248
35.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 166
 
7.4%
도 164
 
7.3%
지 164
 
7.3%
경 156
 
7.0%
번 154
 
6.9%
시 147
 
6.6%
리 122
 
5.5%
면 84
 
3.8%
산 62
 
2.8%
동 55
 
2.5%
Other values (129) 961
43.0%
Common
ValueCountFrequency (%)
627
50.2%
1 136
 
10.9%
- 102
 
8.2%
2 68
 
5.4%
5 56
 
4.5%
4 52
 
4.2%
3 45
 
3.6%
6 38
 
3.0%
0 36
 
2.9%
7 32
 
2.6%
Other values (2) 56
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2235
64.2%
ASCII 1248
35.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
627
50.2%
1 136
 
10.9%
- 102
 
8.2%
2 68
 
5.4%
5 56
 
4.5%
4 52
 
4.2%
3 45
 
3.6%
6 38
 
3.0%
0 36
 
2.9%
7 32
 
2.6%
Other values (2) 56
 
4.5%
Hangul
ValueCountFrequency (%)
기 166
 
7.4%
도 164
 
7.3%
지 164
 
7.3%
경 156
 
7.0%
번 154
 
6.9%
시 147
 
6.6%
리 122
 
5.5%
면 84
 
3.8%
산 62
 
2.8%
동 55
 
2.5%
Other values (129) 961
43.0%

정제우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct118
Distinct (%)75.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14296.872
Minimum10024
Maximum18578
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-10T20:23:04.604474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10024
5-th percentile10753.5
Q112041.75
median12722.5
Q317172.5
95-th percentile17768
Maximum18578
Range8554
Interquartile range (IQR)5130.75

Descriptive statistics

Standard deviation2808.1562
Coefficient of variation (CV)0.19641753
Kurtosis-1.7034161
Mean14296.872
Median Absolute Deviation (MAD)2021.5
Skewness0.12060863
Sum2230312
Variance7885741.5
MonotonicityNot monotonic
2024-05-10T20:23:05.031754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
17406 5
 
3.2%
17500 3
 
1.9%
12617 3
 
1.9%
12646 3
 
1.9%
12614 3
 
1.9%
17505 3
 
1.9%
11155 2
 
1.3%
17414 2
 
1.3%
10830 2
 
1.3%
17170 2
 
1.3%
Other values (108) 128
82.1%
ValueCountFrequency (%)
10024 1
0.6%
10271 1
0.6%
10293 2
1.3%
10453 1
0.6%
10553 1
0.6%
10566 1
0.6%
10596 1
0.6%
10806 1
0.6%
10807 1
0.6%
10829 1
0.6%
ValueCountFrequency (%)
18578 2
1.3%
18544 1
0.6%
18516 1
0.6%
18482 1
0.6%
18465 2
1.3%
18254 1
0.6%
17606 1
0.6%
17534 2
1.3%
17522 2
1.3%
17521 1
0.6%

정제WGS84경도
Real number (ℝ)

MISSING 

Distinct132
Distinct (%)86.3%
Missing3
Missing (%)1.9%
Infinite0
Infinite (%)0.0%
Mean127.26195
Minimum126.53419
Maximum127.74341
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-10T20:23:05.472239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.53419
5-th percentile126.85053
Q1127.12033
median127.27876
Q3127.42021
95-th percentile127.69572
Maximum127.74341
Range1.2092195
Interquartile range (IQR)0.29988376

Descriptive statistics

Standard deviation0.26279782
Coefficient of variation (CV)0.0020650149
Kurtosis-0.31890606
Mean127.26195
Median Absolute Deviation (MAD)0.15263481
Skewness-0.25956593
Sum19471.078
Variance0.069062693
MonotonicityNot monotonic
2024-05-10T20:23:05.946407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.3453064977 2
 
1.3%
127.7265930476 2
 
1.3%
127.4168818722 2
 
1.3%
127.6178657976 2
 
1.3%
127.4314045964 2
 
1.3%
126.8932598867 2
 
1.3%
127.3259391728 2
 
1.3%
127.1783872029 2
 
1.3%
127.3816493378 2
 
1.3%
127.1719993269 2
 
1.3%
Other values (122) 133
85.3%
(Missing) 3
 
1.9%
ValueCountFrequency (%)
126.5341928032 1
0.6%
126.5654892796 1
0.6%
126.7532005181 1
0.6%
126.7713755012 1
0.6%
126.7773182936 1
0.6%
126.8126782079 1
0.6%
126.8350207515 1
0.6%
126.8446196107 1
0.6%
126.8544709844 2
1.3%
126.8583966891 1
0.6%
ValueCountFrequency (%)
127.7434122913 1
0.6%
127.7393866828 1
0.6%
127.7339647837 1
0.6%
127.7265930476 2
1.3%
127.7201400371 1
0.6%
127.7030115092 1
0.6%
127.7014405714 1
0.6%
127.6918987923 1
0.6%
127.6907116469 1
0.6%
127.6560877328 1
0.6%

정제WGS84위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct132
Distinct (%)86.3%
Missing3
Missing (%)1.9%
Infinite0
Infinite (%)0.0%
Mean37.41261
Minimum36.959592
Maximum38.073339
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-10T20:23:06.462682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.959592
5-th percentile37.089208
Q137.181812
median37.310719
Q337.664911
95-th percentile37.929174
Maximum38.073339
Range1.1137471
Interquartile range (IQR)0.48309915

Descriptive statistics

Standard deviation0.29313184
Coefficient of variation (CV)0.0078351079
Kurtosis-0.92280607
Mean37.41261
Median Absolute Deviation (MAD)0.1564531
Skewness0.66780871
Sum5724.1294
Variance0.085926275
MonotonicityNot monotonic
2024-05-10T20:23:06.933475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.1109616372 2
 
1.3%
37.3334034734 2
 
1.3%
37.1805960356 2
 
1.3%
37.1615917511 2
 
1.3%
37.1542659198 2
 
1.3%
37.8246569113 2
 
1.3%
37.134182491 2
 
1.3%
37.321375141 2
 
1.3%
37.0172634986 2
 
1.3%
37.9708996171 2
 
1.3%
Other values (122) 133
85.3%
(Missing) 3
 
1.9%
ValueCountFrequency (%)
36.9595919551 1
0.6%
37.0172634986 2
1.3%
37.0385737233 1
0.6%
37.0469013207 1
0.6%
37.0599544193 1
0.6%
37.0754876649 1
0.6%
37.0838650595 1
0.6%
37.0927706903 2
1.3%
37.0940556436 1
0.6%
37.095336093 1
0.6%
ValueCountFrequency (%)
38.0733390604 2
1.3%
38.0000565528 1
0.6%
37.9909538492 1
0.6%
37.9708996171 2
1.3%
37.9678007073 1
0.6%
37.9332319168 1
0.6%
37.9264683398 2
1.3%
37.9239816889 1
0.6%
37.9017308724 1
0.6%
37.8864077354 1
0.6%

Interactions

2024-05-10T20:22:55.138131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:22:49.750592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:22:50.967933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:22:52.289786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:22:53.817276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:22:55.390601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:22:49.977511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:22:51.230215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:22:52.754661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:22:54.094303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:22:55.622303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:22:50.205808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:22:51.566325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:22:52.972219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:22:54.371228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:22:55.814671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:22:50.429992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:22:51.786172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:22:53.220394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:22:54.619712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:22:56.063657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:22:50.689662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:22:52.073457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:22:53.484215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:22:54.881748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-10T20:23:07.212621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종골프장면적골프장홀수정제우편번호정제WGS84경도정제WGS84위도
업종1.0000.4590.7010.0100.2100.000
골프장면적0.4591.0000.8490.1560.1130.482
골프장홀수0.7010.8491.0000.0000.0000.319
정제우편번호0.0100.1560.0001.0000.7230.737
정제WGS84경도0.2100.1130.0000.7231.0000.585
정제WGS84위도0.0000.4820.3190.7370.5851.000
2024-05-10T20:23:07.692960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
골프장면적골프장홀수정제우편번호정제WGS84경도정제WGS84위도업종
골프장면적1.0000.901-0.0230.1560.0900.306
골프장홀수0.9011.0000.0460.0870.0090.379
정제우편번호-0.0230.0461.0000.165-0.9010.000
정제WGS84경도0.1560.0870.1651.000-0.2540.123
정제WGS84위도0.0900.009-0.901-0.2541.0000.000
업종0.3060.3790.0000.1230.0001.000

Missing values

2024-05-10T20:22:56.393908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-10T20:22:56.743651image/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.
2024-05-10T20:22:57.030222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

업종사업장명골프장면적골프장홀수정제도로명주소정제지번주소정제우편번호정제WGS84경도정제WGS84위도
0비회원(대중형)베뉴지170707327경기도 가평군 가평읍 용추로171번길 100경기도 가평군 가평읍 승안리 산176번지12408127.47815537.843956
1회원크리스탈밸리92608518경기도 가평군 상면 대보간선로 602-111경기도 가평군 상면 항사리 31번지12445127.3872737.79416
2회원가평베네스트170746527경기도 가평군 상면 둔덕말길 232경기도 가평군 상면 상동리 산52번지12443127.30543837.797145
3회원마이다스밸리107872918경기도 가평군 설악면 다락재로 73-111경기도 가평군 설악면 이천리 240번지12459127.45869437.665767
4회원프리스틴밸리115646518경기도 가평군 설악면 유명로 1243-199경기도 가평군 설악면 이천리 산2-12번지12468127.45078537.656201
5회원아난티174445327경기도 가평군 설악면 유명로 961-34경기도 가평군 설악면 방일리 산90-2번지12472127.48227737.620183
6회원한양144008736경기도 고양시 덕양구 고양대로1643번길 164경기도 고양시 덕양구 원당동 198-114번지10293126.85447137.656986
7비회원(대중형)올림픽3139219경기도 고양시 덕양구 혜음로 301경기도 고양시 덕양구 벽제동 467-1번지10271126.89302137.721861
8비회원(대중형)일산스프링힐스2300949경기도 고양시 일산동구 산황로 108경기도 고양시 일산동구 산황동 424-3번지10453126.81267837.656227
9회원그린힐86222818경기도 광주시 곤지암읍 내선길 176경기도 광주시 곤지암읍 이선리 5-27번지12725127.42471437.359529
업종사업장명골프장면적골프장홀수정제도로명주소정제지번주소정제우편번호정제WGS84경도정제WGS84위도
146회원아시아나223067936경기도 용인시 처인구 양지면 양대로 290경기도 용인시 처인구 양지면 대대리 854-34번지17155127.28938637.254525
147비회원(대중형)블루원용인4396889경기도 용인시 처인구 원삼면 보개원삼로1534번길 40경기도 용인시 처인구 원삼면 목신리 356-10번지17170127.32593937.134182
148비회원(대중형)지산1843569경기도 용인시 처인구 원삼면 죽양대로2000번길 60경기도 용인시 처인구 원삼면 맹리 1-29번지17165127.33584137.209879
149회원코리아135101727경기도 용인시 처인구 이동읍 기흥단지로 579경기도 용인시 처인구 이동읍 서리 784-7번지17125127.1547937.219361
150비회원(대중형)세현99784318경기도 용인시 처인구 이동읍 백자로 450경기도 용인시 처인구 이동읍 서리 산70-3번지17127127.1885737.18667
151회원화산103927218경기도 용인시 처인구 이동읍 화산로 239경기도 용인시 처인구 이동읍 화산리 129-64번지17135127.23180237.15409
152비회원(대중형)글렌로스4659169경기도 용인시 처인구 포곡읍 에버랜드로562번길 69경기도 용인시 처인구 포곡읍 가실리 65-3번지17021127.18573437.29447
153비회원사우스스프링스97550918경기도 이천시 모가면 공원로 64경기도 이천시 모가면 소고리 640-6번지17407127.45097537.175198
154비회원(대중형)뉴스프링빌3411799경기도 이천시 모가면 사실로527번길 158경기도 이천시 모가면 두미리 419번지17406127.43140537.154266
155회원비에이비스타158058836경기도 이천시 모가면 어농로 272경기도 이천시 모가면 어농리 386-1번지17406127.41688237.180596