Overview

Dataset statistics

Number of variables13
Number of observations43
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.7 KiB
Average record size in memory111.0 B

Variable types

Numeric4
Text6
Categorical2
DateTime1

Dataset

Description경남도내 등록체육시설(골프장, 스키장) 현황을 제공합니다. 연번, 사업장명, 홀/슬로프의 수 위치, 연락처 ,비고등의 데이터를 제공합니다.
Author경상남도
URLhttps://www.data.go.kr/data/3082694/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
홀 또는 슬로프수 is highly overall correlated with 면적(제곱미터)High correlation
면적(제곱미터) is highly overall correlated with 홀 또는 슬로프수High correlation
연번 has unique valuesUnique
면적(제곱미터) has unique valuesUnique

Reproduction

Analysis started2024-04-13 11:32:18.821003
Analysis finished2024-04-13 11:32:26.814746
Duration7.99 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22
Minimum1
Maximum43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size515.0 B
2024-04-13T20:32:27.018958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.1
Q111.5
median22
Q332.5
95-th percentile40.9
Maximum43
Range42
Interquartile range (IQR)21

Descriptive statistics

Standard deviation12.556539
Coefficient of variation (CV)0.57075176
Kurtosis-1.2
Mean22
Median Absolute Deviation (MAD)11
Skewness0
Sum946
Variance157.66667
MonotonicityStrictly increasing
2024-04-13T20:32:27.434843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
1 1
 
2.3%
2 1
 
2.3%
25 1
 
2.3%
26 1
 
2.3%
27 1
 
2.3%
28 1
 
2.3%
29 1
 
2.3%
30 1
 
2.3%
31 1
 
2.3%
32 1
 
2.3%
Other values (33) 33
76.7%
ValueCountFrequency (%)
1 1
2.3%
2 1
2.3%
3 1
2.3%
4 1
2.3%
5 1
2.3%
6 1
2.3%
7 1
2.3%
8 1
2.3%
9 1
2.3%
10 1
2.3%
ValueCountFrequency (%)
43 1
2.3%
42 1
2.3%
41 1
2.3%
40 1
2.3%
39 1
2.3%
38 1
2.3%
37 1
2.3%
36 1
2.3%
35 1
2.3%
34 1
2.3%

골프장명
Text

Distinct40
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Memory size472.0 B
2024-04-13T20:32:28.151701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length9.5813953
Min length5

Characters and Unicode

Total characters412
Distinct characters97
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)86.0%

Sample

1st row창원 컨트리클럽
2nd row용원 컨트리클럽
3rd row아라미르골프앤리조트
4th row진주 컨트리클럽
5th row통영동원로얄 컨트리클럽
ValueCountFrequency (%)
컨트리클럽 31
38.8%
서경타니 2
 
2.5%
에덴밸리 2
 
2.5%
아난티남해 2
 
2.5%
양산 2
 
2.5%
힐마루 2
 
2.5%
가야 2
 
2.5%
창녕 2
 
2.5%
거창친환경대중골프장 1
 
1.2%
의령친환경대중골프장 1
 
1.2%
Other values (33) 33
41.2%
2024-04-13T20:32:29.412653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
37
 
9.0%
리 36
 
8.7%
클 35
 
8.5%
럽 35
 
8.5%
트 35
 
8.5%
컨 31
 
7.5%
프 10
 
2.4%
골 9
 
2.2%
스 8
 
1.9%
경 6
 
1.5%
Other values (87) 170
41.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 370
89.8%
Space Separator 37
 
9.0%
Lowercase Letter 4
 
1.0%
Uppercase Letter 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 36
 
9.7%
클 35
 
9.5%
럽 35
 
9.5%
트 35
 
9.5%
컨 31
 
8.4%
프 10
 
2.7%
골 9
 
2.4%
스 8
 
2.2%
경 6
 
1.6%
이 5
 
1.4%
Other values (81) 160
43.2%
Lowercase Letter
ValueCountFrequency (%)
n 1
25.0%
o 1
25.0%
i 1
25.0%
e 1
25.0%
Space Separator
ValueCountFrequency (%)
37
100.0%
Uppercase Letter
ValueCountFrequency (%)
R 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 370
89.8%
Common 37
 
9.0%
Latin 5
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 36
 
9.7%
클 35
 
9.5%
럽 35
 
9.5%
트 35
 
9.5%
컨 31
 
8.4%
프 10
 
2.7%
골 9
 
2.4%
스 8
 
2.2%
경 6
 
1.6%
이 5
 
1.4%
Other values (81) 160
43.2%
Latin
ValueCountFrequency (%)
n 1
20.0%
o 1
20.0%
R 1
20.0%
i 1
20.0%
e 1
20.0%
Common
ValueCountFrequency (%)
37
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 370
89.8%
ASCII 42
 
10.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
37
88.1%
n 1
 
2.4%
o 1
 
2.4%
R 1
 
2.4%
i 1
 
2.4%
e 1
 
2.4%
Hangul
ValueCountFrequency (%)
리 36
 
9.7%
클 35
 
9.5%
럽 35
 
9.5%
트 35
 
9.5%
컨 31
 
8.4%
프 10
 
2.7%
골 9
 
2.4%
스 8
 
2.2%
경 6
 
1.6%
이 5
 
1.4%
Other values (81) 160
43.2%

종류
Categorical

Distinct4
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Memory size472.0 B
대중제
26 
회원제
13 
비회원제
3 
<NA>
 
1

Length

Max length4
Median length3
Mean length3.0930233
Min length3

Unique

Unique1 ?
Unique (%)2.3%

Sample

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

Common Values

ValueCountFrequency (%)
대중제 26
60.5%
회원제 13
30.2%
비회원제 3
 
7.0%
<NA> 1
 
2.3%

Length

2024-04-13T20:32:29.820017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-13T20:32:30.156921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대중제 26
60.5%
회원제 13
30.2%
비회원제 3
 
7.0%
na 1
 
2.3%

홀 또는 슬로프수
Real number (ℝ)

HIGH CORRELATION 

Distinct7
Distinct (%)16.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.604651
Minimum7
Maximum45
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size515.0 B
2024-04-13T20:32:30.471709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile9
Q113.5
median18
Q327
95-th percentile35.1
Maximum45
Range38
Interquartile range (IQR)13.5

Descriptive statistics

Standard deviation8.7127152
Coefficient of variation (CV)0.44442082
Kurtosis0.3655508
Mean19.604651
Median Absolute Deviation (MAD)9
Skewness0.59188945
Sum843
Variance75.911406
MonotonicityNot monotonic
2024-04-13T20:32:30.827977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
18 17
39.5%
27 12
27.9%
9 9
20.9%
36 2
 
4.7%
45 1
 
2.3%
8 1
 
2.3%
7 1
 
2.3%
ValueCountFrequency (%)
7 1
 
2.3%
8 1
 
2.3%
9 9
20.9%
18 17
39.5%
27 12
27.9%
36 2
 
4.7%
45 1
 
2.3%
ValueCountFrequency (%)
45 1
 
2.3%
36 2
 
4.7%
27 12
27.9%
18 17
39.5%
9 9
20.9%
8 1
 
2.3%
7 1
 
2.3%

면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1043277.1
Minimum164773
Maximum2822471
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size515.0 B
2024-04-13T20:32:31.227402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum164773
5-th percentile257528.9
Q1629248.5
median995616
Q31403414.5
95-th percentile1803937.4
Maximum2822471
Range2657698
Interquartile range (IQR)774166

Descriptive statistics

Standard deviation543792.26
Coefficient of variation (CV)0.52123472
Kurtosis1.3467497
Mean1043277.1
Median Absolute Deviation (MAD)409932
Skewness0.71513898
Sum44860917
Variance2.9571003 × 1011
MonotonicityNot monotonic
2024-04-13T20:32:31.654285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
1048959 1
 
2.3%
1635886 1
 
2.3%
1599832 1
 
2.3%
1288176 1
 
2.3%
943987 1
 
2.3%
235262 1
 
2.3%
1437044 1
 
2.3%
786500 1
 
2.3%
672813 1
 
2.3%
995616 1
 
2.3%
Other values (33) 33
76.7%
ValueCountFrequency (%)
164773 1
2.3%
235262 1
2.3%
253145 1
2.3%
296984 1
2.3%
377429 1
2.3%
378840 1
2.3%
392688 1
2.3%
437725 1
2.3%
536542 1
2.3%
571765 1
2.3%
ValueCountFrequency (%)
2822471 1
2.3%
2038075 1
2.3%
1817634 1
2.3%
1680668 1
2.3%
1635886 1
2.3%
1599832 1
2.3%
1514206 1
2.3%
1510534 1
2.3%
1437044 1
2.3%
1421947 1
2.3%

등록일자
Date

Distinct40
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Memory size472.0 B
Minimum1917-12-18 00:00:00
Maximum2023-03-24 00:00:00
2024-04-13T20:32:32.035332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:32:32.430341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)

운영자
Text

Distinct38
Distinct (%)88.4%
Missing0
Missing (%)0.0%
Memory size472.0 B
2024-04-13T20:32:33.249791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length6.8372093
Min length3

Characters and Unicode

Total characters294
Distinct characters97
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)76.7%

Sample

1st row(주)창원컨트리클럽
2nd row용원개발㈜
3rd row㈜진해오션리조트
4th row진주개발㈜
5th row동원관광개발㈜
ValueCountFrequency (%)
신세계개발㈜ 2
 
4.4%
가야개발㈜ 2
 
4.4%
㈜동훈 2
 
4.4%
서경타니골프앤리조트㈜ 2
 
4.4%
㈜아난티 2
 
4.4%
에이원컨트리클럽㈜ 1
 
2.2%
㈜이도 1
 
2.2%
국민체육진흥공단 1
 
2.2%
거창군수 1
 
2.2%
㈜경남관광호텔 1
 
2.2%
Other values (30) 30
66.7%
2024-04-13T20:32:34.448471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 38
 
12.9%
개 13
 
4.4%
발 13
 
4.4%
리 13
 
4.4%
트 12
 
4.1%
클 9
 
3.1%
럽 9
 
3.1%
컨 8
 
2.7%
조 5
 
1.7%
경 5
 
1.7%
Other values (87) 169
57.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 246
83.7%
Other Symbol 38
 
12.9%
Space Separator 5
 
1.7%
Open Punctuation 2
 
0.7%
Close Punctuation 2
 
0.7%
Other Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
개 13
 
5.3%
발 13
 
5.3%
리 13
 
5.3%
트 12
 
4.9%
클 9
 
3.7%
럽 9
 
3.7%
컨 8
 
3.3%
조 5
 
2.0%
경 5
 
2.0%
이 5
 
2.0%
Other values (82) 154
62.6%
Other Symbol
ValueCountFrequency (%)
㈜ 38
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 284
96.6%
Common 10
 
3.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 38
 
13.4%
개 13
 
4.6%
발 13
 
4.6%
리 13
 
4.6%
트 12
 
4.2%
클 9
 
3.2%
럽 9
 
3.2%
컨 8
 
2.8%
조 5
 
1.8%
경 5
 
1.8%
Other values (83) 159
56.0%
Common
ValueCountFrequency (%)
5
50.0%
( 2
 
20.0%
) 2
 
20.0%
, 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 246
83.7%
None 38
 
12.9%
ASCII 10
 
3.4%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 38
100.0%
Hangul
ValueCountFrequency (%)
개 13
 
5.3%
발 13
 
5.3%
리 13
 
5.3%
트 12
 
4.9%
클 9
 
3.7%
럽 9
 
3.7%
컨 8
 
3.3%
조 5
 
2.0%
경 5
 
2.0%
이 5
 
2.0%
Other values (82) 154
62.6%
ASCII
ValueCountFrequency (%)
5
50.0%
( 2
 
20.0%
) 2
 
20.0%
, 1
 
10.0%

소재지(도로명주소)
Text

Distinct40
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Memory size472.0 B
2024-04-13T20:32:35.469416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20
Mean length16.511628
Min length11

Characters and Unicode

Total characters710
Distinct characters102
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 (%)86.0%

Sample

1st row창원시 의창구 대봉로 137
2nd row창원시 진해구 가주로 133
3rd row창원시 진해구 수제로 36
4th row진주시 진성면 진성로 464번길 82
5th row통영시 산양읍 담안길 240
ValueCountFrequency (%)
양산시 8
 
4.8%
김해시 5
 
3.0%
사천시 4
 
2.4%
밀양시 4
 
2.4%
창녕군 3
 
1.8%
창원시 3
 
1.8%
어실로 3
 
1.8%
남해군 3
 
1.8%
40-109 2
 
1.2%
거창군 2
 
1.2%
Other values (113) 129
77.7%
2024-04-13T20:32:36.802734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
130
 
18.3%
로 36
 
5.1%
1 34
 
4.8%
시 28
 
3.9%
면 24
 
3.4%
4 24
 
3.4%
9 22
 
3.1%
0 19
 
2.7%
5 19
 
2.7%
산 17
 
2.4%
Other values (92) 357
50.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 384
54.1%
Decimal Number 183
25.8%
Space Separator 130
 
18.3%
Dash Punctuation 13
 
1.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 36
 
9.4%
시 28
 
7.3%
면 24
 
6.2%
산 17
 
4.4%
양 16
 
4.2%
군 15
 
3.9%
길 12
 
3.1%
해 11
 
2.9%
창 10
 
2.6%
성 8
 
2.1%
Other values (80) 207
53.9%
Decimal Number
ValueCountFrequency (%)
1 34
18.6%
4 24
13.1%
9 22
12.0%
0 19
10.4%
5 19
10.4%
3 16
8.7%
2 16
8.7%
7 12
 
6.6%
6 11
 
6.0%
8 10
 
5.5%
Space Separator
ValueCountFrequency (%)
130
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 384
54.1%
Common 326
45.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 36
 
9.4%
시 28
 
7.3%
면 24
 
6.2%
산 17
 
4.4%
양 16
 
4.2%
군 15
 
3.9%
길 12
 
3.1%
해 11
 
2.9%
창 10
 
2.6%
성 8
 
2.1%
Other values (80) 207
53.9%
Common
ValueCountFrequency (%)
130
39.9%
1 34
 
10.4%
4 24
 
7.4%
9 22
 
6.7%
0 19
 
5.8%
5 19
 
5.8%
3 16
 
4.9%
2 16
 
4.9%
- 13
 
4.0%
7 12
 
3.7%
Other values (2) 21
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 384
54.1%
ASCII 326
45.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
130
39.9%
1 34
 
10.4%
4 24
 
7.4%
9 22
 
6.7%
0 19
 
5.8%
5 19
 
5.8%
3 16
 
4.9%
2 16
 
4.9%
- 13
 
4.0%
7 12
 
3.7%
Other values (2) 21
 
6.4%
Hangul
ValueCountFrequency (%)
로 36
 
9.4%
시 28
 
7.3%
면 24
 
6.2%
산 17
 
4.4%
양 16
 
4.2%
군 15
 
3.9%
길 12
 
3.1%
해 11
 
2.9%
창 10
 
2.6%
성 8
 
2.1%
Other values (80) 207
53.9%

소재지(지번주소)
Text

Distinct40
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Memory size472.0 B
2024-04-13T20:32:37.886508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length28
Mean length24.325581
Min length15

Characters and Unicode

Total characters1046
Distinct characters133
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)86.0%

Sample

1st row경상남도 창원시 의창구 봉림동 647 창원컨트리클럽
2nd row경상남도 창원시 진해구 용원동 산39
3rd row경상남도 창원시 진해구 제덕동 898
4th row경상남도 진주시 진성면 구천리 산10 진주 컨트리클럽
5th row경상남도 통영시 산양읍 영운리 965
ValueCountFrequency (%)
경상남도 43
 
18.3%
양산시 8
 
3.4%
김해시 5
 
2.1%
사천시 4
 
1.7%
밀양시 4
 
1.7%
어곡동 3
 
1.3%
창원시 3
 
1.3%
창녕군 3
 
1.3%
남해군 3
 
1.3%
단장면 2
 
0.9%
Other values (134) 157
66.8%
2024-04-13T20:32:39.413972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
192
 
18.4%
남 51
 
4.9%
상 47
 
4.5%
리 47
 
4.5%
경 44
 
4.2%
도 44
 
4.2%
1 33
 
3.2%
산 28
 
2.7%
면 28
 
2.7%
시 28
 
2.7%
Other values (123) 504
48.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 706
67.5%
Space Separator 192
 
18.4%
Decimal Number 132
 
12.6%
Dash Punctuation 10
 
1.0%
Uppercase Letter 6
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 51
 
7.2%
상 47
 
6.7%
리 47
 
6.7%
경 44
 
6.2%
도 44
 
6.2%
산 28
 
4.0%
면 28
 
4.0%
시 28
 
4.0%
양 17
 
2.4%
군 15
 
2.1%
Other values (110) 357
50.6%
Decimal Number
ValueCountFrequency (%)
1 33
25.0%
3 16
12.1%
2 16
12.1%
9 13
 
9.8%
0 12
 
9.1%
4 11
 
8.3%
8 10
 
7.6%
6 9
 
6.8%
5 6
 
4.5%
7 6
 
4.5%
Space Separator
ValueCountFrequency (%)
192
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 706
67.5%
Common 334
31.9%
Latin 6
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 51
 
7.2%
상 47
 
6.7%
리 47
 
6.7%
경 44
 
6.2%
도 44
 
6.2%
산 28
 
4.0%
면 28
 
4.0%
시 28
 
4.0%
양 17
 
2.4%
군 15
 
2.1%
Other values (110) 357
50.6%
Common
ValueCountFrequency (%)
192
57.5%
1 33
 
9.9%
3 16
 
4.8%
2 16
 
4.8%
9 13
 
3.9%
0 12
 
3.6%
4 11
 
3.3%
- 10
 
3.0%
8 10
 
3.0%
6 9
 
2.7%
Other values (2) 12
 
3.6%
Latin
ValueCountFrequency (%)
C 6
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 706
67.5%
ASCII 340
32.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
192
56.5%
1 33
 
9.7%
3 16
 
4.7%
2 16
 
4.7%
9 13
 
3.8%
0 12
 
3.5%
4 11
 
3.2%
- 10
 
2.9%
8 10
 
2.9%
6 9
 
2.6%
Other values (3) 18
 
5.3%
Hangul
ValueCountFrequency (%)
남 51
 
7.2%
상 47
 
6.7%
리 47
 
6.7%
경 44
 
6.2%
도 44
 
6.2%
산 28
 
4.0%
면 28
 
4.0%
시 28
 
4.0%
양 17
 
2.4%
군 15
 
2.1%
Other values (110) 357
50.6%

우편번호
Real number (ℝ)

Distinct36
Distinct (%)83.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51349.884
Minimum50001
Maximum53284
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size515.0 B
2024-04-13T20:32:39.802274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum50001
5-th percentile50158.4
Q150470
median50850
Q352444
95-th percentile53071.3
Maximum53284
Range3283
Interquartile range (IQR)1974

Descriptive statistics

Standard deviation1052.3013
Coefficient of variation (CV)0.02049277
Kurtosis-1.4019842
Mean51349.884
Median Absolute Deviation (MAD)643
Skewness0.47103286
Sum2208045
Variance1107338.1
MonotonicityNot monotonic
2024-04-13T20:32:40.218825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
50540 2
 
4.7%
50811 2
 
4.7%
50416 2
 
4.7%
50337 2
 
4.7%
52433 2
 
4.7%
50584 2
 
4.7%
52506 2
 
4.7%
50001 1
 
2.3%
52455 1
 
2.3%
50119 1
 
2.3%
Other values (26) 26
60.5%
ValueCountFrequency (%)
50001 1
2.3%
50119 1
2.3%
50153 1
2.3%
50207 1
2.3%
50337 2
4.7%
50365 1
2.3%
50404 1
2.3%
50416 2
4.7%
50433 1
2.3%
50507 1
2.3%
ValueCountFrequency (%)
53284 1
2.3%
53200 1
2.3%
53085 1
2.3%
52948 1
2.3%
52916 1
2.3%
52622 1
2.3%
52544 1
2.3%
52509 1
2.3%
52506 2
4.7%
52455 1
2.3%

대표자명
Text

Distinct37
Distinct (%)86.0%
Missing0
Missing (%)0.0%
Memory size472.0 B
2024-04-13T20:32:41.010956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.0232558
Min length2

Characters and Unicode

Total characters130
Distinct characters62
Distinct categories1 ?
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 (%)72.1%

Sample

1st row신진기
2nd row최정호
3rd row최정호
4th row성세연
5th row류경규
ValueCountFrequency (%)
최정호 2
 
4.7%
이만규 2
 
4.7%
문성필 2
 
4.7%
김점동 2
 
4.7%
윤철지 2
 
4.7%
김영섭 2
 
4.7%
배영환 1
 
2.3%
최병호 1
 
2.3%
거창군수 1
 
2.3%
김점판 1
 
2.3%
Other values (27) 27
62.8%
2024-04-13T20:32:42.228903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 12
 
9.2%
호 6
 
4.6%
영 5
 
3.8%
이 5
 
3.8%
수 5
 
3.8%
최 4
 
3.1%
성 4
 
3.1%
정 4
 
3.1%
경 4
 
3.1%
문 3
 
2.3%
Other values (52) 78
60.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 130
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 12
 
9.2%
호 6
 
4.6%
영 5
 
3.8%
이 5
 
3.8%
수 5
 
3.8%
최 4
 
3.1%
성 4
 
3.1%
정 4
 
3.1%
경 4
 
3.1%
문 3
 
2.3%
Other values (52) 78
60.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 130
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 12
 
9.2%
호 6
 
4.6%
영 5
 
3.8%
이 5
 
3.8%
수 5
 
3.8%
최 4
 
3.1%
성 4
 
3.1%
정 4
 
3.1%
경 4
 
3.1%
문 3
 
2.3%
Other values (52) 78
60.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 130
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 12
 
9.2%
호 6
 
4.6%
영 5
 
3.8%
이 5
 
3.8%
수 5
 
3.8%
최 4
 
3.1%
성 4
 
3.1%
정 4
 
3.1%
경 4
 
3.1%
문 3
 
2.3%
Other values (52) 78
60.0%

기관연락처
Text

Distinct38
Distinct (%)88.4%
Missing0
Missing (%)0.0%
Memory size472.0 B
2024-04-13T20:32:42.975370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length11.976744
Min length9

Characters and Unicode

Total characters515
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)76.7%

Sample

1st row055-288-4112
2nd row055-552-0080
3rd row055-548-9999
4th row055-758-0400
5th row055-640-5000
ValueCountFrequency (%)
055-860-0555 2
 
4.7%
055-337-0091 2
 
4.7%
055-520-8000 2
 
4.7%
055-640-5000 2
 
4.7%
055-831-7000 2
 
4.7%
1666-0072 1
 
2.3%
055-930-7777 1
 
2.3%
055-945-2222 1
 
2.3%
055-808-7979 1
 
2.3%
055-960-7000 1
 
2.3%
Other values (28) 28
65.1%
2024-04-13T20:32:44.171139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 142
27.6%
5 109
21.2%
- 84
16.3%
3 37
 
7.2%
8 29
 
5.6%
7 27
 
5.2%
9 22
 
4.3%
1 19
 
3.7%
2 18
 
3.5%
4 14
 
2.7%
Other values (2) 14
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 430
83.5%
Dash Punctuation 84
 
16.3%
Space Separator 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 142
33.0%
5 109
25.3%
3 37
 
8.6%
8 29
 
6.7%
7 27
 
6.3%
9 22
 
5.1%
1 19
 
4.4%
2 18
 
4.2%
4 14
 
3.3%
6 13
 
3.0%
Dash Punctuation
ValueCountFrequency (%)
- 84
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 515
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 142
27.6%
5 109
21.2%
- 84
16.3%
3 37
 
7.2%
8 29
 
5.6%
7 27
 
5.2%
9 22
 
4.3%
1 19
 
3.7%
2 18
 
3.5%
4 14
 
2.7%
Other values (2) 14
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 515
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 142
27.6%
5 109
21.2%
- 84
16.3%
3 37
 
7.2%
8 29
 
5.6%
7 27
 
5.2%
9 22
 
4.3%
1 19
 
3.7%
2 18
 
3.5%
4 14
 
2.7%
Other values (2) 14
 
2.7%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size472.0 B
2024-04-08
43 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-04-08
2nd row2024-04-08
3rd row2024-04-08
4th row2024-04-08
5th row2024-04-08

Common Values

ValueCountFrequency (%)
2024-04-08 43
100.0%

Length

2024-04-13T20:32:44.570262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-13T20:32:44.879928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-04-08 43
100.0%

Interactions

2024-04-13T20:32:24.903005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:32:22.222772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:32:23.188363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:32:23.940893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:32:25.139847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:32:22.460349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:32:23.402162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:32:24.171010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:32:25.399477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:32:22.708079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:32:23.559334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:32:24.425462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:32:25.642015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:32:22.946704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:32:23.706568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T20:32:24.658361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-13T20:32:45.083391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번골프장명종류홀 또는 슬로프수면적(제곱미터)등록일자운영자소재지(도로명주소)소재지(지번주소)우편번호대표자명기관연락처
연번1.0001.0000.4920.0000.4711.0000.9901.0001.0000.8590.9910.988
골프장명1.0001.0000.8620.0000.9790.9991.0000.9990.9991.0001.0001.000
종류0.4920.8621.0000.3010.3330.9720.8900.9720.9720.5750.0000.920
홀 또는 슬로프수0.0000.0000.3011.0000.9000.9890.0000.9890.9890.0000.0000.000
면적(제곱미터)0.4710.9790.3330.9001.0000.9870.9660.9870.9870.0000.9520.974
등록일자1.0000.9990.9720.9890.9871.0001.0001.0001.0001.0001.0001.000
운영자0.9901.0000.8900.0000.9661.0001.0001.0001.0001.0001.0000.999
소재지(도로명주소)1.0000.9990.9720.9890.9871.0001.0001.0001.0001.0001.0001.000
소재지(지번주소)1.0000.9990.9720.9890.9871.0001.0001.0001.0001.0001.0001.000
우편번호0.8591.0000.5750.0000.0001.0001.0001.0001.0001.0001.0000.989
대표자명0.9911.0000.0000.0000.9521.0001.0001.0001.0001.0001.0000.997
기관연락처0.9881.0000.9200.0000.9741.0000.9991.0001.0000.9890.9971.000
2024-04-13T20:32:45.420431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번홀 또는 슬로프수면적(제곱미터)우편번호종류
연번1.000-0.217-0.169-0.3770.300
홀 또는 슬로프수-0.2171.0000.883-0.1710.227
면적(제곱미터)-0.1690.8831.000-0.1500.150
우편번호-0.377-0.171-0.1501.0000.292
종류0.3000.2270.1500.2921.000

Missing values

2024-04-13T20:32:26.010798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-13T20:32:26.575542image/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

연번골프장명종류홀 또는 슬로프수면적(제곱미터)등록일자운영자소재지(도로명주소)소재지(지번주소)우편번호대표자명기관연락처데이터기준일자
01창원 컨트리클럽회원제1810489591984-09-21(주)창원컨트리클럽창원시 의창구 대봉로 137경상남도 창원시 의창구 봉림동 647 창원컨트리클럽51160신진기055-288-41122024-04-08
12용원 컨트리클럽회원제2716358861991-11-08용원개발㈜창원시 진해구 가주로 133경상남도 창원시 진해구 용원동 산3951602최정호055-552-00802024-04-08
23아라미르골프앤리조트비회원제3614063631917-12-18㈜진해오션리조트창원시 진해구 수제로 36경상남도 창원시 진해구 제덕동 89851617최정호055-548-99992024-04-08
34진주 컨트리클럽대중제1810684811996-11-27진주개발㈜진주시 진성면 진성로 464번길 82경상남도 진주시 진성면 구천리 산10 진주 컨트리클럽52622성세연055-758-04002024-04-08
45통영동원로얄 컨트리클럽대중제189666192015-09-10동원관광개발㈜통영시 산양읍 담안길 240경상남도 통영시 산양읍 영운리 96553085류경규055-640-50002024-04-08
56서경타니 컨트리클럽대중제2712219292011-03-11서경타니골프앤리조트㈜사천시 곤양면 흥신로 210경상남도 사천시 곤양면 가화리 312 타니골프앤리조트52506윤철지055-831-70002024-04-08
67서경타니 컨트리클럽대중제94377252011-03-11서경타니골프앤리조트㈜사천시 곤양면 흥신로 210경상남도 사천시 곤양면 가화리 312 타니골프앤리조트52506윤철지055-831-70002024-04-08
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