Overview

Dataset statistics

Number of variables10
Number of observations51
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.2 KiB
Average record size in memory84.6 B

Variable types

Categorical2
Text4
Numeric2
DateTime2

Dataset

Description경상북도 골프장 관련 정보 현황(경상북도 운영중인 골프장명, 업체명, 업종, 면적, 위치, 전화번호 현황입니다. )
Author경상북도
URLhttps://www.data.go.kr/data/15028759/fileData.do

Alerts

면적(평방미터) is highly overall correlated with 업종High correlation
업종 is highly overall correlated with 면적(평방미터)High correlation
골프장명 has unique valuesUnique
등록번호 has unique valuesUnique
면적(평방미터) has unique valuesUnique

Reproduction

Analysis started2023-12-12 14:20:02.792598
Analysis finished2023-12-12 14:20:04.242509
Duration1.45 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

Distinct16
Distinct (%)31.4%
Missing0
Missing (%)0.0%
Memory size540.0 B
경주
12 
포항
4 
영천
4 
고령
4 
칠곡
4 
Other values (11)
23 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique3 ?
Unique (%)5.9%

Sample

1st row포항
2nd row포항
3rd row포항
4th row포항
5th row경주

Common Values

ValueCountFrequency (%)
경주 12
23.5%
포항 4
 
7.8%
영천 4
 
7.8%
고령 4
 
7.8%
칠곡 4
 
7.8%
안동 3
 
5.9%
구미 3
 
5.9%
의성 3
 
5.9%
청도 3
 
5.9%
김천 2
 
3.9%
Other values (6) 9
17.6%

Length

2023-12-12T23:20:04.300057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경주 12
23.5%
포항 4
 
7.8%
영천 4
 
7.8%
고령 4
 
7.8%
칠곡 4
 
7.8%
안동 3
 
5.9%
구미 3
 
5.9%
의성 3
 
5.9%
청도 3
 
5.9%
김천 2
 
3.9%
Other values (6) 9
17.6%

골프장명
Text

UNIQUE 

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
2023-12-12T23:20:04.541129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length7.4705882
Min length5

Characters and Unicode

Total characters381
Distinct characters115
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)100.0%

Sample

1st row오션힐스포항C.C(회18)
2nd row오션힐스포항C.C(대9)
3rd row청하이스턴C.C
4th row포항C.C
5th row경주신라C.C
ValueCountFrequency (%)
골프존카운티 3
 
5.3%
구미 2
 
3.5%
오션힐스포항c.c(회18 1
 
1.8%
청통골프장 1
 
1.8%
뉴스프링빌ⅱ 1
 
1.8%
문경레저타운골프장 1
 
1.8%
대구c.c 1
 
1.8%
인터불고컨트리클럽 1
 
1.8%
구니c.c 1
 
1.8%
군위오펠g.c 1
 
1.8%
Other values (44) 44
77.2%
2023-12-12T23:20:04.931056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
C 65
 
17.1%
. 34
 
8.9%
스 14
 
3.7%
프 11
 
2.9%
골 10
 
2.6%
G 9
 
2.4%
리 9
 
2.4%
오 8
 
2.1%
7
 
1.8%
힐 7
 
1.8%
Other values (105) 207
54.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 250
65.6%
Uppercase Letter 74
 
19.4%
Other Punctuation 35
 
9.2%
Space Separator 7
 
1.8%
Decimal Number 6
 
1.6%
Close Punctuation 4
 
1.0%
Open Punctuation 4
 
1.0%
Letter Number 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 14
 
5.6%
프 11
 
4.4%
골 10
 
4.0%
리 9
 
3.6%
오 8
 
3.2%
힐 7
 
2.8%
럽 6
 
2.4%
이 6
 
2.4%
클 6
 
2.4%
미 5
 
2.0%
Other values (94) 168
67.2%
Decimal Number
ValueCountFrequency (%)
1 2
33.3%
8 2
33.3%
9 2
33.3%
Uppercase Letter
ValueCountFrequency (%)
C 65
87.8%
G 9
 
12.2%
Other Punctuation
ValueCountFrequency (%)
. 34
97.1%
& 1
 
2.9%
Space Separator
ValueCountFrequency (%)
7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 250
65.6%
Latin 75
 
19.7%
Common 56
 
14.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 14
 
5.6%
프 11
 
4.4%
골 10
 
4.0%
리 9
 
3.6%
오 8
 
3.2%
힐 7
 
2.8%
럽 6
 
2.4%
이 6
 
2.4%
클 6
 
2.4%
미 5
 
2.0%
Other values (94) 168
67.2%
Common
ValueCountFrequency (%)
. 34
60.7%
7
 
12.5%
) 4
 
7.1%
( 4
 
7.1%
1 2
 
3.6%
8 2
 
3.6%
9 2
 
3.6%
& 1
 
1.8%
Latin
ValueCountFrequency (%)
C 65
86.7%
G 9
 
12.0%
Ⅱ 1
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 250
65.6%
ASCII 130
34.1%
Number Forms 1
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
C 65
50.0%
. 34
26.2%
G 9
 
6.9%
7
 
5.4%
) 4
 
3.1%
( 4
 
3.1%
1 2
 
1.5%
8 2
 
1.5%
9 2
 
1.5%
& 1
 
0.8%
Hangul
ValueCountFrequency (%)
스 14
 
5.6%
프 11
 
4.4%
골 10
 
4.0%
리 9
 
3.6%
오 8
 
3.2%
힐 7
 
2.8%
럽 6
 
2.4%
이 6
 
2.4%
클 6
 
2.4%
미 5
 
2.0%
Other values (94) 168
67.2%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

업체명
Text

Distinct48
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Memory size540.0 B
2023-12-12T23:20:05.449242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length15
Mean length10.843137
Min length7

Characters and Unicode

Total characters553
Distinct characters170
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)88.2%

Sample

1st row오션힐스골프앤리조트㈜ 김도균
2nd row오션힐스골프앤리조트㈜ 김도균
3rd row㈜이스턴 이일선
4th row㈜홍익레저산업 안추봉
5th row㈜경주신라CC 김철년, 손설호
ValueCountFrequency (%)
서상현 4
 
3.7%
김도균 3
 
2.8%
김성조 2
 
1.8%
이정익 2
 
1.8%
오션힐스골프앤리조트㈜ 2
 
1.8%
경북문화관광공사 2
 
1.8%
윤재연 2
 
1.8%
㈜블루원 2
 
1.8%
케이알스포츠㈜ 1
 
0.9%
최정헌 1
 
0.9%
Other values (88) 88
80.7%
2023-12-12T23:20:05.829227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
60
 
10.8%
㈜ 50
 
9.0%
이 14
 
2.5%
발 14
 
2.5%
개 14
 
2.5%
김 12
 
2.2%
리 9
 
1.6%
스 8
 
1.4%
문 8
 
1.4%
상 7
 
1.3%
Other values (160) 357
64.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 432
78.1%
Space Separator 60
 
10.8%
Other Symbol 50
 
9.0%
Other Punctuation 7
 
1.3%
Uppercase Letter 4
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 14
 
3.2%
발 14
 
3.2%
개 14
 
3.2%
김 12
 
2.8%
리 9
 
2.1%
스 8
 
1.9%
문 8
 
1.9%
상 7
 
1.6%
오 7
 
1.6%
정 6
 
1.4%
Other values (154) 333
77.1%
Other Punctuation
ValueCountFrequency (%)
, 6
85.7%
. 1
 
14.3%
Uppercase Letter
ValueCountFrequency (%)
C 3
75.0%
G 1
 
25.0%
Space Separator
ValueCountFrequency (%)
60
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 50
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 482
87.2%
Common 67
 
12.1%
Latin 4
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 50
 
10.4%
이 14
 
2.9%
발 14
 
2.9%
개 14
 
2.9%
김 12
 
2.5%
리 9
 
1.9%
스 8
 
1.7%
문 8
 
1.7%
상 7
 
1.5%
오 7
 
1.5%
Other values (155) 339
70.3%
Common
ValueCountFrequency (%)
60
89.6%
, 6
 
9.0%
. 1
 
1.5%
Latin
ValueCountFrequency (%)
C 3
75.0%
G 1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 432
78.1%
ASCII 71
 
12.8%
None 50
 
9.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
60
84.5%
, 6
 
8.5%
C 3
 
4.2%
. 1
 
1.4%
G 1
 
1.4%
None
ValueCountFrequency (%)
㈜ 50
100.0%
Hangul
ValueCountFrequency (%)
이 14
 
3.2%
발 14
 
3.2%
개 14
 
3.2%
김 12
 
2.8%
리 9
 
2.1%
스 8
 
1.9%
문 8
 
1.9%
상 7
 
1.6%
오 7
 
1.6%
정 6
 
1.4%
Other values (154) 333
77.1%

등록번호
Real number (ℝ)

UNIQUE 

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51.333333
Minimum1
Maximum82
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size591.0 B
2023-12-12T23:20:05.956448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q140.5
median55
Q368.5
95-th percentile79.5
Maximum82
Range81
Interquartile range (IQR)28

Descriptive statistics

Standard deviation22.132932
Coefficient of variation (CV)0.43116101
Kurtosis-0.091888598
Mean51.333333
Median Absolute Deviation (MAD)14
Skewness-0.75244726
Sum2618
Variance489.86667
MonotonicityNot monotonic
2023-12-12T23:20:06.087973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37 1
 
2.0%
51 1
 
2.0%
52 1
 
2.0%
53 1
 
2.0%
43 1
 
2.0%
1 1
 
2.0%
50 1
 
2.0%
59 1
 
2.0%
69 1
 
2.0%
71 1
 
2.0%
Other values (41) 41
80.4%
ValueCountFrequency (%)
1 1
2.0%
2 1
2.0%
3 1
2.0%
5 1
2.0%
11 1
2.0%
20 1
2.0%
26 1
2.0%
27 1
2.0%
28 1
2.0%
33 1
2.0%
ValueCountFrequency (%)
82 1
2.0%
81 1
2.0%
80 1
2.0%
79 1
2.0%
78 1
2.0%
77 1
2.0%
76 1
2.0%
75 1
2.0%
74 1
2.0%
73 1
2.0%

업종
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)15.7%
Missing0
Missing (%)0.0%
Memory size540.0 B
대18홀
20 
대 9홀
12 
회18홀
5 
회27홀
5 
대27홀
4 
Other values (3)
5 

Length

Max length4
Median length4
Mean length3.9607843
Min length3

Unique

Unique1 ?
Unique (%)2.0%

Sample

1st row회18홀
2nd row대9홀
3rd row대 9홀
4th row대18홀
5th row회36홀

Common Values

ValueCountFrequency (%)
대18홀 20
39.2%
대 9홀 12
23.5%
회18홀 5
 
9.8%
회27홀 5
 
9.8%
대27홀 4
 
7.8%
대9홀 2
 
3.9%
회36홀 2
 
3.9%
대36홀 1
 
2.0%

Length

2023-12-12T23:20:06.200681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:20:06.290818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대18홀 20
31.7%
대 12
19.0%
9홀 12
19.0%
회18홀 5
 
7.9%
회27홀 5
 
7.9%
대27홀 4
 
6.3%
대9홀 2
 
3.2%
회36홀 2
 
3.2%
대36홀 1
 
1.6%

면적(평방미터)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean912823.74
Minimum175806
Maximum2094223
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size591.0 B
2023-12-12T23:20:06.403656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum175806
5-th percentile241484.5
Q1491664.75
median977678
Q31080860.5
95-th percentile1786886.5
Maximum2094223
Range1918417
Interquartile range (IQR)589195.75

Descriptive statistics

Standard deviation461980.56
Coefficient of variation (CV)0.50610051
Kurtosis0.057637466
Mean912823.74
Median Absolute Deviation (MAD)333843
Skewness0.46920523
Sum46554011
Variance2.1342604 × 1011
MonotonicityNot monotonic
2023-12-12T23:20:06.541916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
918976.5 1
 
2.0%
400940.0 1
 
2.0%
1038679.0 1
 
2.0%
1081418.0 1
 
2.0%
1022039.0 1
 
2.0%
1080303.0 1
 
2.0%
1697091.0 1
 
2.0%
841556.0 1
 
2.0%
999080.0 1
 
2.0%
957974.0 1
 
2.0%
Other values (41) 41
80.4%
ValueCountFrequency (%)
175806.0 1
2.0%
186373.1 1
2.0%
238597.0 1
2.0%
244372.0 1
2.0%
249315.0 1
2.0%
375038.9 1
2.0%
385623.0 1
2.0%
400940.0 1
2.0%
404646.0 1
2.0%
428970.0 1
2.0%
ValueCountFrequency (%)
2094223.0 1
2.0%
1979892.0 1
2.0%
1876682.0 1
2.0%
1697091.0 1
2.0%
1465851.0 1
2.0%
1461103.0 1
2.0%
1410518.0 1
2.0%
1363308.0 1
2.0%
1332592.0 1
2.0%
1311521.0 1
2.0%

승인일
Date

Distinct49
Distinct (%)96.1%
Missing0
Missing (%)0.0%
Memory size540.0 B
Minimum1971-06-11 00:00:00
Maximum2019-11-21 00:00:00
2023-12-12T23:20:06.666334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:06.831106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)

등록일
Date

Distinct49
Distinct (%)96.1%
Missing0
Missing (%)0.0%
Memory size540.0 B
Minimum1975-03-13 00:00:00
Maximum2021-08-03 00:00:00
2023-12-12T23:20:06.986531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:07.134783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)

위치
Text

Distinct49
Distinct (%)96.1%
Missing0
Missing (%)0.0%
Memory size540.0 B
2023-12-12T23:20:07.460046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length19
Mean length17.215686
Min length14

Characters and Unicode

Total characters878
Distinct characters123
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)92.2%

Sample

1st row포항시 북구 송라면 대전길 7
2nd row포항시 북구 송라면 대전길 7
3rd row포항시 청하면 용산길 94
4th row포항시 송라면 동해대로 2751번길 126
5th row경주시 보문로 319(신평동)
ValueCountFrequency (%)
경주시 12
 
5.9%
포항시 4
 
2.0%
칠곡군 4
 
2.0%
영천시 4
 
2.0%
고령군 4
 
2.0%
의성군 3
 
1.5%
보문로 3
 
1.5%
안동시 3
 
1.5%
봉양면 3
 
1.5%
청도군 3
 
1.5%
Other values (135) 162
79.0%
2023-12-12T23:20:07.967832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
154
 
17.5%
1 38
 
4.3%
로 34
 
3.9%
면 34
 
3.9%
시 33
 
3.8%
2 31
 
3.5%
7 26
 
3.0%
군 25
 
2.8%
- 21
 
2.4%
동 20
 
2.3%
Other values (113) 462
52.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 487
55.5%
Decimal Number 202
23.0%
Space Separator 154
 
17.5%
Dash Punctuation 21
 
2.4%
Open Punctuation 7
 
0.8%
Close Punctuation 7
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 34
 
7.0%
면 34
 
7.0%
시 33
 
6.8%
군 25
 
5.1%
동 20
 
4.1%
경 17
 
3.5%
길 17
 
3.5%
주 14
 
2.9%
천 13
 
2.7%
산 13
 
2.7%
Other values (99) 267
54.8%
Decimal Number
ValueCountFrequency (%)
1 38
18.8%
2 31
15.3%
7 26
12.9%
3 19
9.4%
4 18
8.9%
8 18
8.9%
5 17
8.4%
9 16
7.9%
0 11
 
5.4%
6 8
 
4.0%
Space Separator
ValueCountFrequency (%)
154
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 487
55.5%
Common 391
44.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 34
 
7.0%
면 34
 
7.0%
시 33
 
6.8%
군 25
 
5.1%
동 20
 
4.1%
경 17
 
3.5%
길 17
 
3.5%
주 14
 
2.9%
천 13
 
2.7%
산 13
 
2.7%
Other values (99) 267
54.8%
Common
ValueCountFrequency (%)
154
39.4%
1 38
 
9.7%
2 31
 
7.9%
7 26
 
6.6%
- 21
 
5.4%
3 19
 
4.9%
4 18
 
4.6%
8 18
 
4.6%
5 17
 
4.3%
9 16
 
4.1%
Other values (4) 33
 
8.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 487
55.5%
ASCII 391
44.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
154
39.4%
1 38
 
9.7%
2 31
 
7.9%
7 26
 
6.6%
- 21
 
5.4%
3 19
 
4.9%
4 18
 
4.6%
8 18
 
4.6%
5 17
 
4.3%
9 16
 
4.1%
Other values (4) 33
 
8.4%
Hangul
ValueCountFrequency (%)
로 34
 
7.0%
면 34
 
7.0%
시 33
 
6.8%
군 25
 
5.1%
동 20
 
4.1%
경 17
 
3.5%
길 17
 
3.5%
주 14
 
2.9%
천 13
 
2.7%
산 13
 
2.7%
Other values (99) 267
54.8%

전화번호
Text

Distinct49
Distinct (%)96.1%
Missing0
Missing (%)0.0%
Memory size540.0 B
2023-12-12T23:20:08.230587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length8
Mean length8.1568627
Min length8

Characters and Unicode

Total characters416
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

Unique47 ?
Unique (%)92.2%

Sample

1st row260-7060
2nd row260-7060
3rd row253-0070
4th row230-2013
5th row740-7013
ValueCountFrequency (%)
260-7060 2
 
3.9%
470-3513 2
 
3.9%
970-3715 1
 
2.0%
730-9071 1
 
2.0%
940-9700 1
 
2.0%
833-1545 1
 
2.0%
830-3314 1
 
2.0%
450-2812 1
 
2.0%
550-5023 1
 
2.0%
053-859-5230 1
 
2.0%
Other values (39) 39
76.5%
2023-12-12T23:20:08.752057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 99
23.8%
- 53
12.7%
7 48
11.5%
3 47
11.3%
5 31
 
7.5%
1 29
 
7.0%
8 27
 
6.5%
9 26
 
6.2%
2 22
 
5.3%
4 18
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 363
87.3%
Dash Punctuation 53
 
12.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 99
27.3%
7 48
13.2%
3 47
12.9%
5 31
 
8.5%
1 29
 
8.0%
8 27
 
7.4%
9 26
 
7.2%
2 22
 
6.1%
4 18
 
5.0%
6 16
 
4.4%
Dash Punctuation
ValueCountFrequency (%)
- 53
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 416
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 99
23.8%
- 53
12.7%
7 48
11.5%
3 47
11.3%
5 31
 
7.5%
1 29
 
7.0%
8 27
 
6.5%
9 26
 
6.2%
2 22
 
5.3%
4 18
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 416
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 99
23.8%
- 53
12.7%
7 48
11.5%
3 47
11.3%
5 31
 
7.5%
1 29
 
7.0%
8 27
 
6.5%
9 26
 
6.2%
2 22
 
5.3%
4 18
 
4.3%

Interactions

2023-12-12T23:20:03.812538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:03.604101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:03.904078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:03.712838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:20:08.886454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분골프장명업체명등록번호업종면적(평방미터)승인일등록일위치전화번호
구분1.0001.0000.9840.3780.0000.0000.9880.9841.0001.000
골프장명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
업체명0.9841.0001.0000.7680.7420.9140.9690.9690.9950.995
등록번호0.3781.0000.7681.0000.5190.6671.0000.9840.9700.970
업종0.0001.0000.7420.5191.0000.8270.9900.9250.0000.000
면적(평방미터)0.0001.0000.9140.6670.8271.0000.8950.8040.9650.965
승인일0.9881.0000.9691.0000.9900.8951.0000.9880.9990.988
등록일0.9841.0000.9690.9840.9250.8040.9881.0000.9880.988
위치1.0001.0000.9950.9700.0000.9650.9990.9881.0000.999
전화번호1.0001.0000.9950.9700.0000.9650.9880.9880.9991.000
2023-12-12T23:20:09.017750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분업종
구분1.0000.000
업종0.0001.000
2023-12-12T23:20:09.101043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록번호면적(평방미터)구분업종
등록번호1.000-0.2660.1190.266
면적(평방미터)-0.2661.0000.0000.578
구분0.1190.0001.0000.000
업종0.2660.5780.0001.000

Missing values

2023-12-12T23:20:04.029856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:20:04.191630image/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

구분골프장명업체명등록번호업종면적(평방미터)승인일등록일위치전화번호
0포항오션힐스포항C.C(회18)오션힐스골프앤리조트㈜ 김도균37회18홀918976.51989-10-232005-11-04포항시 북구 송라면 대전길 7260-7060
1포항오션힐스포항C.C(대9)오션힐스골프앤리조트㈜ 김도균51대9홀400940.02005-11-032008-03-12포항시 북구 송라면 대전길 7260-7060
2포항청하이스턴C.C㈜이스턴 이일선46대 9홀238597.02006-07-142007-08-10포항시 청하면 용산길 94253-0070
3포항포항C.C㈜홍익레저산업 안추봉60대18홀986443.02003-12-262009-08-05포항시 송라면 동해대로 2751번길 126230-2013
4경주경주신라C.C㈜경주신라CC 김철년, 손설호2회36홀1876682.01976-12-291979-09-26경주시 보문로 319(신평동)740-7013
5경주보문G.C경북문화관광공사 김성조3대18홀769499.01985-12-061987-10-21경주시 보문로 182-14 (북군동)745-1680
6경주경주C.C보문개발㈜ 박흥국11대27홀1461103.01990-10-201992-02-21경주시 보문로 182-98 (북군동)778-8918
7경주마우나오션C.C㈜엠오디 장재혁27회18홀789188.01996-10-311999-07-01경주시 양남면 동남로 982740-0602
8경주가든골프클럽㈜코오롱글로텍 김영범5대 9홀175806.01987-03-191988-08-24경주시 불국로 289-17(마동)740-5161
9경주우리G.C㈜퍼블릭개발 임태수33대 9홀442362.02001-08-292003-09-15경주시 양남면 동남로 972740-0805
구분골프장명업체명등록번호업종면적(평방미터)승인일등록일위치전화번호
41청도펜타뷰골프클럽아리유㈜ 이건순77대 9홀249315.02014-09-052016-04-07청도군 금천면 금천로 709516-8001
42고령유니밸리C.C고령컨트리클럽㈜ 박선자55대 9홀385623.02006-10-122008-09-09고령군 고령읍 일량로 588956-7576
43고령마스터피스CC㈜누가개발 김인자76대18홀1034362.02014-05-292015-11-18고령군 쌍림면 산막길 47-80950-2470
44고령대가야CC㈜흥진레저 심병재79대 9홀469310.92014-09-252019-04-15고령군 대가야읍 대가야로 1103956-0009
45고령다산 샤인힐CC두강건설㈜ 이정익80대18홀984323.02016-08-222019-10-08고령군 다산면 벌지로 175-115950-5000
46칠곡파미힐스C.C㈜한길 장문익, 설정수, 차현욱20회36홀2094223.01989-06-291993-03-16칠곡군 왜관읍 봉계로 263971-9900
47칠곡구미 마이다스 골프아카데미㈜대교디앤에스 최득희56대 9홀428970.02005-05-302008-09-18칠곡군 가산면 학하2길 54-171970-3715
48칠곡세븐밸리C.C㈜세블밸리제이씨 유진선61대18홀941849.02007-09-272009-09-29칠곡군 왜관읍 봉계3길 180979-9808
49칠곡칠곡아이위시C.C㈜동화레져 문종혁82대9홀375038.92018-07-192021-08-03칠곡군 기산면 노석1길 49-112940-9700
50예천한맥C.C&노블리아한맥개발㈜ 임기주57대18홀1000226.02006-05-152008-12-26예천군 호명면 한맥 골프장길 72650-7033