Overview

Dataset statistics

Number of variables7
Number of observations128
Missing cells73
Missing cells (%)8.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.4 KiB
Average record size in memory59.0 B

Variable types

Text4
Categorical1
Numeric2

Dataset

Description달성군 내에 운영되고 있는 골프장, 헬스장, 가상체험 시설 등의 업소명, 도로명 주소 등의 현황을 포함하고 있는 데이터입니다.
URLhttps://www.data.go.kr/data/15093669/fileData.do

Alerts

위도 is highly overall correlated with 경도High correlation
경도 is highly overall correlated with 위도High correlation
전화번호 has 9 (7.0%) missing valuesMissing
영업시간 has 64 (50.0%) missing valuesMissing

Reproduction

Analysis started2023-12-12 15:31:10.103447
Analysis finished2023-12-12 15:31:11.761174
Duration1.66 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

Distinct100
Distinct (%)78.1%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-13T00:31:11.969096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length13
Mean length7.9296875
Min length3

Characters and Unicode

Total characters1015
Distinct characters183
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique72 ?
Unique (%)56.2%

Sample

1st row동아헬스
2nd row서재헬스
3rd row새롬헬스
4th row나우 휘트니스 클럽
5th row장수휘트니스클럽
ValueCountFrequency (%)
스크린골프 5
 
2.5%
gym 4
 
2.0%
주식회사 4
 
2.0%
스크린 4
 
2.0%
다사점 3
 
1.5%
다사 3
 
1.5%
임팩트 3
 
1.5%
화원점 3
 
1.5%
헬스위드짐 2
 
1.0%
유황원스타 2
 
1.0%
Other values (125) 164
83.2%
2023-12-13T00:31:12.437398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 74
 
7.3%
69
 
6.8%
골 69
 
6.8%
프 68
 
6.7%
크 41
 
4.0%
린 38
 
3.7%
장 26
 
2.6%
연 23
 
2.3%
습 22
 
2.2%
이 17
 
1.7%
Other values (173) 568
56.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 825
81.3%
Uppercase Letter 85
 
8.4%
Space Separator 69
 
6.8%
Lowercase Letter 16
 
1.6%
Decimal Number 9
 
0.9%
Close Punctuation 5
 
0.5%
Open Punctuation 5
 
0.5%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 74
 
9.0%
골 69
 
8.4%
프 68
 
8.2%
크 41
 
5.0%
린 38
 
4.6%
장 26
 
3.2%
연 23
 
2.8%
습 22
 
2.7%
이 17
 
2.1%
점 16
 
1.9%
Other values (136) 431
52.2%
Uppercase Letter
ValueCountFrequency (%)
G 14
16.5%
M 9
10.6%
S 8
 
9.4%
J 8
 
9.4%
T 6
 
7.1%
P 5
 
5.9%
Y 5
 
5.9%
D 4
 
4.7%
C 3
 
3.5%
O 3
 
3.5%
Other values (9) 20
23.5%
Lowercase Letter
ValueCountFrequency (%)
h 3
18.8%
a 3
18.8%
g 2
12.5%
m 2
12.5%
y 1
 
6.2%
o 1
 
6.2%
k 1
 
6.2%
n 1
 
6.2%
r 1
 
6.2%
e 1
 
6.2%
Decimal Number
ValueCountFrequency (%)
4 3
33.3%
1 3
33.3%
2 2
22.2%
5 1
 
11.1%
Space Separator
ValueCountFrequency (%)
69
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 825
81.3%
Latin 101
 
10.0%
Common 89
 
8.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 74
 
9.0%
골 69
 
8.4%
프 68
 
8.2%
크 41
 
5.0%
린 38
 
4.6%
장 26
 
3.2%
연 23
 
2.8%
습 22
 
2.7%
이 17
 
2.1%
점 16
 
1.9%
Other values (136) 431
52.2%
Latin
ValueCountFrequency (%)
G 14
 
13.9%
M 9
 
8.9%
S 8
 
7.9%
J 8
 
7.9%
T 6
 
5.9%
P 5
 
5.0%
Y 5
 
5.0%
D 4
 
4.0%
C 3
 
3.0%
O 3
 
3.0%
Other values (19) 36
35.6%
Common
ValueCountFrequency (%)
69
77.5%
) 5
 
5.6%
( 5
 
5.6%
4 3
 
3.4%
1 3
 
3.4%
2 2
 
2.2%
5 1
 
1.1%
. 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 825
81.3%
ASCII 190
 
18.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 74
 
9.0%
골 69
 
8.4%
프 68
 
8.2%
크 41
 
5.0%
린 38
 
4.6%
장 26
 
3.2%
연 23
 
2.8%
습 22
 
2.7%
이 17
 
2.1%
점 16
 
1.9%
Other values (136) 431
52.2%
ASCII
ValueCountFrequency (%)
69
36.3%
G 14
 
7.4%
M 9
 
4.7%
S 8
 
4.2%
J 8
 
4.2%
T 6
 
3.2%
P 5
 
2.6%
Y 5
 
2.6%
) 5
 
2.6%
( 5
 
2.6%
Other values (27) 56
29.5%

업종
Categorical

Distinct5
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
골프연습장업
58 
체력단련장업
51 
가상체험 체육시설업
16 
종합체육시설업
 
2
무도학원업
 
1

Length

Max length10
Median length6
Mean length6.5078125
Min length5

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
골프연습장업 58
45.3%
체력단련장업 51
39.8%
가상체험 체육시설업 16
 
12.5%
종합체육시설업 2
 
1.6%
무도학원업 1
 
0.8%

Length

2023-12-13T00:31:12.587252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:31:12.716302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
골프연습장업 58
40.3%
체력단련장업 51
35.4%
가상체험 16
 
11.1%
체육시설업 16
 
11.1%
종합체육시설업 2
 
1.4%
무도학원업 1
 
0.7%

소재지
Text

Distinct101
Distinct (%)78.9%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-13T00:31:13.132911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length36
Mean length27.195312
Min length19

Characters and Unicode

Total characters3481
Distinct characters120
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)57.8%

Sample

1st row대구광역시 달성군 논공읍 논공로 749, 6층
2nd row대구광역시 달성군 다사읍 서재로 141, 4층
3rd row대구광역시 달성군 화원읍 비슬로 2508
4th row대구광역시 달성군 논공읍 논공로5길 229, 2층
5th row대구광역시 달성군 현풍읍 현풍중앙로14길 71
ValueCountFrequency (%)
대구광역시 128
 
16.8%
달성군 128
 
16.8%
다사읍 48
 
6.3%
유가읍 20
 
2.6%
화원읍 18
 
2.4%
3층 15
 
2.0%
2층 14
 
1.8%
현풍읍 13
 
1.7%
논공읍 10
 
1.3%
옥포읍 10
 
1.3%
Other values (185) 359
47.1%
2023-12-13T00:31:13.678614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
635
 
18.2%
대 155
 
4.5%
구 146
 
4.2%
달 142
 
4.1%
성 139
 
4.0%
역 132
 
3.8%
광 131
 
3.8%
시 129
 
3.7%
군 129
 
3.7%
읍 119
 
3.4%
Other values (110) 1624
46.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2180
62.6%
Space Separator 635
 
18.2%
Decimal Number 542
 
15.6%
Other Punctuation 83
 
2.4%
Dash Punctuation 23
 
0.7%
Math Symbol 14
 
0.4%
Uppercase Letter 2
 
0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 155
 
7.1%
구 146
 
6.7%
달 142
 
6.5%
성 139
 
6.4%
역 132
 
6.1%
광 131
 
6.0%
시 129
 
5.9%
군 129
 
5.9%
읍 119
 
5.5%
로 108
 
5.0%
Other values (93) 850
39.0%
Decimal Number
ValueCountFrequency (%)
2 90
16.6%
1 86
15.9%
4 69
12.7%
3 68
12.5%
5 53
9.8%
6 46
8.5%
7 38
7.0%
0 36
 
6.6%
8 31
 
5.7%
9 25
 
4.6%
Space Separator
ValueCountFrequency (%)
635
100.0%
Other Punctuation
ValueCountFrequency (%)
, 83
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%
Math Symbol
ValueCountFrequency (%)
~ 14
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2180
62.6%
Common 1299
37.3%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 155
 
7.1%
구 146
 
6.7%
달 142
 
6.5%
성 139
 
6.4%
역 132
 
6.1%
광 131
 
6.0%
시 129
 
5.9%
군 129
 
5.9%
읍 119
 
5.5%
로 108
 
5.0%
Other values (93) 850
39.0%
Common
ValueCountFrequency (%)
635
48.9%
2 90
 
6.9%
1 86
 
6.6%
, 83
 
6.4%
4 69
 
5.3%
3 68
 
5.2%
5 53
 
4.1%
6 46
 
3.5%
7 38
 
2.9%
0 36
 
2.8%
Other values (6) 95
 
7.3%
Latin
ValueCountFrequency (%)
A 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2180
62.6%
ASCII 1301
37.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
635
48.8%
2 90
 
6.9%
1 86
 
6.6%
, 83
 
6.4%
4 69
 
5.3%
3 68
 
5.2%
5 53
 
4.1%
6 46
 
3.5%
7 38
 
2.9%
0 36
 
2.8%
Other values (7) 97
 
7.5%
Hangul
ValueCountFrequency (%)
대 155
 
7.1%
구 146
 
6.7%
달 142
 
6.5%
성 139
 
6.4%
역 132
 
6.1%
광 131
 
6.0%
시 129
 
5.9%
군 129
 
5.9%
읍 119
 
5.5%
로 108
 
5.0%
Other values (93) 850
39.0%

전화번호
Text

MISSING 

Distinct91
Distinct (%)76.5%
Missing9
Missing (%)7.0%
Memory size1.1 KiB
2023-12-13T00:31:13.982867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.966387
Min length12

Characters and Unicode

Total characters1543
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

Unique66 ?
Unique (%)55.5%

Sample

1st row053-616-6464
2nd row0507-1348-6004
3rd row053-638-4386
4th row053-614-0255
5th row0507-1338-5512
ValueCountFrequency (%)
0507-1307-9788 3
 
2.5%
053-611-3991 3
 
2.5%
053-656-7700 3
 
2.5%
0507-1387-9314 2
 
1.7%
053-242-0775 2
 
1.7%
0507-1404-5847 2
 
1.7%
0507-1309-5393 2
 
1.7%
053-644-0750 2
 
1.7%
0507-1307-0319 2
 
1.7%
0507-1340-0753 2
 
1.7%
Other values (83) 98
81.0%
2023-12-13T00:31:14.416431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 292
18.9%
- 238
15.4%
5 224
14.5%
3 154
10.0%
7 150
9.7%
1 145
9.4%
6 79
 
5.1%
4 77
 
5.0%
8 63
 
4.1%
2 61
 
4.0%
Other values (2) 60
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1303
84.4%
Dash Punctuation 238
 
15.4%
Space Separator 2
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 292
22.4%
5 224
17.2%
3 154
11.8%
7 150
11.5%
1 145
11.1%
6 79
 
6.1%
4 77
 
5.9%
8 63
 
4.8%
2 61
 
4.7%
9 58
 
4.5%
Dash Punctuation
ValueCountFrequency (%)
- 238
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1543
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 292
18.9%
- 238
15.4%
5 224
14.5%
3 154
10.0%
7 150
9.7%
1 145
9.4%
6 79
 
5.1%
4 77
 
5.0%
8 63
 
4.1%
2 61
 
4.0%
Other values (2) 60
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1543
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 292
18.9%
- 238
15.4%
5 224
14.5%
3 154
10.0%
7 150
9.7%
1 145
9.4%
6 79
 
5.1%
4 77
 
5.0%
8 63
 
4.1%
2 61
 
4.0%
Other values (2) 60
 
3.9%

영업시간
Text

MISSING 

Distinct54
Distinct (%)84.4%
Missing64
Missing (%)50.0%
Memory size1.1 KiB
2023-12-13T00:31:14.633083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length95
Median length79
Mean length32.9375
Min length14

Characters and Unicode

Total characters2108
Distinct characters69
Distinct categories8 ?
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 (%)73.4%

Sample

1st row평일 05:30 - 23:00, 토요일 05:30 - 21:00, 일요일 휴무
2nd row평일 06:00 - 24:00
3rd row매일 6:30-21:30, 매주 화요일 휴관
4th row평일 06:00 - 22:00
5th row평일 06:00 - 22:00 (사우나, 헬스), 매일 10:00 - 00:00 (골프), 주말 06:00 - 18:00 (헬스)
ValueCountFrequency (%)
100
20.9%
매일 33
 
6.9%
평일 30
 
6.3%
06:00 22
 
4.6%
09:00 22
 
4.6%
00:00 20
 
4.2%
10:00 19
 
4.0%
토요일 18
 
3.8%
23:00 16
 
3.3%
일요일 16
 
3.3%
Other values (55) 183
38.2%
2023-12-13T00:31:15.052233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 535
25.4%
421
20.0%
: 207
 
9.8%
일 142
 
6.7%
- 103
 
4.9%
2 81
 
3.8%
, 63
 
3.0%
1 54
 
2.6%
휴 49
 
2.3%
요 44
 
2.1%
Other values (59) 409
19.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 822
39.0%
Other Letter 474
22.5%
Space Separator 421
20.0%
Other Punctuation 273
 
13.0%
Dash Punctuation 103
 
4.9%
Open Punctuation 6
 
0.3%
Close Punctuation 6
 
0.3%
Math Symbol 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
일 142
30.0%
휴 49
 
10.3%
요 44
 
9.3%
매 38
 
8.0%
평 30
 
6.3%
무 24
 
5.1%
토 19
 
4.0%
공 18
 
3.8%
주 14
 
3.0%
연 8
 
1.7%
Other values (41) 88
18.6%
Decimal Number
ValueCountFrequency (%)
0 535
65.1%
2 81
 
9.9%
1 54
 
6.6%
3 41
 
5.0%
9 33
 
4.0%
6 24
 
2.9%
8 23
 
2.8%
4 15
 
1.8%
7 9
 
1.1%
5 7
 
0.9%
Other Punctuation
ValueCountFrequency (%)
: 207
75.8%
, 63
 
23.1%
/ 3
 
1.1%
Space Separator
ValueCountFrequency (%)
421
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 103
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1634
77.5%
Hangul 474
 
22.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
일 142
30.0%
휴 49
 
10.3%
요 44
 
9.3%
매 38
 
8.0%
평 30
 
6.3%
무 24
 
5.1%
토 19
 
4.0%
공 18
 
3.8%
주 14
 
3.0%
연 8
 
1.7%
Other values (41) 88
18.6%
Common
ValueCountFrequency (%)
0 535
32.7%
421
25.8%
: 207
 
12.7%
- 103
 
6.3%
2 81
 
5.0%
, 63
 
3.9%
1 54
 
3.3%
3 41
 
2.5%
9 33
 
2.0%
6 24
 
1.5%
Other values (8) 72
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1634
77.5%
Hangul 474
 
22.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 535
32.7%
421
25.8%
: 207
 
12.7%
- 103
 
6.3%
2 81
 
5.0%
, 63
 
3.9%
1 54
 
3.3%
3 41
 
2.5%
9 33
 
2.0%
6 24
 
1.5%
Other values (8) 72
 
4.4%
Hangul
ValueCountFrequency (%)
일 142
30.0%
휴 49
 
10.3%
요 44
 
9.3%
매 38
 
8.0%
평 30
 
6.3%
무 24
 
5.1%
토 19
 
4.0%
공 18
 
3.8%
주 14
 
3.0%
연 8
 
1.7%
Other values (41) 88
18.6%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct122
Distinct (%)95.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.786216
Minimum35.640102
Maximum35.887263
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-13T00:31:15.204891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.640102
5-th percentile35.674596
Q135.696336
median35.79865
Q335.85877
95-th percentile35.874674
Maximum35.887263
Range0.247161
Interquartile range (IQR)0.1624345

Descriptive statistics

Standard deviation0.076411312
Coefficient of variation (CV)0.0021352163
Kurtosis-1.4465191
Mean35.786216
Median Absolute Deviation (MAD)0.069636
Skewness-0.29127634
Sum4580.6356
Variance0.0058386887
MonotonicityNot monotonic
2023-12-13T00:31:15.415730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.862843 2
 
1.6%
35.858951 2
 
1.6%
35.693107 2
 
1.6%
35.797602 2
 
1.6%
35.857257 2
 
1.6%
35.775242 2
 
1.6%
35.675708 1
 
0.8%
35.799544 1
 
0.8%
35.874846 1
 
0.8%
35.781732 1
 
0.8%
Other values (112) 112
87.5%
ValueCountFrequency (%)
35.640102 1
0.8%
35.650869 1
0.8%
35.65486 1
0.8%
35.658393 1
0.8%
35.658683 1
0.8%
35.65878 1
0.8%
35.674575 1
0.8%
35.674634 1
0.8%
35.675708 1
0.8%
35.683785 1
0.8%
ValueCountFrequency (%)
35.887263 1
0.8%
35.876285 1
0.8%
35.876117 1
0.8%
35.875987 1
0.8%
35.874846 1
0.8%
35.87484 1
0.8%
35.874799 1
0.8%
35.874441 1
0.8%
35.874396 1
0.8%
35.874202 1
0.8%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct122
Distinct (%)95.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.46669
Minimum128.40843
Maximum128.62453
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-13T00:31:15.606686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.40843
5-th percentile128.42274
Q1128.45165
median128.46415
Q3128.47962
95-th percentile128.49763
Maximum128.62453
Range0.2160969
Interquartile range (IQR)0.027963875

Descriptive statistics

Standard deviation0.030097771
Coefficient of variation (CV)0.00023428462
Kurtosis10.190352
Mean128.46669
Median Absolute Deviation (MAD)0.01307375
Skewness2.0731319
Sum16443.737
Variance0.00090587579
MonotonicityNot monotonic
2023-12-13T00:31:15.775335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.4604358 2
 
1.6%
128.464438 2
 
1.6%
128.4582125 2
 
1.6%
128.4909483 2
 
1.6%
128.4631921 2
 
1.6%
128.4288234 2
 
1.6%
128.451774 1
 
0.8%
128.49104 1
 
0.8%
128.49727 1
 
0.8%
128.4430181 1
 
0.8%
Other values (112) 112
87.5%
ValueCountFrequency (%)
128.4084293 1
0.8%
128.408794 1
0.8%
128.410672 1
0.8%
128.4179864 1
0.8%
128.4180727 1
0.8%
128.4192093 1
0.8%
128.4194601 1
0.8%
128.4288234 2
1.6%
128.428917 1
0.8%
128.4357966 1
0.8%
ValueCountFrequency (%)
128.6245262 1
0.8%
128.6232465 1
0.8%
128.5130627 1
0.8%
128.5110912 1
0.8%
128.5068936 1
0.8%
128.5063735 1
0.8%
128.497749 1
0.8%
128.4974 1
0.8%
128.4973173 1
0.8%
128.49727 1
0.8%

Interactions

2023-12-13T00:31:11.188076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:31:10.923438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:31:11.284341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:31:11.060739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:31:15.869992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명업종전화번호영업시간위도경도
업소명1.0001.0001.0000.9880.9990.997
업종1.0001.0000.9680.0000.2490.000
전화번호1.0000.9681.0000.9970.9970.998
영업시간0.9880.0000.9971.0000.7900.689
위도0.9990.2490.9970.7901.0000.827
경도0.9970.0000.9980.6890.8271.000
2023-12-13T00:31:15.979393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도업종
위도1.0000.6090.142
경도0.6091.0000.000
업종0.1420.0001.000

Missing values

2023-12-13T00:31:11.441184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:31:11.572937image/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.
2023-12-13T00:31:11.694876image/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

업소명업종소재지전화번호영업시간위도경도
0동아헬스체력단련장업대구광역시 달성군 논공읍 논공로 749, 6층053-616-6464평일 05:30 - 23:00, 토요일 05:30 - 21:00, 일요일 휴무35.728996128.446035
1서재헬스체력단련장업대구광역시 달성군 다사읍 서재로 141, 4층0507-1348-6004평일 06:00 - 24:0035.876117128.496596
2새롬헬스체력단련장업대구광역시 달성군 화원읍 비슬로 2508053-638-4386매일 6:30-21:30, 매주 화요일 휴관35.800317128.492411
3나우 휘트니스 클럽체력단련장업대구광역시 달성군 논공읍 논공로5길 229, 2층053-614-0255<NA>35.731351128.447363
4장수휘트니스클럽체력단련장업대구광역시 달성군 현풍읍 현풍중앙로14길 710507-1338-5512평일 06:00 - 22:0035.694569128.448991
5그린월드체력단련장업대구광역시 달성군 화원읍 비슬로530길 29-15<NA><NA>35.805349128.506894
6휴림원 헬스클럽체력단련장업대구광역시 달성군 다사읍 죽곡1길 16-6053-585-0100평일 06:00 - 22:00 (사우나, 헬스), 매일 10:00 - 00:00 (골프), 주말 06:00 - 18:00 (헬스)35.857257128.463192
7한샘사우나헬스체력단련장업대구광역시 달성군 화원읍 명천로 257, 4층053-551-8888<NA>35.797602128.490948
8귀빈헬스체력단련장업대구광역시 달성군 다사읍 대실역북로 9, 7층053-593-2555평일 06:00 - 23:00, 토요일 06:00 - 20:00, 일요일 휴무, 공휴일 06:00 - 18:0035.858007128.466071
9제이제이휘트니스체력단련장업대구광역시 달성군 다사읍 달구벌대로 873, 5층0507-1329-4566평일 06:00 - 23:30, 토요일 10:00 - 18:0035.858362128.465064
업소명업종소재지전화번호영업시간위도경도
118제이(J)골프골프연습장업대구광역시 달성군 옥포읍 비슬로447길 10-8<NA><NA>35.790594128.467037
119MK골프골프연습장업대구광역시 달성군 화원읍 명천로 246, 2층053-644-0750<NA>35.798663128.491907
120CJ GDR골프연습장골프연습장업대구광역시 달성군 화원읍 성천로26길 50, A동 1층053-656-7700<NA>35.804838128.496334
121주식회사 화성이앤지 달성지점골프연습장업대구광역시 달성군 옥포읍 옥포로 607, 1~3층<NA><NA>35.746285128.488088
122주식회사 세천스크린골프연습장가상체험 체육시설업대구광역시 달성군 다사읍 세천로7길 9, 4~5층053-588-9970<NA>35.874145128.47176
123제이제이골프존파크가상체험 체육시설업대구광역시 달성군 논공읍 달성군청로 30, 3~4층053-611-0072<NA>35.775193128.428917
124다원골프아카데미가상체험 체육시설업대구광역시 달성군 옥포읍 돌미로 65, 5층 501호0507-1311-8469<NA>35.780503128.440822
125가든 15 골프아카데미가상체험 체육시설업대구광역시 달성군 화원읍 성화로 500507-1443-0757<NA>35.800925128.487183
126로얄 카카오 골프 연습장가상체험 체육시설업대구광역시 달성군 옥포읍 돌미상업로1길 14, 3층0507-1472-1341<NA>35.782015128.440815
127현풍무도학원무도학원업대구광역시 달성군 현풍읍 현풍중앙로21길 13, 2층<NA><NA>35.697746128.44263