Overview

Dataset statistics

Number of variables9
Number of observations32
Missing cells20
Missing cells (%)6.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 KiB
Average record size in memory78.1 B

Variable types

Text4
Categorical3
Numeric2

Dataset

Description김해시 유원시설업 현황(사업장명,영업상태명,전화번호,지번주소,도로명주소,위도,경도,개방서비스명,문화체육업종명,지역구분명,시설면적,놀이시설수,시설규모)
Author경상남도 김해시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15033383

Alerts

문화체육업종명 is highly overall correlated with 놀이시설수 and 1 other fieldsHigh correlation
개방서비스명 is highly overall correlated with 놀이시설수 and 1 other fieldsHigh correlation
놀이시설수 is highly overall correlated with 개방서비스명 and 1 other fieldsHigh correlation
영업상태명 is highly imbalanced (55.1%)Imbalance
전화번호 has 12 (37.5%) missing valuesMissing
도로명주소 has 1 (3.1%) missing valuesMissing
시설면적 has 7 (21.9%) missing valuesMissing

Reproduction

Analysis started2023-12-10 23:25:23.990858
Analysis finished2023-12-10 23:25:25.294125
Duration1.3 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사업장명
Text

Distinct31
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-11T08:25:25.475180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length8.53125
Min length4

Characters and Unicode

Total characters273
Distinct characters112
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)93.8%

Sample

1st row가야랜드
2nd row김해가야테마파크
3rd row김해낙동강레일파크
4th row김해랜드
5th row한국엘에스레져
ValueCountFrequency (%)
키즈카페 3
 
6.1%
꼬마대통령 3
 
6.1%
주식회사 2
 
4.1%
김해점 2
 
4.1%
샤랄랄라 2
 
4.1%
롯데워터파크 1
 
2.0%
뽀로로빌리지 1
 
2.0%
주식회사케이커머스 1
 
2.0%
가야랜드 1
 
2.0%
스카이랜드 1
 
2.0%
Other values (32) 32
65.3%
2023-12-11T08:25:25.848234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17
 
6.2%
김 10
 
3.7%
해 10
 
3.7%
스 9
 
3.3%
점 8
 
2.9%
이 7
 
2.6%
키 7
 
2.6%
즈 7
 
2.6%
주 6
 
2.2%
마 6
 
2.2%
Other values (102) 186
68.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 251
91.9%
Space Separator 17
 
6.2%
Other Punctuation 1
 
0.4%
Decimal Number 1
 
0.4%
Other Symbol 1
 
0.4%
Open Punctuation 1
 
0.4%
Close Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 10
 
4.0%
해 10
 
4.0%
스 9
 
3.6%
점 8
 
3.2%
이 7
 
2.8%
키 7
 
2.8%
즈 7
 
2.8%
주 6
 
2.4%
마 6
 
2.4%
카 6
 
2.4%
Other values (96) 175
69.7%
Space Separator
ValueCountFrequency (%)
17
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 252
92.3%
Common 21
 
7.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 10
 
4.0%
해 10
 
4.0%
스 9
 
3.6%
점 8
 
3.2%
이 7
 
2.8%
키 7
 
2.8%
즈 7
 
2.8%
주 6
 
2.4%
마 6
 
2.4%
카 6
 
2.4%
Other values (97) 176
69.8%
Common
ValueCountFrequency (%)
17
81.0%
& 1
 
4.8%
2 1
 
4.8%
( 1
 
4.8%
) 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 251
91.9%
ASCII 21
 
7.7%
None 1
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17
81.0%
& 1
 
4.8%
2 1
 
4.8%
( 1
 
4.8%
) 1
 
4.8%
Hangul
ValueCountFrequency (%)
김 10
 
4.0%
해 10
 
4.0%
스 9
 
3.6%
점 8
 
3.2%
이 7
 
2.8%
키 7
 
2.8%
즈 7
 
2.8%
주 6
 
2.4%
마 6
 
2.4%
카 6
 
2.4%
Other values (96) 175
69.7%
None
ValueCountFrequency (%)
㈜ 1
100.0%

영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size388.0 B
영업중
29 
휴업
3 

Length

Max length3
Median length3
Mean length2.90625
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 29
90.6%
휴업 3
 
9.4%

Length

2023-12-11T08:25:26.029602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:25:26.142242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 29
90.6%
휴업 3
 
9.4%

전화번호
Text

MISSING 

Distinct20
Distinct (%)100.0%
Missing12
Missing (%)37.5%
Memory size388.0 B
2023-12-11T08:25:26.313356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length12
Mean length12.3
Min length12

Characters and Unicode

Total characters246
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)100.0%

Sample

1st row055-346-6000
2nd row055-340-7952
3rd row055-333-8358
4th row051-901-7348(7525)
5th row055-313-0207
ValueCountFrequency (%)
055-723-2258 1
 
5.0%
055-333-8358 1
 
5.0%
055-322-5162 1
 
5.0%
055-900-0100 1
 
5.0%
055-325-5238 1
 
5.0%
055-902-2300 1
 
5.0%
055-311-3325 1
 
5.0%
055-330-6674 1
 
5.0%
055-322-1188 1
 
5.0%
033-649-1234 1
 
5.0%
Other values (10) 10
50.0%
2023-12-11T08:25:26.696522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 46
18.7%
0 42
17.1%
- 40
16.3%
3 32
13.0%
2 22
8.9%
1 16
 
6.5%
8 11
 
4.5%
7 10
 
4.1%
4 9
 
3.7%
9 8
 
3.3%
Other values (3) 10
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 204
82.9%
Dash Punctuation 40
 
16.3%
Open Punctuation 1
 
0.4%
Close Punctuation 1
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 46
22.5%
0 42
20.6%
3 32
15.7%
2 22
10.8%
1 16
 
7.8%
8 11
 
5.4%
7 10
 
4.9%
4 9
 
4.4%
9 8
 
3.9%
6 8
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 40
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 246
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 46
18.7%
0 42
17.1%
- 40
16.3%
3 32
13.0%
2 22
8.9%
1 16
 
6.5%
8 11
 
4.5%
7 10
 
4.1%
4 9
 
3.7%
9 8
 
3.3%
Other values (3) 10
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 246
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 46
18.7%
0 42
17.1%
- 40
16.3%
3 32
13.0%
2 22
8.9%
1 16
 
6.5%
8 11
 
4.5%
7 10
 
4.1%
4 9
 
3.7%
9 8
 
3.3%
Other values (3) 10
 
4.1%

지번주소
Text

Distinct30
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-11T08:25:26.967313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length26.5
Mean length24.0625
Min length17

Characters and Unicode

Total characters770
Distinct characters89
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

Unique28 ?
Unique (%)87.5%

Sample

1st row경상남도 김해시 삼방동 산 123
2nd row경상남도 김해시 어방동 993
3rd row경상남도 김해시 생림면 마사리 654-4
4th row경상남도 김해시 어방동 993
5th row경상남도 김해시 신문동 1414 롯데아울렛
ValueCountFrequency (%)
경상남도 32
19.4%
김해시 32
19.4%
외동 6
 
3.6%
어방동 5
 
3.0%
1264 4
 
2.4%
진영읍 3
 
1.8%
301호 3
 
1.8%
율하동 3
 
1.8%
신문동 3
 
1.8%
529-6 2
 
1.2%
Other values (62) 72
43.6%
2023-12-11T08:25:27.361124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
159
20.6%
1 37
 
4.8%
경 36
 
4.7%
김 33
 
4.3%
해 33
 
4.3%
상 33
 
4.3%
남 32
 
4.2%
도 32
 
4.2%
시 32
 
4.2%
동 28
 
3.6%
Other values (79) 315
40.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 431
56.0%
Decimal Number 161
 
20.9%
Space Separator 159
 
20.6%
Dash Punctuation 19
 
2.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 36
 
8.4%
김 33
 
7.7%
해 33
 
7.7%
상 33
 
7.7%
남 32
 
7.4%
도 32
 
7.4%
시 32
 
7.4%
동 28
 
6.5%
리 7
 
1.6%
호 7
 
1.6%
Other values (67) 158
36.7%
Decimal Number
ValueCountFrequency (%)
1 37
23.0%
4 25
15.5%
2 21
13.0%
3 21
13.0%
5 15
9.3%
0 13
 
8.1%
9 11
 
6.8%
6 10
 
6.2%
7 6
 
3.7%
8 2
 
1.2%
Space Separator
ValueCountFrequency (%)
159
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 431
56.0%
Common 339
44.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 36
 
8.4%
김 33
 
7.7%
해 33
 
7.7%
상 33
 
7.7%
남 32
 
7.4%
도 32
 
7.4%
시 32
 
7.4%
동 28
 
6.5%
리 7
 
1.6%
호 7
 
1.6%
Other values (67) 158
36.7%
Common
ValueCountFrequency (%)
159
46.9%
1 37
 
10.9%
4 25
 
7.4%
2 21
 
6.2%
3 21
 
6.2%
- 19
 
5.6%
5 15
 
4.4%
0 13
 
3.8%
9 11
 
3.2%
6 10
 
2.9%
Other values (2) 8
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 431
56.0%
ASCII 339
44.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
159
46.9%
1 37
 
10.9%
4 25
 
7.4%
2 21
 
6.2%
3 21
 
6.2%
- 19
 
5.6%
5 15
 
4.4%
0 13
 
3.8%
9 11
 
3.2%
6 10
 
2.9%
Other values (2) 8
 
2.4%
Hangul
ValueCountFrequency (%)
경 36
 
8.4%
김 33
 
7.7%
해 33
 
7.7%
상 33
 
7.7%
남 32
 
7.4%
도 32
 
7.4%
시 32
 
7.4%
동 28
 
6.5%
리 7
 
1.6%
호 7
 
1.6%
Other values (67) 158
36.7%

도로명주소
Text

MISSING 

Distinct29
Distinct (%)93.5%
Missing1
Missing (%)3.1%
Memory size388.0 B
2023-12-11T08:25:27.631973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length35
Mean length31.032258
Min length19

Characters and Unicode

Total characters962
Distinct characters109
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

Unique27 ?
Unique (%)87.1%

Sample

1st row경상남도 김해시 인제로 368 (삼방동)
2nd row경상남도 김해시 가야테마길 161 (어방동)
3rd row경상남도 김해시 생림면 마사로473번길 41
4th row경상남도 김해시 가야테마길 161 (어방동)
5th row경상남도 김해시 장유로 469 (신문동)
ValueCountFrequency (%)
경상남도 31
 
15.1%
김해시 31
 
15.1%
김해대로 6
 
2.9%
외동 6
 
2.9%
3층 5
 
2.4%
4층 5
 
2.4%
어방동 5
 
2.4%
2232 4
 
2.0%
장유로 3
 
1.5%
율하동 3
 
1.5%
Other values (85) 106
51.7%
2023-12-11T08:25:28.017068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
174
 
18.1%
김 39
 
4.1%
해 39
 
4.1%
경 35
 
3.6%
도 32
 
3.3%
상 32
 
3.3%
남 31
 
3.2%
시 31
 
3.2%
2 30
 
3.1%
동 29
 
3.0%
Other values (99) 490
50.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 559
58.1%
Space Separator 174
 
18.1%
Decimal Number 155
 
16.1%
Open Punctuation 24
 
2.5%
Close Punctuation 24
 
2.5%
Other Punctuation 22
 
2.3%
Dash Punctuation 3
 
0.3%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 39
 
7.0%
해 39
 
7.0%
경 35
 
6.3%
도 32
 
5.7%
상 32
 
5.7%
남 31
 
5.5%
시 31
 
5.5%
동 29
 
5.2%
로 28
 
5.0%
층 20
 
3.6%
Other values (83) 243
43.5%
Decimal Number
ValueCountFrequency (%)
2 30
19.4%
1 28
18.1%
3 21
13.5%
4 15
9.7%
5 14
9.0%
0 14
9.0%
6 11
 
7.1%
7 11
 
7.1%
9 7
 
4.5%
8 4
 
2.6%
Space Separator
ValueCountFrequency (%)
174
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Other Punctuation
ValueCountFrequency (%)
, 22
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 559
58.1%
Common 402
41.8%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 39
 
7.0%
해 39
 
7.0%
경 35
 
6.3%
도 32
 
5.7%
상 32
 
5.7%
남 31
 
5.5%
시 31
 
5.5%
동 29
 
5.2%
로 28
 
5.0%
층 20
 
3.6%
Other values (83) 243
43.5%
Common
ValueCountFrequency (%)
174
43.3%
2 30
 
7.5%
1 28
 
7.0%
( 24
 
6.0%
) 24
 
6.0%
, 22
 
5.5%
3 21
 
5.2%
4 15
 
3.7%
5 14
 
3.5%
0 14
 
3.5%
Other values (5) 36
 
9.0%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 559
58.1%
ASCII 403
41.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
174
43.2%
2 30
 
7.4%
1 28
 
6.9%
( 24
 
6.0%
) 24
 
6.0%
, 22
 
5.5%
3 21
 
5.2%
4 15
 
3.7%
5 14
 
3.5%
0 14
 
3.5%
Other values (6) 37
 
9.2%
Hangul
ValueCountFrequency (%)
김 39
 
7.0%
해 39
 
7.0%
경 35
 
6.3%
도 32
 
5.7%
상 32
 
5.7%
남 31
 
5.5%
시 31
 
5.5%
동 29
 
5.2%
로 28
 
5.0%
층 20
 
3.6%
Other values (83) 243
43.5%

개방서비스명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Memory size388.0 B
기타유원시설업
25 
일반유원시설업
5 
종합유원시설업
 
2

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row종합유원시설업
2nd row일반유원시설업
3rd row일반유원시설업
4th row일반유원시설업
5th row일반유원시설업

Common Values

ValueCountFrequency (%)
기타유원시설업 25
78.1%
일반유원시설업 5
 
15.6%
종합유원시설업 2
 
6.2%

Length

2023-12-11T08:25:28.141765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:25:28.227336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타유원시설업 25
78.1%
일반유원시설업 5
 
15.6%
종합유원시설업 2
 
6.2%

문화체육업종명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Memory size388.0 B
기타유원시설업
25 
일반유원시설업
5 
종합유원시설업
 
2

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row종합유원시설업
2nd row일반유원시설업
3rd row일반유원시설업
4th row일반유원시설업
5th row일반유원시설업

Common Values

ValueCountFrequency (%)
기타유원시설업 25
78.1%
일반유원시설업 5
 
15.6%
종합유원시설업 2
 
6.2%

Length

2023-12-11T08:25:28.344661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:25:28.442618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타유원시설업 25
78.1%
일반유원시설업 5
 
15.6%
종합유원시설업 2
 
6.2%

시설면적
Real number (ℝ)

MISSING 

Distinct24
Distinct (%)96.0%
Missing7
Missing (%)21.9%
Infinite0
Infinite (%)0.0%
Mean612.8728
Minimum15
Maximum3131.07
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-11T08:25:28.535459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15
5-th percentile60.352
Q1252.6
median427.16
Q3484.71
95-th percentile2647.96
Maximum3131.07
Range3116.07
Interquartile range (IQR)232.11

Descriptive statistics

Standard deviation783.0684
Coefficient of variation (CV)1.2777013
Kurtosis7.6253375
Mean612.8728
Median Absolute Deviation (MAD)138.31
Skewness2.840038
Sum15321.82
Variance613196.12
MonotonicityNot monotonic
2023-12-11T08:25:28.629174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
342.69 2
 
6.2%
484.71 1
 
3.1%
3077.7 1
 
3.1%
40.0 1
 
3.1%
248.8 1
 
3.1%
929.0 1
 
3.1%
288.85 1
 
3.1%
471.64 1
 
3.1%
372.33 1
 
3.1%
15.0 1
 
3.1%
Other values (14) 14
43.8%
(Missing) 7
21.9%
ValueCountFrequency (%)
15.0 1
3.1%
40.0 1
3.1%
141.76 1
3.1%
150.0 1
3.1%
248.8 1
3.1%
250.0 1
3.1%
252.6 1
3.1%
288.85 1
3.1%
308.85 1
3.1%
342.69 2
6.2%
ValueCountFrequency (%)
3131.07 1
3.1%
3077.7 1
3.1%
929.0 1
3.1%
864.45 1
3.1%
828.04 1
3.1%
495.0 1
3.1%
484.71 1
3.1%
484.6 1
3.1%
474.3 1
3.1%
471.64 1
3.1%

놀이시설수
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)46.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.6875
Minimum2
Maximum109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-11T08:25:28.719174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q12
median4
Q312.5
95-th percentile44.45
Maximum109
Range107
Interquartile range (IQR)10.5

Descriptive statistics

Standard deviation21.139227
Coefficient of variation (CV)1.666146
Kurtosis14.344309
Mean12.6875
Median Absolute Deviation (MAD)2
Skewness3.5442922
Sum406
Variance446.86694
MonotonicityNot monotonic
2023-12-11T08:25:28.811823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
2 9
28.1%
4 5
15.6%
3 3
 
9.4%
8 3
 
9.4%
14 2
 
6.2%
109 1
 
3.1%
10 1
 
3.1%
35 1
 
3.1%
6 1
 
3.1%
19 1
 
3.1%
Other values (5) 5
15.6%
ValueCountFrequency (%)
2 9
28.1%
3 3
 
9.4%
4 5
15.6%
6 1
 
3.1%
8 3
 
9.4%
9 1
 
3.1%
10 1
 
3.1%
12 1
 
3.1%
14 2
 
6.2%
19 1
 
3.1%
ValueCountFrequency (%)
109 1
3.1%
56 1
3.1%
35 1
3.1%
28 1
3.1%
23 1
3.1%
19 1
3.1%
14 2
6.2%
12 1
3.1%
10 1
3.1%
9 1
3.1%

Interactions

2023-12-11T08:25:24.670860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:25:24.488560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:25:24.767129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:25:24.577214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:25:28.884675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업장명영업상태명전화번호지번주소도로명주소개방서비스명문화체육업종명시설면적놀이시설수
사업장명1.0001.0001.0000.9740.9721.0001.0000.9561.000
영업상태명1.0001.0001.0000.0000.0000.1740.1740.5290.688
전화번호1.0001.0001.0001.0001.0001.0001.0001.0001.000
지번주소0.9740.0001.0001.0001.0001.0001.0000.0000.000
도로명주소0.9720.0001.0001.0001.0001.0001.0000.0000.000
개방서비스명1.0000.1741.0001.0001.0001.0001.0000.4730.947
문화체육업종명1.0000.1741.0001.0001.0001.0001.0000.4730.947
시설면적0.9560.5291.0000.0000.0000.4730.4731.0000.711
놀이시설수1.0000.6881.0000.0000.0000.9470.9470.7111.000
2023-12-11T08:25:28.987593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
영업상태명문화체육업종명개방서비스명
영업상태명1.0000.2780.278
문화체육업종명0.2781.0001.000
개방서비스명0.2781.0001.000
2023-12-11T08:25:29.067750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설면적놀이시설수영업상태명개방서비스명문화체육업종명
시설면적1.0000.4470.3380.4550.455
놀이시설수0.4471.0000.4660.6810.681
영업상태명0.3380.4661.0000.2780.278
개방서비스명0.4550.6810.2781.0001.000
문화체육업종명0.4550.6810.2781.0001.000

Missing values

2023-12-11T08:25:24.907494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:25:25.118161image/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.
2023-12-11T08:25:25.242987image/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

사업장명영업상태명전화번호지번주소도로명주소개방서비스명문화체육업종명시설면적놀이시설수
0가야랜드영업중055-346-6000경상남도 김해시 삼방동 산 123경상남도 김해시 인제로 368 (삼방동)종합유원시설업종합유원시설업3131.07109
1김해가야테마파크영업중055-340-7952경상남도 김해시 어방동 993경상남도 김해시 가야테마길 161 (어방동)일반유원시설업일반유원시설업<NA>10
2김해낙동강레일파크영업중055-333-8358경상남도 김해시 생림면 마사리 654-4경상남도 김해시 생림면 마사로473번길 41일반유원시설업일반유원시설업<NA>35
3김해랜드영업중<NA>경상남도 김해시 어방동 993경상남도 김해시 가야테마길 161 (어방동)일반유원시설업일반유원시설업150.014
4한국엘에스레져영업중<NA>경상남도 김해시 신문동 1414 롯데아울렛경상남도 김해시 장유로 469 (신문동)일반유원시설업일반유원시설업250.06
5한국마사회 부산경남지역본부영업중051-901-7348(7525)경상남도 김해시 수가동 1333 렛츠런파크경상남도 김해시 가락대로 929-1 (수가동)일반유원시설업일반유원시설업<NA>3
6베니주니키즈카페영업중<NA>경상남도 김해시 진영읍 진영리 1612-4 10층경상남도 김해시 진영읍 김해대로361번길 16, 10층기타유원시설업기타유원시설업828.044
7샤랄랄라 키즈카페영업중055-313-0207경상남도 김해시 삼계동 1502-2 삼성아동병원 3층경상남도 김해시 삼계중앙로 36, 삼성아동병원 3층 (삼계동)기타유원시설업기타유원시설업308.852
8헬로방방 김해율하영업중055-337-8501경상남도 김해시 율하동 1335-1 경보월드경상남도 김해시 율하2로97번길 22, 경보월드 7층 (율하동)기타유원시설업기타유원시설업456.588
9샤랄라 키즈카페영업중<NA>경상남도 김해시 진영읍 여래리 970경상남도 김해시 진영읍 본산로 9, 우리마트 3층기타유원시설업기타유원시설업444.02
사업장명영업상태명전화번호지번주소도로명주소개방서비스명문화체육업종명시설면적놀이시설수
22점핑타임영업중<NA>경상남도 김해시 어방동 474-2경상남도 김해시 인제로 168, 정석빌딩 가동 7층 701호 (어방동)기타유원시설업기타유원시설업288.852
23김해시수도박물관영업중055-330-6674경상남도 김해시 한림면 명동리 736-1경상남도 김해시 한림면 김해대로 1347, 수도박물관 1층기타유원시설업기타유원시설업<NA>2
24키즈다쿵&베이비테라스영업중<NA>경상남도 김해시 장유동 825-1경상남도 김해시 율하6로 62, 율하테라스 4층 (장유동)기타유원시설업기타유원시설업929.012
25천문대오토캠핑장영업중055-311-3325경상남도 김해시 생림면 나전리 30-6경상남도 김해시 생림면 인제로 545-59기타유원시설업기타유원시설업<NA>3
26(주)키즈몬스터영업중055-902-2300경상남도 김해시 장유동 840-4경상남도 김해시 율하숲길 21, 로하스디딤빌딩 4층 402호 (장유동)기타유원시설업기타유원시설업248.82
27주식회사 케이커머스2영업중<NA>경상남도 김해시 외동 1264경상남도 김해시 김해대로 2232, 이마트 1층 (외동)기타유원시설업기타유원시설업40.02
28자람동산영업중055-325-5238경상남도 김해시 주촌면 선지리 479-1경상남도 김해시 주촌면 동선길 38기타유원시설업기타유원시설업<NA>9
29롯데워터파크휴업055-900-0100경상남도 김해시 신문동 1417경상남도 김해시 장유로 555 (신문동)종합유원시설업종합유원시설업<NA>56
30㈜신세계김해점 뽀로로빌리지휴업055-272-1040경상남도 김해시 외동 1264 신세계백화점 5층경상남도 김해시 김해대로 2232, 신세계백화점 5층 (외동)기타유원시설업기타유원시설업3077.723
31꼬마대통령 주니어휴업<NA>경상남도 김해시 어방동 529-6 진성빌딩 401호경상남도 김해시 인제로170번길 7, 진성빌딩 4층 401호 (어방동)기타유원시설업기타유원시설업342.692