Overview

Dataset statistics

Number of variables12
Number of observations272
Missing cells249
Missing cells (%)7.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory26.7 KiB
Average record size in memory100.5 B

Variable types

Text3
Numeric4
Categorical3
Boolean1
DateTime1

Dataset

Description김해시 위탁급식업체 현황(사업장명, 소재지면적, 지번주소, 도로명주소, 위생업태명, 급수시설구분, 다중이용업소여부 등)에 관한 데이터 제공
Author경상남도 김해시
URLhttps://www.data.go.kr/data/15033420/fileData.do

Alerts

위생업태명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
소재지면적 is highly overall correlated with 시설총규모High correlation
시설총규모 is highly overall correlated with 소재지면적High correlation
소재지면적 has 36 (13.2%) missing valuesMissing
도로명주소 has 88 (32.4%) missing valuesMissing
폐업일자 has 125 (46.0%) missing valuesMissing
소재지면적 has 3 (1.1%) zerosZeros
시설총규모 has 39 (14.3%) zerosZeros

Reproduction

Analysis started2023-12-12 10:51:59.685855
Analysis finished2023-12-12 10:52:04.259575
Duration4.57 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사업장명
Text

Distinct262
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2023-12-12T19:52:04.509044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length17
Mean length11.242647
Min length2

Characters and Unicode

Total characters3058
Distinct characters300
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique252 ?
Unique (%)92.6%

Sample

1st row(주)유니온푸드 경원테크
2nd row(주)유니온푸드 동원테크
3rd row김해축협 배합사료공장
4th row(주)제이푸드코리아
5th row(주)동원홈푸드 티엠씨점
ValueCountFrequency (%)
주)아워홈 14
 
3.6%
김해점 11
 
2.8%
구내식당 8
 
2.0%
주)풀무원푸드앤컬처 6
 
1.5%
푸드란 4
 
1.0%
주)유니온푸드 4
 
1.0%
주)새손 4
 
1.0%
주)가내찬 3
 
0.8%
현장식당 3
 
0.8%
주)참다올푸드 3
 
0.8%
Other values (305) 333
84.7%
2023-12-12T19:52:05.192990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 171
 
5.6%
) 171
 
5.6%
주 165
 
5.4%
121
 
4.0%
점 93
 
3.0%
이 85
 
2.8%
스 76
 
2.5%
식 76
 
2.5%
드 71
 
2.3%
푸 68
 
2.2%
Other values (290) 1961
64.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2561
83.7%
Open Punctuation 171
 
5.6%
Close Punctuation 171
 
5.6%
Space Separator 121
 
4.0%
Uppercase Letter 21
 
0.7%
Decimal Number 8
 
0.3%
Dash Punctuation 5
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 165
 
6.4%
점 93
 
3.6%
이 85
 
3.3%
스 76
 
3.0%
식 76
 
3.0%
드 71
 
2.8%
푸 68
 
2.7%
해 67
 
2.6%
김 64
 
2.5%
당 60
 
2.3%
Other values (273) 1736
67.8%
Uppercase Letter
ValueCountFrequency (%)
S 5
23.8%
C 4
19.0%
D 3
14.3%
F 2
 
9.5%
O 2
 
9.5%
J 1
 
4.8%
E 1
 
4.8%
K 1
 
4.8%
T 1
 
4.8%
G 1
 
4.8%
Decimal Number
ValueCountFrequency (%)
2 4
50.0%
1 3
37.5%
5 1
 
12.5%
Open Punctuation
ValueCountFrequency (%)
( 171
100.0%
Close Punctuation
ValueCountFrequency (%)
) 171
100.0%
Space Separator
ValueCountFrequency (%)
121
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2561
83.7%
Common 476
 
15.6%
Latin 21
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 165
 
6.4%
점 93
 
3.6%
이 85
 
3.3%
스 76
 
3.0%
식 76
 
3.0%
드 71
 
2.8%
푸 68
 
2.7%
해 67
 
2.6%
김 64
 
2.5%
당 60
 
2.3%
Other values (273) 1736
67.8%
Latin
ValueCountFrequency (%)
S 5
23.8%
C 4
19.0%
D 3
14.3%
F 2
 
9.5%
O 2
 
9.5%
J 1
 
4.8%
E 1
 
4.8%
K 1
 
4.8%
T 1
 
4.8%
G 1
 
4.8%
Common
ValueCountFrequency (%)
( 171
35.9%
) 171
35.9%
121
25.4%
- 5
 
1.1%
2 4
 
0.8%
1 3
 
0.6%
5 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2561
83.7%
ASCII 497
 
16.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 171
34.4%
) 171
34.4%
121
24.3%
S 5
 
1.0%
- 5
 
1.0%
C 4
 
0.8%
2 4
 
0.8%
1 3
 
0.6%
D 3
 
0.6%
F 2
 
0.4%
Other values (7) 8
 
1.6%
Hangul
ValueCountFrequency (%)
주 165
 
6.4%
점 93
 
3.6%
이 85
 
3.3%
스 76
 
3.0%
식 76
 
3.0%
드 71
 
2.8%
푸 68
 
2.7%
해 67
 
2.6%
김 64
 
2.5%
당 60
 
2.3%
Other values (273) 1736
67.8%

소재지면적
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct202
Distinct (%)85.6%
Missing36
Missing (%)13.2%
Infinite0
Infinite (%)0.0%
Mean268.44292
Minimum0
Maximum881.28
Zeros3
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-12T19:52:05.449945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile77
Q1149.6
median230.1
Q3350.35
95-th percentile578.59
Maximum881.28
Range881.28
Interquartile range (IQR)200.75

Descriptive statistics

Standard deviation162.99202
Coefficient of variation (CV)0.60717571
Kurtosis1.7817123
Mean268.44292
Median Absolute Deviation (MAD)95.65
Skewness1.232683
Sum63352.53
Variance26566.399
MonotonicityNot monotonic
2023-12-12T19:52:05.722470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
324.0 4
 
1.5%
0.0 3
 
1.1%
362.4 2
 
0.7%
608.0 2
 
0.7%
253.9 2
 
0.7%
410.67 2
 
0.7%
229.24 2
 
0.7%
466.3 2
 
0.7%
240.0 2
 
0.7%
162.0 2
 
0.7%
Other values (192) 213
78.3%
(Missing) 36
 
13.2%
ValueCountFrequency (%)
0.0 3
1.1%
38.95 1
 
0.4%
49.0 1
 
0.4%
54.0 1
 
0.4%
60.0 2
0.7%
66.0 1
 
0.4%
67.59 1
 
0.4%
74.9 1
 
0.4%
77.0 2
0.7%
79.2 1
 
0.4%
ValueCountFrequency (%)
881.28 1
0.4%
821.7 1
0.4%
818.63 1
0.4%
795.54 1
0.4%
768.34 1
0.4%
719.4 1
0.4%
708.0 1
0.4%
707.1 1
0.4%
630.0 1
0.4%
608.0 2
0.7%

지번주소
Text

Distinct255
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2023-12-12T19:52:06.229104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length39
Mean length24.830882
Min length16

Characters and Unicode

Total characters6754
Distinct characters211
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

Unique242 ?
Unique (%)89.0%

Sample

1st row경상남도 김해시 진례면 고모리 1582-6번지 1층
2nd row경상남도 김해시 진례면 고모리 1045번지
3rd row경상남도 김해시 한림면 병동리 1105번지 1층
4th row경상남도 김해시 주촌면 농소리 623-1번지
5th row경상남도 김해시 진례면 담안리 1260
ValueCountFrequency (%)
경상남도 272
 
18.9%
김해시 272
 
18.9%
진영읍 39
 
2.7%
주촌면 37
 
2.6%
진례면 34
 
2.4%
한림면 17
 
1.2%
1층 16
 
1.1%
본산리 14
 
1.0%
외 13
 
0.9%
죽곡리 13
 
0.9%
Other values (410) 713
49.5%
2023-12-12T19:52:07.032610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1168
 
17.3%
김 291
 
4.3%
해 291
 
4.3%
1 288
 
4.3%
상 280
 
4.1%
지 279
 
4.1%
시 275
 
4.1%
도 274
 
4.1%
경 272
 
4.0%
남 272
 
4.0%
Other values (201) 3064
45.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4248
62.9%
Space Separator 1168
 
17.3%
Decimal Number 1104
 
16.3%
Dash Punctuation 168
 
2.5%
Uppercase Letter 36
 
0.5%
Close Punctuation 13
 
0.2%
Open Punctuation 13
 
0.2%
Other Punctuation 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 291
 
6.9%
해 291
 
6.9%
상 280
 
6.6%
지 279
 
6.6%
시 275
 
6.5%
도 274
 
6.5%
경 272
 
6.4%
남 272
 
6.4%
번 215
 
5.1%
동 183
 
4.3%
Other values (177) 1616
38.0%
Decimal Number
ValueCountFrequency (%)
1 288
26.1%
2 152
13.8%
0 105
 
9.5%
6 104
 
9.4%
3 98
 
8.9%
5 88
 
8.0%
4 80
 
7.2%
7 72
 
6.5%
8 63
 
5.7%
9 54
 
4.9%
Uppercase Letter
ValueCountFrequency (%)
B 11
30.6%
L 8
22.2%
A 6
16.7%
S 3
 
8.3%
D 3
 
8.3%
C 3
 
8.3%
M 1
 
2.8%
F 1
 
2.8%
Other Punctuation
ValueCountFrequency (%)
, 3
75.0%
. 1
 
25.0%
Space Separator
ValueCountFrequency (%)
1168
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 168
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4248
62.9%
Common 2470
36.6%
Latin 36
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 291
 
6.9%
해 291
 
6.9%
상 280
 
6.6%
지 279
 
6.6%
시 275
 
6.5%
도 274
 
6.5%
경 272
 
6.4%
남 272
 
6.4%
번 215
 
5.1%
동 183
 
4.3%
Other values (177) 1616
38.0%
Common
ValueCountFrequency (%)
1168
47.3%
1 288
 
11.7%
- 168
 
6.8%
2 152
 
6.2%
0 105
 
4.3%
6 104
 
4.2%
3 98
 
4.0%
5 88
 
3.6%
4 80
 
3.2%
7 72
 
2.9%
Other values (6) 147
 
6.0%
Latin
ValueCountFrequency (%)
B 11
30.6%
L 8
22.2%
A 6
16.7%
S 3
 
8.3%
D 3
 
8.3%
C 3
 
8.3%
M 1
 
2.8%
F 1
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4248
62.9%
ASCII 2506
37.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1168
46.6%
1 288
 
11.5%
- 168
 
6.7%
2 152
 
6.1%
0 105
 
4.2%
6 104
 
4.2%
3 98
 
3.9%
5 88
 
3.5%
4 80
 
3.2%
7 72
 
2.9%
Other values (14) 183
 
7.3%
Hangul
ValueCountFrequency (%)
김 291
 
6.9%
해 291
 
6.9%
상 280
 
6.6%
지 279
 
6.6%
시 275
 
6.5%
도 274
 
6.5%
경 272
 
6.4%
남 272
 
6.4%
번 215
 
5.1%
동 183
 
4.3%
Other values (177) 1616
38.0%

도로명주소
Text

MISSING 

Distinct168
Distinct (%)91.3%
Missing88
Missing (%)32.4%
Memory size2.3 KiB
2023-12-12T19:52:07.571373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length39
Mean length27.48913
Min length16

Characters and Unicode

Total characters5058
Distinct characters184
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

Unique152 ?
Unique (%)82.6%

Sample

1st row경상남도 김해시 진례면 테크노밸리1로 71, 1층
2nd row경상남도 김해시 진례면 고모로 480
3rd row경상남도 김해시 한림면 고모로 775, 1층
4th row경상남도 김해시 주촌면 골든루트로 104-2
5th row경상남도 김해시 진례면 고모로324번길 135-59
ValueCountFrequency (%)
경상남도 184
 
17.8%
김해시 184
 
17.8%
진례면 33
 
3.2%
주촌면 33
 
3.2%
진영읍 29
 
2.8%
1층 21
 
2.0%
한림면 16
 
1.6%
서부로179번길 12
 
1.2%
골든루트로 11
 
1.1%
2층 10
 
1.0%
Other values (303) 498
48.3%
2023-12-12T19:52:08.385046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
847
 
16.7%
김 214
 
4.2%
해 214
 
4.2%
1 204
 
4.0%
상 194
 
3.8%
경 184
 
3.6%
남 184
 
3.6%
도 184
 
3.6%
시 184
 
3.6%
로 182
 
3.6%
Other values (174) 2467
48.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2974
58.8%
Decimal Number 947
 
18.7%
Space Separator 847
 
16.7%
Open Punctuation 70
 
1.4%
Close Punctuation 70
 
1.4%
Other Punctuation 67
 
1.3%
Dash Punctuation 67
 
1.3%
Uppercase Letter 16
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 214
 
7.2%
해 214
 
7.2%
상 194
 
6.5%
경 184
 
6.2%
남 184
 
6.2%
도 184
 
6.2%
시 184
 
6.2%
로 182
 
6.1%
동 100
 
3.4%
길 98
 
3.3%
Other values (152) 1236
41.6%
Decimal Number
ValueCountFrequency (%)
1 204
21.5%
2 131
13.8%
3 90
9.5%
5 89
9.4%
0 82
8.7%
4 79
 
8.3%
9 77
 
8.1%
7 73
 
7.7%
6 62
 
6.5%
8 60
 
6.3%
Uppercase Letter
ValueCountFrequency (%)
A 5
31.2%
D 3
18.8%
C 3
18.8%
B 2
 
12.5%
F 1
 
6.2%
M 1
 
6.2%
S 1
 
6.2%
Space Separator
ValueCountFrequency (%)
847
100.0%
Open Punctuation
ValueCountFrequency (%)
( 70
100.0%
Close Punctuation
ValueCountFrequency (%)
) 70
100.0%
Other Punctuation
ValueCountFrequency (%)
, 67
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 67
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2974
58.8%
Common 2068
40.9%
Latin 16
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 214
 
7.2%
해 214
 
7.2%
상 194
 
6.5%
경 184
 
6.2%
남 184
 
6.2%
도 184
 
6.2%
시 184
 
6.2%
로 182
 
6.1%
동 100
 
3.4%
길 98
 
3.3%
Other values (152) 1236
41.6%
Common
ValueCountFrequency (%)
847
41.0%
1 204
 
9.9%
2 131
 
6.3%
3 90
 
4.4%
5 89
 
4.3%
0 82
 
4.0%
4 79
 
3.8%
9 77
 
3.7%
7 73
 
3.5%
( 70
 
3.4%
Other values (5) 326
 
15.8%
Latin
ValueCountFrequency (%)
A 5
31.2%
D 3
18.8%
C 3
18.8%
B 2
 
12.5%
F 1
 
6.2%
M 1
 
6.2%
S 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2974
58.8%
ASCII 2084
41.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
847
40.6%
1 204
 
9.8%
2 131
 
6.3%
3 90
 
4.3%
5 89
 
4.3%
0 82
 
3.9%
4 79
 
3.8%
9 77
 
3.7%
7 73
 
3.5%
( 70
 
3.4%
Other values (12) 342
16.4%
Hangul
ValueCountFrequency (%)
김 214
 
7.2%
해 214
 
7.2%
상 194
 
6.5%
경 184
 
6.2%
남 184
 
6.2%
도 184
 
6.2%
시 184
 
6.2%
로 182
 
6.1%
동 100
 
3.4%
길 98
 
3.3%
Other values (152) 1236
41.6%

위생업태명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
위탁급식영업
272 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
위탁급식영업 272
100.0%

Length

2023-12-12T19:52:08.612791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:52:08.768675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
위탁급식영업 272
100.0%

급수시설구분명
Categorical

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
상수도전용
170 
지하수전용
52 
<NA>
50 

Length

Max length5
Median length5
Mean length4.8161765
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row상수도전용
2nd row지하수전용
3rd row상수도전용
4th row상수도전용
5th row상수도전용

Common Values

ValueCountFrequency (%)
상수도전용 170
62.5%
지하수전용 52
 
19.1%
<NA> 50
 
18.4%

Length

2023-12-12T19:52:08.948992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:52:09.734658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 170
62.5%
지하수전용 52
 
19.1%
na 50
 
18.4%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size404.0 B
False
272 
ValueCountFrequency (%)
False 272
100.0%
2023-12-12T19:52:09.904579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct201
Distinct (%)73.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean231.47077
Minimum0
Maximum881.28
Zeros39
Zeros (%)14.3%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-12T19:52:10.109224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1114.495
median201.31
Q3327.0675
95-th percentile553.953
Maximum881.28
Range881.28
Interquartile range (IQR)212.5725

Descriptive statistics

Standard deviation176.02161
Coefficient of variation (CV)0.76044853
Kurtosis1.3115303
Mean231.47077
Median Absolute Deviation (MAD)105.19
Skewness0.99751285
Sum62960.05
Variance30983.606
MonotonicityNot monotonic
2023-12-12T19:52:10.372129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 39
 
14.3%
324.0 4
 
1.5%
253.9 2
 
0.7%
557.0 2
 
0.7%
212.85 2
 
0.7%
168.45 2
 
0.7%
130.5 2
 
0.7%
324.36 2
 
0.7%
360.0 2
 
0.7%
608.0 2
 
0.7%
Other values (191) 213
78.3%
ValueCountFrequency (%)
0.0 39
14.3%
38.95 1
 
0.4%
49.0 1
 
0.4%
54.0 1
 
0.4%
60.0 2
 
0.7%
66.0 1
 
0.4%
67.59 1
 
0.4%
74.9 1
 
0.4%
77.0 2
 
0.7%
79.2 1
 
0.4%
ValueCountFrequency (%)
881.28 1
0.4%
821.7 1
0.4%
818.63 1
0.4%
795.54 1
0.4%
768.34 1
0.4%
719.4 1
0.4%
708.0 1
0.4%
707.1 1
0.4%
630.0 1
0.4%
608.0 2
0.7%

영업상태
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
폐업
147 
영업
125 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 147
54.0%
영업 125
46.0%

Length

2023-12-12T19:52:10.620138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:52:10.819763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 147
54.0%
영업 125
46.0%

폐업일자
Date

MISSING 

Distinct130
Distinct (%)88.4%
Missing125
Missing (%)46.0%
Memory size2.3 KiB
Minimum2004-03-04 00:00:00
Maximum2021-06-25 00:00:00
2023-12-12T19:52:11.008975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:52:11.276969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

위도
Real number (ℝ)

Distinct215
Distinct (%)79.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.249068
Minimum35.163599
Maximum35.34516
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-12T19:52:11.550169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.163599
5-th percentile35.176648
Q135.221051
median35.241854
Q335.282681
95-th percentile35.319775
Maximum35.34516
Range0.18156074
Interquartile range (IQR)0.06162998

Descriptive statistics

Standard deviation0.041732002
Coefficient of variation (CV)0.0011839179
Kurtosis-0.68633882
Mean35.249068
Median Absolute Deviation (MAD)0.02718441
Skewness0.10959351
Sum9587.7464
Variance0.00174156
MonotonicityNot monotonic
2023-12-12T19:52:11.913840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.25040145 6
 
2.2%
35.24007125 4
 
1.5%
35.18835391 3
 
1.1%
35.18041948 3
 
1.1%
35.23007243 3
 
1.1%
35.24366886 3
 
1.1%
35.2300517 3
 
1.1%
35.22914478 3
 
1.1%
35.17569232 3
 
1.1%
35.17664848 3
 
1.1%
Other values (205) 238
87.5%
ValueCountFrequency (%)
35.16359891 1
 
0.4%
35.16581697 2
0.7%
35.169464 1
 
0.4%
35.17167109 2
0.7%
35.17569232 3
1.1%
35.17613853 1
 
0.4%
35.17644011 2
0.7%
35.17664848 3
1.1%
35.17678715 1
 
0.4%
35.18041948 3
1.1%
ValueCountFrequency (%)
35.34515965 1
0.4%
35.33789246 2
0.7%
35.32454629 1
0.4%
35.32359938 1
0.4%
35.32311151 1
0.4%
35.32265948 1
0.4%
35.32256653 1
0.4%
35.32248945 1
0.4%
35.32231527 1
0.4%
35.32055558 1
0.4%

경도
Real number (ℝ)

Distinct215
Distinct (%)79.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.82865
Minimum128.71609
Maximum128.96915
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-12T19:52:12.321312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.71609
5-th percentile128.7442
Q1128.77795
median128.82574
Q3128.87217
95-th percentile128.91499
Maximum128.96915
Range0.2530601
Interquartile range (IQR)0.094220425

Descriptive statistics

Standard deviation0.05541262
Coefficient of variation (CV)0.00043012654
Kurtosis-0.88273557
Mean128.82865
Median Absolute Deviation (MAD)0.04672105
Skewness0.098778752
Sum35041.392
Variance0.0030705584
MonotonicityNot monotonic
2023-12-12T19:52:12.638351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.9011955 6
 
2.2%
128.9101665 4
 
1.5%
128.8248195 3
 
1.1%
128.8287159 3
 
1.1%
128.8861074 3
 
1.1%
128.8699177 3
 
1.1%
128.8853382 3
 
1.1%
128.8721665 3
 
1.1%
128.8266645 3
 
1.1%
128.8232553 3
 
1.1%
Other values (205) 238
87.5%
ValueCountFrequency (%)
128.7160933 1
0.4%
128.7178667 1
0.4%
128.7192361 1
0.4%
128.7216428 1
0.4%
128.7216813 1
0.4%
128.7227603 1
0.4%
128.7247371 1
0.4%
128.7308016 1
0.4%
128.7330838 1
0.4%
128.7369555 1
0.4%
ValueCountFrequency (%)
128.9691534 1
0.4%
128.9431439 1
0.4%
128.9308398 1
0.4%
128.9307556 1
0.4%
128.9263414 1
0.4%
128.9243482 1
0.4%
128.9220217 1
0.4%
128.9202619 1
0.4%
128.9201518 1
0.4%
128.9183322 1
0.4%

Interactions

2023-12-12T19:52:02.845124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:52:00.871514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:52:01.513735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:52:02.140126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:52:02.986331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:52:01.043995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:52:01.649554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:52:02.281209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:52:03.130135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:52:01.205310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:52:01.830959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:52:02.443060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:52:03.308002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:52:01.378975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:52:01.999506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:52:02.664455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T19:52:12.828411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지면적급수시설구분명시설총규모영업상태위도경도
소재지면적1.0000.0001.0000.0000.2520.164
급수시설구분명0.0001.0000.0000.3340.4370.156
시설총규모1.0000.0001.0000.0610.2880.323
영업상태0.0000.3340.0611.0000.3190.176
위도0.2520.4370.2880.3191.0000.832
경도0.1640.1560.3230.1760.8321.000
2023-12-12T19:52:13.049719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
영업상태급수시설구분명
영업상태1.0000.217
급수시설구분명0.2171.000
2023-12-12T19:52:13.221699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지면적시설총규모위도경도급수시설구분명영업상태
소재지면적1.0000.994-0.1360.0300.0000.000
시설총규모0.9941.000-0.106-0.1420.0000.045
위도-0.136-0.1061.000-0.2920.3300.241
경도0.030-0.142-0.2921.0000.1170.136
급수시설구분명0.0000.0000.3300.1171.0000.217
영업상태0.0000.0450.2410.1360.2171.000

Missing values

2023-12-12T19:52:03.530783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:52:03.864880image/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.
2023-12-12T19:52:04.131631image/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

사업장명소재지면적지번주소도로명주소위생업태명급수시설구분명다중이용업소여부시설총규모영업상태폐업일자위도경도
0(주)유니온푸드 경원테크190.8경상남도 김해시 진례면 고모리 1582-6번지 1층경상남도 김해시 진례면 테크노밸리1로 71, 1층위탁급식영업상수도전용N190.8영업<NA>35.266527128.772123
1(주)유니온푸드 동원테크108.0경상남도 김해시 진례면 고모리 1045번지경상남도 김해시 진례면 고모로 480위탁급식영업지하수전용N108.0영업<NA>35.266705128.776282
2김해축협 배합사료공장145.82경상남도 김해시 한림면 병동리 1105번지 1층경상남도 김해시 한림면 고모로 775, 1층위탁급식영업상수도전용N145.82영업<NA>35.290642128.778724
3(주)제이푸드코리아405.9경상남도 김해시 주촌면 농소리 623-1번지경상남도 김해시 주촌면 골든루트로 104-2위탁급식영업상수도전용N405.9영업<NA>35.214787128.830355
4(주)동원홈푸드 티엠씨점324.0경상남도 김해시 진례면 담안리 1260경상남도 김해시 진례면 고모로324번길 135-59위탁급식영업상수도전용N324.0영업<NA>35.251093128.782687
5롯데푸드(주)롯데로지스틱스 김해점295.5경상남도 김해시 신문동 1419 롯데물류창고 직원식당 3층경상남도 김해시 칠산로 128-1, 롯데물류창고 직원식당 3층 (신문동)위탁급식영업상수도전용N295.5영업<NA>35.184042128.833034
6(주)참다올푸드551.46경상남도 김해시 삼계동 60번지 가야대학교 옥녀관, 3층 5동경상남도 김해시 삼계로 208, 가야대학교 옥녀관 5동 3층 (삼계동)위탁급식영업상수도전용N551.46영업<NA>35.270705128.872024
7(주)참다올푸드 삼원동관점173.8경상남도 김해시 진영읍 본산리 0번지 본산농공단지 2블럭 4로트<NA>위탁급식영업상수도전용N173.8영업<NA>35.319664128.750151
8(주)푸드란 디아이시스템점87.5경상남도 김해시 한림면 신천리 517번지 1층 C동경상남도 김해시 한림면 김해대로 1458-26, C동 1층위탁급식영업지하수전용N87.5영업<NA>35.275601128.831071
9(주)씨엠 연합화스너228.97경상남도 김해시 주촌면 농소리 629-6경상남도 김해시 주촌면 골든루트로66번길 48-5위탁급식영업상수도전용N228.97영업<NA>35.21303128.836762
사업장명소재지면적지번주소도로명주소위생업태명급수시설구분명다중이용업소여부시설총규모영업상태폐업일자위도경도
262(주)가내찬 와이디아이점154.59경상남도 김해시 진영읍 죽곡리 10-5 나동경상남도 김해시 진영읍 서부로179번길 62, 나동위탁급식영업상수도전용N154.59폐업2020-11-0435.28614128.773207
263(주)삼호푸드시스템608.0경상남도 김해시 삼방동 112-1번지<NA>위탁급식영업상수도전용N608.0폐업2010-06-0135.240071128.910167
264우정식당170.0경상남도 김해시 율하동 율하택지개발지구번지 12블럭 2공구<NA>위탁급식영업지하수전용N170.0폐업2009-04-0935.176648128.823255
265(주)선재가311.9경상남도 김해시 삼방동 산 57-1번지<NA>위탁급식영업지하수전용N311.9폐업2007-06-0135.258419128.903948
266고려요양병원 원내식당49.0경상남도 김해시 삼정동 13-1번지<NA>위탁급식영업상수도전용N49.0폐업2011-12-2835.235094128.893352
267소머리국밥326.09경상남도 김해시 진례면 송현리 1009-1 1층경상남도 김해시 진례면 고모로180번길 97-3, 1층위탁급식영업지하수전용N326.09폐업2021-06-2535.241854128.77766
268삼정건설 현장식당201.6경상남도 김해시 삼계동 1060-15 사무실동 1층<NA>위탁급식영업상수도전용N201.6폐업2020-10-2335.272716128.861095
269(주)흥아포밍2공장 푸드란353.4경상남도 김해시 주촌면 망덕리 876-2 2층 가동경상남도 김해시 주촌면 골든루트로129번길 160, 가동 2층위탁급식영업상수도전용N353.4폐업2021-06-1735.220593128.823308
270(주)참새미178.2경상남도 김해시 장유동 0번지 김해율하2지구 S3블럭 시티건설현장<NA>위탁급식영업상수도전용N178.2폐업2019-07-1735.165817128.831769
271씨제이프레시웨이(주) 롯데워터파크 기숙사동303.99경상남도 김해시 신문동 1417 105동경상남도 김해시 장유로 555, 김해롯데워터파크 기숙사동 105동 (신문동)위탁급식영업상수도전용N303.99폐업2021-02-1935.180419128.828716