Overview

Dataset statistics

Number of variables11
Number of observations27
Missing cells18
Missing cells (%)6.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.6 KiB
Average record size in memory96.9 B

Variable types

Text4
Categorical2
Numeric4
Boolean1

Dataset

Description김해시 식품첨가물제조업 현황(사업장명,영업상태,전화번호,주소,위도 및 경도,급수시설구분명,소재지면적,시설총규모,다중이용업소여부)
Author경상남도 김해시
URLhttps://www.data.go.kr/data/15033409/fileData.do

Alerts

다중이용업소여부 has constant value ""Constant
경도 is highly overall correlated with 급수시설구분명High correlation
소재지면적 is highly overall correlated with 시설총규모High correlation
시설총규모 is highly overall correlated with 소재지면적High correlation
급수시설구분명 is highly overall correlated with 경도High correlation
전화번호 has 2 (7.4%) missing valuesMissing
지번주소 has 1 (3.7%) missing valuesMissing
도로명주소 has 9 (33.3%) missing valuesMissing
위도 has 1 (3.7%) missing valuesMissing
경도 has 1 (3.7%) missing valuesMissing
소재지면적 has 4 (14.8%) missing valuesMissing
시설총규모 has 20 (74.1%) zerosZeros

Reproduction

Analysis started2023-12-12 22:48:58.560220
Analysis finished2023-12-12 22:49:00.469986
Duration1.91 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사업장명
Text

Distinct26
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-12-13T07:49:00.583982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length10
Mean length7.1481481
Min length2

Characters and Unicode

Total characters193
Distinct characters71
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)92.6%

Sample

1st row(주)케이아이웍스
2nd row그린풀
3rd row청아산업
4th row대호그린
5th row농업회사법인주식회사 엔투엔
ValueCountFrequency (%)
케이비에프(주 2
 
6.7%
주식회사 2
 
6.7%
주)엠에스바이오 1
 
3.3%
주)한정성 1
 
3.3%
바이오애드 1
 
3.3%
주)다신제약 1
 
3.3%
주)유원코프 1
 
3.3%
백경식품(주 1
 
3.3%
복원환경 1
 
3.3%
태림농산 1
 
3.3%
Other values (18) 18
60.0%
2023-12-13T07:49:00.883073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 17
 
8.8%
( 14
 
7.3%
) 14
 
7.3%
식 9
 
4.7%
이 7
 
3.6%
에 7
 
3.6%
사 7
 
3.6%
회 5
 
2.6%
품 5
 
2.6%
프 5
 
2.6%
Other values (61) 103
53.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 156
80.8%
Open Punctuation 14
 
7.3%
Close Punctuation 14
 
7.3%
Uppercase Letter 4
 
2.1%
Space Separator 3
 
1.6%
Other Punctuation 2
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 17
 
10.9%
식 9
 
5.8%
이 7
 
4.5%
에 7
 
4.5%
사 7
 
4.5%
회 5
 
3.2%
품 5
 
3.2%
프 5
 
3.2%
산 4
 
2.6%
업 4
 
2.6%
Other values (54) 86
55.1%
Uppercase Letter
ValueCountFrequency (%)
F 2
50.0%
C 1
25.0%
G 1
25.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
& 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 156
80.8%
Common 33
 
17.1%
Latin 4
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 17
 
10.9%
식 9
 
5.8%
이 7
 
4.5%
에 7
 
4.5%
사 7
 
4.5%
회 5
 
3.2%
품 5
 
3.2%
프 5
 
3.2%
산 4
 
2.6%
업 4
 
2.6%
Other values (54) 86
55.1%
Common
ValueCountFrequency (%)
( 14
42.4%
) 14
42.4%
3
 
9.1%
& 2
 
6.1%
Latin
ValueCountFrequency (%)
F 2
50.0%
C 1
25.0%
G 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 156
80.8%
ASCII 37
 
19.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 17
 
10.9%
식 9
 
5.8%
이 7
 
4.5%
에 7
 
4.5%
사 7
 
4.5%
회 5
 
3.2%
품 5
 
3.2%
프 5
 
3.2%
산 4
 
2.6%
업 4
 
2.6%
Other values (54) 86
55.1%
ASCII
ValueCountFrequency (%)
( 14
37.8%
) 14
37.8%
3
 
8.1%
& 2
 
5.4%
F 2
 
5.4%
C 1
 
2.7%
G 1
 
2.7%

영업상태명
Categorical

Distinct2
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size348.0 B
폐업
16 
영업
11 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 16
59.3%
영업 11
40.7%

Length

2023-12-13T07:49:01.001180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:49:01.097468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 16
59.3%
영업 11
40.7%

전화번호
Text

MISSING 

Distinct21
Distinct (%)84.0%
Missing2
Missing (%)7.4%
Memory size348.0 B
2023-12-13T07:49:01.286054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.04
Min length12

Characters and Unicode

Total characters301
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

Unique17 ?
Unique (%)68.0%

Sample

1st row055-329-7071
2nd row055-328-9533
3rd row055-327-4412
4th row055-345-3866
5th row055-343-0524
ValueCountFrequency (%)
055-345-4016 2
 
8.0%
055-343-2757 2
 
8.0%
055-329-0525 2
 
8.0%
055-337-3371 2
 
8.0%
055-902-9900 1
 
4.0%
055-312-7505 1
 
4.0%
055-329-6322 1
 
4.0%
055-346-0142 1
 
4.0%
055-323-8888 1
 
4.0%
055-323-8480 1
 
4.0%
Other values (11) 11
44.0%
2023-12-13T07:49:01.611351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 66
21.9%
- 50
16.6%
0 45
15.0%
3 43
14.3%
4 22
 
7.3%
2 20
 
6.6%
8 14
 
4.7%
7 13
 
4.3%
1 10
 
3.3%
9 10
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 251
83.4%
Dash Punctuation 50
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 66
26.3%
0 45
17.9%
3 43
17.1%
4 22
 
8.8%
2 20
 
8.0%
8 14
 
5.6%
7 13
 
5.2%
1 10
 
4.0%
9 10
 
4.0%
6 8
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 50
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 301
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 66
21.9%
- 50
16.6%
0 45
15.0%
3 43
14.3%
4 22
 
7.3%
2 20
 
6.6%
8 14
 
4.7%
7 13
 
4.3%
1 10
 
3.3%
9 10
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 301
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 66
21.9%
- 50
16.6%
0 45
15.0%
3 43
14.3%
4 22
 
7.3%
2 20
 
6.6%
8 14
 
4.7%
7 13
 
4.3%
1 10
 
3.3%
9 10
 
3.3%

지번주소
Text

MISSING 

Distinct25
Distinct (%)96.2%
Missing1
Missing (%)3.7%
Memory size348.0 B
2023-12-13T07:49:01.851512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length24.5
Mean length22.461538
Min length16

Characters and Unicode

Total characters584
Distinct characters66
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

Unique24 ?
Unique (%)92.3%

Sample

1st row경상남도 김해시 주촌면 농소리 158-1번지
2nd row경상남도 김해시 주촌면 천곡리 1086-2번지
3rd row경상남도 김해시 어방동 1065-16
4th row경상남도 김해시 진영읍 하계리 52-2번지 A동
5th row경상남도 김해시 화목동 269-2번지 1층
ValueCountFrequency (%)
경상남도 26
20.6%
김해시 26
20.6%
주촌면 8
 
6.3%
한림면 5
 
4.0%
진영읍 4
 
3.2%
1086-2번지 2
 
1.6%
송정리 2
 
1.6%
진례면 2
 
1.6%
천곡리 2
 
1.6%
내삼리 2
 
1.6%
Other values (44) 47
37.3%
2023-12-13T07:49:02.188717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
100
 
17.1%
상 27
 
4.6%
경 26
 
4.5%
남 26
 
4.5%
도 26
 
4.5%
김 26
 
4.5%
해 26
 
4.5%
시 26
 
4.5%
지 22
 
3.8%
리 21
 
3.6%
Other values (56) 258
44.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 364
62.3%
Space Separator 100
 
17.1%
Decimal Number 100
 
17.1%
Dash Punctuation 19
 
3.3%
Uppercase Letter 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 27
 
7.4%
경 26
 
7.1%
남 26
 
7.1%
도 26
 
7.1%
김 26
 
7.1%
해 26
 
7.1%
시 26
 
7.1%
지 22
 
6.0%
리 21
 
5.8%
번 20
 
5.5%
Other values (43) 118
32.4%
Decimal Number
ValueCountFrequency (%)
1 16
16.0%
2 15
15.0%
6 12
12.0%
4 11
11.0%
0 10
10.0%
9 10
10.0%
8 9
9.0%
3 7
7.0%
7 6
 
6.0%
5 4
 
4.0%
Space Separator
ValueCountFrequency (%)
100
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 364
62.3%
Common 219
37.5%
Latin 1
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 27
 
7.4%
경 26
 
7.1%
남 26
 
7.1%
도 26
 
7.1%
김 26
 
7.1%
해 26
 
7.1%
시 26
 
7.1%
지 22
 
6.0%
리 21
 
5.8%
번 20
 
5.5%
Other values (43) 118
32.4%
Common
ValueCountFrequency (%)
100
45.7%
- 19
 
8.7%
1 16
 
7.3%
2 15
 
6.8%
6 12
 
5.5%
4 11
 
5.0%
0 10
 
4.6%
9 10
 
4.6%
8 9
 
4.1%
3 7
 
3.2%
Other values (2) 10
 
4.6%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 364
62.3%
ASCII 220
37.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
100
45.5%
- 19
 
8.6%
1 16
 
7.3%
2 15
 
6.8%
6 12
 
5.5%
4 11
 
5.0%
0 10
 
4.5%
9 10
 
4.5%
8 9
 
4.1%
3 7
 
3.2%
Other values (3) 11
 
5.0%
Hangul
ValueCountFrequency (%)
상 27
 
7.4%
경 26
 
7.1%
남 26
 
7.1%
도 26
 
7.1%
김 26
 
7.1%
해 26
 
7.1%
시 26
 
7.1%
지 22
 
6.0%
리 21
 
5.8%
번 20
 
5.5%
Other values (43) 118
32.4%

도로명주소
Text

MISSING 

Distinct17
Distinct (%)94.4%
Missing9
Missing (%)33.3%
Memory size348.0 B
2023-12-13T07:49:02.430088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length31
Mean length26.555556
Min length22

Characters and Unicode

Total characters478
Distinct characters60
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

Unique16 ?
Unique (%)88.9%

Sample

1st row경상남도 김해시 주촌면 골든루트로 80-59, 602호
2nd row경상남도 김해시 주촌면 서부로1638번길 133-34
3rd row경상남도 김해시 김해대로2553번길 38-14 (어방동)
4th row경상남도 김해시 진영읍 하계로278번길 5-18, A동 1층
5th row경상남도 김해시 칠산로279번길 12-6, 1층 (화목동)
ValueCountFrequency (%)
경상남도 18
18.8%
김해시 18
18.8%
진영읍 4
 
4.2%
주촌면 4
 
4.2%
한림면 4
 
4.2%
1층 3
 
3.1%
본산로 2
 
2.1%
60-93 2
 
2.1%
100 1
 
1.0%
137 1
 
1.0%
Other values (39) 39
40.6%
2023-12-13T07:49:02.797158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
78
 
16.3%
1 21
 
4.4%
김 20
 
4.2%
해 20
 
4.2%
상 20
 
4.2%
경 18
 
3.8%
남 18
 
3.8%
도 18
 
3.8%
시 18
 
3.8%
로 18
 
3.8%
Other values (50) 229
47.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 267
55.9%
Decimal Number 107
22.4%
Space Separator 78
 
16.3%
Dash Punctuation 12
 
2.5%
Other Punctuation 5
 
1.0%
Close Punctuation 4
 
0.8%
Open Punctuation 4
 
0.8%
Uppercase Letter 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 20
 
7.5%
해 20
 
7.5%
상 20
 
7.5%
경 18
 
6.7%
남 18
 
6.7%
도 18
 
6.7%
시 18
 
6.7%
로 18
 
6.7%
길 11
 
4.1%
번 11
 
4.1%
Other values (34) 95
35.6%
Decimal Number
ValueCountFrequency (%)
1 21
19.6%
3 14
13.1%
2 13
12.1%
0 12
11.2%
5 10
9.3%
6 9
8.4%
9 9
8.4%
4 8
 
7.5%
8 6
 
5.6%
7 5
 
4.7%
Space Separator
ValueCountFrequency (%)
78
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 267
55.9%
Common 210
43.9%
Latin 1
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 20
 
7.5%
해 20
 
7.5%
상 20
 
7.5%
경 18
 
6.7%
남 18
 
6.7%
도 18
 
6.7%
시 18
 
6.7%
로 18
 
6.7%
길 11
 
4.1%
번 11
 
4.1%
Other values (34) 95
35.6%
Common
ValueCountFrequency (%)
78
37.1%
1 21
 
10.0%
3 14
 
6.7%
2 13
 
6.2%
0 12
 
5.7%
- 12
 
5.7%
5 10
 
4.8%
6 9
 
4.3%
9 9
 
4.3%
4 8
 
3.8%
Other values (5) 24
 
11.4%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 267
55.9%
ASCII 211
44.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
78
37.0%
1 21
 
10.0%
3 14
 
6.6%
2 13
 
6.2%
0 12
 
5.7%
- 12
 
5.7%
5 10
 
4.7%
6 9
 
4.3%
9 9
 
4.3%
4 8
 
3.8%
Other values (6) 25
 
11.8%
Hangul
ValueCountFrequency (%)
김 20
 
7.5%
해 20
 
7.5%
상 20
 
7.5%
경 18
 
6.7%
남 18
 
6.7%
도 18
 
6.7%
시 18
 
6.7%
로 18
 
6.7%
길 11
 
4.1%
번 11
 
4.1%
Other values (34) 95
35.6%

위도
Real number (ℝ)

MISSING 

Distinct25
Distinct (%)96.2%
Missing1
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean35.258534
Minimum35.184068
Maximum35.325189
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-13T07:49:02.927328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.184068
5-th percentile35.200489
Q135.230055
median35.246434
Q335.298638
95-th percentile35.319294
Maximum35.325189
Range0.14112121
Interquartile range (IQR)0.068583408

Descriptive statistics

Standard deviation0.041165009
Coefficient of variation (CV)0.001167519
Kurtosis-1.1403939
Mean35.258534
Median Absolute Deviation (MAD)0.030669365
Skewness0.12553308
Sum916.72188
Variance0.001694558
MonotonicityNot monotonic
2023-12-13T07:49:03.058538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
35.31114068 2
 
7.4%
35.21497472 1
 
3.7%
35.30188548 1
 
3.7%
35.2569908 1
 
3.7%
35.2387373 1
 
3.7%
35.22323138 1
 
3.7%
35.23872722 1
 
3.7%
35.22947988 1
 
3.7%
35.27631345 1
 
3.7%
35.3220123 1
 
3.7%
Other values (15) 15
55.6%
ValueCountFrequency (%)
35.18406822 1
3.7%
35.1985984 1
3.7%
35.20615888 1
3.7%
35.21497472 1
3.7%
35.22323138 1
3.7%
35.22916106 1
3.7%
35.22947988 1
3.7%
35.23178003 1
3.7%
35.23197385 1
3.7%
35.23872722 1
3.7%
ValueCountFrequency (%)
35.32518943 1
3.7%
35.3220123 1
3.7%
35.31114068 2
7.4%
35.31083905 1
3.7%
35.30404813 1
3.7%
35.30188548 1
3.7%
35.28889686 1
3.7%
35.28511028 1
3.7%
35.27631345 1
3.7%
35.26876172 1
3.7%

경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct25
Distinct (%)96.2%
Missing1
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean128.81793
Minimum128.73333
Maximum128.91549
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-13T07:49:03.189718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.73333
5-th percentile128.74331
Q1128.79992
median128.82831
Q3128.84183
95-th percentile128.90935
Maximum128.91549
Range0.1821539
Interquartile range (IQR)0.041911725

Descriptive statistics

Standard deviation0.051101056
Coefficient of variation (CV)0.0003966921
Kurtosis-0.30098371
Mean128.81793
Median Absolute Deviation (MAD)0.01990215
Skewness0.020593054
Sum3349.2662
Variance0.0026113179
MonotonicityNot monotonic
2023-12-13T07:49:03.295746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
128.7454735 2
 
7.4%
128.8322813 1
 
3.7%
128.8002918 1
 
3.7%
128.8424882 1
 
3.7%
128.7430848 1
 
3.7%
128.8295856 1
 
3.7%
128.7439906 1
 
3.7%
128.83666 1
 
3.7%
128.8388678 1
 
3.7%
128.8476983 1
 
3.7%
Other values (15) 15
55.6%
ValueCountFrequency (%)
128.7333347 1
3.7%
128.7430848 1
3.7%
128.7439906 1
3.7%
128.7454735 2
7.4%
128.7522537 1
3.7%
128.7997919 1
3.7%
128.8002918 1
3.7%
128.807894 1
3.7%
128.8106044 1
3.7%
128.8107763 1
3.7%
ValueCountFrequency (%)
128.9154886 1
3.7%
128.9103456 1
3.7%
128.9063816 1
3.7%
128.8510354 1
3.7%
128.8476983 1
3.7%
128.847087 1
3.7%
128.8424882 1
3.7%
128.8398498 1
3.7%
128.8388678 1
3.7%
128.83666 1
3.7%

급수시설구분명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size348.0 B
<NA>
19 
상수도전용
7 
전용상수도(특정시설의 자가용 수도)
 
1

Length

Max length19
Median length4
Mean length4.8148148
Min length4

Unique

Unique1 ?
Unique (%)3.7%

Sample

1st row상수도전용
2nd row<NA>
3rd row<NA>
4th row상수도전용
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 19
70.4%
상수도전용 7
 
25.9%
전용상수도(특정시설의 자가용 수도) 1
 
3.7%

Length

2023-12-13T07:49:03.413207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:49:03.800828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 19
65.5%
상수도전용 7
 
24.1%
전용상수도(특정시설의 1
 
3.4%
자가용 1
 
3.4%
수도 1
 
3.4%

소재지면적
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct23
Distinct (%)100.0%
Missing4
Missing (%)14.8%
Infinite0
Infinite (%)0.0%
Mean419.90348
Minimum21.3
Maximum2114.49
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-13T07:49:03.885629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21.3
5-th percentile29.3
Q150.195
median260
Q3361.5
95-th percentile1644.77
Maximum2114.49
Range2093.19
Interquartile range (IQR)311.305

Descriptive statistics

Standard deviation586.95837
Coefficient of variation (CV)1.3978412
Kurtosis2.7747891
Mean419.90348
Median Absolute Deviation (MAD)194.95
Skewness1.9328291
Sum9657.78
Variance344520.13
MonotonicityNot monotonic
2023-12-13T07:49:03.988505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
321.0 1
 
3.7%
139.62 1
 
3.7%
49.72 1
 
3.7%
260.0 1
 
3.7%
295.0 1
 
3.7%
262.5 1
 
3.7%
80.0 1
 
3.7%
403.0 1
 
3.7%
1485.2 1
 
3.7%
40.0 1
 
3.7%
Other values (13) 13
48.1%
(Missing) 4
 
14.8%
ValueCountFrequency (%)
21.3 1
3.7%
29.0 1
3.7%
32.0 1
3.7%
40.0 1
3.7%
49.14 1
3.7%
49.72 1
3.7%
50.67 1
3.7%
65.05 1
3.7%
80.0 1
3.7%
139.62 1
3.7%
ValueCountFrequency (%)
2114.49 1
3.7%
1662.5 1
3.7%
1485.2 1
3.7%
1144.0 1
3.7%
403.0 1
3.7%
402.0 1
3.7%
321.0 1
3.7%
295.0 1
3.7%
280.8 1
3.7%
277.2 1
3.7%

시설총규모
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct8
Distinct (%)29.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean91.761481
Minimum0
Maximum644.31
Zeros20
Zeros (%)74.1%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-13T07:49:04.075789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile583.601
Maximum644.31
Range644.31
Interquartile range (IQR)3

Descriptive statistics

Standard deviation206.17736
Coefficient of variation (CV)2.2468835
Kurtosis2.678698
Mean91.761481
Median Absolute Deviation (MAD)0
Skewness2.0593858
Sum2477.56
Variance42509.102
MonotonicityNot monotonic
2023-12-13T07:49:04.210183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0.0 20
74.1%
23.7 1
 
3.7%
184.32 1
 
3.7%
644.31 1
 
3.7%
593.33 1
 
3.7%
6.0 1
 
3.7%
465.0 1
 
3.7%
560.9 1
 
3.7%
ValueCountFrequency (%)
0.0 20
74.1%
6.0 1
 
3.7%
23.7 1
 
3.7%
184.32 1
 
3.7%
465.0 1
 
3.7%
560.9 1
 
3.7%
593.33 1
 
3.7%
644.31 1
 
3.7%
ValueCountFrequency (%)
644.31 1
 
3.7%
593.33 1
 
3.7%
560.9 1
 
3.7%
465.0 1
 
3.7%
184.32 1
 
3.7%
23.7 1
 
3.7%
6.0 1
 
3.7%
0.0 20
74.1%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size159.0 B
False
27 
ValueCountFrequency (%)
False 27
100.0%
2023-12-13T07:49:04.314254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Interactions

2023-12-13T07:48:59.857437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:48:58.935009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:48:59.224647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:48:59.542765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:48:59.929428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:48:59.007470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:48:59.324568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:48:59.617565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:49:00.005422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:48:59.083516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:48:59.406701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:48:59.714020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:49:00.083175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:48:59.146383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:48:59.471569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:48:59.789310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:49:04.383681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업장명영업상태명전화번호지번주소도로명주소위도경도급수시설구분명소재지면적시설총규모
사업장명1.0000.0001.0000.9881.0000.0001.0001.0001.0000.524
영업상태명0.0001.0000.4641.0000.0000.2270.4340.0000.0000.307
전화번호1.0000.4641.0000.9481.0000.9341.0001.0001.0000.504
지번주소0.9881.0000.9481.0001.0001.0001.0001.0001.0001.000
도로명주소1.0000.0001.0001.0001.0001.0001.0001.0001.0000.599
위도0.0000.2270.9341.0001.0001.0000.4591.0000.6510.692
경도1.0000.4341.0001.0001.0000.4591.0001.0000.4290.110
급수시설구분명1.0000.0001.0001.0001.0001.0001.0001.0000.0000.000
소재지면적1.0000.0001.0001.0001.0000.6510.4290.0001.0000.898
시설총규모0.5240.3070.5041.0000.5990.6920.1100.0000.8981.000
2023-12-13T07:49:04.508301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
영업상태명급수시설구분명
영업상태명1.0000.000
급수시설구분명0.0001.000
2023-12-13T07:49:04.602061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도소재지면적시설총규모영업상태명급수시설구분명
위도1.000-0.054-0.060-0.0810.0790.408
경도-0.0541.0000.0390.0180.4260.707
소재지면적-0.0600.0391.0000.7270.0000.000
시설총규모-0.0810.0180.7271.0000.3440.000
영업상태명0.0790.4260.0000.3441.0000.000
급수시설구분명0.4080.7070.0000.0000.0001.000

Missing values

2023-12-13T07:49:00.176283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:49:00.297976image/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.
2023-12-13T07:49:00.402620image/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

사업장명영업상태명전화번호지번주소도로명주소위도경도급수시설구분명소재지면적시설총규모다중이용업소여부
0(주)케이아이웍스폐업055-329-7071경상남도 김해시 주촌면 농소리 158-1번지경상남도 김해시 주촌면 골든루트로 80-59, 602호35.214975128.832281상수도전용50.670.0N
1그린풀폐업055-328-9533경상남도 김해시 주촌면 천곡리 1086-2번지경상남도 김해시 주촌면 서부로1638번길 133-3435.229161128.836638<NA>321.00.0N
2청아산업폐업055-327-4412경상남도 김해시 어방동 1065-16경상남도 김해시 김해대로2553번길 38-14 (어방동)35.231974128.906382<NA>65.050.0N
3대호그린폐업055-345-3866경상남도 김해시 진영읍 하계리 52-2번지 A동경상남도 김해시 진영읍 하계로278번길 5-18, A동 1층35.288897128.733335상수도전용21.30.0N
4농업회사법인주식회사 엔투엔영업<NA>경상남도 김해시 화목동 269-2번지 1층경상남도 김해시 칠산로279번길 12-6, 1층 (화목동)35.198598128.847087<NA>277.223.7N
5두원에프앤에프(F&F)영업055-343-0524경상남도 김해시 한림면 안곡리 43번지경상남도 김해시 한림면 안곡로492번길 5-4635.304048128.83985상수도전용280.8184.32N
6(주)제일화학영업055-343-0004경상남도 김해시 한림면 안곡리 624-9번지경상남도 김해시 한림면 안곡로 251-435.28511128.851035상수도전용32.00.0N
7에스디아이(주)영업070-8823-1588경상남도 김해시 부곡동 769번지경상남도 김해시 장유로 201 (부곡동)35.206159128.807894상수도전용29.00.0N
8케이비에프(주)영업055-337-3371경상남도 김해시 주촌면 원지리 1066경상남도 김해시 주촌면 서부로1637번길 20335.250793128.827027<NA>1662.5644.31N
9주식회사 신광식품영업055-343-2757경상남도 김해시 진영읍 본산리 940-4번지경상남도 김해시 진영읍 본산로 60-9335.311141128.745474<NA>2114.49593.33N
사업장명영업상태명전화번호지번주소도로명주소위도경도급수시설구분명소재지면적시설총규모다중이용업소여부
17(주)송호식품개발폐업055-338-8495경상남도 김해시 주촌면 내삼리 300번지<NA>35.242075128.810776<NA>403.00.0N
18쉘그린폐업055-323-8480경상남도 김해시 상동면 우계리 431번지경상남도 김해시 상동면 상동로375번길 62-135.310839128.910346<NA>80.00.0N
19태림농산폐업055-323-8888경상남도 김해시 생림면 봉림리 432번지경상남도 김해시 생림면 장재로520번안길 8-1435.322012128.847698<NA>262.50.0N
20복원환경폐업055-346-0142경상남도 김해시 한림면 신천리 260-12번지<NA>35.276313128.838868<NA>295.00.0N
21백경식품(주)폐업055-329-0525<NA><NA><NA><NA><NA><NA>0.0N
22(주)유원코프폐업055-329-6322경상남도 김해시 주촌면 천곡리 1086-2번지<NA>35.22948128.83666<NA>260.00.0N
23(주)다신제약폐업055-345-4016경상남도 김해시 진례면 송정리 718-46<NA>35.238727128.743991<NA><NA>0.0N
24주식회사 바이오애드폐업055-329-0525경상남도 김해시 주촌면 망덕리 278-2번지<NA>35.223231128.829586<NA>49.720.0N
25(주)다산제약식품사업부폐업055-345-4016경상남도 김해시 진례면 송정리 718-2번지<NA>35.238737128.743085<NA>139.620.0N
26케이비에프(주)폐업055-337-3371경상남도 김해시 주촌면 원지리<NA>35.256991128.842488<NA><NA>0.0N