Overview

Dataset statistics

Number of variables7
Number of observations45
Missing cells6
Missing cells (%)1.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.7 KiB
Average record size in memory61.9 B

Variable types

Numeric3
Text3
Categorical1

Dataset

Description경상남도 김해시 농약판매업체 현황에 대한 데이터로 상호,도,군,도로명주소,지번주소,위도,경도 등의 항목을 제공합니다.
Author경상남도 김해시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15092291

Alerts

데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 경도High correlation
경도 is highly overall correlated with 연번High correlation
전화번호 has 6 (13.3%) missing valuesMissing
연번 has unique valuesUnique
상호 has unique valuesUnique
도로명주소 has unique valuesUnique

Reproduction

Analysis started2024-01-05 22:07:23.669770
Analysis finished2024-01-05 22:07:27.261588
Duration3.59 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23
Minimum1
Maximum45
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2024-01-05T22:07:27.468423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.2
Q112
median23
Q334
95-th percentile42.8
Maximum45
Range44
Interquartile range (IQR)22

Descriptive statistics

Standard deviation13.133926
Coefficient of variation (CV)0.57104024
Kurtosis-1.2
Mean23
Median Absolute Deviation (MAD)11
Skewness0
Sum1035
Variance172.5
MonotonicityStrictly increasing
2024-01-05T22:07:27.787239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
1 1
 
2.2%
35 1
 
2.2%
26 1
 
2.2%
27 1
 
2.2%
28 1
 
2.2%
29 1
 
2.2%
30 1
 
2.2%
31 1
 
2.2%
32 1
 
2.2%
33 1
 
2.2%
Other values (35) 35
77.8%
ValueCountFrequency (%)
1 1
2.2%
2 1
2.2%
3 1
2.2%
4 1
2.2%
5 1
2.2%
6 1
2.2%
7 1
2.2%
8 1
2.2%
9 1
2.2%
10 1
2.2%
ValueCountFrequency (%)
45 1
2.2%
44 1
2.2%
43 1
2.2%
42 1
2.2%
41 1
2.2%
40 1
2.2%
39 1
2.2%
38 1
2.2%
37 1
2.2%
36 1
2.2%

상호
Text

UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size492.0 B
2024-01-05T22:07:28.134774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length7
Mean length7.2444444
Min length4

Characters and Unicode

Total characters326
Distinct characters99
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 (%)100.0%

Sample

1st row흥농종묘농약사
2nd row동아종합원예사
3rd row신우농약사
4th row가야농약종묘사
5th row대동농협농약사
ValueCountFrequency (%)
흥농종묘농약사 1
 
2.2%
제일농약종묘사 1
 
2.2%
대동농약종묘사 1
 
2.2%
선진농약종묘사 1
 
2.2%
주식회사윈터그린 1
 
2.2%
진례농업협동조합 1
 
2.2%
진례농약종묘사 1
 
2.2%
정진농약종묘사 1
 
2.2%
풍년농약종묘사 1
 
2.2%
현대종묘농약사 1
 
2.2%
Other values (35) 35
77.8%
2024-01-05T22:07:28.783732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
농 44
 
13.5%
사 31
 
9.5%
약 28
 
8.6%
종 23
 
7.1%
묘 21
 
6.4%
협 11
 
3.4%
동 11
 
3.4%
원 8
 
2.5%
대 7
 
2.1%
합 6
 
1.8%
Other values (89) 136
41.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 320
98.2%
Other Symbol 2
 
0.6%
Uppercase Letter 2
 
0.6%
Open Punctuation 1
 
0.3%
Close Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
농 44
 
13.8%
사 31
 
9.7%
약 28
 
8.8%
종 23
 
7.2%
묘 21
 
6.6%
협 11
 
3.4%
동 11
 
3.4%
원 8
 
2.5%
대 7
 
2.2%
합 6
 
1.9%
Other values (84) 130
40.6%
Uppercase Letter
ValueCountFrequency (%)
N 1
50.0%
K 1
50.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 322
98.8%
Latin 2
 
0.6%
Common 2
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
농 44
 
13.7%
사 31
 
9.6%
약 28
 
8.7%
종 23
 
7.1%
묘 21
 
6.5%
협 11
 
3.4%
동 11
 
3.4%
원 8
 
2.5%
대 7
 
2.2%
합 6
 
1.9%
Other values (85) 132
41.0%
Latin
ValueCountFrequency (%)
N 1
50.0%
K 1
50.0%
Common
ValueCountFrequency (%)
( 1
50.0%
) 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 320
98.2%
ASCII 4
 
1.2%
None 2
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
농 44
 
13.8%
사 31
 
9.7%
약 28
 
8.8%
종 23
 
7.2%
묘 21
 
6.6%
협 11
 
3.4%
동 11
 
3.4%
원 8
 
2.5%
대 7
 
2.2%
합 6
 
1.9%
Other values (84) 130
40.6%
None
ValueCountFrequency (%)
㈜ 2
100.0%
ASCII
ValueCountFrequency (%)
N 1
25.0%
K 1
25.0%
( 1
25.0%
) 1
25.0%

도로명주소
Text

UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size492.0 B
2024-01-05T22:07:29.177130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length27
Mean length20.888889
Min length15

Characters and Unicode

Total characters940
Distinct characters57
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

Unique45 ?
Unique (%)100.0%

Sample

1st row경상남도 김해시 가락로 6-1
2nd row경상남도 김해시 가락로 14
3rd row경상남도 김해시 가락로23번길 11 1층
4th row경상남도 김해시 가락로 11-1
5th row경상남도 김해시 대동면 동남로49번길 87
ValueCountFrequency (%)
경상남도 46
21.3%
김해시 46
21.3%
대동면 8
 
3.7%
진영읍 7
 
3.2%
대동로 4
 
1.9%
주촌면 4
 
1.9%
한림면 3
 
1.4%
진영로 3
 
1.4%
진례로 3
 
1.4%
진례면 3
 
1.4%
Other values (73) 89
41.2%
2024-01-05T22:07:30.082732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
171
18.2%
상 50
 
5.3%
남 48
 
5.1%
경 46
 
4.9%
도 46
 
4.9%
김 46
 
4.9%
해 46
 
4.9%
시 46
 
4.9%
로 44
 
4.7%
1 37
 
3.9%
Other values (47) 360
38.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 585
62.2%
Decimal Number 175
 
18.6%
Space Separator 171
 
18.2%
Dash Punctuation 9
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 50
 
8.5%
남 48
 
8.2%
경 46
 
7.9%
도 46
 
7.9%
김 46
 
7.9%
해 46
 
7.9%
시 46
 
7.9%
로 44
 
7.5%
면 22
 
3.8%
동 21
 
3.6%
Other values (35) 170
29.1%
Decimal Number
ValueCountFrequency (%)
1 37
21.1%
2 26
14.9%
3 23
13.1%
6 20
11.4%
4 16
9.1%
8 14
 
8.0%
7 11
 
6.3%
0 10
 
5.7%
9 9
 
5.1%
5 9
 
5.1%
Space Separator
ValueCountFrequency (%)
171
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 585
62.2%
Common 355
37.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 50
 
8.5%
남 48
 
8.2%
경 46
 
7.9%
도 46
 
7.9%
김 46
 
7.9%
해 46
 
7.9%
시 46
 
7.9%
로 44
 
7.5%
면 22
 
3.8%
동 21
 
3.6%
Other values (35) 170
29.1%
Common
ValueCountFrequency (%)
171
48.2%
1 37
 
10.4%
2 26
 
7.3%
3 23
 
6.5%
6 20
 
5.6%
4 16
 
4.5%
8 14
 
3.9%
7 11
 
3.1%
0 10
 
2.8%
9 9
 
2.5%
Other values (2) 18
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 585
62.2%
ASCII 355
37.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
171
48.2%
1 37
 
10.4%
2 26
 
7.3%
3 23
 
6.5%
6 20
 
5.6%
4 16
 
4.5%
8 14
 
3.9%
7 11
 
3.1%
0 10
 
2.8%
9 9
 
2.5%
Other values (2) 18
 
5.1%
Hangul
ValueCountFrequency (%)
상 50
 
8.5%
남 48
 
8.2%
경 46
 
7.9%
도 46
 
7.9%
김 46
 
7.9%
해 46
 
7.9%
시 46
 
7.9%
로 44
 
7.5%
면 22
 
3.8%
동 21
 
3.6%
Other values (35) 170
29.1%

위도
Real number (ℝ)

Distinct44
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.256839
Minimum35.196041
Maximum35.373799
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2024-01-05T22:07:30.408117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.196041
5-th percentile35.199895
Q135.222281
median35.236443
Q335.302085
95-th percentile35.33294
Maximum35.373799
Range0.17775739
Interquartile range (IQR)0.07980348

Descriptive statistics

Standard deviation0.047307305
Coefficient of variation (CV)0.0013417909
Kurtosis-0.23809883
Mean35.256839
Median Absolute Deviation (MAD)0.02553634
Skewness0.78322268
Sum1586.5578
Variance0.0022379811
MonotonicityNot monotonic
2024-01-05T22:07:30.831129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
35.25663319 2
 
4.4%
35.22714148 1
 
2.2%
35.22215689 1
 
2.2%
35.2370252 1
 
2.2%
35.25012748 1
 
2.2%
35.24780821 1
 
2.2%
35.24699304 1
 
2.2%
35.30336104 1
 
2.2%
35.30480695 1
 
2.2%
35.30265846 1
 
2.2%
Other values (34) 34
75.6%
ValueCountFrequency (%)
35.19604125 1
2.2%
35.19853602 1
2.2%
35.19983048 1
2.2%
35.20015233 1
2.2%
35.20063809 1
2.2%
35.20743643 1
2.2%
35.21090624 1
2.2%
35.21150939 1
2.2%
35.2165309 1
2.2%
35.22106467 1
2.2%
ValueCountFrequency (%)
35.37379864 1
2.2%
35.37317943 1
2.2%
35.3349853 1
2.2%
35.3247592 1
2.2%
35.32212848 1
2.2%
35.30852702 1
2.2%
35.30480695 1
2.2%
35.30467387 1
2.2%
35.3040972 1
2.2%
35.30336104 1
2.2%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct44
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.84575
Minimum128.72676
Maximum128.98991
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2024-01-05T22:07:31.325913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.72676
5-th percentile128.73334
Q1128.803
median128.84175
Q3128.88962
95-th percentile128.98368
Maximum128.98991
Range0.2631528
Interquartile range (IQR)0.0866181

Descriptive statistics

Standard deviation0.07841212
Coefficient of variation (CV)0.00060857361
Kurtosis-0.88129842
Mean128.84575
Median Absolute Deviation (MAD)0.047863
Skewness0.20762815
Sum5798.0585
Variance0.0061484606
MonotonicityNot monotonic
2024-01-05T22:07:31.853598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
128.8204174 2
 
4.4%
128.8827916 1
 
2.2%
128.85008 1
 
2.2%
128.8417536 1
 
2.2%
128.7478383 1
 
2.2%
128.7482675 1
 
2.2%
128.7488973 1
 
2.2%
128.7307025 1
 
2.2%
128.7345531 1
 
2.2%
128.7350724 1
 
2.2%
Other values (34) 34
75.6%
ValueCountFrequency (%)
128.7267557 1
2.2%
128.7307025 1
2.2%
128.733033 1
2.2%
128.7345531 1
2.2%
128.7350724 1
2.2%
128.7356463 1
2.2%
128.7478383 1
2.2%
128.7482675 1
2.2%
128.7488973 1
2.2%
128.7614096 1
2.2%
ValueCountFrequency (%)
128.9899085 1
2.2%
128.9847315 1
2.2%
128.9844743 1
2.2%
128.9804885 1
2.2%
128.9505039 1
2.2%
128.9493494 1
2.2%
128.9491141 1
2.2%
128.9326163 1
2.2%
128.9321262 1
2.2%
128.9263481 1
2.2%

전화번호
Text

MISSING 

Distinct38
Distinct (%)97.4%
Missing6
Missing (%)13.3%
Memory size492.0 B
2024-01-05T22:07:32.323681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters468
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

Unique37 ?
Unique (%)94.9%

Sample

1st row055-332-5060
2nd row055-335-5300
3rd row055-328-6113
4th row055-335-7716
5th row055-331-6590
ValueCountFrequency (%)
055-331-3105 2
 
5.1%
055-343-2077 1
 
2.6%
055-342-7441 1
 
2.6%
055-332-5060 1
 
2.6%
055-343-6106 1
 
2.6%
055-345-3641 1
 
2.6%
055-345-5056 1
 
2.6%
055-346-6523 1
 
2.6%
055-343-2044 1
 
2.6%
055-343-4078 1
 
2.6%
Other values (28) 28
71.8%
2024-01-05T22:07:32.890578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 104
22.2%
3 80
17.1%
- 78
16.7%
0 63
13.5%
1 30
 
6.4%
4 28
 
6.0%
2 27
 
5.8%
6 21
 
4.5%
7 18
 
3.8%
8 14
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 390
83.3%
Dash Punctuation 78
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 104
26.7%
3 80
20.5%
0 63
16.2%
1 30
 
7.7%
4 28
 
7.2%
2 27
 
6.9%
6 21
 
5.4%
7 18
 
4.6%
8 14
 
3.6%
9 5
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 78
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 468
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 104
22.2%
3 80
17.1%
- 78
16.7%
0 63
13.5%
1 30
 
6.4%
4 28
 
6.0%
2 27
 
5.8%
6 21
 
4.5%
7 18
 
3.8%
8 14
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 468
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 104
22.2%
3 80
17.1%
- 78
16.7%
0 63
13.5%
1 30
 
6.4%
4 28
 
6.0%
2 27
 
5.8%
6 21
 
4.5%
7 18
 
3.8%
8 14
 
3.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size492.0 B
2022-08-18
45 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-08-18
2nd row2022-08-18
3rd row2022-08-18
4th row2022-08-18
5th row2022-08-18

Common Values

ValueCountFrequency (%)
2022-08-18 45
100.0%

Length

2024-01-05T22:07:33.293975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-05T22:07:33.597299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-08-18 45
100.0%

Interactions

2024-01-05T22:07:25.983330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T22:07:24.152297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T22:07:25.177341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T22:07:26.223282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T22:07:24.477736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T22:07:25.416039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T22:07:26.483605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T22:07:24.884193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-05T22:07:25.712239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-05T22:07:33.795576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번상호도로명주소위도경도전화번호
연번1.0001.0001.0000.8100.9060.946
상호1.0001.0001.0001.0001.0001.000
도로명주소1.0001.0001.0001.0001.0001.000
위도0.8101.0001.0001.0000.8361.000
경도0.9061.0001.0000.8361.0001.000
전화번호0.9461.0001.0001.0001.0001.000
2024-01-05T22:07:34.055636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도
연번1.0000.206-0.721
위도0.2061.000-0.341
경도-0.721-0.3411.000

Missing values

2024-01-05T22:07:26.807787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-05T22:07:27.117830image/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

연번상호도로명주소위도경도전화번호데이터기준일자
01흥농종묘농약사경상남도 김해시 가락로 6-135.227141128.882792055-332-50602022-08-18
12동아종합원예사경상남도 김해시 가락로 1435.22771128.882688055-335-53002022-08-18
23신우농약사경상남도 김해시 가락로23번길 11 1층35.228325128.881179055-328-61132022-08-18
34가야농약종묘사경상남도 김해시 가락로 11-135.227595128.882379<NA>2022-08-18
45대동농협농약사경상남도 김해시 대동면 동남로49번길 8735.235909128.984732055-335-77162022-08-18
56대동농협대중지점농약사경상남도 김해시 대동면 대동로 28235.235417128.949349055-331-65902022-08-18
67덕산원예농약사경상남도 김해시 대동면 동북로 5335.281274128.980489055-321-52522022-08-18
78연안농약종묘사경상남도 김해시 경상남도 김해시 대동면 동남로 49번길 9535.236443128.984474055-335-51622022-08-18
89제이에이치케미칼경상남도 김해시 대동면 대동로 63-135.224802128.932616<NA>2022-08-18
910김해대동농약종묘사경상남도 김해시 대동면 대동로 28335.235968128.949114<NA>2022-08-18
연번상호도로명주소위도경도전화번호데이터기준일자
3536경남단감원예농협경상남도 김해시 진영읍 여래로 2335.304097128.735646055-343-61062022-08-18
3637농민원예사경상남도 김해시 진영읍 진영로184번길 7-235.302085128.733033055-342-25342022-08-18
3738㈜희망나무종합병원경상남도 김해시 진영읍 진영로 45835.295897128.76141055-345-88852022-08-18
3839칠산농약종묘사경상남도 김해시 칠산로425번길 22-1035.210906128.851522055-323-35732022-08-18
3940풍류종묘농약사경상남도 김해시 칠산로441번길 6-835.211509128.852912055-323-13772022-08-18
4041건국영농경상남도 김해시 칠산로237번길 6-2635.196041128.845217055-323-39332022-08-18
4142㈜포레나무병원경상남도 김해시 칠산로 397 204호35.207436128.852716055-312-73162022-08-18
4243흥농종묘농약경상남도 김해시 한림면 한림로 38835.322128128.802999055-342-74412022-08-18
4344한림농협시산지소경상남도 김해시 한림면 한림로 57035.334985128.791631055-342-80802022-08-18
4445한림전원농약종묘사경상남도 김해시 한림면 한림로398번길 1935.324759128.803201055-345-08572022-08-18