Overview

Dataset statistics

Number of variables7
Number of observations360
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory20.5 KiB
Average record size in memory58.4 B

Variable types

Numeric2
Categorical2
Text3

Dataset

Description완도군 축산농장 현황자료(읍면별 농장별 위치와 규모 현황)
Author전라남도 완도군
URLhttps://www.data.go.kr/data/15063830/fileData.do

Alerts

주사육업종 is highly imbalanced (74.4%)Imbalance
연번 has unique valuesUnique
사육두수 has 29 (8.1%) zerosZeros

Reproduction

Analysis started2023-12-12 08:59:37.592050
Analysis finished2023-12-12 08:59:38.736975
Duration1.14 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct360
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean180.5
Minimum1
Maximum360
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2023-12-12T17:59:38.851622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile18.95
Q190.75
median180.5
Q3270.25
95-th percentile342.05
Maximum360
Range359
Interquartile range (IQR)179.5

Descriptive statistics

Standard deviation104.06729
Coefficient of variation (CV)0.57655006
Kurtosis-1.2
Mean180.5
Median Absolute Deviation (MAD)90
Skewness0
Sum64980
Variance10830
MonotonicityStrictly increasing
2023-12-12T17:59:39.027189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
249 1
 
0.3%
247 1
 
0.3%
246 1
 
0.3%
245 1
 
0.3%
244 1
 
0.3%
243 1
 
0.3%
242 1
 
0.3%
241 1
 
0.3%
240 1
 
0.3%
Other values (350) 350
97.2%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
360 1
0.3%
359 1
0.3%
358 1
0.3%
357 1
0.3%
356 1
0.3%
355 1
0.3%
354 1
0.3%
353 1
0.3%
352 1
0.3%
351 1
0.3%

읍면
Categorical

Distinct11
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
고금면
140 
완도읍
73 
약산면
51 
신지면
44 
군외면
20 
Other values (6)
32 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
고금면 140
38.9%
완도읍 73
20.3%
약산면 51
 
14.2%
신지면 44
 
12.2%
군외면 20
 
5.6%
금일읍 12
 
3.3%
노화읍 6
 
1.7%
생일면 6
 
1.7%
금당면 4
 
1.1%
청산면 3
 
0.8%

Length

2023-12-12T17:59:39.220471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
고금면 140
38.9%
완도읍 73
20.3%
약산면 51
 
14.2%
신지면 44
 
12.2%
군외면 20
 
5.6%
금일읍 12
 
3.3%
노화읍 6
 
1.7%
생일면 6
 
1.7%
금당면 4
 
1.1%
청산면 3
 
0.8%

사업장명칭
Text

Distinct120
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
2023-12-12T17:59:39.572441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length4
Mean length4.2361111
Min length3

Characters and Unicode

Total characters1525
Distinct characters133
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique114 ?
Unique (%)31.7%

Sample

1st row솔개농장
2nd row청해농장
3rd row개인농장
4th row백두목장
5th row시장축산
ValueCountFrequency (%)
개인농장 235
64.0%
현대농장 3
 
0.8%
농장 2
 
0.5%
청해농장 2
 
0.5%
우정축산 2
 
0.5%
오성축산 2
 
0.5%
청해농원 2
 
0.5%
약산흑염소솔중매농장 1
 
0.3%
약성흑염소농장 1
 
0.3%
서부흑염소 1
 
0.3%
Other values (116) 116
31.6%
2023-12-12T17:59:40.084797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 311
20.4%
농 306
20.1%
개 237
15.5%
인 235
15.4%
산 53
 
3.5%
축 48
 
3.1%
대 18
 
1.2%
소 13
 
0.9%
약 13
 
0.9%
흑 13
 
0.9%
Other values (123) 278
18.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1514
99.3%
Space Separator 7
 
0.5%
Decimal Number 4
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 311
20.5%
농 306
20.2%
개 237
15.7%
인 235
15.5%
산 53
 
3.5%
축 48
 
3.2%
대 18
 
1.2%
소 13
 
0.9%
약 13
 
0.9%
흑 13
 
0.9%
Other values (118) 267
17.6%
Decimal Number
ValueCountFrequency (%)
2 1
25.0%
5 1
25.0%
3 1
25.0%
1 1
25.0%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1514
99.3%
Common 11
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 311
20.5%
농 306
20.2%
개 237
15.7%
인 235
15.5%
산 53
 
3.5%
축 48
 
3.2%
대 18
 
1.2%
소 13
 
0.9%
약 13
 
0.9%
흑 13
 
0.9%
Other values (118) 267
17.6%
Common
ValueCountFrequency (%)
7
63.6%
2 1
 
9.1%
5 1
 
9.1%
3 1
 
9.1%
1 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1514
99.3%
ASCII 11
 
0.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 311
20.5%
농 306
20.2%
개 237
15.7%
인 235
15.5%
산 53
 
3.5%
축 48
 
3.2%
대 18
 
1.2%
소 13
 
0.9%
약 13
 
0.9%
흑 13
 
0.9%
Other values (118) 267
17.6%
ASCII
ValueCountFrequency (%)
7
63.6%
2 1
 
9.1%
5 1
 
9.1%
3 1
 
9.1%
1 1
 
9.1%

주사육업종
Categorical

IMBALANCE 

Distinct7
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
한우
320 
산양
 
15
돼지
 
13
염소
 
9
산란계
 
1
Other values (2)
 
2

Length

Max length3
Median length2
Mean length2.0027778
Min length2

Unique

Unique3 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
한우 320
88.9%
산양 15
 
4.2%
돼지 13
 
3.6%
염소 9
 
2.5%
산란계 1
 
0.3%
사슴 1
 
0.3%
육우 1
 
0.3%

Length

2023-12-12T17:59:40.276533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:59:40.408550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한우 320
88.9%
산양 15
 
4.2%
돼지 13
 
3.6%
염소 9
 
2.5%
산란계 1
 
0.3%
사슴 1
 
0.3%
육우 1
 
0.3%

사업장소재지(지번)
Text

Distinct350
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
2023-12-12T17:59:40.733453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length56
Mean length26.769444
Min length21

Characters and Unicode

Total characters9637
Distinct characters95
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique340 ?
Unique (%)94.4%

Sample

1st row전라남도 완도군 완도읍 대야리 785-1
2nd row전라남도 완도군 완도읍 대야리 386번지 1호
3rd row전라남도 완도군 완도읍 대야리 386번지 1호
4th row전라남도 완도군 완도읍 군내리 91번지 1호
5th row전라남도 완도군 완도읍 화흥리 677번지
ValueCountFrequency (%)
전라남도 360
17.5%
완도군 360
17.5%
고금면 140
 
6.8%
1호 73
 
3.5%
완도읍 73
 
3.5%
약산면 51
 
2.5%
신지면 44
 
2.1%
농상리 27
 
1.3%
청용리 21
 
1.0%
덕암리 21
 
1.0%
Other values (446) 889
43.2%
2023-12-12T17:59:41.228850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2363
24.5%
도 832
 
8.6%
완 433
 
4.5%
지 429
 
4.5%
군 383
 
4.0%
남 381
 
4.0%
번 364
 
3.8%
리 361
 
3.7%
1 360
 
3.7%
라 360
 
3.7%
Other values (85) 3371
35.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5636
58.5%
Space Separator 2363
24.5%
Decimal Number 1543
 
16.0%
Other Punctuation 49
 
0.5%
Dash Punctuation 42
 
0.4%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 832
14.8%
완 433
 
7.7%
지 429
 
7.6%
군 383
 
6.8%
남 381
 
6.8%
번 364
 
6.5%
리 361
 
6.4%
라 360
 
6.4%
전 360
 
6.4%
면 269
 
4.8%
Other values (70) 1464
26.0%
Decimal Number
ValueCountFrequency (%)
1 360
23.3%
3 154
10.0%
4 152
9.9%
2 151
9.8%
6 131
 
8.5%
5 129
 
8.4%
0 122
 
7.9%
7 120
 
7.8%
8 116
 
7.5%
9 108
 
7.0%
Space Separator
ValueCountFrequency (%)
2363
100.0%
Other Punctuation
ValueCountFrequency (%)
, 49
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 42
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5636
58.5%
Common 4001
41.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 832
14.8%
완 433
 
7.7%
지 429
 
7.6%
군 383
 
6.8%
남 381
 
6.8%
번 364
 
6.5%
리 361
 
6.4%
라 360
 
6.4%
전 360
 
6.4%
면 269
 
4.8%
Other values (70) 1464
26.0%
Common
ValueCountFrequency (%)
2363
59.1%
1 360
 
9.0%
3 154
 
3.8%
4 152
 
3.8%
2 151
 
3.8%
6 131
 
3.3%
5 129
 
3.2%
0 122
 
3.0%
7 120
 
3.0%
8 116
 
2.9%
Other values (5) 203
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5636
58.5%
ASCII 4001
41.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2363
59.1%
1 360
 
9.0%
3 154
 
3.8%
4 152
 
3.8%
2 151
 
3.8%
6 131
 
3.3%
5 129
 
3.2%
0 122
 
3.0%
7 120
 
3.0%
8 116
 
2.9%
Other values (5) 203
 
5.1%
Hangul
ValueCountFrequency (%)
도 832
14.8%
완 433
 
7.7%
지 429
 
7.6%
군 383
 
6.8%
남 381
 
6.8%
번 364
 
6.5%
리 361
 
6.4%
라 360
 
6.4%
전 360
 
6.4%
면 269
 
4.8%
Other values (70) 1464
26.0%

사육두수
Real number (ℝ)

ZEROS 

Distinct83
Distinct (%)23.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42.475
Minimum0
Maximum750
Zeros29
Zeros (%)8.1%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2023-12-12T17:59:41.376631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q110
median21
Q344
95-th percentile140.25
Maximum750
Range750
Interquartile range (IQR)34

Descriptive statistics

Standard deviation76.394588
Coefficient of variation (CV)1.7985777
Kurtosis40.2733
Mean42.475
Median Absolute Deviation (MAD)14
Skewness5.6054237
Sum15291
Variance5836.1331
MonotonicityNot monotonic
2023-12-12T17:59:41.534648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 29
 
8.1%
20 19
 
5.3%
30 19
 
5.3%
15 13
 
3.6%
40 13
 
3.6%
5 12
 
3.3%
10 12
 
3.3%
2 10
 
2.8%
12 10
 
2.8%
7 10
 
2.8%
Other values (73) 213
59.2%
ValueCountFrequency (%)
0 29
8.1%
1 2
 
0.6%
2 10
 
2.8%
3 3
 
0.8%
4 2
 
0.6%
5 12
3.3%
6 5
 
1.4%
7 10
 
2.8%
8 6
 
1.7%
9 3
 
0.8%
ValueCountFrequency (%)
750 1
 
0.3%
650 1
 
0.3%
600 1
 
0.3%
360 1
 
0.3%
350 1
 
0.3%
304 1
 
0.3%
300 1
 
0.3%
280 1
 
0.3%
250 1
 
0.3%
200 4
1.1%

농장규모(㎡)
Text

Distinct271
Distinct (%)75.3%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
2023-12-12T17:59:41.876505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length4.0527778
Min length2

Characters and Unicode

Total characters1459
Distinct characters12
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

Unique228 ?
Unique (%)63.3%

Sample

1st row872
2nd row560
3rd row713.4
4th row736
5th row362
ValueCountFrequency (%)
330 18
 
5.0%
320 7
 
1.9%
384 7
 
1.9%
360 6
 
1.7%
240 5
 
1.4%
352 5
 
1.4%
336 5
 
1.4%
33 5
 
1.4%
450 3
 
0.8%
324 3
 
0.8%
Other values (261) 296
82.2%
2023-12-12T17:59:42.386594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 216
14.8%
0 157
10.8%
2 156
10.7%
1 136
9.3%
. 133
9.1%
8 124
8.5%
4 123
8.4%
6 121
8.3%
5 108
7.4%
7 76
 
5.2%
Other values (2) 109
7.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1291
88.5%
Other Punctuation 168
 
11.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 216
16.7%
0 157
12.2%
2 156
12.1%
1 136
10.5%
8 124
9.6%
4 123
9.5%
6 121
9.4%
5 108
8.4%
7 76
 
5.9%
9 74
 
5.7%
Other Punctuation
ValueCountFrequency (%)
. 133
79.2%
, 35
 
20.8%

Most occurring scripts

ValueCountFrequency (%)
Common 1459
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 216
14.8%
0 157
10.8%
2 156
10.7%
1 136
9.3%
. 133
9.1%
8 124
8.5%
4 123
8.4%
6 121
8.3%
5 108
7.4%
7 76
 
5.2%
Other values (2) 109
7.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1459
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 216
14.8%
0 157
10.8%
2 156
10.7%
1 136
9.3%
. 133
9.1%
8 124
8.5%
4 123
8.4%
6 121
8.3%
5 108
7.4%
7 76
 
5.2%
Other values (2) 109
7.5%

Interactions

2023-12-12T17:59:38.243725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:59:38.005024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:59:38.367172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:59:38.118801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:59:42.500767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번읍면주사육업종사육두수
연번1.0000.5140.4180.155
읍면0.5141.0000.6160.000
주사육업종0.4180.6161.0000.566
사육두수0.1550.0000.5661.000
2023-12-12T17:59:42.606207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면주사육업종
읍면1.0000.361
주사육업종0.3611.000
2023-12-12T17:59:43.016581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번사육두수읍면주사육업종
연번1.000-0.1470.2470.225
사육두수-0.1471.0000.0000.348
읍면0.2470.0001.0000.361
주사육업종0.2250.3480.3611.000

Missing values

2023-12-12T17:59:38.519119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:59:38.679373image/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

연번읍면사업장명칭주사육업종사업장소재지(지번)사육두수농장규모(㎡)
01완도읍솔개농장한우전라남도 완도군 완도읍 대야리 785-188872
12완도읍청해농장한우전라남도 완도군 완도읍 대야리 386번지 1호55560
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