Overview

Dataset statistics

Number of variables5
Number of observations1573
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory64.6 KiB
Average record size in memory42.1 B

Variable types

Numeric2
Text2
Categorical1

Dataset

Description충청북도 청주시 소 사육 농가 현황
Author충청북도 청주시
URLhttps://www.data.go.kr/data/15067876/fileData.do

Alerts

축종 is highly imbalanced (57.1%)Imbalance
연번 has unique valuesUnique
사육두수 has 28 (1.8%) zerosZeros

Reproduction

Analysis started2023-12-12 07:46:10.778807
Analysis finished2023-12-12 07:46:11.713156
Duration0.93 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct1573
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean787
Minimum1
Maximum1573
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.0 KiB
2023-12-12T16:46:11.774942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile79.6
Q1394
median787
Q31180
95-th percentile1494.4
Maximum1573
Range1572
Interquartile range (IQR)786

Descriptive statistics

Standard deviation454.2303
Coefficient of variation (CV)0.57716684
Kurtosis-1.2
Mean787
Median Absolute Deviation (MAD)393
Skewness0
Sum1237951
Variance206325.17
MonotonicityStrictly increasing
2023-12-12T16:46:11.906559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
1058 1
 
0.1%
1056 1
 
0.1%
1055 1
 
0.1%
1054 1
 
0.1%
1053 1
 
0.1%
1052 1
 
0.1%
1051 1
 
0.1%
1050 1
 
0.1%
1049 1
 
0.1%
Other values (1563) 1563
99.4%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
1573 1
0.1%
1572 1
0.1%
1571 1
0.1%
1570 1
0.1%
1569 1
0.1%
1568 1
0.1%
1567 1
0.1%
1566 1
0.1%
1565 1
0.1%
1564 1
0.1%

사업장명칭
Text

Distinct1320
Distinct (%)83.9%
Missing0
Missing (%)0.0%
Memory size12.4 KiB
2023-12-12T16:46:12.218095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length4
Mean length4.1290528
Min length1

Characters and Unicode

Total characters6495
Distinct characters343
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

Unique1145 ?
Unique (%)72.8%

Sample

1st row비하목장
2nd row고니농장
3rd row삼산목장
4th row성규목장
5th row청풍농장
ValueCountFrequency (%)
농장 9
 
0.6%
우리농장 8
 
0.5%
부자농장 7
 
0.4%
한우농장 7
 
0.4%
목장 6
 
0.4%
대성농장 6
 
0.4%
석성농장 6
 
0.4%
서당농장 6
 
0.4%
푸른목장 5
 
0.3%
토성목장 5
 
0.3%
Other values (1317) 1539
95.9%
2023-12-12T16:46:12.653574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 1362
21.0%
농 853
 
13.1%
목 513
 
7.9%
산 99
 
1.5%
성 91
 
1.4%
정 85
 
1.3%
원 82
 
1.3%
우 73
 
1.1%
영 69
 
1.1%
한 65
 
1.0%
Other values (333) 3203
49.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6372
98.1%
Decimal Number 35
 
0.5%
Space Separator 31
 
0.5%
Close Punctuation 20
 
0.3%
Open Punctuation 20
 
0.3%
Uppercase Letter 15
 
0.2%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 1362
21.4%
농 853
 
13.4%
목 513
 
8.1%
산 99
 
1.6%
성 91
 
1.4%
정 85
 
1.3%
원 82
 
1.3%
우 73
 
1.1%
영 69
 
1.1%
한 65
 
1.0%
Other values (312) 3080
48.3%
Uppercase Letter
ValueCountFrequency (%)
K 3
20.0%
S 2
13.3%
C 1
 
6.7%
A 1
 
6.7%
U 1
 
6.7%
R 1
 
6.7%
D 1
 
6.7%
E 1
 
6.7%
M 1
 
6.7%
F 1
 
6.7%
Other values (2) 2
13.3%
Decimal Number
ValueCountFrequency (%)
2 21
60.0%
1 8
 
22.9%
3 4
 
11.4%
5 1
 
2.9%
7 1
 
2.9%
Space Separator
ValueCountFrequency (%)
31
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6372
98.1%
Common 108
 
1.7%
Latin 15
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 1362
21.4%
농 853
 
13.4%
목 513
 
8.1%
산 99
 
1.6%
성 91
 
1.4%
정 85
 
1.3%
원 82
 
1.3%
우 73
 
1.1%
영 69
 
1.1%
한 65
 
1.0%
Other values (312) 3080
48.3%
Latin
ValueCountFrequency (%)
K 3
20.0%
S 2
13.3%
C 1
 
6.7%
A 1
 
6.7%
U 1
 
6.7%
R 1
 
6.7%
D 1
 
6.7%
E 1
 
6.7%
M 1
 
6.7%
F 1
 
6.7%
Other values (2) 2
13.3%
Common
ValueCountFrequency (%)
31
28.7%
2 21
19.4%
) 20
18.5%
( 20
18.5%
1 8
 
7.4%
3 4
 
3.7%
- 2
 
1.9%
5 1
 
0.9%
7 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6372
98.1%
ASCII 123
 
1.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 1362
21.4%
농 853
 
13.4%
목 513
 
8.1%
산 99
 
1.6%
성 91
 
1.4%
정 85
 
1.3%
원 82
 
1.3%
우 73
 
1.1%
영 69
 
1.1%
한 65
 
1.0%
Other values (312) 3080
48.3%
ASCII
ValueCountFrequency (%)
31
25.2%
2 21
17.1%
) 20
16.3%
( 20
16.3%
1 8
 
6.5%
3 4
 
3.3%
K 3
 
2.4%
- 2
 
1.6%
S 2
 
1.6%
C 1
 
0.8%
Other values (11) 11
 
8.9%

축종
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size12.4 KiB
한우
1366 
젖소
141 
육우
 
66

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
한우 1366
86.8%
젖소 141
 
9.0%
육우 66
 
4.2%

Length

2023-12-12T16:46:12.829975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:46:12.923697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한우 1366
86.8%
젖소 141
 
9.0%
육우 66
 
4.2%

사업장 소재지
Text

Distinct1535
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size12.4 KiB
2023-12-12T16:46:13.291749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length73
Median length67
Mean length30.596313
Min length18

Characters and Unicode

Total characters48128
Distinct characters182
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1505 ?
Unique (%)95.7%

Sample

1st row충청북도 청주시 흥덕구 주봉로34번길 55 (비하동)
2nd row충청북도 청주시 서원구 용평로93번길 7-15 (분평동)
3rd row충청북도 청주시 서원구 남이면 석실4길 15-10
4th row충청북도 청주시 서원구 남이면 사동구암로 286
5th row충청북도 청주시 서원구 대림로421번길 34-20 (죽림동)
ValueCountFrequency (%)
충청북도 1573
 
14.9%
청주시 1573
 
14.9%
청원구 683
 
6.5%
상당구 381
 
3.6%
흥덕구 350
 
3.3%
1호 322
 
3.1%
북이면 267
 
2.5%
오창읍 257
 
2.4%
2호 166
 
1.6%
옥산면 163
 
1.5%
Other values (1194) 4799
45.6%
2023-12-12T16:46:13.790991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11814
24.5%
청 3847
 
8.0%
북 1868
 
3.9%
지 1699
 
3.5%
도 1650
 
3.4%
번 1609
 
3.3%
구 1599
 
3.3%
주 1597
 
3.3%
시 1586
 
3.3%
충 1573
 
3.3%
Other values (172) 19286
40.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 29124
60.5%
Space Separator 11814
24.5%
Decimal Number 6514
 
13.5%
Other Punctuation 251
 
0.5%
Dash Punctuation 244
 
0.5%
Open Punctuation 91
 
0.2%
Close Punctuation 90
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 3847
 
13.2%
북 1868
 
6.4%
지 1699
 
5.8%
도 1650
 
5.7%
번 1609
 
5.5%
구 1599
 
5.5%
주 1597
 
5.5%
시 1586
 
5.4%
충 1573
 
5.4%
리 1432
 
4.9%
Other values (155) 10664
36.6%
Decimal Number
ValueCountFrequency (%)
1 1314
20.2%
2 1028
15.8%
3 847
13.0%
4 681
10.5%
5 526
8.1%
6 482
 
7.4%
8 444
 
6.8%
7 434
 
6.7%
9 380
 
5.8%
0 378
 
5.8%
Other Punctuation
ValueCountFrequency (%)
, 243
96.8%
. 7
 
2.8%
: 1
 
0.4%
Space Separator
ValueCountFrequency (%)
11814
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 244
100.0%
Open Punctuation
ValueCountFrequency (%)
( 91
100.0%
Close Punctuation
ValueCountFrequency (%)
) 90
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 29080
60.4%
Common 19004
39.5%
Han 44
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 3847
 
13.2%
북 1868
 
6.4%
지 1699
 
5.8%
도 1650
 
5.7%
번 1609
 
5.5%
구 1599
 
5.5%
주 1597
 
5.5%
시 1586
 
5.5%
충 1573
 
5.4%
리 1432
 
4.9%
Other values (149) 10620
36.5%
Common
ValueCountFrequency (%)
11814
62.2%
1 1314
 
6.9%
2 1028
 
5.4%
3 847
 
4.5%
4 681
 
3.6%
5 526
 
2.8%
6 482
 
2.5%
8 444
 
2.3%
7 434
 
2.3%
9 380
 
2.0%
Other values (7) 1054
 
5.5%
Han
ValueCountFrequency (%)
岩 14
31.8%
山 8
18.2%
基 8
18.2%
華 7
15.9%
岐 6
13.6%
花 1
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 29080
60.4%
ASCII 19004
39.5%
CJK 44
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11814
62.2%
1 1314
 
6.9%
2 1028
 
5.4%
3 847
 
4.5%
4 681
 
3.6%
5 526
 
2.8%
6 482
 
2.5%
8 444
 
2.3%
7 434
 
2.3%
9 380
 
2.0%
Other values (7) 1054
 
5.5%
Hangul
ValueCountFrequency (%)
청 3847
 
13.2%
북 1868
 
6.4%
지 1699
 
5.8%
도 1650
 
5.7%
번 1609
 
5.5%
구 1599
 
5.5%
주 1597
 
5.5%
시 1586
 
5.5%
충 1573
 
5.4%
리 1432
 
4.9%
Other values (149) 10620
36.5%
CJK
ValueCountFrequency (%)
岩 14
31.8%
山 8
18.2%
基 8
18.2%
華 7
15.9%
岐 6
13.6%
花 1
 
2.3%

사육두수
Real number (ℝ)

ZEROS 

Distinct178
Distinct (%)11.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49.99555
Minimum0
Maximum1021
Zeros28
Zeros (%)1.8%
Negative0
Negative (%)0.0%
Memory size14.0 KiB
2023-12-12T16:46:13.943808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q112
median27
Q356
95-th percentile174
Maximum1021
Range1021
Interquartile range (IQR)44

Descriptive statistics

Standard deviation80.168132
Coefficient of variation (CV)1.6035054
Kurtosis41.493771
Mean49.99555
Median Absolute Deviation (MAD)18
Skewness5.3504482
Sum78643
Variance6426.9294
MonotonicityNot monotonic
2023-12-12T16:46:14.069452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30 80
 
5.1%
10 64
 
4.1%
20 62
 
3.9%
40 61
 
3.9%
50 50
 
3.2%
15 45
 
2.9%
5 42
 
2.7%
7 40
 
2.5%
6 40
 
2.5%
60 39
 
2.5%
Other values (168) 1050
66.8%
ValueCountFrequency (%)
0 28
1.8%
1 5
 
0.3%
2 18
1.1%
3 30
1.9%
4 26
1.7%
5 42
2.7%
6 40
2.5%
7 40
2.5%
8 29
1.8%
9 37
2.4%
ValueCountFrequency (%)
1021 1
 
0.1%
912 1
 
0.1%
805 1
 
0.1%
748 1
 
0.1%
710 1
 
0.1%
600 3
0.2%
550 1
 
0.1%
520 1
 
0.1%
455 1
 
0.1%
450 1
 
0.1%

Interactions

2023-12-12T16:46:11.320410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:46:11.132381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:46:11.441330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:46:11.225973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:46:14.148455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번축종사육두수
연번1.0000.3500.248
축종0.3501.0000.415
사육두수0.2480.4151.000
2023-12-12T16:46:14.224972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번사육두수축종
연번1.000-0.0990.224
사육두수-0.0991.0000.274
축종0.2240.2741.000

Missing values

2023-12-12T16:46:11.576254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:46:11.679134image/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

연번사업장명칭축종사업장 소재지사육두수
01비하목장한우충청북도 청주시 흥덕구 주봉로34번길 55 (비하동)24
12고니농장한우충청북도 청주시 서원구 용평로93번길 7-15 (분평동)14
23삼산목장젖소충청북도 청주시 서원구 남이면 석실4길 15-1094
34성규목장한우충청북도 청주시 서원구 남이면 사동구암로 28673
45청풍농장한우충청북도 청주시 서원구 대림로421번길 34-20 (죽림동)20
56태훈농장한우충청북도 청주시 서원구 남이면 부용외천3길 116-474
67영종농장한우충청북도 청주시 흥덕구 옥산면 금계사정로 272-7830
78관석농장한우충청북도 청주시 흥덕구 오송읍 공북3길 67-8630
89햇살농장한우충청북도 청주시 흥덕구 옥산면 소로1길 62-4297
910부용농장한우충청북도 청주시 흥덕구 오송읍 공북3길 67-5440
연번사업장명칭축종사업장 소재지사육두수
15631564상호농장한우충청북도 청주시 청원구 북이면 추학리 443번지2
15641565학소리농장한우충청북도 청주시 청원구 오창읍 학소리 764번지30
15651566서당농장한우충청북도 청주시 청원구 북이면 서당리 566번지27
15661567석성농장한우충청북도 청주시 청원구 북이면 석성리 746번지39
15671568기열농장한우충청북도 청주시 청원구 북이면 금암리 319번지 4호20
15681569서당농장한우충청북도 청주시 청원구 내수읍 학평리 317번지94
15691570부경농장한우충청북도 청주시 청원구 내수읍 학평리 317번지 1호100
15701571태호농장(제2농장)한우충청북도 청주시 청원구 북이면 석성리 708번지62
15711572성수2농장한우충청북도 청주시 청원구 북이면 화하리 601번지100
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