Overview

Dataset statistics

Number of variables6
Number of observations176
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.4 KiB
Average record size in memory48.8 B

Variable types

Text6

Dataset

Description2020.11~12에 제주도 내 44개 지역에서 측정한 감귤(노지감귤)의 크기 데이터 / 1주마다 임의로 5그루를 선정하여 캘리퍼스로 측정함
Author제주국제자유도시개발센터
URLhttps://www.data.go.kr/data/15087734/fileData.do

Reproduction

Analysis started2023-12-12 04:35:43.468209
Analysis finished2023-12-12 04:35:44.204921
Duration0.74 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

농가 관리번호(나무구분)
Text

Distinct173
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-12T13:35:44.658741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.8693182
Min length4

Characters and Unicode

Total characters857
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique170 ?
Unique (%)96.6%

Sample

1st row1(1)
2nd row1(2)
3rd row1(3)
4th row1(4)
5th row1(5)
ValueCountFrequency (%)
46(1 2
 
1.1%
46(2 2
 
1.1%
46(3 2
 
1.1%
50(3 1
 
0.6%
35(2 1
 
0.6%
38(1 1
 
0.6%
37(5 1
 
0.6%
1(1 1
 
0.6%
36(1 1
 
0.6%
34(1 1
 
0.6%
Other values (163) 163
92.6%
2023-12-12T13:35:45.334641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 176
20.5%
) 175
20.4%
3 103
12.0%
1 102
11.9%
2 98
11.4%
4 83
9.7%
5 44
 
5.1%
0 21
 
2.5%
6 20
 
2.3%
8 13
 
1.5%
Other values (2) 22
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 506
59.0%
Open Punctuation 176
 
20.5%
Close Punctuation 175
 
20.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 103
20.4%
1 102
20.2%
2 98
19.4%
4 83
16.4%
5 44
8.7%
0 21
 
4.2%
6 20
 
4.0%
8 13
 
2.6%
7 11
 
2.2%
9 11
 
2.2%
Open Punctuation
ValueCountFrequency (%)
( 176
100.0%
Close Punctuation
ValueCountFrequency (%)
) 175
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 857
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
( 176
20.5%
) 175
20.4%
3 103
12.0%
1 102
11.9%
2 98
11.4%
4 83
9.7%
5 44
 
5.1%
0 21
 
2.5%
6 20
 
2.3%
8 13
 
1.5%
Other values (2) 22
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 857
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 176
20.5%
) 175
20.4%
3 103
12.0%
1 102
11.9%
2 98
11.4%
4 83
9.7%
5 44
 
5.1%
0 21
 
2.5%
6 20
 
2.3%
8 13
 
1.5%
Other values (2) 22
 
2.6%

1차 측정 크기(mm)
Text

Distinct162
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-12T13:35:45.847086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.7443182
Min length2

Characters and Unicode

Total characters835
Distinct characters14
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

Unique158 ?
Unique (%)89.8%

Sample

1st row63.52
2nd row71.21
3rd row74.68
4th row68.19
5th row74.81
ValueCountFrequency (%)
미측정 12
 
6.8%
48.06 2
 
1.1%
63.41 2
 
1.1%
53.5 2
 
1.1%
53.87 1
 
0.6%
54.04 1
 
0.6%
63.52 1
 
0.6%
49.41 1
 
0.6%
61.89 1
 
0.6%
71.58 1
 
0.6%
Other values (152) 152
86.4%
2023-12-12T13:35:46.591455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 163
19.5%
6 115
13.8%
5 102
12.2%
7 68
8.1%
4 66
7.9%
3 65
 
7.8%
2 54
 
6.5%
9 51
 
6.1%
8 48
 
5.7%
1 39
 
4.7%
Other values (4) 64
 
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 636
76.2%
Other Punctuation 163
 
19.5%
Other Letter 36
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 115
18.1%
5 102
16.0%
7 68
10.7%
4 66
10.4%
3 65
10.2%
2 54
8.5%
9 51
8.0%
8 48
7.5%
1 39
 
6.1%
0 28
 
4.4%
Other Letter
ValueCountFrequency (%)
미 12
33.3%
측 12
33.3%
정 12
33.3%
Other Punctuation
ValueCountFrequency (%)
. 163
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 799
95.7%
Hangul 36
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
. 163
20.4%
6 115
14.4%
5 102
12.8%
7 68
8.5%
4 66
8.3%
3 65
 
8.1%
2 54
 
6.8%
9 51
 
6.4%
8 48
 
6.0%
1 39
 
4.9%
Hangul
ValueCountFrequency (%)
미 12
33.3%
측 12
33.3%
정 12
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 799
95.7%
Hangul 36
 
4.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 163
20.4%
6 115
14.4%
5 102
12.8%
7 68
8.5%
4 66
8.3%
3 65
 
8.1%
2 54
 
6.8%
9 51
 
6.4%
8 48
 
6.0%
1 39
 
4.9%
Hangul
ValueCountFrequency (%)
미 12
33.3%
측 12
33.3%
정 12
33.3%

2차 측정 크기(mm)
Text

Distinct160
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-12T13:35:46.996052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.7159091
Min length2

Characters and Unicode

Total characters830
Distinct characters14
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

Unique156 ?
Unique (%)88.6%

Sample

1st row61.94
2nd row67.2
3rd row68.02
4th row69.02
5th row68.56
ValueCountFrequency (%)
미측정 14
 
8.0%
68.14 2
 
1.1%
60.4 2
 
1.1%
66.02 2
 
1.1%
60.48 1
 
0.6%
67.08 1
 
0.6%
62.04 1
 
0.6%
48.39 1
 
0.6%
66.65 1
 
0.6%
62.84 1
 
0.6%
Other values (150) 150
85.2%
2023-12-12T13:35:47.623198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 160
19.3%
6 115
13.9%
5 107
12.9%
4 65
7.8%
8 60
 
7.2%
7 56
 
6.7%
1 52
 
6.3%
3 50
 
6.0%
9 46
 
5.5%
0 40
 
4.8%
Other values (4) 79
9.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 628
75.7%
Other Punctuation 160
 
19.3%
Other Letter 42
 
5.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 115
18.3%
5 107
17.0%
4 65
10.4%
8 60
9.6%
7 56
8.9%
1 52
8.3%
3 50
8.0%
9 46
 
7.3%
0 40
 
6.4%
2 37
 
5.9%
Other Letter
ValueCountFrequency (%)
미 14
33.3%
측 14
33.3%
정 14
33.3%
Other Punctuation
ValueCountFrequency (%)
. 160
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 788
94.9%
Hangul 42
 
5.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 160
20.3%
6 115
14.6%
5 107
13.6%
4 65
8.2%
8 60
 
7.6%
7 56
 
7.1%
1 52
 
6.6%
3 50
 
6.3%
9 46
 
5.8%
0 40
 
5.1%
Hangul
ValueCountFrequency (%)
미 14
33.3%
측 14
33.3%
정 14
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 788
94.9%
Hangul 42
 
5.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 160
20.3%
6 115
14.6%
5 107
13.6%
4 65
8.2%
8 60
 
7.6%
7 56
 
7.1%
1 52
 
6.6%
3 50
 
6.3%
9 46
 
5.8%
0 40
 
5.1%
Hangul
ValueCountFrequency (%)
미 14
33.3%
측 14
33.3%
정 14
33.3%

3차 측정 크기(mm)
Text

Distinct158
Distinct (%)89.8%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-12T13:35:48.038614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.7727273
Min length2

Characters and Unicode

Total characters840
Distinct characters14
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

Unique151 ?
Unique (%)85.8%

Sample

1st row61.12
2nd row61.22
3rd row64.46
4th row65.64
5th row65.01
ValueCountFrequency (%)
미측정 13
 
7.4%
61.72 2
 
1.1%
61.12 2
 
1.1%
60.23 2
 
1.1%
65.01 2
 
1.1%
65.21 2
 
1.1%
55.93 2
 
1.1%
54.68 1
 
0.6%
57.28 1
 
0.6%
62.73 1
 
0.6%
Other values (148) 148
84.1%
2023-12-12T13:35:48.666002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 162
19.3%
6 127
15.1%
5 117
13.9%
7 67
8.0%
3 61
 
7.3%
4 61
 
7.3%
2 52
 
6.2%
1 50
 
6.0%
9 36
 
4.3%
8 36
 
4.3%
Other values (4) 71
8.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 639
76.1%
Other Punctuation 162
 
19.3%
Other Letter 39
 
4.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 127
19.9%
5 117
18.3%
7 67
10.5%
3 61
9.5%
4 61
9.5%
2 52
8.1%
1 50
 
7.8%
9 36
 
5.6%
8 36
 
5.6%
0 32
 
5.0%
Other Letter
ValueCountFrequency (%)
미 13
33.3%
측 13
33.3%
정 13
33.3%
Other Punctuation
ValueCountFrequency (%)
. 162
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 801
95.4%
Hangul 39
 
4.6%

Most frequent character per script

Common
ValueCountFrequency (%)
. 162
20.2%
6 127
15.9%
5 117
14.6%
7 67
8.4%
3 61
 
7.6%
4 61
 
7.6%
2 52
 
6.5%
1 50
 
6.2%
9 36
 
4.5%
8 36
 
4.5%
Hangul
ValueCountFrequency (%)
미 13
33.3%
측 13
33.3%
정 13
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 801
95.4%
Hangul 39
 
4.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 162
20.2%
6 127
15.9%
5 117
14.6%
7 67
8.4%
3 61
 
7.6%
4 61
 
7.6%
2 52
 
6.5%
1 50
 
6.2%
9 36
 
4.5%
8 36
 
4.5%
Hangul
ValueCountFrequency (%)
미 13
33.3%
측 13
33.3%
정 13
33.3%

4차 측정 크기(mm)
Text

Distinct159
Distinct (%)90.3%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-12T13:35:49.063841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.75
Min length2

Characters and Unicode

Total characters836
Distinct characters14
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

Unique151 ?
Unique (%)85.8%

Sample

1st row57.21
2nd row58.1
3rd row58.72
4th row59.69
5th row59
ValueCountFrequency (%)
미측정 11
 
6.2%
60.87 2
 
1.1%
56.78 2
 
1.1%
58.58 2
 
1.1%
56.71 2
 
1.1%
57.71 2
 
1.1%
58.1 2
 
1.1%
61.85 2
 
1.1%
55.92 1
 
0.6%
64.54 1
 
0.6%
Other values (149) 149
84.7%
2023-12-12T13:35:49.648068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 162
19.4%
5 140
16.7%
6 82
9.8%
7 70
8.4%
8 65
7.8%
4 63
 
7.5%
9 60
 
7.2%
1 51
 
6.1%
2 46
 
5.5%
3 34
 
4.1%
Other values (4) 63
 
7.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 641
76.7%
Other Punctuation 162
 
19.4%
Other Letter 33
 
3.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 140
21.8%
6 82
12.8%
7 70
10.9%
8 65
10.1%
4 63
9.8%
9 60
9.4%
1 51
 
8.0%
2 46
 
7.2%
3 34
 
5.3%
0 30
 
4.7%
Other Letter
ValueCountFrequency (%)
미 11
33.3%
측 11
33.3%
정 11
33.3%
Other Punctuation
ValueCountFrequency (%)
. 162
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 803
96.1%
Hangul 33
 
3.9%

Most frequent character per script

Common
ValueCountFrequency (%)
. 162
20.2%
5 140
17.4%
6 82
10.2%
7 70
8.7%
8 65
8.1%
4 63
 
7.8%
9 60
 
7.5%
1 51
 
6.4%
2 46
 
5.7%
3 34
 
4.2%
Hangul
ValueCountFrequency (%)
미 11
33.3%
측 11
33.3%
정 11
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 803
96.1%
Hangul 33
 
3.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 162
20.2%
5 140
17.4%
6 82
10.2%
7 70
8.7%
8 65
8.1%
4 63
 
7.8%
9 60
 
7.5%
1 51
 
6.4%
2 46
 
5.7%
3 34
 
4.2%
Hangul
ValueCountFrequency (%)
미 11
33.3%
측 11
33.3%
정 11
33.3%

5차 측정 크기(mm)
Text

Distinct162
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-12T13:35:50.091377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.7727273
Min length3

Characters and Unicode

Total characters840
Distinct characters14
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

Unique158 ?
Unique (%)89.8%

Sample

1st row65.8
2nd row66.18
3rd row68.27
4th row69.67
5th row69.59
ValueCountFrequency (%)
미측정 12
 
6.8%
58.94 2
 
1.1%
73.64 2
 
1.1%
48.97 2
 
1.1%
56.88 1
 
0.6%
65.8 1
 
0.6%
64.96 1
 
0.6%
65.91 1
 
0.6%
71.8 1
 
0.6%
72.1 1
 
0.6%
Other values (152) 152
86.4%
2023-12-12T13:35:50.729037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 164
19.5%
5 117
13.9%
6 100
11.9%
4 78
9.3%
7 69
8.2%
8 69
8.2%
2 54
 
6.4%
9 50
 
6.0%
1 45
 
5.4%
3 36
 
4.3%
Other values (4) 58
 
6.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 640
76.2%
Other Punctuation 164
 
19.5%
Other Letter 36
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 117
18.3%
6 100
15.6%
4 78
12.2%
7 69
10.8%
8 69
10.8%
2 54
8.4%
9 50
7.8%
1 45
 
7.0%
3 36
 
5.6%
0 22
 
3.4%
Other Letter
ValueCountFrequency (%)
미 12
33.3%
측 12
33.3%
정 12
33.3%
Other Punctuation
ValueCountFrequency (%)
. 164
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 804
95.7%
Hangul 36
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
. 164
20.4%
5 117
14.6%
6 100
12.4%
4 78
9.7%
7 69
8.6%
8 69
8.6%
2 54
 
6.7%
9 50
 
6.2%
1 45
 
5.6%
3 36
 
4.5%
Hangul
ValueCountFrequency (%)
미 12
33.3%
측 12
33.3%
정 12
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 804
95.7%
Hangul 36
 
4.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 164
20.4%
5 117
14.6%
6 100
12.4%
4 78
9.7%
7 69
8.6%
8 69
8.6%
2 54
 
6.7%
9 50
 
6.2%
1 45
 
5.6%
3 36
 
4.5%
Hangul
ValueCountFrequency (%)
미 12
33.3%
측 12
33.3%
정 12
33.3%

Missing values

2023-12-12T13:35:44.018702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:35:44.141638image/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

농가 관리번호(나무구분)1차 측정 크기(mm)2차 측정 크기(mm)3차 측정 크기(mm)4차 측정 크기(mm)5차 측정 크기(mm)
01(1)63.5261.9461.1257.2165.8
11(2)71.2167.261.2258.166.18
21(3)74.6868.0264.4658.7268.27
31(4)68.1969.0265.6459.6969.67
41(5)74.8168.5665.015969.59
52(1)77.3266.2661.9966.1172.04
62(2)62.2773.0664.5464.9970.73
72(3)63.6973.1165.0464.1372.39
82(4)64.43미측정65.2164.4573.64
93(1)63.9158.0461.7275.9453.15
농가 관리번호(나무구분)1차 측정 크기(mm)2차 측정 크기(mm)3차 측정 크기(mm)4차 측정 크기(mm)5차 측정 크기(mm)
16649(1)47.851.1850.3154.447.53
16749(2)48.0651.4951.5555.5648.51
16849(3)48.1951.5956.9850.1648.64
16949(4)48.251.7844.3750.4248.17
17049(5)53.4251.8857.3350.5648.22
17150(1)61.5550.1963.3555.7257.59
17250(2)62.3150.5565.4357.3857.74
17350(3)62.8250.9365.5757.7158.59
17450(4)63.1350.9665.5857.7958.63
17550(5)63.4151.0365.6157.8258.76