Overview

Dataset statistics

Number of variables17
Number of observations514
Missing cells1855
Missing cells (%)21.2%
Duplicate rows4
Duplicate rows (%)0.8%
Total size in memory68.4 KiB
Average record size in memory136.3 B

Variable types

Text15
Categorical2

Dataset

Description학교급식 친환경 농산물 주요 품목(71개) 규모
Author농림축산식품부
URLhttps://data.mafra.go.kr/opendata/data/indexOpenDataDetail.do?data_id=20210930000000001625

Alerts

Dataset has 4 (0.8%) duplicate rowsDuplicates
Unnamed: 2 is highly overall correlated with Unnamed: 3High correlation
Unnamed: 3 is highly overall correlated with Unnamed: 2High correlation
학교급식 품목별 친환경농산물 주요 품목별 규모 has 440 (85.6%) missing valuesMissing
Unnamed: 1 has 442 (86.0%) missing valuesMissing
Unnamed: 4 has 74 (14.4%) missing valuesMissing
Unnamed: 5 has 75 (14.6%) missing valuesMissing
Unnamed: 6 has 75 (14.6%) missing valuesMissing
Unnamed: 7 has 75 (14.6%) missing valuesMissing
Unnamed: 8 has 75 (14.6%) missing valuesMissing
Unnamed: 9 has 75 (14.6%) missing valuesMissing
Unnamed: 10 has 75 (14.6%) missing valuesMissing
Unnamed: 11 has 75 (14.6%) missing valuesMissing
Unnamed: 12 has 75 (14.6%) missing valuesMissing
Unnamed: 13 has 75 (14.6%) missing valuesMissing
Unnamed: 14 has 74 (14.4%) missing valuesMissing
Unnamed: 15 has 75 (14.6%) missing valuesMissing
Unnamed: 16 has 75 (14.6%) missing valuesMissing

Reproduction

Analysis started2023-12-11 03:33:24.489441
Analysis finished2023-12-11 03:33:26.082574
Duration1.59 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

학교급식 품목별 친환경농산물 주요 품목별 규모
Text

MISSING 

Distinct74
Distinct (%)100.0%
Missing440
Missing (%)85.6%
Memory size4.1 KiB
2023-12-11T12:33:26.283818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.8783784
Min length1

Characters and Unicode

Total characters139
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)100.0%

Sample

1st row구분
2nd row전체
3rd row1
4th row2
5th row3
ValueCountFrequency (%)
17 1
 
1.4%
36 1
 
1.4%
52 1
 
1.4%
51 1
 
1.4%
50 1
 
1.4%
49 1
 
1.4%
48 1
 
1.4%
47 1
 
1.4%
46 1
 
1.4%
45 1
 
1.4%
Other values (64) 64
86.5%
2023-12-11T12:33:26.775519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 18
12.9%
2 18
12.9%
3 17
12.2%
4 17
12.2%
5 17
12.2%
6 17
12.2%
7 10
7.2%
8 7
 
5.0%
9 7
 
5.0%
0 7
 
5.0%
Other values (4) 4
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 135
97.1%
Other Letter 4
 
2.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 18
13.3%
2 18
13.3%
3 17
12.6%
4 17
12.6%
5 17
12.6%
6 17
12.6%
7 10
7.4%
8 7
 
5.2%
9 7
 
5.2%
0 7
 
5.2%
Other Letter
ValueCountFrequency (%)
전 1
25.0%
체 1
25.0%
구 1
25.0%
분 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 135
97.1%
Hangul 4
 
2.9%

Most frequent character per script

Common
ValueCountFrequency (%)
1 18
13.3%
2 18
13.3%
3 17
12.6%
4 17
12.6%
5 17
12.6%
6 17
12.6%
7 10
7.4%
8 7
 
5.2%
9 7
 
5.2%
0 7
 
5.2%
Hangul
ValueCountFrequency (%)
전 1
25.0%
체 1
25.0%
구 1
25.0%
분 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 135
97.1%
Hangul 4
 
2.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 18
13.3%
2 18
13.3%
3 17
12.6%
4 17
12.6%
5 17
12.6%
6 17
12.6%
7 10
7.4%
8 7
 
5.2%
9 7
 
5.2%
0 7
 
5.2%
Hangul
ValueCountFrequency (%)
전 1
25.0%
체 1
25.0%
구 1
25.0%
분 1
25.0%

Unnamed: 1
Text

MISSING 

Distinct72
Distinct (%)100.0%
Missing442
Missing (%)86.0%
Memory size4.1 KiB
2023-12-11T12:33:27.125581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.25
Min length1

Characters and Unicode

Total characters162
Distinct characters90
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique72 ?
Unique (%)100.0%

Sample

1st row쌀
2nd row양파
3rd row감자
4th row마늘
5th row사과
ValueCountFrequency (%)
쌀 1
 
1.4%
양파 1
 
1.4%
자두 1
 
1.4%
녹두 1
 
1.4%
콩 1
 
1.4%
팥 1
 
1.4%
더덕 1
 
1.4%
땅콩 1
 
1.4%
보리 1
 
1.4%
블루베리 1
 
1.4%
Other values (62) 62
86.1%
2023-12-11T12:33:27.607564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
추 6
 
3.7%
버 6
 
3.7%
섯 6
 
3.7%
리 5
 
3.1%
마 5
 
3.1%
수 5
 
3.1%
고 4
 
2.5%
두 4
 
2.5%
토 4
 
2.5%
양 4
 
2.5%
Other values (80) 113
69.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 162
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
추 6
 
3.7%
버 6
 
3.7%
섯 6
 
3.7%
리 5
 
3.1%
마 5
 
3.1%
수 5
 
3.1%
고 4
 
2.5%
두 4
 
2.5%
토 4
 
2.5%
양 4
 
2.5%
Other values (80) 113
69.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 162
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
추 6
 
3.7%
버 6
 
3.7%
섯 6
 
3.7%
리 5
 
3.1%
마 5
 
3.1%
수 5
 
3.1%
고 4
 
2.5%
두 4
 
2.5%
토 4
 
2.5%
양 4
 
2.5%
Other values (80) 113
69.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 162
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
추 6
 
3.7%
버 6
 
3.7%
섯 6
 
3.7%
리 5
 
3.1%
마 5
 
3.1%
수 5
 
3.1%
고 4
 
2.5%
두 4
 
2.5%
토 4
 
2.5%
양 4
 
2.5%
Other values (80) 113
69.8%

Unnamed: 2
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
친환경
146 
전체
73 
(A)
73 
(B)
73 
비율
73 
Other values (2)
76 

Length

Max length5
Median length3
Mean length3.0058366
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row전체
5th row(A)

Common Values

ValueCountFrequency (%)
친환경 146
28.4%
전체 73
14.2%
(A) 73
14.2%
(B) 73
14.2%
비율 73
14.2%
(B/A) 73
14.2%
<NA> 3
 
0.6%

Length

2023-12-11T12:33:27.756748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:33:27.878958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
친환경 146
28.4%
전체 73
14.2%
a 73
14.2%
b 73
14.2%
비율 73
14.2%
b/a 73
14.2%
na 3
 
0.6%

Unnamed: 3
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
물량
219 
매출액
219 
<NA>
76 

Length

Max length4
Median length3
Mean length2.7217899
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
물량 219
42.6%
매출액 219
42.6%
<NA> 76
 
14.8%

Length

2023-12-11T12:33:28.039301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:33:28.184962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
물량 219
42.6%
매출액 219
42.6%
na 76
 
14.8%

Unnamed: 4
Text

MISSING 

Distinct213
Distinct (%)48.4%
Missing74
Missing (%)14.4%
Memory size4.1 KiB
2023-12-11T12:33:28.555960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.3113636
Min length1

Characters and Unicode

Total characters1017
Distinct characters15
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

Unique153 ?
Unique (%)34.8%

Sample

1st row2020년
2nd row3월
3rd row1,831
4th row8,020
5th row869
ValueCountFrequency (%)
0 43
 
9.8%
1 30
 
6.8%
20
 
4.5%
3 11
 
2.5%
2 11
 
2.5%
5 10
 
2.3%
8 10
 
2.3%
4 7
 
1.6%
28 6
 
1.4%
6 6
 
1.4%
Other values (203) 286
65.0%
2023-12-11T12:33:29.085586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 148
14.6%
. 119
11.7%
2 111
10.9%
3 104
10.2%
4 102
10.0%
0 90
8.8%
5 88
8.7%
8 70
6.9%
6 63
6.2%
9 58
 
5.7%
Other values (5) 64
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 872
85.7%
Other Punctuation 123
 
12.1%
Dash Punctuation 20
 
2.0%
Other Letter 2
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 148
17.0%
2 111
12.7%
3 104
11.9%
4 102
11.7%
0 90
10.3%
5 88
10.1%
8 70
8.0%
6 63
7.2%
9 58
 
6.7%
7 38
 
4.4%
Other Punctuation
ValueCountFrequency (%)
. 119
96.7%
, 4
 
3.3%
Other Letter
ValueCountFrequency (%)
월 1
50.0%
년 1
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1015
99.8%
Hangul 2
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 148
14.6%
. 119
11.7%
2 111
10.9%
3 104
10.2%
4 102
10.0%
0 90
8.9%
5 88
8.7%
8 70
6.9%
6 63
6.2%
9 58
 
5.7%
Other values (3) 62
6.1%
Hangul
ValueCountFrequency (%)
월 1
50.0%
년 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1015
99.8%
Hangul 2
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 148
14.6%
. 119
11.7%
2 111
10.9%
3 104
10.2%
4 102
10.0%
0 90
8.9%
5 88
8.7%
8 70
6.9%
6 63
6.2%
9 58
 
5.7%
Other values (3) 62
6.1%
Hangul
ValueCountFrequency (%)
월 1
50.0%
년 1
50.0%

Unnamed: 5
Text

MISSING 

Distinct182
Distinct (%)41.5%
Missing75
Missing (%)14.6%
Memory size4.1 KiB
2023-12-11T12:33:29.420322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.1275626
Min length1

Characters and Unicode

Total characters934
Distinct characters14
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

Unique134 ?
Unique (%)30.5%

Sample

1st row4월
2nd row761
3rd row3,206
4th row348
5th row1,491
ValueCountFrequency (%)
0 58
 
13.2%
34
 
7.7%
1 25
 
5.7%
2 23
 
5.2%
3 21
 
4.8%
7 13
 
3.0%
5 9
 
2.1%
11 9
 
2.1%
6 7
 
1.6%
23 6
 
1.4%
Other values (172) 234
53.3%
2023-12-11T12:33:29.878644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 127
13.6%
. 122
13.1%
2 99
10.6%
3 96
10.3%
0 90
9.6%
4 78
8.4%
5 71
7.6%
7 63
6.7%
6 55
5.9%
8 50
 
5.4%
Other values (4) 83
8.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 775
83.0%
Other Punctuation 124
 
13.3%
Dash Punctuation 34
 
3.6%
Other Letter 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 127
16.4%
2 99
12.8%
3 96
12.4%
0 90
11.6%
4 78
10.1%
5 71
9.2%
7 63
8.1%
6 55
7.1%
8 50
 
6.5%
9 46
 
5.9%
Other Punctuation
ValueCountFrequency (%)
. 122
98.4%
, 2
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 34
100.0%
Other Letter
ValueCountFrequency (%)
월 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 933
99.9%
Hangul 1
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 127
13.6%
. 122
13.1%
2 99
10.6%
3 96
10.3%
0 90
9.6%
4 78
8.4%
5 71
7.6%
7 63
6.8%
6 55
5.9%
8 50
 
5.4%
Other values (3) 82
8.8%
Hangul
ValueCountFrequency (%)
월 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 933
99.9%
Hangul 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 127
13.6%
. 122
13.1%
2 99
10.6%
3 96
10.3%
0 90
9.6%
4 78
8.4%
5 71
7.6%
7 63
6.8%
6 55
5.9%
8 50
 
5.4%
Other values (3) 82
8.8%
Hangul
ValueCountFrequency (%)
월 1
100.0%

Unnamed: 6
Text

MISSING 

Distinct182
Distinct (%)41.5%
Missing75
Missing (%)14.6%
Memory size4.1 KiB
2023-12-11T12:33:30.191374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.0911162
Min length1

Characters and Unicode

Total characters918
Distinct characters14
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

Unique133 ?
Unique (%)30.3%

Sample

1st row5월
2nd row893
3rd row3,363
4th row367
5th row1,371
ValueCountFrequency (%)
0 69
 
15.7%
32
 
7.3%
2 24
 
5.5%
1 23
 
5.2%
3 13
 
3.0%
6 12
 
2.7%
4 10
 
2.3%
5 8
 
1.8%
10 7
 
1.6%
8 6
 
1.4%
Other values (172) 235
53.5%
2023-12-11T12:33:30.675672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 119
13.0%
2 117
12.7%
1 105
11.4%
3 102
11.1%
0 95
10.3%
4 66
7.2%
5 62
6.8%
6 61
6.6%
7 58
6.3%
8 53
5.8%
Other values (4) 80
8.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 764
83.2%
Other Punctuation 121
 
13.2%
Dash Punctuation 32
 
3.5%
Other Letter 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 117
15.3%
1 105
13.7%
3 102
13.4%
0 95
12.4%
4 66
8.6%
5 62
8.1%
6 61
8.0%
7 58
7.6%
8 53
6.9%
9 45
 
5.9%
Other Punctuation
ValueCountFrequency (%)
. 119
98.3%
, 2
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%
Other Letter
ValueCountFrequency (%)
월 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 917
99.9%
Hangul 1
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 119
13.0%
2 117
12.8%
1 105
11.5%
3 102
11.1%
0 95
10.4%
4 66
7.2%
5 62
6.8%
6 61
6.7%
7 58
6.3%
8 53
5.8%
Other values (3) 79
8.6%
Hangul
ValueCountFrequency (%)
월 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 917
99.9%
Hangul 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 119
13.0%
2 117
12.8%
1 105
11.5%
3 102
11.1%
0 95
10.4%
4 66
7.2%
5 62
6.8%
6 61
6.7%
7 58
6.3%
8 53
5.8%
Other values (3) 79
8.6%
Hangul
ValueCountFrequency (%)
월 1
100.0%

Unnamed: 7
Text

MISSING 

Distinct217
Distinct (%)49.4%
Missing75
Missing (%)14.6%
Memory size4.1 KiB
2023-12-11T12:33:31.139297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3758542
Min length1

Characters and Unicode

Total characters1043
Distinct characters14
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

Unique148 ?
Unique (%)33.7%

Sample

1st row6월
2nd row2,811
3rd row10,890
4th row1,193
5th row4,600
ValueCountFrequency (%)
0 33
 
7.5%
1 32
 
7.3%
2 14
 
3.2%
14
 
3.2%
4 8
 
1.8%
3 8
 
1.8%
6 8
 
1.8%
7 8
 
1.8%
23 7
 
1.6%
8 7
 
1.6%
Other values (207) 300
68.3%
2023-12-11T12:33:31.658719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 161
15.4%
2 134
12.8%
. 127
12.2%
3 120
11.5%
4 82
7.9%
5 79
7.6%
8 76
7.3%
0 69
6.6%
6 69
6.6%
9 56
 
5.4%
Other values (4) 70
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 895
85.8%
Other Punctuation 133
 
12.8%
Dash Punctuation 14
 
1.3%
Other Letter 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 161
18.0%
2 134
15.0%
3 120
13.4%
4 82
9.2%
5 79
8.8%
8 76
8.5%
0 69
7.7%
6 69
7.7%
9 56
 
6.3%
7 49
 
5.5%
Other Punctuation
ValueCountFrequency (%)
. 127
95.5%
, 6
 
4.5%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%
Other Letter
ValueCountFrequency (%)
월 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1042
99.9%
Hangul 1
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 161
15.5%
2 134
12.9%
. 127
12.2%
3 120
11.5%
4 82
7.9%
5 79
7.6%
8 76
7.3%
0 69
6.6%
6 69
6.6%
9 56
 
5.4%
Other values (3) 69
6.6%
Hangul
ValueCountFrequency (%)
월 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1042
99.9%
Hangul 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 161
15.5%
2 134
12.9%
. 127
12.2%
3 120
11.5%
4 82
7.9%
5 79
7.6%
8 76
7.3%
0 69
6.6%
6 69
6.6%
9 56
 
5.4%
Other values (3) 69
6.6%
Hangul
ValueCountFrequency (%)
월 1
100.0%

Unnamed: 8
Text

MISSING 

Distinct224
Distinct (%)51.0%
Missing75
Missing (%)14.6%
Memory size4.1 KiB
2023-12-11T12:33:32.049606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.405467
Min length1

Characters and Unicode

Total characters1056
Distinct characters14
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

Unique161 ?
Unique (%)36.7%

Sample

1st row7월
2nd row2,548
3rd row9,800
4th row1,072
5th row4,143
ValueCountFrequency (%)
0 41
 
9.3%
1 28
 
6.4%
3 12
 
2.7%
6 10
 
2.3%
2 10
 
2.3%
4 9
 
2.1%
5 6
 
1.4%
12 6
 
1.4%
27 6
 
1.4%
13 6
 
1.4%
Other values (214) 305
69.5%
2023-12-11T12:33:32.632897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 158
15.0%
. 131
12.4%
2 128
12.1%
4 107
10.1%
3 105
9.9%
5 82
7.8%
0 80
7.6%
6 74
7.0%
9 64
6.1%
7 60
 
5.7%
Other values (4) 67
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 914
86.6%
Other Punctuation 137
 
13.0%
Dash Punctuation 4
 
0.4%
Other Letter 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 158
17.3%
2 128
14.0%
4 107
11.7%
3 105
11.5%
5 82
9.0%
0 80
8.8%
6 74
8.1%
9 64
7.0%
7 60
 
6.6%
8 56
 
6.1%
Other Punctuation
ValueCountFrequency (%)
. 131
95.6%
, 6
 
4.4%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Other Letter
ValueCountFrequency (%)
월 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1055
99.9%
Hangul 1
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 158
15.0%
. 131
12.4%
2 128
12.1%
4 107
10.1%
3 105
10.0%
5 82
7.8%
0 80
7.6%
6 74
7.0%
9 64
6.1%
7 60
 
5.7%
Other values (3) 66
6.3%
Hangul
ValueCountFrequency (%)
월 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1055
99.9%
Hangul 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 158
15.0%
. 131
12.4%
2 128
12.1%
4 107
10.1%
3 105
10.0%
5 82
7.8%
0 80
7.6%
6 74
7.0%
9 64
6.1%
7 60
 
5.7%
Other values (3) 66
6.3%
Hangul
ValueCountFrequency (%)
월 1
100.0%

Unnamed: 9
Text

MISSING 

Distinct201
Distinct (%)45.8%
Missing75
Missing (%)14.6%
Memory size4.1 KiB
2023-12-11T12:33:33.046137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.2277904
Min length1

Characters and Unicode

Total characters978
Distinct characters14
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

Unique154 ?
Unique (%)35.1%

Sample

1st row8월
2nd row1,536
3rd row5,834
4th row618
5th row2,312
ValueCountFrequency (%)
0 57
 
13.0%
1 26
 
5.9%
2 20
 
4.6%
7 11
 
2.5%
4 10
 
2.3%
10
 
2.3%
3 9
 
2.1%
10 8
 
1.8%
5 8
 
1.8%
9 8
 
1.8%
Other values (191) 272
62.0%
2023-12-11T12:33:33.669060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 137
14.0%
2 130
13.3%
. 123
12.6%
3 121
12.4%
4 90
9.2%
0 89
9.1%
5 68
7.0%
8 57
5.8%
6 53
 
5.4%
7 51
 
5.2%
Other values (4) 59
6.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 840
85.9%
Other Punctuation 127
 
13.0%
Dash Punctuation 10
 
1.0%
Other Letter 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 137
16.3%
2 130
15.5%
3 121
14.4%
4 90
10.7%
0 89
10.6%
5 68
8.1%
8 57
6.8%
6 53
 
6.3%
7 51
 
6.1%
9 44
 
5.2%
Other Punctuation
ValueCountFrequency (%)
. 123
96.9%
, 4
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Other Letter
ValueCountFrequency (%)
월 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 977
99.9%
Hangul 1
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 137
14.0%
2 130
13.3%
. 123
12.6%
3 121
12.4%
4 90
9.2%
0 89
9.1%
5 68
7.0%
8 57
5.8%
6 53
 
5.4%
7 51
 
5.2%
Other values (3) 58
5.9%
Hangul
ValueCountFrequency (%)
월 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 977
99.9%
Hangul 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 137
14.0%
2 130
13.3%
. 123
12.6%
3 121
12.4%
4 90
9.2%
0 89
9.1%
5 68
7.0%
8 57
5.8%
6 53
 
5.4%
7 51
 
5.2%
Other values (3) 58
5.9%
Hangul
ValueCountFrequency (%)
월 1
100.0%

Unnamed: 10
Text

MISSING 

Distinct225
Distinct (%)51.3%
Missing75
Missing (%)14.6%
Memory size4.1 KiB
2023-12-11T12:33:34.084670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3530752
Min length1

Characters and Unicode

Total characters1033
Distinct characters14
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

Unique163 ?
Unique (%)37.1%

Sample

1st row9월
2nd row2,782
3rd row11,727
4th row1,171
5th row4,776
ValueCountFrequency (%)
0 42
 
9.6%
1 32
 
7.3%
2 14
 
3.2%
4 10
 
2.3%
5 9
 
2.1%
8
 
1.8%
13 8
 
1.8%
3 8
 
1.8%
7 7
 
1.6%
9 7
 
1.6%
Other values (215) 294
67.0%
2023-12-11T12:33:34.719802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 169
16.4%
. 123
11.9%
2 116
11.2%
3 110
10.6%
4 87
8.4%
0 79
7.6%
7 77
7.5%
5 75
7.3%
6 67
 
6.5%
9 60
 
5.8%
Other values (4) 70
6.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 895
86.6%
Other Punctuation 129
 
12.5%
Dash Punctuation 8
 
0.8%
Other Letter 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 169
18.9%
2 116
13.0%
3 110
12.3%
4 87
9.7%
0 79
8.8%
7 77
8.6%
5 75
8.4%
6 67
 
7.5%
9 60
 
6.7%
8 55
 
6.1%
Other Punctuation
ValueCountFrequency (%)
. 123
95.3%
, 6
 
4.7%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Other Letter
ValueCountFrequency (%)
월 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1032
99.9%
Hangul 1
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 169
16.4%
. 123
11.9%
2 116
11.2%
3 110
10.7%
4 87
8.4%
0 79
7.7%
7 77
7.5%
5 75
7.3%
6 67
 
6.5%
9 60
 
5.8%
Other values (3) 69
6.7%
Hangul
ValueCountFrequency (%)
월 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1032
99.9%
Hangul 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 169
16.4%
. 123
11.9%
2 116
11.2%
3 110
10.7%
4 87
8.4%
0 79
7.7%
7 77
7.5%
5 75
7.3%
6 67
 
6.5%
9 60
 
5.8%
Other values (3) 69
6.7%
Hangul
ValueCountFrequency (%)
월 1
100.0%

Unnamed: 11
Text

MISSING 

Distinct251
Distinct (%)57.2%
Missing75
Missing (%)14.6%
Memory size4.1 KiB
2023-12-11T12:33:35.098423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.4783599
Min length1

Characters and Unicode

Total characters1088
Distinct characters14
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

Unique190 ?
Unique (%)43.3%

Sample

1st row10월
2nd row4,097
3rd row19,023
4th row1,748
5th row7,942
ValueCountFrequency (%)
0 38
 
8.7%
1 23
 
5.2%
2 17
 
3.9%
12
 
2.7%
3 8
 
1.8%
6 7
 
1.6%
5 5
 
1.1%
15 5
 
1.1%
4 5
 
1.1%
9 5
 
1.1%
Other values (241) 314
71.5%
2023-12-11T12:33:35.923747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 162
14.9%
2 135
12.4%
. 126
11.6%
3 115
10.6%
4 103
9.5%
0 90
8.3%
5 85
7.8%
7 73
6.7%
9 70
6.4%
6 58
 
5.3%
Other values (4) 71
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 942
86.6%
Other Punctuation 133
 
12.2%
Dash Punctuation 12
 
1.1%
Other Letter 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 162
17.2%
2 135
14.3%
3 115
12.2%
4 103
10.9%
0 90
9.6%
5 85
9.0%
7 73
7.7%
9 70
7.4%
6 58
 
6.2%
8 51
 
5.4%
Other Punctuation
ValueCountFrequency (%)
. 126
94.7%
, 7
 
5.3%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Other Letter
ValueCountFrequency (%)
월 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1087
99.9%
Hangul 1
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 162
14.9%
2 135
12.4%
. 126
11.6%
3 115
10.6%
4 103
9.5%
0 90
8.3%
5 85
7.8%
7 73
6.7%
9 70
6.4%
6 58
 
5.3%
Other values (3) 70
6.4%
Hangul
ValueCountFrequency (%)
월 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1087
99.9%
Hangul 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 162
14.9%
2 135
12.4%
. 126
11.6%
3 115
10.6%
4 103
9.5%
0 90
8.3%
5 85
7.8%
7 73
6.7%
9 70
6.4%
6 58
 
5.3%
Other values (3) 70
6.4%
Hangul
ValueCountFrequency (%)
월 1
100.0%

Unnamed: 12
Text

MISSING 

Distinct245
Distinct (%)55.8%
Missing75
Missing (%)14.6%
Memory size4.1 KiB
2023-12-11T12:33:36.279048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.4646925
Min length1

Characters and Unicode

Total characters1082
Distinct characters14
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

Unique192 ?
Unique (%)43.7%

Sample

1st row11월
2nd row1,499
3rd row23,555
4th row911
5th row10,135
ValueCountFrequency (%)
0 45
 
10.3%
1 30
 
6.8%
2 11
 
2.5%
3 10
 
2.3%
4 10
 
2.3%
5 8
 
1.8%
9 8
 
1.8%
13 6
 
1.4%
6
 
1.4%
15 5
 
1.1%
Other values (235) 300
68.3%
2023-12-11T12:33:36.786031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 171
15.8%
. 127
11.7%
3 110
10.2%
0 98
9.1%
4 98
9.1%
5 98
9.1%
2 92
8.5%
6 89
8.2%
8 65
 
6.0%
7 60
 
5.5%
Other values (4) 74
6.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 938
86.7%
Other Punctuation 137
 
12.7%
Dash Punctuation 6
 
0.6%
Other Letter 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 171
18.2%
3 110
11.7%
0 98
10.4%
4 98
10.4%
5 98
10.4%
2 92
9.8%
6 89
9.5%
8 65
 
6.9%
7 60
 
6.4%
9 57
 
6.1%
Other Punctuation
ValueCountFrequency (%)
. 127
92.7%
, 10
 
7.3%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Other Letter
ValueCountFrequency (%)
월 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1081
99.9%
Hangul 1
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 171
15.8%
. 127
11.7%
3 110
10.2%
0 98
9.1%
4 98
9.1%
5 98
9.1%
2 92
8.5%
6 89
8.2%
8 65
 
6.0%
7 60
 
5.6%
Other values (3) 73
6.8%
Hangul
ValueCountFrequency (%)
월 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1081
99.9%
Hangul 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 171
15.8%
. 127
11.7%
3 110
10.2%
0 98
9.1%
4 98
9.1%
5 98
9.1%
2 92
8.5%
6 89
8.2%
8 65
 
6.0%
7 60
 
5.6%
Other values (3) 73
6.8%
Hangul
ValueCountFrequency (%)
월 1
100.0%

Unnamed: 13
Text

MISSING 

Distinct232
Distinct (%)52.8%
Missing75
Missing (%)14.6%
Memory size4.1 KiB
2023-12-11T12:33:37.190191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3348519
Min length1

Characters and Unicode

Total characters1025
Distinct characters14
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

Unique174 ?
Unique (%)39.6%

Sample

1st row12월
2nd row2,863
3rd row12,899
4th row1,275
5th row5,507
ValueCountFrequency (%)
0 46
 
10.5%
1 26
 
5.9%
2 14
 
3.2%
12
 
2.7%
9 11
 
2.5%
3 9
 
2.1%
7 8
 
1.8%
4 7
 
1.6%
17 6
 
1.4%
5 5
 
1.1%
Other values (222) 295
67.2%
2023-12-11T12:33:37.784618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 158
15.4%
2 125
12.2%
. 117
11.4%
3 110
10.7%
4 84
8.2%
5 84
8.2%
0 81
7.9%
8 68
6.6%
7 60
 
5.9%
6 60
 
5.9%
Other values (4) 78
7.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 889
86.7%
Other Punctuation 123
 
12.0%
Dash Punctuation 12
 
1.2%
Other Letter 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 158
17.8%
2 125
14.1%
3 110
12.4%
4 84
9.4%
5 84
9.4%
0 81
9.1%
8 68
7.6%
7 60
 
6.7%
6 60
 
6.7%
9 59
 
6.6%
Other Punctuation
ValueCountFrequency (%)
. 117
95.1%
, 6
 
4.9%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Other Letter
ValueCountFrequency (%)
월 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1024
99.9%
Hangul 1
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 158
15.4%
2 125
12.2%
. 117
11.4%
3 110
10.7%
4 84
8.2%
5 84
8.2%
0 81
7.9%
8 68
6.6%
7 60
 
5.9%
6 60
 
5.9%
Other values (3) 77
7.5%
Hangul
ValueCountFrequency (%)
월 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1024
99.9%
Hangul 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 158
15.4%
2 125
12.2%
. 117
11.4%
3 110
10.7%
4 84
8.2%
5 84
8.2%
0 81
7.9%
8 68
6.6%
7 60
 
5.9%
6 60
 
5.9%
Other values (3) 77
7.5%
Hangul
ValueCountFrequency (%)
월 1
100.0%

Unnamed: 14
Text

MISSING 

Distinct175
Distinct (%)39.8%
Missing74
Missing (%)14.4%
Memory size4.1 KiB
2023-12-11T12:33:38.152755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.0590909
Min length1

Characters and Unicode

Total characters906
Distinct characters15
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

Unique129 ?
Unique (%)29.3%

Sample

1st row2021년
2nd row1월
3rd row734
4th row3,445
5th row319
ValueCountFrequency (%)
0 66
 
15.0%
46
 
10.5%
1 26
 
5.9%
2 20
 
4.5%
3 18
 
4.1%
6 11
 
2.5%
4 9
 
2.0%
5 9
 
2.0%
7 7
 
1.6%
11 6
 
1.4%
Other values (165) 222
50.5%
2023-12-11T12:33:38.704016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 131
14.5%
. 111
12.3%
3 102
11.3%
4 95
10.5%
2 94
10.4%
0 90
9.9%
5 61
6.7%
6 59
6.5%
- 46
 
5.1%
7 44
 
4.9%
Other values (5) 73
8.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 745
82.2%
Other Punctuation 113
 
12.5%
Dash Punctuation 46
 
5.1%
Other Letter 2
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 131
17.6%
3 102
13.7%
4 95
12.8%
2 94
12.6%
0 90
12.1%
5 61
8.2%
6 59
7.9%
7 44
 
5.9%
8 40
 
5.4%
9 29
 
3.9%
Other Punctuation
ValueCountFrequency (%)
. 111
98.2%
, 2
 
1.8%
Other Letter
ValueCountFrequency (%)
월 1
50.0%
년 1
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 904
99.8%
Hangul 2
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 131
14.5%
. 111
12.3%
3 102
11.3%
4 95
10.5%
2 94
10.4%
0 90
10.0%
5 61
6.7%
6 59
6.5%
- 46
 
5.1%
7 44
 
4.9%
Other values (3) 71
7.9%
Hangul
ValueCountFrequency (%)
월 1
50.0%
년 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 904
99.8%
Hangul 2
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 131
14.5%
. 111
12.3%
3 102
11.3%
4 95
10.5%
2 94
10.4%
0 90
10.0%
5 61
6.7%
6 59
6.5%
- 46
 
5.1%
7 44
 
4.9%
Other values (3) 71
7.9%
Hangul
ValueCountFrequency (%)
월 1
50.0%
년 1
50.0%

Unnamed: 15
Text

MISSING 

Distinct167
Distinct (%)38.0%
Missing75
Missing (%)14.6%
Memory size4.1 KiB
2023-12-11T12:33:39.039257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length2.0182232
Min length1

Characters and Unicode

Total characters886
Distinct characters14
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

Unique124 ?
Unique (%)28.2%

Sample

1st row2월
2nd row490
3rd row2,338
4th row255
5th row1,199
ValueCountFrequency (%)
0 79
 
18.0%
42
 
9.6%
1 40
 
9.1%
2 23
 
5.2%
5 12
 
2.7%
3 10
 
2.3%
4 9
 
2.1%
8 8
 
1.8%
12 6
 
1.4%
9 5
 
1.1%
Other values (157) 205
46.7%
2023-12-11T12:33:39.533408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 128
14.4%
. 120
13.5%
0 110
12.4%
2 99
11.2%
4 82
9.3%
5 72
8.1%
3 65
7.3%
7 52
5.9%
6 45
 
5.1%
- 42
 
4.7%
Other values (4) 71
8.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 721
81.4%
Other Punctuation 122
 
13.8%
Dash Punctuation 42
 
4.7%
Other Letter 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 128
17.8%
0 110
15.3%
2 99
13.7%
4 82
11.4%
5 72
10.0%
3 65
9.0%
7 52
7.2%
6 45
 
6.2%
9 36
 
5.0%
8 32
 
4.4%
Other Punctuation
ValueCountFrequency (%)
. 120
98.4%
, 2
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 42
100.0%
Other Letter
ValueCountFrequency (%)
월 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 885
99.9%
Hangul 1
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 128
14.5%
. 120
13.6%
0 110
12.4%
2 99
11.2%
4 82
9.3%
5 72
8.1%
3 65
7.3%
7 52
5.9%
6 45
 
5.1%
- 42
 
4.7%
Other values (3) 70
7.9%
Hangul
ValueCountFrequency (%)
월 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 885
99.9%
Hangul 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 128
14.5%
. 120
13.6%
0 110
12.4%
2 99
11.2%
4 82
9.3%
5 72
8.1%
3 65
7.3%
7 52
5.9%
6 45
 
5.1%
- 42
 
4.7%
Other values (3) 70
7.9%
Hangul
ValueCountFrequency (%)
월 1
100.0%

Unnamed: 16
Text

MISSING 

Distinct330
Distinct (%)75.2%
Missing75
Missing (%)14.6%
Memory size4.1 KiB
2023-12-11T12:33:39.900806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length3.0341686
Min length1

Characters and Unicode

Total characters1332
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

Unique274 ?
Unique (%)62.4%

Sample

1st row합계
2nd row22,845
3rd row114,100
4th row10,147
5th row48,753
ValueCountFrequency (%)
0 17
 
3.9%
1 8
 
1.8%
3 7
 
1.6%
16 6
 
1.4%
4 6
 
1.4%
2 5
 
1.1%
6 5
 
1.1%
69 3
 
0.7%
5 3
 
0.7%
10 3
 
0.7%
Other values (320) 376
85.6%
2023-12-11T12:33:40.394092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 200
15.0%
2 163
12.2%
3 140
10.5%
. 128
9.6%
4 120
9.0%
5 104
7.8%
6 96
7.2%
7 92
6.9%
8 89
6.7%
9 75
 
5.6%
Other values (4) 125
9.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1151
86.4%
Other Punctuation 179
 
13.4%
Other Letter 2
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 200
17.4%
2 163
14.2%
3 140
12.2%
4 120
10.4%
5 104
9.0%
6 96
8.3%
7 92
8.0%
8 89
7.7%
9 75
 
6.5%
0 72
 
6.3%
Other Punctuation
ValueCountFrequency (%)
. 128
71.5%
, 51
 
28.5%
Other Letter
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1330
99.8%
Hangul 2
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 200
15.0%
2 163
12.3%
3 140
10.5%
. 128
9.6%
4 120
9.0%
5 104
7.8%
6 96
7.2%
7 92
6.9%
8 89
6.7%
9 75
 
5.6%
Other values (2) 123
9.2%
Hangul
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1330
99.8%
Hangul 2
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 200
15.0%
2 163
12.3%
3 140
10.5%
. 128
9.6%
4 120
9.0%
5 104
7.8%
6 96
7.2%
7 92
6.9%
8 89
6.7%
9 75
 
5.6%
Other values (2) 123
9.2%
Hangul
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%

Correlations

2023-12-11T12:33:40.501893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
학교급식 품목별 친환경농산물 주요 품목별 규모Unnamed: 1Unnamed: 2Unnamed: 3
학교급식 품목별 친환경농산물 주요 품목별 규모1.0001.000NaNNaN
Unnamed: 11.0001.000NaNNaN
Unnamed: 2NaNNaN1.0001.000
Unnamed: 3NaNNaN1.0001.000
2023-12-11T12:33:40.630477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 2Unnamed: 3
Unnamed: 21.0000.997
Unnamed: 30.9971.000
2023-12-11T12:33:40.714279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 2Unnamed: 3
Unnamed: 21.0000.997
Unnamed: 30.9971.000

Missing values

2023-12-11T12:33:25.295560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T12:33:25.564343image/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.
2023-12-11T12:33:25.827579image/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

학교급식 품목별 친환경농산물 주요 품목별 규모Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16
0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1구분<NA><NA><NA>2020년<NA><NA><NA><NA><NA><NA><NA><NA><NA>2021년<NA>합계
2<NA><NA><NA><NA>3월4월5월6월7월8월9월10월11월12월1월2월<NA>
3전체<NA>전체물량1,8317618932,8112,5481,5362,7824,0971,4992,86373449022,845
4<NA><NA>(A)매출액8,0203,2063,36310,8909,8005,83411,72719,02323,55512,8993,4452,338114,100
5<NA><NA>친환경물량8693483671,1931,0726181,1711,7489111,27531925510,147
6<NA><NA>(B)매출액3,8121,4911,3714,6004,1432,3124,7767,94210,1355,5071,4641,19948,753
7<NA><NA>친환경물량47.545.741.142.442.140.342.142.760.844.543.552.144.4
8<NA><NA>비율<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
9<NA><NA>(B/A)매출액47.546.540.842.242.339.640.741.84342.742.551.342.7
학교급식 품목별 친환경농산물 주요 품목별 규모Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16
504<NA><NA>친환경물량22.2---9.333.620.45.729.85.1-503
505<NA><NA>비율<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
506<NA><NA>(B/A)매출액19.2---7.134.230.74.5125.1-71.22.6
50772호밀전체물량0---0-0000--0
508<NA><NA>(A)매출액0---0-0000--2
509<NA><NA>친환경물량0---0-0000--0
510<NA><NA>(B)매출액0---0-0000--0
511<NA><NA>친환경물량100---52.6-100100100100--14.2
512<NA><NA>비율<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
513<NA><NA>(B/A)매출액100---18.5-100100100100--11.8

Duplicate rows

Most frequently occurring

학교급식 품목별 친환경농산물 주요 품목별 규모Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16# duplicates
0<NA><NA>비율<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>73
2<NA><NA>친환경물량00000000000014
1<NA><NA>친환경물량00000000000002
3<NA><NA>친환경물량10011011110062