Overview

Dataset statistics

Number of variables16
Number of observations57
Missing cells471
Missing cells (%)51.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.3 KiB
Average record size in memory130.3 B

Variable types

Text11
Categorical5

Dataset

Description수출입식물 품목 및 대상 해충별 농약등록 현황에 대한 정보 제공
Author농림축산식품부
URLhttps://www.data.go.kr/data/15047512/fileData.do

Alerts

Unnamed: 5 is highly overall correlated with Unnamed: 6 and 2 other fieldsHigh correlation
Unnamed: 10 is highly overall correlated with Unnamed: 4 and 3 other fieldsHigh correlation
Unnamed: 4 is highly overall correlated with Unnamed: 6 and 2 other fieldsHigh correlation
Unnamed: 7 is highly overall correlated with Unnamed: 4 and 3 other fieldsHigh correlation
Unnamed: 6 is highly overall correlated with Unnamed: 4 and 3 other fieldsHigh correlation
Unnamed: 10 is highly imbalanced (52.3%)Imbalance
수출입 식물 품목별 농약 등록 현황 has 36 (63.2%) missing valuesMissing
Unnamed: 1 has 24 (42.1%) missing valuesMissing
Unnamed: 2 has 7 (12.3%) missing valuesMissing
Unnamed: 3 has 35 (61.4%) missing valuesMissing
Unnamed: 8 has 54 (94.7%) missing valuesMissing
Unnamed: 9 has 55 (96.5%) missing valuesMissing
Unnamed: 11 has 52 (91.2%) missing valuesMissing
Unnamed: 12 has 51 (89.5%) missing valuesMissing
Unnamed: 13 has 52 (91.2%) missing valuesMissing
Unnamed: 14 has 51 (89.5%) missing valuesMissing
Unnamed: 15 has 54 (94.7%) missing valuesMissing

Reproduction

Analysis started2023-12-12 10:40:15.511692
Analysis finished2023-12-12 10:40:17.461712
Duration1.95 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

수출입 식물 품목별 농약 등록 현황
Text

MISSING 

Distinct21
Distinct (%)100.0%
Missing36
Missing (%)63.2%
Memory size588.0 B
2023-12-12T19:40:17.666539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length3
Mean length3.2380952
Min length2

Characters and Unicode

Total characters68
Distinct characters42
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)100.0%

Sample

1st row유형
2nd row종자류
3rd row묘목류
4th row절화류
5th row구근류
ValueCountFrequency (%)
유형 1
 
4.3%
버섯류 1
 
4.3%
목재류 1
 
4.3%
향신료 1
 
4.3%
및 1
 
4.3%
기호 1
 
4.3%
한약재 1
 
4.3%
유료류 1
 
4.3%
섬유류 1
 
4.3%
건초류 1
 
4.3%
Other values (13) 13
56.5%
2023-12-12T19:40:18.175850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
류 17
25.0%
유 3
 
4.4%
건 3
 
4.4%
재 2
 
2.9%
목 2
 
2.9%
채 2
 
2.9%
과 2
 
2.9%
료 2
 
2.9%
2
 
2.9%
및 1
 
1.5%
Other values (32) 32
47.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 62
91.2%
Space Separator 2
 
2.9%
Control 1
 
1.5%
Open Punctuation 1
 
1.5%
Close Punctuation 1
 
1.5%
Other Punctuation 1
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
류 17
27.4%
유 3
 
4.8%
건 3
 
4.8%
재 2
 
3.2%
목 2
 
3.2%
채 2
 
3.2%
과 2
 
3.2%
료 2
 
3.2%
및 1
 
1.6%
약 1
 
1.6%
Other values (27) 27
43.5%
Space Separator
ValueCountFrequency (%)
2
100.0%
Control
ValueCountFrequency (%)
1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Other Punctuation
ValueCountFrequency (%)
: 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 62
91.2%
Common 6
 
8.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
류 17
27.4%
유 3
 
4.8%
건 3
 
4.8%
재 2
 
3.2%
목 2
 
3.2%
채 2
 
3.2%
과 2
 
3.2%
료 2
 
3.2%
및 1
 
1.6%
약 1
 
1.6%
Other values (27) 27
43.5%
Common
ValueCountFrequency (%)
2
33.3%
1
16.7%
( 1
16.7%
) 1
16.7%
: 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 62
91.2%
ASCII 6
 
8.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
류 17
27.4%
유 3
 
4.8%
건 3
 
4.8%
재 2
 
3.2%
목 2
 
3.2%
채 2
 
3.2%
과 2
 
3.2%
료 2
 
3.2%
및 1
 
1.6%
약 1
 
1.6%
Other values (27) 27
43.5%
ASCII
ValueCountFrequency (%)
2
33.3%
1
16.7%
( 1
16.7%
) 1
16.7%
: 1
16.7%

Unnamed: 1
Text

MISSING 

Distinct19
Distinct (%)57.6%
Missing24
Missing (%)42.1%
Memory size588.0 B
2023-12-12T19:40:18.379227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length127
Median length6
Mean length5.8181818
Min length1

Characters and Unicode

Total characters192
Distinct characters89
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)51.5%

Sample

1st row대상
2nd row곡류
3rd row특작
4th row목초
5th row수목
ValueCountFrequency (%)
14
31.8%
mb 2
 
4.5%
수목 2
 
4.5%
비검역용 1
 
2.3%
유라간디투(씨켐 1
 
2.3%
에틸렌포메이트 1
 
2.3%
베이퍼메이트(린데코리아 1
 
2.3%
알루미늄포스파이드 1
 
2.3%
에피흄(농협케미컬 1
 
2.3%
마그네슘포스파이드 1
 
2.3%
Other values (19) 19
43.2%
2023-12-12T19:40:18.728069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 14
 
7.3%
11
 
5.7%
, 11
 
5.7%
) 6
 
3.1%
포 6
 
3.1%
( 6
 
3.1%
이 6
 
3.1%
스 5
 
2.6%
류 5
 
2.6%
과 4
 
2.1%
Other values (79) 118
61.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 133
69.3%
Dash Punctuation 14
 
7.3%
Space Separator 11
 
5.7%
Other Punctuation 11
 
5.7%
Uppercase Letter 7
 
3.6%
Close Punctuation 6
 
3.1%
Open Punctuation 6
 
3.1%
Decimal Number 4
 
2.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
포 6
 
4.5%
이 6
 
4.5%
스 5
 
3.8%
류 5
 
3.8%
과 4
 
3.0%
채 4
 
3.0%
마 3
 
2.3%
비 3
 
2.3%
미 3
 
2.3%
수 3
 
2.3%
Other values (65) 91
68.4%
Uppercase Letter
ValueCountFrequency (%)
B 2
28.6%
M 2
28.6%
C 1
14.3%
H 1
14.3%
N 1
14.3%
Decimal Number
ValueCountFrequency (%)
2 1
25.0%
0 1
25.0%
1 1
25.0%
4 1
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%
Space Separator
ValueCountFrequency (%)
11
100.0%
Other Punctuation
ValueCountFrequency (%)
, 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 133
69.3%
Common 52
 
27.1%
Latin 7
 
3.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
포 6
 
4.5%
이 6
 
4.5%
스 5
 
3.8%
류 5
 
3.8%
과 4
 
3.0%
채 4
 
3.0%
마 3
 
2.3%
비 3
 
2.3%
미 3
 
2.3%
수 3
 
2.3%
Other values (65) 91
68.4%
Common
ValueCountFrequency (%)
- 14
26.9%
11
21.2%
, 11
21.2%
) 6
11.5%
( 6
11.5%
2 1
 
1.9%
0 1
 
1.9%
1 1
 
1.9%
4 1
 
1.9%
Latin
ValueCountFrequency (%)
B 2
28.6%
M 2
28.6%
C 1
14.3%
H 1
14.3%
N 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 133
69.3%
ASCII 59
30.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 14
23.7%
11
18.6%
, 11
18.6%
) 6
10.2%
( 6
10.2%
B 2
 
3.4%
M 2
 
3.4%
C 1
 
1.7%
H 1
 
1.7%
2 1
 
1.7%
Other values (4) 4
 
6.8%
Hangul
ValueCountFrequency (%)
포 6
 
4.5%
이 6
 
4.5%
스 5
 
3.8%
류 5
 
3.8%
과 4
 
3.0%
채 4
 
3.0%
마 3
 
2.3%
비 3
 
2.3%
미 3
 
2.3%
수 3
 
2.3%
Other values (65) 91
68.4%

Unnamed: 2
Text

MISSING 

Distinct46
Distinct (%)92.0%
Missing7
Missing (%)12.3%
Memory size588.0 B
2023-12-12T19:40:19.040124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length3.14
Min length1

Characters and Unicode

Total characters157
Distinct characters95
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)84.0%

Sample

1st row품목
2nd row호맥
3rd row벼
4th row유채
5th row참깨
ValueCountFrequency (%)
땅콩 2
 
3.9%
소나무 2
 
3.9%
참깨 2
 
3.9%
옥수수 2
 
3.9%
호두 2
 
3.9%
알팔파건초 1
 
2.0%
새송이버섯 1
 
2.0%
파인애플(바나나 1
 
2.0%
건포도 1
 
2.0%
건대추 1
 
2.0%
Other values (36) 36
70.6%
2023-12-12T19:40:19.485496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
나 6
 
3.8%
두 5
 
3.2%
건 5
 
3.2%
추 5
 
3.2%
라 4
 
2.5%
수 4
 
2.5%
호 3
 
1.9%
감 3
 
1.9%
리 3
 
1.9%
오 3
 
1.9%
Other values (85) 116
73.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 149
94.9%
Close Punctuation 3
 
1.9%
Open Punctuation 3
 
1.9%
Other Punctuation 1
 
0.6%
Space Separator 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
나 6
 
4.0%
두 5
 
3.4%
건 5
 
3.4%
추 5
 
3.4%
라 4
 
2.7%
수 4
 
2.7%
호 3
 
2.0%
감 3
 
2.0%
리 3
 
2.0%
오 3
 
2.0%
Other values (81) 108
72.5%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 149
94.9%
Common 8
 
5.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
나 6
 
4.0%
두 5
 
3.4%
건 5
 
3.4%
추 5
 
3.4%
라 4
 
2.7%
수 4
 
2.7%
호 3
 
2.0%
감 3
 
2.0%
리 3
 
2.0%
오 3
 
2.0%
Other values (81) 108
72.5%
Common
ValueCountFrequency (%)
) 3
37.5%
( 3
37.5%
, 1
 
12.5%
1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 149
94.9%
ASCII 8
 
5.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
나 6
 
4.0%
두 5
 
3.4%
건 5
 
3.4%
추 5
 
3.4%
라 4
 
2.7%
수 4
 
2.7%
호 3
 
2.0%
감 3
 
2.0%
리 3
 
2.0%
오 3
 
2.0%
Other values (81) 108
72.5%
ASCII
ValueCountFrequency (%)
) 3
37.5%
( 3
37.5%
, 1
 
12.5%
1
 
12.5%

Unnamed: 3
Text

MISSING 

Distinct12
Distinct (%)54.5%
Missing35
Missing (%)61.4%
Memory size588.0 B
2023-12-12T19:40:19.690324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length7.1818182
Min length4

Characters and Unicode

Total characters158
Distinct characters47
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

Unique8 ?
Unique (%)36.4%

Sample

1st row대상해충
2nd row밤빛쌀도둑 쌀바구미
3rd row가루깍지벌레
4th row점박이응애
5th row뿌리응애
ValueCountFrequency (%)
밤빛쌀도둑 8
25.0%
쌀바구미 8
25.0%
점박이응애 2
 
6.2%
귤가루깍지벌레 2
 
6.2%
화랑곡나방 2
 
6.2%
대상해충 1
 
3.1%
가루깍지벌레 1
 
3.1%
뿌리응애 1
 
3.1%
감자뿔나방 1
 
3.1%
밤바구미 1
 
3.1%
Other values (5) 5
15.6%
2023-12-12T19:40:19.996014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
쌀 16
 
10.1%
10
 
6.3%
미 10
 
6.3%
밤 9
 
5.7%
바 9
 
5.7%
구 9
 
5.7%
빛 8
 
5.1%
도 8
 
5.1%
둑 8
 
5.1%
벌 5
 
3.2%
Other values (37) 66
41.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 148
93.7%
Control 10
 
6.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
쌀 16
 
10.8%
미 10
 
6.8%
밤 9
 
6.1%
바 9
 
6.1%
구 9
 
6.1%
빛 8
 
5.4%
도 8
 
5.4%
둑 8
 
5.4%
벌 5
 
3.4%
레 5
 
3.4%
Other values (36) 61
41.2%
Control
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 148
93.7%
Common 10
 
6.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
쌀 16
 
10.8%
미 10
 
6.8%
밤 9
 
6.1%
바 9
 
6.1%
구 9
 
6.1%
빛 8
 
5.4%
도 8
 
5.4%
둑 8
 
5.4%
벌 5
 
3.4%
레 5
 
3.4%
Other values (36) 61
41.2%
Common
ValueCountFrequency (%)
10
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 148
93.7%
ASCII 10
 
6.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
쌀 16
 
10.8%
미 10
 
6.8%
밤 9
 
6.1%
바 9
 
6.1%
구 9
 
6.1%
빛 8
 
5.4%
도 8
 
5.4%
둑 8
 
5.4%
벌 5
 
3.4%
레 5
 
3.4%
Other values (36) 61
41.2%
ASCII
ValueCountFrequency (%)
10
100.0%

Unnamed: 4
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size588.0 B
<NA>
29 
√
26 
검토항목
 
1
약효
 
1

Length

Max length4
Median length4
Mean length2.5964912
Min length1

Unique

Unique2 ?
Unique (%)3.5%

Sample

1st row<NA>
2nd row검토항목
3rd row약효
4th row√
5th row√

Common Values

ValueCountFrequency (%)
<NA> 29
50.9%
√ 26
45.6%
검토항목 1
 
1.8%
약효 1
 
1.8%

Length

2023-12-12T19:40:20.150673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:40:20.327247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 29
50.9%
√ 26
45.6%
검토항목 1
 
1.8%
약효 1
 
1.8%

Unnamed: 5
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size588.0 B
√
44 
<NA>
12 
약해
 
1

Length

Max length4
Median length1
Mean length1.6491228
Min length1

Unique

Unique1 ?
Unique (%)1.8%

Sample

1st row<NA>
2nd row<NA>
3rd row약해
4th row√
5th row√

Common Values

ValueCountFrequency (%)
√ 44
77.2%
<NA> 12
 
21.1%
약해 1
 
1.8%

Length

2023-12-12T19:40:20.484726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:40:20.622169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
√ 44
77.2%
na 12
 
21.1%
약해 1
 
1.8%

Unnamed: 6
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)12.3%
Missing0
Missing (%)0.0%
Memory size588.0 B
<NA>
29 
√
23 
농약잔류
 
1
방울토마토 풋고추
 
1
표고버섯
 
1
Other values (2)
 
2

Length

Max length9
Median length4
Mean length2.8070175
Min length1

Unique

Unique5 ?
Unique (%)8.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 29
50.9%
√ 23
40.4%
농약잔류 1
 
1.8%
방울토마토 풋고추 1
 
1.8%
표고버섯 1
 
1.8%
유채 1
 
1.8%
담재 1
 
1.8%

Length

2023-12-12T19:40:20.770791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:40:20.904435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 29
50.0%
√ 23
39.7%
농약잔류 1
 
1.7%
방울토마토 1
 
1.7%
풋고추 1
 
1.7%
표고버섯 1
 
1.7%
유채 1
 
1.7%
담재 1
 
1.7%

Unnamed: 7
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)10.5%
Missing0
Missing (%)0.0%
Memory size588.0 B
<NA>
31 
√(영일) √(마간)
22 
등록여부
 
1
MB
 
1
√(마간)
 
1

Length

Max length11
Median length4
Mean length6.7017544
Min length2

Unique

Unique4 ?
Unique (%)7.0%

Sample

1st row<NA>
2nd row등록여부
3rd rowMB
4th row√(마간)
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 31
54.4%
√(영일) √(마간) 22
38.6%
등록여부 1
 
1.8%
MB 1
 
1.8%
√(마간) 1
 
1.8%
√(영일) 1
 
1.8%

Length

2023-12-12T19:40:21.054802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:40:21.218184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 31
39.2%
√(영일 23
29.1%
√(마간 23
29.1%
등록여부 1
 
1.3%
mb 1
 
1.3%

Unnamed: 8
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing54
Missing (%)94.7%
Memory size588.0 B
2023-12-12T19:40:21.401316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length8
Mean length10
Min length7

Characters and Unicode

Total characters30
Distinct characters17
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row√(마간) 거배라,백합,장미
2nd row√(마간) 쌀
3rd row√(마간) 목재
ValueCountFrequency (%)
√(마간 3
50.0%
거배라,백합,장미 1
 
16.7%
쌀 1
 
16.7%
목재 1
 
16.7%
2023-12-12T19:40:21.837085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
√ 3
10.0%
마 3
10.0%
간 3
10.0%
) 3
10.0%
3
10.0%
( 3
10.0%
, 2
 
6.7%
장 1
 
3.3%
목 1
 
3.3%
쌀 1
 
3.3%
Other values (7) 7
23.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16
53.3%
Math Symbol 3
 
10.0%
Close Punctuation 3
 
10.0%
Control 3
 
10.0%
Open Punctuation 3
 
10.0%
Other Punctuation 2
 
6.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
마 3
18.8%
간 3
18.8%
장 1
 
6.2%
목 1
 
6.2%
쌀 1
 
6.2%
미 1
 
6.2%
라 1
 
6.2%
합 1
 
6.2%
백 1
 
6.2%
배 1
 
6.2%
Other values (2) 2
12.5%
Math Symbol
ValueCountFrequency (%)
√ 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Control
ValueCountFrequency (%)
3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16
53.3%
Common 14
46.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
마 3
18.8%
간 3
18.8%
장 1
 
6.2%
목 1
 
6.2%
쌀 1
 
6.2%
미 1
 
6.2%
라 1
 
6.2%
합 1
 
6.2%
백 1
 
6.2%
배 1
 
6.2%
Other values (2) 2
12.5%
Common
ValueCountFrequency (%)
√ 3
21.4%
) 3
21.4%
3
21.4%
( 3
21.4%
, 2
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16
53.3%
ASCII 11
36.7%
Math Operators 3
 
10.0%

Most frequent character per block

Math Operators
ValueCountFrequency (%)
√ 3
100.0%
Hangul
ValueCountFrequency (%)
마 3
18.8%
간 3
18.8%
장 1
 
6.2%
목 1
 
6.2%
쌀 1
 
6.2%
미 1
 
6.2%
라 1
 
6.2%
합 1
 
6.2%
백 1
 
6.2%
배 1
 
6.2%
Other values (2) 2
12.5%
ASCII
ValueCountFrequency (%)
) 3
27.3%
3
27.3%
( 3
27.3%
, 2
18.2%

Unnamed: 9
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing55
Missing (%)96.5%
Memory size588.0 B
2023-12-12T19:40:22.035850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4.5
Mean length4.5
Min length3

Characters and Unicode

Total characters9
Distinct characters9
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowMgP
2nd row√(마그나)
ValueCountFrequency (%)
mgp 1
50.0%
√(마그나 1
50.0%
2023-12-12T19:40:22.446752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
M 1
11.1%
g 1
11.1%
P 1
11.1%
√ 1
11.1%
( 1
11.1%
마 1
11.1%
그 1
11.1%
나 1
11.1%
) 1
11.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3
33.3%
Uppercase Letter 2
22.2%
Lowercase Letter 1
 
11.1%
Math Symbol 1
 
11.1%
Open Punctuation 1
 
11.1%
Close Punctuation 1
 
11.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
마 1
33.3%
그 1
33.3%
나 1
33.3%
Uppercase Letter
ValueCountFrequency (%)
M 1
50.0%
P 1
50.0%
Lowercase Letter
ValueCountFrequency (%)
g 1
100.0%
Math Symbol
ValueCountFrequency (%)
√ 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3
33.3%
Common 3
33.3%
Hangul 3
33.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
M 1
33.3%
g 1
33.3%
P 1
33.3%
Common
ValueCountFrequency (%)
√ 1
33.3%
( 1
33.3%
) 1
33.3%
Hangul
ValueCountFrequency (%)
마 1
33.3%
그 1
33.3%
나 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5
55.6%
Hangul 3
33.3%
Math Operators 1
 
11.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
M 1
20.0%
g 1
20.0%
P 1
20.0%
( 1
20.0%
) 1
20.0%
Math Operators
ValueCountFrequency (%)
√ 1
100.0%
Hangul
ValueCountFrequency (%)
마 1
33.3%
그 1
33.3%
나 1
33.3%

Unnamed: 10
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct8
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Memory size588.0 B
<NA>
40 
√(에피흄)
11 
AIP
 
1
√(에피흄) 마늘
 
1
√(에피흄) 쌀
 
1
Other values (3)
 
3

Length

Max length15
Median length4
Mean length4.9298246
Min length3

Unique

Unique6 ?
Unique (%)10.5%

Sample

1st row<NA>
2nd row<NA>
3rd rowAIP
4th row√(에피흄)
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 40
70.2%
√(에피흄) 11
 
19.3%
AIP 1
 
1.8%
√(에피흄) 마늘 1
 
1.8%
√(에피흄) 쌀 1
 
1.8%
√(에피흄) 바나나 1
 
1.8%
√(에피흄) +저장 1
 
1.8%
√(에피흄) +담배+저장해충 1
 
1.8%

Length

2023-12-12T19:40:22.658867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:40:22.827682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 40
64.5%
√(에피흄 16
 
25.8%
aip 1
 
1.6%
마늘 1
 
1.6%
쌀 1
 
1.6%
바나나 1
 
1.6%
저장 1
 
1.6%
담배+저장해충 1
 
1.6%

Unnamed: 11
Text

MISSING 

Distinct5
Distinct (%)100.0%
Missing52
Missing (%)91.2%
Memory size588.0 B
2023-12-12T19:40:23.054541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length9
Mean length9.6
Min length6

Characters and Unicode

Total characters48
Distinct characters27
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st rowPH3+CO2
2nd row√(비바킬) 드라세나
3rd row√(비바킬) 야자
4th row√(비바킬) 국화,장미,백합
5th row√(비바킬)
ValueCountFrequency (%)
√(비바킬 4
50.0%
ph3+co2 1
 
12.5%
드라세나 1
 
12.5%
야자 1
 
12.5%
국화,장미,백합 1
 
12.5%
2023-12-12T19:40:23.397949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
√ 4
 
8.3%
( 4
 
8.3%
비 4
 
8.3%
바 4
 
8.3%
킬 4
 
8.3%
) 4
 
8.3%
3
 
6.2%
, 2
 
4.2%
나 1
 
2.1%
백 1
 
2.1%
Other values (17) 17
35.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 24
50.0%
Math Symbol 5
 
10.4%
Open Punctuation 4
 
8.3%
Close Punctuation 4
 
8.3%
Uppercase Letter 4
 
8.3%
Control 3
 
6.2%
Other Punctuation 2
 
4.2%
Decimal Number 2
 
4.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
비 4
16.7%
바 4
16.7%
킬 4
16.7%
나 1
 
4.2%
백 1
 
4.2%
미 1
 
4.2%
장 1
 
4.2%
화 1
 
4.2%
국 1
 
4.2%
자 1
 
4.2%
Other values (5) 5
20.8%
Uppercase Letter
ValueCountFrequency (%)
P 1
25.0%
H 1
25.0%
O 1
25.0%
C 1
25.0%
Math Symbol
ValueCountFrequency (%)
√ 4
80.0%
+ 1
 
20.0%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
3 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Control
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 24
50.0%
Common 20
41.7%
Latin 4
 
8.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
비 4
16.7%
바 4
16.7%
킬 4
16.7%
나 1
 
4.2%
백 1
 
4.2%
미 1
 
4.2%
장 1
 
4.2%
화 1
 
4.2%
국 1
 
4.2%
자 1
 
4.2%
Other values (5) 5
20.8%
Common
ValueCountFrequency (%)
√ 4
20.0%
( 4
20.0%
) 4
20.0%
3
15.0%
, 2
10.0%
2 1
 
5.0%
+ 1
 
5.0%
3 1
 
5.0%
Latin
ValueCountFrequency (%)
P 1
25.0%
H 1
25.0%
O 1
25.0%
C 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 24
50.0%
ASCII 20
41.7%
Math Operators 4
 
8.3%

Most frequent character per block

Math Operators
ValueCountFrequency (%)
√ 4
100.0%
ASCII
ValueCountFrequency (%)
( 4
20.0%
) 4
20.0%
3
15.0%
, 2
10.0%
P 1
 
5.0%
H 1
 
5.0%
2 1
 
5.0%
O 1
 
5.0%
C 1
 
5.0%
+ 1
 
5.0%
Hangul
ValueCountFrequency (%)
비 4
16.7%
바 4
16.7%
킬 4
16.7%
나 1
 
4.2%
백 1
 
4.2%
미 1
 
4.2%
장 1
 
4.2%
화 1
 
4.2%
국 1
 
4.2%
자 1
 
4.2%
Other values (5) 5
20.8%

Unnamed: 12
Text

MISSING 

Distinct3
Distinct (%)50.0%
Missing51
Missing (%)89.5%
Memory size588.0 B
2023-12-12T19:40:23.556012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length6
Mean length7.1666667
Min length2

Characters and Unicode

Total characters43
Distinct characters18
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

Unique2 ?
Unique (%)33.3%

Sample

1st rowEF
2nd row√(베이퍼)
3rd row√(베이퍼) 키위,자몽,파인애플
4th row√(베이퍼)
5th row√(베이퍼)
ValueCountFrequency (%)
√(베이퍼 5
71.4%
ef 1
 
14.3%
키위,자몽,파인애플 1
 
14.3%
2023-12-12T19:40:23.866219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
√ 5
11.6%
베 5
11.6%
이 5
11.6%
퍼 5
11.6%
) 5
11.6%
( 5
11.6%
, 2
 
4.7%
자 1
 
2.3%
애 1
 
2.3%
인 1
 
2.3%
Other values (8) 8
18.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 23
53.5%
Math Symbol 5
 
11.6%
Close Punctuation 5
 
11.6%
Open Punctuation 5
 
11.6%
Other Punctuation 2
 
4.7%
Uppercase Letter 2
 
4.7%
Control 1
 
2.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
베 5
21.7%
이 5
21.7%
퍼 5
21.7%
자 1
 
4.3%
애 1
 
4.3%
인 1
 
4.3%
파 1
 
4.3%
몽 1
 
4.3%
키 1
 
4.3%
위 1
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
F 1
50.0%
E 1
50.0%
Math Symbol
ValueCountFrequency (%)
√ 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 23
53.5%
Common 18
41.9%
Latin 2
 
4.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
베 5
21.7%
이 5
21.7%
퍼 5
21.7%
자 1
 
4.3%
애 1
 
4.3%
인 1
 
4.3%
파 1
 
4.3%
몽 1
 
4.3%
키 1
 
4.3%
위 1
 
4.3%
Common
ValueCountFrequency (%)
√ 5
27.8%
) 5
27.8%
( 5
27.8%
, 2
 
11.1%
1
 
5.6%
Latin
ValueCountFrequency (%)
F 1
50.0%
E 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 23
53.5%
ASCII 15
34.9%
Math Operators 5
 
11.6%

Most frequent character per block

Math Operators
ValueCountFrequency (%)
√ 5
100.0%
Hangul
ValueCountFrequency (%)
베 5
21.7%
이 5
21.7%
퍼 5
21.7%
자 1
 
4.3%
애 1
 
4.3%
인 1
 
4.3%
파 1
 
4.3%
몽 1
 
4.3%
키 1
 
4.3%
위 1
 
4.3%
ASCII
ValueCountFrequency (%)
) 5
33.3%
( 5
33.3%
, 2
 
13.3%
1
 
6.7%
F 1
 
6.7%
E 1
 
6.7%

Unnamed: 13
Text

MISSING 

Distinct5
Distinct (%)100.0%
Missing52
Missing (%)91.2%
Memory size588.0 B
2023-12-12T19:40:24.030235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length10
Mean length10.4
Min length3

Characters and Unicode

Total characters52
Distinct characters22
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

Unique5 ?
Unique (%)100.0%

Sample

1st rowHCN
2nd row√(HCN) 국화,카네이션
3rd row√(HCN) 단호박
4th row√(HCN) 오이
5th row√(HCN) 배추,상추,양배추
ValueCountFrequency (%)
√(hcn 4
44.4%
hcn 1
 
11.1%
국화,카네이션 1
 
11.1%
단호박 1
 
11.1%
오이 1
 
11.1%
배추,상추,양배추 1
 
11.1%
2023-12-12T19:40:24.348858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
H 5
 
9.6%
N 5
 
9.6%
C 5
 
9.6%
√ 4
 
7.7%
( 4
 
7.7%
) 4
 
7.7%
4
 
7.7%
추 3
 
5.8%
, 3
 
5.8%
배 2
 
3.8%
Other values (12) 13
25.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18
34.6%
Uppercase Letter 15
28.8%
Math Symbol 4
 
7.7%
Open Punctuation 4
 
7.7%
Close Punctuation 4
 
7.7%
Control 4
 
7.7%
Other Punctuation 3
 
5.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
추 3
16.7%
배 2
11.1%
이 2
11.1%
호 1
 
5.6%
상 1
 
5.6%
오 1
 
5.6%
박 1
 
5.6%
네 1
 
5.6%
단 1
 
5.6%
션 1
 
5.6%
Other values (4) 4
22.2%
Uppercase Letter
ValueCountFrequency (%)
H 5
33.3%
N 5
33.3%
C 5
33.3%
Math Symbol
ValueCountFrequency (%)
√ 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Control
ValueCountFrequency (%)
4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 19
36.5%
Hangul 18
34.6%
Latin 15
28.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
추 3
16.7%
배 2
11.1%
이 2
11.1%
호 1
 
5.6%
상 1
 
5.6%
오 1
 
5.6%
박 1
 
5.6%
네 1
 
5.6%
단 1
 
5.6%
션 1
 
5.6%
Other values (4) 4
22.2%
Common
ValueCountFrequency (%)
√ 4
21.1%
( 4
21.1%
) 4
21.1%
4
21.1%
, 3
15.8%
Latin
ValueCountFrequency (%)
H 5
33.3%
N 5
33.3%
C 5
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30
57.7%
Hangul 18
34.6%
Math Operators 4
 
7.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
H 5
16.7%
N 5
16.7%
C 5
16.7%
( 4
13.3%
) 4
13.3%
4
13.3%
, 3
10.0%
Math Operators
ValueCountFrequency (%)
√ 4
100.0%
Hangul
ValueCountFrequency (%)
추 3
16.7%
배 2
11.1%
이 2
11.1%
호 1
 
5.6%
상 1
 
5.6%
오 1
 
5.6%
박 1
 
5.6%
네 1
 
5.6%
단 1
 
5.6%
션 1
 
5.6%
Other values (4) 4
22.2%

Unnamed: 14
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing51
Missing (%)89.5%
Memory size588.0 B
2023-12-12T19:40:24.529760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length15
Mean length12.833333
Min length10

Characters and Unicode

Total characters77
Distinct characters40
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st row2014. 3.31현재
2nd row√(HCN) 백합,장미
3rd row√(HCN) 오렌지
4th row√(HCN) 바나나,파인애플
5th row√(HCN) 가지,고추,방울토마토
ValueCountFrequency (%)
√(hcn 5
41.7%
2014 1
 
8.3%
3.31현재 1
 
8.3%
백합,장미 1
 
8.3%
오렌지 1
 
8.3%
바나나,파인애플 1
 
8.3%
가지,고추,방울토마토 1
 
8.3%
들깨잎 1
 
8.3%
2023-12-12T19:40:24.889800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 5
 
6.5%
√ 5
 
6.5%
5
 
6.5%
) 5
 
6.5%
C 5
 
6.5%
H 5
 
6.5%
( 5
 
6.5%
, 4
 
5.2%
지 2
 
2.6%
나 2
 
2.6%
Other values (30) 34
44.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 28
36.4%
Uppercase Letter 15
19.5%
Decimal Number 7
 
9.1%
Other Punctuation 6
 
7.8%
Math Symbol 5
 
6.5%
Control 5
 
6.5%
Close Punctuation 5
 
6.5%
Open Punctuation 5
 
6.5%
Space Separator 1
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 2
 
7.1%
나 2
 
7.1%
토 2
 
7.1%
마 1
 
3.6%
인 1
 
3.6%
들 1
 
3.6%
울 1
 
3.6%
방 1
 
3.6%
깨 1
 
3.6%
추 1
 
3.6%
Other values (15) 15
53.6%
Decimal Number
ValueCountFrequency (%)
3 2
28.6%
1 2
28.6%
2 1
14.3%
0 1
14.3%
4 1
14.3%
Uppercase Letter
ValueCountFrequency (%)
N 5
33.3%
C 5
33.3%
H 5
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
66.7%
. 2
33.3%
Math Symbol
ValueCountFrequency (%)
√ 5
100.0%
Control
ValueCountFrequency (%)
5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 34
44.2%
Hangul 28
36.4%
Latin 15
19.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 2
 
7.1%
나 2
 
7.1%
토 2
 
7.1%
마 1
 
3.6%
인 1
 
3.6%
들 1
 
3.6%
울 1
 
3.6%
방 1
 
3.6%
깨 1
 
3.6%
추 1
 
3.6%
Other values (15) 15
53.6%
Common
ValueCountFrequency (%)
√ 5
14.7%
5
14.7%
) 5
14.7%
( 5
14.7%
, 4
11.8%
3 2
 
5.9%
. 2
 
5.9%
1 2
 
5.9%
2 1
 
2.9%
0 1
 
2.9%
Other values (2) 2
 
5.9%
Latin
ValueCountFrequency (%)
N 5
33.3%
C 5
33.3%
H 5
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 44
57.1%
Hangul 28
36.4%
Math Operators 5
 
6.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 5
11.4%
5
11.4%
) 5
11.4%
C 5
11.4%
H 5
11.4%
( 5
11.4%
, 4
9.1%
3 2
 
4.5%
. 2
 
4.5%
1 2
 
4.5%
Other values (4) 4
9.1%
Math Operators
ValueCountFrequency (%)
√ 5
100.0%
Hangul
ValueCountFrequency (%)
지 2
 
7.1%
나 2
 
7.1%
토 2
 
7.1%
마 1
 
3.6%
인 1
 
3.6%
들 1
 
3.6%
울 1
 
3.6%
방 1
 
3.6%
깨 1
 
3.6%
추 1
 
3.6%
Other values (15) 15
53.6%

Unnamed: 15
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing54
Missing (%)94.7%
Memory size588.0 B
2023-12-12T19:40:25.093692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length6
Mean length7
Min length3

Characters and Unicode

Total characters21
Distinct characters15
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row2014. 3.31현재
2nd rowEDN
3rd row√(EDN)
ValueCountFrequency (%)
2014 1
25.0%
3.31현재 1
25.0%
edn 1
25.0%
√(edn 1
25.0%
2023-12-12T19:40:25.451116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2
 
9.5%
. 2
 
9.5%
3 2
 
9.5%
E 2
 
9.5%
D 2
 
9.5%
N 2
 
9.5%
2 1
 
4.8%
0 1
 
4.8%
4 1
 
4.8%
1
 
4.8%
Other values (5) 5
23.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7
33.3%
Uppercase Letter 6
28.6%
Other Punctuation 2
 
9.5%
Other Letter 2
 
9.5%
Space Separator 1
 
4.8%
Math Symbol 1
 
4.8%
Open Punctuation 1
 
4.8%
Close Punctuation 1
 
4.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2
28.6%
3 2
28.6%
2 1
14.3%
0 1
14.3%
4 1
14.3%
Uppercase Letter
ValueCountFrequency (%)
E 2
33.3%
D 2
33.3%
N 2
33.3%
Other Letter
ValueCountFrequency (%)
현 1
50.0%
재 1
50.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Math Symbol
ValueCountFrequency (%)
√ 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13
61.9%
Latin 6
28.6%
Hangul 2
 
9.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2
15.4%
. 2
15.4%
3 2
15.4%
2 1
7.7%
0 1
7.7%
4 1
7.7%
1
7.7%
√ 1
7.7%
( 1
7.7%
) 1
7.7%
Latin
ValueCountFrequency (%)
E 2
33.3%
D 2
33.3%
N 2
33.3%
Hangul
ValueCountFrequency (%)
현 1
50.0%
재 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18
85.7%
Hangul 2
 
9.5%
Math Operators 1
 
4.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2
11.1%
. 2
11.1%
3 2
11.1%
E 2
11.1%
D 2
11.1%
N 2
11.1%
2 1
5.6%
0 1
5.6%
4 1
5.6%
1
5.6%
Other values (2) 2
11.1%
Hangul
ValueCountFrequency (%)
현 1
50.0%
재 1
50.0%
Math Operators
ValueCountFrequency (%)
√ 1
100.0%

Correlations

2023-12-12T19:40:25.570282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수출입 식물 품목별 농약 등록 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15
수출입 식물 품목별 농약 등록 현황1.0001.0001.0001.0001.000NaN1.0001.0001.000NaN1.0000.000NaN1.0001.000NaN
Unnamed: 11.0001.0001.0000.8731.000NaN0.7930.749NaNNaN0.4311.0001.0001.0001.000NaN
Unnamed: 21.0001.0001.0001.0001.000NaN1.0001.0001.000NaN1.0001.0001.0001.0001.000NaN
Unnamed: 31.0000.8731.0001.0001.000NaN1.0000.0001.000NaN0.6320.0000.0001.0001.000NaN
Unnamed: 41.0001.0001.0001.0001.0000.6401.0001.000NaN0.0001.0001.0001.0001.000NaN0.000
Unnamed: 5NaNNaNNaNNaN0.6401.000NaN1.000NaN0.0001.0001.0001.0001.000NaNNaN
Unnamed: 61.0000.7931.0001.0001.000NaN1.0000.921NaNNaNNaNNaN0.0001.0001.000NaN
Unnamed: 71.0000.7491.0000.0001.0001.0000.9211.000NaN0.0000.8050.0001.0001.000NaNNaN
Unnamed: 81.000NaN1.0001.000NaNNaNNaNNaN1.000NaNNaN0.000NaNNaNNaNNaN
Unnamed: 9NaNNaNNaNNaN0.0000.000NaN0.000NaN1.0000.000NaNNaNNaNNaNNaN
Unnamed: 101.0000.4311.0000.6321.0001.000NaN0.805NaN0.0001.000NaN0.0000.0000.000NaN
Unnamed: 110.0001.0001.0000.0001.0001.000NaN0.0000.000NaNNaN1.000NaN0.000NaN0.000
Unnamed: 12NaN1.0001.0000.0001.0001.0000.0001.000NaNNaN0.000NaN1.0001.0001.000NaN
Unnamed: 131.0001.0001.0001.0001.0001.0001.0001.000NaNNaN0.0000.0001.0001.0000.000NaN
Unnamed: 141.0001.0001.0001.000NaNNaN1.000NaNNaNNaN0.000NaN1.0000.0001.000NaN
Unnamed: 15NaNNaNNaNNaN0.000NaNNaNNaNNaNNaNNaN0.000NaNNaNNaN1.000
2023-12-12T19:40:25.735646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 5Unnamed: 10Unnamed: 4Unnamed: 7Unnamed: 6
Unnamed: 51.0000.7840.4400.9511.000
Unnamed: 100.7841.0000.7070.6081.000
Unnamed: 40.4400.7071.0000.9130.926
Unnamed: 70.9510.6080.9131.0000.653
Unnamed: 61.0001.0000.9260.6531.000
2023-12-12T19:40:25.865057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 10
Unnamed: 41.0000.4400.9260.9130.707
Unnamed: 50.4401.0001.0000.9510.784
Unnamed: 60.9261.0001.0000.6531.000
Unnamed: 70.9130.9510.6531.0000.608
Unnamed: 100.7070.7841.0000.6081.000

Missing values

2023-12-12T19:40:16.661395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:40:16.886603image/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.
2023-12-12T19:40:17.180034image/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

수출입 식물 품목별 농약 등록 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15
0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2014. 3.31현재2014. 3.31현재
1유형대상품목대상해충검토항목<NA>농약잔류등록여부<NA><NA><NA><NA><NA><NA><NA><NA>
2<NA><NA><NA><NA>약효약해<NA>MB<NA>MgPAIPPH3+CO2EFHCN<NA>EDN
3종자류곡류호맥밤빛쌀도둑 쌀바구미√√<NA>√(마간)<NA>√(마그나)√(에피흄)<NA><NA><NA><NA><NA>
4<NA><NA>벼<NA>√√<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
5<NA>특작유채<NA><NA>√<NA>√(영일) √(마간)<NA><NA>√(에피흄)<NA><NA><NA><NA><NA>
6<NA><NA>참깨<NA><NA>√<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
7<NA><NA>땅콩<NA><NA>√<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
8<NA>목초오차드그라스<NA>√√<NA>√(영일) √(마간)<NA><NA>√(에피흄)<NA><NA><NA><NA><NA>
9<NA><NA>옥수수<NA>√√<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
수출입 식물 품목별 농약 등록 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15
47<NA><NA>인삼<NA>√√√<NA><NA><NA><NA><NA><NA><NA><NA><NA>
48기호 및 향신료-커피원두밤빛쌀도둑 쌀바구미<NA>√√√(영일) √(마간)<NA><NA>√(에피흄) +담배+저장해충<NA><NA><NA><NA><NA>
49<NA><NA>엽연초<NA><NA>√담재<NA><NA><NA><NA><NA><NA><NA><NA><NA>
50<NA><NA>후추<NA><NA>√√<NA><NA><NA><NA><NA><NA><NA><NA><NA>
51목재류-소나무흰개미 소나무좀√<NA><NA><NA>√(마간) 목재<NA><NA>√(비바킬)<NA><NA><NA>√(EDN)
52<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
53<NA>식물검역용<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
54<NA>비검역용<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
55<NA>2014예정<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
56상표(업체):영일엠비(농협케미컬, MB), 마간엠비(아트라텍, MB), 마그나포스(유나이티드포스포로스코리아, 마그네슘포스파이드), 에피흄(농협케미컬, 알루미늄포스파이드), 베이퍼메이트(린데코리아, 에틸렌포메이트), 유라간디투(씨켐, HCN)<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>