Overview

Dataset statistics

Number of variables12
Number of observations122
Missing cells557
Missing cells (%)38.0%
Duplicate rows1
Duplicate rows (%)0.8%
Total size in memory11.7 KiB
Average record size in memory98.0 B

Variable types

Text8
Categorical3
Unsupported1

Dataset

Description곤충산업 현황 실태조사
Author농림축산식품부
URLhttps://data.mafra.go.kr/opendata/data/indexOpenDataDetail.do?data_id=20210727000000001441

Alerts

Unnamed: 10 has constant value ""Constant
Dataset has 1 (0.8%) duplicate rowsDuplicates
Unnamed: 6 is highly overall correlated with Unnamed: 7High correlation
Unnamed: 7 is highly overall correlated with Unnamed: 6High correlation
8. 지자체 곤충관련 사업 재정 지원 현황 has 108 (88.5%) missing valuesMissing
Unnamed: 1 has 22 (18.0%) missing valuesMissing
Unnamed: 2 has 9 (7.4%) missing valuesMissing
Unnamed: 3 has 9 (7.4%) missing valuesMissing
Unnamed: 5 has 91 (74.6%) missing valuesMissing
Unnamed: 8 has 53 (43.4%) missing valuesMissing
Unnamed: 9 has 22 (18.0%) missing valuesMissing
Unnamed: 10 has 121 (99.2%) missing valuesMissing
Unnamed: 11 has 122 (100.0%) missing valuesMissing
Unnamed: 11 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-21 21:53:08.018679
Analysis finished2024-04-21 21:53:11.930493
Duration3.91 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

8. 지자체 곤충관련 사업 재정 지원 현황
Text

MISSING 

Distinct14
Distinct (%)100.0%
Missing108
Missing (%)88.5%
Memory size1.1 KiB
2024-04-22T06:53:12.420551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters28
Distinct characters18
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

Unique14 ?
Unique (%)100.0%

Sample

1st row?
2nd row서울
3rd row울산
4th row대전
5th row경기
ValueCountFrequency (%)
1
 
7.1%
서울 1
 
7.1%
울산 1
 
7.1%
대전 1
 
7.1%
경기 1
 
7.1%
강원 1
 
7.1%
충북 1
 
7.1%
충남 1
 
7.1%
전북 1
 
7.1%
전남 1
 
7.1%
Other values (4) 4
28.6%
2024-04-22T06:53:13.195550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
전 3
 
10.7%
경 3
 
10.7%
남 3
 
10.7%
북 3
 
10.7%
충 2
 
7.1%
울 2
 
7.1%
? 1
 
3.6%
합 1
 
3.6%
주 1
 
3.6%
제 1
 
3.6%
Other values (8) 8
28.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 26
92.9%
Other Punctuation 1
 
3.6%
Space Separator 1
 
3.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 3
11.5%
경 3
11.5%
남 3
11.5%
북 3
11.5%
충 2
 
7.7%
울 2
 
7.7%
합 1
 
3.8%
주 1
 
3.8%
제 1
 
3.8%
강 1
 
3.8%
Other values (6) 6
23.1%
Other Punctuation
ValueCountFrequency (%)
? 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 26
92.9%
Common 2
 
7.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 3
11.5%
경 3
11.5%
남 3
11.5%
북 3
11.5%
충 2
 
7.7%
울 2
 
7.7%
합 1
 
3.8%
주 1
 
3.8%
제 1
 
3.8%
강 1
 
3.8%
Other values (6) 6
23.1%
Common
ValueCountFrequency (%)
? 1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 26
92.9%
ASCII 2
 
7.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
전 3
11.5%
경 3
11.5%
남 3
11.5%
북 3
11.5%
충 2
 
7.7%
울 2
 
7.7%
합 1
 
3.8%
주 1
 
3.8%
제 1
 
3.8%
강 1
 
3.8%
Other values (6) 6
23.1%
ASCII
ValueCountFrequency (%)
? 1
50.0%
1
50.0%

Unnamed: 1
Text

MISSING 

Distinct59
Distinct (%)59.0%
Missing22
Missing (%)18.0%
Memory size1.1 KiB
2024-04-22T06:53:13.955446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3
Min length2

Characters and Unicode

Total characters300
Distinct characters68
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

Unique40 ?
Unique (%)40.0%

Sample

1st row시군구명
2nd row서울시
3rd row금천구
4th row울주군
5th row중구
ValueCountFrequency (%)
여주시 8
 
7.9%
진주시 8
 
7.9%
예천군 5
 
5.0%
용인시 4
 
4.0%
장수군 3
 
3.0%
시흥시 3
 
3.0%
안성시 3
 
3.0%
함안군 3
 
3.0%
익산시 3
 
3.0%
경상북도 3
 
3.0%
Other values (49) 58
57.4%
2024-04-22T06:53:14.981456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 55
18.3%
군 31
 
10.3%
주 26
 
8.7%
진 12
 
4.0%
천 11
 
3.7%
여 9
 
3.0%
성 8
 
2.7%
안 8
 
2.7%
산 6
 
2.0%
창 6
 
2.0%
Other values (58) 128
42.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 297
99.0%
Space Separator 2
 
0.7%
Other Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 55
18.5%
군 31
 
10.4%
주 26
 
8.8%
진 12
 
4.0%
천 11
 
3.7%
여 9
 
3.0%
성 8
 
2.7%
안 8
 
2.7%
산 6
 
2.0%
창 6
 
2.0%
Other values (56) 125
42.1%
Space Separator
ValueCountFrequency (%)
2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 297
99.0%
Common 3
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 55
18.5%
군 31
 
10.4%
주 26
 
8.8%
진 12
 
4.0%
천 11
 
3.7%
여 9
 
3.0%
성 8
 
2.7%
안 8
 
2.7%
산 6
 
2.0%
창 6
 
2.0%
Other values (56) 125
42.1%
Common
ValueCountFrequency (%)
2
66.7%
, 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 297
99.0%
ASCII 3
 
1.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 55
18.5%
군 31
 
10.4%
주 26
 
8.8%
진 12
 
4.0%
천 11
 
3.7%
여 9
 
3.0%
성 8
 
2.7%
안 8
 
2.7%
산 6
 
2.0%
창 6
 
2.0%
Other values (56) 125
42.1%
ASCII
ValueCountFrequency (%)
2
66.7%
, 1
33.3%

Unnamed: 2
Text

MISSING 

Distinct85
Distinct (%)75.2%
Missing9
Missing (%)7.4%
Memory size1.1 KiB
2024-04-22T06:53:15.906910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length23
Mean length13.212389
Min length1

Characters and Unicode

Total characters1493
Distinct characters180
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

Unique74 ?
Unique (%)65.5%

Sample

1st row사업명
2nd row곤충산업 창업 기반확대
3rd row곤충산업 창업 기반확대
4th row2
5th row곤충유통사업지원
ValueCountFrequency (%)
지원사업 23
 
6.5%
유용곤충 17
 
4.8%
시범 12
 
3.4%
개발 11
 
3.1%
곤충산업 10
 
2.8%
사육 10
 
2.8%
식용곤충 8
 
2.3%
사육시설 7
 
2.0%
및 7
 
2.0%
곤충 6
 
1.7%
Other values (156) 244
68.7%
2024-04-22T06:53:17.112885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
242
 
16.2%
충 98
 
6.6%
곤 93
 
6.2%
사 82
 
5.5%
업 62
 
4.2%
용 51
 
3.4%
육 46
 
3.1%
지 43
 
2.9%
시 42
 
2.8%
원 38
 
2.5%
Other values (170) 696
46.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1225
82.0%
Space Separator 242
 
16.2%
Decimal Number 18
 
1.2%
Other Punctuation 4
 
0.3%
Close Punctuation 2
 
0.1%
Open Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
충 98
 
8.0%
곤 93
 
7.6%
사 82
 
6.7%
업 62
 
5.1%
용 51
 
4.2%
육 46
 
3.8%
지 43
 
3.5%
시 42
 
3.4%
원 38
 
3.1%
산 31
 
2.5%
Other values (160) 639
52.2%
Decimal Number
ValueCountFrequency (%)
2 5
27.8%
6 4
22.2%
9 3
16.7%
4 3
16.7%
1 2
 
11.1%
3 1
 
5.6%
Space Separator
ValueCountFrequency (%)
242
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1225
82.0%
Common 268
 
18.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
충 98
 
8.0%
곤 93
 
7.6%
사 82
 
6.7%
업 62
 
5.1%
용 51
 
4.2%
육 46
 
3.8%
지 43
 
3.5%
시 42
 
3.4%
원 38
 
3.1%
산 31
 
2.5%
Other values (160) 639
52.2%
Common
ValueCountFrequency (%)
242
90.3%
2 5
 
1.9%
6 4
 
1.5%
, 4
 
1.5%
9 3
 
1.1%
4 3
 
1.1%
) 2
 
0.7%
( 2
 
0.7%
1 2
 
0.7%
3 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1225
82.0%
ASCII 268
 
18.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
242
90.3%
2 5
 
1.9%
6 4
 
1.5%
, 4
 
1.5%
9 3
 
1.1%
4 3
 
1.1%
) 2
 
0.7%
( 2
 
0.7%
1 2
 
0.7%
3 1
 
0.4%
Hangul
ValueCountFrequency (%)
충 98
 
8.0%
곤 93
 
7.6%
사 82
 
6.7%
업 62
 
5.1%
용 51
 
4.2%
육 46
 
3.8%
지 43
 
3.5%
시 42
 
3.4%
원 38
 
3.1%
산 31
 
2.5%
Other values (160) 639
52.2%

Unnamed: 3
Text

MISSING 

Distinct53
Distinct (%)46.9%
Missing9
Missing (%)7.4%
Memory size1.1 KiB
2024-04-22T06:53:17.808707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length7
Mean length7.5752212
Min length6

Characters and Unicode

Total characters856
Distinct characters23
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)32.7%

Sample

1st row 총사업비 (백만원)
2nd row 72.00
3rd row 3.00
4th row 75.00
5th row 260.00
ValueCountFrequency (%)
30.00 12
 
10.5%
50.00 11
 
9.6%
10.00 11
 
9.6%
100.00 6
 
5.3%
200.00 6
 
5.3%
80.00 5
 
4.4%
25.00 3
 
2.6%
20.00 3
 
2.6%
40.00 3
 
2.6%
240.00 3
 
2.6%
Other values (44) 51
44.7%
2024-04-22T06:53:18.739922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 327
38.2%
226
26.4%
. 112
 
13.1%
5 32
 
3.7%
2 30
 
3.5%
3 30
 
3.5%
1 29
 
3.4%
4 15
 
1.8%
6 12
 
1.4%
7 9
 
1.1%
Other values (13) 34
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 499
58.3%
Space Separator 226
26.4%
Other Punctuation 121
 
14.1%
Other Letter 7
 
0.8%
Control 1
 
0.1%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 327
65.5%
5 32
 
6.4%
2 30
 
6.0%
3 30
 
6.0%
1 29
 
5.8%
4 15
 
3.0%
6 12
 
2.4%
7 9
 
1.8%
8 9
 
1.8%
9 6
 
1.2%
Other Letter
ValueCountFrequency (%)
총 1
14.3%
사 1
14.3%
업 1
14.3%
비 1
14.3%
백 1
14.3%
만 1
14.3%
원 1
14.3%
Other Punctuation
ValueCountFrequency (%)
. 112
92.6%
, 9
 
7.4%
Space Separator
ValueCountFrequency (%)
226
100.0%
Control
ValueCountFrequency (%)
1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 849
99.2%
Hangul 7
 
0.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 327
38.5%
226
26.6%
. 112
 
13.2%
5 32
 
3.8%
2 30
 
3.5%
3 30
 
3.5%
1 29
 
3.4%
4 15
 
1.8%
6 12
 
1.4%
7 9
 
1.1%
Other values (6) 27
 
3.2%
Hangul
ValueCountFrequency (%)
총 1
14.3%
사 1
14.3%
업 1
14.3%
비 1
14.3%
백 1
14.3%
만 1
14.3%
원 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 849
99.2%
Hangul 7
 
0.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 327
38.5%
226
26.6%
. 112
 
13.2%
5 32
 
3.8%
2 30
 
3.5%
3 30
 
3.5%
1 29
 
3.4%
4 15
 
1.8%
6 12
 
1.4%
7 9
 
1.1%
Other values (6) 27
 
3.2%
Hangul
ValueCountFrequency (%)
총 1
14.3%
사 1
14.3%
업 1
14.3%
비 1
14.3%
백 1
14.3%
만 1
14.3%
원 1
14.3%

Unnamed: 4
Categorical

Distinct47
Distinct (%)38.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
22 
곤충사육농가
13 
곤충사육 단체, 법인
10 
곤충 사육농가, 법인
8 
경남농업기술원
8 
Other values (42)
61 

Length

Max length23
Median length21
Mean length8.1803279
Min length2

Unique

Unique34 ?
Unique (%)27.9%

Sample

1st row사업대상자
2nd row<NA>
3rd row곤충창업자 및 창업예정자
4th row곤충사육농가 및 사업자
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 22
18.0%
곤충사육농가 13
 
10.7%
곤충사육 단체, 법인 10
 
8.2%
곤충 사육농가, 법인 8
 
6.6%
경남농업기술원 8
 
6.6%
곤충사육농가, 법인 7
 
5.7%
지자체 사업소 5
 
4.1%
곤충농업법인 4
 
3.3%
곤충산업연구회 3
 
2.5%
경북잠사곤충사업장 2
 
1.6%
Other values (37) 40
32.8%

Length

2024-04-22T06:53:19.077100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
법인 32
14.5%
곤충사육농가 27
 
12.2%
na 22
 
10.0%
곤충사육 16
 
7.2%
단체 13
 
5.9%
곤충 9
 
4.1%
사육농가 8
 
3.6%
경남농업기술원 8
 
3.6%
및 7
 
3.2%
지자체 5
 
2.3%
Other values (46) 74
33.5%

Unnamed: 5
Text

MISSING 

Distinct20
Distinct (%)64.5%
Missing91
Missing (%)74.6%
Memory size1.1 KiB
2024-04-22T06:53:19.570782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length7
Mean length5.7419355
Min length2

Characters and Unicode

Total characters178
Distinct characters18
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

Unique14 ?
Unique (%)45.2%

Sample

1st row지원조건
2nd row국비
3rd row130.0
4th row130.0
5th row25.0
ValueCountFrequency (%)
130.0 4
 
12.9%
30.0 3
 
9.7%
120.0 3
 
9.7%
100.0 3
 
9.7%
1500.0 2
 
6.5%
80.0 2
 
6.5%
300.0 1
 
3.2%
420.0 1
 
3.2%
552.0 1
 
3.2%
33.0 1
 
3.2%
Other values (10) 10
32.3%
2024-04-22T06:53:20.340168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 61
34.3%
30
16.9%
. 29
16.3%
1 17
 
9.6%
3 11
 
6.2%
2 9
 
5.1%
5 8
 
4.5%
8 2
 
1.1%
4 2
 
1.1%
조 1
 
0.6%
Other values (8) 8
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 112
62.9%
Space Separator 30
 
16.9%
Other Punctuation 30
 
16.9%
Other Letter 6
 
3.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 61
54.5%
1 17
 
15.2%
3 11
 
9.8%
2 9
 
8.0%
5 8
 
7.1%
8 2
 
1.8%
4 2
 
1.8%
9 1
 
0.9%
6 1
 
0.9%
Other Letter
ValueCountFrequency (%)
조 1
16.7%
건 1
16.7%
비 1
16.7%
원 1
16.7%
지 1
16.7%
국 1
16.7%
Other Punctuation
ValueCountFrequency (%)
. 29
96.7%
, 1
 
3.3%
Space Separator
ValueCountFrequency (%)
30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 172
96.6%
Hangul 6
 
3.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 61
35.5%
30
17.4%
. 29
16.9%
1 17
 
9.9%
3 11
 
6.4%
2 9
 
5.2%
5 8
 
4.7%
8 2
 
1.2%
4 2
 
1.2%
, 1
 
0.6%
Other values (2) 2
 
1.2%
Hangul
ValueCountFrequency (%)
조 1
16.7%
건 1
16.7%
비 1
16.7%
원 1
16.7%
지 1
16.7%
국 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 172
96.6%
Hangul 6
 
3.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 61
35.5%
30
17.4%
. 29
16.9%
1 17
 
9.9%
3 11
 
6.4%
2 9
 
5.2%
5 8
 
4.7%
8 2
 
1.2%
4 2
 
1.2%
, 1
 
0.6%
Other values (2) 2
 
1.2%
Hangul
ValueCountFrequency (%)
조 1
16.7%
건 1
16.7%
비 1
16.7%
원 1
16.7%
지 1
16.7%
국 1
16.7%

Unnamed: 6
Categorical

HIGH CORRELATION 

Distinct38
Distinct (%)31.1%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
45 
7.5
9 
9.0
9 
1.2
6 
12.0
 
4
Other values (33)
49 

Length

Max length10
Median length4
Mean length4.5491803
Min length3

Unique

Unique24 ?
Unique (%)19.7%

Sample

1st row<NA>
2nd row시도비
3rd row72.0
4th row<NA>
5th row72.0

Common Values

ValueCountFrequency (%)
<NA> 45
36.9%
7.5 9
 
7.4%
9.0 9
 
7.4%
1.2 6
 
4.9%
12.0 4
 
3.3%
15.0 4
 
3.3%
72.0 4
 
3.3%
100.0 3
 
2.5%
90.0 3
 
2.5%
36.0 3
 
2.5%
Other values (28) 32
26.2%

Length

2024-04-22T06:53:20.581449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 45
36.9%
9.0 9
 
7.4%
7.5 9
 
7.4%
1.2 6
 
4.9%
12.0 4
 
3.3%
15.0 4
 
3.3%
72.0 4
 
3.3%
100.0 3
 
2.5%
90.0 3
 
2.5%
36.0 3
 
2.5%
Other values (28) 32
26.2%

Unnamed: 7
Categorical

HIGH CORRELATION 

Distinct50
Distinct (%)41.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
23 
17.50
9 
15.00
8 
21.00
 
6
3.80
 
6
Other values (45)
70 

Length

Max length10
Median length8
Mean length5.7377049
Min length4

Unique

Unique33 ?
Unique (%)27.0%

Sample

1st row<NA>
2nd row시군구비
3rd row<NA>
4th row3.00
5th row3.00

Common Values

ValueCountFrequency (%)
<NA> 23
18.9%
17.50 9
 
7.4%
15.00 8
 
6.6%
21.00 6
 
4.9%
3.80 6
 
4.9%
100.00 5
 
4.1%
10.00 4
 
3.3%
35.00 4
 
3.3%
20.00 3
 
2.5%
3.00 3
 
2.5%
Other values (40) 51
41.8%

Length

2024-04-22T06:53:20.813449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 23
18.9%
17.50 9
 
7.4%
15.00 8
 
6.6%
21.00 6
 
4.9%
3.80 6
 
4.9%
100.00 5
 
4.1%
10.00 4
 
3.3%
35.00 4
 
3.3%
20.00 3
 
2.5%
3.00 3
 
2.5%
Other values (40) 51
41.8%

Unnamed: 8
Text

MISSING 

Distinct37
Distinct (%)53.6%
Missing53
Missing (%)43.4%
Memory size1.1 KiB
2024-04-22T06:53:21.411753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length7
Mean length5.8695652
Min length3

Characters and Unicode

Total characters405
Distinct characters16
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

Unique25 ?
Unique (%)36.2%

Sample

1st row자부담
2nd row2.80
3rd row4.00
4th row21.20
5th row28.00
ValueCountFrequency (%)
25.00 8
 
11.6%
5.00 8
 
11.6%
6.00 6
 
8.7%
30.00 4
 
5.8%
15.00 3
 
4.3%
20.00 3
 
4.3%
60.00 2
 
2.9%
120.00 2
 
2.9%
150.00 2
 
2.9%
185.00 2
 
2.9%
Other values (27) 29
42.0%
2024-04-22T06:53:22.252654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 148
36.5%
69
17.0%
. 68
16.8%
5 33
 
8.1%
2 24
 
5.9%
1 20
 
4.9%
6 11
 
2.7%
3 7
 
1.7%
8 6
 
1.5%
4 5
 
1.2%
Other values (6) 14
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 264
65.2%
Space Separator 69
 
17.0%
Other Punctuation 69
 
17.0%
Other Letter 3
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 148
56.1%
5 33
 
12.5%
2 24
 
9.1%
1 20
 
7.6%
6 11
 
4.2%
3 7
 
2.7%
8 6
 
2.3%
4 5
 
1.9%
9 5
 
1.9%
7 5
 
1.9%
Other Letter
ValueCountFrequency (%)
자 1
33.3%
부 1
33.3%
담 1
33.3%
Other Punctuation
ValueCountFrequency (%)
. 68
98.6%
, 1
 
1.4%
Space Separator
ValueCountFrequency (%)
69
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 402
99.3%
Hangul 3
 
0.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 148
36.8%
69
17.2%
. 68
16.9%
5 33
 
8.2%
2 24
 
6.0%
1 20
 
5.0%
6 11
 
2.7%
3 7
 
1.7%
8 6
 
1.5%
4 5
 
1.2%
Other values (3) 11
 
2.7%
Hangul
ValueCountFrequency (%)
자 1
33.3%
부 1
33.3%
담 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 402
99.3%
Hangul 3
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 148
36.8%
69
17.2%
. 68
16.9%
5 33
 
8.2%
2 24
 
6.0%
1 20
 
5.0%
6 11
 
2.7%
3 7
 
1.7%
8 6
 
1.5%
4 5
 
1.2%
Other values (3) 11
 
2.7%
Hangul
ValueCountFrequency (%)
자 1
33.3%
부 1
33.3%
담 1
33.3%

Unnamed: 9
Text

MISSING 

Distinct82
Distinct (%)82.0%
Missing22
Missing (%)18.0%
Memory size1.1 KiB
2024-04-22T06:53:23.607337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length28
Mean length21.64
Min length4

Characters and Unicode

Total characters2164
Distinct characters218
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

Unique77 ?
Unique (%)77.0%

Sample

1st row사업내용
2nd row곤충 및 자재지원과 곤충산업 마케팅 교육
3rd row곤충자재 등 지원
4th row곤충유통 사업지원
5th row곤충사육에 필요한 기자재 지원 등
ValueCountFrequency (%)
지원 50
 
9.2%
등 40
 
7.4%
및 35
 
6.5%
곤충 16
 
3.0%
곤충사육시설 13
 
2.4%
기자재 13
 
2.4%
사육시설 12
 
2.2%
신축 11
 
2.0%
장비 10
 
1.8%
개발 9
 
1.7%
Other values (226) 332
61.4%
2024-04-22T06:53:25.219659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
441
 
20.4%
충 95
 
4.4%
곤 91
 
4.2%
사 83
 
3.8%
육 69
 
3.2%
지 67
 
3.1%
, 61
 
2.8%
원 61
 
2.8%
기 44
 
2.0%
시 41
 
1.9%
Other values (208) 1111
51.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1648
76.2%
Space Separator 441
 
20.4%
Other Punctuation 61
 
2.8%
Close Punctuation 4
 
0.2%
Open Punctuation 4
 
0.2%
Decimal Number 2
 
0.1%
Lowercase Letter 2
 
0.1%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
충 95
 
5.8%
곤 91
 
5.5%
사 83
 
5.0%
육 69
 
4.2%
지 67
 
4.1%
원 61
 
3.7%
기 44
 
2.7%
시 41
 
2.5%
등 41
 
2.5%
설 40
 
2.4%
Other values (198) 1016
61.7%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
6 1
50.0%
Lowercase Letter
ValueCountFrequency (%)
t 1
50.0%
c 1
50.0%
Uppercase Letter
ValueCountFrequency (%)
I 1
50.0%
N 1
50.0%
Space Separator
ValueCountFrequency (%)
441
100.0%
Other Punctuation
ValueCountFrequency (%)
, 61
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1648
76.2%
Common 512
 
23.7%
Latin 4
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
충 95
 
5.8%
곤 91
 
5.5%
사 83
 
5.0%
육 69
 
4.2%
지 67
 
4.1%
원 61
 
3.7%
기 44
 
2.7%
시 41
 
2.5%
등 41
 
2.5%
설 40
 
2.4%
Other values (198) 1016
61.7%
Common
ValueCountFrequency (%)
441
86.1%
, 61
 
11.9%
) 4
 
0.8%
( 4
 
0.8%
1 1
 
0.2%
6 1
 
0.2%
Latin
ValueCountFrequency (%)
t 1
25.0%
c 1
25.0%
I 1
25.0%
N 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1648
76.2%
ASCII 516
 
23.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
441
85.5%
, 61
 
11.8%
) 4
 
0.8%
( 4
 
0.8%
1 1
 
0.2%
t 1
 
0.2%
c 1
 
0.2%
I 1
 
0.2%
N 1
 
0.2%
6 1
 
0.2%
Hangul
ValueCountFrequency (%)
충 95
 
5.8%
곤 91
 
5.5%
사 83
 
5.0%
육 69
 
4.2%
지 67
 
4.1%
원 61
 
3.7%
기 44
 
2.7%
시 41
 
2.5%
등 41
 
2.5%
설 40
 
2.4%
Other values (198) 1016
61.7%

Unnamed: 10
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing121
Missing (%)99.2%
Memory size1.1 KiB
2024-04-22T06:53:25.357072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
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

Unique1 ?
Unique (%)100.0%

Sample

1st row?
ValueCountFrequency (%)
1
100.0%
2024-04-22T06:53:25.673805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
? 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 1
100.0%

Most frequent character per category

Other Punctuation
ValueCountFrequency (%)
? 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
? 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
? 1
100.0%

Unnamed: 11
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing122
Missing (%)100.0%
Memory size1.2 KiB

Correlations

2024-04-22T06:53:25.825909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
8. 지자체 곤충관련 사업 재정 지원 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9
8. 지자체 곤충관련 사업 재정 지원 현황1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 11.0001.0000.0000.0000.9840.7430.0000.7090.8310.000
Unnamed: 21.0000.0001.0000.9910.9780.9770.9870.9910.9931.000
Unnamed: 31.0000.0000.9911.0000.7320.9910.9960.9950.9900.996
Unnamed: 41.0000.9840.9780.7321.0000.8030.8690.8680.9170.992
Unnamed: 51.0000.7430.9770.9910.8031.0000.9910.9761.0000.968
Unnamed: 61.0000.0000.9870.9960.8690.9911.0000.9940.9920.992
Unnamed: 71.0000.7090.9910.9950.8680.9760.9941.0000.9910.995
Unnamed: 81.0000.8310.9930.9900.9171.0000.9920.9911.0000.991
Unnamed: 91.0000.0001.0000.9960.9920.9680.9920.9950.9911.000
2024-04-22T06:53:26.043147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 6Unnamed: 7Unnamed: 4
Unnamed: 61.0000.8430.341
Unnamed: 70.8431.0000.244
Unnamed: 40.3410.2441.000
2024-04-22T06:53:26.196587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 4Unnamed: 6Unnamed: 7
Unnamed: 41.0000.3410.244
Unnamed: 60.3411.0000.843
Unnamed: 70.2440.8431.000

Missing values

2024-04-22T06:53:11.191419image/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.
2024-04-22T06:53:11.631135image/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

8. 지자체 곤충관련 사업 재정 지원 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11
0?시군구명사업명총사업비 (백만원)사업대상자지원조건<NA><NA><NA>사업내용<NA><NA>
1<NA><NA><NA><NA><NA>국비시도비시군구비자부담<NA><NA><NA>
2서울서울시곤충산업 창업 기반확대72.00곤충창업자 및 창업예정자<NA>72.0<NA><NA>곤충 및 자재지원과 곤충산업 마케팅 교육<NA><NA>
3<NA>금천구곤충산업 창업 기반확대3.00곤충사육농가 및 사업자<NA><NA>3.00<NA>곤충자재 등 지원<NA><NA>
4<NA><NA>275.00<NA><NA>72.03.00<NA><NA><NA><NA>
5울산울주군곤충유통사업지원260.00(사)한국곤충산업중앙회 울산지부130.065.065.00<NA>곤충유통 사업지원<NA><NA>
6<NA><NA>1260.00<NA>130.065.065.00<NA><NA><NA><NA>
7대전중구곤충사육농가 소득증대사업7.00곤충사육농가<NA>2.12.102.80곤충사육에 필요한 기자재 지원 등<NA><NA>
8<NA>동구곤충사육농가 소득증대사업10.00곤충사육농가<NA>3.03.004.00곤충사육에 필요한 기자재 지원 등<NA><NA>
9<NA>유성구곤충사육농가 소득증대사업53.00곤충사육농가<NA>15.915.9021.20곤충사육에 필요한 기자재 지원 등<NA><NA>
8. 지자체 곤충관련 사업 재정 지원 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11
112<NA><NA>2350.00<NA><NA>250.0<NA>100.00<NA><NA><NA>
113합계<NA>9916,493.50<NA>4,162.003,040.707,338.551,952.25<NA><NA><NA>
114<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
115<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
116<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
117<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
118<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
119<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
120<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
121<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

8. 지자체 곤충관련 사업 재정 지원 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10# duplicates
0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>8