Overview

Dataset statistics

Number of variables12
Number of observations22
Missing cells185
Missing cells (%)70.1%
Duplicate rows2
Duplicate rows (%)9.1%
Total size in memory2.2 KiB
Average record size in memory104.0 B

Variable types

Text9
Categorical1
Unsupported2

Dataset

Description연도별천일염생산현황2015년도말
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=201985

Alerts

Dataset has 2 (9.1%) duplicate rowsDuplicates
천일염 연도별 생산 현황 has 18 (81.8%) missing valuesMissing
Unnamed: 1 has 15 (68.2%) missing valuesMissing
Unnamed: 3 has 14 (63.6%) missing valuesMissing
Unnamed: 4 has 15 (68.2%) missing valuesMissing
Unnamed: 5 has 16 (72.7%) missing valuesMissing
Unnamed: 6 has 16 (72.7%) missing valuesMissing
Unnamed: 7 has 16 (72.7%) missing valuesMissing
Unnamed: 8 has 16 (72.7%) missing valuesMissing
Unnamed: 9 has 15 (68.2%) missing valuesMissing
Unnamed: 10 has 22 (100.0%) missing valuesMissing
Unnamed: 11 has 22 (100.0%) missing valuesMissing
Unnamed: 10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 11 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-14 01:47:24.537062
Analysis finished2024-03-14 01:47:25.307299
Duration0.77 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

천일염 연도별 생산 현황
Text

MISSING 

Distinct4
Distinct (%)100.0%
Missing18
Missing (%)81.8%
Memory size308.0 B
2024-03-14T10:47:25.376284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.25
Min length2

Characters and Unicode

Total characters9
Distinct characters8
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

Unique4 ?
Unique (%)100.0%

Sample

1st row시.군
2nd row군산
3rd row고창
4th row부안
ValueCountFrequency (%)
시.군 1
25.0%
군산 1
25.0%
고창 1
25.0%
부안 1
25.0%
2024-03-14T10:47:25.802455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
군 2
22.2%
시 1
11.1%
. 1
11.1%
산 1
11.1%
고 1
11.1%
창 1
11.1%
부 1
11.1%
안 1
11.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8
88.9%
Other Punctuation 1
 
11.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
군 2
25.0%
시 1
12.5%
산 1
12.5%
고 1
12.5%
창 1
12.5%
부 1
12.5%
안 1
12.5%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8
88.9%
Common 1
 
11.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
군 2
25.0%
시 1
12.5%
산 1
12.5%
고 1
12.5%
창 1
12.5%
부 1
12.5%
안 1
12.5%
Common
ValueCountFrequency (%)
. 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8
88.9%
ASCII 1
 
11.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
군 2
25.0%
시 1
12.5%
산 1
12.5%
고 1
12.5%
창 1
12.5%
부 1
12.5%
안 1
12.5%
ASCII
ValueCountFrequency (%)
. 1
100.0%

Unnamed: 1
Text

MISSING 

Distinct7
Distinct (%)100.0%
Missing15
Missing (%)68.2%
Memory size308.0 B
2024-03-14T10:47:25.947325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length7.1428571
Min length3

Characters and Unicode

Total characters50
Distinct characters21
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

Unique7 ?
Unique (%)100.0%

Sample

1st row생산어가(종사자)
2nd row1어가(가족경영 3명)
3rd row18어가(42명)
4th row1어가
5th row(가족경영 2명)
ValueCountFrequency (%)
생산어가(종사자 1
11.1%
1어가(가족경영 1
11.1%
3명 1
11.1%
18어가(42명 1
11.1%
1어가 1
11.1%
가족경영 1
11.1%
2명 1
11.1%
9어가 1
11.1%
26명 1
11.1%
2024-03-14T10:47:26.188578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
가 7
14.0%
어 5
10.0%
( 5
10.0%
) 5
10.0%
명 4
 
8.0%
2 3
 
6.0%
1 3
 
6.0%
족 2
 
4.0%
경 2
 
4.0%
영 2
 
4.0%
Other values (11) 12
24.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 27
54.0%
Decimal Number 11
22.0%
Open Punctuation 5
 
10.0%
Close Punctuation 5
 
10.0%
Space Separator 2
 
4.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
가 7
25.9%
어 5
18.5%
명 4
14.8%
족 2
 
7.4%
경 2
 
7.4%
영 2
 
7.4%
생 1
 
3.7%
산 1
 
3.7%
자 1
 
3.7%
사 1
 
3.7%
Decimal Number
ValueCountFrequency (%)
2 3
27.3%
1 3
27.3%
9 1
 
9.1%
4 1
 
9.1%
8 1
 
9.1%
3 1
 
9.1%
6 1
 
9.1%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 27
54.0%
Common 23
46.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
가 7
25.9%
어 5
18.5%
명 4
14.8%
족 2
 
7.4%
경 2
 
7.4%
영 2
 
7.4%
생 1
 
3.7%
산 1
 
3.7%
자 1
 
3.7%
사 1
 
3.7%
Common
ValueCountFrequency (%)
( 5
21.7%
) 5
21.7%
2 3
13.0%
1 3
13.0%
2
 
8.7%
9 1
 
4.3%
4 1
 
4.3%
8 1
 
4.3%
3 1
 
4.3%
6 1
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 27
54.0%
ASCII 23
46.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
가 7
25.9%
어 5
18.5%
명 4
14.8%
족 2
 
7.4%
경 2
 
7.4%
영 2
 
7.4%
생 1
 
3.7%
산 1
 
3.7%
자 1
 
3.7%
사 1
 
3.7%
ASCII
ValueCountFrequency (%)
( 5
21.7%
) 5
21.7%
2 3
13.0%
1 3
13.0%
2
 
8.7%
9 1
 
4.3%
4 1
 
4.3%
8 1
 
4.3%
3 1
 
4.3%
6 1
 
4.3%

Unnamed: 2
Categorical

Distinct5
Distinct (%)22.7%
Missing0
Missing (%)0.0%
Memory size308.0 B
<NA>
13 
천일염
4 
(고무장판, 타일)
3 
염종류
 
1
(고무장판)
 
1

Length

Max length10
Median length4
Mean length4.6818182
Min length3

Unique

Unique2 ?
Unique (%)9.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 13
59.1%
천일염 4
 
18.2%
(고무장판, 타일) 3
 
13.6%
염종류 1
 
4.5%
(고무장판) 1
 
4.5%

Length

2024-03-14T10:47:26.303163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:47:26.396265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 13
52.0%
천일염 4
 
16.0%
고무장판 4
 
16.0%
타일 3
 
12.0%
염종류 1
 
4.0%

Unnamed: 3
Text

MISSING 

Distinct8
Distinct (%)100.0%
Missing14
Missing (%)63.6%
Memory size308.0 B
2024-03-14T10:47:26.554066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length5.75
Min length3

Characters and Unicode

Total characters46
Distinct characters18
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)100.0%

Sample

1st row염 전
2nd row면 적
3rd row(㎡)
4th row3,219,614
5th row36,959
ValueCountFrequency (%)
염 1
10.0%
전 1
10.0%
면 1
10.0%
적 1
10.0%
㎡ 1
10.0%
3,219,614 1
10.0%
36,959 1
10.0%
2,585,185 1
10.0%
19,328 1
10.0%
578,142 1
10.0%
2024-03-14T10:47:26.823209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 7
15.2%
5 5
10.9%
1 5
10.9%
2 4
8.7%
8 4
8.7%
9 4
8.7%
3 3
 
6.5%
4 2
 
4.3%
6 2
 
4.3%
2
 
4.3%
Other values (8) 8
17.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 30
65.2%
Other Punctuation 7
 
15.2%
Other Letter 4
 
8.7%
Space Separator 2
 
4.3%
Close Punctuation 1
 
2.2%
Other Symbol 1
 
2.2%
Open Punctuation 1
 
2.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 5
16.7%
1 5
16.7%
2 4
13.3%
8 4
13.3%
9 4
13.3%
3 3
10.0%
4 2
 
6.7%
6 2
 
6.7%
7 1
 
3.3%
Other Letter
ValueCountFrequency (%)
염 1
25.0%
적 1
25.0%
면 1
25.0%
전 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 42
91.3%
Hangul 4
 
8.7%

Most frequent character per script

Common
ValueCountFrequency (%)
, 7
16.7%
5 5
11.9%
1 5
11.9%
2 4
9.5%
8 4
9.5%
9 4
9.5%
3 3
7.1%
4 2
 
4.8%
6 2
 
4.8%
2
 
4.8%
Other values (4) 4
9.5%
Hangul
ValueCountFrequency (%)
염 1
25.0%
적 1
25.0%
면 1
25.0%
전 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 41
89.1%
Hangul 4
 
8.7%
CJK Compat 1
 
2.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 7
17.1%
5 5
12.2%
1 5
12.2%
2 4
9.8%
8 4
9.8%
9 4
9.8%
3 3
7.3%
4 2
 
4.9%
6 2
 
4.9%
2
 
4.9%
Other values (3) 3
7.3%
Hangul
ValueCountFrequency (%)
염 1
25.0%
적 1
25.0%
면 1
25.0%
전 1
25.0%
CJK Compat
ValueCountFrequency (%)
㎡ 1
100.0%

Unnamed: 4
Text

MISSING 

Distinct7
Distinct (%)100.0%
Missing15
Missing (%)68.2%
Memory size308.0 B
2024-03-14T10:47:26.983890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length5
Mean length9
Min length2

Characters and Unicode

Total characters63
Distinct characters17
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

Unique7 ?
Unique (%)100.0%

Sample

1st row 생산량(톤)
2nd row2010년
3rd row6,419
4th row91
5th row4,500
ValueCountFrequency (%)
생산량(톤 1
14.3%
2010년 1
14.3%
6,419 1
14.3%
91 1
14.3%
4,500 1
14.3%
180 1
14.3%
1,640 1
14.3%
2024-03-14T10:47:27.251311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
32
50.8%
0 6
 
9.5%
1 5
 
7.9%
, 3
 
4.8%
4 3
 
4.8%
6 2
 
3.2%
9 2
 
3.2%
산 1
 
1.6%
량 1
 
1.6%
( 1
 
1.6%
Other values (7) 7
 
11.1%

Most occurring categories

ValueCountFrequency (%)
Space Separator 32
50.8%
Decimal Number 21
33.3%
Other Letter 5
 
7.9%
Other Punctuation 3
 
4.8%
Open Punctuation 1
 
1.6%
Close Punctuation 1
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6
28.6%
1 5
23.8%
4 3
14.3%
6 2
 
9.5%
9 2
 
9.5%
2 1
 
4.8%
5 1
 
4.8%
8 1
 
4.8%
Other Letter
ValueCountFrequency (%)
산 1
20.0%
량 1
20.0%
톤 1
20.0%
생 1
20.0%
년 1
20.0%
Space Separator
ValueCountFrequency (%)
32
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 58
92.1%
Hangul 5
 
7.9%

Most frequent character per script

Common
ValueCountFrequency (%)
32
55.2%
0 6
 
10.3%
1 5
 
8.6%
, 3
 
5.2%
4 3
 
5.2%
6 2
 
3.4%
9 2
 
3.4%
( 1
 
1.7%
) 1
 
1.7%
2 1
 
1.7%
Other values (2) 2
 
3.4%
Hangul
ValueCountFrequency (%)
산 1
20.0%
량 1
20.0%
톤 1
20.0%
생 1
20.0%
년 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 58
92.1%
Hangul 5
 
7.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
32
55.2%
0 6
 
10.3%
1 5
 
8.6%
, 3
 
5.2%
4 3
 
5.2%
6 2
 
3.4%
9 2
 
3.4%
( 1
 
1.7%
) 1
 
1.7%
2 1
 
1.7%
Other values (2) 2
 
3.4%
Hangul
ValueCountFrequency (%)
산 1
20.0%
량 1
20.0%
톤 1
20.0%
생 1
20.0%
년 1
20.0%

Unnamed: 5
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing16
Missing (%)72.7%
Memory size308.0 B
2024-03-14T10:47:27.383507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.1666667
Min length2

Characters and Unicode

Total characters25
Distinct characters11
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

Unique6 ?
Unique (%)100.0%

Sample

1st row2011년
2nd row6,922
3rd row51
4th row4,470
5th row181
ValueCountFrequency (%)
2011년 1
16.7%
6,922 1
16.7%
51 1
16.7%
4,470 1
16.7%
181 1
16.7%
2,220 1
16.7%
2024-03-14T10:47:27.615061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 6
24.0%
1 5
20.0%
0 3
12.0%
, 3
12.0%
4 2
 
8.0%
년 1
 
4.0%
6 1
 
4.0%
9 1
 
4.0%
5 1
 
4.0%
7 1
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 21
84.0%
Other Punctuation 3
 
12.0%
Other Letter 1
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 6
28.6%
1 5
23.8%
0 3
14.3%
4 2
 
9.5%
6 1
 
4.8%
9 1
 
4.8%
5 1
 
4.8%
7 1
 
4.8%
8 1
 
4.8%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Other Letter
ValueCountFrequency (%)
년 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24
96.0%
Hangul 1
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 6
25.0%
1 5
20.8%
0 3
12.5%
, 3
12.5%
4 2
 
8.3%
6 1
 
4.2%
9 1
 
4.2%
5 1
 
4.2%
7 1
 
4.2%
8 1
 
4.2%
Hangul
ValueCountFrequency (%)
년 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24
96.0%
Hangul 1
 
4.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 6
25.0%
1 5
20.8%
0 3
12.5%
, 3
12.5%
4 2
 
8.3%
6 1
 
4.2%
9 1
 
4.2%
5 1
 
4.2%
7 1
 
4.2%
8 1
 
4.2%
Hangul
ValueCountFrequency (%)
년 1
100.0%

Unnamed: 6
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing16
Missing (%)72.7%
Memory size308.0 B
2024-03-14T10:47:27.740464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.1666667
Min length2

Characters and Unicode

Total characters25
Distinct characters12
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

Unique6 ?
Unique (%)100.0%

Sample

1st row2012년
2nd row7,829
3rd row51
4th row5,465
5th row300
ValueCountFrequency (%)
2012년 1
16.7%
7,829 1
16.7%
51 1
16.7%
5,465 1
16.7%
300 1
16.7%
2,013 1
16.7%
2024-03-14T10:47:27.972724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 4
16.0%
0 4
16.0%
1 3
12.0%
, 3
12.0%
5 3
12.0%
3 2
8.0%
년 1
 
4.0%
7 1
 
4.0%
8 1
 
4.0%
9 1
 
4.0%
Other values (2) 2
8.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 21
84.0%
Other Punctuation 3
 
12.0%
Other Letter 1
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 4
19.0%
0 4
19.0%
1 3
14.3%
5 3
14.3%
3 2
9.5%
7 1
 
4.8%
8 1
 
4.8%
9 1
 
4.8%
4 1
 
4.8%
6 1
 
4.8%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Other Letter
ValueCountFrequency (%)
년 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24
96.0%
Hangul 1
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 4
16.7%
0 4
16.7%
1 3
12.5%
, 3
12.5%
5 3
12.5%
3 2
8.3%
7 1
 
4.2%
8 1
 
4.2%
9 1
 
4.2%
4 1
 
4.2%
Hangul
ValueCountFrequency (%)
년 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24
96.0%
Hangul 1
 
4.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 4
16.7%
0 4
16.7%
1 3
12.5%
, 3
12.5%
5 3
12.5%
3 2
8.3%
7 1
 
4.2%
8 1
 
4.2%
9 1
 
4.2%
4 1
 
4.2%
Hangul
ValueCountFrequency (%)
년 1
100.0%

Unnamed: 7
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing16
Missing (%)72.7%
Memory size308.0 B
2024-03-14T10:47:28.110289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.1666667
Min length2

Characters and Unicode

Total characters25
Distinct characters11
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

Unique6 ?
Unique (%)100.0%

Sample

1st row2013년
2nd row6,991
3rd row24
4th row5,045
5th row173
ValueCountFrequency (%)
2013년 1
16.7%
6,991 1
16.7%
24 1
16.7%
5,045 1
16.7%
173 1
16.7%
1,749 1
16.7%
2024-03-14T10:47:28.345585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 4
16.0%
, 3
12.0%
9 3
12.0%
4 3
12.0%
2 2
8.0%
0 2
8.0%
3 2
8.0%
5 2
8.0%
7 2
8.0%
년 1
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 21
84.0%
Other Punctuation 3
 
12.0%
Other Letter 1
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4
19.0%
9 3
14.3%
4 3
14.3%
2 2
9.5%
0 2
9.5%
3 2
9.5%
5 2
9.5%
7 2
9.5%
6 1
 
4.8%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Other Letter
ValueCountFrequency (%)
년 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24
96.0%
Hangul 1
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 4
16.7%
, 3
12.5%
9 3
12.5%
4 3
12.5%
2 2
8.3%
0 2
8.3%
3 2
8.3%
5 2
8.3%
7 2
8.3%
6 1
 
4.2%
Hangul
ValueCountFrequency (%)
년 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24
96.0%
Hangul 1
 
4.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 4
16.7%
, 3
12.5%
9 3
12.5%
4 3
12.5%
2 2
8.3%
0 2
8.3%
3 2
8.3%
5 2
8.3%
7 2
8.3%
6 1
 
4.2%
Hangul
ValueCountFrequency (%)
년 1
100.0%

Unnamed: 8
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing16
Missing (%)72.7%
Memory size308.0 B
2024-03-14T10:47:28.469096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.1666667
Min length2

Characters and Unicode

Total characters25
Distinct characters12
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

Unique6 ?
Unique (%)100.0%

Sample

1st row2014년
2nd row8,077
3rd row36
4th row6,385
5th row217
ValueCountFrequency (%)
2014년 1
16.7%
8,077 1
16.7%
36 1
16.7%
6,385 1
16.7%
217 1
16.7%
1,439 1
16.7%
2024-03-14T10:47:28.712793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3
12.0%
, 3
12.0%
7 3
12.0%
3 3
12.0%
2 2
8.0%
0 2
8.0%
4 2
8.0%
8 2
8.0%
6 2
8.0%
년 1
 
4.0%
Other values (2) 2
8.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 21
84.0%
Other Punctuation 3
 
12.0%
Other Letter 1
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3
14.3%
7 3
14.3%
3 3
14.3%
2 2
9.5%
0 2
9.5%
4 2
9.5%
8 2
9.5%
6 2
9.5%
5 1
 
4.8%
9 1
 
4.8%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Other Letter
ValueCountFrequency (%)
년 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24
96.0%
Hangul 1
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3
12.5%
, 3
12.5%
7 3
12.5%
3 3
12.5%
2 2
8.3%
0 2
8.3%
4 2
8.3%
8 2
8.3%
6 2
8.3%
5 1
 
4.2%
Hangul
ValueCountFrequency (%)
년 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24
96.0%
Hangul 1
 
4.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3
12.5%
, 3
12.5%
7 3
12.5%
3 3
12.5%
2 2
8.3%
0 2
8.3%
4 2
8.3%
8 2
8.3%
6 2
8.3%
5 1
 
4.2%
Hangul
ValueCountFrequency (%)
년 1
100.0%

Unnamed: 9
Text

MISSING 

Distinct7
Distinct (%)100.0%
Missing15
Missing (%)68.2%
Memory size308.0 B
2024-03-14T10:47:28.875502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length5
Mean length5.1428571
Min length1

Characters and Unicode

Total characters36
Distinct characters17
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)100.0%

Sample

1st row (‘15. 12월)
2nd row2015년
3rd row7,408
4th row0
5th row5,947
ValueCountFrequency (%)
‘15 1
12.5%
12월 1
12.5%
2015년 1
12.5%
7,408 1
12.5%
0 1
12.5%
5,947 1
12.5%
153 1
12.5%
1,308 1
12.5%
2024-03-14T10:47:29.130197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 5
13.9%
0 4
11.1%
5 4
11.1%
3
8.3%
, 3
8.3%
8 2
 
5.6%
4 2
 
5.6%
7 2
 
5.6%
3 2
 
5.6%
2 2
 
5.6%
Other values (7) 7
19.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 24
66.7%
Other Punctuation 4
 
11.1%
Space Separator 3
 
8.3%
Other Letter 2
 
5.6%
Open Punctuation 1
 
2.8%
Initial Punctuation 1
 
2.8%
Close Punctuation 1
 
2.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 5
20.8%
0 4
16.7%
5 4
16.7%
8 2
 
8.3%
4 2
 
8.3%
7 2
 
8.3%
3 2
 
8.3%
2 2
 
8.3%
9 1
 
4.2%
Other Punctuation
ValueCountFrequency (%)
, 3
75.0%
. 1
 
25.0%
Other Letter
ValueCountFrequency (%)
년 1
50.0%
월 1
50.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 34
94.4%
Hangul 2
 
5.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 5
14.7%
0 4
11.8%
5 4
11.8%
3
8.8%
, 3
8.8%
8 2
 
5.9%
4 2
 
5.9%
7 2
 
5.9%
3 2
 
5.9%
2 2
 
5.9%
Other values (5) 5
14.7%
Hangul
ValueCountFrequency (%)
년 1
50.0%
월 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 33
91.7%
Hangul 2
 
5.6%
Punctuation 1
 
2.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 5
15.2%
0 4
12.1%
5 4
12.1%
3
9.1%
, 3
9.1%
8 2
 
6.1%
4 2
 
6.1%
7 2
 
6.1%
3 2
 
6.1%
2 2
 
6.1%
Other values (4) 4
12.1%
Hangul
ValueCountFrequency (%)
년 1
50.0%
월 1
50.0%
Punctuation
ValueCountFrequency (%)
‘ 1
100.0%

Unnamed: 10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing22
Missing (%)100.0%
Memory size330.0 B

Unnamed: 11
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing22
Missing (%)100.0%
Memory size330.0 B

Correlations

2024-03-14T10:47:29.243882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
천일염 연도별 생산 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9
천일염 연도별 생산 현황1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 11.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 21.0001.0001.0001.0001.000NaNNaNNaNNaNNaN
Unnamed: 31.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 41.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 51.0001.000NaN1.0001.0001.0001.0001.0001.0001.000
Unnamed: 61.0001.000NaN1.0001.0001.0001.0001.0001.0001.000
Unnamed: 71.0001.000NaN1.0001.0001.0001.0001.0001.0001.000
Unnamed: 81.0001.000NaN1.0001.0001.0001.0001.0001.0001.000
Unnamed: 91.0001.000NaN1.0001.0001.0001.0001.0001.0001.000

Missing values

2024-03-14T10:47:24.917428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T10:47:25.075155image/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.
2024-03-14T10:47:25.198273image/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

천일염 연도별 생산 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11
0<NA><NA><NA><NA><NA><NA><NA><NA><NA>(‘15. 12월)<NA><NA>
1시.군생산어가(종사자)염종류염 전생산량(톤)<NA><NA><NA><NA><NA><NA><NA>
2<NA><NA><NA>면 적<NA><NA><NA><NA><NA><NA><NA><NA>
3<NA><NA><NA>(㎡)2010년2011년2012년2013년2014년2015년<NA><NA>
4<NA><NA><NA>3,219,6146,4196,9227,8296,9918,0777,408<NA><NA>
5군산1어가(가족경영 3명)천일염36,95991515124360<NA><NA>
6<NA><NA>(고무장판, 타일)<NA><NA><NA><NA><NA><NA><NA><NA><NA>
7고창18어가(42명)천일염2,585,1854,5004,4705,4655,0456,3855,947<NA><NA>
8<NA><NA>(고무장판, 타일)<NA><NA><NA><NA><NA><NA><NA><NA><NA>
9<NA>1어가천일염19,328180181300173217153<NA><NA>
천일염 연도별 생산 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11
12<NA>(26명)(고무장판, 타일)<NA><NA><NA><NA><NA><NA><NA><NA><NA>
13<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
14<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
15<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
16<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
17<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
18<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
19<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
20<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
21<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

천일염 연도별 생산 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9# duplicates
1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>9
0<NA><NA>(고무장판, 타일)<NA><NA><NA><NA><NA><NA><NA>2