Overview

Dataset statistics

Number of variables6
Number of observations21
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 KiB
Average record size in memory54.3 B

Variable types

Categorical2
Text4

Dataset

Description인천광역시 농업협동조합의 수, 조합원 수, 직원 수, 주요경제사업실적 등에 대한 항목값에 대한 데이터 정보를 제공합니다.
Author인천광역시
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15064997&srcSe=7661IVAWM27C61E190

Alerts

조합별(1) has constant value ""Constant
2019 has unique valuesUnique

Reproduction

Analysis started2024-03-18 05:40:05.300805
Analysis finished2024-03-18 05:40:07.375637
Duration2.07 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

조합별(1)
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
합계
21 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row합계
2nd row합계
3rd row합계
4th row합계
5th row합계

Common Values

ValueCountFrequency (%)
합계 21
100.0%

Length

2024-03-18T14:40:07.464876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T14:40:07.574923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
합계 21
100.0%

실적총괄별(1)
Categorical

Distinct6
Distinct (%)28.6%
Missing0
Missing (%)0.0%
Memory size300.0 B
주요경제사업실적 (백만원)
10 
직원수 (명)
3 
연중여신실적 (백만원)
3 
연말현재예금잔고 (백만원)
3 
조합수 (개)
 
1

Length

Max length14
Median length14
Mean length12.095238
Min length7

Unique

Unique2 ?
Unique (%)9.5%

Sample

1st row조합수 (개)
2nd row조합원수 (명)
3rd row직원수 (명)
4th row직원수 (명)
5th row직원수 (명)

Common Values

ValueCountFrequency (%)
주요경제사업실적 (백만원) 10
47.6%
직원수 (명) 3
 
14.3%
연중여신실적 (백만원) 3
 
14.3%
연말현재예금잔고 (백만원) 3
 
14.3%
조합수 (개) 1
 
4.8%
조합원수 (명) 1
 
4.8%

Length

2024-03-18T14:40:07.727190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T14:40:07.849315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
백만원 16
38.1%
주요경제사업실적 10
23.8%
명 4
 
9.5%
직원수 3
 
7.1%
연중여신실적 3
 
7.1%
연말현재예금잔고 3
 
7.1%
조합수 1
 
2.4%
개 1
 
2.4%
조합원수 1
 
2.4%

실적총괄별(2)
Text

Distinct17
Distinct (%)81.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2024-03-18T14:40:08.000269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
Mean length2.7619048
Min length1

Characters and Unicode

Total characters58
Distinct characters39
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

Unique16 ?
Unique (%)76.2%

Sample

1st row소계
2nd row소계
3rd row소계
4th row남
5th row여
ValueCountFrequency (%)
소계 5
22.7%
남 1
 
4.5%
저축성예금 1
 
4.5%
정책자금 1
 
4.5%
금융자금 1
 
4.5%
이용기타 1
 
4.5%
공제 1
 
4.5%
보험 1
 
4.5%
운송 1
 
4.5%
창고 1
 
4.5%
Other values (8) 8
36.4%
2024-03-18T14:40:08.248492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
소 5
 
8.6%
계 5
 
8.6%
금 5
 
8.6%
매 3
 
5.2%
자 3
 
5.2%
예 2
 
3.4%
구 2
 
3.4%
공 2
 
3.4%
타 1
 
1.7%
제 1
 
1.7%
Other values (29) 29
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 57
98.3%
Space Separator 1
 
1.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
소 5
 
8.8%
계 5
 
8.8%
금 5
 
8.8%
매 3
 
5.3%
자 3
 
5.3%
예 2
 
3.5%
구 2
 
3.5%
공 2
 
3.5%
타 1
 
1.8%
제 1
 
1.8%
Other values (28) 28
49.1%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 57
98.3%
Common 1
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
소 5
 
8.8%
계 5
 
8.8%
금 5
 
8.8%
매 3
 
5.3%
자 3
 
5.3%
예 2
 
3.5%
구 2
 
3.5%
공 2
 
3.5%
타 1
 
1.8%
제 1
 
1.8%
Other values (28) 28
49.1%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 57
98.3%
ASCII 1
 
1.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
소 5
 
8.8%
계 5
 
8.8%
금 5
 
8.8%
매 3
 
5.3%
자 3
 
5.3%
예 2
 
3.5%
구 2
 
3.5%
공 2
 
3.5%
타 1
 
1.8%
제 1
 
1.8%
Other values (28) 28
49.1%
ASCII
ValueCountFrequency (%)
1
100.0%

2017
Text

Distinct19
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
2024-03-18T14:40:08.404855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length4.3333333
Min length1

Characters and Unicode

Total characters91
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)85.7%

Sample

1st row14
2nd row28744
3rd row1554
4th row914
5th row640
ValueCountFrequency (%)
3
 
14.3%
14 1
 
4.8%
76 1
 
4.8%
6526393 1
 
4.8%
10733432 1
 
4.8%
83981 1
 
4.8%
8656331 1
 
4.8%
8740312 1
 
4.8%
12992 1
 
4.8%
21 1
 
4.8%
Other values (9) 9
42.9%
2024-03-18T14:40:08.693001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
14.3%
4 13
14.3%
3 11
12.1%
2 10
11.0%
9 9
9.9%
6 8
8.8%
8 7
7.7%
5 6
6.6%
7 6
6.6%
0 5
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 88
96.7%
Dash Punctuation 3
 
3.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
14.8%
4 13
14.8%
3 11
12.5%
2 10
11.4%
9 9
10.2%
6 8
9.1%
8 7
8.0%
5 6
6.8%
7 6
6.8%
0 5
 
5.7%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 91
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
14.3%
4 13
14.3%
3 11
12.1%
2 10
11.0%
9 9
9.9%
6 8
8.8%
8 7
7.7%
5 6
6.6%
7 6
6.6%
0 5
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 91
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13
14.3%
4 13
14.3%
3 11
12.1%
2 10
11.0%
9 9
9.9%
6 8
8.8%
8 7
7.7%
5 6
6.6%
7 6
6.6%
0 5
 
5.5%

2018
Text

Distinct19
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
2024-03-18T14:40:08.833121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length4.3333333
Min length1

Characters and Unicode

Total characters91
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)85.7%

Sample

1st row14
2nd row28144
3rd row1503
4th row878
5th row625
ValueCountFrequency (%)
3
 
14.3%
14 1
 
4.8%
76 1
 
4.8%
6526393 1
 
4.8%
10733432 1
 
4.8%
83981 1
 
4.8%
8656331 1
 
4.8%
8740312 1
 
4.8%
12992 1
 
4.8%
21 1
 
4.8%
Other values (9) 9
42.9%
2024-03-18T14:40:09.102551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
14.3%
3 12
13.2%
2 11
12.1%
4 10
11.0%
8 9
9.9%
9 8
8.8%
6 8
8.8%
5 6
6.6%
7 6
6.6%
0 5
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 88
96.7%
Dash Punctuation 3
 
3.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
14.8%
3 12
13.6%
2 11
12.5%
4 10
11.4%
8 9
10.2%
9 8
9.1%
6 8
9.1%
5 6
6.8%
7 6
6.8%
0 5
 
5.7%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 91
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
14.3%
3 12
13.2%
2 11
12.1%
4 10
11.0%
8 9
9.9%
9 8
8.8%
6 8
8.8%
5 6
6.6%
7 6
6.6%
0 5
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 91
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13
14.3%
3 12
13.2%
2 11
12.1%
4 10
11.0%
8 9
9.9%
9 8
8.8%
6 8
8.8%
5 6
6.6%
7 6
6.6%
0 5
 
5.5%

2019
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2024-03-18T14:40:09.268196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length4.7142857
Min length1

Characters and Unicode

Total characters99
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
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 row14
2nd row29582
3rd row1755
4th row1007
5th row748
ValueCountFrequency (%)
14 1
 
4.8%
17 1
 
4.8%
10330402 1
 
4.8%
11379875 1
 
4.8%
92261 1
 
4.8%
9300502 1
 
4.8%
9392763 1
 
4.8%
13424 1
 
4.8%
1
 
4.8%
123235 1
 
4.8%
Other values (11) 11
52.4%
2024-03-18T14:40:09.677961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 17
17.2%
1 13
13.1%
0 11
11.1%
3 11
11.1%
9 10
10.1%
5 9
9.1%
7 9
9.1%
4 8
8.1%
8 5
 
5.1%
6 5
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 98
99.0%
Dash Punctuation 1
 
1.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 17
17.3%
1 13
13.3%
0 11
11.2%
3 11
11.2%
9 10
10.2%
5 9
9.2%
7 9
9.2%
4 8
8.2%
8 5
 
5.1%
6 5
 
5.1%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 99
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 17
17.2%
1 13
13.1%
0 11
11.1%
3 11
11.1%
9 10
10.1%
5 9
9.1%
7 9
9.1%
4 8
8.1%
8 5
 
5.1%
6 5
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 99
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 17
17.2%
1 13
13.1%
0 11
11.1%
3 11
11.1%
9 10
10.1%
5 9
9.1%
7 9
9.1%
4 8
8.1%
8 5
 
5.1%
6 5
 
5.1%

Correlations

2024-03-18T14:40:09.771479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
실적총괄별(1)실적총괄별(2)201720182019
실적총괄별(1)1.0000.0001.0001.0001.000
실적총괄별(2)0.0001.0000.7670.7671.000
20171.0000.7671.0001.0001.000
20181.0000.7671.0001.0001.000
20191.0001.0001.0001.0001.000

Missing values

2024-03-18T14:40:07.176237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T14:40:07.318475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

조합별(1)실적총괄별(1)실적총괄별(2)201720182019
0합계조합수 (개)소계141414
1합계조합원수 (명)소계287442814429582
2합계직원수 (명)소계155415031755
3합계직원수 (명)남9148781007
4합계직원수 (명)여640625748
5합계주요경제사업실적 (백만원)판매266214266214261022
6합계주요경제사업실적 (백만원)구매959479594795049
7합계주요경제사업실적 (백만원)마트 매출액--122389
8합계주요경제사업실적 (백만원)생활물자11538411538462
9합계주요경제사업실적 (백만원)가공194819482586
조합별(1)실적총괄별(1)실적총괄별(2)201720182019
11합계주요경제사업실적 (백만원)운송212117
12합계주요경제사업실적 (백만원)보험--123235
13합계주요경제사업실적 (백만원)공제---
14합계주요경제사업실적 (백만원)이용기타129921299213424
15합계연중여신실적 (백만원)소계874031287403129392763
16합계연중여신실적 (백만원)금융자금865633186563319300502
17합계연중여신실적 (백만원)정책자금839818398192261
18합계연말현재예금잔고 (백만원)소계107334321073343211379875
19합계연말현재예금잔고 (백만원)저축성예금6526393652639310330402
20합계연말현재예금잔고 (백만원)요구불예금420703942070391049473