Overview

Dataset statistics

Number of variables5
Number of observations37
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.6 KiB
Average record size in memory43.6 B

Variable types

Text4
Categorical1

Dataset

Description파일 다운로드
AuthorSH공사
URLhttps://data.seoul.go.kr/dataList/OA-12920/F/1/datasetView.do

Reproduction

Analysis started2023-12-11 04:51:03.376369
Analysis finished2023-12-11 04:51:03.792094
Duration0.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

과목
Text

Distinct34
Distinct (%)91.9%
Missing0
Missing (%)0.0%
Memory size428.0 B
2023-12-11T13:51:03.916666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length7.3783784
Min length4

Characters and Unicode

Total characters273
Distinct characters73
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

Unique31 ?
Unique (%)83.8%

Sample

1st row1.유동자산
2nd row - 당좌자산
3rd row - 재고자산
4th row2. 비유동자산
5th row - 투자자산
ValueCountFrequency (%)
18
25.4%
2 4
 
5.6%
3 2
 
2.8%
주택건설사업 2
 
2.8%
4 2
 
2.8%
영업외 2
 
2.8%
1 2
 
2.8%
기타사업 2
 
2.8%
임대사업 2
 
2.8%
매출총이익 1
 
1.4%
Other values (34) 34
47.9%
2023-12-11T13:51:04.312810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
52
19.0%
- 18
 
6.6%
. 15
 
5.5%
자 14
 
5.1%
업 9
 
3.3%
산 9
 
3.3%
익 8
 
2.9%
비 7
 
2.6%
유 6
 
2.2%
사 6
 
2.2%
Other values (63) 129
47.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 173
63.4%
Space Separator 52
 
19.0%
Dash Punctuation 18
 
6.6%
Other Punctuation 15
 
5.5%
Decimal Number 15
 
5.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
자 14
 
8.1%
업 9
 
5.2%
산 9
 
5.2%
익 8
 
4.6%
비 7
 
4.0%
유 6
 
3.5%
사 6
 
3.5%
이 6
 
3.5%
기 5
 
2.9%
계 5
 
2.9%
Other values (53) 98
56.6%
Decimal Number
ValueCountFrequency (%)
1 4
26.7%
2 4
26.7%
4 2
13.3%
3 2
13.3%
5 1
 
6.7%
6 1
 
6.7%
7 1
 
6.7%
Space Separator
ValueCountFrequency (%)
52
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Other Punctuation
ValueCountFrequency (%)
. 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 173
63.4%
Common 100
36.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
자 14
 
8.1%
업 9
 
5.2%
산 9
 
5.2%
익 8
 
4.6%
비 7
 
4.0%
유 6
 
3.5%
사 6
 
3.5%
이 6
 
3.5%
기 5
 
2.9%
계 5
 
2.9%
Other values (53) 98
56.6%
Common
ValueCountFrequency (%)
52
52.0%
- 18
 
18.0%
. 15
 
15.0%
1 4
 
4.0%
2 4
 
4.0%
4 2
 
2.0%
3 2
 
2.0%
5 1
 
1.0%
6 1
 
1.0%
7 1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 173
63.4%
ASCII 100
36.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
52
52.0%
- 18
 
18.0%
. 15
 
15.0%
1 4
 
4.0%
2 4
 
4.0%
4 2
 
2.0%
3 2
 
2.0%
5 1
 
1.0%
6 1
 
1.0%
7 1
 
1.0%
Hangul
ValueCountFrequency (%)
자 14
 
8.1%
업 9
 
5.2%
산 9
 
5.2%
익 8
 
4.6%
비 7
 
4.0%
유 6
 
3.5%
사 6
 
3.5%
이 6
 
3.5%
기 5
 
2.9%
계 5
 
2.9%
Other values (53) 98
56.6%

2019년
Text

Distinct35
Distinct (%)94.6%
Missing0
Missing (%)0.0%
Memory size428.0 B
2023-12-11T13:51:04.566937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.2162162
Min length3

Characters and Unicode

Total characters193
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

Unique33 ?
Unique (%)89.2%

Sample

1st row74733억
2nd row25864억
3rd row48869억
4th row172822억
5th row3542억
ValueCountFrequency (%)
1579억 2
 
5.4%
247555억 2
 
5.4%
74733억 1
 
2.7%
48억 1
 
2.7%
1389억 1
 
2.7%
50억 1
 
2.7%
11461억 1
 
2.7%
2379억 1
 
2.7%
3656억 1
 
2.7%
9305억 1
 
2.7%
Other values (25) 25
67.6%
2023-12-11T13:51:05.007682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
억 37
19.2%
1 22
11.4%
4 20
10.4%
2 19
9.8%
8 19
9.8%
5 18
9.3%
3 16
8.3%
6 12
 
6.2%
7 11
 
5.7%
9 11
 
5.7%
Other values (2) 8
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 154
79.8%
Other Letter 37
 
19.2%
Dash Punctuation 2
 
1.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 22
14.3%
4 20
13.0%
2 19
12.3%
8 19
12.3%
5 18
11.7%
3 16
10.4%
6 12
7.8%
7 11
7.1%
9 11
7.1%
0 6
 
3.9%
Other Letter
ValueCountFrequency (%)
억 37
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 156
80.8%
Hangul 37
 
19.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 22
14.1%
4 20
12.8%
2 19
12.2%
8 19
12.2%
5 18
11.5%
3 16
10.3%
6 12
7.7%
7 11
7.1%
9 11
7.1%
0 6
 
3.8%
Hangul
ValueCountFrequency (%)
억 37
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 156
80.8%
Hangul 37
 
19.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
억 37
100.0%
ASCII
ValueCountFrequency (%)
1 22
14.1%
4 20
12.8%
2 19
12.2%
8 19
12.2%
5 18
11.5%
3 16
10.3%
6 12
7.7%
7 11
7.1%
9 11
7.1%
0 6
 
3.8%

2018년
Text

Distinct35
Distinct (%)94.6%
Missing0
Missing (%)0.0%
Memory size428.0 B
2023-12-11T13:51:05.283653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.2972973
Min length3

Characters and Unicode

Total characters196
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

Unique33 ?
Unique (%)89.2%

Sample

1st row67093억
2nd row18435억
3rd row48658억
4th row160897억
5th row2066억
ValueCountFrequency (%)
1645억 2
 
5.4%
227990억 2
 
5.4%
67093억 1
 
2.7%
32억 1
 
2.7%
1265억 1
 
2.7%
48억 1
 
2.7%
19347억 1
 
2.7%
4426억 1
 
2.7%
10019억 1
 
2.7%
15059억 1
 
2.7%
Other values (25) 25
67.6%
2023-12-11T13:51:05.726734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
억 37
18.9%
1 20
10.2%
4 20
10.2%
2 19
9.7%
0 17
8.7%
5 15
7.7%
6 14
 
7.1%
3 14
 
7.1%
7 13
 
6.6%
8 13
 
6.6%
Other values (2) 14
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 157
80.1%
Other Letter 37
 
18.9%
Dash Punctuation 2
 
1.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 20
12.7%
4 20
12.7%
2 19
12.1%
0 17
10.8%
5 15
9.6%
6 14
8.9%
3 14
8.9%
7 13
8.3%
8 13
8.3%
9 12
7.6%
Other Letter
ValueCountFrequency (%)
억 37
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 159
81.1%
Hangul 37
 
18.9%

Most frequent character per script

Common
ValueCountFrequency (%)
1 20
12.6%
4 20
12.6%
2 19
11.9%
0 17
10.7%
5 15
9.4%
6 14
8.8%
3 14
8.8%
7 13
8.2%
8 13
8.2%
9 12
7.5%
Hangul
ValueCountFrequency (%)
억 37
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 159
81.1%
Hangul 37
 
18.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
억 37
100.0%
ASCII
ValueCountFrequency (%)
1 20
12.6%
4 20
12.6%
2 19
11.9%
0 17
10.7%
5 15
9.4%
6 14
8.8%
3 14
8.8%
7 13
8.2%
8 13
8.2%
9 12
7.5%

증감
Text

Distinct35
Distinct (%)94.6%
Missing0
Missing (%)0.0%
Memory size428.0 B
2023-12-11T13:51:05.993508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.8108108
Min length2

Characters and Unicode

Total characters178
Distinct characters13
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

Unique33 ?
Unique (%)89.2%

Sample

1st row7640억
2nd row7429억
3rd row211억
4th row11925억
5th row1476억
ValueCountFrequency (%)
66억 2
 
5.4%
19565억 2
 
5.4%
7640억 1
 
2.7%
16억 1
 
2.7%
124억 1
 
2.7%
2억 1
 
2.7%
7886억 1
 
2.7%
2047억 1
 
2.7%
6363억 1
 
2.7%
5754억 1
 
2.7%
Other values (25) 25
67.6%
2023-12-11T13:51:06.427394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
억 37
20.8%
1 24
13.5%
4 17
9.6%
- 14
 
7.9%
6 14
 
7.9%
5 13
 
7.3%
9 11
 
6.2%
7 11
 
6.2%
2 10
 
5.6%
8 10
 
5.6%
Other values (3) 17
9.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 123
69.1%
Other Letter 37
 
20.8%
Dash Punctuation 14
 
7.9%
Space Separator 4
 
2.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 24
19.5%
4 17
13.8%
6 14
11.4%
5 13
10.6%
9 11
8.9%
7 11
8.9%
2 10
8.1%
8 10
8.1%
3 7
 
5.7%
0 6
 
4.9%
Other Letter
ValueCountFrequency (%)
억 37
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 141
79.2%
Hangul 37
 
20.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 24
17.0%
4 17
12.1%
- 14
9.9%
6 14
9.9%
5 13
9.2%
9 11
7.8%
7 11
7.8%
2 10
7.1%
8 10
7.1%
3 7
 
5.0%
Other values (2) 10
7.1%
Hangul
ValueCountFrequency (%)
억 37
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 141
79.2%
Hangul 37
 
20.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
억 37
100.0%
ASCII
ValueCountFrequency (%)
1 24
17.0%
4 17
12.1%
- 14
9.9%
6 14
9.9%
5 13
9.2%
9 11
7.8%
7 11
7.8%
2 10
7.1%
8 10
7.1%
3 7
 
5.0%
Other values (2) 10
7.1%

비고
Categorical

Distinct2
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size428.0 B
손익계산서
19 
재무상태표 [요약]
18 

Length

Max length10
Median length5
Mean length7.4324324
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row재무상태표 [요약]
2nd row재무상태표 [요약]
3rd row재무상태표 [요약]
4th row재무상태표 [요약]
5th row재무상태표 [요약]

Common Values

ValueCountFrequency (%)
손익계산서 19
51.4%
재무상태표 [요약] 18
48.6%

Length

2023-12-11T13:51:06.618427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T13:51:06.744225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
손익계산서 19
34.5%
재무상태표 18
32.7%
요약 18
32.7%

Correlations

2023-12-11T13:51:06.841925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과목2019년2018년증감비고
과목1.0000.9430.9430.9431.000
2019년0.9431.0001.0001.0001.000
2018년0.9431.0001.0001.0001.000
증감0.9431.0001.0001.0001.000
비고1.0001.0001.0001.0001.000

Missing values

2023-12-11T13:51:03.640651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T13:51:03.744343image/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

과목2019년2018년증감비고
01.유동자산74733억67093억7640억재무상태표 [요약]
1- 당좌자산25864억18435억7429억재무상태표 [요약]
2- 재고자산48869억48658억211억재무상태표 [요약]
32. 비유동자산172822억160897억11925억재무상태표 [요약]
4- 투자자산3542억2066억1476억재무상태표 [요약]
5- 유형자산162826억154397억8429억재무상태표 [요약]
6- 무형자산43억42억1억재무상태표 [요약]
7- 기타비유동자산6411억4392억2019억재무상태표 [요약]
8자산합계247555억227990억19565억재무상태표 [요약]
91. 유동부채43268억34517억8751억재무상태표 [요약]
과목2019년2018년증감비고
27- 기타사업48억32억16억손익계산서
283. 매출총이익2113억2288억-175억손익계산서
29- 판매비와 관리비885억1028억-143억손익계산서
304. 영업이익1228억1260억-32억손익계산서
31- 영업외 수익840억725억115억손익계산서
32- 영업외 비용489억340억149억손익계산서
335. 경상이익1579억1645억-66억손익계산서
346. 세전순이익1579억1645억-66억손익계산서
35- 법인세비용485억404억81억손익계산서
367. 당기순이익1094억1241억-147억손익계산서