Overview

Dataset statistics

Number of variables3
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory322.3 KiB
Average record size in memory33.0 B

Variable types

DateTime1
Categorical1
Text1

Dataset

Description농가의 일일 영농활동(교육, 시비 작업 등), 생산, 판매 활동 등 기록 관리시스템으로 일자, 달력유형, 표출명등을 제공합니다.
Author충청북도
URLhttps://www.data.go.kr/data/15050311/fileData.do

Alerts

달력유형 is highly imbalanced (95.6%)Imbalance

Reproduction

Analysis started2024-04-20 18:49:31.783367
Analysis finished2024-04-20 18:49:32.497425
Duration0.71 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일자
Date

Distinct9946
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2000-01-02 00:00:00
Maximum2050-12-31 00:00:00
2024-04-21T03:49:32.702918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:49:33.077625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

달력유형
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9909 
3
 
37
1
 
32
2
 
22

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 9909
99.1%
3 37
 
0.4%
1 32
 
0.3%
2 22
 
0.2%

Length

2024-04-21T03:49:33.315950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:49:33.484462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 9909
99.1%
3 37
 
0.4%
1 32
 
0.3%
2 22
 
0.2%

표출명
Text

Distinct9783
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-21T03:49:34.379408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.9525
Min length2

Characters and Unicode

Total characters79525
Distinct characters71
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

Unique9595 ?
Unique (%)96.0%

Sample

1st row20461230
2nd row20460524
3rd row20160229
4th row20490722
5th row20010410
ValueCountFrequency (%)
추석 11
 
0.1%
설날 6
 
0.1%
어린이날 4
 
< 0.1%
대체공휴일 4
 
< 0.1%
광복절 4
 
< 0.1%
기독탄신일 4
 
< 0.1%
삼일절 3
 
< 0.1%
입추 3
 
< 0.1%
동지 3
 
< 0.1%
춘분 3
 
< 0.1%
Other values (9773) 9955
99.6%
2024-04-21T03:49:35.534299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 25056
31.5%
2 18823
23.7%
1 11405
14.3%
3 4977
 
6.3%
4 4826
 
6.1%
5 3021
 
3.8%
6 2814
 
3.5%
9 2797
 
3.5%
8 2793
 
3.5%
7 2760
 
3.5%
Other values (61) 253
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 79272
99.7%
Other Letter 253
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
일 19
 
7.5%
추 16
 
6.3%
석 14
 
5.5%
절 13
 
5.1%
날 12
 
4.7%
신 9
 
3.6%
대 7
 
2.8%
설 7
 
2.8%
탄 7
 
2.8%
소 6
 
2.4%
Other values (51) 143
56.5%
Decimal Number
ValueCountFrequency (%)
0 25056
31.6%
2 18823
23.7%
1 11405
14.4%
3 4977
 
6.3%
4 4826
 
6.1%
5 3021
 
3.8%
6 2814
 
3.5%
9 2797
 
3.5%
8 2793
 
3.5%
7 2760
 
3.5%

Most occurring scripts

ValueCountFrequency (%)
Common 79272
99.7%
Hangul 253
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
일 19
 
7.5%
추 16
 
6.3%
석 14
 
5.5%
절 13
 
5.1%
날 12
 
4.7%
신 9
 
3.6%
대 7
 
2.8%
설 7
 
2.8%
탄 7
 
2.8%
소 6
 
2.4%
Other values (51) 143
56.5%
Common
ValueCountFrequency (%)
0 25056
31.6%
2 18823
23.7%
1 11405
14.4%
3 4977
 
6.3%
4 4826
 
6.1%
5 3021
 
3.8%
6 2814
 
3.5%
9 2797
 
3.5%
8 2793
 
3.5%
7 2760
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 79272
99.7%
Hangul 253
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 25056
31.6%
2 18823
23.7%
1 11405
14.4%
3 4977
 
6.3%
4 4826
 
6.1%
5 3021
 
3.8%
6 2814
 
3.5%
9 2797
 
3.5%
8 2793
 
3.5%
7 2760
 
3.5%
Hangul
ValueCountFrequency (%)
일 19
 
7.5%
추 16
 
6.3%
석 14
 
5.5%
절 13
 
5.1%
날 12
 
4.7%
신 9
 
3.6%
대 7
 
2.8%
설 7
 
2.8%
탄 7
 
2.8%
소 6
 
2.4%
Other values (51) 143
56.5%

Missing values

2024-04-21T03:49:32.139584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T03:49:32.386407image/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

일자달력유형표출명
183352047-01-25020461230
181162046-06-28020460524
79342016-04-06020160229
174262049-08-20020490722
50092001-06-01020010410
143822028-07-05020280513
22432020-11-08020200923
56782003-04-11020030310
116822041-11-26020411103
42822001-01-19020001225
일자달력유형표출명
180552046-04-20020460315
71832007-05-25020070409
135072034-02-09020331221
147012029-05-19020290407
135242034-02-26020340108
137642026-10-26020260916
52922002-03-24020020211
97762036-09-24020360805
62262004-10-30020040917
65172005-07-04020050528