Overview

Dataset statistics

Number of variables4
Number of observations42
Missing cells9
Missing cells (%)5.4%
Duplicate rows1
Duplicate rows (%)2.4%
Total size in memory1.4 KiB
Average record size in memory35.1 B

Variable types

Unsupported2
Categorical1
Text1

Alerts

Dataset has 1 (2.4%) duplicate rowsDuplicates
도유림 조림 현황 has 5 (11.9%) missing valuesMissing
Unnamed: 2 has 2 (4.8%) missing valuesMissing
Unnamed: 3 has 2 (4.8%) missing valuesMissing
도유림 조림 현황 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 2 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-14 00:07:45.953861
Analysis finished2024-03-14 00:07:46.502835
Duration0.55 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

도유림 조림 현황
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5
Missing (%)11.9%
Memory size468.0 B

Unnamed: 1
Categorical

Distinct18
Distinct (%)42.9%
Missing0
Missing (%)0.0%
Memory size468.0 B
<NA>
6 
완주군 동상면 대아리 산1-2
6 
진안군 백운면 신암리 산1
5 
진안군 백운면 신암리 산1-11
5 
장수군 장계면 명덕리 산154-1
4 
Other values (13)
16 

Length

Max length21
Median length17
Mean length14.952381
Min length4

Unique

Unique10 ?
Unique (%)23.8%

Sample

1st row<NA>
2nd row<NA>
3rd row위 치
4th row<NA>
5th row장수군 장계면 명덕리 산154-1

Common Values

ValueCountFrequency (%)
<NA> 6
14.3%
완주군 동상면 대아리 산1-2 6
14.3%
진안군 백운면 신암리 산1 5
11.9%
진안군 백운면 신암리 산1-11 5
11.9%
장수군 장계면 명덕리 산154-1 4
9.5%
장수군 장계면 명덕리 산154-93 2
 
4.8%
완주군 운주면 고당리 산30 2
 
4.8%
진안군 백운면 신암리 산1, 산1-11 2
 
4.8%
완주군 소양면 신촌리 산18-1외 2필 1
 
2.4%
진안군 백운면 노촌리 산1외 1필 1
 
2.4%
Other values (8) 8
19.0%

Length

2024-03-14T09:07:46.562327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
진안군 15
 
9.6%
백운면 15
 
9.6%
신암리 12
 
7.7%
완주군 10
 
6.4%
산1 8
 
5.1%
동상면 7
 
4.5%
산1-11 7
 
4.5%
na 6
 
3.8%
대아리 6
 
3.8%
산1-2 6
 
3.8%
Other values (33) 64
41.0%

Unnamed: 2
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2
Missing (%)4.8%
Memory size468.0 B

Unnamed: 3
Text

MISSING 

Distinct38
Distinct (%)95.0%
Missing2
Missing (%)4.8%
Memory size468.0 B
2024-03-14T09:07:46.733605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length9.55
Min length4

Characters and Unicode

Total characters382
Distinct characters24
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

Unique36 ?
Unique (%)90.0%

Sample

1st row (단위 : ha)
2nd row사업기간
3rd row10.22~11.20
4th row2.26~4.16
5th row2.28~4.19
ValueCountFrequency (%)
03.30~05.16 2
 
4.8%
3.15~4.23 2
 
4.8%
10.26~11.23 1
 
2.4%
3.14~6.11 1
 
2.4%
03.31~05.29 1
 
2.4%
4.6~4.27 1
 
2.4%
11.1~12.11 1
 
2.4%
3.12~4.21 1
 
2.4%
3.17~4.8 1
 
2.4%
10.05~10.21 1
 
2.4%
Other values (30) 30
71.4%
2024-03-14T09:07:47.038726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 76
19.9%
1 75
19.6%
0 38
9.9%
~ 38
9.9%
2 36
9.4%
3 32
8.4%
4 24
 
6.3%
5 14
 
3.7%
6 10
 
2.6%
8 9
 
2.4%
Other values (14) 30
 
7.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 254
66.5%
Other Punctuation 77
 
20.2%
Math Symbol 38
 
9.9%
Other Letter 6
 
1.6%
Space Separator 3
 
0.8%
Lowercase Letter 2
 
0.5%
Open Punctuation 1
 
0.3%
Close Punctuation 1
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 75
29.5%
0 38
15.0%
2 36
14.2%
3 32
12.6%
4 24
 
9.4%
5 14
 
5.5%
6 10
 
3.9%
8 9
 
3.5%
9 9
 
3.5%
7 7
 
2.8%
Other Letter
ValueCountFrequency (%)
단 1
16.7%
위 1
16.7%
간 1
16.7%
기 1
16.7%
업 1
16.7%
사 1
16.7%
Other Punctuation
ValueCountFrequency (%)
. 76
98.7%
: 1
 
1.3%
Lowercase Letter
ValueCountFrequency (%)
a 1
50.0%
h 1
50.0%
Math Symbol
ValueCountFrequency (%)
~ 38
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 374
97.9%
Hangul 6
 
1.6%
Latin 2
 
0.5%

Most frequent character per script

Common
ValueCountFrequency (%)
. 76
20.3%
1 75
20.1%
0 38
10.2%
~ 38
10.2%
2 36
9.6%
3 32
8.6%
4 24
 
6.4%
5 14
 
3.7%
6 10
 
2.7%
8 9
 
2.4%
Other values (6) 22
 
5.9%
Hangul
ValueCountFrequency (%)
단 1
16.7%
위 1
16.7%
간 1
16.7%
기 1
16.7%
업 1
16.7%
사 1
16.7%
Latin
ValueCountFrequency (%)
a 1
50.0%
h 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 376
98.4%
Hangul 6
 
1.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 76
20.2%
1 75
19.9%
0 38
10.1%
~ 38
10.1%
2 36
9.6%
3 32
8.5%
4 24
 
6.4%
5 14
 
3.7%
6 10
 
2.7%
8 9
 
2.4%
Other values (8) 24
 
6.4%
Hangul
ValueCountFrequency (%)
단 1
16.7%
위 1
16.7%
간 1
16.7%
기 1
16.7%
업 1
16.7%
사 1
16.7%

Correlations

2024-03-14T09:07:47.123170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 1Unnamed: 3
Unnamed: 11.0000.987
Unnamed: 30.9871.000

Missing values

2024-03-14T09:07:46.075663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T09:07:46.372138image/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.
2024-03-14T09:07:46.449859image/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

도유림 조림 현황Unnamed: 1Unnamed: 2Unnamed: 3
0NaN<NA>NaN<NA>
1NaN<NA>NaN(단위 : ha)
2시행년도위 치사업량사업기간
3합계<NA>322.3<NA>
42001장수군 장계면 명덕리 산154-12.410.22~11.20
52001장수군 장계면 명덕리 산154-1152.26~4.16
62001완주군 소양면 신촌리 산18-1외 2필102.28~4.19
72001진안군 백운면 신암리 산153.2~4.17
82002장수군 장계면 명덕리 산154-1123.15~4.23
92002순창군 쌍치면 금성리 산434.610.23~11.22
도유림 조림 현황Unnamed: 1Unnamed: 2Unnamed: 3
322012진안군 백운면 신암리 산11503.13~04.23
332012완주군 동상면 대아리 산1-21003.14~06.11
342012진안군 백운면 신암리 산1, 산1-111003.08~04.27
352012완주군 동상면 대아리 산1-2510.19~11.08
362013진안군 백운면 신암리 산1104.22~5.20
37NaN<NA>0.510.8~11.6
382013진안군 백운면 신암리 산1-1123.29~4.28
392014진안군 백운면 신암리 산1253.15~4.23
40NaN<NA>13.14~6.11
41NaN<NA>0.29.25~10.18

Duplicate rows

Most frequently occurring

Unnamed: 1Unnamed: 3# duplicates
0<NA><NA>2