Overview

Dataset statistics

Number of variables4
Number of observations48
Missing cells6
Missing cells (%)3.1%
Duplicate rows1
Duplicate rows (%)2.1%
Total size in memory1.6 KiB
Average record size in memory34.8 B

Variable types

Unsupported2
Categorical1
Text1

Alerts

Dataset has 1 (2.1%) duplicate rowsDuplicates
도유림 조림 현황 has 2 (4.2%) missing valuesMissing
Unnamed: 2 has 2 (4.2%) missing valuesMissing
Unnamed: 3 has 2 (4.2%) 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 02:10:33.539584
Analysis finished2024-03-14 02:10:33.949547
Duration0.41 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

도유림 조림 현황
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2
Missing (%)4.2%
Memory size516.0 B

Unnamed: 1
Categorical

Distinct20
Distinct (%)41.7%
Missing0
Missing (%)0.0%
Memory size516.0 B
진안군 백운면 신암리 산1
8 
완주군 동상면 대아리 산1-2
6 
진안군 백운면 신암리 산1-11
6 
장수군 장계면 명덕리 산154-1
4 
<NA>
3 
Other values (15)
21 

Length

Max length21
Median length18
Mean length15.9375
Min length4

Unique

Unique9 ?
Unique (%)18.8%

Sample

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

Common Values

ValueCountFrequency (%)
진안군 백운면 신암리 산1 8
16.7%
완주군 동상면 대아리 산1-2 6
12.5%
진안군 백운면 신암리 산1-11 6
12.5%
장수군 장계면 명덕리 산154-1 4
 
8.3%
<NA> 3
 
6.2%
완주군 운주면 고당리 산30 2
 
4.2%
진안군 백운면 신암리 산1, 산1-11 2
 
4.2%
진안군 백운면 노촌리 산1 2
 
4.2%
장수군 장계면 명덕리 산154-93 2
 
4.2%
진안군 백운면 신암리 산1외 1필 2
 
4.2%
Other values (10) 11
22.9%

Length

2024-03-14T11:10:34.048012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
진안군 22
 
11.4%
백운면 22
 
11.4%
신암리 18
 
9.3%
산1 12
 
6.2%
완주군 11
 
5.7%
산1-11 8
 
4.1%
장계면 7
 
3.6%
장수군 7
 
3.6%
명덕리 7
 
3.6%
동상면 7
 
3.6%
Other values (35) 72
37.3%

Unnamed: 2
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2
Missing (%)4.2%
Memory size516.0 B

Unnamed: 3
Text

MISSING 

Distinct43
Distinct (%)93.5%
Missing2
Missing (%)4.2%
Memory size516.0 B
2024-03-14T11:10:34.310498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length9.4782609
Min length4

Characters and Unicode

Total characters436
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

Unique40 ?
Unique (%)87.0%

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
 
4.2%
3.15~4.23 2
 
4.2%
3.26~4.24 2
 
4.2%
9.23~10.22 1
 
2.1%
3.25~4.23 1
 
2.1%
ha 1
 
2.1%
11.1~12.11 1
 
2.1%
03.08~04.27 1
 
2.1%
3.12~4.21 1
 
2.1%
3.17~4.8 1
 
2.1%
Other values (35) 35
72.9%
2024-03-14T11:10:34.824710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 88
20.2%
1 77
17.7%
2 47
10.8%
~ 44
10.1%
0 40
9.2%
3 38
8.7%
4 31
 
7.1%
5 17
 
3.9%
6 13
 
3.0%
8 10
 
2.3%
Other values (14) 31
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 290
66.5%
Other Punctuation 89
 
20.4%
Math Symbol 44
 
10.1%
Other Letter 6
 
1.4%
Space Separator 3
 
0.7%
Lowercase Letter 2
 
0.5%
Open Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 77
26.6%
2 47
16.2%
0 40
13.8%
3 38
13.1%
4 31
10.7%
5 17
 
5.9%
6 13
 
4.5%
8 10
 
3.4%
9 10
 
3.4%
7 7
 
2.4%
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 (%)
. 88
98.9%
: 1
 
1.1%
Lowercase Letter
ValueCountFrequency (%)
a 1
50.0%
h 1
50.0%
Math Symbol
ValueCountFrequency (%)
~ 44
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 428
98.2%
Hangul 6
 
1.4%
Latin 2
 
0.5%

Most frequent character per script

Common
ValueCountFrequency (%)
. 88
20.6%
1 77
18.0%
2 47
11.0%
~ 44
10.3%
0 40
9.3%
3 38
8.9%
4 31
 
7.2%
5 17
 
4.0%
6 13
 
3.0%
8 10
 
2.3%
Other values (6) 23
 
5.4%
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%
Latin
ValueCountFrequency (%)
a 1
50.0%
h 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 430
98.6%
Hangul 6
 
1.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 88
20.5%
1 77
17.9%
2 47
10.9%
~ 44
10.2%
0 40
9.3%
3 38
8.8%
4 31
 
7.2%
5 17
 
4.0%
6 13
 
3.0%
8 10
 
2.3%
Other values (8) 25
 
5.8%
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

2024-03-14T11:10:34.897756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 1Unnamed: 3
Unnamed: 11.0000.897
Unnamed: 30.8971.000

Missing values

2024-03-14T11:10:33.664702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T11:10:33.760493image/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.
2024-03-14T11:10:33.863740image/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>369.3<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
382013진안군 백운면 신암리 산10.510.8~11.6
392013진안군 백운면 신암리 산1-1123.29~4.28
402014진안군 백운면 신암리 산123.83.15~4.23
412014진안군 백운면 신암리 산113.14~6.11
422014진안군 백운면 신암리 산10.29.25~10.18
432015진안군 백운면 신암리 산1외 1필103.25~4.23
442015장수군 장계면 명덕리 산 154-133.26~4.24
452015진안군 백운면 노촌리 산153.26~4.24
462015진안군 백운면 신암리 산1-1159.23~10.22
472016진안군 백운면 신암리 산1외 1필203.25~5.8

Duplicate rows

Most frequently occurring

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