Overview

Dataset statistics

Number of variables4
Number of observations38
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 KiB
Average record size in memory37.5 B

Variable types

Numeric2
Categorical1
Text1

Reproduction

Analysis started2024-03-14 00:07:43.712536
Analysis finished2024-03-14 00:07:44.238291
Duration0.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시행년도
Real number (ℝ)

Distinct14
Distinct (%)36.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2007.4474
Minimum2001
Maximum2014
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size474.0 B
2024-03-14T09:07:44.283858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2001
5-th percentile2001
Q12004
median2007
Q32011.75
95-th percentile2014
Maximum2014
Range13
Interquartile range (IQR)7.75

Descriptive statistics

Standard deviation4.3102478
Coefficient of variation (CV)0.0021471287
Kurtosis-1.3490989
Mean2007.4474
Median Absolute Deviation (MAD)4
Skewness0.04169776
Sum76283
Variance18.578236
MonotonicityIncreasing
2024-03-14T09:07:44.392361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
2001 4
10.5%
2004 4
10.5%
2006 4
10.5%
2012 4
10.5%
2007 3
7.9%
2011 3
7.9%
2013 3
7.9%
2014 3
7.9%
2002 2
 
5.3%
2003 2
 
5.3%
Other values (4) 6
15.8%
ValueCountFrequency (%)
2001 4
10.5%
2002 2
5.3%
2003 2
5.3%
2004 4
10.5%
2005 2
5.3%
2006 4
10.5%
2007 3
7.9%
2008 1
 
2.6%
2009 2
5.3%
2010 1
 
2.6%
ValueCountFrequency (%)
2014 3
7.9%
2013 3
7.9%
2012 4
10.5%
2011 3
7.9%
2010 1
 
2.6%
2009 2
5.3%
2008 1
 
2.6%
2007 3
7.9%
2006 4
10.5%
2005 2
5.3%

위 치
Categorical

Distinct16
Distinct (%)42.1%
Missing0
Missing (%)0.0%
Memory size436.0 B
진안군 백운면 신암리 산1
8 
완주군 동상면 대아리 산1-2
6 
진안군 백운면 신암리 산1-11
5 
장수군 장계면 명덕리 산154-1
4 
장수군 장계면 명덕리 산154-93
2 
Other values (11)
13 

Length

Max length21
Median length18
Mean length16.894737
Min length14

Unique

Unique9 ?
Unique (%)23.7%

Sample

1st row장수군 장계면 명덕리 산154-1
2nd row장수군 장계면 명덕리 산154-1
3rd row완주군 소양면 신촌리 산18-1외 2필
4th row진안군 백운면 신암리 산1
5th row장수군 장계면 명덕리 산154-1

Common Values

ValueCountFrequency (%)
진안군 백운면 신암리 산1 8
21.1%
완주군 동상면 대아리 산1-2 6
15.8%
진안군 백운면 신암리 산1-11 5
13.2%
장수군 장계면 명덕리 산154-1 4
10.5%
장수군 장계면 명덕리 산154-93 2
 
5.3%
완주군 운주면 고당리 산30 2
 
5.3%
진안군 백운면 신암리 산1, 산1-11 2
 
5.3%
완주군 소양면 신촌리 산18-1외 2필 1
 
2.6%
순창군 쌍치면 금성리 산43 1
 
2.6%
완주군 동상면 사봉리 산144-2 1
 
2.6%
Other values (6) 6
15.8%

Length

2024-03-14T09:07:44.502965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
진안군 18
 
11.2%
백운면 18
 
11.2%
신암리 15
 
9.4%
산1 11
 
6.9%
완주군 10
 
6.2%
동상면 7
 
4.4%
산1-11 7
 
4.4%
대아리 6
 
3.8%
산1-2 6
 
3.8%
장수군 6
 
3.8%
Other values (30) 56
35.0%

사업량
Real number (ℝ)

Distinct19
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.4815789
Minimum0.2
Maximum25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size474.0 B
2024-03-14T09:07:44.618657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.2
5-th percentile0.585
Q13
median10
Q312.15
95-th percentile20
Maximum25
Range24.8
Interquartile range (IQR)9.15

Descriptive statistics

Standard deviation6.5424128
Coefficient of variation (CV)0.77136732
Kurtosis-0.40475307
Mean8.4815789
Median Absolute Deviation (MAD)5.2
Skewness0.6095611
Sum322.3
Variance42.803165
MonotonicityNot monotonic
2024-03-14T09:07:44.705637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
10.0 9
23.7%
5.0 4
10.5%
15.0 4
10.5%
3.0 3
 
7.9%
1.0 2
 
5.3%
20.0 2
 
5.3%
2.0 2
 
5.3%
2.4 1
 
2.6%
0.2 1
 
2.6%
25.0 1
 
2.6%
Other values (9) 9
23.7%
ValueCountFrequency (%)
0.2 1
 
2.6%
0.5 1
 
2.6%
0.6 1
 
2.6%
0.8 1
 
2.6%
1.0 2
5.3%
2.0 2
5.3%
2.4 1
 
2.6%
3.0 3
7.9%
4.0 1
 
2.6%
4.6 1
 
2.6%
ValueCountFrequency (%)
25.0 1
 
2.6%
20.0 2
 
5.3%
19.2 1
 
2.6%
15.8 1
 
2.6%
15.0 4
10.5%
12.2 1
 
2.6%
12.0 1
 
2.6%
10.0 9
23.7%
5.0 4
10.5%
4.6 1
 
2.6%

사업기간
Text

Distinct36
Distinct (%)94.7%
Missing0
Missing (%)0.0%
Memory size436.0 B
2024-03-14T09:07:44.883742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length9.6842105
Min length8

Characters and Unicode

Total characters368
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)89.5%

Sample

1st row10.22~11.20
2nd row2.26~4.16
3rd row2.28~4.19
4th row3.2~4.17
5th row3.15~4.23
ValueCountFrequency (%)
3.15~4.23 2
 
5.3%
03.30~05.16 2
 
5.3%
03.31~05.29 1
 
2.6%
10.22~11.20 1
 
2.6%
03.13~04.23 1
 
2.6%
3.12~4.21 1
 
2.6%
3.17~4.8 1
 
2.6%
10.05~10.21 1
 
2.6%
04.12~05.04 1
 
2.6%
03.14~06.11 1
 
2.6%
Other values (26) 26
68.4%
2024-03-14T09:07:45.177130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 76
20.7%
1 75
20.4%
~ 38
10.3%
0 38
10.3%
2 36
9.8%
3 32
8.7%
4 24
 
6.5%
5 14
 
3.8%
6 10
 
2.7%
9 9
 
2.4%
Other values (2) 16
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 254
69.0%
Other Punctuation 76
 
20.7%
Math Symbol 38
 
10.3%

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%
9 9
 
3.5%
8 9
 
3.5%
7 7
 
2.8%
Other Punctuation
ValueCountFrequency (%)
. 76
100.0%
Math Symbol
ValueCountFrequency (%)
~ 38
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 368
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 76
20.7%
1 75
20.4%
~ 38
10.3%
0 38
10.3%
2 36
9.8%
3 32
8.7%
4 24
 
6.5%
5 14
 
3.8%
6 10
 
2.7%
9 9
 
2.4%
Other values (2) 16
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 368
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 76
20.7%
1 75
20.4%
~ 38
10.3%
0 38
10.3%
2 36
9.8%
3 32
8.7%
4 24
 
6.5%
5 14
 
3.8%
6 10
 
2.7%
9 9
 
2.4%
Other values (2) 16
 
4.3%

Interactions

2024-03-14T09:07:44.008298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:07:43.847299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:07:44.072379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:07:43.926508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T09:07:45.248134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시행년도위 치사업량사업기간
시행년도1.0000.8330.0000.956
위 치0.8331.0000.0000.974
사업량0.0000.0001.0000.000
사업기간0.9560.9740.0001.000
2024-03-14T09:07:45.323172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시행년도사업량위 치
시행년도1.000-0.2090.421
사업량-0.2091.0000.000
위 치0.4210.0001.000

Missing values

2024-03-14T09:07:44.153591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T09:07:44.213713image/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

시행년도위 치사업량사업기간
02001장수군 장계면 명덕리 산154-12.410.22~11.20
12001장수군 장계면 명덕리 산154-115.02.26~4.16
22001완주군 소양면 신촌리 산18-1외 2필10.02.28~4.19
32001진안군 백운면 신암리 산15.03.2~4.17
42002장수군 장계면 명덕리 산154-112.03.15~4.23
52002순창군 쌍치면 금성리 산434.610.23~11.22
62003진안군 백운면 신암리 산1-1110.03.17~4.14
72003장수군 장계면 명덕리 산154-9312.210.10~11.8
82004완주군 운주면 고당리 산3010.02.9~4.10
92004진안군 백운면 신암리 산1-1120.02.9~4.17
시행년도위 치사업량사업기간
282012진안군 백운면 신암리 산115.003.13~04.23
292012완주군 동상면 대아리 산1-210.003.14~06.11
302012진안군 백운면 신암리 산1, 산1-1110.003.08~04.27
312012완주군 동상면 대아리 산1-25.010.19~11.08
322013진안군 백운면 신암리 산110.04.22~5.20
332013진안군 백운면 신암리 산10.510.8~11.6
342013진안군 백운면 신암리 산1-112.03.29~4.28
352014진안군 백운면 신암리 산125.03.15~4.23
362014진안군 백운면 신암리 산11.03.14~6.11
372014진안군 백운면 신암리 산10.29.25~10.18