Overview

Dataset statistics

Number of variables4
Number of observations35
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 KiB
Average record size in memory37.8 B

Variable types

Numeric2
Categorical1
Text1

Reproduction

Analysis started2024-03-14 00:33:32.879096
Analysis finished2024-03-14 00:33:33.411583
Duration0.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시행년도
Real number (ℝ)

Distinct13
Distinct (%)37.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2006.8857
Minimum2001
Maximum2013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2024-03-14T09:33:33.450717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2001
5-th percentile2001
Q12004
median2006
Q32011
95-th percentile2013
Maximum2013
Range12
Interquartile range (IQR)7

Descriptive statistics

Standard deviation4.0130041
Coefficient of variation (CV)0.0019996176
Kurtosis-1.3050494
Mean2006.8857
Median Absolute Deviation (MAD)3
Skewness0.09739735
Sum70241
Variance16.104202
MonotonicityIncreasing
2024-03-14T09:33:33.539364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
2001 4
11.4%
2004 4
11.4%
2006 4
11.4%
2012 4
11.4%
2007 3
8.6%
2011 3
8.6%
2013 3
8.6%
2002 2
5.7%
2003 2
5.7%
2005 2
5.7%
Other values (3) 4
11.4%
ValueCountFrequency (%)
2001 4
11.4%
2002 2
5.7%
2003 2
5.7%
2004 4
11.4%
2005 2
5.7%
2006 4
11.4%
2007 3
8.6%
2008 1
 
2.9%
2009 2
5.7%
2010 1
 
2.9%
ValueCountFrequency (%)
2013 3
8.6%
2012 4
11.4%
2011 3
8.6%
2010 1
 
2.9%
2009 2
5.7%
2008 1
 
2.9%
2007 3
8.6%
2006 4
11.4%
2005 2
5.7%
2004 4
11.4%

위 치
Categorical

Distinct16
Distinct (%)45.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
완주군 동상면 대아리 산1-2
6 
진안군 백운면 신암리 산1
5 
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 length17.142857
Min length14

Unique

Unique9 ?
Unique (%)25.7%

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 (%)
완주군 동상면 대아리 산1-2 6
17.1%
진안군 백운면 신암리 산1 5
14.3%
진안군 백운면 신암리 산1-11 5
14.3%
장수군 장계면 명덕리 산154-1 4
11.4%
장수군 장계면 명덕리 산154-93 2
 
5.7%
완주군 운주면 고당리 산30 2
 
5.7%
진안군 백운면 신암리 산1, 산1-11 2
 
5.7%
완주군 소양면 신촌리 산18-1외 2필 1
 
2.9%
순창군 쌍치면 금성리 산43 1
 
2.9%
완주군 동상면 사봉리 산144-2 1
 
2.9%
Other values (6) 6
17.1%

Length

2024-03-14T09:33:33.638999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
진안군 15
 
10.1%
백운면 15
 
10.1%
신암리 12
 
8.1%
완주군 10
 
6.8%
산1 8
 
5.4%
동상면 7
 
4.7%
산1-11 7
 
4.7%
대아리 6
 
4.1%
산1-2 6
 
4.1%
장수군 6
 
4.1%
Other values (30) 56
37.8%

사업량
Real number (ℝ)

Distinct17
Distinct (%)48.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.46
Minimum0.5
Maximum20
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2024-03-14T09:33:33.735025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.5
5-th percentile0.74
Q13
median10
Q312.1
95-th percentile19.44
Maximum20
Range19.5
Interquartile range (IQR)9.1

Descriptive statistics

Standard deviation5.9068355
Coefficient of variation (CV)0.69820751
Kurtosis-0.90702304
Mean8.46
Median Absolute Deviation (MAD)5
Skewness0.38442701
Sum296.1
Variance34.890706
MonotonicityNot monotonic
2024-03-14T09:33:33.824329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
10.0 9
25.7%
5.0 4
11.4%
15.0 4
11.4%
3.0 3
 
8.6%
20.0 2
 
5.7%
2.0 2
 
5.7%
0.8 1
 
2.9%
0.5 1
 
2.9%
0.6 1
 
2.9%
4.0 1
 
2.9%
Other values (7) 7
20.0%
ValueCountFrequency (%)
0.5 1
 
2.9%
0.6 1
 
2.9%
0.8 1
 
2.9%
1.0 1
 
2.9%
2.0 2
5.7%
2.4 1
 
2.9%
3.0 3
8.6%
4.0 1
 
2.9%
4.6 1
 
2.9%
5.0 4
11.4%
ValueCountFrequency (%)
20.0 2
 
5.7%
19.2 1
 
2.9%
15.8 1
 
2.9%
15.0 4
11.4%
12.2 1
 
2.9%
12.0 1
 
2.9%
10.0 9
25.7%
5.0 4
11.4%
4.6 1
 
2.9%
4.0 1
 
2.9%

사업기간
Text

Distinct34
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size412.0 B
2024-03-14T09:33:33.981927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length9.7142857
Min length8

Characters and Unicode

Total characters340
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

Unique33 ?
Unique (%)94.3%

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 (%)
03.30~05.16 2
 
5.7%
2.26~4.16 1
 
2.9%
10.8~11.6 1
 
2.9%
4.22~5.20 1
 
2.9%
10.19~11.08 1
 
2.9%
03.08~04.27 1
 
2.9%
03.14~06.11 1
 
2.9%
03.13~04.23 1
 
2.9%
03.31~05.29 1
 
2.9%
2.9~4.17 1
 
2.9%
Other values (24) 24
68.6%
2024-03-14T09:33:34.326322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 70
20.6%
1 69
20.3%
0 37
10.9%
~ 35
10.3%
2 34
10.0%
3 29
8.5%
4 22
 
6.5%
5 12
 
3.5%
6 9
 
2.6%
9 8
 
2.4%
Other values (2) 15
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 235
69.1%
Other Punctuation 70
 
20.6%
Math Symbol 35
 
10.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 69
29.4%
0 37
15.7%
2 34
14.5%
3 29
12.3%
4 22
 
9.4%
5 12
 
5.1%
6 9
 
3.8%
9 8
 
3.4%
8 8
 
3.4%
7 7
 
3.0%
Other Punctuation
ValueCountFrequency (%)
. 70
100.0%
Math Symbol
ValueCountFrequency (%)
~ 35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 340
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 70
20.6%
1 69
20.3%
0 37
10.9%
~ 35
10.3%
2 34
10.0%
3 29
8.5%
4 22
 
6.5%
5 12
 
3.5%
6 9
 
2.6%
9 8
 
2.4%
Other values (2) 15
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 340
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 70
20.6%
1 69
20.3%
0 37
10.9%
~ 35
10.3%
2 34
10.0%
3 29
8.5%
4 22
 
6.5%
5 12
 
3.5%
6 9
 
2.6%
9 8
 
2.4%
Other values (2) 15
 
4.4%

Interactions

2024-03-14T09:33:33.152384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:33:33.007861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:33:33.220721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:33:33.079473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T09:33:34.436650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시행년도위 치사업량사업기간
시행년도1.0000.8420.5021.000
위 치0.8421.0000.0000.974
사업량0.5020.0001.0000.943
사업기간1.0000.9740.9431.000
2024-03-14T09:33:34.531345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시행년도사업량위 치
시행년도1.000-0.1870.434
사업량-0.1871.0000.000
위 치0.4340.0001.000

Missing values

2024-03-14T09:33:33.325883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T09:33:33.386293image/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
252011진안군 백운면 신암리 산1, 산1-113.003.30~05.16
262011진안군 백운면 신암리 산110.003.30~05.16
272011완주군 동상면 대아리 산1-215.003.31~05.29
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