Overview

Dataset statistics

Number of variables6
Number of observations34
Missing cells14
Missing cells (%)6.9%
Duplicate rows1
Duplicate rows (%)2.9%
Total size in memory1.9 KiB
Average record size in memory55.9 B

Variable types

Categorical2
Text2
Numeric2

Dataset

Description산림토목관리시스템 내 사방댐, 계류보전, 산지보전 사업 등 사업종별 기준 시공 단가 정보간선임도, 작업임도, 산불예방임도 등 산림토목 정보
Author산림청
URLhttps://www.data.go.kr/data/15041979/fileData.do

Alerts

기준년도 has constant value ""Constant
자부담사업비 has constant value ""Constant
Dataset has 1 (2.9%) duplicate rowsDuplicates
산림토목시설구분명 has 14 (41.2%) missing valuesMissing
국비사업비 has 4 (11.8%) zerosZeros
지방비사업비 has 22 (64.7%) zerosZeros

Reproduction

Analysis started2023-12-12 04:37:49.074821
Analysis finished2023-12-12 04:37:49.984151
Duration0.91 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년도
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size404.0 B
2023
34 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023
2nd row2023
3rd row2023
4th row2023
5th row2023

Common Values

ValueCountFrequency (%)
2023 34
100.0%

Length

2023-12-12T13:37:50.052034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:37:50.172282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023 34
100.0%

토목사업분류명
Text

Distinct17
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size404.0 B
2023-12-12T13:37:50.364424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length8.3529412
Min length5

Characters and Unicode

Total characters284
Distinct characters43
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row임도_간선
2nd row임도_지선
3rd row임도_작업
4th row임도_산림재해예방
5th row사방_산지사방사업
ValueCountFrequency (%)
임도_간선 2
 
5.9%
사방_해안침식방지 2
 
5.9%
사방_국가지점번호 2
 
5.9%
사방_사방댐안전조치 2
 
5.9%
사방_계류보전안전조치 2
 
5.9%
사방_사방댐점검 2
 
5.9%
사방_사방지점검 2
 
5.9%
사방_타당성평가 2
 
5.9%
사방_해안방재림조성 2
 
5.9%
임도_지선 2
 
5.9%
Other values (7) 14
41.2%
2023-12-12T13:37:50.778344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
방 44
15.5%
사 44
15.5%
_ 34
 
12.0%
지 10
 
3.5%
임 8
 
2.8%
안 8
 
2.8%
업 8
 
2.8%
도 8
 
2.8%
댐 8
 
2.8%
전 8
 
2.8%
Other values (33) 104
36.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 246
86.6%
Connector Punctuation 34
 
12.0%
Close Punctuation 2
 
0.7%
Open Punctuation 2
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
방 44
17.9%
사 44
17.9%
지 10
 
4.1%
임 8
 
3.3%
안 8
 
3.3%
업 8
 
3.3%
도 8
 
3.3%
댐 8
 
3.3%
전 8
 
3.3%
조 6
 
2.4%
Other values (30) 94
38.2%
Connector Punctuation
ValueCountFrequency (%)
_ 34
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 246
86.6%
Common 38
 
13.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
방 44
17.9%
사 44
17.9%
지 10
 
4.1%
임 8
 
3.3%
안 8
 
3.3%
업 8
 
3.3%
도 8
 
3.3%
댐 8
 
3.3%
전 8
 
3.3%
조 6
 
2.4%
Other values (30) 94
38.2%
Common
ValueCountFrequency (%)
_ 34
89.5%
) 2
 
5.3%
( 2
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 246
86.6%
ASCII 38
 
13.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
방 44
17.9%
사 44
17.9%
지 10
 
4.1%
임 8
 
3.3%
안 8
 
3.3%
업 8
 
3.3%
도 8
 
3.3%
댐 8
 
3.3%
전 8
 
3.3%
조 6
 
2.4%
Other values (30) 94
38.2%
ASCII
ValueCountFrequency (%)
_ 34
89.5%
) 2
 
5.3%
( 2
 
5.3%

산림토목시설구분명
Text

MISSING 

Distinct10
Distinct (%)50.0%
Missing14
Missing (%)41.2%
Memory size404.0 B
2023-12-12T13:37:50.959035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length4
Mean length5.1
Min length4

Characters and Unicode

Total characters102
Distinct characters31
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

Unique0 ?
Unique (%)0.0%

Sample

1st row간선임도
2nd row지선임도
3rd row작업임도
4th row산불진화임도
5th row산지보전
ValueCountFrequency (%)
간선임도 2
 
7.7%
지선임도 2
 
7.7%
작업임도 2
 
7.7%
산불진화임도 2
 
7.7%
산지보전 2
 
7.7%
계류보전 2
 
7.7%
사방댐 2
 
7.7%
설치 2
 
7.7%
해안방재림 2
 
7.7%
조성 2
 
7.7%
Other values (3) 6
23.1%
2023-12-12T13:37:51.326458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
임 8
 
7.8%
도 8
 
7.8%
지 6
 
5.9%
6
 
5.9%
방 6
 
5.9%
안 4
 
3.9%
선 4
 
3.9%
산 4
 
3.9%
해 4
 
3.9%
보 4
 
3.9%
Other values (21) 48
47.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 96
94.1%
Space Separator 6
 
5.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
임 8
 
8.3%
도 8
 
8.3%
지 6
 
6.2%
방 6
 
6.2%
안 4
 
4.2%
선 4
 
4.2%
산 4
 
4.2%
해 4
 
4.2%
보 4
 
4.2%
전 4
 
4.2%
Other values (20) 44
45.8%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 96
94.1%
Common 6
 
5.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
임 8
 
8.3%
도 8
 
8.3%
지 6
 
6.2%
방 6
 
6.2%
안 4
 
4.2%
선 4
 
4.2%
산 4
 
4.2%
해 4
 
4.2%
보 4
 
4.2%
전 4
 
4.2%
Other values (20) 44
45.8%
Common
ValueCountFrequency (%)
6
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 96
94.1%
ASCII 6
 
5.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
임 8
 
8.3%
도 8
 
8.3%
지 6
 
6.2%
방 6
 
6.2%
안 4
 
4.2%
선 4
 
4.2%
산 4
 
4.2%
해 4
 
4.2%
보 4
 
4.2%
전 4
 
4.2%
Other values (20) 44
45.8%
ASCII
ValueCountFrequency (%)
6
100.0%

국비사업비
Real number (ℝ)

ZEROS 

Distinct29
Distinct (%)85.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean84663540
Minimum0
Maximum3.34 × 108
Zeros4
Zeros (%)11.8%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T13:37:51.463242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1500000
median44100000
Q31.3753125 × 108
95-th percentile2.7395102 × 108
Maximum3.34 × 108
Range3.34 × 108
Interquartile range (IQR)1.3703125 × 108

Descriptive statistics

Standard deviation1.0126693 × 108
Coefficient of variation (CV)1.1961103
Kurtosis0.033270254
Mean84663540
Median Absolute Deviation (MAD)43921500
Skewness1.0728963
Sum2.8785604 × 109
Variance1.0254991 × 1016
MonotonicityNot monotonic
2023-12-12T13:37:51.912120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0 4
 
11.8%
500000 2
 
5.9%
50000000 2
 
5.9%
220889000 1
 
2.9%
35000000 1
 
2.9%
26740000 1
 
2.9%
309400 1
 
2.9%
147000 1
 
2.9%
2745400 1
 
2.9%
222902050 1
 
2.9%
Other values (19) 19
55.9%
ValueCountFrequency (%)
0 4
11.8%
147000 1
 
2.9%
210000 1
 
2.9%
309400 1
 
2.9%
442000 1
 
2.9%
500000 2
5.9%
2745400 1
 
2.9%
3922000 1
 
2.9%
4900000 1
 
2.9%
7000000 1
 
2.9%
ValueCountFrequency (%)
334000000 1
2.9%
318431500 1
2.9%
250000000 1
2.9%
223000000 1
2.9%
222902050 1
2.9%
220889000 1
2.9%
197679000 1
2.9%
175000000 1
2.9%
138375000 1
2.9%
135000000 1
2.9%

지방비사업비
Real number (ℝ)

ZEROS 

Distinct13
Distinct (%)38.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9251930.9
Minimum0
Maximum95529450
Zeros22
Zeros (%)64.7%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T13:37:52.078056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31007450
95-th percentile64797600
Maximum95529450
Range95529450
Interquartile range (IQR)1007450

Descriptive statistics

Standard deviation22836964
Coefficient of variation (CV)2.4683457
Kurtosis7.5053791
Mean9251930.9
Median Absolute Deviation (MAD)0
Skewness2.8219055
Sum3.1456565 × 108
Variance5.2152691 × 1014
MonotonicityNot monotonic
2023-12-12T13:37:52.236491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 22
64.7%
24300000 1
 
2.9%
59304000 1
 
2.9%
75000000 1
 
2.9%
2100000 1
 
2.9%
30000000 1
 
2.9%
95529450 1
 
2.9%
1176600 1
 
2.9%
63000 1
 
2.9%
132600 1
 
2.9%
Other values (3) 3
 
8.8%
ValueCountFrequency (%)
0 22
64.7%
63000 1
 
2.9%
132600 1
 
2.9%
500000 1
 
2.9%
1176600 1
 
2.9%
2100000 1
 
2.9%
11460000 1
 
2.9%
15000000 1
 
2.9%
24300000 1
 
2.9%
30000000 1
 
2.9%
ValueCountFrequency (%)
95529450 1
2.9%
75000000 1
2.9%
59304000 1
2.9%
30000000 1
2.9%
24300000 1
2.9%
15000000 1
2.9%
11460000 1
2.9%
2100000 1
2.9%
1176600 1
2.9%
500000 1
2.9%

자부담사업비
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size404.0 B
0
34 

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 34
100.0%

Length

2023-12-12T13:37:52.375959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:37:52.511885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 34
100.0%

Interactions

2023-12-12T13:37:49.549097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:49.267855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:49.659422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:37:49.434793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:37:52.578386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
토목사업분류명산림토목시설구분명국비사업비지방비사업비
토목사업분류명1.0001.0000.8630.263
산림토목시설구분명1.0001.0000.7890.319
국비사업비0.8630.7891.0000.504
지방비사업비0.2630.3190.5041.000
2023-12-12T13:37:52.680856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
국비사업비지방비사업비
국비사업비1.0000.057
지방비사업비0.0571.000

Missing values

2023-12-12T13:37:49.794095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:37:49.934628image/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

기준년도토목사업분류명산림토목시설구분명국비사업비지방비사업비자부담사업비
02023임도_간선간선임도22300000000
12023임도_지선지선임도000
22023임도_작업작업임도13500000000
32023임도_산림재해예방산불진화임도33400000000
42023사방_산지사방사업산지보전8100000000
52023사방_계류보전사업계류보전19767900000
62023사방_사방댐사방댐 설치25000000000
72023사방_사방댐관리(준설)<NA>700000000
82023사방_해안방재림조성해안방재림 조성10000000000
92023사방_해안침식방지해안침식 방지31843150000
기준년도토목사업분류명산림토목시설구분명국비사업비지방비사업비자부담사업비
242023사방_사방댐관리(준설)<NA>490000021000000
252023사방_해안방재림조성해안방재림 조성70000000300000000
262023사방_해안침식방지해안침식 방지222902050955294500
272023사방_타당성평가<NA>274540011766000
282023사방_사방지점검<NA>147000630000
292023사방_사방댐점검<NA>3094001326000
302023사방_계류보전안전조치<NA>26740000114600000
312023사방_사방댐안전조치<NA>35000000150000000
322023사방_국가지점번호<NA>5000005000000
332023사방_계류복원사업계류복원000

Duplicate rows

Most frequently occurring

기준년도토목사업분류명산림토목시설구분명국비사업비지방비사업비자부담사업비# duplicates
02023임도_지선지선임도0002