Overview

Dataset statistics

Number of variables7
Number of observations70
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.3 KiB
Average record size in memory62.8 B

Variable types

Numeric4
Categorical2
Text1

Dataset

Description전북특별자치도 사방사업 추진 현황 데이터입니다.번호, 구분, 위치 및 사업명, 사업비, 도급액, 관급액 등을 제공합니다.
Author전북특별자치도
URLhttps://www.data.go.kr/data/15055679/fileData.do

Alerts

구분 is highly overall correlated with 사업명High correlation
총사업비(원) is highly overall correlated with 도급액(원) and 2 other fieldsHigh correlation
도급액(원) is highly overall correlated with 총사업비(원) and 2 other fieldsHigh correlation
관급액(원) is highly overall correlated with 총사업비(원) and 2 other fieldsHigh correlation
사업명 is highly overall correlated with 구분 and 3 other fieldsHigh correlation
사업량 is highly imbalanced (73.3%)Imbalance
구분 has unique valuesUnique
위치 has unique valuesUnique
총사업비(원) has unique valuesUnique
도급액(원) has unique valuesUnique
관급액(원) has unique valuesUnique

Reproduction

Analysis started2024-03-14 10:49:12.537382
Analysis finished2024-03-14 10:49:17.675204
Duration5.14 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct70
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.5
Minimum1
Maximum70
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size758.0 B
2024-03-14T19:49:17.875231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.45
Q118.25
median35.5
Q352.75
95-th percentile66.55
Maximum70
Range69
Interquartile range (IQR)34.5

Descriptive statistics

Standard deviation20.351085
Coefficient of variation (CV)0.57327
Kurtosis-1.2
Mean35.5
Median Absolute Deviation (MAD)17.5
Skewness0
Sum2485
Variance414.16667
MonotonicityStrictly increasing
2024-03-14T19:49:18.323208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.4%
46 1
 
1.4%
52 1
 
1.4%
51 1
 
1.4%
50 1
 
1.4%
49 1
 
1.4%
48 1
 
1.4%
47 1
 
1.4%
45 1
 
1.4%
54 1
 
1.4%
Other values (60) 60
85.7%
ValueCountFrequency (%)
1 1
1.4%
2 1
1.4%
3 1
1.4%
4 1
1.4%
5 1
1.4%
6 1
1.4%
7 1
1.4%
8 1
1.4%
9 1
1.4%
10 1
1.4%
ValueCountFrequency (%)
70 1
1.4%
69 1
1.4%
68 1
1.4%
67 1
1.4%
66 1
1.4%
65 1
1.4%
64 1
1.4%
63 1
1.4%
62 1
1.4%
61 1
1.4%

사업명
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size688.0 B
사방댐
38 
계류보전
24 
산지
7 
산림유역
 
1

Length

Max length4
Median length3
Mean length3.2571429
Min length2

Unique

Unique1 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
사방댐 38
54.3%
계류보전 24
34.3%
산지 7
 
10.0%
산림유역 1
 
1.4%

Length

2024-03-14T19:49:18.787025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T19:49:19.354769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사방댐 38
54.3%
계류보전 24
34.3%
산지 7
 
10.0%
산림유역 1
 
1.4%

위치
Text

UNIQUE 

Distinct70
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size688.0 B
2024-03-14T19:49:20.459485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length16.057143
Min length12

Characters and Unicode

Total characters1124
Distinct characters118
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

Unique70 ?
Unique (%)100.0%

Sample

1st row전주시 덕진구 진북동 산107-1
2nd row익산시 여산면 원수리 산88-71
3rd row남원시 향교동 457-24
4th row순창군 인계면 심초리 171
5th row고창군 고수면 상평리 산78
ValueCountFrequency (%)
남원시 14
 
5.0%
장수군 11
 
4.0%
진안군 10
 
3.6%
산동면 6
 
2.2%
정읍시 6
 
2.2%
번암면 5
 
1.8%
임실군 5
 
1.8%
완주군 5
 
1.8%
고창군 4
 
1.4%
안천면 4
 
1.4%
Other values (176) 208
74.8%
2024-03-14T19:49:22.074900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
208
18.5%
산 68
 
6.0%
리 63
 
5.6%
면 62
 
5.5%
1 54
 
4.8%
군 46
 
4.1%
- 33
 
2.9%
2 29
 
2.6%
시 26
 
2.3%
4 21
 
1.9%
Other values (108) 514
45.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 670
59.6%
Decimal Number 213
 
19.0%
Space Separator 208
 
18.5%
Dash Punctuation 33
 
2.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 68
 
10.1%
리 63
 
9.4%
면 62
 
9.3%
군 46
 
6.9%
시 26
 
3.9%
원 19
 
2.8%
동 19
 
2.8%
남 18
 
2.7%
수 17
 
2.5%
안 16
 
2.4%
Other values (96) 316
47.2%
Decimal Number
ValueCountFrequency (%)
1 54
25.4%
2 29
13.6%
4 21
 
9.9%
3 19
 
8.9%
7 18
 
8.5%
6 18
 
8.5%
5 16
 
7.5%
0 16
 
7.5%
8 14
 
6.6%
9 8
 
3.8%
Space Separator
ValueCountFrequency (%)
208
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 670
59.6%
Common 454
40.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 68
 
10.1%
리 63
 
9.4%
면 62
 
9.3%
군 46
 
6.9%
시 26
 
3.9%
원 19
 
2.8%
동 19
 
2.8%
남 18
 
2.7%
수 17
 
2.5%
안 16
 
2.4%
Other values (96) 316
47.2%
Common
ValueCountFrequency (%)
208
45.8%
1 54
 
11.9%
- 33
 
7.3%
2 29
 
6.4%
4 21
 
4.6%
3 19
 
4.2%
7 18
 
4.0%
6 18
 
4.0%
5 16
 
3.5%
0 16
 
3.5%
Other values (2) 22
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 670
59.6%
ASCII 454
40.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
208
45.8%
1 54
 
11.9%
- 33
 
7.3%
2 29
 
6.4%
4 21
 
4.6%
3 19
 
4.2%
7 18
 
4.0%
6 18
 
4.0%
5 16
 
3.5%
0 16
 
3.5%
Other values (2) 22
 
4.8%
Hangul
ValueCountFrequency (%)
산 68
 
10.1%
리 63
 
9.4%
면 62
 
9.3%
군 46
 
6.9%
시 26
 
3.9%
원 19
 
2.8%
동 19
 
2.8%
남 18
 
2.7%
수 17
 
2.5%
안 16
 
2.4%
Other values (96) 316
47.2%

사업량
Categorical

IMBALANCE 

Distinct3
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size688.0 B
1
65 
2
 
4
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.4%

Sample

1st row2
2nd row1
3rd row2
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 65
92.9%
2 4
 
5.7%
3 1
 
1.4%

Length

2024-03-14T19:49:22.510967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T19:49:22.784839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 65
92.9%
2 4
 
5.7%
3 1
 
1.4%

총사업비(원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct70
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0380713 × 108
Minimum65512110
Maximum7.8769996 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size758.0 B
2024-03-14T19:49:22.989373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum65512110
5-th percentile93682203
Q11.6557300 × 108
median2.0121193 × 108
Q32.3666217 × 108
95-th percentile2.7414486 × 108
Maximum7.8769996 × 108
Range7.2218785 × 108
Interquartile range (IQR)71089162

Descriptive statistics

Standard deviation88131040
Coefficient of variation (CV)0.43242373
Kurtosis27.807206
Mean2.0380713 × 108
Median Absolute Deviation (MAD)36478655
Skewness4.119875
Sum1.4266499 × 1010
Variance7.7670802 × 1015
MonotonicityNot monotonic
2024-03-14T19:49:23.250957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
148726610 1
 
1.4%
187234730 1
 
1.4%
236541680 1
 
1.4%
198911830 1
 
1.4%
211501350 1
 
1.4%
206817540 1
 
1.4%
215275430 1
 
1.4%
250092530 1
 
1.4%
254446050 1
 
1.4%
240691020 1
 
1.4%
Other values (60) 60
85.7%
ValueCountFrequency (%)
65512110 1
1.4%
67346780 1
1.4%
79745880 1
1.4%
82814550 1
1.4%
106964890 1
1.4%
108128340 1
1.4%
118703430 1
1.4%
123450430 1
1.4%
133253290 1
1.4%
136937910 1
1.4%
ValueCountFrequency (%)
787699960 1
1.4%
303916600 1
1.4%
301560470 1
1.4%
276677470 1
1.4%
271049450 1
1.4%
256281430 1
1.4%
254446050 1
1.4%
254207500 1
1.4%
250092530 1
1.4%
247537370 1
1.4%

도급액(원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct70
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5678665 × 108
Minimum53023000
Maximum6.09402 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size758.0 B
2024-03-14T19:49:23.542406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum53023000
5-th percentile75698150
Q11.3048825 × 108
median1.53566 × 108
Q31.7790925 × 108
95-th percentile2.0588836 × 108
Maximum6.09402 × 108
Range5.56379 × 108
Interquartile range (IQR)47421000

Descriptive statistics

Standard deviation67074166
Coefficient of variation (CV)0.42780533
Kurtosis30.054213
Mean1.5678665 × 108
Median Absolute Deviation (MAD)23902500
Skewness4.3762833
Sum1.0975066 × 1010
Variance4.4989438 × 1015
MonotonicityNot monotonic
2024-03-14T19:49:23.840109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
142922000 1
 
1.4%
141013000 1
 
1.4%
170257000 1
 
1.4%
147770000 1
 
1.4%
151855000 1
 
1.4%
146464000 1
 
1.4%
162765000 1
 
1.4%
178467000 1
 
1.4%
202774000 1
 
1.4%
171000000 1
 
1.4%
Other values (60) 60
85.7%
ValueCountFrequency (%)
53023000 1
1.4%
55728000 1
1.4%
68313000 1
1.4%
75488000 1
1.4%
75955000 1
1.4%
87464000 1
1.4%
92670000 1
1.4%
102166000 1
1.4%
104286000 1
1.4%
104825000 1
1.4%
ValueCountFrequency (%)
609402000 1
1.4%
219619000 1
1.4%
219077000 1
1.4%
206369740 1
1.4%
205300000 1
1.4%
203740000 1
1.4%
203494000 1
1.4%
202774000 1
1.4%
199448000 1
1.4%
191911000 1
1.4%

관급액(원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct70
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47020475
Minimum5804610
Maximum1.7829796 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size758.0 B
2024-03-14T19:49:24.087667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5804610
5-th percentile12010428
Q133231132
median47392905
Q358353072
95-th percentile73331063
Maximum1.7829796 × 108
Range1.7249335 × 108
Interquartile range (IQR)25121940

Descriptive statistics

Standard deviation24054909
Coefficient of variation (CV)0.51158371
Kurtosis11.815417
Mean47020475
Median Absolute Deviation (MAD)12740250
Skewness2.2155246
Sum3.2914332 × 109
Variance5.7863864 × 1014
MonotonicityNot monotonic
2024-03-14T19:49:24.350681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5804610 1
 
1.4%
46221730 1
 
1.4%
66284680 1
 
1.4%
51141830 1
 
1.4%
59646350 1
 
1.4%
60353540 1
 
1.4%
52510430 1
 
1.4%
71625530 1
 
1.4%
51672050 1
 
1.4%
69691020 1
 
1.4%
Other values (60) 60
85.7%
ValueCountFrequency (%)
5804610 1
1.4%
7326550 1
1.4%
11432880 1
1.4%
11618780 1
1.4%
12489110 1
1.4%
14294890 1
1.4%
18625430 1
1.4%
21004310 1
1.4%
25476960 1
1.4%
25605910 1
1.4%
ValueCountFrequency (%)
178297960 1
1.4%
84297600 1
1.4%
82483470 1
1.4%
74726500 1
1.4%
71625530 1
1.4%
71601450 1
1.4%
70307730 1
1.4%
69691020 1
1.4%
66587370 1
1.4%
66284680 1
1.4%

Interactions

2024-03-14T19:49:16.004677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:49:12.901119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:49:13.941769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:49:14.987921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:49:16.270148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:49:13.163116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:49:14.205743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:49:15.244660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:49:16.538110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:49:13.425292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:49:14.471445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:49:15.501891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:49:16.795878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:49:13.678056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:49:14.722822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:49:15.747051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T19:49:24.533262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분사업명위치사업량총사업비(원)도급액(원)관급액(원)
구분1.0000.9031.0000.2660.4030.3790.355
사업명0.9031.0001.0000.3010.7150.9230.820
위치1.0001.0001.0001.0001.0001.0001.000
사업량0.2660.3011.0001.0000.1300.0000.421
총사업비(원)0.4030.7151.0000.1301.0000.8810.873
도급액(원)0.3790.9231.0000.0000.8811.0000.845
관급액(원)0.3550.8201.0000.4210.8730.8451.000
2024-03-14T19:49:24.745523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업명사업량
사업명1.0000.287
사업량0.2871.000
2024-03-14T19:49:24.936716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분총사업비(원)도급액(원)관급액(원)사업명사업량
구분1.0000.4540.4110.4150.7500.150
총사업비(원)0.4541.0000.9590.8040.6610.099
도급액(원)0.4110.9591.0000.6260.6470.000
관급액(원)0.4150.8040.6261.0000.6780.133
사업명0.7500.6610.6470.6781.0000.287
사업량0.1500.0990.0000.1330.2871.000

Missing values

2024-03-14T19:49:17.150214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T19:49:17.529262image/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

구분사업명위치사업량총사업비(원)도급액(원)관급액(원)
01산지전주시 덕진구 진북동 산107-121487266101429220005804610
12산지익산시 여산면 원수리 산88-711673467805572800011618780
23산지남원시 향교동 457-24216374502010506600058679020
34산지순창군 인계면 심초리 1711797458806831300011432880
45산지고창군 고수면 상평리 산78182814550754880007326550
56산지고창군 상하면 자룡리 497319965896017418200025476960
67산지장수군 장계면 대곡리 산8-431655121105302300012489110
78계류보전전주시 완산구 서서학동 1022-1117479307013109200043701070
89계류보전군산시 나포면 주곡리 124-3115004431012904000021004310
910계류보전정읍시 쌍암동 686-2외2118818992013274400055445920
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6061사방댐임실군 덕치면 가곡리 산144120705577015887200048183770
6162사방댐임실군 관촌면 상월리 246120977207015332900056443070
6263사방댐임실군 오수면 신기리 산10122178925017106600050723250
6364사방댐순창군 동계면 어치리 532-8127104945019944800071601450
6465사방댐고창군 고창면 월산리 산130-1117770899013691700040791990
6566사방댐임실군 운암면 청운리 317123080177017460900056192770
6667사방댐남원군 산동면 식련리 산47127667747020636974070307730
6768사방댐진안군 안천면 노성리 산64113862419010428600034338190
6869사방댐장수군 장계면 명뎍리 산154-1122973519018345900046276190
6970산림유역완주군 소양면 신촌리 산18-11787699960609402000178297960