Overview

Dataset statistics

Number of variables7
Number of observations210
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.8 KiB
Average record size in memory62.6 B

Variable types

Numeric5
Text1
Categorical1

Dataset

Description전북특별자치도 진안군 도시계획정보시스템 도로 기종점 현황에 대한 데이터로 공간정보관리번호, X좌표 및 Y좌표 정보, 현황도형 관리번호, 기종점구분 정보를 제공합니다.
Author전북특별자치도 진안군
URLhttps://www.data.go.kr/data/15119124/fileData.do

Alerts

공간정보관리번호 is highly overall correlated with 기종점구분High correlation
X좌표최소값 is highly overall correlated with X좌표최대값High correlation
Y좌표최소값 is highly overall correlated with Y좌표최대값High correlation
X좌표최대값 is highly overall correlated with X좌표최소값High correlation
Y좌표최대값 is highly overall correlated with Y좌표최소값High correlation
기종점구분 is highly overall correlated with 공간정보관리번호High correlation
공간정보관리번호 has unique valuesUnique
X좌표최소값 has unique valuesUnique
Y좌표최소값 has unique valuesUnique
X좌표최대값 has unique valuesUnique
Y좌표최대값 has unique valuesUnique

Reproduction

Analysis started2024-04-17 11:18:54.495253
Analysis finished2024-04-17 11:18:58.170512
Duration3.68 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

공간정보관리번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct210
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean105.5
Minimum1
Maximum210
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-04-17T20:18:58.239597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile11.45
Q153.25
median105.5
Q3157.75
95-th percentile199.55
Maximum210
Range209
Interquartile range (IQR)104.5

Descriptive statistics

Standard deviation60.765944
Coefficient of variation (CV)0.57598052
Kurtosis-1.2
Mean105.5
Median Absolute Deviation (MAD)52.5
Skewness0
Sum22155
Variance3692.5
MonotonicityStrictly increasing
2024-04-17T20:18:58.356071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
159 1
 
0.5%
135 1
 
0.5%
136 1
 
0.5%
137 1
 
0.5%
138 1
 
0.5%
139 1
 
0.5%
140 1
 
0.5%
141 1
 
0.5%
142 1
 
0.5%
Other values (200) 200
95.2%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 1
0.5%
7 1
0.5%
8 1
0.5%
9 1
0.5%
10 1
0.5%
ValueCountFrequency (%)
210 1
0.5%
209 1
0.5%
208 1
0.5%
207 1
0.5%
206 1
0.5%
205 1
0.5%
204 1
0.5%
203 1
0.5%
202 1
0.5%
201 1
0.5%

X좌표최소값
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct210
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23861820
Minimum22476672
Maximum25573416
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-04-17T20:18:58.470043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22476672
5-th percentile22844662
Q123806920
median23851440
Q323931112
95-th percentile25014362
Maximum25573416
Range3096744
Interquartile range (IQR)124192

Descriptive statistics

Standard deviation515764.84
Coefficient of variation (CV)0.021614648
Kurtosis3.3166756
Mean23861820
Median Absolute Deviation (MAD)57058.5
Skewness0.43748061
Sum5.0109821 × 109
Variance2.6601337 × 1011
MonotonicityNot monotonic
2024-04-17T20:18:58.601042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
23803370 1
 
0.5%
22777936 1
 
0.5%
23811024 1
 
0.5%
23484898 1
 
0.5%
23161068 1
 
0.5%
23998110 1
 
0.5%
24706813 1
 
0.5%
23994714 1
 
0.5%
25056427 1
 
0.5%
25255374 1
 
0.5%
Other values (200) 200
95.2%
ValueCountFrequency (%)
22476672 1
0.5%
22519320 1
0.5%
22536880 1
0.5%
22559290 1
0.5%
22593734 1
0.5%
22600080 1
0.5%
22628060 1
0.5%
22628571 1
0.5%
22652157 1
0.5%
22672594 1
0.5%
ValueCountFrequency (%)
25573416 1
0.5%
25493415 1
0.5%
25441191 1
0.5%
25403161 1
0.5%
25395905 1
0.5%
25391086 1
0.5%
25385940 1
0.5%
25255374 1
0.5%
25079785 1
0.5%
25056427 1
0.5%

Y좌표최소값
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct210
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25511116
Minimum23775756
Maximum27889237
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-04-17T20:18:58.730341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23775756
5-th percentile24422569
Q125407444
median25470012
Q325517872
95-th percentile26445757
Maximum27889237
Range4113481
Interquartile range (IQR)110428.25

Descriptive statistics

Standard deviation593300.09
Coefficient of variation (CV)0.023256532
Kurtosis4.555063
Mean25511116
Median Absolute Deviation (MAD)57226.5
Skewness0.9172202
Sum5.3573343 × 109
Variance3.5200499 × 1011
MonotonicityNot monotonic
2024-04-17T20:18:58.848636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25566877 1
 
0.5%
24300499 1
 
0.5%
25535642 1
 
0.5%
27858685 1
 
0.5%
27025301 1
 
0.5%
26382812 1
 
0.5%
27254014 1
 
0.5%
26198052 1
 
0.5%
25553628 1
 
0.5%
26689367 1
 
0.5%
Other values (200) 200
95.2%
ValueCountFrequency (%)
23775756 1
0.5%
24026031 1
0.5%
24027404 1
0.5%
24050085 1
0.5%
24104953 1
0.5%
24128976 1
0.5%
24239601 1
0.5%
24274245 1
0.5%
24283577 1
0.5%
24300499 1
0.5%
ValueCountFrequency (%)
27889237 1
0.5%
27858685 1
0.5%
27657999 1
0.5%
27600424 1
0.5%
27485321 1
0.5%
27254014 1
0.5%
27025301 1
0.5%
26689367 1
0.5%
26672609 1
0.5%
26535384 1
0.5%

X좌표최대값
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct210
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23862728
Minimum22477547
Maximum25574271
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-04-17T20:18:58.967929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22477547
5-th percentile22846010
Q123808050
median23852560
Q323931873
95-th percentile25015193
Maximum25574271
Range3096724
Interquartile range (IQR)123822.75

Descriptive statistics

Standard deviation515753.33
Coefficient of variation (CV)0.021613343
Kurtosis3.3166957
Mean23862728
Median Absolute Deviation (MAD)57727.5
Skewness0.43748261
Sum5.0111729 × 109
Variance2.660015 × 1011
MonotonicityNot monotonic
2024-04-17T20:18:59.089251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
23803979 1
 
0.5%
22778797 1
 
0.5%
23811784 1
 
0.5%
23485609 1
 
0.5%
23161705 1
 
0.5%
23998805 1
 
0.5%
24707744 1
 
0.5%
23995679 1
 
0.5%
25057315 1
 
0.5%
25256251 1
 
0.5%
Other values (200) 200
95.2%
ValueCountFrequency (%)
22477547 1
0.5%
22520182 1
0.5%
22537758 1
0.5%
22560186 1
0.5%
22594697 1
0.5%
22600977 1
0.5%
22628989 1
0.5%
22629476 1
0.5%
22653165 1
0.5%
22673513 1
0.5%
ValueCountFrequency (%)
25574271 1
0.5%
25494250 1
0.5%
25442118 1
0.5%
25404054 1
0.5%
25396738 1
0.5%
25391998 1
0.5%
25386863 1
0.5%
25256251 1
0.5%
25080647 1
0.5%
25057315 1
0.5%

Y좌표최대값
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct210
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25512028
Minimum23776649
Maximum27889968
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-04-17T20:18:59.216476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23776649
5-th percentile24423467
Q125408846
median25470658
Q325518530
95-th percentile26446650
Maximum27889968
Range4113319
Interquartile range (IQR)109684

Descriptive statistics

Standard deviation593284.68
Coefficient of variation (CV)0.023255097
Kurtosis4.5545463
Mean25512028
Median Absolute Deviation (MAD)57530
Skewness0.91707902
Sum5.3575258 × 109
Variance3.5198671 × 1011
MonotonicityNot monotonic
2024-04-17T20:18:59.338131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25567542 1
 
0.5%
24301375 1
 
0.5%
25536402 1
 
0.5%
27859433 1
 
0.5%
27026002 1
 
0.5%
26383511 1
 
0.5%
27254895 1
 
0.5%
26199136 1
 
0.5%
25554419 1
 
0.5%
26690227 1
 
0.5%
Other values (200) 200
95.2%
ValueCountFrequency (%)
23776649 1
0.5%
24026835 1
0.5%
24028215 1
0.5%
24050954 1
0.5%
24106296 1
0.5%
24129799 1
0.5%
24240320 1
0.5%
24275375 1
0.5%
24284496 1
0.5%
24301375 1
0.5%
ValueCountFrequency (%)
27889968 1
0.5%
27859433 1
0.5%
27658741 1
0.5%
27601349 1
0.5%
27486069 1
0.5%
27254895 1
0.5%
27026002 1
0.5%
26690227 1
0.5%
26673442 1
0.5%
26536333 1
0.5%

현황도형 관리번호
Text

Distinct105
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-04-17T20:18:59.522204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters5040
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
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 row45720UQ151PS200906190055
2nd row45720UQ151PS200906190075
3rd row45720UQ151PS200906190001
4th row45720UQ151PS200906190042
5th row45720UQ151PS200908310014
ValueCountFrequency (%)
45720uq151ps200906190055 2
 
1.0%
45720uq151ps200906190087 2
 
1.0%
45720uq151ps201005070022 2
 
1.0%
45720uq151ps201005070050 2
 
1.0%
45720uq151ps201005070045 2
 
1.0%
45720uq151ps201005070033 2
 
1.0%
45720uq151ps201005070021 2
 
1.0%
45720uq151ps201005070104 2
 
1.0%
45720uq151ps201005070037 2
 
1.0%
45720uq151ps201107010059 2
 
1.0%
Other values (95) 190
90.5%
2024-04-17T20:18:59.805418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1342
26.6%
1 706
14.0%
5 508
 
10.1%
2 466
 
9.2%
9 322
 
6.4%
7 304
 
6.0%
4 256
 
5.1%
U 210
 
4.2%
Q 210
 
4.2%
P 210
 
4.2%
Other values (4) 506
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4200
83.3%
Uppercase Letter 840
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1342
32.0%
1 706
16.8%
5 508
 
12.1%
2 466
 
11.1%
9 322
 
7.7%
7 304
 
7.2%
4 256
 
6.1%
6 164
 
3.9%
3 68
 
1.6%
8 64
 
1.5%
Uppercase Letter
ValueCountFrequency (%)
U 210
25.0%
Q 210
25.0%
P 210
25.0%
S 210
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4200
83.3%
Latin 840
 
16.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1342
32.0%
1 706
16.8%
5 508
 
12.1%
2 466
 
11.1%
9 322
 
7.7%
7 304
 
7.2%
4 256
 
6.1%
6 164
 
3.9%
3 68
 
1.6%
8 64
 
1.5%
Latin
ValueCountFrequency (%)
U 210
25.0%
Q 210
25.0%
P 210
25.0%
S 210
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5040
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1342
26.6%
1 706
14.0%
5 508
 
10.1%
2 466
 
9.2%
9 322
 
6.4%
7 304
 
6.0%
4 256
 
5.1%
U 210
 
4.2%
Q 210
 
4.2%
P 210
 
4.2%
Other values (4) 506
 
10.0%

기종점구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
1
105 
0
105 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 105
50.0%
0 105
50.0%

Length

2024-04-17T20:18:59.918598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T20:19:00.002384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 105
50.0%
0 105
50.0%

Interactions

2024-04-17T20:18:57.644384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:18:55.834704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:18:56.242183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:18:56.619236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:18:57.271907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:18:57.711764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:18:55.948817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:18:56.313099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:18:56.687007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:18:57.337545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:18:57.785313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:18:56.028250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:18:56.389282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:18:56.775679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:18:57.416262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:18:57.851879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:18:56.096240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:18:56.465200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:18:56.845791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:18:57.487331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:18:57.926967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:18:56.171427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:18:56.542700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:18:56.920499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:18:57.567536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-17T20:19:00.065070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공간정보관리번호X좌표최소값Y좌표최소값X좌표최대값Y좌표최대값기종점구분
공간정보관리번호1.0000.6850.7670.6850.7670.976
X좌표최소값0.6851.0000.9131.0000.9130.000
Y좌표최소값0.7670.9131.0000.9131.0000.000
X좌표최대값0.6851.0000.9131.0000.9130.000
Y좌표최대값0.7670.9131.0000.9131.0000.000
기종점구분0.9760.0000.0000.0000.0001.000
2024-04-17T20:19:00.156655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공간정보관리번호X좌표최소값Y좌표최소값X좌표최대값Y좌표최대값기종점구분
공간정보관리번호1.0000.021-0.0020.021-0.0010.849
X좌표최소값0.0211.0000.4461.0000.4470.000
Y좌표최소값-0.0020.4461.0000.4451.0000.000
X좌표최대값0.0211.0000.4451.0000.4460.000
Y좌표최대값-0.0010.4471.0000.4461.0000.000
기종점구분0.8490.0000.0000.0000.0001.000

Missing values

2024-04-17T20:18:58.024058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T20:18:58.130255image/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

공간정보관리번호X좌표최소값Y좌표최소값X좌표최대값Y좌표최대값현황도형 관리번호기종점구분
012380337025566877238039792556754245720UQ151PS2009061900551
122376397125559370237650562556038145720UQ151PS2009061900751
232384427325528893238453612552993645720UQ151PS2009061900011
342391862825590889239195032559164845720UQ151PS2009061900421
452398725525587209239893992558953245720UQ151PS2009083100141
562397853825539894239792292554062745720UQ151PS2009061900511
672396211125490851239626722549141945720UQ151PS2009061900821
782396377225465246239644902546605045720UQ151PS2009083100531
892396405325480124239647032548072545720UQ151PS2009061901001
9102396988525475095239707742547605045720UQ151PS2009061900401
공간정보관리번호X좌표최소값Y좌표최소값X좌표최대값Y좌표최대값현황도형 관리번호기종점구분
2002012383412627485321238348752748606945720UQ151PS2011070100590
2012022393257227889237239333032788996845720UQ151PS2011070100570
2022032347333027657999234740722765874145720UQ151PS2009031400020
2032042380943225455309238101672545608845720UQ151PS2009061900461
2042052376988826402258237707892640327445720UQ151PS2010081301051
2052062399734726382440239980672638310145720UQ151PS2010050700621
2062072394747425243477239490902524518245720UQ151PS2009061900031
2072082390896125243939239108692524584745720UQ151PS2009061900030
2082092389227725593502238929662559419145720UQ151PS2010050700620
2092102377721926411742237785862641311045720UQ151PS2010081301050