Overview

Dataset statistics

Number of variables6
Number of observations2595
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory126.8 KiB
Average record size in memory50.0 B

Variable types

Text2
Categorical2
Numeric2

Dataset

Description전북특별자치도 진안군 도시계획정보시스템 도면이미지에 대한 데이터로, 도면이미지 관리번호, 도면 이미지이름, 파일 확장자명 등의 정보를 제공합니다.
Author전북특별자치도 진안군
URLhttps://www.data.go.kr/data/15119120/fileData.do

Alerts

파일 확장자명 has constant value ""Constant
생성일시 is highly imbalanced (69.3%)Imbalance
도면 이미지 관리번호 has unique valuesUnique
도면 이미지이름 has unique valuesUnique

Reproduction

Analysis started2024-03-15 00:08:30.924833
Analysis finished2024-03-15 00:08:32.841861
Duration1.92 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

도면 이미지 관리번호
Text

UNIQUE 

Distinct2595
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size20.4 KiB
2024-03-15T09:08:33.404076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters51900
Distinct characters13
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

Unique2595 ?
Unique (%)100.0%

Sample

1st row45720DRI200812260789
2nd row45720DRI200812260790
3rd row45720DRI200812260791
4th row45720DRI200812260792
5th row45720DRI200812260793
ValueCountFrequency (%)
45720dri200812260789 1
 
< 0.1%
45720dri201806292281 1
 
< 0.1%
45720dri201301181064 1
 
< 0.1%
45720dri201301181072 1
 
< 0.1%
45720dri201301181065 1
 
< 0.1%
45720dri201301181066 1
 
< 0.1%
45720dri201301181067 1
 
< 0.1%
45720dri201301181068 1
 
< 0.1%
45720dri201301181069 1
 
< 0.1%
45720dri201301181070 1
 
< 0.1%
Other values (2585) 2585
99.6%
2024-03-15T09:08:34.343882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10684
20.6%
2 8371
16.1%
1 5770
11.1%
7 3938
 
7.6%
5 3910
 
7.5%
4 3601
 
6.9%
D 2595
 
5.0%
R 2595
 
5.0%
I 2595
 
5.0%
9 2370
 
4.6%
Other values (3) 5471
10.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 44115
85.0%
Uppercase Letter 7785
 
15.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10684
24.2%
2 8371
19.0%
1 5770
13.1%
7 3938
 
8.9%
5 3910
 
8.9%
4 3601
 
8.2%
9 2370
 
5.4%
6 2258
 
5.1%
8 1855
 
4.2%
3 1358
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
D 2595
33.3%
R 2595
33.3%
I 2595
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 44115
85.0%
Latin 7785
 
15.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10684
24.2%
2 8371
19.0%
1 5770
13.1%
7 3938
 
8.9%
5 3910
 
8.9%
4 3601
 
8.2%
9 2370
 
5.4%
6 2258
 
5.1%
8 1855
 
4.2%
3 1358
 
3.1%
Latin
ValueCountFrequency (%)
D 2595
33.3%
R 2595
33.3%
I 2595
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 51900
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10684
20.6%
2 8371
16.1%
1 5770
11.1%
7 3938
 
7.6%
5 3910
 
7.5%
4 3601
 
6.9%
D 2595
 
5.0%
R 2595
 
5.0%
I 2595
 
5.0%
9 2370
 
4.6%
Other values (3) 5471
10.5%

도면 이미지이름
Text

UNIQUE 

Distinct2595
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size20.4 KiB
2024-03-15T09:08:35.185263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length78
Median length68
Mean length55.006936
Min length29

Characters and Unicode

Total characters142743
Distinct characters211
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2595 ?
Unique (%)100.0%

Sample

1st row전라북도_2008-497_2008-12-26_106_진안군관리계획(관리지역세분)결정고시도(진안087)_지역
2nd row전라북도_2008-497_2008-12-26_107_진안군관리계획(관리지역세분)결정고시도(진안088)_지역
3rd row전라북도_2008-497_2008-12-26_108_진안군관리계획(관리지역세분)결정고시도(진안089)_지역
4th row전라북도_2008-497_2008-12-26_109_진안군관리계획(관리지역세분)결정고시도(진안090)_지역
5th row전라북도_2008-497_2008-12-26_113_진안군관리계획(관리지역세분)결정고시도(진안091)
ValueCountFrequency (%)
도시계획시설(공원_월랑공원)지형도면 8
 
0.3%
결정도 4
 
0.2%
저수지 3
 
0.1%
진안군 3
 
0.1%
유통업무설비 2
 
0.1%
보행환경개선지구 2
 
0.1%
위치도 2
 
0.1%
전라북도_2012-137_2012-06-08_002_노촌지구 2
 
0.1%
지형도면고시도 2
 
0.1%
진안군_2011-75_2011-12-23_086_진안군관리계획(용도지구-자연취락지구)결정도(임실008)_지구 1
 
< 0.1%
Other values (2633) 2633
98.9%
2024-03-15T09:08:36.672985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 16306
 
11.4%
_ 11448
 
8.0%
1 9771
 
6.8%
2 8974
 
6.3%
- 8026
 
5.6%
도 5849
 
4.1%
안 4600
 
3.2%
진 4599
 
3.2%
( 4260
 
3.0%
) 4260
 
3.0%
Other values (201) 64650
45.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 56329
39.5%
Decimal Number 54339
38.1%
Connector Punctuation 11448
 
8.0%
Dash Punctuation 8026
 
5.6%
Open Punctuation 4426
 
3.1%
Close Punctuation 4426
 
3.1%
Space Separator 2661
 
1.9%
Uppercase Letter 485
 
0.3%
Math Symbol 465
 
0.3%
Other Punctuation 135
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 5849
 
10.4%
안 4600
 
8.2%
진 4599
 
8.2%
군 3500
 
6.2%
지 3011
 
5.3%
획 2378
 
4.2%
계 2369
 
4.2%
정 2292
 
4.1%
관 2288
 
4.1%
리 2250
 
4.0%
Other values (172) 23193
41.2%
Decimal Number
ValueCountFrequency (%)
0 16306
30.0%
1 9771
18.0%
2 8974
16.5%
9 3603
 
6.6%
8 3084
 
5.7%
5 2958
 
5.4%
7 2865
 
5.3%
3 2587
 
4.8%
6 2273
 
4.2%
4 1918
 
3.5%
Uppercase Letter
ValueCountFrequency (%)
S 465
95.9%
I 16
 
3.3%
N 1
 
0.2%
D 1
 
0.2%
E 1
 
0.2%
X 1
 
0.2%
Lowercase Letter
ValueCountFrequency (%)
g 1
33.3%
p 1
33.3%
j 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 4260
96.2%
[ 166
 
3.8%
Close Punctuation
ValueCountFrequency (%)
) 4260
96.2%
] 166
 
3.8%
Other Punctuation
ValueCountFrequency (%)
, 130
96.3%
. 5
 
3.7%
Connector Punctuation
ValueCountFrequency (%)
_ 11448
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8026
100.0%
Space Separator
ValueCountFrequency (%)
2661
100.0%
Math Symbol
ValueCountFrequency (%)
= 465
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 85926
60.2%
Hangul 56329
39.5%
Latin 488
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 5849
 
10.4%
안 4600
 
8.2%
진 4599
 
8.2%
군 3500
 
6.2%
지 3011
 
5.3%
획 2378
 
4.2%
계 2369
 
4.2%
정 2292
 
4.1%
관 2288
 
4.1%
리 2250
 
4.0%
Other values (172) 23193
41.2%
Common
ValueCountFrequency (%)
0 16306
19.0%
_ 11448
13.3%
1 9771
11.4%
2 8974
10.4%
- 8026
9.3%
( 4260
 
5.0%
) 4260
 
5.0%
9 3603
 
4.2%
8 3084
 
3.6%
5 2958
 
3.4%
Other values (10) 13236
15.4%
Latin
ValueCountFrequency (%)
S 465
95.3%
I 16
 
3.3%
N 1
 
0.2%
D 1
 
0.2%
E 1
 
0.2%
X 1
 
0.2%
g 1
 
0.2%
p 1
 
0.2%
j 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 86414
60.5%
Hangul 56329
39.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 16306
18.9%
_ 11448
13.2%
1 9771
11.3%
2 8974
10.4%
- 8026
9.3%
( 4260
 
4.9%
) 4260
 
4.9%
9 3603
 
4.2%
8 3084
 
3.6%
5 2958
 
3.4%
Other values (19) 13724
15.9%
Hangul
ValueCountFrequency (%)
도 5849
 
10.4%
안 4600
 
8.2%
진 4599
 
8.2%
군 3500
 
6.2%
지 3011
 
5.3%
획 2378
 
4.2%
계 2369
 
4.2%
정 2292
 
4.1%
관 2288
 
4.1%
리 2250
 
4.0%
Other values (172) 23193
41.2%

파일 확장자명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size20.4 KiB
jpg
2595 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
jpg 2595
100.0%

Length

2024-03-15T09:08:37.019395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T09:08:37.369565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
jpg 2595
100.0%

이미지 가로 해상도
Real number (ℝ)

Distinct561
Distinct (%)21.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4045.9037
Minimum334
Maximum11984
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.9 KiB
2024-03-15T09:08:37.768109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum334
5-th percentile3494
Q13842
median3842
Q34168
95-th percentile5355.8
Maximum11984
Range11650
Interquartile range (IQR)326

Descriptive statistics

Standard deviation664.87948
Coefficient of variation (CV)0.16433399
Kurtosis35.749922
Mean4045.9037
Median Absolute Deviation (MAD)63
Skewness3.9382321
Sum10499120
Variance442064.73
MonotonicityNot monotonic
2024-03-15T09:08:38.400884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3842 1038
40.0%
4168 368
 
14.2%
3905 174
 
6.7%
3779 167
 
6.4%
4393 45
 
1.7%
5900 34
 
1.3%
4238 25
 
1.0%
6000 14
 
0.5%
3464 13
 
0.5%
4678 10
 
0.4%
Other values (551) 707
27.2%
ValueCountFrequency (%)
334 1
< 0.1%
335 2
0.1%
599 1
< 0.1%
1653 1
< 0.1%
1754 1
< 0.1%
1900 1
< 0.1%
2245 2
0.1%
2312 1
< 0.1%
2479 2
0.1%
2598 2
0.1%
ValueCountFrequency (%)
11984 1
< 0.1%
11760 1
< 0.1%
10672 1
< 0.1%
10629 1
< 0.1%
10586 1
< 0.1%
10252 1
< 0.1%
10009 1
< 0.1%
9974 1
< 0.1%
7086 1
< 0.1%
6736 1
< 0.1%

이미지 세로 해상도
Real number (ℝ)

Distinct548
Distinct (%)21.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5259.8212
Minimum475
Maximum9552
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.9 KiB
2024-03-15T09:08:38.866597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum475
5-th percentile3657
Q15116
median5300
Q35679.5
95-th percentile5980
Maximum9552
Range9077
Interquartile range (IQR)563.5

Descriptive statistics

Standard deviation646.74093
Coefficient of variation (CV)0.12295873
Kurtosis7.6451672
Mean5259.8212
Median Absolute Deviation (MAD)196
Skewness-1.89024
Sum13649236
Variance418273.82
MonotonicityNot monotonic
2024-03-15T09:08:39.300833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5900 470
 
18.1%
5300 83
 
3.2%
5299 63
 
2.4%
5314 45
 
1.7%
6000 43
 
1.7%
5332 42
 
1.6%
5315 35
 
1.3%
5290 35
 
1.3%
5298 35
 
1.3%
5333 34
 
1.3%
Other values (538) 1710
65.9%
ValueCountFrequency (%)
475 2
0.1%
484 1
< 0.1%
876 1
< 0.1%
1981 1
< 0.1%
1984 1
< 0.1%
2190 1
< 0.1%
2337 1
< 0.1%
2373 1
< 0.1%
2474 1
< 0.1%
2482 1
< 0.1%
ValueCountFrequency (%)
9552 1
< 0.1%
6623 1
< 0.1%
6537 1
< 0.1%
6533 1
< 0.1%
6480 1
< 0.1%
6429 1
< 0.1%
6412 2
0.1%
6382 1
< 0.1%
6376 1
< 0.1%
6363 1
< 0.1%

생성일시
Categorical

IMBALANCE 

Distinct17
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size20.4 KiB
2013-01-31
1978 
2018-11-23
370 
2016-01-21
 
134
2020-08-03
 
26
2018-07-19
 
25
Other values (12)
 
62

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique3 ?
Unique (%)0.1%

Sample

1st row2013-01-31
2nd row2013-01-31
3rd row2013-01-31
4th row2013-01-31
5th row2013-01-31

Common Values

ValueCountFrequency (%)
2013-01-31 1978
76.2%
2018-11-23 370
 
14.3%
2016-01-21 134
 
5.2%
2020-08-03 26
 
1.0%
2018-07-19 25
 
1.0%
2016-07-04 17
 
0.7%
2022-11-30 10
 
0.4%
2016-04-05 8
 
0.3%
2021-09-30 7
 
0.3%
2021-06-30 5
 
0.2%
Other values (7) 15
 
0.6%

Length

2024-03-15T09:08:39.728886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2013-01-31 1978
76.2%
2018-11-23 370
 
14.3%
2016-01-21 134
 
5.2%
2020-08-03 26
 
1.0%
2018-07-19 25
 
1.0%
2016-07-04 17
 
0.7%
2022-11-30 10
 
0.4%
2016-04-05 8
 
0.3%
2021-09-30 7
 
0.3%
2021-06-30 5
 
0.2%
Other values (7) 15
 
0.6%

Interactions

2024-03-15T09:08:31.941528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:08:31.408617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:08:32.215538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:08:31.681026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T09:08:39.972929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
이미지 가로 해상도이미지 세로 해상도생성일시
이미지 가로 해상도1.0000.8980.569
이미지 세로 해상도0.8981.0000.660
생성일시0.5690.6601.000
2024-03-15T09:08:40.243185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
이미지 가로 해상도이미지 세로 해상도생성일시
이미지 가로 해상도1.0000.3530.277
이미지 세로 해상도0.3531.0000.334
생성일시0.2770.3341.000

Missing values

2024-03-15T09:08:32.472473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T09:08:32.687058image/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

도면 이미지 관리번호도면 이미지이름파일 확장자명이미지 가로 해상도이미지 세로 해상도생성일시
045720DRI200812260789전라북도_2008-497_2008-12-26_106_진안군관리계획(관리지역세분)결정고시도(진안087)_지역jpg356450462013-01-31
145720DRI200812260790전라북도_2008-497_2008-12-26_107_진안군관리계획(관리지역세분)결정고시도(진안088)_지역jpg353350622013-01-31
245720DRI200812260791전라북도_2008-497_2008-12-26_108_진안군관리계획(관리지역세분)결정고시도(진안089)_지역jpg357650432013-01-31
345720DRI200812260792전라북도_2008-497_2008-12-26_109_진안군관리계획(관리지역세분)결정고시도(진안090)_지역jpg359051052013-01-31
445720DRI200812260793전라북도_2008-497_2008-12-26_113_진안군관리계획(관리지역세분)결정고시도(진안091)jpg354250572013-01-31
545720DRI200812260794전라북도_2008-497_2008-12-26_114_진안군관리계획(관리지역세분)결정고시도(진안092)jpg354250892013-01-31
645720DRI200812260795전라북도_2008-497_2008-12-26_115_진안군관리계획(관리지역세분)결정고시도(진안093)jpg349650362013-01-31
745720DRI200812260796전라북도_2008-497_2008-12-26_116_진안군관리계획(관리지역세분)결정고시도(진안094)jpg344750822013-01-31
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