Overview

Dataset statistics

Number of variables4
Number of observations211
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.1 KiB
Average record size in memory34.6 B

Variable types

Text1
Categorical1
Numeric2

Dataset

Description충청남도 천안시 도시계획정보시스템(UPIS) 방재시설 현황으로 현황도형 관리번호, 라벨명 등의 항목을 제공합니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=14&beforeMenuCd=DOM_000000201001001000&publicdatapk=15123196

Alerts

면적_도형 is highly overall correlated with 길이_도형 and 1 other fieldsHigh correlation
길이_도형 is highly overall correlated with 면적_도형High correlation
라벨명 is highly overall correlated with 면적_도형High correlation
현황도형 관리번호 has unique valuesUnique
면적_도형 has unique valuesUnique
길이_도형 has unique valuesUnique

Reproduction

Analysis started2024-01-09 22:44:30.400678
Analysis finished2024-01-09 22:44:30.909728
Duration0.51 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

현황도형 관리번호
Text

UNIQUE 

Distinct211
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-01-10T07:44:31.027531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters5064
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

Unique211 ?
Unique (%)100.0%

Sample

1st row44130UQ156PS200812010054
2nd row44130UQ156PS200812010055
3rd row44130UQ156PS200812010057
4th row44130UQ156PS200812010058
5th row44130UQ156PS200812010061
ValueCountFrequency (%)
44130uq156ps200812010054 1
 
0.5%
44130uq156ps201303210014 1
 
0.5%
44130uq156ps200407200001 1
 
0.5%
44130uq156ps201607110685 1
 
0.5%
44130uq156ps201510264520 1
 
0.5%
44130uq156ps200812010117 1
 
0.5%
44130uq156ps201812200002 1
 
0.5%
44130uq156ps200812010025 1
 
0.5%
44130uq156ps200812010029 1
 
0.5%
44130uq156ps202003270031 1
 
0.5%
Other values (201) 201
95.3%
2024-01-10T07:44:31.298090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1198
23.7%
1 942
18.6%
2 479
 
9.5%
4 478
 
9.4%
6 273
 
5.4%
3 269
 
5.3%
5 267
 
5.3%
8 214
 
4.2%
U 211
 
4.2%
Q 211
 
4.2%
Other values (4) 522
10.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4220
83.3%
Uppercase Letter 844
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1198
28.4%
1 942
22.3%
2 479
 
11.4%
4 478
 
11.3%
6 273
 
6.5%
3 269
 
6.4%
5 267
 
6.3%
8 214
 
5.1%
7 51
 
1.2%
9 49
 
1.2%
Uppercase Letter
ValueCountFrequency (%)
U 211
25.0%
Q 211
25.0%
P 211
25.0%
S 211
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4220
83.3%
Latin 844
 
16.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1198
28.4%
1 942
22.3%
2 479
 
11.4%
4 478
 
11.3%
6 273
 
6.5%
3 269
 
6.4%
5 267
 
6.3%
8 214
 
5.1%
7 51
 
1.2%
9 49
 
1.2%
Latin
ValueCountFrequency (%)
U 211
25.0%
Q 211
25.0%
P 211
25.0%
S 211
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5064
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1198
23.7%
1 942
18.6%
2 479
 
9.5%
4 478
 
9.4%
6 273
 
5.4%
3 269
 
5.3%
5 267
 
5.3%
8 214
 
4.2%
U 211
 
4.2%
Q 211
 
4.2%
Other values (4) 522
10.3%

라벨명
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
소하천
144 
지방2급하천
26 
저류시설
18 
유수시설
 
13
기타하천시설
 
5
Other values (3)
 
5

Length

Max length7
Median length3
Mean length3.6635071
Min length3

Unique

Unique2 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
소하천 144
68.2%
지방2급하천 26
 
12.3%
저류시설 18
 
8.5%
유수시설 13
 
6.2%
기타하천시설 5
 
2.4%
기타저수지시설 3
 
1.4%
국가하천 1
 
0.5%
지방1급하천 1
 
0.5%

Length

2024-01-10T07:44:31.437982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:44:31.562289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
소하천 144
68.2%
지방2급하천 26
 
12.3%
저류시설 18
 
8.5%
유수시설 13
 
6.2%
기타하천시설 5
 
2.4%
기타저수지시설 3
 
1.4%
국가하천 1
 
0.5%
지방1급하천 1
 
0.5%

면적_도형
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct211
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean90452.157
Minimum277.16875
Maximum2045627.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-01-10T07:44:31.677630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum277.16875
5-th percentile4531.5614
Q110011.408
median21316.811
Q342885.904
95-th percentile430801.48
Maximum2045627.7
Range2045350.5
Interquartile range (IQR)32874.496

Descriptive statistics

Standard deviation265505.61
Coefficient of variation (CV)2.9353154
Kurtosis26.621311
Mean90452.157
Median Absolute Deviation (MAD)13209.173
Skewness4.9819278
Sum19085405
Variance7.0493229 × 1010
MonotonicityNot monotonic
2024-01-10T07:44:31.811172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6457.819847 1
 
0.5%
561133.7735 1
 
0.5%
96251.41091 1
 
0.5%
25393.72781 1
 
0.5%
264223.2621 1
 
0.5%
813984.6092 1
 
0.5%
1525090.894 1
 
0.5%
4174.31503 1
 
0.5%
4566.761229 1
 
0.5%
102474.9186 1
 
0.5%
Other values (201) 201
95.3%
ValueCountFrequency (%)
277.1687477 1
0.5%
550.1530821 1
0.5%
835.03322 1
0.5%
1278.071725 1
0.5%
1564.292921 1
0.5%
2274.651627 1
0.5%
3723.122356 1
0.5%
3767.721955 1
0.5%
4105.276366 1
0.5%
4174.31503 1
0.5%
ValueCountFrequency (%)
2045627.687 1
0.5%
1553423.01 1
0.5%
1525090.894 1
0.5%
1481935.595 1
0.5%
1205520.221 1
0.5%
929422.411 1
0.5%
922012.5211 1
0.5%
813984.6092 1
0.5%
561133.7735 1
0.5%
472285.0843 1
0.5%

길이_도형
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct211
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4244.5495
Minimum66.724638
Maximum52911.715
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-01-10T07:44:32.182091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum66.724638
5-th percentile328.6441
Q11479.2956
median3035.3328
Q34642.2477
95-th percentile13823.449
Maximum52911.715
Range52844.99
Interquartile range (IQR)3162.9522

Descriptive statistics

Standard deviation5872.0149
Coefficient of variation (CV)1.3834248
Kurtosis27.826331
Mean4244.5495
Median Absolute Deviation (MAD)1591.2847
Skewness4.6030988
Sum895599.94
Variance34480558
MonotonicityNot monotonic
2024-01-10T07:44:32.315269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4352.272542 1
 
0.5%
22915.76669 1
 
0.5%
7618.907024 1
 
0.5%
2910.413313 1
 
0.5%
4738.060279 1
 
0.5%
28322.0796 1
 
0.5%
29583.90386 1
 
0.5%
290.3856377 1
 
0.5%
284.0077683 1
 
0.5%
1829.645123 1
 
0.5%
Other values (201) 201
95.3%
ValueCountFrequency (%)
66.72463787 1
0.5%
97.6998374 1
0.5%
116.5192017 1
0.5%
173.0817121 1
0.5%
183.3168802 1
0.5%
210.9256811 1
0.5%
282.4740905 1
0.5%
284.0077683 1
0.5%
290.3856377 1
0.5%
301.3007817 1
0.5%
ValueCountFrequency (%)
52911.71464 1
0.5%
31727.19058 1
0.5%
29583.90386 1
0.5%
28322.0796 1
0.5%
27640.26739 1
0.5%
22915.76669 1
0.5%
18951.90404 1
0.5%
17690.15829 1
0.5%
15161.98923 1
0.5%
14718.64067 1
0.5%

Interactions

2024-01-10T07:44:30.653550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:44:30.490332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:44:30.728003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:44:30.574996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T07:44:32.408794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
라벨명면적_도형길이_도형
라벨명1.0000.9130.554
면적_도형0.9131.0000.892
길이_도형0.5540.8921.000
2024-01-10T07:44:32.501304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
면적_도형길이_도형라벨명
면적_도형1.0000.8950.551
길이_도형0.8951.0000.336
라벨명0.5510.3361.000

Missing values

2024-01-10T07:44:30.811893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T07:44:30.881229image/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

현황도형 관리번호라벨명면적_도형길이_도형
044130UQ156PS200812010054소하천6457.8198474352.272542
144130UQ156PS200812010055소하천26393.542454049.607025
244130UQ156PS200812010057소하천42929.837233166.760058
344130UQ156PS200812010058소하천39318.594523914.206043
444130UQ156PS200812010061소하천8388.4900262190.898483
544130UQ156PS200812010063소하천18289.26293006.603863
644130UQ156PS200801030001소하천19973.224713944.892388
744130UQ156PS200812010066소하천21470.561124238.809476
844130UQ156PS200812010067소하천20881.067842859.128245
944130UQ156PS200812010068소하천12400.967972486.048127
현황도형 관리번호라벨명면적_도형길이_도형
20144130UQ156PS200812010043소하천30935.713534180.00911
20244130UQ156PS200812010044소하천8798.6579321633.879198
20344130UQ156PS200812010045소하천14993.027543408.957264
20444130UQ156PS200812010046소하천5185.7272531175.219816
20544130UQ156PS200812010047소하천52721.887616331.912445
20644130UQ156PS200812010048소하천12129.387793259.00959
20744130UQ156PS200812010050소하천4105.2763661298.994426
20844130UQ156PS200812010051소하천5176.4175811304.869913
20944130UQ156PS200812010052소하천8254.5736141784.072487
21044130UQ156PS200812010053소하천5911.0906311671.073453