Overview

Dataset statistics

Number of variables6
Number of observations29
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 KiB
Average record size in memory54.6 B

Variable types

Numeric2
Text1
Categorical1
DateTime2

Dataset

Description인천광역시 서구에 위치한 산사태취약지역 지정현황에 관한 데이터셋입니다. 인천광역시 서구에 위치한 산사태취약지역 지정현황의 소재지지번, 지목, 지정면적에 관한 정보를 포함하고 있습니다.
Author인천광역시 서구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15090810&srcSe=7661IVAWM27C61E190

Alerts

데이터기준일자 has constant value ""Constant
연번 has unique valuesUnique
소재지지번 has unique valuesUnique

Reproduction

Analysis started2024-03-18 04:50:19.639579
Analysis finished2024-03-18 04:50:21.668911
Duration2.03 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15
Minimum1
Maximum29
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2024-03-18T13:50:21.719068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.4
Q18
median15
Q322
95-th percentile27.6
Maximum29
Range28
Interquartile range (IQR)14

Descriptive statistics

Standard deviation8.5146932
Coefficient of variation (CV)0.56764621
Kurtosis-1.2
Mean15
Median Absolute Deviation (MAD)7
Skewness0
Sum435
Variance72.5
MonotonicityStrictly increasing
2024-03-18T13:50:21.816194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
1 1
 
3.4%
2 1
 
3.4%
29 1
 
3.4%
28 1
 
3.4%
27 1
 
3.4%
26 1
 
3.4%
25 1
 
3.4%
24 1
 
3.4%
23 1
 
3.4%
22 1
 
3.4%
Other values (19) 19
65.5%
ValueCountFrequency (%)
1 1
3.4%
2 1
3.4%
3 1
3.4%
4 1
3.4%
5 1
3.4%
6 1
3.4%
7 1
3.4%
8 1
3.4%
9 1
3.4%
10 1
3.4%
ValueCountFrequency (%)
29 1
3.4%
28 1
3.4%
27 1
3.4%
26 1
3.4%
25 1
3.4%
24 1
3.4%
23 1
3.4%
22 1
3.4%
21 1
3.4%
20 1
3.4%

소재지지번
Text

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
2024-03-18T13:50:21.991179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length18
Mean length17.206897
Min length15

Characters and Unicode

Total characters499
Distinct characters40
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

Unique29 ?
Unique (%)100.0%

Sample

1st row인천광역시 서구 시천동 133
2nd row인천광역시 서구 시천동 산37-1
3rd row인천광역시 서구 검암동 산16
4th row인천광역시 서구 검암동 산50-6
5th row인천광역시 서구 공촌동 산155
ValueCountFrequency (%)
인천광역시 29
25.0%
서구 29
25.0%
당하동 6
 
5.2%
마전동 4
 
3.4%
대곡동 3
 
2.6%
심곡동 2
 
1.7%
금곡동 2
 
1.7%
공촌동 2
 
1.7%
산16 2
 
1.7%
검암동 2
 
1.7%
Other values (32) 35
30.2%
2024-03-18T13:50:22.299281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
87
17.4%
천 31
 
6.2%
시 31
 
6.2%
인 29
 
5.8%
광 29
 
5.8%
역 29
 
5.8%
서 29
 
5.8%
구 29
 
5.8%
동 29
 
5.8%
1 24
 
4.8%
Other values (30) 152
30.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 311
62.3%
Space Separator 87
 
17.4%
Decimal Number 86
 
17.2%
Dash Punctuation 15
 
3.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 31
10.0%
시 31
10.0%
인 29
9.3%
광 29
9.3%
역 29
9.3%
서 29
9.3%
구 29
9.3%
동 29
9.3%
산 21
6.8%
곡 7
 
2.3%
Other values (18) 47
15.1%
Decimal Number
ValueCountFrequency (%)
1 24
27.9%
5 14
16.3%
2 11
12.8%
6 10
11.6%
3 10
11.6%
8 6
 
7.0%
4 4
 
4.7%
7 4
 
4.7%
0 2
 
2.3%
9 1
 
1.2%
Space Separator
ValueCountFrequency (%)
87
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 311
62.3%
Common 188
37.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 31
10.0%
시 31
10.0%
인 29
9.3%
광 29
9.3%
역 29
9.3%
서 29
9.3%
구 29
9.3%
동 29
9.3%
산 21
6.8%
곡 7
 
2.3%
Other values (18) 47
15.1%
Common
ValueCountFrequency (%)
87
46.3%
1 24
 
12.8%
- 15
 
8.0%
5 14
 
7.4%
2 11
 
5.9%
6 10
 
5.3%
3 10
 
5.3%
8 6
 
3.2%
4 4
 
2.1%
7 4
 
2.1%
Other values (2) 3
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 311
62.3%
ASCII 188
37.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
87
46.3%
1 24
 
12.8%
- 15
 
8.0%
5 14
 
7.4%
2 11
 
5.9%
6 10
 
5.3%
3 10
 
5.3%
8 6
 
3.2%
4 4
 
2.1%
7 4
 
2.1%
Other values (2) 3
 
1.6%
Hangul
ValueCountFrequency (%)
천 31
10.0%
시 31
10.0%
인 29
9.3%
광 29
9.3%
역 29
9.3%
서 29
9.3%
구 29
9.3%
동 29
9.3%
산 21
6.8%
곡 7
 
2.3%
Other values (18) 47
15.1%

지목
Categorical

Distinct6
Distinct (%)20.7%
Missing0
Missing (%)0.0%
Memory size364.0 B
임
22 
답
 
2
전
 
2
도
 
1
대
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique3 ?
Unique (%)10.3%

Sample

1st row답
2nd row임
3rd row임
4th row임
5th row임

Common Values

ValueCountFrequency (%)
임 22
75.9%
답 2
 
6.9%
전 2
 
6.9%
도 1
 
3.4%
대 1
 
3.4%
장 1
 
3.4%

Length

2024-03-18T13:50:22.406368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T13:50:22.495816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
임 22
75.9%
답 2
 
6.9%
전 2
 
6.9%
도 1
 
3.4%
대 1
 
3.4%
장 1
 
3.4%

지정면적
Real number (ℝ)

Distinct23
Distinct (%)79.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4387.2069
Minimum946
Maximum10600
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2024-03-18T13:50:22.601357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum946
5-th percentile1000
Q12341
median4600
Q35600
95-th percentile8600
Maximum10600
Range9654
Interquartile range (IQR)3259

Descriptive statistics

Standard deviation2456.3853
Coefficient of variation (CV)0.55989729
Kurtosis0.15959802
Mean4387.2069
Median Absolute Deviation (MAD)1400
Skewness0.58734163
Sum127229
Variance6033828.5
MonotonicityNot monotonic
2024-03-18T13:50:22.694864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
4600 3
 
10.3%
1000 2
 
6.9%
8600 2
 
6.9%
5600 2
 
6.9%
3800 2
 
6.9%
3200 1
 
3.4%
1834 1
 
3.4%
1638 1
 
3.4%
2768 1
 
3.4%
4700 1
 
3.4%
Other values (13) 13
44.8%
ValueCountFrequency (%)
946 1
3.4%
1000 2
6.9%
1320 1
3.4%
1638 1
3.4%
1834 1
3.4%
2182 1
3.4%
2341 1
3.4%
2768 1
3.4%
3200 1
3.4%
3500 1
3.4%
ValueCountFrequency (%)
10600 1
3.4%
8600 2
6.9%
7500 1
3.4%
6500 1
3.4%
5800 1
3.4%
5600 2
6.9%
5500 1
3.4%
5400 1
3.4%
4900 1
3.4%
4800 1
3.4%

지정일
Date

Distinct3
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Memory size364.0 B
Minimum2013-10-04 00:00:00
Maximum2015-06-30 00:00:00
2024-03-18T13:50:22.776043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:50:22.845933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=3)

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size364.0 B
Minimum2022-09-01 00:00:00
Maximum2022-09-01 00:00:00
2024-03-18T13:50:22.953004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:50:23.067353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-18T13:50:21.376995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:50:21.189544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:50:21.443308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:50:21.315258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-18T13:50:23.128181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번소재지지번지목지정면적지정일
연번1.0001.0000.3230.0000.000
소재지지번1.0001.0001.0001.0001.000
지목0.3231.0001.0000.0000.000
지정면적0.0001.0000.0001.0000.915
지정일0.0001.0000.0000.9151.000
2024-03-18T13:50:23.210438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번지정면적지목
연번1.0000.1190.112
지정면적0.1191.0000.000
지목0.1120.0001.000

Missing values

2024-03-18T13:50:21.544324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T13:50:21.632876image/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

연번소재지지번지목지정면적지정일데이터기준일자
01인천광역시 서구 시천동 133답32002014-07-302022-09-01
12인천광역시 서구 시천동 산37-1임75002014-07-302022-09-01
23인천광역시 서구 검암동 산16임21822015-06-302022-09-01
34인천광역시 서구 검암동 산50-6임9462015-06-302022-09-01
45인천광역시 서구 공촌동 산155임106002014-07-302022-09-01
56인천광역시 서구 공촌동 산158임10002013-10-042022-09-01
67인천광역시 서구 심곡동 산67임86002014-07-302022-09-01
78인천광역시 서구 심곡동 산52전13202015-06-302022-09-01
89인천광역시 서구 가정동 산7임58002014-07-302022-09-01
910인천광역시 서구 석남동 산2-1임54002014-07-302022-09-01
연번소재지지번지목지정면적지정일데이터기준일자
1920인천광역시 서구 당하동 765-2답55002014-07-302022-09-01
2021인천광역시 서구 당하동 산150임56002014-07-302022-09-01
2122인천광역시 서구 당하동 산135임46002014-07-302022-09-01
2223인천광역시 서구 대곡동 산24임48002014-07-302022-09-01
2324인천광역시 서구 대곡동 산31임47002014-07-302022-09-01
2425인천광역시 서구 대곡동 658-1전46002014-07-302022-09-01
2526인천광역시 서구 금곡동 산138-3임86002014-07-302022-09-01
2627인천광역시 서구 금곡동 산146임27682015-06-302022-09-01
2728인천광역시 서구 왕길동 226-3임56002014-07-302022-09-01
2829인천광역시 서구 왕길동 산12-2임16382015-06-302022-09-01