Overview

Dataset statistics

Number of variables11
Number of observations85
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.7 KiB
Average record size in memory92.6 B

Variable types

Numeric3
DateTime2
Categorical5
Text1

Dataset

Description광산구 내 재난피해_풍수(피해일시,재해명, 피해위치, 피해요인, 업태구분, 시설구분, 시설등급, 피해물량, 피해액 등) 정보를 제공합니다.
Author공공데이터포털
URLhttps://www.data.go.kr/data/15049616/fileData.do

Alerts

피해일시 has constant value ""Constant
재해명 has constant value ""Constant
피해요인 has constant value ""Constant
단위 has constant value ""Constant
데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 업무구분High correlation
피해물량 is highly overall correlated with 피해액(천원)High correlation
피해액(천원) is highly overall correlated with 피해물량High correlation
업무구분 is highly overall correlated with 연번High correlation
시설구분 is highly imbalanced (83.9%)Imbalance
연번 has unique valuesUnique
주소 has unique valuesUnique
피해액(천원) has 25 (29.4%) zerosZeros

Reproduction

Analysis started2024-04-17 13:23:53.875412
Analysis finished2024-04-17 13:23:55.340277
Duration1.46 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct85
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43
Minimum1
Maximum85
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size897.0 B
2024-04-17T22:23:55.413633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.2
Q122
median43
Q364
95-th percentile80.8
Maximum85
Range84
Interquartile range (IQR)42

Descriptive statistics

Standard deviation24.681302
Coefficient of variation (CV)0.57398377
Kurtosis-1.2
Mean43
Median Absolute Deviation (MAD)21
Skewness0
Sum3655
Variance609.16667
MonotonicityStrictly increasing
2024-04-17T22:23:55.530058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.2%
55 1
 
1.2%
63 1
 
1.2%
62 1
 
1.2%
61 1
 
1.2%
60 1
 
1.2%
59 1
 
1.2%
58 1
 
1.2%
57 1
 
1.2%
56 1
 
1.2%
Other values (75) 75
88.2%
ValueCountFrequency (%)
1 1
1.2%
2 1
1.2%
3 1
1.2%
4 1
1.2%
5 1
1.2%
6 1
1.2%
7 1
1.2%
8 1
1.2%
9 1
1.2%
10 1
1.2%
ValueCountFrequency (%)
85 1
1.2%
84 1
1.2%
83 1
1.2%
82 1
1.2%
81 1
1.2%
80 1
1.2%
79 1
1.2%
78 1
1.2%
77 1
1.2%
76 1
1.2%

피해일시
Date

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size812.0 B
Minimum2023-09-03 00:00:00
Maximum2023-09-03 00:00:00
2024-04-17T22:23:55.621415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T22:23:55.703660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

재해명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size812.0 B
태풍
85 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
태풍 85
100.0%

Length

2024-04-17T22:23:55.798454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T22:23:55.881122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
태풍 85
100.0%

주소
Text

UNIQUE 

Distinct85
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size812.0 B
2024-04-17T22:23:56.145128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length68
Median length49
Mean length21.976471
Min length17

Characters and Unicode

Total characters1868
Distinct characters61
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique85 ?
Unique (%)100.0%

Sample

1st row광주광역시 광산구 신촌동 462-1 (외 1필지)
2nd row광주광역시 광산구 진곡동 302-2 진곡동 47-4
3rd row광주광역시 광산구 안청동 5-12
4th row광주광역시 광산구 진곡동 318-1 진곡동 318-4, 318-5, 318-6, 339-11, 339-16, 342-1
5th row광주광역시 광산구 진곡동 300-20 진곡동 300-21, 300-22, 300-32
ValueCountFrequency (%)
광산구 87
22.3%
광주광역시 85
21.7%
신룡동 24
 
6.1%
진곡동 11
 
2.8%
두정동 7
 
1.8%
임곡동 5
 
1.3%
산 5
 
1.3%
요기동 5
 
1.3%
용곡동 5
 
1.3%
외 4
 
1.0%
Other values (133) 153
39.1%
2024-04-17T22:23:56.574581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
341
18.3%
광 257
13.8%
산 107
 
5.7%
동 98
 
5.2%
1 89
 
4.8%
구 87
 
4.7%
역 85
 
4.6%
시 85
 
4.6%
주 85
 
4.6%
- 84
 
4.5%
Other values (51) 550
29.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1000
53.5%
Decimal Number 421
22.5%
Space Separator 341
 
18.3%
Dash Punctuation 84
 
4.5%
Other Punctuation 12
 
0.6%
Open Punctuation 5
 
0.3%
Close Punctuation 5
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 257
25.7%
산 107
10.7%
동 98
 
9.8%
구 87
 
8.7%
역 85
 
8.5%
시 85
 
8.5%
주 85
 
8.5%
신 29
 
2.9%
룡 24
 
2.4%
곡 22
 
2.2%
Other values (36) 121
12.1%
Decimal Number
ValueCountFrequency (%)
1 89
21.1%
2 69
16.4%
3 57
13.5%
4 36
8.6%
6 34
 
8.1%
5 32
 
7.6%
0 31
 
7.4%
8 30
 
7.1%
9 22
 
5.2%
7 21
 
5.0%
Space Separator
ValueCountFrequency (%)
341
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 84
100.0%
Other Punctuation
ValueCountFrequency (%)
, 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1000
53.5%
Common 868
46.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 257
25.7%
산 107
10.7%
동 98
 
9.8%
구 87
 
8.7%
역 85
 
8.5%
시 85
 
8.5%
주 85
 
8.5%
신 29
 
2.9%
룡 24
 
2.4%
곡 22
 
2.2%
Other values (36) 121
12.1%
Common
ValueCountFrequency (%)
341
39.3%
1 89
 
10.3%
- 84
 
9.7%
2 69
 
7.9%
3 57
 
6.6%
4 36
 
4.1%
6 34
 
3.9%
5 32
 
3.7%
0 31
 
3.6%
8 30
 
3.5%
Other values (5) 65
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1000
53.5%
ASCII 868
46.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
341
39.3%
1 89
 
10.3%
- 84
 
9.7%
2 69
 
7.9%
3 57
 
6.6%
4 36
 
4.1%
6 34
 
3.9%
5 32
 
3.7%
0 31
 
3.6%
8 30
 
3.5%
Other values (5) 65
 
7.5%
Hangul
ValueCountFrequency (%)
광 257
25.7%
산 107
10.7%
동 98
 
9.8%
구 87
 
8.7%
역 85
 
8.5%
시 85
 
8.5%
주 85
 
8.5%
신 29
 
2.9%
룡 24
 
2.4%
곡 22
 
2.2%
Other values (36) 121
12.1%

피해요인
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size812.0 B
강풍
85 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
강풍 85
100.0%

Length

2024-04-17T22:23:56.698656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T22:23:56.779267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강풍 85
100.0%

업무구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size812.0 B
농림시설
53 
산림시설
32 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
농림시설 53
62.4%
산림시설 32
37.6%

Length

2024-04-17T22:23:56.860433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T22:23:56.945407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
농림시설 53
62.4%
산림시설 32
37.6%

시설구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size812.0 B
농약대
83 
대파대
 
2

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
농약대 83
97.6%
대파대 2
 
2.4%

Length

2024-04-17T22:23:57.035779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T22:23:57.118292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
농약대 83
97.6%
대파대 2
 
2.4%

피해물량
Real number (ℝ)

HIGH CORRELATION 

Distinct81
Distinct (%)95.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4406.1519
Minimum15
Maximum40893.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size897.0 B
2024-04-17T22:23:57.212976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15
5-th percentile388.9
Q11281
median2245
Q34906
95-th percentile18693.4
Maximum40893.3
Range40878.3
Interquartile range (IQR)3625

Descriptive statistics

Standard deviation6733.4282
Coefficient of variation (CV)1.528188
Kurtosis13.977657
Mean4406.1519
Median Absolute Deviation (MAD)1275
Skewness3.5458877
Sum374522.91
Variance45339056
MonotonicityNot monotonic
2024-04-17T22:23:57.342526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2245.0 2
 
2.4%
926.0 2
 
2.4%
6942.0 2
 
2.4%
80.0 2
 
2.4%
1900.0 1
 
1.2%
1449.0 1
 
1.2%
1281.0 1
 
1.2%
1194.0 1
 
1.2%
1960.0 1
 
1.2%
6329.0 1
 
1.2%
Other values (71) 71
83.5%
ValueCountFrequency (%)
15.0 1
1.2%
80.0 2
2.4%
110.2 1
1.2%
383.0 1
1.2%
412.5 1
1.2%
517.5 1
1.2%
554.0 1
1.2%
580.0 1
1.2%
641.0 1
1.2%
689.0 1
1.2%
ValueCountFrequency (%)
40893.3 1
1.2%
31915.8 1
1.2%
25509.0 1
1.2%
23236.0 1
1.2%
20573.0 1
1.2%
11175.0 1
1.2%
10038.0 1
1.2%
8717.0 1
1.2%
8245.0 1
1.2%
7790.0 1
1.2%

단위
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size812.0 B
㎡
85 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row㎡
2nd row㎡
3rd row㎡
4th row㎡
5th row㎡

Common Values

ValueCountFrequency (%)
㎡ 85
100.0%

Length

2024-04-17T22:23:57.460157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T22:23:57.542481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
㎡ 85
100.0%

피해액(천원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct10
Distinct (%)11.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1058.8235
Minimum0
Maximum6500
Zeros25
Zeros (%)29.4%
Negative0
Negative (%)0.0%
Memory size897.0 B
2024-04-17T22:23:57.614878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1000
Q31500
95-th percentile3000
Maximum6500
Range6500
Interquartile range (IQR)1500

Descriptive statistics

Standard deviation1235.4192
Coefficient of variation (CV)1.1667848
Kurtosis5.8690462
Mean1058.8235
Median Absolute Deviation (MAD)1000
Skewness2.0632717
Sum90000
Variance1526260.5
MonotonicityNot monotonic
2024-04-17T22:23:57.705666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 25
29.4%
1000 20
23.5%
500 17
20.0%
2000 8
 
9.4%
3000 5
 
5.9%
2500 4
 
4.7%
1500 3
 
3.5%
6000 1
 
1.2%
6500 1
 
1.2%
3500 1
 
1.2%
ValueCountFrequency (%)
0 25
29.4%
500 17
20.0%
1000 20
23.5%
1500 3
 
3.5%
2000 8
 
9.4%
2500 4
 
4.7%
3000 5
 
5.9%
3500 1
 
1.2%
6000 1
 
1.2%
6500 1
 
1.2%
ValueCountFrequency (%)
6500 1
 
1.2%
6000 1
 
1.2%
3500 1
 
1.2%
3000 5
 
5.9%
2500 4
 
4.7%
2000 8
 
9.4%
1500 3
 
3.5%
1000 20
23.5%
500 17
20.0%
0 25
29.4%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size812.0 B
Minimum2022-12-31 00:00:00
Maximum2022-12-31 00:00:00
2024-04-17T22:23:57.801259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T22:23:57.878043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-04-17T22:23:54.573322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T22:23:54.131561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T22:23:54.336047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T22:23:54.645750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T22:23:54.190278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T22:23:54.413631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T22:23:54.726322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T22:23:54.258294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T22:23:54.497192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-17T22:23:57.941773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번주소업무구분시설구분피해물량피해액(천원)
연번1.0001.0000.9980.4300.2350.441
주소1.0001.0001.0001.0001.0001.000
업무구분0.9981.0001.0000.0800.2520.174
시설구분0.4301.0000.0801.0000.0000.000
피해물량0.2351.0000.2520.0001.0000.876
피해액(천원)0.4411.0000.1740.0000.8761.000
2024-04-17T22:23:58.027527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설구분업무구분
시설구분1.0000.049
업무구분0.0491.000
2024-04-17T22:23:58.098634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번피해물량피해액(천원)업무구분시설구분
연번1.000-0.455-0.2700.9100.312
피해물량-0.4551.0000.6840.2600.000
피해액(천원)-0.2700.6841.0000.1780.000
업무구분0.9100.2600.1781.0000.049
시설구분0.3120.0000.0000.0491.000

Missing values

2024-04-17T22:23:55.122674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T22:23:55.274671image/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

연번피해일시재해명주소피해요인업무구분시설구분피해물량단위피해액(천원)데이터기준일자
012023-09-03태풍광주광역시 광산구 신촌동 462-1 (외 1필지)강풍농림시설농약대1900.0㎡5002022-12-31
122023-09-03태풍광주광역시 광산구 진곡동 302-2 진곡동 47-4강풍농림시설농약대2700.0㎡10002022-12-31
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342023-09-03태풍광주광역시 광산구 진곡동 318-1 진곡동 318-4, 318-5, 318-6, 339-11, 339-16, 342-1강풍농림시설농약대11175.0㎡30002022-12-31
452023-09-03태풍광주광역시 광산구 진곡동 300-20 진곡동 300-21, 300-22, 300-32강풍농림시설농약대8245.0㎡25002022-12-31
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연번피해일시재해명주소피해요인업무구분시설구분피해물량단위피해액(천원)데이터기준일자
75762023-09-03태풍광주광역시 광산구 두정동 183강풍산림시설농약대2644.8㎡10002022-12-31
76772023-09-03태풍광주광역시 광산구 두정동 251-5강풍산림시설농약대1230.0㎡5002022-12-31
77782023-09-03태풍광주광역시 광산구 신룡동 산 61-1강풍산림시설농약대6682.5㎡35002022-12-31
78792023-09-03태풍광주광역시 광산구 우산동 741-3 광산구 우산동 741-3강풍산림시설농약대1000.0㎡5002022-12-31
79802023-09-03태풍광주광역시 광산구 신룡동 1-14강풍산림시설농약대1332.9㎡5002022-12-31
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81822023-09-03태풍광주광역시 광산구 두정동 529-7강풍산림시설농약대1354.4㎡5002022-12-31
82832023-09-03태풍광주광역시 광산구 사호동 214강풍산림시설농약대1356.0㎡5002022-12-31
83842023-09-03태풍광주광역시 광산구 선암동 29-11강풍산림시설대파대110.2㎡02022-12-31
84852023-09-03태풍광주광역시 광산구 선암동 29-1강풍산림시설대파대15.0㎡02022-12-31