Overview

Dataset statistics

Number of variables16
Number of observations247
Missing cells148
Missing cells (%)3.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory32.5 KiB
Average record size in memory134.5 B

Variable types

Categorical9
Text3
Numeric4

Dataset

Description경상북도 청손군의 산사태 위험지역에 대한 주소와 위도, 경도, 취약지역 지정사유, 토지의 소유자(국유지,사유지)에 대해 안내합니다.
Author경상북도 청송군
URLhttps://www.data.go.kr/data/15123728/fileData.do

Alerts

관할 has constant value ""Constant
조사지(시도) has constant value ""Constant
조사지(시군구) has constant value ""Constant
위도(도) has constant value ""Constant
소유별 has constant value ""Constant
데이터기준일자 has constant value ""Constant
위도(분) is highly overall correlated with 조사지(읍면동) and 1 other fieldsHigh correlation
경도(분) is highly overall correlated with 조사지(읍면동) and 1 other fieldsHigh correlation
조사지(읍면동) is highly overall correlated with 위도(분) and 2 other fieldsHigh correlation
경도(도) is highly overall correlated with 위도(분) and 2 other fieldsHigh correlation
취약지역유형 is highly imbalanced (50.2%)Imbalance
기타지번 has 148 (59.9%) missing valuesMissing
경도(분) has 21 (8.5%) zerosZeros

Reproduction

Analysis started2023-12-12 08:24:21.728186
Analysis finished2023-12-12 08:24:24.418567
Duration2.69 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관할
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
청송군
247 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
청송군 247
100.0%

Length

2023-12-12T17:24:24.483318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:24:24.577486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
청송군 247
100.0%

조사지(시도)
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
경상북도
247 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경상북도 247
100.0%

Length

2023-12-12T17:24:24.685977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:24:24.782544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상북도 247
100.0%

조사지(시군구)
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
청송군
247 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
청송군 247
100.0%

Length

2023-12-12T17:24:24.874732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:24:24.965219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
청송군 247
100.0%

조사지(읍면동)
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
부남면
56 
현서면
48 
파천면
38 
안덕면
30 
주왕산면
26 
Other values (3)
49 

Length

Max length4
Median length3
Mean length3.1052632
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row현서면
2nd row청송읍
3rd row현동면
4th row현동면
5th row청송읍

Common Values

ValueCountFrequency (%)
부남면 56
22.7%
현서면 48
19.4%
파천면 38
15.4%
안덕면 30
12.1%
주왕산면 26
10.5%
청송읍 18
 
7.3%
현동면 17
 
6.9%
진보면 14
 
5.7%

Length

2023-12-12T17:24:25.067908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:24:25.182742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부남면 56
22.7%
현서면 48
19.4%
파천면 38
15.4%
안덕면 30
12.1%
주왕산면 26
10.5%
청송읍 18
 
7.3%
현동면 17
 
6.9%
진보면 14
 
5.7%

조사지(리)
Text

Distinct66
Distinct (%)26.7%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2023-12-12T17:24:25.426827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.9392713
Min length2

Characters and Unicode

Total characters726
Distinct characters80
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)4.9%

Sample

1st row수락리
2nd row월외리
3rd row도평리
4th row눌인리
5th row거대리
ValueCountFrequency (%)
양숙리 14
 
5.7%
대전리 12
 
4.9%
모계리 9
 
3.6%
이현리 8
 
3.2%
덕천리 8
 
3.2%
부곡리 8
 
3.2%
구천리 7
 
2.8%
두현리 7
 
2.8%
노래리 7
 
2.8%
수락리 7
 
2.8%
Other values (56) 160
64.8%
2023-12-12T17:24:25.811038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 247
34.0%
천 28
 
3.9%
지 19
 
2.6%
현 17
 
2.3%
전 15
 
2.1%
양 14
 
1.9%
숙 14
 
1.9%
평 13
 
1.8%
신 13
 
1.8%
대 13
 
1.8%
Other values (70) 333
45.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 726
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 247
34.0%
천 28
 
3.9%
지 19
 
2.6%
현 17
 
2.3%
전 15
 
2.1%
양 14
 
1.9%
숙 14
 
1.9%
평 13
 
1.8%
신 13
 
1.8%
대 13
 
1.8%
Other values (70) 333
45.9%

Most occurring scripts

ValueCountFrequency (%)
Hangul 726
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 247
34.0%
천 28
 
3.9%
지 19
 
2.6%
현 17
 
2.3%
전 15
 
2.1%
양 14
 
1.9%
숙 14
 
1.9%
평 13
 
1.8%
신 13
 
1.8%
대 13
 
1.8%
Other values (70) 333
45.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 726
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 247
34.0%
천 28
 
3.9%
지 19
 
2.6%
현 17
 
2.3%
전 15
 
2.1%
양 14
 
1.9%
숙 14
 
1.9%
평 13
 
1.8%
신 13
 
1.8%
대 13
 
1.8%
Other values (70) 333
45.9%

지번
Text

Distinct211
Distinct (%)85.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2023-12-12T17:24:26.184462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length8
Mean length5.8704453
Min length3

Characters and Unicode

Total characters1450
Distinct characters26
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

Unique183 ?
Unique (%)74.1%

Sample

1st row산 59 임
2nd row산 31-1 임
3rd row산 94-8
4th row산 94
5th row산 47-1 임
ValueCountFrequency (%)
산 210
33.9%
임 126
20.3%
구 20
 
3.2%
전 6
 
1.0%
53 5
 
0.8%
66 4
 
0.6%
83 4
 
0.6%
8 4
 
0.6%
41 4
 
0.6%
21 4
 
0.6%
Other values (183) 233
37.6%
2023-12-12T17:24:27.185023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
374
25.8%
산 211
14.6%
1 147
 
10.1%
임 126
 
8.7%
2 77
 
5.3%
3 68
 
4.7%
5 59
 
4.1%
6 59
 
4.1%
4 58
 
4.0%
- 56
 
3.9%
Other values (16) 215
14.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 643
44.3%
Other Letter 377
26.0%
Space Separator 374
25.8%
Dash Punctuation 56
 
3.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 211
56.0%
임 126
33.4%
구 20
 
5.3%
전 6
 
1.6%
답 2
 
0.5%
대 2
 
0.5%
천 2
 
0.5%
가 2
 
0.5%
팔 1
 
0.3%
수 1
 
0.3%
Other values (4) 4
 
1.1%
Decimal Number
ValueCountFrequency (%)
1 147
22.9%
2 77
12.0%
3 68
10.6%
5 59
9.2%
6 59
9.2%
4 58
 
9.0%
8 50
 
7.8%
0 45
 
7.0%
7 42
 
6.5%
9 38
 
5.9%
Space Separator
ValueCountFrequency (%)
374
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 56
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1073
74.0%
Hangul 377
 
26.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 211
56.0%
임 126
33.4%
구 20
 
5.3%
전 6
 
1.6%
답 2
 
0.5%
대 2
 
0.5%
천 2
 
0.5%
가 2
 
0.5%
팔 1
 
0.3%
수 1
 
0.3%
Other values (4) 4
 
1.1%
Common
ValueCountFrequency (%)
374
34.9%
1 147
 
13.7%
2 77
 
7.2%
3 68
 
6.3%
5 59
 
5.5%
6 59
 
5.5%
4 58
 
5.4%
- 56
 
5.2%
8 50
 
4.7%
0 45
 
4.2%
Other values (2) 80
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1073
74.0%
Hangul 377
 
26.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
374
34.9%
1 147
 
13.7%
2 77
 
7.2%
3 68
 
6.3%
5 59
 
5.5%
6 59
 
5.5%
4 58
 
5.4%
- 56
 
5.2%
8 50
 
4.7%
0 45
 
4.2%
Other values (2) 80
 
7.5%
Hangul
ValueCountFrequency (%)
산 211
56.0%
임 126
33.4%
구 20
 
5.3%
전 6
 
1.6%
답 2
 
0.5%
대 2
 
0.5%
천 2
 
0.5%
가 2
 
0.5%
팔 1
 
0.3%
수 1
 
0.3%
Other values (4) 4
 
1.1%

기타지번
Text

MISSING 

Distinct98
Distinct (%)99.0%
Missing148
Missing (%)59.9%
Memory size2.1 KiB
2023-12-12T17:24:27.584991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length34
Mean length14.727273
Min length3

Characters and Unicode

Total characters1458
Distinct characters26
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique97 ?
Unique (%)98.0%

Sample

1st row221, 222, 223, 224, 844, 산 93, 226-1
2nd row산 54-1 임
3rd row산 203 임
4th row496 임
5th row690 구
ValueCountFrequency (%)
산 114
27.0%
임 24
 
5.7%
구 14
 
3.3%
전 5
 
1.2%
답 4
 
0.9%
74 3
 
0.7%
557 3
 
0.7%
127 3
 
0.7%
51 2
 
0.5%
304 2
 
0.5%
Other values (223) 249
58.9%
2023-12-12T17:24:28.127985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
326
22.4%
, 158
10.8%
1 135
9.3%
산 114
 
7.8%
2 108
 
7.4%
3 83
 
5.7%
4 75
 
5.1%
5 69
 
4.7%
7 65
 
4.5%
6 58
 
4.0%
Other values (16) 267
18.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 750
51.4%
Space Separator 326
22.4%
Other Letter 169
 
11.6%
Other Punctuation 158
 
10.8%
Dash Punctuation 55
 
3.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 114
67.5%
임 24
 
14.2%
구 14
 
8.3%
전 5
 
3.0%
답 4
 
2.4%
가 1
 
0.6%
도 1
 
0.6%
천 1
 
0.6%
대 1
 
0.6%
목 1
 
0.6%
Other values (3) 3
 
1.8%
Decimal Number
ValueCountFrequency (%)
1 135
18.0%
2 108
14.4%
3 83
11.1%
4 75
10.0%
5 69
9.2%
7 65
8.7%
6 58
7.7%
8 57
7.6%
9 54
 
7.2%
0 46
 
6.1%
Space Separator
ValueCountFrequency (%)
326
100.0%
Other Punctuation
ValueCountFrequency (%)
, 158
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 55
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1289
88.4%
Hangul 169
 
11.6%

Most frequent character per script

Common
ValueCountFrequency (%)
326
25.3%
, 158
12.3%
1 135
10.5%
2 108
 
8.4%
3 83
 
6.4%
4 75
 
5.8%
5 69
 
5.4%
7 65
 
5.0%
6 58
 
4.5%
8 57
 
4.4%
Other values (3) 155
12.0%
Hangul
ValueCountFrequency (%)
산 114
67.5%
임 24
 
14.2%
구 14
 
8.3%
전 5
 
3.0%
답 4
 
2.4%
가 1
 
0.6%
도 1
 
0.6%
천 1
 
0.6%
대 1
 
0.6%
목 1
 
0.6%
Other values (3) 3
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1289
88.4%
Hangul 169
 
11.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
326
25.3%
, 158
12.3%
1 135
10.5%
2 108
 
8.4%
3 83
 
6.4%
4 75
 
5.8%
5 69
 
5.4%
7 65
 
5.0%
6 58
 
4.5%
8 57
 
4.4%
Other values (3) 155
12.0%
Hangul
ValueCountFrequency (%)
산 114
67.5%
임 24
 
14.2%
구 14
 
8.3%
전 5
 
3.0%
답 4
 
2.4%
가 1
 
0.6%
도 1
 
0.6%
천 1
 
0.6%
대 1
 
0.6%
목 1
 
0.6%
Other values (3) 3
 
1.8%

위도(도)
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
36
247 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row36
2nd row36
3rd row36
4th row36
5th row36

Common Values

ValueCountFrequency (%)
36 247
100.0%

Length

2023-12-12T17:24:28.271948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:24:28.374276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
36 247
100.0%

위도(분)
Real number (ℝ)

HIGH CORRELATION 

Distinct25
Distinct (%)10.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.748988
Minimum10
Maximum34
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2023-12-12T17:24:28.509431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile12
Q116
median19
Q325
95-th percentile29
Maximum34
Range24
Interquartile range (IQR)9

Descriptive statistics

Standard deviation5.4818389
Coefficient of variation (CV)0.27757569
Kurtosis-0.78675278
Mean19.748988
Median Absolute Deviation (MAD)4
Skewness0.42573074
Sum4878
Variance30.050558
MonotonicityNot monotonic
2023-12-12T17:24:28.635557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
17 24
 
9.7%
26 22
 
8.9%
18 21
 
8.5%
19 19
 
7.7%
16 19
 
7.7%
14 17
 
6.9%
13 13
 
5.3%
22 13
 
5.3%
15 12
 
4.9%
28 12
 
4.9%
Other values (15) 75
30.4%
ValueCountFrequency (%)
10 2
 
0.8%
11 4
 
1.6%
12 11
4.5%
13 13
5.3%
14 17
6.9%
15 12
4.9%
16 19
7.7%
17 24
9.7%
18 21
8.5%
19 19
7.7%
ValueCountFrequency (%)
34 1
 
0.4%
33 2
 
0.8%
32 1
 
0.4%
31 2
 
0.8%
30 2
 
0.8%
29 6
 
2.4%
28 12
4.9%
27 11
4.5%
26 22
8.9%
25 6
 
2.4%

위도(초)
Real number (ℝ)

Distinct239
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30.659057
Minimum0
Maximum59
Zeros1
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2023-12-12T17:24:28.797640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.7513
Q117.302
median31.999
Q343.1975
95-th percentile54.9684
Maximum59
Range59
Interquartile range (IQR)25.8955

Descriptive statistics

Standard deviation15.907553
Coefficient of variation (CV)0.51885332
Kurtosis-1.0254858
Mean30.659057
Median Absolute Deviation (MAD)12.601
Skewness-0.16291282
Sum7572.787
Variance253.05025
MonotonicityNot monotonic
2023-12-12T17:24:28.941262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
27.299 2
 
0.8%
57.0 2
 
0.8%
2.799 2
 
0.8%
27.099 2
 
0.8%
34.499 2
 
0.8%
31.499 2
 
0.8%
30.999 2
 
0.8%
36.999 2
 
0.8%
37.1 1
 
0.4%
27.713 1
 
0.4%
Other values (229) 229
92.7%
ValueCountFrequency (%)
0.0 1
0.4%
0.999 1
0.4%
1.099 1
0.4%
1.999 1
0.4%
2.0 1
0.4%
2.054 1
0.4%
2.099 1
0.4%
2.616 1
0.4%
2.731 1
0.4%
2.799 2
0.8%
ValueCountFrequency (%)
59.0 1
0.4%
58.999 1
0.4%
58.299 1
0.4%
57.799 1
0.4%
57.499 1
0.4%
57.0 2
0.8%
56.899 1
0.4%
56.085 1
0.4%
55.591 1
0.4%
55.471 1
0.4%

경도(도)
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
129
169 
128
78 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row128
2nd row129
3rd row129
4th row129
5th row129

Common Values

ValueCountFrequency (%)
129 169
68.4%
128 78
31.6%

Length

2023-12-12T17:24:29.084229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:24:29.199964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
129 169
68.4%
128 78
31.6%

경도(분)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.068826
Minimum0
Maximum59
Zeros21
Zeros (%)8.5%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2023-12-12T17:24:29.325490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median7
Q354
95-th percentile58
Maximum59
Range59
Interquartile range (IQR)51

Descriptive statistics

Standard deviation23.979313
Coefficient of variation (CV)1.1381419
Kurtosis-1.3642638
Mean21.068826
Median Absolute Deviation (MAD)6
Skewness0.75054651
Sum5204
Variance575.00744
MonotonicityNot monotonic
2023-12-12T17:24:29.452949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
1 21
 
8.5%
0 21
 
8.5%
58 16
 
6.5%
6 15
 
6.1%
3 15
 
6.1%
4 15
 
6.1%
54 15
 
6.1%
7 15
 
6.1%
2 14
 
5.7%
56 13
 
5.3%
Other values (13) 87
35.2%
ValueCountFrequency (%)
0 21
8.5%
1 21
8.5%
2 14
5.7%
3 15
6.1%
4 15
6.1%
5 9
3.6%
6 15
6.1%
7 15
6.1%
8 13
5.3%
9 3
 
1.2%
ValueCountFrequency (%)
59 10
4.0%
58 16
6.5%
57 4
 
1.6%
56 13
5.3%
55 11
4.5%
54 15
6.1%
53 7
2.8%
52 2
 
0.8%
14 2
 
0.8%
13 2
 
0.8%

경도(초)
Real number (ℝ)

Distinct228
Distinct (%)92.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30.348275
Minimum0.2
Maximum59.392
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2023-12-12T17:24:29.616537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.2
5-th percentile2.4426
Q115.8
median31.563
Q345.388
95-th percentile56.3846
Maximum59.392
Range59.192
Interquartile range (IQR)29.588

Descriptive statistics

Standard deviation17.529954
Coefficient of variation (CV)0.57762602
Kurtosis-1.1816961
Mean30.348275
Median Absolute Deviation (MAD)14.537
Skewness-0.11688862
Sum7496.024
Variance307.29927
MonotonicityNot monotonic
2023-12-12T17:24:29.764958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.8 3
 
1.2%
5.0 3
 
1.2%
10.1 3
 
1.2%
48.6 2
 
0.8%
30.0 2
 
0.8%
24.6 2
 
0.8%
32.6 2
 
0.8%
26.4 2
 
0.8%
43.7 2
 
0.8%
1.2 2
 
0.8%
Other values (218) 224
90.7%
ValueCountFrequency (%)
0.2 1
0.4%
0.621 1
0.4%
0.7 1
0.4%
0.9 2
0.8%
0.902 1
0.4%
1.2 2
0.8%
1.377 1
0.4%
1.783 1
0.4%
2.0 1
0.4%
2.184 1
0.4%
ValueCountFrequency (%)
59.392 1
0.4%
59.053 1
0.4%
59.0 1
0.4%
58.83 1
0.4%
58.3 1
0.4%
58.0 1
0.4%
57.935 1
0.4%
57.9 1
0.4%
57.815 1
0.4%
57.5 1
0.4%

취약지역유형
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
토석류
220 
산사태
27 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
토석류 220
89.1%
산사태 27
 
10.9%

Length

2023-12-12T17:24:29.891009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:24:30.013654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
토석류 220
89.1%
산사태 27
 
10.9%

소유별
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
사유림
247 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사유림 247
100.0%

Length

2023-12-12T17:24:30.112794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:24:30.199477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사유림 247
100.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2023-09-21
247 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-09-21
2nd row2023-09-21
3rd row2023-09-21
4th row2023-09-21
5th row2023-09-21

Common Values

ValueCountFrequency (%)
2023-09-21 247
100.0%

Length

2023-12-12T17:24:30.290853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:24:30.382966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-09-21 247
100.0%

Interactions

2023-12-12T17:24:23.600149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:24:22.343967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:24:22.752494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:24:23.151400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:24:23.722513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:24:22.443454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:24:22.853643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:24:23.250755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:24:23.848339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:24:22.546566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:24:22.955093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:24:23.359586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:24:23.956157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:24:22.652189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:24:23.058430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:24:23.496223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:24:30.449474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
조사지(읍면동)조사지(리)기타지번위도(분)위도(초)경도(도)경도(분)경도(초)취약지역유형
조사지(읍면동)1.0001.0000.9570.8200.2270.9650.7290.2240.107
조사지(리)1.0001.0000.9990.9910.0000.9960.9830.4980.000
기타지번0.9570.9991.0000.9760.9141.0000.9391.0001.000
위도(분)0.8200.9910.9761.0000.0000.6640.6750.0700.000
위도(초)0.2270.0000.9140.0001.0000.0000.0000.3980.000
경도(도)0.9650.9961.0000.6640.0001.0001.0000.3410.000
경도(분)0.7290.9830.9390.6750.0001.0001.0000.3050.049
경도(초)0.2240.4981.0000.0700.3980.3410.3051.0000.000
취약지역유형0.1070.0001.0000.0000.0000.0000.0490.0001.000
2023-12-12T17:24:30.591708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
취약지역유형경도(도)조사지(읍면동)
취약지역유형1.0000.0000.079
경도(도)0.0001.0000.826
조사지(읍면동)0.0790.8261.000
2023-12-12T17:24:30.691114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도(분)위도(초)경도(분)경도(초)조사지(읍면동)경도(도)취약지역유형
위도(분)1.000-0.069-0.447-0.0170.5870.5110.000
위도(초)-0.0691.0000.045-0.1010.1090.0000.000
경도(분)-0.4470.0451.0000.1880.5590.9940.059
경도(초)-0.017-0.1010.1881.0000.1070.2570.000
조사지(읍면동)0.5870.1090.5590.1071.0000.8260.079
경도(도)0.5110.0000.9940.2570.8261.0000.000
취약지역유형0.0000.0000.0590.0000.0790.0001.000

Missing values

2023-12-12T17:24:24.128754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:24:24.343432image/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

관할조사지(시도)조사지(시군구)조사지(읍면동)조사지(리)지번기타지번위도(도)위도(분)위도(초)경도(도)경도(분)경도(초)취약지역유형소유별데이터기준일자
0청송군경상북도청송군현서면수락리산 59 임<NA>361237.11285712.099토석류사유림2023-09-21
1청송군경상북도청송군청송읍월외리산 31-1 임<NA>362657.0129651.999토석류사유림2023-09-21
2청송군경상북도청송군현동면도평리산 94-8221, 222, 223, 224, 844, 산 93, 226-1361710.398129326.588토석류사유림2023-09-21
3청송군경상북도청송군현동면눌인리산 94<NA>36149.344129413.477토석류사유림2023-09-21
4청송군경상북도청송군청송읍거대리산 47-1 임<NA>362447.076129621.092토석류사유림2023-09-21
5청송군경상북도청송군현서면무계리산 54-2 임산 54-1 임361137.9991285758.0토석류사유림2023-09-21
6청송군경상북도청송군현동면눌인리산 120-1 임<NA>361352.99912934.0토석류사유림2023-09-21
7청송군경상북도청송군현동면눌인리산 202 임산 203 임36141.999129156.0토석류사유림2023-09-21
8청송군경상북도청송군현서면월정리산 117 임496 임361239.9991285424.0토석류사유림2023-09-21
9청송군경상북도청송군현서면수락리산 82 임690 구361254.999128564.0토석류사유림2023-09-21
관할조사지(시도)조사지(시군구)조사지(읍면동)조사지(리)지번기타지번위도(도)위도(분)위도(초)경도(도)경도(분)경도(초)취약지역유형소유별데이터기준일자
237청송군경상북도청송군부남면양숙리산 296 임<NA>361733.299129755.4토석류사유림2023-09-21
238청송군경상북도청송군부남면양숙리0-9189 가 팔수식당 주변산<NA>361646.399129843.3토석류사유림2023-09-21
239청송군경상북도청송군부남면화장리산 93 임<NA>361843.799129748.6토석류사유림2023-09-21
240청송군경상북도청송군부남면이현리315 전<NA>361739.6251291149.108토석류사유림2023-09-21
241청송군경상북도청송군부남면이현리산 187-7산 187-736175.39129123.338토석류사유림2023-09-21
242청송군경상북도청송군부남면중기리산 100-1<NA>36152.01291059.0토석류사유림2023-09-21
243청송군경상북도청송군부남면중기리산 1211218, 산 194, 314, 127, 315, 304-1, 123, 316, 304361436.91291030.4토석류사유림2023-09-21
244청송군경상북도청송군부남면이현리산 68<NA>361745.4129112.4토석류사유림2023-09-21
245청송군경상북도청송군부남면중기리산 118산 193, 1218, 130, 131, 129361435.91291045.3토석류사유림2023-09-21
246청송군경상북도청송군부남면이현리산 173산 178, 산 177361729.3129114.4토석류사유림2023-09-21