Overview

Dataset statistics

Number of variables5
Number of observations10000
Missing cells10139
Missing cells (%)20.3%
Duplicate rows68
Duplicate rows (%)0.7%
Total size in memory498.0 KiB
Average record size in memory51.0 B

Variable types

Numeric3
Text2

Dataset

Description지역의 급경사지 위치 및 위험성 등 부분적 정보제공
Author충청남도
URLhttps://alldam.chungnam.go.kr/bigdata/collect/view.chungnam?menuCd=DOM_000000201001001000&apiIdx=3022

Alerts

Dataset has 68 (0.7%) duplicate rowsDuplicates
비탈면용도(보호목적)코드 has 1822 (18.2%) missing valuesMissing
주소 has 8317 (83.2%) missing valuesMissing

Reproduction

Analysis started2024-01-09 21:13:15.692495
Analysis finished2024-01-09 21:13:17.683374
Duration1.99 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지역코드
Real number (ℝ)

Distinct4772
Distinct (%)47.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.3108434 × 109
Minimum1.1110101 × 109
Maximum5.183035 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:13:17.752487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1110101 × 109
5-th percentile1.1710104 × 109
Q14.183034 × 109
median4.679034 × 109
Q34.8330253 × 109
95-th percentile5.1770253 × 109
Maximum5.183035 × 109
Range4.0720249 × 109
Interquartile range (IQR)6.499913 × 108

Descriptive statistics

Standard deviation9.8147899 × 108
Coefficient of variation (CV)0.22767679
Kurtosis3.3367227
Mean4.3108434 × 109
Median Absolute Deviation (MAD)2.6402183 × 108
Skewness-1.9752055
Sum4.3108434 × 1013
Variance9.6330102 × 1017
MonotonicityNot monotonic
2024-01-10T06:13:17.885090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5179025027 34
 
0.3%
5181032024 33
 
0.3%
5121011200 28
 
0.3%
1154510300 23
 
0.2%
5176036027 19
 
0.2%
1126010100 19
 
0.2%
4825011800 17
 
0.2%
1162010200 17
 
0.2%
5177025923 17
 
0.2%
1126010600 16
 
0.2%
Other values (4762) 9777
97.8%
ValueCountFrequency (%)
1111010100 1
 
< 0.1%
1111016500 2
 
< 0.1%
1111017000 1
 
< 0.1%
1111017300 1
 
< 0.1%
1111017400 7
0.1%
1111017800 1
 
< 0.1%
1111018100 1
 
< 0.1%
1111018200 3
< 0.1%
1111018300 6
0.1%
1111018400 3
< 0.1%
ValueCountFrequency (%)
5183035031 1
 
< 0.1%
5183034038 2
< 0.1%
5183034031 3
< 0.1%
5183034030 2
< 0.1%
5183034025 1
 
< 0.1%
5183033030 2
< 0.1%
5183033028 1
 
< 0.1%
5183033026 2
< 0.1%
5183033023 1
 
< 0.1%
5183032040 1
 
< 0.1%

비탈면용도(보호목적)코드
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)0.1%
Missing1822
Missing (%)18.2%
Infinite0
Infinite (%)0.0%
Mean2.1438004
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:13:17.994789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q33
95-th percentile6
Maximum6
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.7165857
Coefficient of variation (CV)0.80072083
Kurtosis0.18541865
Mean2.1438004
Median Absolute Deviation (MAD)0
Skewness1.2698443
Sum17532
Variance2.9466663
MonotonicityNot monotonic
2024-01-10T06:13:18.086603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 5048
50.5%
3 1220
 
12.2%
6 850
 
8.5%
2 456
 
4.6%
5 396
 
4.0%
4 208
 
2.1%
(Missing) 1822
 
18.2%
ValueCountFrequency (%)
1 5048
50.5%
2 456
 
4.6%
3 1220
 
12.2%
4 208
 
2.1%
5 396
 
4.0%
6 850
 
8.5%
ValueCountFrequency (%)
6 850
 
8.5%
5 396
 
4.0%
4 208
 
2.1%
3 1220
 
12.2%
2 456
 
4.6%
1 5048
50.5%

급경사지명
Text

Distinct9635
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-01-10T06:13:18.429223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length25
Mean length8.7952
Min length1

Characters and Unicode

Total characters87952
Distinct characters556
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9326 ?
Unique (%)93.3%

Sample

1st row경남 하동 북천 직전 N1지구
2nd row홍천-82
3rd row무등산시계탑~전망대
4th row경기 가평 조종 운악 N5지구
5th row신창
ValueCountFrequency (%)
n1지구 694
 
3.4%
n2지구 342
 
1.7%
경북 282
 
1.4%
경기 280
 
1.4%
경남 271
 
1.3%
충청 259
 
1.3%
강원 243
 
1.2%
n3지구 197
 
1.0%
전남 178
 
0.9%
충북 156
 
0.8%
Other values (9873) 17279
85.6%
2024-01-10T06:13:18.950585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10181
 
11.6%
지 5908
 
6.7%
구 5413
 
6.2%
1 4176
 
4.7%
2 2518
 
2.9%
- 2184
 
2.5%
N 1867
 
2.1%
0 1854
 
2.1%
동 1786
 
2.0%
경 1725
 
2.0%
Other values (546) 50340
57.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 55234
62.8%
Decimal Number 16010
 
18.2%
Space Separator 10181
 
11.6%
Dash Punctuation 2184
 
2.5%
Uppercase Letter 1944
 
2.2%
Open Punctuation 1083
 
1.2%
Close Punctuation 1080
 
1.2%
Lowercase Letter 95
 
0.1%
Math Symbol 80
 
0.1%
Other Punctuation 46
 
0.1%
Other values (2) 15
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 5908
 
10.7%
구 5413
 
9.8%
동 1786
 
3.2%
경 1725
 
3.1%
산 1415
 
2.6%
남 1136
 
2.1%
선 998
 
1.8%
북 976
 
1.8%
원 969
 
1.8%
천 865
 
1.6%
Other values (492) 34043
61.6%
Uppercase Letter
ValueCountFrequency (%)
N 1867
96.0%
A 18
 
0.9%
S 12
 
0.6%
T 10
 
0.5%
P 7
 
0.4%
H 6
 
0.3%
D 6
 
0.3%
M 5
 
0.3%
C 3
 
0.2%
B 3
 
0.2%
Other values (5) 7
 
0.4%
Lowercase Letter
ValueCountFrequency (%)
k 41
43.2%
t 9
 
9.5%
s 9
 
9.5%
e 8
 
8.4%
m 7
 
7.4%
d 6
 
6.3%
a 4
 
4.2%
g 3
 
3.2%
z 2
 
2.1%
i 2
 
2.1%
Other values (4) 4
 
4.2%
Decimal Number
ValueCountFrequency (%)
1 4176
26.1%
2 2518
15.7%
0 1854
11.6%
3 1688
10.5%
4 1531
 
9.6%
5 1035
 
6.5%
6 977
 
6.1%
7 859
 
5.4%
8 760
 
4.7%
9 612
 
3.8%
Other Punctuation
ValueCountFrequency (%)
& 9
19.6%
; 9
19.6%
# 9
19.6%
@ 8
17.4%
. 6
13.0%
! 3
 
6.5%
: 1
 
2.2%
/ 1
 
2.2%
Space Separator
ValueCountFrequency (%)
10181
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2184
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1083
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1080
100.0%
Math Symbol
ValueCountFrequency (%)
~ 80
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 14
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 55234
62.8%
Common 30679
34.9%
Latin 2039
 
2.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 5908
 
10.7%
구 5413
 
9.8%
동 1786
 
3.2%
경 1725
 
3.1%
산 1415
 
2.6%
남 1136
 
2.1%
선 998
 
1.8%
북 976
 
1.8%
원 969
 
1.8%
천 865
 
1.6%
Other values (492) 34043
61.6%
Latin
ValueCountFrequency (%)
N 1867
91.6%
k 41
 
2.0%
A 18
 
0.9%
S 12
 
0.6%
T 10
 
0.5%
t 9
 
0.4%
s 9
 
0.4%
e 8
 
0.4%
m 7
 
0.3%
P 7
 
0.3%
Other values (19) 51
 
2.5%
Common
ValueCountFrequency (%)
10181
33.2%
1 4176
13.6%
2 2518
 
8.2%
- 2184
 
7.1%
0 1854
 
6.0%
3 1688
 
5.5%
4 1531
 
5.0%
( 1083
 
3.5%
) 1080
 
3.5%
5 1035
 
3.4%
Other values (15) 3349
 
10.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 55231
62.8%
ASCII 32718
37.2%
Compat Jamo 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10181
31.1%
1 4176
12.8%
2 2518
 
7.7%
- 2184
 
6.7%
N 1867
 
5.7%
0 1854
 
5.7%
3 1688
 
5.2%
4 1531
 
4.7%
( 1083
 
3.3%
) 1080
 
3.3%
Other values (44) 4556
13.9%
Hangul
ValueCountFrequency (%)
지 5908
 
10.7%
구 5413
 
9.8%
동 1786
 
3.2%
경 1725
 
3.1%
산 1415
 
2.6%
남 1136
 
2.1%
선 998
 
1.8%
북 976
 
1.8%
원 969
 
1.8%
천 865
 
1.6%
Other values (491) 34040
61.6%
Compat Jamo
ValueCountFrequency (%)
ㅎ 3
100.0%

관리주체구분
Real number (ℝ)

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.2701
Minimum1
Maximum99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:13:19.080663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q38
95-th percentile9
Maximum99
Range98
Interquartile range (IQR)7

Descriptive statistics

Standard deviation12.84985
Coefficient of variation (CV)2.4382555
Kurtosis46.298139
Mean5.2701
Median Absolute Deviation (MAD)0
Skewness6.7384397
Sum52701
Variance165.11866
MonotonicityNot monotonic
2024-01-10T06:13:19.211996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1 5286
52.9%
8 1757
 
17.6%
5 1361
 
13.6%
9 633
 
6.3%
7 326
 
3.3%
3 233
 
2.3%
99 174
 
1.7%
2 157
 
1.6%
4 55
 
0.5%
6 16
 
0.2%
ValueCountFrequency (%)
1 5286
52.9%
2 157
 
1.6%
3 233
 
2.3%
4 55
 
0.5%
5 1361
 
13.6%
6 16
 
0.2%
7 326
 
3.3%
8 1757
 
17.6%
9 633
 
6.3%
10 2
 
< 0.1%
ValueCountFrequency (%)
99 174
 
1.7%
10 2
 
< 0.1%
9 633
 
6.3%
8 1757
17.6%
7 326
 
3.3%
6 16
 
0.2%
5 1361
13.6%
4 55
 
0.5%
3 233
 
2.3%
2 157
 
1.6%

주소
Text

MISSING 

Distinct1414
Distinct (%)84.0%
Missing8317
Missing (%)83.2%
Memory size156.2 KiB
2024-01-10T06:13:19.526055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length37
Mean length12.252525
Min length1

Characters and Unicode

Total characters20621
Distinct characters487
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1326 ?
Unique (%)78.8%

Sample

1st row환경사업소 입구
2nd row천동 자연관찰로
3rd row군도6 모릿재
4th row덕수산업
5th row번지 일원
ValueCountFrequency (%)
영동선 81
 
2.2%
일원 69
 
1.9%
좌 67
 
1.8%
우 51
 
1.4%
중앙선 45
 
1.2%
강릉선 34
 
0.9%
서원기(현 33
 
0.9%
상선 33
 
0.9%
뒤 32
 
0.9%
부근 29
 
0.8%
Other values (2139) 3201
87.1%
2024-01-10T06:13:20.052952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1992
 
9.7%
0 854
 
4.1%
1 785
 
3.8%
) 614
 
3.0%
( 613
 
3.0%
선 567
 
2.7%
2 551
 
2.7%
- 515
 
2.5%
4 490
 
2.4%
5 431
 
2.1%
Other values (477) 13209
64.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11284
54.7%
Decimal Number 4565
22.1%
Space Separator 1992
 
9.7%
Close Punctuation 615
 
3.0%
Open Punctuation 615
 
3.0%
Lowercase Letter 546
 
2.6%
Dash Punctuation 515
 
2.5%
Other Punctuation 285
 
1.4%
Math Symbol 174
 
0.8%
Uppercase Letter 30
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
선 567
 
5.0%
도 366
 
3.2%
지 332
 
2.9%
동 322
 
2.9%
산 309
 
2.7%
원 251
 
2.2%
간 238
 
2.1%
호 227
 
2.0%
리 219
 
1.9%
아 195
 
1.7%
Other values (436) 8258
73.2%
Uppercase Letter
ValueCountFrequency (%)
K 11
36.7%
I 4
 
13.3%
P 3
 
10.0%
C 3
 
10.0%
A 2
 
6.7%
T 2
 
6.7%
B 1
 
3.3%
R 1
 
3.3%
V 1
 
3.3%
L 1
 
3.3%
Decimal Number
ValueCountFrequency (%)
0 854
18.7%
1 785
17.2%
2 551
12.1%
4 490
10.7%
5 431
9.4%
3 355
7.8%
8 307
 
6.7%
6 305
 
6.7%
9 250
 
5.5%
7 237
 
5.2%
Other Punctuation
ValueCountFrequency (%)
. 110
38.6%
# 55
19.3%
& 55
19.3%
; 55
19.3%
/ 8
 
2.8%
: 2
 
0.7%
Lowercase Letter
ValueCountFrequency (%)
k 372
68.1%
m 169
31.0%
t 2
 
0.4%
e 2
 
0.4%
s 1
 
0.2%
Math Symbol
ValueCountFrequency (%)
~ 172
98.9%
+ 1
 
0.6%
= 1
 
0.6%
Close Punctuation
ValueCountFrequency (%)
) 614
99.8%
] 1
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 613
99.7%
[ 2
 
0.3%
Space Separator
ValueCountFrequency (%)
1992
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 515
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11284
54.7%
Common 8761
42.5%
Latin 576
 
2.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
선 567
 
5.0%
도 366
 
3.2%
지 332
 
2.9%
동 322
 
2.9%
산 309
 
2.7%
원 251
 
2.2%
간 238
 
2.1%
호 227
 
2.0%
리 219
 
1.9%
아 195
 
1.7%
Other values (436) 8258
73.2%
Common
ValueCountFrequency (%)
1992
22.7%
0 854
9.7%
1 785
 
9.0%
) 614
 
7.0%
( 613
 
7.0%
2 551
 
6.3%
- 515
 
5.9%
4 490
 
5.6%
5 431
 
4.9%
3 355
 
4.1%
Other values (15) 1561
17.8%
Latin
ValueCountFrequency (%)
k 372
64.6%
m 169
29.3%
K 11
 
1.9%
I 4
 
0.7%
P 3
 
0.5%
C 3
 
0.5%
t 2
 
0.3%
e 2
 
0.3%
A 2
 
0.3%
T 2
 
0.3%
Other values (6) 6
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11278
54.7%
ASCII 9337
45.3%
Compat Jamo 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1992
21.3%
0 854
9.1%
1 785
 
8.4%
) 614
 
6.6%
( 613
 
6.6%
2 551
 
5.9%
- 515
 
5.5%
4 490
 
5.2%
5 431
 
4.6%
k 372
 
4.0%
Other values (31) 2120
22.7%
Hangul
ValueCountFrequency (%)
선 567
 
5.0%
도 366
 
3.2%
지 332
 
2.9%
동 322
 
2.9%
산 309
 
2.7%
원 251
 
2.2%
간 238
 
2.1%
호 227
 
2.0%
리 219
 
1.9%
아 195
 
1.7%
Other values (432) 8252
73.2%
Compat Jamo
ValueCountFrequency (%)
ㄹ 2
33.3%
ㅇ 2
33.3%
ㄴ 1
16.7%
ㅁ 1
16.7%

Interactions

2024-01-10T06:13:16.902334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:13:16.374505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:13:16.638753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:13:17.000437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:13:16.462788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:13:16.738905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:13:17.112744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:13:16.551696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:13:16.819295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T06:13:20.166167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역코드비탈면용도(보호목적)코드관리주체구분
지역코드1.0000.3240.185
비탈면용도(보호목적)코드0.3241.0000.238
관리주체구분0.1850.2381.000
2024-01-10T06:13:20.288974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역코드비탈면용도(보호목적)코드관리주체구분
지역코드1.000-0.082-0.160
비탈면용도(보호목적)코드-0.0821.0000.276
관리주체구분-0.1600.2761.000

Missing values

2024-01-10T06:13:17.223895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:13:17.556969image/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.
2024-01-10T06:13:17.635580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

지역코드비탈면용도(보호목적)코드급경사지명관리주체구분주소
2600548850390231경남 하동 북천 직전 N1지구1<NA>
1276451720390235홍천-827<NA>
534529110110001무등산시계탑~전망대1<NA>
1547041820345283경기 가평 조종 운악 N5지구8<NA>
662329200118005신창8<NA>
968411680103003NDMS_테스트!!!2<NA>
1101143730380211이백지구1환경사업소 입구
84143800250345천동지구(소백 03-02-01)7천동 자연관찰로
373826710310331일광면 용천리산229-81<NA>
178145720250001가막11<NA>
지역코드비탈면용도(보호목적)코드급경사지명관리주체구분주소
538128720360216영흥지구198<NA>
119074423032022<NA>충청 호남고속335<NA>
2599848840250281평현51봉성~서면 경계 지점
120873611032024<NA>수청굴 경부 상행선5번지선
2376948250117001어방12지구1<NA>
1039345720340241전북 진안 상전 월포 N4지구8<NA>
2674448890430243경남 합천 삼가 일부 N1지구8<NA>
281251790340251삼일6지구(북부지소)1<NA>
1753346780253215벌교1지구1<NA>
1108343730380351충북 옥천 군북 국원 N4지구1<NA>

Duplicate rows

Most frequently occurring

지역코드비탈면용도(보호목적)코드급경사지명관리주체구분주소# duplicates
4447750315245상의지구7<NA>5
6451790310211유촌지구(본청)1<NA>5
3846870253371백수읍 구수리2<NA>4
6151150370285소금강지구7<NA>4
111230105002답십리동아아파트8<NA>3
311380114006자연비탈7<NA>3
92771025329<NA>논공북리지구1<NA>3
144141010600<NA>군급305<NA>3
3446830320256금정면남송지구2<NA>3
4547750315275절골지구7<NA>3