Overview

Dataset statistics

Number of variables7
Number of observations10000
Missing cells1691
Missing cells (%)2.4%
Duplicate rows3
Duplicate rows (%)< 0.1%
Total size in memory654.3 KiB
Average record size in memory67.0 B

Variable types

Text4
Numeric3

Dataset

Description부산광역시 도시공간정보시스템 내에 지반 시추 정보에 대한 현황 입니다.(프로젝트 명, 시추 공 코드, 고도, 시추 공명 등)
Author부산광역시
URLhttps://www.data.go.kr/data/15080798/fileData.do

Alerts

Dataset has 3 (< 0.1%) duplicate rowsDuplicates
좌표(GRS80_X) is highly overall correlated with 좌표(GRS80_Y)High correlation
좌표(GRS80_Y) is highly overall correlated with 좌표(GRS80_X)High correlation
시추공코드 has 336 (3.4%) missing valuesMissing
시추공명 has 336 (3.4%) missing valuesMissing
고도 has 337 (3.4%) missing valuesMissing
좌표(GRS80_X) has 337 (3.4%) missing valuesMissing
좌표(GRS80_Y) has 337 (3.4%) missing valuesMissing
고도 is highly skewed (γ1 = 98.29885323)Skewed
고도 has 941 (9.4%) zerosZeros

Reproduction

Analysis started2024-04-29 22:48:15.979927
Analysis finished2024-04-29 22:48:19.660146
Duration3.68 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

프로젝트코드
Text

Distinct547
Distinct (%)5.5%
Missing3
Missing (%)< 0.1%
Memory size156.2 KiB
2024-04-30T07:48:19.906902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length5
Mean length4.9405822
Min length4

Characters and Unicode

Total characters49391
Distinct characters25
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)0.4%

Sample

1st rowP0330
2nd rowP1204
3rd row(부록1
4th rowP0642
5th rowB0577
ValueCountFrequency (%)
부록1 338
 
3.4%
p0570 336
 
3.4%
p0316 329
 
3.3%
p0330 266
 
2.7%
p0871 152
 
1.5%
p0532 141
 
1.4%
p0936 140
 
1.4%
b7206 135
 
1.4%
p0530 133
 
1.3%
b0488 124
 
1.2%
Other values (537) 7903
79.1%
2024-04-30T07:48:20.387041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7301
14.8%
B 4714
9.5%
2 3971
8.0%
5 3908
7.9%
3 3860
7.8%
1 3843
7.8%
P 3505
7.1%
4 3430
6.9%
6 3273
 
6.6%
7 3174
 
6.4%
Other values (15) 8412
17.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 38153
77.2%
Uppercase Letter 10209
 
20.7%
Other Letter 676
 
1.4%
Open Punctuation 338
 
0.7%
Other Punctuation 14
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7301
19.1%
2 3971
10.4%
5 3908
10.2%
3 3860
10.1%
1 3843
10.1%
4 3430
9.0%
6 3273
8.6%
7 3174
8.3%
8 3117
8.2%
9 2276
 
6.0%
Uppercase Letter
ValueCountFrequency (%)
B 4714
46.2%
P 3505
34.3%
W 1116
 
10.9%
S 546
 
5.3%
K 243
 
2.4%
R 76
 
0.7%
M 5
 
< 0.1%
H 3
 
< 0.1%
D 1
 
< 0.1%
Other Letter
ValueCountFrequency (%)
부 338
50.0%
록 338
50.0%
Other Punctuation
ValueCountFrequency (%)
, 8
57.1%
. 6
42.9%
Open Punctuation
ValueCountFrequency (%)
( 338
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 38506
78.0%
Latin 10209
 
20.7%
Hangul 676
 
1.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7301
19.0%
2 3971
10.3%
5 3908
10.1%
3 3860
10.0%
1 3843
10.0%
4 3430
8.9%
6 3273
8.5%
7 3174
8.2%
8 3117
8.1%
9 2276
 
5.9%
Other values (4) 353
 
0.9%
Latin
ValueCountFrequency (%)
B 4714
46.2%
P 3505
34.3%
W 1116
 
10.9%
S 546
 
5.3%
K 243
 
2.4%
R 76
 
0.7%
M 5
 
< 0.1%
H 3
 
< 0.1%
D 1
 
< 0.1%
Hangul
ValueCountFrequency (%)
부 338
50.0%
록 338
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 48715
98.6%
Hangul 676
 
1.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7301
15.0%
B 4714
9.7%
2 3971
8.2%
5 3908
8.0%
3 3860
7.9%
1 3843
7.9%
P 3505
7.2%
4 3430
7.0%
6 3273
6.7%
7 3174
6.5%
Other values (13) 7736
15.9%
Hangul
ValueCountFrequency (%)
부 338
50.0%
록 338
50.0%

프로젝트명
Text

Distinct535
Distinct (%)5.4%
Missing5
Missing (%)< 0.1%
Memory size156.2 KiB
2024-04-30T07:48:20.641599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length41
Mean length26.092846
Min length3

Characters and Unicode

Total characters260798
Distinct characters383
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)0.4%

Sample

1st row부산 정관신도시 건설공사 토질조사보고서
2nd row해안순환도로 건설사업(북항구간) 기본설계
3rd row2)"
4th row장림하수처리장 2단계 건설 차집관로 2공구공사(지하굴착에 따른 지하흙막이 공사와 관련한) 검토보고서
5th row부산~울산고속국도 민간투자사업 건설공사(4공구)
ValueCountFrequency (%)
지반조사 2138
 
5.0%
건설공사 1570
 
3.7%
실시설계 1524
 
3.6%
지반조사보고서 1269
 
3.0%
및 1246
 
2.9%
부산 1132
 
2.7%
토질조사보고서 808
 
1.9%
지질조사보고서 794
 
1.9%
기본 683
 
1.6%
기타공사 674
 
1.6%
Other values (1037) 30522
72.1%
2024-04-30T07:48:21.039476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
32513
 
12.5%
사 14131
 
5.4%
지 9446
 
3.6%
공 9116
 
3.5%
부 8797
 
3.4%
산 8663
 
3.3%
설 7618
 
2.9%
조 7322
 
2.8%
구 6138
 
2.4%
고 6029
 
2.3%
Other values (373) 151025
57.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 201939
77.4%
Space Separator 32513
 
12.5%
Decimal Number 10107
 
3.9%
Close Punctuation 5156
 
2.0%
Open Punctuation 4832
 
1.9%
Math Symbol 2261
 
0.9%
Uppercase Letter 1362
 
0.5%
Dash Punctuation 1328
 
0.5%
Other Punctuation 1290
 
0.5%
Connector Punctuation 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 14131
 
7.0%
지 9446
 
4.7%
공 9116
 
4.5%
부 8797
 
4.4%
산 8663
 
4.3%
설 7618
 
3.8%
조 7322
 
3.6%
구 6138
 
3.0%
고 6029
 
3.0%
반 5033
 
2.5%
Other values (325) 119646
59.2%
Uppercase Letter
ValueCountFrequency (%)
B 437
32.1%
L 341
25.0%
A 196
14.4%
I 150
 
11.0%
C 75
 
5.5%
T 68
 
5.0%
S 19
 
1.4%
P 18
 
1.3%
M 11
 
0.8%
H 9
 
0.7%
Other values (8) 38
 
2.8%
Decimal Number
ValueCountFrequency (%)
2 2546
25.2%
1 2449
24.2%
3 1502
14.9%
4 1492
14.8%
0 786
 
7.8%
5 596
 
5.9%
9 224
 
2.2%
6 214
 
2.1%
7 198
 
2.0%
8 100
 
1.0%
Other Punctuation
ValueCountFrequency (%)
, 360
27.9%
" 338
26.2%
: 245
19.0%
. 229
17.8%
· 53
 
4.1%
/ 20
 
1.6%
; 15
 
1.2%
& 15
 
1.2%
# 15
 
1.2%
Math Symbol
ValueCountFrequency (%)
~ 2209
97.7%
～ 37
 
1.6%
∼ 15
 
0.7%
Close Punctuation
ValueCountFrequency (%)
) 4829
93.7%
] 327
 
6.3%
Open Punctuation
ValueCountFrequency (%)
( 4491
92.9%
[ 341
 
7.1%
Space Separator
ValueCountFrequency (%)
32513
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1328
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 9
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 201939
77.4%
Common 57496
 
22.0%
Latin 1363
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 14131
 
7.0%
지 9446
 
4.7%
공 9116
 
4.5%
부 8797
 
4.4%
산 8663
 
4.3%
설 7618
 
3.8%
조 7322
 
3.6%
구 6138
 
3.0%
고 6029
 
3.0%
반 5033
 
2.5%
Other values (325) 119646
59.2%
Common
ValueCountFrequency (%)
32513
56.5%
) 4829
 
8.4%
( 4491
 
7.8%
2 2546
 
4.4%
1 2449
 
4.3%
~ 2209
 
3.8%
3 1502
 
2.6%
4 1492
 
2.6%
- 1328
 
2.3%
0 786
 
1.4%
Other values (19) 3351
 
5.8%
Latin
ValueCountFrequency (%)
B 437
32.1%
L 341
25.0%
A 196
14.4%
I 150
 
11.0%
C 75
 
5.5%
T 68
 
5.0%
S 19
 
1.4%
P 18
 
1.3%
M 11
 
0.8%
H 9
 
0.7%
Other values (9) 39
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 201925
77.4%
ASCII 58753
 
22.5%
None 90
 
< 0.1%
Math Operators 15
 
< 0.1%
Compat Jamo 14
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
32513
55.3%
) 4829
 
8.2%
( 4491
 
7.6%
2 2546
 
4.3%
1 2449
 
4.2%
~ 2209
 
3.8%
3 1502
 
2.6%
4 1492
 
2.5%
- 1328
 
2.3%
0 786
 
1.3%
Other values (34) 4608
 
7.8%
Hangul
ValueCountFrequency (%)
사 14131
 
7.0%
지 9446
 
4.7%
공 9116
 
4.5%
부 8797
 
4.4%
산 8663
 
4.3%
설 7618
 
3.8%
조 7322
 
3.6%
구 6138
 
3.0%
고 6029
 
3.0%
반 5033
 
2.5%
Other values (324) 119632
59.2%
None
ValueCountFrequency (%)
· 53
58.9%
～ 37
41.1%
Math Operators
ValueCountFrequency (%)
∼ 15
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅇ 14
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

시추공코드
Text

MISSING 

Distinct9664
Distinct (%)100.0%
Missing336
Missing (%)3.4%
Memory size156.2 KiB
2024-04-30T07:48:21.253171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.9650248
Min length8

Characters and Unicode

Total characters96302
Distinct characters22
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

Unique9664 ?
Unique (%)100.0%

Sample

1st rowP0330BH083
2nd rowP1204BH030
3rd rowP0316BH242
4th rowP0642BH026
5th rowB0577BB026
ValueCountFrequency (%)
b7315bh035 1
 
< 0.1%
bs056b0007 1
 
< 0.1%
p0572sb066 1
 
< 0.1%
w4629bh005 1
 
< 0.1%
p0532cb139 1
 
< 0.1%
p0330bb064 1
 
< 0.1%
b5487bh007 1
 
< 0.1%
b2248bh028 1
 
< 0.1%
p0852bh039 1
 
< 0.1%
b2136bh030 1
 
< 0.1%
Other values (9654) 9654
99.9%
2024-04-30T07:48:21.602262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 21004
21.8%
B 15215
15.8%
1 7399
 
7.7%
2 6592
 
6.8%
H 6316
 
6.6%
3 5858
 
6.1%
5 5253
 
5.5%
4 4969
 
5.2%
6 4496
 
4.7%
7 4306
 
4.5%
Other values (12) 14894
15.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 67264
69.8%
Uppercase Letter 29038
30.2%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
B 15215
52.4%
H 6316
21.8%
P 3798
 
13.1%
W 1116
 
3.8%
S 1018
 
3.5%
T 602
 
2.1%
C 412
 
1.4%
K 243
 
0.8%
A 235
 
0.8%
R 77
 
0.3%
Other values (2) 6
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
0 21004
31.2%
1 7399
 
11.0%
2 6592
 
9.8%
3 5858
 
8.7%
5 5253
 
7.8%
4 4969
 
7.4%
6 4496
 
6.7%
7 4306
 
6.4%
8 4148
 
6.2%
9 3239
 
4.8%

Most occurring scripts

ValueCountFrequency (%)
Common 67264
69.8%
Latin 29038
30.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
B 15215
52.4%
H 6316
21.8%
P 3798
 
13.1%
W 1116
 
3.8%
S 1018
 
3.5%
T 602
 
2.1%
C 412
 
1.4%
K 243
 
0.8%
A 235
 
0.8%
R 77
 
0.3%
Other values (2) 6
 
< 0.1%
Common
ValueCountFrequency (%)
0 21004
31.2%
1 7399
 
11.0%
2 6592
 
9.8%
3 5858
 
8.7%
5 5253
 
7.8%
4 4969
 
7.4%
6 4496
 
6.7%
7 4306
 
6.4%
8 4148
 
6.2%
9 3239
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 96302
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 21004
21.8%
B 15215
15.8%
1 7399
 
7.7%
2 6592
 
6.8%
H 6316
 
6.6%
3 5858
 
6.1%
5 5253
 
5.5%
4 4969
 
5.2%
6 4496
 
4.7%
7 4306
 
4.5%
Other values (12) 14894
15.5%

시추공명
Text

MISSING 

Distinct3612
Distinct (%)37.4%
Missing336
Missing (%)3.4%
Memory size156.2 KiB
2024-04-30T07:48:21.920800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length25
Mean length5.020178
Min length1

Characters and Unicode

Total characters48515
Distinct characters178
Distinct categories13 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2589 ?
Unique (%)26.8%

Sample

1st row회로차
2nd rowBH-40
3rd rowB-162
4th rowBH-26
5th row26좌광천
ValueCountFrequency (%)
bh-1 251
 
2.5%
bh-2 238
 
2.4%
bh-3 191
 
1.9%
bh-4 163
 
1.6%
bh-5 142
 
1.4%
bh-6 123
 
1.2%
bh-7 111
 
1.1%
bh-8 94
 
0.9%
bh-10 86
 
0.9%
bh-9 75
 
0.8%
Other values (3470) 8525
85.3%
2024-04-30T07:48:22.383980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 9815
20.2%
B 8638
17.8%
H 5244
10.8%
1 4175
 
8.6%
2 2904
 
6.0%
3 2010
 
4.1%
4 1626
 
3.4%
0 1291
 
2.7%
5 1276
 
2.6%
6 1039
 
2.1%
Other values (168) 10497
21.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 18456
38.0%
Decimal Number 16947
34.9%
Dash Punctuation 9815
20.2%
Other Letter 2058
 
4.2%
Close Punctuation 355
 
0.7%
Open Punctuation 355
 
0.7%
Space Separator 341
 
0.7%
Other Punctuation 83
 
0.2%
Math Symbol 44
 
0.1%
Lowercase Letter 37
 
0.1%
Other values (3) 24
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
정 127
 
6.2%
교 93
 
4.5%
가 82
 
4.0%
고 78
 
3.8%
송 76
 
3.7%
로 75
 
3.6%
광 74
 
3.6%
관 74
 
3.6%
제 70
 
3.4%
선 54
 
2.6%
Other values (117) 1255
61.0%
Uppercase Letter
ValueCountFrequency (%)
B 8638
46.8%
H 5244
28.4%
N 920
 
5.0%
T 740
 
4.0%
C 514
 
2.8%
P 503
 
2.7%
S 494
 
2.7%
A 487
 
2.6%
L 152
 
0.8%
M 141
 
0.8%
Other values (13) 623
 
3.4%
Decimal Number
ValueCountFrequency (%)
1 4175
24.6%
2 2904
17.1%
3 2010
11.9%
4 1626
 
9.6%
0 1291
 
7.6%
5 1276
 
7.5%
6 1039
 
6.1%
7 955
 
5.6%
8 884
 
5.2%
9 787
 
4.6%
Lowercase Letter
ValueCountFrequency (%)
b 20
54.1%
h 13
35.1%
n 1
 
2.7%
x 1
 
2.7%
m 1
 
2.7%
j 1
 
2.7%
Other Punctuation
ValueCountFrequency (%)
. 55
66.3%
/ 20
 
24.1%
, 7
 
8.4%
* 1
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 9815
100.0%
Close Punctuation
ValueCountFrequency (%)
) 355
100.0%
Open Punctuation
ValueCountFrequency (%)
( 355
100.0%
Space Separator
ValueCountFrequency (%)
341
100.0%
Math Symbol
ValueCountFrequency (%)
+ 44
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 20
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%
Other Symbol
ValueCountFrequency (%)
® 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 27964
57.6%
Latin 18493
38.1%
Hangul 2058
 
4.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
정 127
 
6.2%
교 93
 
4.5%
가 82
 
4.0%
고 78
 
3.8%
송 76
 
3.7%
로 75
 
3.6%
광 74
 
3.6%
관 74
 
3.6%
제 70
 
3.4%
선 54
 
2.6%
Other values (117) 1255
61.0%
Latin
ValueCountFrequency (%)
B 8638
46.7%
H 5244
28.4%
N 920
 
5.0%
T 740
 
4.0%
C 514
 
2.8%
P 503
 
2.7%
S 494
 
2.7%
A 487
 
2.6%
L 152
 
0.8%
M 141
 
0.8%
Other values (19) 660
 
3.6%
Common
ValueCountFrequency (%)
- 9815
35.1%
1 4175
14.9%
2 2904
 
10.4%
3 2010
 
7.2%
4 1626
 
5.8%
0 1291
 
4.6%
5 1276
 
4.6%
6 1039
 
3.7%
7 955
 
3.4%
8 884
 
3.2%
Other values (12) 1989
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46456
95.8%
Hangul 2058
 
4.2%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 9815
21.1%
B 8638
18.6%
H 5244
11.3%
1 4175
9.0%
2 2904
 
6.3%
3 2010
 
4.3%
4 1626
 
3.5%
0 1291
 
2.8%
5 1276
 
2.7%
6 1039
 
2.2%
Other values (40) 8438
18.2%
Hangul
ValueCountFrequency (%)
정 127
 
6.2%
교 93
 
4.5%
가 82
 
4.0%
고 78
 
3.8%
송 76
 
3.7%
로 75
 
3.6%
광 74
 
3.6%
관 74
 
3.6%
제 70
 
3.4%
선 54
 
2.6%
Other values (117) 1255
61.0%
None
ValueCountFrequency (%)
® 1
100.0%

고도
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct4001
Distinct (%)41.4%
Missing337
Missing (%)3.4%
Infinite0
Infinite (%)0.0%
Mean210.71307
Minimum-118.58
Maximum1583642
Zeros941
Zeros (%)9.4%
Negative538
Negative (%)5.4%
Memory size166.0 KiB
2024-04-30T07:48:22.536595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-118.58
5-th percentile-0.467
Q12.1
median19.5
Q398.15
95-th percentile147.99
Maximum1583642
Range1583760.6
Interquartile range (IQR)96.05

Descriptive statistics

Standard deviation16109.82
Coefficient of variation (CV)76.453825
Kurtosis9662.7763
Mean210.71307
Median Absolute Deviation (MAD)19.5
Skewness98.298853
Sum2036120.4
Variance2.595263 × 108
MonotonicityNot monotonic
2024-04-30T07:48:22.690156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 941
 
9.4%
1.1 46
 
0.5%
0.9 41
 
0.4%
102.5 39
 
0.4%
0.5 36
 
0.4%
0.4 36
 
0.4%
0.7 33
 
0.3%
102.6 32
 
0.3%
102.7 31
 
0.3%
30.77 29
 
0.3%
Other values (3991) 8399
84.0%
(Missing) 337
 
3.4%
ValueCountFrequency (%)
-118.58 1
< 0.1%
-53.0 1
< 0.1%
-47.1 1
< 0.1%
-16.0 1
< 0.1%
-14.5 1
< 0.1%
-12.2 1
< 0.1%
-12.0 1
< 0.1%
-11.7 1
< 0.1%
-11.6 1
< 0.1%
-11.5 1
< 0.1%
ValueCountFrequency (%)
1583642.0 1
< 0.1%
801.89 1
< 0.1%
393.0 1
< 0.1%
328.0 1
< 0.1%
287.0 1
< 0.1%
282.0 1
< 0.1%
277.5 2
< 0.1%
265.0 1
< 0.1%
263.2 1
< 0.1%
258.88 1
< 0.1%

좌표(GRS80_X)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct9453
Distinct (%)97.8%
Missing337
Missing (%)3.4%
Infinite0
Infinite (%)0.0%
Mean387570.49
Minimum364728.81
Maximum408731.36
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-30T07:48:23.030523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum364728.81
5-th percentile367389.49
Q1379538.98
median388131.78
Q3397289.43
95-th percentile403513.17
Maximum408731.36
Range44002.552
Interquartile range (IQR)17750.45

Descriptive statistics

Standard deviation11123.559
Coefficient of variation (CV)0.028700738
Kurtosis-0.94121983
Mean387570.49
Median Absolute Deviation (MAD)9045.7323
Skewness-0.26270161
Sum3.7450937 × 109
Variance1.2373357 × 108
MonotonicityNot monotonic
2024-04-30T07:48:23.169444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
387668.456 5
 
0.1%
373971.5034 5
 
0.1%
375135.8279 4
 
< 0.1%
368172.4278 3
 
< 0.1%
405042.4709 3
 
< 0.1%
368985.8122 3
 
< 0.1%
369144.9115 3
 
< 0.1%
368097.9514 3
 
< 0.1%
375136.4206 3
 
< 0.1%
369382.995 3
 
< 0.1%
Other values (9443) 9628
96.3%
(Missing) 337
 
3.4%
ValueCountFrequency (%)
364728.8097 1
< 0.1%
364741.829 1
< 0.1%
364839.8945 1
< 0.1%
364872.816 1
< 0.1%
364929.9024 1
< 0.1%
364931.5486 1
< 0.1%
364933.1459 1
< 0.1%
364977.9872 1
< 0.1%
364980.1683 1
< 0.1%
365037.3105 1
< 0.1%
ValueCountFrequency (%)
408731.3616 1
< 0.1%
408730.4416 1
< 0.1%
408629.8471 1
< 0.1%
408573.6589 1
< 0.1%
408564.6744 1
< 0.1%
408343.0987 1
< 0.1%
408342.1657 1
< 0.1%
408244.8133 1
< 0.1%
408227.4077 1
< 0.1%
408200.3663 1
< 0.1%

좌표(GRS80_Y)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct9465
Distinct (%)98.0%
Missing337
Missing (%)3.4%
Infinite0
Infinite (%)0.0%
Mean289378.01
Minimum270383.76
Maximum311912.43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-30T07:48:23.311906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum270383.76
5-th percentile277436.32
Q1282681.87
median288271.2
Q3293402.87
95-th percentile306593.65
Maximum311912.43
Range41528.667
Interquartile range (IQR)10721

Descriptive statistics

Standard deviation8690.2558
Coefficient of variation (CV)0.03003081
Kurtosis-0.30760744
Mean289378.01
Median Absolute Deviation (MAD)5292.103
Skewness0.59270644
Sum2.7962597 × 109
Variance75520546
MonotonicityNot monotonic
2024-04-30T07:48:23.490506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
285894.261 5
 
0.1%
278434.8542 5
 
0.1%
276636.9024 4
 
< 0.1%
282882.1723 4
 
< 0.1%
282632.1379 3
 
< 0.1%
282753.4809 3
 
< 0.1%
304692.9723 3
 
< 0.1%
281252.6532 3
 
< 0.1%
280936.243 3
 
< 0.1%
282966.1217 3
 
< 0.1%
Other values (9455) 9627
96.3%
(Missing) 337
 
3.4%
ValueCountFrequency (%)
270383.7639 1
< 0.1%
270474.7436 1
< 0.1%
272832.0959 1
< 0.1%
273578.148 1
< 0.1%
274298.7316 1
< 0.1%
274431.6959 1
< 0.1%
274433.6072 1
< 0.1%
274493.2885 1
< 0.1%
274517.6529 1
< 0.1%
274633.9774 1
< 0.1%
ValueCountFrequency (%)
311912.4307 1
< 0.1%
311911.4908 1
< 0.1%
311821.9064 1
< 0.1%
311809.0823 1
< 0.1%
311808.6205 1
< 0.1%
311800.7719 1
< 0.1%
311794.9984 1
< 0.1%
311788.521 1
< 0.1%
311681.8194 1
< 0.1%
311677.8595 1
< 0.1%

Interactions

2024-04-30T07:48:18.980797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:48:18.340109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:48:18.683226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:48:19.081907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:48:18.501342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:48:18.786547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:48:19.171220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:48:18.592261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:48:18.882529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-30T07:48:23.581737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
고도좌표(GRS80_X)좌표(GRS80_Y)
고도1.0000.0000.012
좌표(GRS80_X)0.0001.0000.818
좌표(GRS80_Y)0.0120.8181.000
2024-04-30T07:48:23.661787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
고도좌표(GRS80_X)좌표(GRS80_Y)
고도1.0000.3650.368
좌표(GRS80_X)0.3651.0000.729
좌표(GRS80_Y)0.3680.7291.000

Missing values

2024-04-30T07:48:19.281055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-30T07:48:19.392481image/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.
2024-04-30T07:48:19.532807image/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

프로젝트코드프로젝트명시추공코드시추공명고도좌표(GRS80_X)좌표(GRS80_Y)
7560P0330부산 정관신도시 건설공사 토질조사보고서P0330BH083회로차82.3398505.3824305827.1702
8165P1204해안순환도로 건설사업(북항구간) 기본설계P1204BH030BH-402.67387282.2461286942.1008
3136(부록12)"P0316BH242B-162102.9387548.7826284220.359
9299P0642장림하수처리장 2단계 건설 차집관로 2공구공사(지하굴착에 따른 지하흙막이 공사와 관련한) 검토보고서P0642BH026BH-269.09382864.3281278493.5928
7731B0577부산~울산고속국도 민간투자사업 건설공사(4공구)B0577BB02626좌광천46.1402983.2146304570.7712
6868P0850신호지방공업단지개발사업 토질조사보고서P0850BH002BH-21.2371048.0994278354.1162
705B224905 부산내리 B-1BL지구 지반조사B2249BH007H-710.93400867.6819291949.2777
7238B1208냉정-부산간 고속국도 제 104호선 남해고속도로 확장공사(3-1공구)-4B1208BB001BB-1-0.6372036.3117287030.2793
1538P0316서울-부산간 경부고속철도 제14공구 노반신설 기타공사 지질조사보고서<NA><NA><NA><NA><NA>
6965B212402 부산 송정1지구 지반조사보고서B2124BH020H-250.0400152.6994289653.0828
프로젝트코드프로젝트명시추공코드시추공명고도좌표(GRS80_X)좌표(GRS80_Y)
621B3095부산강서지구 택지개발사업 조사설계 용역B3095BH025BH-252.5380710.5341293230.9812
9349B1098부산신평지구 지반조사B1098BH013H-40.0379703.5371279406.852
1000B2294부산반여지구 지반조사B2294BH019H-1915.53393253.6169291549.2323
6553B3595북항대교~동명오거리간 고가.지하차도 실시설계에 따른 지반조사B3595BH006BH-62.72390498.685281162.8627
5606K179아산국가공단 토질조사K179BH027BH-7230.54387675.1986286296.8162
6605B5886식만~사상간(대저대교)도로건설공사B5886BH004BH-40.9375328.9539291836.2451
3055P0316서울-부산간 경부고속철도 제14공구 노반신설 기타공사 지질조사보고서<NA><NA><NA><NA><NA>
2298B5929부산명지지구 B-1블록 지반조사B5929BH002H-021.48374273.839279528.5885
3271P0330부산 정관신도시 건설공사 토질조사보고서P0330CB008CB-8180.9396497.9111306318.0241
1324P0459광안대로 제5공구 지질조사P0459BH009RP3-13.65394838.1673287595.2955

Duplicate rows

Most frequently occurring

프로젝트코드프로젝트명시추공코드시추공명고도좌표(GRS80_X)좌표(GRS80_Y)# duplicates
1P0316서울-부산간 경부고속철도 제14공구 노반신설 기타공사 지질조사보고서<NA><NA><NA><NA><NA>329
2<NA><NA><NA><NA><NA><NA><NA>3
0B3523학장천 정비공사 지반조사<NA><NA><NA><NA><NA>2