Overview

Dataset statistics

Number of variables8
Number of observations30
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.1 KiB
Average record size in memory70.4 B

Variable types

Numeric2
DateTime1
Boolean1
Text2
Categorical2

Dataset

Description국토지리정보원에서 대민서비스인 국토정보플랫폼에서 정기점검보고(관측점, 점검구분, 파일 등) 정보를 제공합니다.
Author국토교통부 국토지리정보원
URLhttps://www.data.go.kr/data/15122732/fileData.do

Alerts

점검구분 has constant value ""Constant
상세코멘트 has constant value ""Constant
정기점검순번 is highly overall correlated with 관측점순번 and 1 other fieldsHigh correlation
관측점순번 is highly overall correlated with 정기점검순번 and 1 other fieldsHigh correlation
보고자 is highly overall correlated with 정기점검순번 and 1 other fieldsHigh correlation
정기점검순번 has unique valuesUnique
관측점순번 has unique valuesUnique
파일명 has unique valuesUnique
파일경로 has unique valuesUnique

Reproduction

Analysis started2023-12-12 15:50:48.242295
Analysis finished2023-12-12 15:50:49.569914
Duration1.33 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

정기점검순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.5
Minimum1
Maximum30
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-13T00:50:49.642238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.45
Q18.25
median15.5
Q322.75
95-th percentile28.55
Maximum30
Range29
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation8.8034084
Coefficient of variation (CV)0.56796183
Kurtosis-1.2
Mean15.5
Median Absolute Deviation (MAD)7.5
Skewness0
Sum465
Variance77.5
MonotonicityStrictly increasing
2023-12-13T00:50:49.809042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
1 1
 
3.3%
17 1
 
3.3%
30 1
 
3.3%
29 1
 
3.3%
28 1
 
3.3%
27 1
 
3.3%
26 1
 
3.3%
25 1
 
3.3%
24 1
 
3.3%
23 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
1 1
3.3%
2 1
3.3%
3 1
3.3%
4 1
3.3%
5 1
3.3%
6 1
3.3%
7 1
3.3%
8 1
3.3%
9 1
3.3%
10 1
3.3%
ValueCountFrequency (%)
30 1
3.3%
29 1
3.3%
28 1
3.3%
27 1
3.3%
26 1
3.3%
25 1
3.3%
24 1
3.3%
23 1
3.3%
22 1
3.3%
21 1
3.3%

관측점순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.5
Minimum1
Maximum30
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-13T00:50:49.991372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.45
Q18.25
median15.5
Q322.75
95-th percentile28.55
Maximum30
Range29
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation8.8034084
Coefficient of variation (CV)0.56796183
Kurtosis-1.2
Mean15.5
Median Absolute Deviation (MAD)7.5
Skewness0
Sum465
Variance77.5
MonotonicityStrictly increasing
2023-12-13T00:50:50.123308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
1 1
 
3.3%
17 1
 
3.3%
30 1
 
3.3%
29 1
 
3.3%
28 1
 
3.3%
27 1
 
3.3%
26 1
 
3.3%
25 1
 
3.3%
24 1
 
3.3%
23 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
1 1
3.3%
2 1
3.3%
3 1
3.3%
4 1
3.3%
5 1
3.3%
6 1
3.3%
7 1
3.3%
8 1
3.3%
9 1
3.3%
10 1
3.3%
ValueCountFrequency (%)
30 1
3.3%
29 1
3.3%
28 1
3.3%
27 1
3.3%
26 1
3.3%
25 1
3.3%
24 1
3.3%
23 1
3.3%
22 1
3.3%
21 1
3.3%

등록일자
Date

Distinct8
Distinct (%)26.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2022-04-07 00:00:00
Maximum2022-05-06 00:00:00
2023-12-13T00:50:50.238214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:50:50.351190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)

점검구분
Boolean

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size162.0 B
True
30 
ValueCountFrequency (%)
True 30
100.0%
2023-12-13T00:50:50.443178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

파일명
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-13T00:50:50.687819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length9
Min length8

Characters and Unicode

Total characters270
Distinct characters28
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row서울319.jpg
2nd row서울439.jpg
3rd row서울469.jpg
4th row인천311.jpg
5th row인천313.jpg
ValueCountFrequency (%)
서울319.jpg 1
 
3.3%
서울439.jpg 1
 
3.3%
당진303.jpg 1
 
3.3%
당진403.jpg 1
 
3.3%
당진408.jpg 1
 
3.3%
서산424.jpg 1
 
3.3%
서산457.jpg 1
 
3.3%
서산430.jpg 1
 
3.3%
서산21.jpg 1
 
3.3%
서산405.jpg 1
 
3.3%
Other values (20) 20
66.7%
2023-12-13T00:50:51.295255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 30
11.1%
j 30
11.1%
p 30
11.1%
g 30
11.1%
3 22
 
8.1%
4 21
 
7.8%
1 13
 
4.8%
0 13
 
4.8%
서 8
 
3.0%
안 7
 
2.6%
Other values (18) 66
24.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 90
33.3%
Decimal Number 89
33.0%
Other Letter 61
22.6%
Other Punctuation 30
 
11.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 8
13.1%
안 7
11.5%
양 7
11.5%
인 7
11.5%
천 7
11.5%
산 5
8.2%
당 4
6.6%
진 4
6.6%
울 3
 
4.9%
대 3
 
4.9%
Other values (4) 6
9.8%
Decimal Number
ValueCountFrequency (%)
3 22
24.7%
4 21
23.6%
1 13
14.6%
0 13
14.6%
2 5
 
5.6%
9 5
 
5.6%
5 4
 
4.5%
8 3
 
3.4%
6 2
 
2.2%
7 1
 
1.1%
Lowercase Letter
ValueCountFrequency (%)
j 30
33.3%
p 30
33.3%
g 30
33.3%
Other Punctuation
ValueCountFrequency (%)
. 30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 119
44.1%
Latin 90
33.3%
Hangul 61
22.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 8
13.1%
안 7
11.5%
양 7
11.5%
인 7
11.5%
천 7
11.5%
산 5
8.2%
당 4
6.6%
진 4
6.6%
울 3
 
4.9%
대 3
 
4.9%
Other values (4) 6
9.8%
Common
ValueCountFrequency (%)
. 30
25.2%
3 22
18.5%
4 21
17.6%
1 13
10.9%
0 13
10.9%
2 5
 
4.2%
9 5
 
4.2%
5 4
 
3.4%
8 3
 
2.5%
6 2
 
1.7%
Latin
ValueCountFrequency (%)
j 30
33.3%
p 30
33.3%
g 30
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 209
77.4%
Hangul 61
 
22.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 30
14.4%
j 30
14.4%
p 30
14.4%
g 30
14.4%
3 22
10.5%
4 21
10.0%
1 13
6.2%
0 13
6.2%
2 5
 
2.4%
9 5
 
2.4%
Other values (4) 10
 
4.8%
Hangul
ValueCountFrequency (%)
서 8
13.1%
안 7
11.5%
양 7
11.5%
인 7
11.5%
천 7
11.5%
산 5
8.2%
당 4
6.6%
진 4
6.6%
울 3
 
4.9%
대 3
 
4.9%
Other values (4) 6
9.8%

파일경로
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-13T00:50:51.716166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length41
Mean length41
Min length40

Characters and Unicode

Total characters1230
Distinct characters43
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row/map/측량성과물/관측점/2022/서해1/02_기록사진/서울319.jpg
2nd row/map/측량성과물/관측점/2022/서해1/02_기록사진/서울439.jpg
3rd row/map/측량성과물/관측점/2022/서해1/02_기록사진/서울469.jpg
4th row/map/측량성과물/관측점/2022/서해1/02_기록사진/인천311.jpg
5th row/map/측량성과물/관측점/2022/서해1/02_기록사진/인천313.jpg
ValueCountFrequency (%)
map/측량성과물/관측점/2022/서해1/02_기록사진/서울319.jpg 1
 
3.3%
map/측량성과물/관측점/2022/서해1/02_기록사진/서울439.jpg 1
 
3.3%
map/측량성과물/관측점/2022/서해2/02_기록사진/당진303.jpg 1
 
3.3%
map/측량성과물/관측점/2022/서해2/02_기록사진/당진403.jpg 1
 
3.3%
map/측량성과물/관측점/2022/서해2/02_기록사진/당진408.jpg 1
 
3.3%
map/측량성과물/관측점/2022/서해2/02_기록사진/서산424.jpg 1
 
3.3%
map/측량성과물/관측점/2022/서해2/02_기록사진/서산457.jpg 1
 
3.3%
map/측량성과물/관측점/2022/서해2/02_기록사진/서산430.jpg 1
 
3.3%
map/측량성과물/관측점/2022/서해2/02_기록사진/서산21.jpg 1
 
3.3%
map/측량성과물/관측점/2022/서해2/02_기록사진/서산405.jpg 1
 
3.3%
Other values (20) 20
66.7%
2023-12-13T00:50:52.343759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 210
 
17.1%
2 135
 
11.0%
0 73
 
5.9%
p 60
 
4.9%
측 60
 
4.9%
서 38
 
3.1%
진 34
 
2.8%
1 33
 
2.7%
g 30
 
2.4%
j 30
 
2.4%
Other values (33) 527
42.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 481
39.1%
Decimal Number 299
24.3%
Other Punctuation 240
19.5%
Lowercase Letter 180
 
14.6%
Connector Punctuation 30
 
2.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
측 60
12.5%
서 38
 
7.9%
진 34
 
7.1%
사 30
 
6.2%
록 30
 
6.2%
기 30
 
6.2%
성 30
 
6.2%
점 30
 
6.2%
관 30
 
6.2%
물 30
 
6.2%
Other values (15) 139
28.9%
Decimal Number
ValueCountFrequency (%)
2 135
45.2%
0 73
24.4%
1 33
 
11.0%
3 22
 
7.4%
4 21
 
7.0%
9 5
 
1.7%
5 4
 
1.3%
8 3
 
1.0%
6 2
 
0.7%
7 1
 
0.3%
Lowercase Letter
ValueCountFrequency (%)
p 60
33.3%
g 30
16.7%
j 30
16.7%
m 30
16.7%
a 30
16.7%
Other Punctuation
ValueCountFrequency (%)
/ 210
87.5%
. 30
 
12.5%
Connector Punctuation
ValueCountFrequency (%)
_ 30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 569
46.3%
Hangul 481
39.1%
Latin 180
 
14.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
측 60
12.5%
서 38
 
7.9%
진 34
 
7.1%
사 30
 
6.2%
록 30
 
6.2%
기 30
 
6.2%
성 30
 
6.2%
점 30
 
6.2%
관 30
 
6.2%
물 30
 
6.2%
Other values (15) 139
28.9%
Common
ValueCountFrequency (%)
/ 210
36.9%
2 135
23.7%
0 73
 
12.8%
1 33
 
5.8%
. 30
 
5.3%
_ 30
 
5.3%
3 22
 
3.9%
4 21
 
3.7%
9 5
 
0.9%
5 4
 
0.7%
Other values (3) 6
 
1.1%
Latin
ValueCountFrequency (%)
p 60
33.3%
g 30
16.7%
j 30
16.7%
m 30
16.7%
a 30
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 749
60.9%
Hangul 481
39.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 210
28.0%
2 135
18.0%
0 73
 
9.7%
p 60
 
8.0%
1 33
 
4.4%
g 30
 
4.0%
j 30
 
4.0%
. 30
 
4.0%
m 30
 
4.0%
_ 30
 
4.0%
Other values (8) 88
11.7%
Hangul
ValueCountFrequency (%)
측 60
12.5%
서 38
 
7.9%
진 34
 
7.1%
사 30
 
6.2%
록 30
 
6.2%
기 30
 
6.2%
성 30
 
6.2%
점 30
 
6.2%
관 30
 
6.2%
물 30
 
6.2%
Other values (15) 139
28.9%

보고자
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
박일영
10 
이윤식
9 
허영환
4 
이홍기
4 
김정호
3 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row허영환
2nd row허영환
3rd row허영환
4th row허영환
5th row김정호

Common Values

ValueCountFrequency (%)
박일영 10
33.3%
이윤식 9
30.0%
허영환 4
 
13.3%
이홍기 4
 
13.3%
김정호 3
 
10.0%

Length

2023-12-13T00:50:52.550626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:50:52.689446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
박일영 10
33.3%
이윤식 9
30.0%
허영환 4
 
13.3%
이홍기 4
 
13.3%
김정호 3
 
10.0%

상세코멘트
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
이상없음
30 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
이상없음 30
100.0%

Length

2023-12-13T00:50:52.844342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:50:52.966526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
이상없음 30
100.0%

Interactions

2023-12-13T00:50:48.717089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:50:48.503059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:50:48.858624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:50:48.602194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:50:53.062110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정기점검순번관측점순번등록일자파일명파일경로보고자
정기점검순번1.0001.0000.7991.0001.0000.972
관측점순번1.0001.0000.7991.0001.0000.972
등록일자0.7990.7991.0001.0001.0001.000
파일명1.0001.0001.0001.0001.0001.000
파일경로1.0001.0001.0001.0001.0001.000
보고자0.9720.9721.0001.0001.0001.000
2023-12-13T00:50:53.202134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정기점검순번관측점순번보고자
정기점검순번1.0001.0000.681
관측점순번1.0001.0000.681
보고자0.6810.6811.000

Missing values

2023-12-13T00:50:49.364414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:50:49.513145image/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

정기점검순번관측점순번등록일자점검구분파일명파일경로보고자상세코멘트
0112022-04-07Y서울319.jpg/map/측량성과물/관측점/2022/서해1/02_기록사진/서울319.jpg허영환이상없음
1222022-04-07Y서울439.jpg/map/측량성과물/관측점/2022/서해1/02_기록사진/서울439.jpg허영환이상없음
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