Overview

Dataset statistics

Number of variables5
Number of observations101
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.2 KiB
Average record size in memory42.3 B

Variable types

Categorical4
Text1

Dataset

DescriptionSample
Author㈜지오시스템리서치
URLhttps://www.bigdata-coast.kr/gdsInfo/gdsInfoDetail.do?gdsCd=CT09GSR006

Alerts

SIDO_NM has constant value ""Constant
SGG_NM has constant value ""Constant
TRGET_AREA_NM has constant value ""Constant
VIDO_MNRG_AVG_VIDO_FILE_NM has unique valuesUnique

Reproduction

Analysis started2024-03-13 12:45:00.104949
Analysis finished2024-03-13 12:45:00.459205
Duration0.35 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

SIDO_NM
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size940.0 B
강원도
101 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
강원도 101
100.0%

Length

2024-03-13T21:45:00.548859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:45:00.674547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강원도 101
100.0%

SGG_NM
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size940.0 B
강릉시
101 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
강릉시 101
100.0%

Length

2024-03-13T21:45:00.807321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:45:00.981560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강릉시 101
100.0%

TRGET_AREA_NM
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size940.0 B
경포대
101 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경포대 101
100.0%

Length

2024-03-13T21:45:01.130089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:45:01.251051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경포대 101
100.0%

VIDO_MNRG_WTCH_YMD
Categorical

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size940.0 B
20210801
24 
20210802
24 
20210803
24 
20210804
24 
20210805
5 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20210801
2nd row20210801
3rd row20210801
4th row20210801
5th row20210801

Common Values

ValueCountFrequency (%)
20210801 24
23.8%
20210802 24
23.8%
20210803 24
23.8%
20210804 24
23.8%
20210805 5
 
5.0%

Length

2024-03-13T21:45:01.373588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:45:01.512115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20210801 24
23.8%
20210802 24
23.8%
20210803 24
23.8%
20210804 24
23.8%
20210805 5
 
5.0%

VIDO_MNRG_AVG_VIDO_FILE_NM
Text

UNIQUE 

Distinct101
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size940.0 B
2024-03-13T21:45:01.766723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters2222
Distinct characters17
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique101 ?
Unique (%)100.0%

Sample

1st rowAAAC1202108010700m.jpg
2nd rowAAAC1202108010730m.jpg
3rd rowAAAC1202108010800m.jpg
4th rowAAAC1202108010830m.jpg
5th rowAAAC1202108010900m.jpg
ValueCountFrequency (%)
aaac1202108010700m.jpg 1
 
1.0%
aaac1202108030900m.jpg 1
 
1.0%
aaac1202108040800m.jpg 1
 
1.0%
aaac1202108040730m.jpg 1
 
1.0%
aaac1202108040700m.jpg 1
 
1.0%
aaac1202108031830m.jpg 1
 
1.0%
aaac1202108031800m.jpg 1
 
1.0%
aaac1202108031730m.jpg 1
 
1.0%
aaac1202108031700m.jpg 1
 
1.0%
aaac1202108031630m.jpg 1
 
1.0%
Other values (91) 91
90.1%
2024-03-13T21:45:02.261858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 492
22.1%
1 306
13.8%
A 303
13.6%
2 234
10.5%
8 119
 
5.4%
j 101
 
4.5%
g 101
 
4.5%
p 101
 
4.5%
. 101
 
4.5%
C 101
 
4.5%
Other values (7) 263
11.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1313
59.1%
Uppercase Letter 404
 
18.2%
Lowercase Letter 404
 
18.2%
Other Punctuation 101
 
4.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 492
37.5%
1 306
23.3%
2 234
17.8%
8 119
 
9.1%
3 82
 
6.2%
4 32
 
2.4%
7 18
 
1.4%
5 13
 
1.0%
9 9
 
0.7%
6 8
 
0.6%
Lowercase Letter
ValueCountFrequency (%)
j 101
25.0%
g 101
25.0%
p 101
25.0%
m 101
25.0%
Uppercase Letter
ValueCountFrequency (%)
A 303
75.0%
C 101
 
25.0%
Other Punctuation
ValueCountFrequency (%)
. 101
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1414
63.6%
Latin 808
36.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 492
34.8%
1 306
21.6%
2 234
16.5%
8 119
 
8.4%
. 101
 
7.1%
3 82
 
5.8%
4 32
 
2.3%
7 18
 
1.3%
5 13
 
0.9%
9 9
 
0.6%
Latin
ValueCountFrequency (%)
A 303
37.5%
j 101
 
12.5%
g 101
 
12.5%
p 101
 
12.5%
C 101
 
12.5%
m 101
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2222
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 492
22.1%
1 306
13.8%
A 303
13.6%
2 234
10.5%
8 119
 
5.4%
j 101
 
4.5%
g 101
 
4.5%
p 101
 
4.5%
. 101
 
4.5%
C 101
 
4.5%
Other values (7) 263
11.8%

Missing values

2024-03-13T21:45:00.238968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T21:45:00.405525image/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

SIDO_NMSGG_NMTRGET_AREA_NMVIDO_MNRG_WTCH_YMDVIDO_MNRG_AVG_VIDO_FILE_NM
0강원도강릉시경포대20210801AAAC1202108010700m.jpg
1강원도강릉시경포대20210801AAAC1202108010730m.jpg
2강원도강릉시경포대20210801AAAC1202108010800m.jpg
3강원도강릉시경포대20210801AAAC1202108010830m.jpg
4강원도강릉시경포대20210801AAAC1202108010900m.jpg
5강원도강릉시경포대20210801AAAC1202108010930m.jpg
6강원도강릉시경포대20210801AAAC1202108011000m.jpg
7강원도강릉시경포대20210801AAAC1202108011030m.jpg
8강원도강릉시경포대20210801AAAC1202108011100m.jpg
9강원도강릉시경포대20210801AAAC1202108011130m.jpg
SIDO_NMSGG_NMTRGET_AREA_NMVIDO_MNRG_WTCH_YMDVIDO_MNRG_AVG_VIDO_FILE_NM
91강원도강릉시경포대20210804AAAC1202108041630m.jpg
92강원도강릉시경포대20210804AAAC1202108041700m.jpg
93강원도강릉시경포대20210804AAAC1202108041730m.jpg
94강원도강릉시경포대20210804AAAC1202108041800m.jpg
95강원도강릉시경포대20210804AAAC1202108041830m.jpg
96강원도강릉시경포대20210805AAAC1202108050700m.jpg
97강원도강릉시경포대20210805AAAC1202108050730m.jpg
98강원도강릉시경포대20210805AAAC1202108050800m.jpg
99강원도강릉시경포대20210805AAAC1202108050830m.jpg
100강원도강릉시경포대20210805AAAC1202108050900m.jpg