Overview

Dataset statistics

Number of variables3
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory312.5 KiB
Average record size in memory32.0 B

Variable types

Categorical1
DateTime1
Text1

Dataset

Description부산광역시_대기진단평가시스템 수신 기상청제공 위성자료 파일명데이터로 위성자료종류, 측정날짜, 위성자료파일명 등 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15120959/fileData.do

Alerts

위성자료종류 is highly imbalanced (83.3%)Imbalance
위성자료파일명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 21:19:56.799469
Analysis finished2023-12-12 21:19:57.126333
Duration0.33 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

위성자료종류
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
gdps
9541 
ldps
 
259
terra
 
103
aqua
 
97

Length

Max length5
Median length4
Mean length4.0103
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
gdps 9541
95.4%
ldps 259
 
2.6%
terra 103
 
1.0%
aqua 97
 
1.0%

Length

2023-12-13T06:19:57.198788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:19:57.293976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
gdps 9541
95.4%
ldps 259
 
2.6%
terra 103
 
1.0%
aqua 97
 
1.0%

측정날짜
Date

Distinct540
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-06-01 00:00:00
Maximum2023-08-25 03:56:00
2023-12-13T06:19:57.409431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:19:57.554288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

위성자료파일명
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T06:19:57.804647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length35
Mean length35.148
Min length35

Characters and Unicode

Total characters351480
Distinct characters32
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

Unique10000 ?
Unique (%)100.0%

Sample

1st rowgdps_skew_47159_s042_2023081000.gif
2nd rowgdps_skew_47159_s036_2023062112.gif
3rd rowgdps_skew_47159_s096_2023081312.gif
4th rowgdps_skew_47159_s081_2023081418.gif
5th rowgdps_skew_47159_s018_2023061712.gif
ValueCountFrequency (%)
gdps_skew_47159_s042_2023081000.gif 1
 
< 0.1%
gdps_skew_47159_s045_2023072318.gif 1
 
< 0.1%
gdps_skew_47159_s108_2023062800.gif 1
 
< 0.1%
gdps_skew_47159_s042_2023080618.gif 1
 
< 0.1%
gdps_skew_47159_s288_2023062300.gif 1
 
< 0.1%
gdps_skew_47159_s057_2023080600.gif 1
 
< 0.1%
gdps_skew_47159_s024_2023070806.gif 1
 
< 0.1%
gdps_skew_47159_s012_2023070606.gif 1
 
< 0.1%
gdps_skew_47159_s108_2023060212.gif 1
 
< 0.1%
gdps_skew_47159_s144_2023080612.gif 1
 
< 0.1%
Other values (9990) 9990
99.9%
2023-12-13T06:19:58.240632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 42361
 
12.1%
_ 40459
 
11.5%
2 30281
 
8.6%
s 29541
 
8.4%
1 22150
 
6.3%
g 19541
 
5.6%
7 15501
 
4.4%
3 13395
 
3.8%
4 13059
 
3.7%
5 12617
 
3.6%
Other values (22) 112575
32.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 177505
50.5%
Lowercase Letter 123516
35.1%
Connector Punctuation 40459
 
11.5%
Other Punctuation 10000
 
2.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 29541
23.9%
g 19541
15.8%
p 10518
 
8.5%
d 10400
 
8.4%
i 10259
 
8.3%
k 9800
 
7.9%
f 9800
 
7.9%
e 9644
 
7.8%
w 9541
 
7.7%
a 956
 
0.8%
Other values (10) 3516
 
2.8%
Decimal Number
ValueCountFrequency (%)
0 42361
23.9%
2 30281
17.1%
1 22150
12.5%
7 15501
 
8.7%
3 13395
 
7.5%
4 13059
 
7.4%
5 12617
 
7.1%
9 11610
 
6.5%
6 8858
 
5.0%
8 7673
 
4.3%
Connector Punctuation
ValueCountFrequency (%)
_ 40459
100.0%
Other Punctuation
ValueCountFrequency (%)
. 10000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 227964
64.9%
Latin 123516
35.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 29541
23.9%
g 19541
15.8%
p 10518
 
8.5%
d 10400
 
8.4%
i 10259
 
8.3%
k 9800
 
7.9%
f 9800
 
7.9%
e 9644
 
7.8%
w 9541
 
7.7%
a 956
 
0.8%
Other values (10) 3516
 
2.8%
Common
ValueCountFrequency (%)
0 42361
18.6%
_ 40459
17.7%
2 30281
13.3%
1 22150
9.7%
7 15501
 
6.8%
3 13395
 
5.9%
4 13059
 
5.7%
5 12617
 
5.5%
9 11610
 
5.1%
. 10000
 
4.4%
Other values (2) 16531
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 351480
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 42361
 
12.1%
_ 40459
 
11.5%
2 30281
 
8.6%
s 29541
 
8.4%
1 22150
 
6.3%
g 19541
 
5.6%
7 15501
 
4.4%
3 13395
 
3.8%
4 13059
 
3.7%
5 12617
 
3.6%
Other values (22) 112575
32.0%

Missing values

2023-12-13T06:19:57.009486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:19:57.086005image/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

위성자료종류측정날짜위성자료파일명
11135gdps2023-08-10 00:00gdps_skew_47159_s042_2023081000.gif
3273gdps2023-06-21 12:00gdps_skew_47159_s036_2023062112.gif
11709gdps2023-08-13 12:00gdps_skew_47159_s096_2023081312.gif
11913gdps2023-08-14 18:00gdps_skew_47159_s081_2023081418.gif
2630gdps2023-06-17 12:00gdps_skew_47159_s018_2023061712.gif
11754gdps2023-08-13 18:00gdps_skew_47159_s081_2023081318.gif
3443gdps2023-06-22 12:00gdps_skew_47159_s072_2023062212.gif
280gdps2023-06-02 12:00gdps_skew_47159_s228_2023060212.gif
3081gdps2023-06-20 06:00gdps_skew_47159_s030_2023062006.gif
12978gdps2023-08-21 12:00gdps_skew_47159_s084_2023082112.gif
위성자료종류측정날짜위성자료파일명
7023gdps2023-07-15 00:00gdps_skew_47159_s132_2023071500.gif
12200gdps2023-08-16 12:00gdps_skew_47159_s264_2023081612.gif
1124gdps2023-06-08 00:00gdps_skew_47159_s036_2023060800.gif
2897gdps2023-06-19 00:00gdps_skew_47159_s168_2023061900.gif
12944gdps2023-08-21 06:00gdps_skew_47159_s075_2023082106.gif
13191gdps2023-08-23 00:00gdps_skew_47159_s012_2023082300.gif
9751gdps2023-08-01 06:00gdps_skew_47159_s024_2023080106.gif
11919gdps2023-08-15 00:00gdps_skew_47159_s009_2023081500.gif
718gdps2023-06-05 12:00gdps_skew_47159_s009_2023060512.gif
9568gdps2023-07-31 00:00gdps_skew_47159_s144_2023073100.gif