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_대기질진단평가기상청위성자료_20230825
Author부산광역시
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15120959

Alerts

위성자료종류 is highly imbalanced (84.5%)Imbalance
위성자료파일명 has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:17:13.512499
Analysis finished2023-12-10 16:17:14.209150
Duration0.7 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
9583 
ldps
 
237
aqua
 
91
terra
 
89

Length

Max length5
Median length4
Mean length4.0089
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
gdps 9583
95.8%
ldps 237
 
2.4%
aqua 91
 
0.9%
terra 89
 
0.9%

Length

2023-12-11T01:17:14.326408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:17:14.434297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
gdps 9583
95.8%
ldps 237
 
2.4%
aqua 91
 
0.9%
terra 89
 
0.9%

측정날짜
Date

Distinct521
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-06-01 00:00:00
Maximum2023-08-25 03:56:00
2023-12-11T01:17:14.562216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:17:14.723311image/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
2023-12-11T01:17:14.991024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length35
Mean length35.134
Min length35

Characters and Unicode

Total characters351340
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_s048_2023081800.gif
2nd rowgdps_skew_47159_s042_2023081600.gif
3rd rowgdps_skew_47159_s024_2023070706.gif
4th rowgdps_skew_47159_s066_2023060100.gif
5th rowgdps_skew_47159_s108_2023080200.gif
ValueCountFrequency (%)
gdps_skew_47159_s048_2023081800.gif 1
 
< 0.1%
gdps_skew_47159_s240_2023070500.gif 1
 
< 0.1%
gdps_skew_47159_s030_2023071800.gif 1
 
< 0.1%
gdps_skew_47159_s063_2023071112.gif 1
 
< 0.1%
gdps_skew_47159_s144_2023062712.gif 1
 
< 0.1%
gdps_skew_47159_s066_2023062312.gif 1
 
< 0.1%
gdps_skew_47159_s039_2023082300.gif 1
 
< 0.1%
gdps_skew_47159_s021_2023071612.gif 1
 
< 0.1%
gdps_skew_47159_s030_2023071518.gif 1
 
< 0.1%
gdps_skew_47159_s075_2023072206.gif 1
 
< 0.1%
Other values (9990) 9990
99.9%
2023-12-11T01:17:15.409584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 42435
 
12.1%
_ 40417
 
11.5%
2 30180
 
8.6%
s 29583
 
8.4%
1 22074
 
6.3%
g 19583
 
5.6%
7 15617
 
4.4%
3 13402
 
3.8%
4 13167
 
3.7%
5 12655
 
3.6%
Other values (22) 112227
31.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 177735
50.6%
Lowercase Letter 123188
35.1%
Connector Punctuation 40417
 
11.5%
Other Punctuation 10000
 
2.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 29583
24.0%
g 19583
15.9%
p 10474
 
8.5%
d 10360
 
8.4%
i 10237
 
8.3%
f 9820
 
8.0%
k 9820
 
8.0%
e 9672
 
7.9%
w 9583
 
7.8%
a 868
 
0.7%
Other values (10) 3188
 
2.6%
Decimal Number
ValueCountFrequency (%)
0 42435
23.9%
2 30180
17.0%
1 22074
12.4%
7 15617
 
8.8%
3 13402
 
7.5%
4 13167
 
7.4%
5 12655
 
7.1%
9 11651
 
6.6%
6 8908
 
5.0%
8 7646
 
4.3%
Connector Punctuation
ValueCountFrequency (%)
_ 40417
100.0%
Other Punctuation
ValueCountFrequency (%)
. 10000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 228152
64.9%
Latin 123188
35.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 29583
24.0%
g 19583
15.9%
p 10474
 
8.5%
d 10360
 
8.4%
i 10237
 
8.3%
f 9820
 
8.0%
k 9820
 
8.0%
e 9672
 
7.9%
w 9583
 
7.8%
a 868
 
0.7%
Other values (10) 3188
 
2.6%
Common
ValueCountFrequency (%)
0 42435
18.6%
_ 40417
17.7%
2 30180
13.2%
1 22074
9.7%
7 15617
 
6.8%
3 13402
 
5.9%
4 13167
 
5.8%
5 12655
 
5.5%
9 11651
 
5.1%
. 10000
 
4.4%
Other values (2) 16554
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 351340
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 42435
 
12.1%
_ 40417
 
11.5%
2 30180
 
8.6%
s 29583
 
8.4%
1 22074
 
6.3%
g 19583
 
5.6%
7 15617
 
4.4%
3 13402
 
3.8%
4 13167
 
3.7%
5 12655
 
3.6%
Other values (22) 112227
31.9%

Missing values

2023-12-11T01:17:14.002960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:17:14.094290image/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
12408gdps2023-08-18 00:00gdps_skew_47159_s048_2023081800.gif
12089gdps2023-08-16 00:00gdps_skew_47159_s042_2023081600.gif
5778gdps2023-07-07 06:00gdps_skew_47159_s024_2023070706.gif
22gdps2023-06-01 00:00gdps_skew_47159_s066_2023060100.gif
9882gdps2023-08-02 00:00gdps_skew_47159_s108_2023080200.gif
12021gdps2023-08-15 12:00gdps_skew_47159_s072_2023081512.gif
7918gdps2023-07-20 18:00gdps_skew_47159_s009_2023072018.gif
11105gdps2023-08-09 18:00gdps_skew_47159_s042_2023080918.gif
7141gdps2023-07-15 18:00gdps_skew_47159_s066_2023071518.gif
8918gdps2023-07-27 00:00gdps_skew_47159_s063_2023072700.gif
위성자료종류측정날짜위성자료파일명
8423gdps2023-07-24 00:00gdps_skew_47159_s006_2023072400.gif
199gdps2023-06-02 00:00gdps_skew_47159_s240_2023060200.gif
8472gdps2023-07-24 06:00gdps_skew_47159_s003_2023072406.gif
2011gdps2023-06-13 12:00gdps_skew_47159_s069_2023061312.gif
11781gdps2023-08-14 00:00gdps_skew_47159_s072_2023081400.gif
8379gdps2023-07-23 12:00gdps_skew_47159_s156_2023072312.gif
7843gdps2023-07-20 06:00gdps_skew_47159_s018_2023072006.gif
392gdps2023-06-03 06:00gdps_skew_47159_s075_2023060306.gif
4238gdps2023-06-27 12:00gdps_skew_47159_s072_2023062712.gif
11402gdps2023-08-11 12:00gdps_skew_47159_s228_2023081112.gif