Overview

Dataset statistics

Number of variables3
Number of observations106
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.6 KiB
Average record size in memory25.2 B

Variable types

Categorical1
Text1
DateTime1

Dataset

Description국립공원에서 운영되고 있는 우량국에 대해 국립공원사무소별로 구분되어 있으며, 최근 호출일시 정보가 포함된 데이터입니다.
Author국립공원공단
URLhttps://www.data.go.kr/data/15090618/fileData.do

Alerts

위치명(SLOCALNAME) has unique valuesUnique

Reproduction

Analysis started2023-12-12 20:01:59.371512
Analysis finished2023-12-12 20:01:59.637315
Duration0.27 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

산명칭(SAREANAME)
Categorical

Distinct21
Distinct (%)19.8%
Missing0
Missing (%)0.0%
Memory size980.0 B
지리산경남
24 
지리산전남
15 
월악산
9 
설악산
8 
치악산
6 
Other values (16)
44 

Length

Max length5
Median length4.5
Mean length3.990566
Min length3

Unique

Unique3 ?
Unique (%)2.8%

Sample

1st row설악산
2nd row지리산경남
3rd row지리산경남
4th row지리산경남
5th row지리산경남

Common Values

ValueCountFrequency (%)
지리산경남 24
22.6%
지리산전남 15
14.2%
월악산 9
 
8.5%
설악산 8
 
7.5%
치악산 6
 
5.7%
지리산전북 5
 
4.7%
속리산 4
 
3.8%
소백산 4
 
3.8%
태백산 4
 
3.8%
주왕산 4
 
3.8%
Other values (11) 23
21.7%

Length

2023-12-13T05:01:59.724972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
지리산경남 24
22.6%
지리산전남 15
14.2%
월악산 9
 
8.5%
설악산 8
 
7.5%
치악산 6
 
5.7%
지리산전북 5
 
4.7%
태백산 4
 
3.8%
주왕산 4
 
3.8%
덕유산 4
 
3.8%
소백산 4
 
3.8%
Other values (11) 23
21.7%

위치명(SLOCALNAME)
Text

UNIQUE 

Distinct106
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size980.0 B
2023-12-13T05:01:59.955598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length6.6320755
Min length5

Characters and Unicode

Total characters703
Distinct characters144
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique106 ?
Unique (%)100.0%

Sample

1st row장군바위우량국
2nd row순두류(지자체)
3rd row안내원(지자체)
4th row조개골우량국
5th row법계사(지자체)
ValueCountFrequency (%)
장군바위우량국 1
 
0.9%
도장골(지자체 1
 
0.9%
천문대우량국 1
 
0.9%
한신폭포우량국 1
 
0.9%
가야산중봉우량국 1
 
0.9%
상남탐방로우량국 1
 
0.9%
비로봉상우량국 1
 
0.9%
산동1우량국 1
 
0.9%
수렴동우량국 1
 
0.9%
까치봉능선우량국 1
 
0.9%
Other values (97) 97
90.7%
2023-12-13T05:02:00.382630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
우 92
 
13.1%
량 92
 
13.1%
국 86
 
12.2%
지 21
 
3.0%
자 20
 
2.8%
) 20
 
2.8%
체 20
 
2.8%
( 20
 
2.8%
봉 15
 
2.1%
사 13
 
1.8%
Other values (134) 304
43.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 644
91.6%
Close Punctuation 20
 
2.8%
Open Punctuation 20
 
2.8%
Decimal Number 18
 
2.6%
Space Separator 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
우 92
 
14.3%
량 92
 
14.3%
국 86
 
13.4%
지 21
 
3.3%
자 20
 
3.1%
체 20
 
3.1%
봉 15
 
2.3%
사 13
 
2.0%
골 12
 
1.9%
수 9
 
1.4%
Other values (127) 264
41.0%
Decimal Number
ValueCountFrequency (%)
2 8
44.4%
1 7
38.9%
3 2
 
11.1%
4 1
 
5.6%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 644
91.6%
Common 59
 
8.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
우 92
 
14.3%
량 92
 
14.3%
국 86
 
13.4%
지 21
 
3.3%
자 20
 
3.1%
체 20
 
3.1%
봉 15
 
2.3%
사 13
 
2.0%
골 12
 
1.9%
수 9
 
1.4%
Other values (127) 264
41.0%
Common
ValueCountFrequency (%)
) 20
33.9%
( 20
33.9%
2 8
 
13.6%
1 7
 
11.9%
3 2
 
3.4%
4 1
 
1.7%
1
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 644
91.6%
ASCII 59
 
8.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
우 92
 
14.3%
량 92
 
14.3%
국 86
 
13.4%
지 21
 
3.3%
자 20
 
3.1%
체 20
 
3.1%
봉 15
 
2.3%
사 13
 
2.0%
골 12
 
1.9%
수 9
 
1.4%
Other values (127) 264
41.0%
ASCII
ValueCountFrequency (%)
) 20
33.9%
( 20
33.9%
2 8
 
13.6%
1 7
 
11.9%
3 2
 
3.4%
4 1
 
1.7%
1
 
1.7%

최근호출일시(LASTCALLTIME)
Date

Distinct12
Distinct (%)11.3%
Missing0
Missing (%)0.0%
Memory size980.0 B
Minimum2021-08-22 21:00:00
Maximum2021-09-28 18:00:00
2023-12-13T05:02:00.504109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:02:00.618528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)

Correlations

2023-12-13T05:02:00.706913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
산명칭(SAREANAME)최근호출일시(LASTCALLTIME)
산명칭(SAREANAME)1.0000.512
최근호출일시(LASTCALLTIME)0.5121.000

Missing values

2023-12-13T05:01:59.521276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:01:59.600245image/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

산명칭(SAREANAME)위치명(SLOCALNAME)최근호출일시(LASTCALLTIME)
0설악산장군바위우량국2021/09/28 18:00
1지리산경남순두류(지자체)2021/09/28 18:00
2지리산경남안내원(지자체)2021/09/28 18:00
3지리산경남조개골우량국2021/09/28 18:00
4지리산경남법계사(지자체)2021/09/28 18:00
5설악산성국사우량국2021/09/28 18:00
6지리산전북와운우량국2021/09/28 18:00
7속리산쌍곡폭포우량국2021/09/28 18:00
8월악산덕주우량국2021/09/28 18:00
9월악산청벽대우량국2021/09/28 18:00
산명칭(SAREANAME)위치명(SLOCALNAME)최근호출일시(LASTCALLTIME)
96지리산전북달궁우량국2021/09/28 18:00
97속리산제수리재우량국2021/09/28 18:00
98덕유산백련사우량국2021/09/28 18:00
99치악산세렴우량국2021/09/28 18:00
100월악산만수우량국2021/09/28 18:00
101무등산동부도원우량국2021/09/28 18:00
102태백산부쇠봉2우량2021/09/28 18:00
103지리산경남두지터(지자체)2021/09/27 07:00
104지리산전남심원3우량국2021/09/28 18:00
105지리산전남천은사1우량국2021/09/28 18:00