Overview

Dataset statistics

Number of variables4
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows2
Duplicate rows (%)< 0.1%
Total size in memory390.6 KiB
Average record size in memory40.0 B

Variable types

Categorical1
Text2
DateTime1

Dataset

Description창원시설공단 시설/일자별 이용객 현황
Author창원시설공단
URLhttps://www.data.go.kr/data/15074944/fileData.do

Alerts

Dataset has 2 (< 0.1%) duplicate rowsDuplicates

Reproduction

Analysis started2023-12-12 20:06:10.442259
Analysis finished2023-12-12 20:06:10.931794
Duration0.49 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사업
Categorical

Distinct32
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
마산야구센터
874 
진동종합복지관
722 
의창스포츠센터
675 
성산스포츠센터
 
614
늘푸른전당
 
601
Other values (27)
6514 

Length

Max length11
Median length10
Mean length6.9758
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row성산스포츠센터
2nd row창원축구센터
3rd row늘푸른전당
4th row창원실내수영장
5th row진동종합복지관

Common Values

ValueCountFrequency (%)
마산야구센터 874
 
8.7%
진동종합복지관 722
 
7.2%
의창스포츠센터 675
 
6.8%
성산스포츠센터 614
 
6.1%
늘푸른전당 601
 
6.0%
창원국제사격장 532
 
5.3%
창원스포츠파크 529
 
5.3%
시민생활체육관 529
 
5.3%
우리누리청소년문화센터 481
 
4.8%
의창노인복지관 472
 
4.7%
Other values (22) 3971
39.7%

Length

2023-12-13T05:06:11.044029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
마산야구센터 874
 
8.7%
진동종합복지관 722
 
7.1%
의창스포츠센터 675
 
6.7%
성산스포츠센터 614
 
6.1%
늘푸른전당 601
 
5.9%
창원국제사격장 532
 
5.3%
창원스포츠파크 529
 
5.2%
시민생활체육관 529
 
5.2%
우리누리청소년문화센터 481
 
4.8%
의창노인복지관 472
 
4.7%
Other values (23) 4072
40.3%

이용고객
Text

Distinct176
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T05:06:11.312834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length6.0967
Min length2

Characters and Unicode

Total characters60967
Distinct characters205
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)0.1%

Sample

1st row수영
2nd row숙소동
3rd row헬스
4th row헬스
5th row진동-학교연계
ValueCountFrequency (%)
헬스 501
 
4.2%
사격장 497
 
4.1%
수영 407
 
3.4%
테니스장 391
 
3.2%
기타 360
 
3.0%
생활체육 327
 
2.7%
교육지원 251
 
2.1%
상복공원 235
 
2.0%
아쿠아로빅 235
 
2.0%
관광 210
 
1.7%
Other values (166) 8620
71.6%
2023-12-13T05:06:11.805068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 2847
 
4.7%
스 2126
 
3.5%
2034
 
3.3%
- 1617
 
2.7%
관 1330
 
2.2%
육 1310
 
2.1%
원 1222
 
2.0%
수 1188
 
1.9%
동 1178
 
1.9%
사 1144
 
1.9%
Other values (195) 44971
73.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 55256
90.6%
Space Separator 2034
 
3.3%
Dash Punctuation 1617
 
2.7%
Open Punctuation 940
 
1.5%
Close Punctuation 940
 
1.5%
Decimal Number 109
 
0.2%
Other Punctuation 71
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 2847
 
5.2%
스 2126
 
3.8%
관 1330
 
2.4%
육 1310
 
2.4%
원 1222
 
2.2%
수 1188
 
2.1%
동 1178
 
2.1%
사 1144
 
2.1%
기 1132
 
2.0%
체 1120
 
2.0%
Other values (183) 40659
73.6%
Decimal Number
ValueCountFrequency (%)
1 49
45.0%
4 47
43.1%
5 7
 
6.4%
3 3
 
2.8%
2 2
 
1.8%
6 1
 
0.9%
Other Punctuation
ValueCountFrequency (%)
/ 64
90.1%
. 7
 
9.9%
Space Separator
ValueCountFrequency (%)
2034
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1617
100.0%
Open Punctuation
ValueCountFrequency (%)
( 940
100.0%
Close Punctuation
ValueCountFrequency (%)
) 940
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 55256
90.6%
Common 5711
 
9.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 2847
 
5.2%
스 2126
 
3.8%
관 1330
 
2.4%
육 1310
 
2.4%
원 1222
 
2.2%
수 1188
 
2.1%
동 1178
 
2.1%
사 1144
 
2.1%
기 1132
 
2.0%
체 1120
 
2.0%
Other values (183) 40659
73.6%
Common
ValueCountFrequency (%)
2034
35.6%
- 1617
28.3%
( 940
16.5%
) 940
16.5%
/ 64
 
1.1%
1 49
 
0.9%
4 47
 
0.8%
5 7
 
0.1%
. 7
 
0.1%
3 3
 
0.1%
Other values (2) 3
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 55256
90.6%
ASCII 5711
 
9.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 2847
 
5.2%
스 2126
 
3.8%
관 1330
 
2.4%
육 1310
 
2.4%
원 1222
 
2.2%
수 1188
 
2.1%
동 1178
 
2.1%
사 1144
 
2.1%
기 1132
 
2.0%
체 1120
 
2.0%
Other values (183) 40659
73.6%
ASCII
ValueCountFrequency (%)
2034
35.6%
- 1617
28.3%
( 940
16.5%
) 940
16.5%
/ 64
 
1.1%
1 49
 
0.9%
4 47
 
0.8%
5 7
 
0.1%
. 7
 
0.1%
3 3
 
0.1%
Other values (2) 3
 
0.1%

일자
Date

Distinct365
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2019-01-01 00:00:00
Maximum2019-12-31 00:00:00
2023-12-13T05:06:11.992125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:06:12.175512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인원
Text

Distinct1557
Distinct (%)15.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T05:06:12.618725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.6974
Min length1

Characters and Unicode

Total characters26974
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique702 ?
Unique (%)7.0%

Sample

1st row1,268
2nd row25
3rd row418
4th row756
5th row40
ValueCountFrequency (%)
30 198
 
2.0%
50 193
 
1.9%
400 157
 
1.6%
20 154
 
1.5%
25 149
 
1.5%
2 143
 
1.4%
15 119
 
1.2%
100 106
 
1.1%
40 105
 
1.1%
4 104
 
1.0%
Other values (1547) 8572
85.7%
2023-12-13T05:06:13.221604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4080
15.1%
1 3805
14.1%
2 3356
12.4%
5 2914
10.8%
3 2658
9.9%
4 2363
8.8%
6 1991
7.4%
8 1748
6.5%
7 1647
6.1%
9 1520
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 26082
96.7%
Other Punctuation 892
 
3.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4080
15.6%
1 3805
14.6%
2 3356
12.9%
5 2914
11.2%
3 2658
10.2%
4 2363
9.1%
6 1991
7.6%
8 1748
6.7%
7 1647
6.3%
9 1520
 
5.8%
Other Punctuation
ValueCountFrequency (%)
, 892
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 26974
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4080
15.1%
1 3805
14.1%
2 3356
12.4%
5 2914
10.8%
3 2658
9.9%
4 2363
8.8%
6 1991
7.4%
8 1748
6.5%
7 1647
6.1%
9 1520
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26974
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4080
15.1%
1 3805
14.1%
2 3356
12.4%
5 2914
10.8%
3 2658
9.9%
4 2363
8.8%
6 1991
7.4%
8 1748
6.5%
7 1647
6.1%
9 1520
 
5.6%

Missing values

2023-12-13T05:06:10.753633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:06:10.867248image/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

사업이용고객일자인원
17104성산스포츠센터수영2019-08-291,268
51458창원축구센터숙소동2019-06-2225
3299늘푸른전당헬스2019-09-20418
50521창원실내수영장헬스2019-05-13756
37300진동종합복지관진동-학교연계2019-04-1340
20473시민생활체육관볼링2019-07-20729
22346시민생활체육관헬스2019-11-10800
27877의창노인복지관경로당활성화사업2019-11-068
4584마산합포노인복지관건강증진2019-03-15421
6777마산야구센터댄스2019-10-0734
사업이용고객일자인원
27854의창노인복지관건강증진2019-12-18322
10480마산야구센터올림픽배드민턴2019-05-02360
24568용원국민체육센터쥬니어스포츠2019-09-11199
965늘푸른전당기타시설2019-02-09500
51984창원축구센터인조구장42019-01-26130
21851시민생활체육관탁구2019-05-0629
1404늘푸른전당성문화센터2019-05-24130
5465마산합포노인복지관방문객2019-08-1249
40668진해해양레포츠스쿨해양시설팀12019-11-152
29171의창노인복지관이미용실2019-03-2015

Duplicate rows

Most frequently occurring

사업이용고객일자인원# duplicates
0마산야구센터아쿠아로빅2019-12-234282
1진해국민체육센터생활체육2019-08-071642