Overview

Dataset statistics

Number of variables5
Number of observations96
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.0 KiB
Average record size in memory42.4 B

Variable types

Numeric1
Categorical3
Text1

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15241/S/1/datasetView.do

Alerts

사용자코드 has constant value ""Constant

Reproduction

Analysis started2024-05-11 08:55:30.301322
Analysis finished2024-05-11 08:55:31.429448
Duration1.13 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

가입일시
Real number (ℝ)

Distinct6
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean202303.5
Minimum202301
Maximum202306
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size996.0 B
2024-05-11T08:55:31.676440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum202301
5-th percentile202301
Q1202302
median202303.5
Q3202305
95-th percentile202306
Maximum202306
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.7167902
Coefficient of variation (CV)8.4862108 × 10-6
Kurtosis-1.2720071
Mean202303.5
Median Absolute Deviation (MAD)1.5
Skewness0
Sum19421136
Variance2.9473684
MonotonicityIncreasing
2024-05-11T08:55:31.980299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
202301 16
16.7%
202302 16
16.7%
202303 16
16.7%
202304 16
16.7%
202305 16
16.7%
202306 16
16.7%
ValueCountFrequency (%)
202301 16
16.7%
202302 16
16.7%
202303 16
16.7%
202304 16
16.7%
202305 16
16.7%
202306 16
16.7%
ValueCountFrequency (%)
202306 16
16.7%
202305 16
16.7%
202304 16
16.7%
202303 16
16.7%
202302 16
16.7%
202301 16
16.7%

사용자코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size900.0 B
회원-내국인
96 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row회원-내국인
2nd row회원-내국인
3rd row회원-내국인
4th row회원-내국인
5th row회원-내국인

Common Values

ValueCountFrequency (%)
회원-내국인 96
100.0%

Length

2024-05-11T08:55:32.325449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:55:32.535903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
회원-내국인 96
100.0%

연령대코드
Categorical

Distinct8
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size900.0 B
~10대
12 
20대
12 
30대
12 
40대
12 
50대
12 
Other values (3)
36 

Length

Max length5
Median length3
Mean length3.25
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row~10대
2nd row20대
3rd row30대
4th row40대
5th row50대

Common Values

ValueCountFrequency (%)
~10대 12
12.5%
20대 12
12.5%
30대 12
12.5%
40대 12
12.5%
50대 12
12.5%
60대 12
12.5%
70대이상 12
12.5%
기타 12
12.5%

Length

2024-05-11T08:55:32.869148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:55:33.234622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10대 12
12.5%
20대 12
12.5%
30대 12
12.5%
40대 12
12.5%
50대 12
12.5%
60대 12
12.5%
70대이상 12
12.5%
기타 12
12.5%

성별
Categorical

Distinct2
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size900.0 B
F
48 
M
48 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
F 48
50.0%
M 48
50.0%

Length

2024-05-11T08:55:33.610808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:55:34.102744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
f 48
50.0%
m 48
50.0%

가입 수
Text

Distinct92
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Memory size900.0 B
2024-05-11T08:55:34.650149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length6.1041667
Min length2

Characters and Unicode

Total characters586
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique88 ?
Unique (%)91.7%

Sample

1st row 1,096
2nd row 2,006
3rd row 961
4th row 794
5th row 479
ValueCountFrequency (%)
39 2
 
2.1%
1,305 2
 
2.1%
66 2
 
2.1%
221 2
 
2.1%
2,322 1
 
1.0%
2,650 1
 
1.0%
4,544 1
 
1.0%
7,401 1
 
1.0%
14,840 1
 
1.0%
4,970 1
 
1.0%
Other values (82) 82
85.4%
2024-05-11T08:55:35.664401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
190
32.4%
, 59
 
10.1%
1 50
 
8.5%
2 40
 
6.8%
3 38
 
6.5%
4 37
 
6.3%
6 36
 
6.1%
9 33
 
5.6%
0 31
 
5.3%
5 26
 
4.4%
Other values (2) 46
 
7.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 337
57.5%
Space Separator 190
32.4%
Other Punctuation 59
 
10.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 50
14.8%
2 40
11.9%
3 38
11.3%
4 37
11.0%
6 36
10.7%
9 33
9.8%
0 31
9.2%
5 26
7.7%
8 24
7.1%
7 22
6.5%
Space Separator
ValueCountFrequency (%)
190
100.0%
Other Punctuation
ValueCountFrequency (%)
, 59
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 586
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
190
32.4%
, 59
 
10.1%
1 50
 
8.5%
2 40
 
6.8%
3 38
 
6.5%
4 37
 
6.3%
6 36
 
6.1%
9 33
 
5.6%
0 31
 
5.3%
5 26
 
4.4%
Other values (2) 46
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 586
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
190
32.4%
, 59
 
10.1%
1 50
 
8.5%
2 40
 
6.8%
3 38
 
6.5%
4 37
 
6.3%
6 36
 
6.1%
9 33
 
5.6%
0 31
 
5.3%
5 26
 
4.4%
Other values (2) 46
 
7.8%

Interactions

2024-05-11T08:55:30.599290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T08:55:35.945631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가입일시연령대코드성별가입 수
가입일시1.0000.0000.0000.499
연령대코드0.0001.0000.0000.954
성별0.0000.0001.0000.900
가입 수0.4990.9540.9001.000
2024-05-11T08:55:36.223605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
성별연령대코드
성별1.0000.000
연령대코드0.0001.000
2024-05-11T08:55:36.464198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가입일시연령대코드성별
가입일시1.0000.0000.000
연령대코드0.0001.0000.000
성별0.0000.0001.000

Missing values

2024-05-11T08:55:30.933325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T08:55:31.355989image/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

가입일시사용자코드연령대코드성별가입 수
0202301회원-내국인~10대F1,096
1202301회원-내국인20대F2,006
2202301회원-내국인30대F961
3202301회원-내국인40대F794
4202301회원-내국인50대F479
5202301회원-내국인60대F133
6202301회원-내국인70대이상F20
7202301회원-내국인기타F3
8202301회원-내국인~10대M1,286
9202301회원-내국인20대M2,177
가입일시사용자코드연령대코드성별가입 수
86202306회원-내국인70대이상F124
87202306회원-내국인기타F39
88202306회원-내국인~10대M4,923
89202306회원-내국인20대M11,694
90202306회원-내국인30대M7,983
91202306회원-내국인40대M5,734
92202306회원-내국인50대M3,583
93202306회원-내국인60대M1,305
94202306회원-내국인70대이상M236
95202306회원-내국인기타M68