Overview

Dataset statistics

Number of variables7
Number of observations9638
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory564.9 KiB
Average record size in memory60.0 B

Variable types

Categorical1
Numeric4
Text1
DateTime1

Dataset

Description충청북도 청주시에 위치한 고인쇄박물관에 소장하고 있는 고인쇄 문화, 금속활자 등 유물의 전시관리에 대한 정보를 제공합니다.
URLhttps://www.data.go.kr/data/15041949/fileData.do

Alerts

박물관 코드 has constant value ""Constant
메이저 is highly skewed (γ1 = 36.15731867)Skewed
배터리잔량율 is highly skewed (γ1 = -49.81486655)Skewed

Reproduction

Analysis started2023-12-12 08:05:38.429379
Analysis finished2023-12-12 08:05:40.519324
Duration2.09 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

박물관 코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size75.4 KiB
PS01003018
9638 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPS01003018
2nd rowPS01003018
3rd rowPS01003018
4th rowPS01003018
5th rowPS01003018

Common Values

ValueCountFrequency (%)
PS01003018 9638
100.0%

Length

2023-12-12T17:05:40.608271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:05:40.724308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
ps01003018 9638
100.0%

비콘순번
Real number (ℝ)

Distinct9632
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean110016.08
Minimum105111
Maximum114874
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size84.8 KiB
2023-12-12T17:05:40.841095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum105111
5-th percentile105666.85
Q1107594.25
median110003.5
Q3112450.75
95-th percentile114392.15
Maximum114874
Range9763
Interquartile range (IQR)4856.5

Descriptive statistics

Standard deviation2805.526
Coefficient of variation (CV)0.025501053
Kurtosis-1.1950331
Mean110016.08
Median Absolute Deviation (MAD)2428.5
Skewness0.00018656686
Sum1.060335 × 109
Variance7870975.9
MonotonicityNot monotonic
2023-12-12T17:05:41.016939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
105189 2
 
< 0.1%
105190 2
 
< 0.1%
105191 2
 
< 0.1%
105192 2
 
< 0.1%
105193 2
 
< 0.1%
105188 2
 
< 0.1%
111695 1
 
< 0.1%
111694 1
 
< 0.1%
111643 1
 
< 0.1%
111644 1
 
< 0.1%
Other values (9622) 9622
99.8%
ValueCountFrequency (%)
105111 1
< 0.1%
105112 1
< 0.1%
105113 1
< 0.1%
105114 1
< 0.1%
105115 1
< 0.1%
105116 1
< 0.1%
105117 1
< 0.1%
105118 1
< 0.1%
105119 1
< 0.1%
105120 1
< 0.1%
ValueCountFrequency (%)
114874 1
< 0.1%
114873 1
< 0.1%
114872 1
< 0.1%
114871 1
< 0.1%
114870 1
< 0.1%
114869 1
< 0.1%
114868 1
< 0.1%
114867 1
< 0.1%
114866 1
< 0.1%
114865 1
< 0.1%

맥주소
Text

Distinct119
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size75.4 KiB
2023-12-12T17:05:41.274626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length17
Mean length17
Min length17

Characters and Unicode

Total characters163846
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)0.2%

Sample

1st rowC2:00:16:00:00:C9
2nd rowC2:00:16:00:00:7A
3rd rowC2:00:16:00:00:81
4th rowC2:00:16:00:00:57
5th rowC2:00:16:00:00:9B
ValueCountFrequency (%)
c2:00:16:00:00:8c 214
 
2.2%
c2:00:16:00:00:7d 210
 
2.2%
c2:00:16:00:00:7e 209
 
2.2%
c2:00:16:00:00:8b 208
 
2.2%
c2:00:16:00:00:79 208
 
2.2%
c1:00:ba:00:00:b1 208
 
2.2%
c2:00:16:00:00:73 207
 
2.1%
c2:00:16:00:00:7a 203
 
2.1%
c1:00:ba:00:00:bf 202
 
2.1%
c2:00:16:00:00:81 201
 
2.1%
Other values (109) 7568
78.5%
2023-12-12T17:05:41.703410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 58276
35.6%
: 48190
29.4%
C 11066
 
6.8%
6 10874
 
6.6%
1 10083
 
6.2%
2 9144
 
5.6%
7 2944
 
1.8%
B 2446
 
1.5%
8 2007
 
1.2%
5 1874
 
1.1%
Other values (7) 6942
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 98229
60.0%
Other Punctuation 48190
29.4%
Uppercase Letter 17427
 
10.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 58276
59.3%
6 10874
 
11.1%
1 10083
 
10.3%
2 9144
 
9.3%
7 2944
 
3.0%
8 2007
 
2.0%
5 1874
 
1.9%
9 1659
 
1.7%
4 715
 
0.7%
3 653
 
0.7%
Uppercase Letter
ValueCountFrequency (%)
C 11066
63.5%
B 2446
 
14.0%
A 1699
 
9.7%
D 838
 
4.8%
E 729
 
4.2%
F 649
 
3.7%
Other Punctuation
ValueCountFrequency (%)
: 48190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 146419
89.4%
Latin 17427
 
10.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 58276
39.8%
: 48190
32.9%
6 10874
 
7.4%
1 10083
 
6.9%
2 9144
 
6.2%
7 2944
 
2.0%
8 2007
 
1.4%
5 1874
 
1.3%
9 1659
 
1.1%
4 715
 
0.5%
Latin
ValueCountFrequency (%)
C 11066
63.5%
B 2446
 
14.0%
A 1699
 
9.7%
D 838
 
4.8%
E 729
 
4.2%
F 649
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 163846
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 58276
35.6%
: 48190
29.4%
C 11066
 
6.8%
6 10874
 
6.6%
1 10083
 
6.2%
2 9144
 
5.6%
7 2944
 
1.8%
B 2446
 
1.5%
8 2007
 
1.2%
5 1874
 
1.1%
Other values (7) 6942
 
4.2%

메이저
Real number (ℝ)

SKEWED 

Distinct14
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3029.4344
Minimum1001
Maximum30001
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size84.8 KiB
2023-12-12T17:05:41.870658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1001
5-th percentile3018
Q13018
median3018
Q33018
95-th percentile3018
Maximum30001
Range29000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation616.28435
Coefficient of variation (CV)0.20343215
Kurtosis1535.8095
Mean3029.4344
Median Absolute Deviation (MAD)0
Skewness36.157319
Sum29197689
Variance379806.39
MonotonicityNot monotonic
2023-12-12T17:05:42.004533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
3018 9566
99.3%
1001 17
 
0.2%
9002 12
 
0.1%
1012 10
 
0.1%
2001 10
 
0.1%
30001 4
 
< 0.1%
9001 4
 
< 0.1%
1010 3
 
< 0.1%
1007 3
 
< 0.1%
1003 3
 
< 0.1%
Other values (4) 6
 
0.1%
ValueCountFrequency (%)
1001 17
0.2%
1003 3
 
< 0.1%
1007 3
 
< 0.1%
1008 2
 
< 0.1%
1010 3
 
< 0.1%
1011 1
 
< 0.1%
1012 10
0.1%
1013 1
 
< 0.1%
1611 2
 
< 0.1%
2001 10
0.1%
ValueCountFrequency (%)
30001 4
 
< 0.1%
9002 12
 
0.1%
9001 4
 
< 0.1%
3018 9566
99.3%
2001 10
 
0.1%
1611 2
 
< 0.1%
1013 1
 
< 0.1%
1012 10
 
0.1%
1011 1
 
< 0.1%
1010 3
 
< 0.1%

마이너
Real number (ℝ)

Distinct117
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2026.2661
Minimum77
Maximum50052
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size84.8 KiB
2023-12-12T17:05:42.178660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum77
5-th percentile1031
Q11082
median2042
Q32142
95-th percentile4022
Maximum50052
Range49975
Interquartile range (IQR)1060

Descriptive statistics

Standard deviation2259.8364
Coefficient of variation (CV)1.1152713
Kurtosis219.48793
Mean2026.2661
Median Absolute Deviation (MAD)930
Skewness13.497989
Sum19529153
Variance5106860.8
MonotonicityNot monotonic
2023-12-12T17:05:42.371387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1051 214
 
2.2%
1102 211
 
2.2%
1101 209
 
2.2%
1062 208
 
2.2%
1061 208
 
2.2%
1071 208
 
2.2%
1052 207
 
2.1%
1072 203
 
2.1%
1081 202
 
2.1%
1031 201
 
2.1%
Other values (107) 7567
78.5%
ValueCountFrequency (%)
77 2
 
< 0.1%
1011 180
1.9%
1012 184
1.9%
1021 30
 
0.3%
1022 28
 
0.3%
1031 201
2.1%
1032 187
1.9%
1041 38
 
0.4%
1042 44
 
0.5%
1051 214
2.2%
ValueCountFrequency (%)
50052 1
 
< 0.1%
50051 1
 
< 0.1%
44014 1
 
< 0.1%
39022 2
 
< 0.1%
39021 3
< 0.1%
39012 6
0.1%
39011 5
0.1%
37012 2
 
< 0.1%
37011 2
 
< 0.1%
36082 1
 
< 0.1%

배터리잔량율
Real number (ℝ)

SKEWED 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean99.96161
Minimum6
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size84.8 KiB
2023-12-12T17:05:42.514923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile100
Q1100
median100
Q3100
95-th percentile100
Maximum100
Range94
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.6431644
Coefficient of variation (CV)0.016437954
Kurtosis2594.0078
Mean99.96161
Median Absolute Deviation (MAD)0
Skewness-49.814867
Sum963430
Variance2.6999892
MonotonicityNot monotonic
2023-12-12T17:05:42.637399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
100 9627
99.9%
97 4
 
< 0.1%
88 2
 
< 0.1%
55 1
 
< 0.1%
18 1
 
< 0.1%
6 1
 
< 0.1%
73 1
 
< 0.1%
14 1
 
< 0.1%
ValueCountFrequency (%)
6 1
 
< 0.1%
14 1
 
< 0.1%
18 1
 
< 0.1%
55 1
 
< 0.1%
73 1
 
< 0.1%
88 2
 
< 0.1%
97 4
 
< 0.1%
100 9627
99.9%
ValueCountFrequency (%)
100 9627
99.9%
97 4
 
< 0.1%
88 2
 
< 0.1%
73 1
 
< 0.1%
55 1
 
< 0.1%
18 1
 
< 0.1%
14 1
 
< 0.1%
6 1
 
< 0.1%

수정일자
Date

Distinct173
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size75.4 KiB
Minimum2018-03-12 00:00:00
Maximum2019-12-15 00:00:00
2023-12-12T17:05:42.764856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:05:42.931972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-12T17:05:39.979313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:05:38.915504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:05:39.286473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:05:39.665551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:05:40.057506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:05:39.005830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:05:39.393767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:05:39.746093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:05:40.159572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:05:39.108366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:05:39.494773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:05:39.829916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:05:40.241410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:05:39.196220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:05:39.583609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:05:39.903715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:05:43.058644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비콘순번메이저마이너배터리잔량율
비콘순번1.0000.0940.0760.024
메이저0.0941.0000.9360.000
마이너0.0760.9361.0000.643
배터리잔량율0.0240.0000.6431.000
2023-12-12T17:05:43.218478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비콘순번메이저마이너배터리잔량율
비콘순번1.0000.0140.030-0.037
메이저0.0141.000-0.0420.319
마이너0.030-0.0421.000-0.028
배터리잔량율-0.0370.319-0.0281.000

Missing values

2023-12-12T17:05:40.352582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:05:40.467628image/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

박물관 코드비콘순번맥주소메이저마이너배터리잔량율수정일자
0PS01003018105111C2:00:16:00:00:C9301840321002019-02-24
1PS01003018105112C2:00:16:00:00:7A301810721002019-04-14
2PS01003018105113C2:00:16:00:00:81301810311002019-04-14
3PS01003018105114C2:00:16:00:00:57301830221002019-04-14
4PS01003018105115C2:00:16:00:00:9B301821311002019-04-14
5PS01003018105116C2:00:16:00:00:6F301820911002019-04-14
6PS01003018105117C1:00:BA:00:00:2F301821621002019-04-14
7PS01003018105118C2:00:16:00:00:88301830311002019-03-23
8PS01003018105119C2:00:16:00:00:91301840711002018-07-17
9PS01003018105120C2:00:16:00:00:93301830421002019-03-03
박물관 코드비콘순번맥주소메이저마이너배터리잔량율수정일자
9628PS01003018114865C2:00:16:00:00:58301830211002019-12-15
9629PS01003018114866C1:00:BA:00:00:B5301820621002019-12-15
9630PS01003018114867C2:00:16:00:00:89301810421002019-12-15
9631PS01003018114868C2:00:16:00:00:86301840421002019-12-15
9632PS01003018114869C2:00:16:00:00:87301830321002019-12-15
9633PS01003018114870C2:00:16:00:00:6A301810321002019-12-15
9634PS01003018114871C1:00:BA:00:00:B7301820721002019-12-15
9635PS01003018114872C2:00:16:00:00:5C301820711002019-12-15
9636PS01003018114873C2:00:16:00:00:79301810711002019-12-15
9637PS01003018114874C2:00:16:00:00:7A301810721002019-12-15