Overview

Dataset statistics

Number of variables7
Number of observations90
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.5 KiB
Average record size in memory62.5 B

Variable types

Categorical1
Text1
Numeric5

Dataset

Description독립기념관 소장자료 현황으로 제목, 분류, 시대, 저자, 발행처 등의 정보를 제공합니다.
Author독립기념관
URLhttps://www.data.go.kr/data/15007464/fileData.do

Alerts

구입 is highly overall correlated with 기증 and 1 other fieldsHigh correlation
기증 is highly overall correlated with 구입 and 2 other fieldsHigh correlation
복제 is highly overall correlated with 기증 and 1 other fieldsHigh correlation
합계 is highly overall correlated with 구입 and 2 other fieldsHigh correlation
구입 has 11 (12.2%) zerosZeros
기증 has 4 (4.4%) zerosZeros
복제 has 28 (31.1%) zerosZeros
위탁 has 47 (52.2%) zerosZeros

Reproduction

Analysis started2023-12-12 00:49:26.924284
Analysis finished2023-12-12 00:49:30.093195
Duration3.17 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

Distinct9
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size852.0 B
전적류
12 
문서류
11 
과학기술류
11 
문화예술종교
10 
생활류
10 
Other values (4)
36 

Length

Max length6
Median length5
Mean length4.0666667
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전적류 12
13.3%
문서류 11
12.2%
과학기술류 11
12.2%
문화예술종교 10
11.1%
생활류 10
11.1%
군장류 10
11.1%
사진필름류 10
11.1%
산업생업류 8
8.9%
동영상류 8
8.9%

Length

2023-12-12T09:49:30.189726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:49:30.339305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전적류 12
13.3%
문서류 11
12.2%
과학기술류 11
12.2%
문화예술종교 10
11.1%
생활류 10
11.1%
군장류 10
11.1%
사진필름류 10
11.1%
산업생업류 8
8.9%
동영상류 8
8.9%

종류
Text

Distinct73
Distinct (%)81.1%
Missing0
Missing (%)0.0%
Memory size852.0 B
2023-12-12T09:49:30.700585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length3.8666667
Min length2

Characters and Unicode

Total characters348
Distinct characters124
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique69 ?
Unique (%)76.7%

Sample

1st row고서류
2nd row단행본류
3rd row화보/도록류
4th row일기/수기류
5th row원고류
ValueCountFrequency (%)
합계 8
 
8.9%
기타류 8
 
8.9%
미지정 3
 
3.3%
기치류 2
 
2.2%
상업 1
 
1.1%
의료 1
 
1.1%
지리 1
 
1.1%
천문 1
 
1.1%
광업 1
 
1.1%
임업 1
 
1.1%
Other values (63) 63
70.0%
2023-12-12T09:49:31.236375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
류 52
 
14.9%
기 14
 
4.0%
/ 14
 
4.0%
서 11
 
3.2%
문 10
 
2.9%
사 9
 
2.6%
합 8
 
2.3%
타 8
 
2.3%
계 8
 
2.3%
활 6
 
1.7%
Other values (114) 208
59.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 319
91.7%
Other Punctuation 14
 
4.0%
Uppercase Letter 9
 
2.6%
Close Punctuation 3
 
0.9%
Open Punctuation 3
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
류 52
 
16.3%
기 14
 
4.4%
서 11
 
3.4%
문 10
 
3.1%
사 9
 
2.8%
합 8
 
2.5%
타 8
 
2.5%
계 8
 
2.5%
활 6
 
1.9%
지 6
 
1.9%
Other values (105) 187
58.6%
Uppercase Letter
ValueCountFrequency (%)
D 3
33.3%
P 2
22.2%
S 1
 
11.1%
L 1
 
11.1%
C 1
 
11.1%
V 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
/ 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 319
91.7%
Common 20
 
5.7%
Latin 9
 
2.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
류 52
 
16.3%
기 14
 
4.4%
서 11
 
3.4%
문 10
 
3.1%
사 9
 
2.8%
합 8
 
2.5%
타 8
 
2.5%
계 8
 
2.5%
활 6
 
1.9%
지 6
 
1.9%
Other values (105) 187
58.6%
Latin
ValueCountFrequency (%)
D 3
33.3%
P 2
22.2%
S 1
 
11.1%
L 1
 
11.1%
C 1
 
11.1%
V 1
 
11.1%
Common
ValueCountFrequency (%)
/ 14
70.0%
) 3
 
15.0%
( 3
 
15.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 319
91.7%
ASCII 29
 
8.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
류 52
 
16.3%
기 14
 
4.4%
서 11
 
3.4%
문 10
 
3.1%
사 9
 
2.8%
합 8
 
2.5%
타 8
 
2.5%
계 8
 
2.5%
활 6
 
1.9%
지 6
 
1.9%
Other values (105) 187
58.6%
ASCII
ValueCountFrequency (%)
/ 14
48.3%
D 3
 
10.3%
) 3
 
10.3%
( 3
 
10.3%
P 2
 
6.9%
S 1
 
3.4%
L 1
 
3.4%
C 1
 
3.4%
V 1
 
3.4%

구입
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct58
Distinct (%)64.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean581.83333
Minimum0
Maximum7891
Zeros11
Zeros (%)12.2%
Negative0
Negative (%)0.0%
Memory size942.0 B
2023-12-12T09:49:31.421281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.25
median31.5
Q3266
95-th percentile2933.15
Maximum7891
Range7891
Interquartile range (IQR)264.75

Descriptive statistics

Standard deviation1542.625
Coefficient of variation (CV)2.6513178
Kurtosis12.984175
Mean581.83333
Median Absolute Deviation (MAD)31.5
Skewness3.600053
Sum52365
Variance2379692
MonotonicityNot monotonic
2023-12-12T09:49:31.624495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 12
 
13.3%
0 11
 
12.2%
2 5
 
5.6%
9 3
 
3.3%
5 3
 
3.3%
8 2
 
2.2%
7 2
 
2.2%
4 2
 
2.2%
15 1
 
1.1%
25 1
 
1.1%
Other values (48) 48
53.3%
ValueCountFrequency (%)
0 11
12.2%
1 12
13.3%
2 5
5.6%
4 2
 
2.2%
5 3
 
3.3%
6 1
 
1.1%
7 2
 
2.2%
8 2
 
2.2%
9 3
 
3.3%
15 1
 
1.1%
ValueCountFrequency (%)
7891 1
1.1%
7485 1
1.1%
6988 1
1.1%
5647 1
1.1%
2984 1
1.1%
2871 1
1.1%
2780 1
1.1%
2434 1
1.1%
2328 1
1.1%
1520 1
1.1%

기증
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct75
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1141.6
Minimum0
Maximum28986
Zeros4
Zeros (%)4.4%
Negative0
Negative (%)0.0%
Memory size942.0 B
2023-12-12T09:49:31.823025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q118.25
median103
Q3645.5
95-th percentile5324.65
Maximum28986
Range28986
Interquartile range (IQR)627.25

Descriptive statistics

Standard deviation3507.2171
Coefficient of variation (CV)3.0721944
Kurtosis45.968462
Mean1141.6
Median Absolute Deviation (MAD)102.5
Skewness6.2450981
Sum102744
Variance12300572
MonotonicityNot monotonic
2023-12-12T09:49:32.018855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4
 
4.4%
2 4
 
4.4%
3 3
 
3.3%
41 3
 
3.3%
7 2
 
2.2%
9 2
 
2.2%
14 2
 
2.2%
1 2
 
2.2%
222 2
 
2.2%
6 1
 
1.1%
Other values (65) 65
72.2%
ValueCountFrequency (%)
0 4
4.4%
1 2
2.2%
2 4
4.4%
3 3
3.3%
6 1
 
1.1%
7 2
2.2%
8 1
 
1.1%
9 2
2.2%
13 1
 
1.1%
14 2
2.2%
ValueCountFrequency (%)
28986 1
1.1%
10779 1
1.1%
10082 1
1.1%
6383 1
1.1%
6109 1
1.1%
4366 1
1.1%
3640 1
1.1%
2894 1
1.1%
1936 1
1.1%
1908 1
1.1%

복제
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct51
Distinct (%)56.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean249.86667
Minimum0
Maximum7609
Zeros28
Zeros (%)31.1%
Negative0
Negative (%)0.0%
Memory size942.0 B
2023-12-12T09:49:32.170302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median11.5
Q386.75
95-th percentile1299.6
Maximum7609
Range7609
Interquartile range (IQR)86.75

Descriptive statistics

Standard deviation913.12668
Coefficient of variation (CV)3.6544558
Kurtosis48.734032
Mean249.86667
Median Absolute Deviation (MAD)11.5
Skewness6.4760858
Sum22488
Variance833800.34
MonotonicityNot monotonic
2023-12-12T09:49:32.337802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 28
31.1%
4 3
 
3.3%
27 3
 
3.3%
10 2
 
2.2%
5 2
 
2.2%
12 2
 
2.2%
8 2
 
2.2%
35 2
 
2.2%
2 2
 
2.2%
3 2
 
2.2%
Other values (41) 42
46.7%
ValueCountFrequency (%)
0 28
31.1%
1 2
 
2.2%
2 2
 
2.2%
3 2
 
2.2%
4 3
 
3.3%
5 2
 
2.2%
6 1
 
1.1%
8 2
 
2.2%
10 2
 
2.2%
11 1
 
1.1%
ValueCountFrequency (%)
7609 1
1.1%
2518 1
1.1%
2494 1
1.1%
2061 1
1.1%
1314 1
1.1%
1282 1
1.1%
856 1
1.1%
493 1
1.1%
411 1
1.1%
333 1
1.1%

위탁
Real number (ℝ)

ZEROS 

Distinct28
Distinct (%)31.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.344444
Minimum0
Maximum323
Zeros47
Zeros (%)52.2%
Negative0
Negative (%)0.0%
Memory size942.0 B
2023-12-12T09:49:32.524086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q37.75
95-th percentile143.3
Maximum323
Range323
Interquartile range (IQR)7.75

Descriptive statistics

Standard deviation55.520653
Coefficient of variation (CV)2.7290327
Kurtosis14.422467
Mean20.344444
Median Absolute Deviation (MAD)0
Skewness3.7371288
Sum1831
Variance3082.5429
MonotonicityNot monotonic
2023-12-12T09:49:32.683871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0 47
52.2%
1 7
 
7.8%
2 4
 
4.4%
7 3
 
3.3%
3 2
 
2.2%
5 2
 
2.2%
30 2
 
2.2%
15 2
 
2.2%
27 2
 
2.2%
323 1
 
1.1%
Other values (18) 18
 
20.0%
ValueCountFrequency (%)
0 47
52.2%
1 7
 
7.8%
2 4
 
4.4%
3 2
 
2.2%
4 1
 
1.1%
5 2
 
2.2%
6 1
 
1.1%
7 3
 
3.3%
8 1
 
1.1%
10 1
 
1.1%
ValueCountFrequency (%)
323 1
1.1%
236 1
1.1%
226 1
1.1%
186 1
1.1%
182 1
1.1%
96 1
1.1%
95 1
1.1%
58 1
1.1%
52 1
1.1%
38 1
1.1%

합계
Real number (ℝ)

HIGH CORRELATION 

Distinct84
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1993.6444
Minimum1
Maximum44672
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size942.0 B
2023-12-12T09:49:32.819659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q154
median224
Q31545.75
95-th percentile8862.8
Maximum44672
Range44671
Interquartile range (IQR)1491.75

Descriptive statistics

Standard deviation5537.1109
Coefficient of variation (CV)2.7773814
Kurtosis41.197933
Mean1993.6444
Median Absolute Deviation (MAD)219.5
Skewness5.8604744
Sum179428
Variance30659597
MonotonicityNot monotonic
2023-12-12T09:49:33.241912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16 3
 
3.3%
63 2
 
2.2%
3 2
 
2.2%
1777 2
 
2.2%
4 2
 
2.2%
2584 1
 
1.1%
259 1
 
1.1%
211 1
 
1.1%
30 1
 
1.1%
2039 1
 
1.1%
Other values (74) 74
82.2%
ValueCountFrequency (%)
1 1
 
1.1%
2 1
 
1.1%
3 2
2.2%
4 2
2.2%
5 1
 
1.1%
9 1
 
1.1%
12 1
 
1.1%
13 1
 
1.1%
16 3
3.3%
22 1
 
1.1%
ValueCountFrequency (%)
44672 1
1.1%
20812 1
1.1%
11899 1
1.1%
10265 1
1.1%
9932 1
1.1%
7556 1
1.1%
7434 1
1.1%
6926 1
1.1%
5208 1
1.1%
4609 1
1.1%

Interactions

2023-12-12T09:49:29.399076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:49:27.236826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:49:27.822337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:49:28.337966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:49:28.909615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:49:29.507045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:49:27.348508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:49:27.915571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:49:28.499526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:49:29.014531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:49:29.597252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:49:27.463770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:49:28.014042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:49:28.587545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:49:29.105494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:49:29.707155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:49:27.593321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:49:28.114094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:49:28.694542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:49:29.196401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:49:29.791002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:49:27.719719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:49:28.217056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:49:28.813283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:49:29.296500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T09:49:33.344838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분종류구입기증복제위탁합계
구분1.0000.0000.0900.1680.0880.0000.399
종류0.0001.0000.7560.0000.0000.0000.000
구입0.0900.7561.0000.6930.6990.5590.789
기증0.1680.0000.6931.0000.9260.6200.984
복제0.0880.0000.6990.9261.0000.5340.935
위탁0.0000.0000.5590.6200.5341.0000.604
합계0.3990.0000.7890.9840.9350.6041.000
2023-12-12T09:49:33.452726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구입기증복제위탁합계구분
구입1.0000.7190.3520.2200.8430.033
기증0.7191.0000.5220.4240.9420.089
복제0.3520.5221.0000.4910.5390.038
위탁0.2200.4240.4911.0000.4240.000
합계0.8430.9420.5390.4241.0000.236
구분0.0330.0890.0380.0000.2361.000

Missing values

2023-12-12T09:49:29.908600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:49:30.045071image/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

구분종류구입기증복제위탁합계
0전적류고서류3971766411102584
1전적류단행본류27803640493136926
2전적류화보/도록류7487506829
3전적류일기/수기류832221630468
4전적류원고류8519230550
5전적류교과서류446384270857
6전적류연간물9776264701650
7전적류신문류15201365128214168
8전적류지도류300666330999
9전적류기타류22215163901777
구분종류구입기증복제위탁합계
80사진필름류흑백사진78443660585208
81사진필름류흑백복사56471908017556
82사진필름류칼라사진242775001017
83사진필름류칼라복사58029300873
84사진필름류유리원판010500105
85사진필름류마이크로필름6988446007434
86사진필름류사진첩/앨범2851492001777
87사진필름류슬라이드필름23453100765
88사진필름류기타류5522600578
89사진필름류미지정10001