Overview

Dataset statistics

Number of variables12
Number of observations100
Missing cells1
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.7 KiB
Average record size in memory99.3 B

Variable types

Numeric2
Text3
Categorical7

Alerts

ty_nm has constant value ""Constant
signgu_nm is highly overall correlated with data_manage_no and 6 other fieldsHigh correlation
lwprt_cl_nm is highly overall correlated with sumry_cn and 2 other fieldsHigh correlation
sumry_cn is highly overall correlated with data_manage_no and 6 other fieldsHigh correlation
ctprvn_nm is highly overall correlated with data_manage_no and 4 other fieldsHigh correlation
cl_nm is highly overall correlated with sumry_cn and 3 other fieldsHigh correlation
data_manage_no is highly overall correlated with sumry_cn and 3 other fieldsHigh correlation
regist_de is highly overall correlated with sumry_cn and 2 other fieldsHigh correlation
lwprt_data_ty_nm is highly overall correlated with data_manage_no and 4 other fieldsHigh correlation
cl_nm is highly imbalanced (91.9%)Imbalance
lwprt_cl_nm is highly imbalanced (58.2%)Imbalance
lwprt_data_ty_nm is highly imbalanced (58.4%)Imbalance
data_manage_no has unique valuesUnique
cntnts_url has unique valuesUnique

Reproduction

Analysis started2023-12-10 09:48:43.219487
Analysis finished2023-12-10 09:48:45.882243
Duration2.66 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

data_manage_no
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13668.25
Minimum10963
Maximum29471
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:48:46.021536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10963
5-th percentile12813.95
Q112834.75
median12860.5
Q312885.25
95-th percentile13951.5
Maximum29471
Range18508
Interquartile range (IQR)50.5

Descriptive statistics

Standard deviation3652.3702
Coefficient of variation (CV)0.26721564
Kurtosis15.672045
Mean13668.25
Median Absolute Deviation (MAD)25.5
Skewness4.1475483
Sum1366825
Variance13339808
MonotonicityNot monotonic
2023-12-10T18:48:46.337496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12442 1
 
1.0%
12894 1
 
1.0%
13132 1
 
1.0%
13131 1
 
1.0%
13130 1
 
1.0%
13129 1
 
1.0%
12905 1
 
1.0%
12903 1
 
1.0%
12901 1
 
1.0%
12899 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
10963 1
1.0%
10967 1
1.0%
12442 1
1.0%
12812 1
1.0%
12813 1
1.0%
12814 1
1.0%
12816 1
1.0%
12817 1
1.0%
12818 1
1.0%
12819 1
1.0%
ValueCountFrequency (%)
29471 1
1.0%
29470 1
1.0%
29469 1
1.0%
29447 1
1.0%
29446 1
1.0%
13136 1
1.0%
13135 1
1.0%
13134 1
1.0%
13133 1
1.0%
13132 1
1.0%

data_title_nm
Text

Distinct60
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:48:46.938707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length18
Mean length11.34
Min length2

Characters and Unicode

Total characters1134
Distinct characters207
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

Unique49 ?
Unique (%)49.0%

Sample

1st row모전들소리 보존 사업 '모심기 소리'
2nd row늙은 호박전
3rd row목사행렬 재현 영상 콘텐츠
4th row해남 향토문화 제2막 3장 영상콘텐츠
5th row관립교동소학교 표석
ValueCountFrequency (%)
서울 27
 
9.5%
풍물시장-골동품 11
 
3.9%
풍물시장-청춘일번가 9
 
3.2%
터 9
 
3.2%
표석 7
 
2.5%
풍물시장 7
 
2.5%
조선시대 7
 
2.5%
시전행랑 7
 
2.5%
육의전과 6
 
2.1%
종로 6
 
2.1%
Other values (144) 189
66.3%
2023-12-10T18:48:47.858100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
185
 
16.3%
시 46
 
4.1%
장 36
 
3.2%
물 34
 
3.0%
서 29
 
2.6%
울 28
 
2.5%
풍 27
 
2.4%
동 21
 
1.9%
조 20
 
1.8%
- 20
 
1.8%
Other values (197) 688
60.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 913
80.5%
Space Separator 185
 
16.3%
Dash Punctuation 20
 
1.8%
Decimal Number 8
 
0.7%
Close Punctuation 3
 
0.3%
Open Punctuation 3
 
0.3%
Other Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 46
 
5.0%
장 36
 
3.9%
물 34
 
3.7%
서 29
 
3.2%
울 28
 
3.1%
풍 27
 
3.0%
동 21
 
2.3%
조 20
 
2.2%
사 19
 
2.1%
전 19
 
2.1%
Other values (189) 634
69.4%
Decimal Number
ValueCountFrequency (%)
8 6
75.0%
3 1
 
12.5%
2 1
 
12.5%
Space Separator
ValueCountFrequency (%)
185
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Other Punctuation
ValueCountFrequency (%)
' 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 913
80.5%
Common 221
 
19.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 46
 
5.0%
장 36
 
3.9%
물 34
 
3.7%
서 29
 
3.2%
울 28
 
3.1%
풍 27
 
3.0%
동 21
 
2.3%
조 20
 
2.2%
사 19
 
2.1%
전 19
 
2.1%
Other values (189) 634
69.4%
Common
ValueCountFrequency (%)
185
83.7%
- 20
 
9.0%
8 6
 
2.7%
) 3
 
1.4%
( 3
 
1.4%
' 2
 
0.9%
3 1
 
0.5%
2 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 913
80.5%
ASCII 221
 
19.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
185
83.7%
- 20
 
9.0%
8 6
 
2.7%
) 3
 
1.4%
( 3
 
1.4%
' 2
 
0.9%
3 1
 
0.5%
2 1
 
0.5%
Hangul
ValueCountFrequency (%)
시 46
 
5.0%
장 36
 
3.9%
물 34
 
3.7%
서 29
 
3.2%
울 28
 
3.1%
풍 27
 
3.0%
동 21
 
2.3%
조 20
 
2.2%
사 19
 
2.1%
전 19
 
2.1%
Other values (189) 634
69.4%

sumry_cn
Categorical

HIGH CORRELATION 

Distinct35
Distinct (%)35.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
서울 풍물시장
27 
<NA>
13 
육의전
11 
종로 피맛길
6 
구 조선중앙일보 사옥
6 
Other values (30)
37 

Length

Max length221
Median length153
Mean length12.92
Min length3

Unique

Unique27 ?
Unique (%)27.0%

Sample

1st row경상북도 무형문화재 제46호로 지정된 문경 모전들소리를 재현한 영상이다. 문경지역 향토성을 느낄 수 있는 들지신 밟기, 목도소리 등 총 10개로 구성된 소리를 가사와 함께 공연 영상으로 제작하였다.
2nd row<NA>
3rd row16세기 제봉 고경명이 쓴 기행문인 유서석록(遊瑞石錄)에서 화순적벽에 대한 내용을 기반으로 당시의 선비 풍류를 재현한 영상이다. 전남 화순군의 적벽은 국가지정문화재 명승지다. 1519년 기묘사화로 유배 중이던 신재 최산두가 이곳의 절경을 보고, 중국의 적벽에 비유하여 '적벽’이라 이름 지었다. 이후 김삿갓, 정약용 등 당대의 명사가 수없이 다녀갔다.
4th row해남 옥 산업의 역사를 다룬 다큐멘터리이다. 전남 '땅끝마을' 해남은 이순신 장군의 명량해전, 추사 김정희, 공재 윤두서, 다산 정약용 등 굵직한 인물·사건의 흔적이 즐비한 역사와 문화, 예술의 고장이다. 해남은 또한 옥(玉) 산지이자 옥 공예로도 유명한데, 해남 옥 산업의 역사와 관련 사건들을 과거 문헌과 전문가 인터뷰를 기반으로 살펴본다. 또한 옥 공예 명인의 인터뷰와 작품도 함께 담았다.
5th row관립교동소학교

Common Values

ValueCountFrequency (%)
서울 풍물시장 27
27.0%
<NA> 13
13.0%
육의전 11
11.0%
종로 피맛길 6
 
6.0%
구 조선중앙일보 사옥 6
 
6.0%
동묘시장 5
 
5.0%
관립교동소학교 3
 
3.0%
조광조 집터 표석 2
 
2.0%
문자 풀어 혼인 날 받기 1
 
1.0%
설 차례상 1
 
1.0%
Other values (25) 25
25.0%

Length

2023-12-10T18:48:48.112419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울 27
 
7.9%
풍물시장 27
 
7.9%
na 13
 
3.8%
육의전 11
 
3.2%
구 6
 
1.8%
조선중앙일보 6
 
1.8%
사옥 6
 
1.8%
피맛길 6
 
1.8%
종로 6
 
1.8%
동묘시장 5
 
1.5%
Other values (201) 229
67.0%

cl_nm
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
생활과 민속
99 
자연과 지리
 
1

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row생활과 민속
2nd row생활과 민속
3rd row생활과 민속
4th row자연과 지리
5th row생활과 민속

Common Values

ValueCountFrequency (%)
생활과 민속 99
99.0%
자연과 지리 1
 
1.0%

Length

2023-12-10T18:48:48.360899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:48:48.514862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
생활과 99
49.5%
민속 99
49.5%
자연과 1
 
0.5%
지리 1
 
0.5%

lwprt_cl_nm
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
민속
85 
생활
14 
마을경관
 
1

Length

Max length4
Median length2
Mean length2.02
Min length2

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row민속
2nd row생활
3rd row민속
4th row마을경관
5th row민속

Common Values

ValueCountFrequency (%)
민속 85
85.0%
생활 14
 
14.0%
마을경관 1
 
1.0%

Length

2023-12-10T18:48:48.723198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:48:48.931568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
민속 85
85.0%
생활 14
 
14.0%
마을경관 1
 
1.0%

ty_nm
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
시청각물
100 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
시청각물 100
100.0%

Length

2023-12-10T18:48:49.166848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:48:49.387919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
시청각물 100
100.0%

lwprt_data_ty_nm
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
사진
87 
기타
10 
동영상
 
3

Length

Max length3
Median length2
Mean length2.03
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row동영상
2nd row사진
3rd row동영상
4th row동영상
5th row사진

Common Values

ValueCountFrequency (%)
사진 87
87.0%
기타 10
 
10.0%
동영상 3
 
3.0%

Length

2023-12-10T18:48:49.561154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:48:49.740596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사진 87
87.0%
기타 10
 
10.0%
동영상 3
 
3.0%

ctprvn_nm
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
서울특별시
61 
<NA>
13 
강원도
 
6
전라북도
 
6
전라남도
 
3
Other values (5)
11 

Length

Max length5
Median length5
Mean length4.54
Min length3

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row경상북도
2nd row<NA>
3rd row전라남도
4th row전라남도
5th row서울특별시

Common Values

ValueCountFrequency (%)
서울특별시 61
61.0%
<NA> 13
 
13.0%
강원도 6
 
6.0%
전라북도 6
 
6.0%
전라남도 3
 
3.0%
충청북도 3
 
3.0%
경기도 3
 
3.0%
경상북도 2
 
2.0%
인천광역시 2
 
2.0%
경상남도 1
 
1.0%

Length

2023-12-10T18:48:49.956558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:48:50.244098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 61
61.0%
na 13
 
13.0%
강원도 6
 
6.0%
전라북도 6
 
6.0%
전라남도 3
 
3.0%
충청북도 3
 
3.0%
경기도 3
 
3.0%
경상북도 2
 
2.0%
인천광역시 2
 
2.0%
경상남도 1
 
1.0%

signgu_nm
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
종로구
33 
동대문구
27 
<NA>
19 
영월군
 
3
남구
 
2
Other values (15)
16 

Length

Max length4
Median length3
Mean length3.44
Min length2

Unique

Unique14 ?
Unique (%)14.0%

Sample

1st row문경시
2nd row<NA>
3rd row화순군
4th row해남군
5th row종로구

Common Values

ValueCountFrequency (%)
종로구 33
33.0%
동대문구 27
27.0%
<NA> 19
19.0%
영월군 3
 
3.0%
남구 2
 
2.0%
정읍시 2
 
2.0%
완주군 1
 
1.0%
화순군 1
 
1.0%
해남군 1
 
1.0%
강북구 1
 
1.0%
Other values (10) 10
 
10.0%

Length

2023-12-10T18:48:50.502462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
종로구 33
33.0%
동대문구 27
27.0%
na 19
19.0%
영월군 3
 
3.0%
남구 2
 
2.0%
정읍시 2
 
2.0%
문경시 1
 
1.0%
진주시 1
 
1.0%
여주군 1
 
1.0%
충주시 1
 
1.0%
Other values (10) 10
 
10.0%

regist_de
Real number (ℝ)

HIGH CORRELATION 

Distinct7
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20190219
Minimum20190103
Maximum20190610
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:48:50.717871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20190103
5-th percentile20190108
Q120190213
median20190213
Q320190213
95-th percentile20190228
Maximum20190610
Range507
Interquartile range (IQR)0

Descriptive statistics

Standard deviation87.954835
Coefficient of variation (CV)4.356309 × 10-6
Kurtosis12.279976
Mean20190219
Median Absolute Deviation (MAD)0
Skewness3.2169003
Sum2.0190219 × 109
Variance7736.0529
MonotonicityNot monotonic
2023-12-10T18:48:50.919271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
20190213 84
84.0%
20190108 7
 
7.0%
20190610 3
 
3.0%
20190110 2
 
2.0%
20190509 2
 
2.0%
20190103 1
 
1.0%
20190107 1
 
1.0%
ValueCountFrequency (%)
20190103 1
 
1.0%
20190107 1
 
1.0%
20190108 7
 
7.0%
20190110 2
 
2.0%
20190213 84
84.0%
20190509 2
 
2.0%
20190610 3
 
3.0%
ValueCountFrequency (%)
20190610 3
 
3.0%
20190509 2
 
2.0%
20190213 84
84.0%
20190110 2
 
2.0%
20190108 7
 
7.0%
20190107 1
 
1.0%
20190103 1
 
1.0%

main_thumb_url
Text

Distinct99
Distinct (%)100.0%
Missing1
Missing (%)1.0%
Memory size932.0 B
2023-12-10T18:48:51.423740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length106
Median length68
Mean length68.666667
Min length66

Characters and Unicode

Total characters6798
Distinct characters41
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique99 ?
Unique (%)100.0%

Sample

1st rowhttps://minio.nculture.org/amsweb-opt/videos/207/27259/27259_thumbnail.jpg
2nd rowhttps://www.nculture.org/nfs/kccf_assets/147/195/29239_thumbnail.jpg
3rd rowhttps://minio.nculture.org/amsweb-opt/videos/126/27271/27271_thumbnail.jpg
4th rowhttps://minio.nculture.org/amsweb-opt/videos/127/27273/27273_thumbnail.jpg
5th rowhttps://www.nculture.org/nfs/kccf_assets/43/100//27568_thumbnail.jpg
ValueCountFrequency (%)
https://minio.nculture.org/amsweb-opt/videos/207/27259/27259_thumbnail.jpg 1
 
1.0%
https://www.nculture.org/nfs/kccf_assets/117/132//27264_thumbnail.png 1
 
1.0%
https://www.nculture.org/nfs/kccf_assets/117/132//27266_thumbnail.png 1
 
1.0%
https://www.nculture.org/nfs/kccf_assets/117/132//27267_thumbnail.png 1
 
1.0%
https://www.nculture.org/nfs/kccf_assets/117/132//27268_thumbnail.png 1
 
1.0%
https://www.nculture.org/nfs/kccf_assets/117/132//27662_thumbnail.png 1
 
1.0%
https://www.nculture.org/nfs/kccf_assets/117/132//27660_thumbnail.png 1
 
1.0%
https://www.nculture.org/nfs/kccf_assets/117/132//27657_thumbnail.png 1
 
1.0%
https://www.nculture.org/nfs/kccf_assets/117/132//27656_thumbnail.png 1
 
1.0%
https://www.nculture.org/nfs/kccf_assets/117/132//27655_thumbnail.png 1
 
1.0%
Other values (89) 89
89.9%
2023-12-10T18:48:52.160068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 785
 
11.5%
t 495
 
7.3%
s 486
 
7.1%
n 329
 
4.8%
. 297
 
4.4%
u 297
 
4.4%
c 292
 
4.3%
w 289
 
4.3%
e 203
 
3.0%
p 202
 
3.0%
Other values (31) 3123
45.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4376
64.4%
Other Punctuation 1190
 
17.5%
Decimal Number 1023
 
15.0%
Connector Punctuation 193
 
2.8%
Uppercase Letter 10
 
0.1%
Dash Punctuation 6
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 495
 
11.3%
s 486
 
11.1%
n 329
 
7.5%
u 297
 
6.8%
c 292
 
6.7%
w 289
 
6.6%
e 203
 
4.6%
p 202
 
4.6%
r 200
 
4.6%
h 198
 
4.5%
Other values (12) 1385
31.6%
Decimal Number
ValueCountFrequency (%)
2 195
19.1%
1 186
18.2%
7 161
15.7%
6 103
10.1%
3 87
8.5%
4 77
 
7.5%
0 76
 
7.4%
5 70
 
6.8%
9 41
 
4.0%
8 27
 
2.6%
Other Punctuation
ValueCountFrequency (%)
/ 785
66.0%
. 297
 
25.0%
: 99
 
8.3%
% 9
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
C 5
50.0%
E 3
30.0%
A 2
 
20.0%
Connector Punctuation
ValueCountFrequency (%)
_ 193
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4386
64.5%
Common 2412
35.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 495
 
11.3%
s 486
 
11.1%
n 329
 
7.5%
u 297
 
6.8%
c 292
 
6.7%
w 289
 
6.6%
e 203
 
4.6%
p 202
 
4.6%
r 200
 
4.6%
h 198
 
4.5%
Other values (15) 1395
31.8%
Common
ValueCountFrequency (%)
/ 785
32.5%
. 297
 
12.3%
2 195
 
8.1%
_ 193
 
8.0%
1 186
 
7.7%
7 161
 
6.7%
6 103
 
4.3%
: 99
 
4.1%
3 87
 
3.6%
4 77
 
3.2%
Other values (6) 229
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6798
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 785
 
11.5%
t 495
 
7.3%
s 486
 
7.1%
n 329
 
4.8%
. 297
 
4.4%
u 297
 
4.4%
c 292
 
4.3%
w 289
 
4.3%
e 203
 
3.0%
p 202
 
3.0%
Other values (31) 3123
45.9%

cntnts_url
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:48:52.644083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length56
Mean length55.88
Min length52

Characters and Unicode

Total characters5588
Distinct characters36
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st rowhttps://www.nculture.org/cmm/nvodView.do?nvod=B27259
2nd rowhttps://www.nculture.org/cmm/nImageView.do?nimage=B29239
3rd rowhttps://www.nculture.org/cmm/nvodView.do?nvod=B27271
4th rowhttps://www.nculture.org/cmm/nvodView.do?nvod=B27273
5th rowhttps://www.nculture.org/cmm/nImageView.do?nimage=B27568
ValueCountFrequency (%)
https://www.nculture.org/cmm/nvodview.do?nvod=b27259 1
 
1.0%
https://www.nculture.org/cmm/nimageview.do?nimage=b27644 1
 
1.0%
https://www.nculture.org/cmm/nimageview.do?nimage=b27266 1
 
1.0%
https://www.nculture.org/cmm/nimageview.do?nimage=b27267 1
 
1.0%
https://www.nculture.org/cmm/nimageview.do?nimage=b27268 1
 
1.0%
https://www.nculture.org/cmm/nimageview.do?nimage=b27662 1
 
1.0%
https://www.nculture.org/cmm/nimageview.do?nimage=b27660 1
 
1.0%
https://www.nculture.org/cmm/nimageview.do?nimage=b27657 1
 
1.0%
https://www.nculture.org/cmm/nimageview.do?nimage=b27656 1
 
1.0%
https://www.nculture.org/cmm/nimageview.do?nimage=b27655 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T18:48:53.665344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 400
 
7.2%
w 400
 
7.2%
m 394
 
7.1%
e 394
 
7.1%
. 300
 
5.4%
n 300
 
5.4%
t 300
 
5.4%
g 294
 
5.3%
o 206
 
3.7%
u 200
 
3.6%
Other values (26) 2400
42.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3791
67.8%
Other Punctuation 900
 
16.1%
Decimal Number 500
 
8.9%
Uppercase Letter 297
 
5.3%
Math Symbol 100
 
1.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 400
10.6%
m 394
10.4%
e 394
10.4%
n 300
 
7.9%
t 300
 
7.9%
g 294
 
7.8%
o 206
 
5.4%
u 200
 
5.3%
c 200
 
5.3%
r 200
 
5.3%
Other values (8) 903
23.8%
Decimal Number
ValueCountFrequency (%)
2 136
27.2%
7 117
23.4%
6 76
15.2%
5 45
 
9.0%
9 24
 
4.8%
1 22
 
4.4%
3 22
 
4.4%
0 21
 
4.2%
8 19
 
3.8%
4 18
 
3.6%
Other Punctuation
ValueCountFrequency (%)
/ 400
44.4%
. 300
33.3%
? 100
 
11.1%
: 100
 
11.1%
Uppercase Letter
ValueCountFrequency (%)
B 100
33.7%
V 100
33.7%
I 97
32.7%
Math Symbol
ValueCountFrequency (%)
= 100
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4088
73.2%
Common 1500
 
26.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 400
 
9.8%
m 394
 
9.6%
e 394
 
9.6%
n 300
 
7.3%
t 300
 
7.3%
g 294
 
7.2%
o 206
 
5.0%
u 200
 
4.9%
c 200
 
4.9%
r 200
 
4.9%
Other values (11) 1200
29.4%
Common
ValueCountFrequency (%)
/ 400
26.7%
. 300
20.0%
2 136
 
9.1%
7 117
 
7.8%
= 100
 
6.7%
? 100
 
6.7%
: 100
 
6.7%
6 76
 
5.1%
5 45
 
3.0%
9 24
 
1.6%
Other values (5) 102
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 400
 
7.2%
w 400
 
7.2%
m 394
 
7.1%
e 394
 
7.1%
. 300
 
5.4%
n 300
 
5.4%
t 300
 
5.4%
g 294
 
5.3%
o 206
 
3.7%
u 200
 
3.6%
Other values (26) 2400
42.9%

Interactions

2023-12-10T18:48:44.980863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:48:44.656011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:48:45.151060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:48:44.810609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T18:48:53.867329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
data_manage_nodata_title_nmsumry_cncl_nmlwprt_cl_nmlwprt_data_ty_nmctprvn_nmsigngu_nmregist_demain_thumb_urlcntnts_url
data_manage_no1.0001.0000.920NaN0.1700.8140.3890.7520.6741.0001.000
data_title_nm1.0001.0001.0001.0001.0001.0001.0001.0000.9971.0001.000
sumry_cn0.9201.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
cl_nmNaN1.0001.0001.0001.0000.3500.5061.0000.3731.0001.000
lwprt_cl_nm0.1701.0001.0001.0001.0000.7400.6090.8600.3571.0001.000
lwprt_data_ty_nm0.8141.0001.0000.3500.7401.0000.8900.9730.3201.0001.000
ctprvn_nm0.3891.0001.0000.5060.6090.8901.0001.0000.7831.0001.000
signgu_nm0.7521.0001.0001.0000.8600.9731.0001.0001.0001.0001.000
regist_de0.6740.9971.0000.3730.3570.3200.7831.0001.0001.0001.000
main_thumb_url1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
cntnts_url1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
2023-12-10T18:48:54.107265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
signgu_nmlwprt_cl_nmsumry_cnlwprt_data_ty_nmctprvn_nmcl_nm
signgu_nm1.0000.6310.9250.8370.9280.886
lwprt_cl_nm0.6311.0000.7940.3960.3190.995
sumry_cn0.9250.7941.0000.7940.8580.790
lwprt_data_ty_nm0.8370.3960.7941.0000.5980.556
ctprvn_nm0.9280.3190.8580.5981.0000.485
cl_nm0.8860.9950.7900.5560.4851.000
2023-12-10T18:48:54.275982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
data_manage_noregist_desumry_cncl_nmlwprt_cl_nmlwprt_data_ty_nmctprvn_nmsigngu_nm
data_manage_no1.0000.0290.6930.4160.3550.5320.5020.616
regist_de0.0291.0000.7900.2280.3380.3550.7910.886
sumry_cn0.6930.7901.0000.7900.7940.7940.8580.925
cl_nm0.4160.2280.7901.0000.9950.5560.4850.886
lwprt_cl_nm0.3550.3380.7940.9951.0000.3960.3190.631
lwprt_data_ty_nm0.5320.3550.7940.5560.3961.0000.5980.837
ctprvn_nm0.5020.7910.8580.4850.3190.5981.0000.928
signgu_nm0.6160.8860.9250.8860.6310.8370.9281.000

Missing values

2023-12-10T18:48:45.360849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T18:48:45.759194image/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

data_manage_nodata_title_nmsumry_cncl_nmlwprt_cl_nmty_nmlwprt_data_ty_nmctprvn_nmsigngu_nmregist_demain_thumb_urlcntnts_url
012442모전들소리 보존 사업 '모심기 소리'경상북도 무형문화재 제46호로 지정된 문경 모전들소리를 재현한 영상이다. 문경지역 향토성을 느낄 수 있는 들지신 밟기, 목도소리 등 총 10개로 구성된 소리를 가사와 함께 공연 영상으로 제작하였다.생활과 민속민속시청각물동영상경상북도문경시20190103https://minio.nculture.org/amsweb-opt/videos/207/27259/27259_thumbnail.jpghttps://www.nculture.org/cmm/nvodView.do?nvod=B27259
129469늙은 호박전<NA>생활과 민속생활시청각물사진<NA><NA>20190610https://www.nculture.org/nfs/kccf_assets/147/195/29239_thumbnail.jpghttps://www.nculture.org/cmm/nImageView.do?nimage=B29239
210967목사행렬 재현 영상 콘텐츠16세기 제봉 고경명이 쓴 기행문인 유서석록(遊瑞石錄)에서 화순적벽에 대한 내용을 기반으로 당시의 선비 풍류를 재현한 영상이다. 전남 화순군의 적벽은 국가지정문화재 명승지다. 1519년 기묘사화로 유배 중이던 신재 최산두가 이곳의 절경을 보고, 중국의 적벽에 비유하여 '적벽’이라 이름 지었다. 이후 김삿갓, 정약용 등 당대의 명사가 수없이 다녀갔다.생활과 민속민속시청각물동영상전라남도화순군20190110https://minio.nculture.org/amsweb-opt/videos/126/27271/27271_thumbnail.jpghttps://www.nculture.org/cmm/nvodView.do?nvod=B27271
310963해남 향토문화 제2막 3장 영상콘텐츠해남 옥 산업의 역사를 다룬 다큐멘터리이다. 전남 '땅끝마을' 해남은 이순신 장군의 명량해전, 추사 김정희, 공재 윤두서, 다산 정약용 등 굵직한 인물·사건의 흔적이 즐비한 역사와 문화, 예술의 고장이다. 해남은 또한 옥(玉) 산지이자 옥 공예로도 유명한데, 해남 옥 산업의 역사와 관련 사건들을 과거 문헌과 전문가 인터뷰를 기반으로 살펴본다. 또한 옥 공예 명인의 인터뷰와 작품도 함께 담았다.자연과 지리마을경관시청각물동영상전라남도해남군20190110https://minio.nculture.org/amsweb-opt/videos/127/27273/27273_thumbnail.jpghttps://www.nculture.org/cmm/nvodView.do?nvod=B27273
412812관립교동소학교 표석관립교동소학교생활과 민속민속시청각물사진서울특별시종로구20190213https://www.nculture.org/nfs/kccf_assets/43/100//27568_thumbnail.jpghttps://www.nculture.org/cmm/nImageView.do?nimage=B27568
512813관립교동소학교 표석관립교동소학교생활과 민속민속시청각물사진서울특별시종로구20190213https://www.nculture.org/nfs/kccf_assets/43/100//27569_thumbnail.jpghttps://www.nculture.org/cmm/nImageView.do?nimage=B27569
612814관립교동소학교관립교동소학교생활과 민속민속시청각물사진서울특별시종로구20190213https://www.nculture.org/nfs/kccf_assets/43/100//27570_thumbnail.jpghttps://www.nculture.org/cmm/nImageView.do?nimage=B27570
729470대구 육개장<NA>생활과 민속생활시청각물사진<NA><NA>20190610https://www.nculture.org/nfs/kccf_assets/147/195/29240_thumbnail.jpghttps://www.nculture.org/cmm/nImageView.do?nimage=B29240
812816구 조선중앙일보 서울미래유산구 조선중앙일보 사옥생활과 민속민속시청각물사진서울특별시종로구20190213https://www.nculture.org/nfs/kccf_assets/44/101//27572_thumbnail.jpghttps://www.nculture.org/cmm/nImageView.do?nimage=B27572
912817구 조선중앙일보 표석구 조선중앙일보 사옥생활과 민속민속시청각물사진서울특별시종로구20190213https://www.nculture.org/nfs/kccf_assets/44/101//27573_thumbnail.jpghttps://www.nculture.org/cmm/nImageView.do?nimage=B27573
data_manage_nodata_title_nmsumry_cncl_nmlwprt_cl_nmty_nmlwprt_data_ty_nmctprvn_nmsigngu_nmregist_demain_thumb_urlcntnts_url
9012872조선시대 육의전과 시전행랑 터육의전생활과 민속생활시청각물사진서울특별시종로구20190213https://www.nculture.org/nfs/kccf_assets/9/25//27628_thumbnail.jpghttps://www.nculture.org/cmm/nImageView.do?nimage=B27628
9113108조선시대 육의전과 시전행랑 터육의전생활과 민속생활시청각물사진서울특별시종로구20190213https://www.nculture.org/nfs/kccf_assets/9/25//27630_thumbnail.jpghttps://www.nculture.org/cmm/nImageView.do?nimage=B27630
9212875조광조 집터 표석조광조 집터 표석생활과 민속민속시청각물사진서울특별시종로구20190213https://www.nculture.org/nfs/kccf_assets/47/104//27632_thumbnail.jpghttps://www.nculture.org/cmm/nImageView.do?nimage=B27632
9312877조광조 집터 표석조광조 집터 표석생활과 민속민속시청각물사진서울특별시종로구20190213https://www.nculture.org/nfs/kccf_assets/47/104//27634_thumbnail.jpghttps://www.nculture.org/cmm/nImageView.do?nimage=B27634
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