Overview

Dataset statistics

Number of variables12
Number of observations5287
Missing cells5286
Missing cells (%)8.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory516.4 KiB
Average record size in memory100.0 B

Variable types

Text5
Numeric4
Categorical3

Dataset

Description국립극장이 보유하고 있는 공연에 사용하는 의상, 소품, 장신구, 배경막 등의 모든 소품을 등록하고 관리하여 자체 공연에 활용 할고 외부에 대여도 할 수 있음.
Author문화체육관광부 국립중앙극장
URLhttps://www.data.go.kr/data/3062566/fileData.do

Alerts

보관처 has constant value ""Constant
보관처상세 has constant value ""Constant
총수량 is highly overall correlated with 보유수량High correlation
보유수량 is highly overall correlated with 총수량High correlation
단가 is highly overall correlated with 대여비 and 1 other fieldsHigh correlation
대여비 is highly overall correlated with 단가 and 1 other fieldsHigh correlation
단위 is highly overall correlated with 부서High correlation
부서 is highly overall correlated with 단가 and 2 other fieldsHigh correlation
단위 is highly imbalanced (64.9%)Imbalance
보관처상세 has 5286 (> 99.9%) missing valuesMissing
총수량 is highly skewed (γ1 = 26.37538754)Skewed
보유수량 is highly skewed (γ1 = 26.385266)Skewed
번호 has unique valuesUnique
물품번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 12:04:34.452521
Analysis finished2023-12-12 12:04:37.510230
Duration3.06 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Text

UNIQUE 

Distinct5287
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size41.4 KiB
2023-12-12T21:04:37.920123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.6016645
Min length1

Characters and Unicode

Total characters24329
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

Unique5287 ?
Unique (%)100.0%

Sample

1st row1
2nd row2
3rd row3
4th row4
5th row5
ValueCountFrequency (%)
1 1
 
< 0.1%
3,530 1
 
< 0.1%
3,528 1
 
< 0.1%
3,527 1
 
< 0.1%
3,526 1
 
< 0.1%
3,525 1
 
< 0.1%
3,524 1
 
< 0.1%
3,523 1
 
< 0.1%
3,522 1
 
< 0.1%
3,521 1
 
< 0.1%
Other values (5277) 5277
99.8%
2023-12-12T21:04:38.595169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 4288
17.6%
1 2659
10.9%
2 2647
10.9%
3 2559
10.5%
4 2559
10.5%
5 1847
7.6%
6 1559
 
6.4%
7 1559
 
6.4%
8 1556
 
6.4%
9 1548
 
6.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20041
82.4%
Other Punctuation 4288
 
17.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2659
13.3%
2 2647
13.2%
3 2559
12.8%
4 2559
12.8%
5 1847
9.2%
6 1559
7.8%
7 1559
7.8%
8 1556
7.8%
9 1548
7.7%
0 1548
7.7%
Other Punctuation
ValueCountFrequency (%)
, 4288
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24329
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
, 4288
17.6%
1 2659
10.9%
2 2647
10.9%
3 2559
10.5%
4 2559
10.5%
5 1847
7.6%
6 1559
 
6.4%
7 1559
 
6.4%
8 1556
 
6.4%
9 1548
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24329
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 4288
17.6%
1 2659
10.9%
2 2647
10.9%
3 2559
10.5%
4 2559
10.5%
5 1847
7.6%
6 1559
 
6.4%
7 1559
 
6.4%
8 1556
 
6.4%
9 1548
 
6.4%

물품명
Text

Distinct4535
Distinct (%)85.8%
Missing0
Missing (%)0.0%
Memory size41.4 KiB
2023-12-12T21:04:39.071599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length15
Mean length4.7480613
Min length1

Characters and Unicode

Total characters25103
Distinct characters776
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4060 ?
Unique (%)76.8%

Sample

1st row2014-테트스여의상
2nd row품2015
3rd row조용진
4th row조용진
5th row황태인
ValueCountFrequency (%)
기 33
 
0.5%
모자 23
 
0.4%
구두 22
 
0.4%
운동화 20
 
0.3%
大 18
 
0.3%
칼 16
 
0.3%
小 16
 
0.3%
춘향 16
 
0.3%
어린이 16
 
0.3%
왕 16
 
0.3%
Other values (4476) 6062
96.9%
2023-12-12T21:04:39.734483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
979
 
3.9%
) 854
 
3.4%
( 854
 
3.4%
자 543
 
2.2%
1 542
 
2.2%
이 433
 
1.7%
기 429
 
1.7%
2 404
 
1.6%
무 371
 
1.5%
사 341
 
1.4%
Other values (766) 19353
77.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 20068
79.9%
Decimal Number 1724
 
6.9%
Space Separator 979
 
3.9%
Close Punctuation 854
 
3.4%
Open Punctuation 854
 
3.4%
Dash Punctuation 314
 
1.3%
Other Punctuation 152
 
0.6%
Uppercase Letter 112
 
0.4%
Lowercase Letter 32
 
0.1%
Math Symbol 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
자 543
 
2.7%
이 433
 
2.2%
기 429
 
2.1%
무 371
 
1.8%
사 341
 
1.7%
여 324
 
1.6%
리 293
 
1.5%
스 274
 
1.4%
장 269
 
1.3%
지 258
 
1.3%
Other values (721) 16533
82.4%
Uppercase Letter
ValueCountFrequency (%)
A 33
29.5%
B 30
26.8%
C 15
13.4%
E 12
 
10.7%
L 5
 
4.5%
D 4
 
3.6%
P 4
 
3.6%
T 3
 
2.7%
V 2
 
1.8%
Y 2
 
1.8%
Decimal Number
ValueCountFrequency (%)
1 542
31.4%
2 404
23.4%
3 198
 
11.5%
4 135
 
7.8%
5 108
 
6.3%
6 83
 
4.8%
7 73
 
4.2%
0 66
 
3.8%
8 61
 
3.5%
9 54
 
3.1%
Lowercase Letter
ValueCountFrequency (%)
a 9
28.1%
b 8
25.0%
e 4
12.5%
t 3
 
9.4%
s 3
 
9.4%
k 2
 
6.2%
g 1
 
3.1%
v 1
 
3.1%
m 1
 
3.1%
Other Punctuation
ValueCountFrequency (%)
. 81
53.3%
, 59
38.8%
/ 8
 
5.3%
& 2
 
1.3%
* 2
 
1.3%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
20.0%
Ⅰ 1
20.0%
Ⅴ 1
20.0%
Ⅳ 1
20.0%
Ⅲ 1
20.0%
Space Separator
ValueCountFrequency (%)
979
100.0%
Close Punctuation
ValueCountFrequency (%)
) 854
100.0%
Open Punctuation
ValueCountFrequency (%)
( 854
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 314
100.0%
Math Symbol
ValueCountFrequency (%)
+ 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19873
79.2%
Common 4886
 
19.5%
Han 195
 
0.8%
Latin 149
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
자 543
 
2.7%
이 433
 
2.2%
기 429
 
2.2%
무 371
 
1.9%
사 341
 
1.7%
여 324
 
1.6%
리 293
 
1.5%
스 274
 
1.4%
장 269
 
1.4%
지 258
 
1.3%
Other values (717) 16338
82.2%
Latin
ValueCountFrequency (%)
A 33
22.1%
B 30
20.1%
C 15
10.1%
E 12
 
8.1%
a 9
 
6.0%
b 8
 
5.4%
L 5
 
3.4%
D 4
 
2.7%
P 4
 
2.7%
e 4
 
2.7%
Other values (15) 25
16.8%
Common
ValueCountFrequency (%)
979
20.0%
) 854
17.5%
( 854
17.5%
1 542
11.1%
2 404
8.3%
- 314
 
6.4%
3 198
 
4.1%
4 135
 
2.8%
5 108
 
2.2%
6 83
 
1.7%
Other values (10) 415
8.5%
Han
ValueCountFrequency (%)
大 73
37.4%
小 67
34.4%
中 54
27.7%
特 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19873
79.2%
ASCII 5030
 
20.0%
CJK 195
 
0.8%
Number Forms 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
979
19.5%
) 854
17.0%
( 854
17.0%
1 542
10.8%
2 404
8.0%
- 314
 
6.2%
3 198
 
3.9%
4 135
 
2.7%
5 108
 
2.1%
6 83
 
1.7%
Other values (30) 559
11.1%
Hangul
ValueCountFrequency (%)
자 543
 
2.7%
이 433
 
2.2%
기 429
 
2.2%
무 371
 
1.9%
사 341
 
1.7%
여 324
 
1.6%
리 293
 
1.5%
스 274
 
1.4%
장 269
 
1.4%
지 258
 
1.3%
Other values (717) 16338
82.2%
CJK
ValueCountFrequency (%)
大 73
37.4%
小 67
34.4%
中 54
27.7%
特 1
 
0.5%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
20.0%
Ⅰ 1
20.0%
Ⅴ 1
20.0%
Ⅳ 1
20.0%
Ⅲ 1
20.0%

공연명
Text

Distinct261
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size41.4 KiB
2023-12-12T21:04:40.057791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length16
Mean length7.5207112
Min length2

Characters and Unicode

Total characters39762
Distinct characters289
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)0.5%

Sample

1st row2014-테스트
2nd row2015 품
3rd row2016 기본활용법
4th row2016 기본활용법
5th row2016 기본활용법
ValueCountFrequency (%)
기타공연 992
 
15.8%
코카서스의백묵원2015 111
 
1.8%
다른춘향2014 96
 
1.5%
화선 88
 
1.4%
프린세스 87
 
1.4%
콩쥐2011 87
 
1.4%
성춘향2002 82
 
1.3%
장화홍련2012 79
 
1.3%
밀레니엄로드2008 77
 
1.2%
도미부인2012 77
 
1.2%
Other values (312) 4511
71.8%
2023-12-12T21:04:40.791701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5139
 
12.9%
2 3760
 
9.5%
1 2489
 
6.3%
9 1324
 
3.3%
연 1145
 
2.9%
기 1092
 
2.7%
공 1070
 
2.7%
타 1065
 
2.7%
1000
 
2.5%
향 808
 
2.0%
Other values (279) 20870
52.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 23906
60.1%
Decimal Number 14740
37.1%
Space Separator 1000
 
2.5%
Other Punctuation 101
 
0.3%
Uppercase Letter 9
 
< 0.1%
Dash Punctuation 4
 
< 0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
연 1145
 
4.8%
기 1092
 
4.6%
공 1070
 
4.5%
타 1065
 
4.5%
향 808
 
3.4%
춘 732
 
3.1%
가 476
 
2.0%
의 464
 
1.9%
전 427
 
1.8%
다 399
 
1.7%
Other values (259) 16228
67.9%
Decimal Number
ValueCountFrequency (%)
0 5139
34.9%
2 3760
25.5%
1 2489
16.9%
9 1324
 
9.0%
4 485
 
3.3%
3 389
 
2.6%
6 348
 
2.4%
5 326
 
2.2%
7 244
 
1.7%
8 236
 
1.6%
Other Punctuation
ValueCountFrequency (%)
, 59
58.4%
' 26
25.7%
" 16
 
15.8%
Uppercase Letter
ValueCountFrequency (%)
B 3
33.3%
S 3
33.3%
K 3
33.3%
Space Separator
ValueCountFrequency (%)
1000
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 23904
60.1%
Common 15847
39.9%
Latin 9
 
< 0.1%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
연 1145
 
4.8%
기 1092
 
4.6%
공 1070
 
4.5%
타 1065
 
4.5%
향 808
 
3.4%
춘 732
 
3.1%
가 476
 
2.0%
의 464
 
1.9%
전 427
 
1.8%
다 399
 
1.7%
Other values (257) 16226
67.9%
Common
ValueCountFrequency (%)
0 5139
32.4%
2 3760
23.7%
1 2489
15.7%
9 1324
 
8.4%
1000
 
6.3%
4 485
 
3.1%
3 389
 
2.5%
6 348
 
2.2%
5 326
 
2.1%
7 244
 
1.5%
Other values (7) 343
 
2.2%
Latin
ValueCountFrequency (%)
B 3
33.3%
S 3
33.3%
K 3
33.3%
Han
ValueCountFrequency (%)
梅 1
50.0%
窓 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 23904
60.1%
ASCII 15856
39.9%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5139
32.4%
2 3760
23.7%
1 2489
15.7%
9 1324
 
8.4%
1000
 
6.3%
4 485
 
3.1%
3 389
 
2.5%
6 348
 
2.2%
5 326
 
2.1%
7 244
 
1.5%
Other values (10) 352
 
2.2%
Hangul
ValueCountFrequency (%)
연 1145
 
4.8%
기 1092
 
4.6%
공 1070
 
4.5%
타 1065
 
4.5%
향 808
 
3.4%
춘 732
 
3.1%
가 476
 
2.0%
의 464
 
1.9%
전 427
 
1.8%
다 399
 
1.7%
Other values (257) 16226
67.9%
CJK
ValueCountFrequency (%)
梅 1
50.0%
窓 1
50.0%

물품번호
Text

UNIQUE 

Distinct5287
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size41.4 KiB
2023-12-12T21:04:41.078442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length15
Mean length15
Min length15

Characters and Unicode

Total characters79305
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5287 ?
Unique (%)100.0%

Sample

1st rowC20140962108010
2nd rowC20160331033014
3rd rowC20160331025001
4th rowC20160331026001
5th rowC20160331027001
ValueCountFrequency (%)
c20140962108010 1
 
< 0.1%
p20141014078001 1
 
< 0.1%
p20160814114007 1
 
< 0.1%
p20141014065002 1
 
< 0.1%
p20141014173003 1
 
< 0.1%
p20141014063005 1
 
< 0.1%
p20140914147001 1
 
< 0.1%
p20141014156046 1
 
< 0.1%
p20141014138006 1
 
< 0.1%
p20140914181001 1
 
< 0.1%
Other values (5277) 5277
99.8%
2023-12-12T21:04:41.450777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 24833
31.3%
1 13754
17.3%
2 11261
14.2%
4 7823
 
9.9%
8 4332
 
5.5%
3 4035
 
5.1%
C 2544
 
3.2%
6 2280
 
2.9%
9 2222
 
2.8%
P 1975
 
2.5%
Other values (4) 4246
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 74018
93.3%
Uppercase Letter 5287
 
6.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 24833
33.5%
1 13754
18.6%
2 11261
15.2%
4 7823
 
10.6%
8 4332
 
5.9%
3 4035
 
5.5%
6 2280
 
3.1%
9 2222
 
3.0%
5 1970
 
2.7%
7 1508
 
2.0%
Uppercase Letter
ValueCountFrequency (%)
C 2544
48.1%
P 1975
37.4%
A 592
 
11.2%
D 176
 
3.3%

Most occurring scripts

ValueCountFrequency (%)
Common 74018
93.3%
Latin 5287
 
6.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 24833
33.5%
1 13754
18.6%
2 11261
15.2%
4 7823
 
10.6%
8 4332
 
5.9%
3 4035
 
5.5%
6 2280
 
3.1%
9 2222
 
3.0%
5 1970
 
2.7%
7 1508
 
2.0%
Latin
ValueCountFrequency (%)
C 2544
48.1%
P 1975
37.4%
A 592
 
11.2%
D 176
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 79305
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 24833
31.3%
1 13754
17.3%
2 11261
14.2%
4 7823
 
9.9%
8 4332
 
5.5%
3 4035
 
5.1%
C 2544
 
3.2%
6 2280
 
2.9%
9 2222
 
2.8%
P 1975
 
2.5%
Other values (4) 4246
 
5.4%

총수량
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct53
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.0582561
Minimum1
Maximum500
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.6 KiB
2023-12-12T21:04:41.653544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q34
95-th percentile16
Maximum500
Range499
Interquartile range (IQR)3

Descriptive statistics

Standard deviation9.9299481
Coefficient of variation (CV)2.446851
Kurtosis1210.7908
Mean4.0582561
Median Absolute Deviation (MAD)0
Skewness26.375388
Sum21456
Variance98.60387
MonotonicityNot monotonic
2023-12-12T21:04:41.824742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 2992
56.6%
2 730
 
13.8%
3 226
 
4.3%
4 183
 
3.5%
5 173
 
3.3%
6 110
 
2.1%
8 108
 
2.0%
7 97
 
1.8%
10 91
 
1.7%
9 72
 
1.4%
Other values (43) 505
 
9.6%
ValueCountFrequency (%)
1 2992
56.6%
2 730
 
13.8%
3 226
 
4.3%
4 183
 
3.5%
5 173
 
3.3%
6 110
 
2.1%
7 97
 
1.8%
8 108
 
2.0%
9 72
 
1.4%
10 91
 
1.7%
ValueCountFrequency (%)
500 1
 
< 0.1%
200 1
 
< 0.1%
100 1
 
< 0.1%
78 2
 
< 0.1%
60 5
0.1%
54 3
0.1%
53 1
 
< 0.1%
50 6
0.1%
49 2
 
< 0.1%
48 2
 
< 0.1%

보유수량
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct53
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.0557972
Minimum1
Maximum500
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.6 KiB
2023-12-12T21:04:42.027625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q34
95-th percentile16
Maximum500
Range499
Interquartile range (IQR)3

Descriptive statistics

Standard deviation9.9287715
Coefficient of variation (CV)2.4480443
Kurtosis1211.3922
Mean4.0557972
Median Absolute Deviation (MAD)0
Skewness26.385266
Sum21443
Variance98.580503
MonotonicityNot monotonic
2023-12-12T21:04:42.180545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 2992
56.6%
2 730
 
13.8%
3 227
 
4.3%
4 183
 
3.5%
5 172
 
3.3%
6 111
 
2.1%
8 109
 
2.1%
7 98
 
1.9%
10 89
 
1.7%
9 71
 
1.3%
Other values (43) 505
 
9.6%
ValueCountFrequency (%)
1 2992
56.6%
2 730
 
13.8%
3 227
 
4.3%
4 183
 
3.5%
5 172
 
3.3%
6 111
 
2.1%
7 98
 
1.9%
8 109
 
2.1%
9 71
 
1.3%
10 89
 
1.7%
ValueCountFrequency (%)
500 1
 
< 0.1%
200 1
 
< 0.1%
100 1
 
< 0.1%
78 2
 
< 0.1%
60 5
0.1%
54 3
0.1%
53 1
 
< 0.1%
50 6
0.1%
49 2
 
< 0.1%
48 2
 
< 0.1%

단위
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct15
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size41.4 KiB
개
2544 
벌
2464 
켤레
 
101
습
 
75
점
 
41
Other values (10)
 
62

Length

Max length2
Median length1
Mean length1.0281823
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row벌
2nd row습
3rd row점
4th row점
5th row점

Common Values

ValueCountFrequency (%)
개 2544
48.1%
벌 2464
46.6%
켤레 101
 
1.9%
습 75
 
1.4%
점 41
 
0.8%
자루 37
 
0.7%
셋트 7
 
0.1%
권 4
 
0.1%
장 3
 
0.1%
채 3
 
0.1%
Other values (5) 8
 
0.2%

Length

2023-12-12T21:04:42.316454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
개 2544
48.1%
벌 2464
46.6%
켤레 101
 
1.9%
습 75
 
1.4%
점 41
 
0.8%
자루 37
 
0.7%
셋트 7
 
0.1%
권 4
 
0.1%
장 3
 
0.1%
채 3
 
0.1%
Other values (5) 8
 
0.2%

단가
Real number (ℝ)

HIGH CORRELATION 

Distinct746
Distinct (%)14.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean346131.19
Minimum1
Maximum11111111
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.6 KiB
2023-12-12T21:04:42.457922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile11111
Q170000
median200000
Q3347000
95-th percentile981000
Maximum11111111
Range11111110
Interquartile range (IQR)277000

Descriptive statistics

Standard deviation698033.81
Coefficient of variation (CV)2.0166741
Kurtosis52.685565
Mean346131.19
Median Absolute Deviation (MAD)132000
Skewness6.1896338
Sum1.8299956 × 109
Variance4.872512 × 1011
MonotonicityNot monotonic
2023-12-12T21:04:42.619060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50000 319
 
6.0%
100000 305
 
5.8%
200000 251
 
4.7%
300000 246
 
4.7%
30000 243
 
4.6%
150000 227
 
4.3%
250000 161
 
3.0%
80000 136
 
2.6%
70000 115
 
2.2%
20000 115
 
2.2%
Other values (736) 3169
59.9%
ValueCountFrequency (%)
1 3
 
0.1%
10 31
0.6%
11 3
 
0.1%
20 2
 
< 0.1%
28 1
 
< 0.1%
33 1
 
< 0.1%
83 1
 
< 0.1%
100 2
 
< 0.1%
111 1
 
< 0.1%
125 2
 
< 0.1%
ValueCountFrequency (%)
11111111 2
 
< 0.1%
7541323 1
 
< 0.1%
7400000 9
 
0.2%
6600000 1
 
< 0.1%
6350000 1
 
< 0.1%
6052800 1
 
< 0.1%
4200000 1
 
< 0.1%
3800000 1
 
< 0.1%
3600000 113
2.1%
3400000 1
 
< 0.1%

대여비
Real number (ℝ)

HIGH CORRELATION 

Distinct738
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17306.576
Minimum1
Maximum555556
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.6 KiB
2023-12-12T21:04:42.778521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile556
Q13500
median10000
Q317350
95-th percentile49050
Maximum555556
Range555555
Interquartile range (IQR)13850

Descriptive statistics

Standard deviation34901.691
Coefficient of variation (CV)2.0166722
Kurtosis52.685617
Mean17306.576
Median Absolute Deviation (MAD)6600
Skewness6.1896355
Sum91499869
Variance1.2181281 × 109
MonotonicityNot monotonic
2023-12-12T21:04:42.940274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2500 319
 
6.0%
5000 305
 
5.8%
10000 251
 
4.7%
15000 246
 
4.7%
1500 243
 
4.6%
7500 227
 
4.3%
12500 161
 
3.0%
4000 136
 
2.6%
3500 115
 
2.2%
1000 115
 
2.2%
Other values (728) 3169
59.9%
ValueCountFrequency (%)
1 40
0.8%
2 1
 
< 0.1%
4 1
 
< 0.1%
5 2
 
< 0.1%
6 3
 
0.1%
7 2
 
< 0.1%
8 7
 
0.1%
10 1
 
< 0.1%
13 3
 
0.1%
17 6
 
0.1%
ValueCountFrequency (%)
555556 2
 
< 0.1%
377066 1
 
< 0.1%
370000 9
 
0.2%
330000 1
 
< 0.1%
317500 1
 
< 0.1%
302640 1
 
< 0.1%
210000 1
 
< 0.1%
190000 1
 
< 0.1%
180000 113
2.1%
170000 1
 
< 0.1%

보관처
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size41.4 KiB
제2보관창고(파주시)
5287 

Length

Max length11
Median length11
Mean length11
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row제2보관창고(파주시)
2nd row제2보관창고(파주시)
3rd row제2보관창고(파주시)
4th row제2보관창고(파주시)
5th row제2보관창고(파주시)

Common Values

ValueCountFrequency (%)
제2보관창고(파주시) 5287
100.0%

Length

2023-12-12T21:04:43.078789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:04:43.178317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제2보관창고(파주시 5287
100.0%

보관처상세
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing5286
Missing (%)> 99.9%
Memory size41.4 KiB
2023-12-12T21:04:43.315200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters10
Distinct characters9
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row행거 밑에 박스보관
ValueCountFrequency (%)
행거 1
33.3%
밑에 1
33.3%
박스보관 1
33.3%
2023-12-12T21:04:43.680894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2
20.0%
행 1
10.0%
거 1
10.0%
밑 1
10.0%
에 1
10.0%
박 1
10.0%
스 1
10.0%
보 1
10.0%
관 1
10.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8
80.0%
Space Separator 2
 
20.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
행 1
12.5%
거 1
12.5%
밑 1
12.5%
에 1
12.5%
박 1
12.5%
스 1
12.5%
보 1
12.5%
관 1
12.5%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8
80.0%
Common 2
 
20.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
행 1
12.5%
거 1
12.5%
밑 1
12.5%
에 1
12.5%
박 1
12.5%
스 1
12.5%
보 1
12.5%
관 1
12.5%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8
80.0%
ASCII 2
 
20.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2
100.0%
Hangul
ValueCountFrequency (%)
행 1
12.5%
거 1
12.5%
밑 1
12.5%
에 1
12.5%
박 1
12.5%
스 1
12.5%
보 1
12.5%
관 1
12.5%

부서
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size41.4 KiB
의상실
2568 
소품실
1975 
장신구실
570 
장치실
 
174

Length

Max length4
Median length3
Mean length3.1078116
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
의상실 2568
48.6%
소품실 1975
37.4%
장신구실 570
 
10.8%
장치실 174
 
3.3%

Length

2023-12-12T21:04:43.820813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:04:43.953869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
의상실 2568
48.6%
소품실 1975
37.4%
장신구실 570
 
10.8%
장치실 174
 
3.3%

Interactions

2023-12-12T21:04:36.746527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:04:35.452510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:04:35.803876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:04:36.228679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:04:36.860976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:04:35.532732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:04:35.897055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:04:36.377445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:04:36.969194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:04:35.617306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:04:35.982558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:04:36.505845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:04:37.091772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:04:35.708577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:04:36.114208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:04:36.630538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:04:44.053351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
총수량보유수량단위단가대여비부서
총수량1.0001.0000.0000.0000.0000.047
보유수량1.0001.0000.0000.0000.0000.047
단위0.0000.0001.0000.1640.1640.809
단가0.0000.0000.1641.0001.0000.667
대여비0.0000.0000.1641.0001.0000.667
부서0.0470.0470.8090.6670.6671.000
2023-12-12T21:04:44.174246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부서단위
부서1.0000.613
단위0.6131.000
2023-12-12T21:04:44.274743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
총수량보유수량단가대여비단위부서
총수량1.0001.000-0.193-0.1930.0000.019
보유수량1.0001.000-0.193-0.1930.0000.019
단가-0.193-0.1931.0001.0000.0740.529
대여비-0.193-0.1931.0001.0000.0740.529
단위0.0000.0000.0740.0741.0000.613
부서0.0190.0190.5290.5290.6131.000

Missing values

2023-12-12T21:04:37.251168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:04:37.437921image/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

번호물품명공연명물품번호총수량보유수량단위단가대여비보관처보관처상세부서
012014-테트스여의상2014-테스트C20140962108010106벌25000012500제2보관창고(파주시)<NA>의상실
12품20152015 품C201603310330141414습80000040000제2보관창고(파주시)<NA>의상실
23조용진2016 기본활용법C2016033102500111점37000018500제2보관창고(파주시)<NA>의상실
34조용진2016 기본활용법C2016033102600111점1700008500제2보관창고(파주시)<NA>의상실
45황태인2016 기본활용법C2016033102700111점20000010000제2보관창고(파주시)<NA>의상실
56동래학춤4인4색, 나흘간의춤이야기2000C201408631500282828벌25420012710제2보관창고(파주시)<NA>의상실
67사랑가,남자4인4색, 나흘간의춤이야기2000C2014086115200111벌33961016981제2보관창고(파주시)<NA>의상실
78사랑가,여자4인4색, 나흘간의춤이야기2000C2014086215300111벌42894021447제2보관창고(파주시)<NA>의상실
89산조(남)4인4색, 나흘간의춤이야기2000C2014086115500111벌35167017584제2보관창고(파주시)<NA>의상실
910산조(여)4인4색, 나흘간의춤이야기2000C2014086215600111벌35167017584제2보관창고(파주시)<NA>의상실
번호물품명공연명물품번호총수량보유수량단위단가대여비보관처보관처상세부서
52775,278숲 속의 무지개흥보가1990D2014102900700111개3600000180000제2보관창고(파주시)<NA>장치실
52785,279하늘흥보가1990D2014102900900111개3600000180000제2보관창고(파주시)<NA>장치실
52795,280놀부 집흥보전1990D2014102900500111개3600000180000제2보관창고(파주시)<NA>장치실
52805,281산수화흥보전1990D2014102900200111개3600000180000제2보관창고(파주시)<NA>장치실
52815,282산수화흥보전1990D2014102900100111개3600000180000제2보관창고(파주시)<NA>장치실
52825,283움막흥보전1990D2014102901700111개2200000110000제2보관창고(파주시)<NA>장치실
52835,284전각흥보전1990D2015012900300111권3600000180000제2보관창고(파주시)<NA>장치실
52845,285초가집흥보전1990D2014102901500111개2200000110000제2보관창고(파주시)<NA>장치실
52855,286해외용 흥부집흥보전1990D2014102901600111개2200000110000제2보관창고(파주시)<NA>장치실
52865,287혼례행렬흥보전1990D2014102901100111개3600000180000제2보관창고(파주시)<NA>장치실