Overview

Dataset statistics

Number of variables6
Number of observations2301
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory110.2 KiB
Average record size in memory49.1 B

Variable types

Numeric1
Text3
Categorical2

Dataset

Description대구광역시 동구 관내 도서관 신착도서에 관한 데이터로 도서명, 저자, 출판사, 보유도서관의 데이터를 제공합니다.
URLhttps://www.data.go.kr/data/15102155/fileData.do

Alerts

데이터기준일 has constant value ""Constant
연번 is highly overall correlated with 보유도서관High correlation
보유도서관 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 12:38:52.634731
Analysis finished2023-12-12 12:38:54.072711
Duration1.44 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct2301
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1151
Minimum1
Maximum2301
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size20.4 KiB
2023-12-12T21:38:54.162777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile116
Q1576
median1151
Q31726
95-th percentile2186
Maximum2301
Range2300
Interquartile range (IQR)1150

Descriptive statistics

Standard deviation664.38581
Coefficient of variation (CV)0.57722485
Kurtosis-1.2
Mean1151
Median Absolute Deviation (MAD)575
Skewness0
Sum2648451
Variance441408.5
MonotonicityStrictly increasing
2023-12-12T21:38:54.349320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
1538 1
 
< 0.1%
1532 1
 
< 0.1%
1533 1
 
< 0.1%
1534 1
 
< 0.1%
1535 1
 
< 0.1%
1536 1
 
< 0.1%
1537 1
 
< 0.1%
1539 1
 
< 0.1%
1530 1
 
< 0.1%
Other values (2291) 2291
99.6%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
2301 1
< 0.1%
2300 1
< 0.1%
2299 1
< 0.1%
2298 1
< 0.1%
2297 1
< 0.1%
2296 1
< 0.1%
2295 1
< 0.1%
2294 1
< 0.1%
2293 1
< 0.1%
2292 1
< 0.1%

도서명
Text

Distinct1940
Distinct (%)84.3%
Missing0
Missing (%)0.0%
Memory size18.1 KiB
2023-12-12T21:38:54.719754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length114
Median length57
Mean length25.141243
Min length1

Characters and Unicode

Total characters57850
Distinct characters1104
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks10 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1676 ?
Unique (%)72.8%

Sample

1st row안락탐정 : 고바야시 야스미 연작소설
2nd row태양의 마녀 나코와 코기 봉봉. 3, 기적의 별똥별을 찾아라!
3rd row태양의 마녀 나코와 코기 봉봉. 4, 달의 성을 둘러싼 무시무시한 음모
4th row오늘부터 명탐정
5th row태양의 마녀 나코와 코기 봉봉. 5, 스위봉에 걸린 저주를 풀어라!
ValueCountFrequency (%)
1182
 
7.6%
위한 110
 
0.7%
2 89
 
0.6%
이야기 87
 
0.6%
1 78
 
0.5%
내 64
 
0.4%
수업 47
 
0.3%
어떻게 45
 
0.3%
우리 45
 
0.3%
비밀 42
 
0.3%
Other values (6690) 13691
88.4%
2023-12-12T21:38:55.318287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13180
 
22.8%
: 1170
 
2.0%
의 1122
 
1.9%
이 1080
 
1.9%
는 954
 
1.6%
, 582
 
1.0%
기 541
 
0.9%
한 529
 
0.9%
지 526
 
0.9%
사 525
 
0.9%
Other values (1094) 37641
65.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 37604
65.0%
Space Separator 13180
 
22.8%
Other Punctuation 2478
 
4.3%
Lowercase Letter 2186
 
3.8%
Decimal Number 1141
 
2.0%
Uppercase Letter 386
 
0.7%
Open Punctuation 349
 
0.6%
Close Punctuation 349
 
0.6%
Math Symbol 141
 
0.2%
Dash Punctuation 26
 
< 0.1%
Other values (4) 10
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 1122
 
3.0%
이 1080
 
2.9%
는 954
 
2.5%
기 541
 
1.4%
한 529
 
1.4%
지 526
 
1.4%
사 525
 
1.4%
가 500
 
1.3%
리 463
 
1.2%
을 449
 
1.2%
Other values (997) 30915
82.2%
Lowercase Letter
ValueCountFrequency (%)
e 239
10.9%
o 213
 
9.7%
i 187
 
8.6%
a 172
 
7.9%
r 161
 
7.4%
n 160
 
7.3%
t 152
 
7.0%
s 149
 
6.8%
l 94
 
4.3%
h 78
 
3.6%
Other values (16) 581
26.6%
Uppercase Letter
ValueCountFrequency (%)
T 62
16.1%
G 37
 
9.6%
S 34
 
8.8%
M 32
 
8.3%
B 24
 
6.2%
I 22
 
5.7%
P 22
 
5.7%
N 21
 
5.4%
A 14
 
3.6%
C 13
 
3.4%
Other values (16) 105
27.2%
Other Punctuation
ValueCountFrequency (%)
: 1170
47.2%
, 582
23.5%
. 379
 
15.3%
! 142
 
5.7%
? 89
 
3.6%
· 34
 
1.4%
' 30
 
1.2%
＆ 11
 
0.4%
％ 10
 
0.4%
& 10
 
0.4%
Other values (6) 21
 
0.8%
Decimal Number
ValueCountFrequency (%)
1 274
24.0%
2 227
19.9%
0 195
17.1%
3 125
11.0%
5 85
 
7.4%
4 72
 
6.3%
6 52
 
4.6%
7 48
 
4.2%
9 33
 
2.9%
8 30
 
2.6%
Math Symbol
ValueCountFrequency (%)
= 122
86.5%
~ 10
 
7.1%
× 5
 
3.5%
＋ 2
 
1.4%
+ 2
 
1.4%
Open Punctuation
ValueCountFrequency (%)
( 332
95.1%
[ 16
 
4.6%
「 1
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 332
95.1%
] 16
 
4.6%
」 1
 
0.3%
Other Symbol
ValueCountFrequency (%)
℃ 2
40.0%
★ 2
40.0%
♡ 1
20.0%
Space Separator
ValueCountFrequency (%)
13180
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 26
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 3
100.0%
Other Number
ValueCountFrequency (%)
① 1
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 37587
65.0%
Common 17673
30.5%
Latin 2573
 
4.4%
Han 17
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 1122
 
3.0%
이 1080
 
2.9%
는 954
 
2.5%
기 541
 
1.4%
한 529
 
1.4%
지 526
 
1.4%
사 525
 
1.4%
가 500
 
1.3%
리 463
 
1.2%
을 449
 
1.2%
Other values (980) 30898
82.2%
Latin
ValueCountFrequency (%)
e 239
 
9.3%
o 213
 
8.3%
i 187
 
7.3%
a 172
 
6.7%
r 161
 
6.3%
n 160
 
6.2%
t 152
 
5.9%
s 149
 
5.8%
l 94
 
3.7%
h 78
 
3.0%
Other values (43) 968
37.6%
Common
ValueCountFrequency (%)
13180
74.6%
: 1170
 
6.6%
, 582
 
3.3%
. 379
 
2.1%
( 332
 
1.9%
) 332
 
1.9%
1 274
 
1.6%
2 227
 
1.3%
0 195
 
1.1%
! 142
 
0.8%
Other values (34) 860
 
4.9%
Han
ValueCountFrequency (%)
記 1
 
5.9%
筆 1
 
5.9%
堂 1
 
5.9%
自 1
 
5.9%
然 1
 
5.9%
風 1
 
5.9%
多 1
 
5.9%
古 1
 
5.9%
現 1
 
5.9%
代 1
 
5.9%
Other values (7) 7
41.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 37567
64.9%
ASCII 20170
34.9%
None 67
 
0.1%
Compat Jamo 20
 
< 0.1%
CJK 17
 
< 0.1%
Misc Symbols 3
 
< 0.1%
Letterlike Symbols 2
 
< 0.1%
Punctuation 2
 
< 0.1%
Enclosed Alphanum 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
13180
65.3%
: 1170
 
5.8%
, 582
 
2.9%
. 379
 
1.9%
( 332
 
1.6%
) 332
 
1.6%
1 274
 
1.4%
e 239
 
1.2%
2 227
 
1.1%
o 213
 
1.1%
Other values (73) 3242
 
16.1%
Hangul
ValueCountFrequency (%)
의 1122
 
3.0%
이 1080
 
2.9%
는 954
 
2.5%
기 541
 
1.4%
한 529
 
1.4%
지 526
 
1.4%
사 525
 
1.4%
가 500
 
1.3%
리 463
 
1.2%
을 449
 
1.2%
Other values (973) 30878
82.2%
None
ValueCountFrequency (%)
· 34
50.7%
＆ 11
 
16.4%
％ 10
 
14.9%
× 5
 
7.5%
／ 3
 
4.5%
＋ 2
 
3.0%
」 1
 
1.5%
「 1
 
1.5%
Compat Jamo
ValueCountFrequency (%)
ㅅ 4
20.0%
ㄱ 4
20.0%
ㄴ 4
20.0%
ㄷ 4
20.0%
ㅎ 2
10.0%
ㄹ 1
 
5.0%
ㅇ 1
 
5.0%
Letterlike Symbols
ValueCountFrequency (%)
℃ 2
100.0%
Misc Symbols
ValueCountFrequency (%)
★ 2
66.7%
♡ 1
33.3%
Punctuation
ValueCountFrequency (%)
… 2
100.0%
CJK
ValueCountFrequency (%)
記 1
 
5.9%
筆 1
 
5.9%
堂 1
 
5.9%
自 1
 
5.9%
然 1
 
5.9%
風 1
 
5.9%
多 1
 
5.9%
古 1
 
5.9%
現 1
 
5.9%
代 1
 
5.9%
Other values (7) 7
41.2%
Enclosed Alphanum
ValueCountFrequency (%)
① 1
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

저자
Text

Distinct1718
Distinct (%)74.7%
Missing0
Missing (%)0.0%
Memory size18.1 KiB
2023-12-12T21:38:55.745593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length49
Mean length14.3103
Min length2

Characters and Unicode

Total characters32928
Distinct characters696
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1349 ?
Unique (%)58.6%

Sample

1st row고바야시 야스미 지음 ; 주자덕 옮김
2nd row히로시마 레이코 글 ; KeG 그림 ; 김정화 옮김
3rd row히로시마 레이코 글 ; KeG 그림 ; 김정화 옮김
4th row정해연 글 ; 국민지 그림
5th row히로시마 레이코 글 ; KeG 그림 ; 김정화 옮김
ValueCountFrequency (%)
1492
 
14.7%
지음 1324
 
13.0%
옮김 683
 
6.7%
그림 661
 
6.5%
글 545
 
5.4%
글·그림 178
 
1.7%
공]지음 55
 
0.5%
공]글 38
 
0.4%
저 36
 
0.4%
외 34
 
0.3%
Other values (3047) 5135
50.4%
2023-12-12T21:38:56.351073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7886
23.9%
지 1627
 
4.9%
; 1491
 
4.5%
음 1445
 
4.4%
김 1270
 
3.9%
그 896
 
2.7%
림 881
 
2.7%
글 795
 
2.4%
이 737
 
2.2%
옮 700
 
2.1%
Other values (686) 15200
46.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22367
67.9%
Space Separator 7886
 
23.9%
Other Punctuation 1979
 
6.0%
Open Punctuation 180
 
0.5%
Close Punctuation 180
 
0.5%
Lowercase Letter 171
 
0.5%
Uppercase Letter 139
 
0.4%
Decimal Number 15
 
< 0.1%
Dash Punctuation 10
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 1627
 
7.3%
음 1445
 
6.5%
김 1270
 
5.7%
그 896
 
4.0%
림 881
 
3.9%
글 795
 
3.6%
이 737
 
3.3%
옮 700
 
3.1%
정 389
 
1.7%
스 335
 
1.5%
Other values (618) 13292
59.4%
Uppercase Letter
ValueCountFrequency (%)
G 16
11.5%
T 14
10.1%
S 14
10.1%
A 13
9.4%
M 11
 
7.9%
N 10
 
7.2%
K 10
 
7.2%
J 9
 
6.5%
H 7
 
5.0%
R 5
 
3.6%
Other values (13) 30
21.6%
Lowercase Letter
ValueCountFrequency (%)
e 26
15.2%
t 20
11.7%
o 16
9.4%
a 16
9.4%
r 14
8.2%
i 13
7.6%
y 10
 
5.8%
m 10
 
5.8%
n 9
 
5.3%
s 7
 
4.1%
Other values (11) 30
17.5%
Other Punctuation
ValueCountFrequency (%)
; 1491
75.3%
, 231
 
11.7%
· 206
 
10.4%
. 43
 
2.2%
? 4
 
0.2%
/ 2
 
0.1%
: 1
 
0.1%
@ 1
 
0.1%
Decimal Number
ValueCountFrequency (%)
2 7
46.7%
1 4
26.7%
0 2
 
13.3%
4 1
 
6.7%
6 1
 
6.7%
Open Punctuation
ValueCountFrequency (%)
[ 172
95.6%
( 5
 
2.8%
〈 2
 
1.1%
「 1
 
0.6%
Close Punctuation
ValueCountFrequency (%)
] 172
95.6%
) 5
 
2.8%
〉 2
 
1.1%
」 1
 
0.6%
Space Separator
ValueCountFrequency (%)
7886
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22367
67.9%
Common 10251
31.1%
Latin 310
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 1627
 
7.3%
음 1445
 
6.5%
김 1270
 
5.7%
그 896
 
4.0%
림 881
 
3.9%
글 795
 
3.6%
이 737
 
3.3%
옮 700
 
3.1%
정 389
 
1.7%
스 335
 
1.5%
Other values (618) 13292
59.4%
Latin
ValueCountFrequency (%)
e 26
 
8.4%
t 20
 
6.5%
o 16
 
5.2%
G 16
 
5.2%
a 16
 
5.2%
r 14
 
4.5%
T 14
 
4.5%
S 14
 
4.5%
i 13
 
4.2%
A 13
 
4.2%
Other values (34) 148
47.7%
Common
ValueCountFrequency (%)
7886
76.9%
; 1491
 
14.5%
, 231
 
2.3%
· 206
 
2.0%
[ 172
 
1.7%
] 172
 
1.7%
. 43
 
0.4%
- 10
 
0.1%
2 7
 
0.1%
( 5
 
< 0.1%
Other values (14) 28
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22367
67.9%
ASCII 10349
31.4%
None 212
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7886
76.2%
; 1491
 
14.4%
, 231
 
2.2%
[ 172
 
1.7%
] 172
 
1.7%
. 43
 
0.4%
e 26
 
0.3%
t 20
 
0.2%
o 16
 
0.2%
G 16
 
0.2%
Other values (53) 276
 
2.7%
Hangul
ValueCountFrequency (%)
지 1627
 
7.3%
음 1445
 
6.5%
김 1270
 
5.7%
그 896
 
4.0%
림 881
 
3.9%
글 795
 
3.6%
이 737
 
3.3%
옮 700
 
3.1%
정 389
 
1.7%
스 335
 
1.5%
Other values (618) 13292
59.4%
None
ValueCountFrequency (%)
· 206
97.2%
〈 2
 
0.9%
〉 2
 
0.9%
」 1
 
0.5%
「 1
 
0.5%

출판사
Text

Distinct988
Distinct (%)42.9%
Missing0
Missing (%)0.0%
Memory size18.1 KiB
2023-12-12T21:38:56.674078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length20
Mean length5.2385919
Min length1

Characters and Unicode

Total characters12054
Distinct characters540
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique582 ?
Unique (%)25.3%

Sample

1st row아프로스미디어
2nd row웅진주니어:웅진씽크빅
3rd row웅진주니어:웅진씽크빅
4th row리틀씨앤톡:씨앤톡
5th row웅진주니어:웅진씽크빅
ValueCountFrequency (%)
비룡소 55
 
2.3%
창비 48
 
2.0%
위즈덤하우스 38
 
1.6%
문학동네 38
 
1.6%
아울북 28
 
1.2%
길벗어린이 25
 
1.1%
책읽는곰 25
 
1.1%
우리학교 21
 
0.9%
서울문화사 20
 
0.8%
다산북스 18
 
0.8%
Other values (993) 2045
86.6%
2023-12-12T21:38:57.172224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 510
 
4.2%
북 445
 
3.7%
이 421
 
3.5%
어 293
 
2.4%
사 269
 
2.2%
: 240
 
2.0%
아 235
 
1.9%
미 170
 
1.4%
비 162
 
1.3%
리 146
 
1.2%
Other values (530) 9163
76.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10753
89.2%
Lowercase Letter 374
 
3.1%
Uppercase Letter 277
 
2.3%
Other Punctuation 255
 
2.1%
Close Punctuation 143
 
1.2%
Open Punctuation 143
 
1.2%
Space Separator 60
 
0.5%
Decimal Number 49
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 510
 
4.7%
북 445
 
4.1%
이 421
 
3.9%
어 293
 
2.7%
사 269
 
2.5%
아 235
 
2.2%
미 170
 
1.6%
비 162
 
1.5%
리 146
 
1.4%
문 141
 
1.3%
Other values (468) 7961
74.0%
Lowercase Letter
ValueCountFrequency (%)
o 74
19.8%
s 39
10.4%
e 35
9.4%
k 31
8.3%
i 28
 
7.5%
a 27
 
7.2%
n 22
 
5.9%
r 22
 
5.9%
g 12
 
3.2%
d 12
 
3.2%
Other values (12) 72
19.3%
Uppercase Letter
ValueCountFrequency (%)
B 54
19.5%
K 36
13.0%
R 26
9.4%
H 24
8.7%
E 20
 
7.2%
S 20
 
7.2%
M 15
 
5.4%
O 14
 
5.1%
P 11
 
4.0%
F 10
 
3.6%
Other values (12) 47
17.0%
Decimal Number
ValueCountFrequency (%)
2 25
51.0%
1 13
26.5%
6 2
 
4.1%
4 2
 
4.1%
9 2
 
4.1%
0 2
 
4.1%
8 1
 
2.0%
7 1
 
2.0%
3 1
 
2.0%
Other Punctuation
ValueCountFrequency (%)
: 240
94.1%
& 8
 
3.1%
＆ 3
 
1.2%
? 2
 
0.8%
, 1
 
0.4%
; 1
 
0.4%
Close Punctuation
ValueCountFrequency (%)
) 143
100.0%
Open Punctuation
ValueCountFrequency (%)
( 143
100.0%
Space Separator
ValueCountFrequency (%)
60
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10752
89.2%
Latin 651
 
5.4%
Common 650
 
5.4%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 510
 
4.7%
북 445
 
4.1%
이 421
 
3.9%
어 293
 
2.7%
사 269
 
2.5%
아 235
 
2.2%
미 170
 
1.6%
비 162
 
1.5%
리 146
 
1.4%
문 141
 
1.3%
Other values (467) 7960
74.0%
Latin
ValueCountFrequency (%)
o 74
 
11.4%
B 54
 
8.3%
s 39
 
6.0%
K 36
 
5.5%
e 35
 
5.4%
k 31
 
4.8%
i 28
 
4.3%
a 27
 
4.1%
R 26
 
4.0%
H 24
 
3.7%
Other values (34) 277
42.5%
Common
ValueCountFrequency (%)
: 240
36.9%
) 143
22.0%
( 143
22.0%
60
 
9.2%
2 25
 
3.8%
1 13
 
2.0%
& 8
 
1.2%
＆ 3
 
0.5%
6 2
 
0.3%
4 2
 
0.3%
Other values (8) 11
 
1.7%
Han
ValueCountFrequency (%)
濱 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10752
89.2%
ASCII 1298
 
10.8%
None 3
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 510
 
4.7%
북 445
 
4.1%
이 421
 
3.9%
어 293
 
2.7%
사 269
 
2.5%
아 235
 
2.2%
미 170
 
1.6%
비 162
 
1.5%
리 146
 
1.4%
문 141
 
1.3%
Other values (467) 7960
74.0%
ASCII
ValueCountFrequency (%)
: 240
18.5%
) 143
 
11.0%
( 143
 
11.0%
o 74
 
5.7%
60
 
4.6%
B 54
 
4.2%
s 39
 
3.0%
K 36
 
2.8%
e 35
 
2.7%
k 31
 
2.4%
Other values (51) 443
34.1%
None
ValueCountFrequency (%)
＆ 3
100.0%
CJK
ValueCountFrequency (%)
濱 1
100.0%

보유도서관
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size18.1 KiB
안심도서관
1365 
신천도서관
410 
반야월역사 작은도서관
138 
신암2동작은도서관
 
116
불로어울림 작은도서관
 
53
Other values (9)
219 

Length

Max length11
Median length5
Mean length6.0877879
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
안심도서관 1365
59.3%
신천도서관 410
 
17.8%
반야월역사 작은도서관 138
 
6.0%
신암2동작은도서관 116
 
5.0%
불로어울림 작은도서관 53
 
2.3%
신천3동작은도서관 34
 
1.5%
지저동 작은도서관 33
 
1.4%
신암3동작은도서관 26
 
1.1%
효목2동작은도서관 26
 
1.1%
방촌동 작은도서관 24
 
1.0%
Other values (4) 76
 
3.3%

Length

2023-12-12T21:38:57.340668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
안심도서관 1365
52.4%
신천도서관 410
 
15.7%
작은도서관 304
 
11.7%
반야월역사 138
 
5.3%
신암2동작은도서관 116
 
4.5%
불로어울림 53
 
2.0%
신천3동작은도서관 34
 
1.3%
지저동 33
 
1.3%
신암3동작은도서관 26
 
1.0%
효목2동작은도서관 26
 
1.0%
Other values (5) 100
 
3.8%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size18.1 KiB
2023-05-15
2301 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-05-15
2nd row2023-05-15
3rd row2023-05-15
4th row2023-05-15
5th row2023-05-15

Common Values

ValueCountFrequency (%)
2023-05-15 2301
100.0%

Length

2023-12-12T21:38:57.490256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:38:57.606581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-05-15 2301
100.0%

Interactions

2023-12-12T21:38:53.748054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:38:57.677664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번보유도서관
연번1.0000.848
보유도서관0.8481.000
2023-12-12T21:38:57.772335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번보유도서관
연번1.0000.555
보유도서관0.5551.000

Missing values

2023-12-12T21:38:53.892784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:38:54.022973image/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

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