Overview

Dataset statistics

Number of variables9
Number of observations6899
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory518.9 KiB
Average record size in memory77.0 B

Variable types

Categorical4
Text2
Numeric3

Dataset

Description문화체육관광부에서 제공하는 국가도서관통계시스템 내 전국작은도서관정보에 대한 주요 통계정보를 제공하여 국민들의 문화체육관광 통계데이터 활성화 제고
Author문화체육관광부
URLhttps://www.data.go.kr/data/15072349/fileData.do

Alerts

평가년도 has constant value ""Constant
도서관구분 has constant value ""Constant
장서수 is highly overall correlated with 도서예산High correlation
도서예산 is highly overall correlated with 장서수High correlation
사서수 is highly imbalanced (74.6%)Imbalance
방문자수 has 162 (2.3%) zerosZeros
도서예산 has 1833 (26.6%) zerosZeros

Reproduction

Analysis started2023-12-12 01:44:29.267601
Analysis finished2023-12-12 01:44:32.271887
Duration3 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

평가년도
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size54.0 KiB
2022
6899 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2022 6899
100.0%

Length

2023-12-12T10:44:32.345817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:44:32.458861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 6899
100.0%

도서관구분
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size54.0 KiB
LIBTYPE000002003
6899 

Length

Max length16
Median length16
Mean length16
Min length16

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowLIBTYPE000002003
2nd rowLIBTYPE000002003
3rd rowLIBTYPE000002003
4th rowLIBTYPE000002003
5th rowLIBTYPE000002003

Common Values

ValueCountFrequency (%)
LIBTYPE000002003 6899
100.0%

Length

2023-12-12T10:44:32.565888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:44:32.674579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
libtype000002003 6899
100.0%

도서관명
Text

Distinct6245
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Memory size54.0 KiB
2023-12-12T10:44:33.061355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length25
Mean length9.555008
Min length2

Characters and Unicode

Total characters65920
Distinct characters826
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5904 ?
Unique (%)85.6%

Sample

1st row경희궁자이3단지 작은도서관
2nd row꿈꾸는 평창동 작은도서관
3rd row나무와 열매 어린이 도서관
4th row도담도담한옥도서관
5th row두산아파트문고
ValueCountFrequency (%)
작은도서관 2252
 
21.4%
도서관 182
 
1.7%
새마을문고 93
 
0.9%
꿈꾸는 49
 
0.5%
작은 38
 
0.4%
북카페 34
 
0.3%
새마을작은도서관 33
 
0.3%
새마을 29
 
0.3%
문고 24
 
0.2%
공립 19
 
0.2%
Other values (6495) 7793
73.9%
2023-12-12T10:44:33.651789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
도 6456
 
9.8%
서 6438
 
9.8%
관 6328
 
9.6%
은 5396
 
8.2%
작 5251
 
8.0%
3719
 
5.6%
마 962
 
1.5%
동 852
 
1.3%
을 759
 
1.2%
이 672
 
1.0%
Other values (816) 29087
44.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 60282
91.4%
Space Separator 3719
 
5.6%
Decimal Number 770
 
1.2%
Uppercase Letter 661
 
1.0%
Lowercase Letter 229
 
0.3%
Open Punctuation 85
 
0.1%
Close Punctuation 85
 
0.1%
Other Punctuation 67
 
0.1%
Dash Punctuation 18
 
< 0.1%
Modifier Symbol 1
 
< 0.1%
Other values (3) 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 6456
 
10.7%
서 6438
 
10.7%
관 6328
 
10.5%
은 5396
 
9.0%
작 5251
 
8.7%
마 962
 
1.6%
동 852
 
1.4%
을 759
 
1.3%
이 672
 
1.1%
문 568
 
0.9%
Other values (743) 26600
44.1%
Uppercase Letter
ValueCountFrequency (%)
H 172
26.0%
L 155
23.4%
S 49
 
7.4%
B 28
 
4.2%
K 28
 
4.2%
C 26
 
3.9%
E 19
 
2.9%
A 19
 
2.9%
O 18
 
2.7%
I 18
 
2.7%
Other values (15) 129
19.5%
Lowercase Letter
ValueCountFrequency (%)
e 46
20.1%
o 39
17.0%
k 22
9.6%
i 15
 
6.6%
a 15
 
6.6%
s 12
 
5.2%
r 12
 
5.2%
l 11
 
4.8%
n 8
 
3.5%
h 6
 
2.6%
Other values (12) 43
18.8%
Decimal Number
ValueCountFrequency (%)
1 246
31.9%
2 234
30.4%
3 104
13.5%
4 61
 
7.9%
5 42
 
5.5%
7 26
 
3.4%
6 24
 
3.1%
9 12
 
1.6%
8 11
 
1.4%
0 10
 
1.3%
Other Punctuation
ValueCountFrequency (%)
' 22
32.8%
& 15
22.4%
. 13
19.4%
, 10
14.9%
? 2
 
3.0%
@ 2
 
3.0%
" 2
 
3.0%
# 1
 
1.5%
Space Separator
ValueCountFrequency (%)
3719
100.0%
Open Punctuation
ValueCountFrequency (%)
( 85
100.0%
Close Punctuation
ValueCountFrequency (%)
) 85
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Other Symbol
ValueCountFrequency (%)
♡ 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 60258
91.4%
Common 4747
 
7.2%
Latin 891
 
1.4%
Han 24
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 6456
 
10.7%
서 6438
 
10.7%
관 6328
 
10.5%
은 5396
 
9.0%
작 5251
 
8.7%
마 962
 
1.6%
동 852
 
1.4%
을 759
 
1.3%
이 672
 
1.1%
문 568
 
0.9%
Other values (724) 26576
44.1%
Latin
ValueCountFrequency (%)
H 172
19.3%
L 155
17.4%
S 49
 
5.5%
e 46
 
5.2%
o 39
 
4.4%
B 28
 
3.1%
K 28
 
3.1%
C 26
 
2.9%
k 22
 
2.5%
E 19
 
2.1%
Other values (38) 307
34.5%
Common
ValueCountFrequency (%)
3719
78.3%
1 246
 
5.2%
2 234
 
4.9%
3 104
 
2.2%
( 85
 
1.8%
) 85
 
1.8%
4 61
 
1.3%
5 42
 
0.9%
7 26
 
0.5%
6 24
 
0.5%
Other values (15) 121
 
2.5%
Han
ValueCountFrequency (%)
休 4
16.7%
愛 2
 
8.3%
書 2
 
8.3%
光 1
 
4.2%
大 1
 
4.2%
林 1
 
4.2%
家 1
 
4.2%
希 1
 
4.2%
讀 1
 
4.2%
五 1
 
4.2%
Other values (9) 9
37.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 60258
91.4%
ASCII 5636
 
8.5%
CJK 24
 
< 0.1%
Misc Symbols 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
도 6456
 
10.7%
서 6438
 
10.7%
관 6328
 
10.5%
은 5396
 
9.0%
작 5251
 
8.7%
마 962
 
1.6%
동 852
 
1.4%
을 759
 
1.3%
이 672
 
1.1%
문 568
 
0.9%
Other values (724) 26576
44.1%
ASCII
ValueCountFrequency (%)
3719
66.0%
1 246
 
4.4%
2 234
 
4.2%
H 172
 
3.1%
L 155
 
2.8%
3 104
 
1.8%
( 85
 
1.5%
) 85
 
1.5%
4 61
 
1.1%
S 49
 
0.9%
Other values (61) 726
 
12.9%
CJK
ValueCountFrequency (%)
休 4
16.7%
愛 2
 
8.3%
書 2
 
8.3%
光 1
 
4.2%
大 1
 
4.2%
林 1
 
4.2%
家 1
 
4.2%
希 1
 
4.2%
讀 1
 
4.2%
五 1
 
4.2%
Other values (9) 9
37.5%
Misc Symbols
ValueCountFrequency (%)
♡ 1
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

행정구역
Categorical

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size54.0 KiB
경기
1676 
서울
943 
경남
489 
부산
430 
충남
389 
Other values (12)
2972 

Length

Max length7
Median length2
Mean length2.0427598
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기 1676
24.3%
서울 943
13.7%
경남 489
 
7.1%
부산 430
 
6.2%
충남 389
 
5.6%
전북 352
 
5.1%
광주 346
 
5.0%
전남 337
 
4.9%
인천 300
 
4.3%
경북 293
 
4.2%
Other values (7) 1344
19.5%

Length

2023-12-12T10:44:33.828202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기 1676
24.3%
서울 943
13.7%
경남 489
 
7.1%
부산 430
 
6.2%
충남 389
 
5.6%
전북 352
 
5.1%
광주 346
 
5.0%
전남 337
 
4.9%
인천 300
 
4.3%
경북 293
 
4.2%
Other values (7) 1344
19.5%

시군구
Text

Distinct242
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size54.0 KiB
2023-12-12T10:44:34.234960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length2.9359327
Min length2

Characters and Unicode

Total characters20255
Distinct characters159
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

Unique28 ?
Unique (%)0.4%

Sample

1st row종로구
2nd row종로구
3rd row종로구
4th row종로구
5th row종로구
ValueCountFrequency (%)
서구 219
 
3.2%
화성시 214
 
3.1%
북구 199
 
2.9%
남구 154
 
2.2%
수원시 150
 
2.2%
동구 149
 
2.2%
중구 143
 
2.1%
전주시 125
 
1.8%
용인시 121
 
1.8%
청주시 114
 
1.7%
Other values (232) 5311
77.0%
2023-12-12T10:44:34.821234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 3557
 
17.6%
구 2637
 
13.0%
군 958
 
4.7%
주 871
 
4.3%
성 650
 
3.2%
산 634
 
3.1%
남 534
 
2.6%
천 521
 
2.6%
서 514
 
2.5%
양 484
 
2.4%
Other values (149) 8895
43.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 20243
99.9%
Decimal Number 12
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 3557
17.6%
구 2637
 
13.0%
군 958
 
4.7%
주 871
 
4.3%
성 650
 
3.2%
산 634
 
3.1%
남 534
 
2.6%
천 521
 
2.6%
서 514
 
2.5%
양 484
 
2.4%
Other values (146) 8883
43.9%
Decimal Number
ValueCountFrequency (%)
1 8
66.7%
3 3
 
25.0%
2 1
 
8.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 20243
99.9%
Common 12
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 3557
17.6%
구 2637
 
13.0%
군 958
 
4.7%
주 871
 
4.3%
성 650
 
3.2%
산 634
 
3.1%
남 534
 
2.6%
천 521
 
2.6%
서 514
 
2.5%
양 484
 
2.4%
Other values (146) 8883
43.9%
Common
ValueCountFrequency (%)
1 8
66.7%
3 3
 
25.0%
2 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 20243
99.9%
ASCII 12
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 3557
17.6%
구 2637
 
13.0%
군 958
 
4.7%
주 871
 
4.3%
성 650
 
3.2%
산 634
 
3.1%
남 534
 
2.6%
천 521
 
2.6%
서 514
 
2.5%
양 484
 
2.4%
Other values (146) 8883
43.9%
ASCII
ValueCountFrequency (%)
1 8
66.7%
3 3
 
25.0%
2 1
 
8.3%

장서수
Real number (ℝ)

HIGH CORRELATION 

Distinct4177
Distinct (%)60.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6273.2699
Minimum1000
Maximum56544
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size60.8 KiB
2023-12-12T10:44:35.043204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1000
5-th percentile1200
Q12600
median4976
Q38369
95-th percentile15727.5
Maximum56544
Range55544
Interquartile range (IQR)5769

Descriptive statistics

Standard deviation5068.2615
Coefficient of variation (CV)0.80791383
Kurtosis8.1154998
Mean6273.2699
Median Absolute Deviation (MAD)2676
Skewness2.1289235
Sum43279289
Variance25687275
MonotonicityNot monotonic
2023-12-12T10:44:35.234587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3000 148
 
2.1%
2000 135
 
2.0%
1500 112
 
1.6%
1000 104
 
1.5%
2500 87
 
1.3%
4000 81
 
1.2%
1200 77
 
1.1%
5000 75
 
1.1%
3500 67
 
1.0%
1300 39
 
0.6%
Other values (4167) 5974
86.6%
ValueCountFrequency (%)
1000 104
1.5%
1002 4
 
0.1%
1003 3
 
< 0.1%
1004 1
 
< 0.1%
1005 2
 
< 0.1%
1006 1
 
< 0.1%
1007 1
 
< 0.1%
1008 1
 
< 0.1%
1009 1
 
< 0.1%
1010 6
 
0.1%
ValueCountFrequency (%)
56544 1
< 0.1%
50103 1
< 0.1%
46209 1
< 0.1%
43756 1
< 0.1%
43400 1
< 0.1%
41410 1
< 0.1%
39934 1
< 0.1%
39557 1
< 0.1%
39050 1
< 0.1%
37594 1
< 0.1%

사서수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.0 KiB
0
6111 
1
687 
2
 
79
3
 
14
4
 
8

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 6111
88.6%
1 687
 
10.0%
2 79
 
1.1%
3 14
 
0.2%
4 8
 
0.1%

Length

2023-12-12T10:44:35.394570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:44:35.558533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 6111
88.6%
1 687
 
10.0%
2 79
 
1.1%
3 14
 
0.2%
4 8
 
0.1%

방문자수
Real number (ℝ)

ZEROS 

Distinct1530
Distinct (%)22.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4054.4928
Minimum0
Maximum142146
Zeros162
Zeros (%)2.3%
Negative0
Negative (%)0.0%
Memory size60.8 KiB
2023-12-12T10:44:35.712185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile155.7
Q1939
median2349
Q34800
95-th percentile13050
Maximum142146
Range142146
Interquartile range (IQR)3861

Descriptive statistics

Standard deviation6650.554
Coefficient of variation (CV)1.6402925
Kurtosis79.452297
Mean4054.4928
Median Absolute Deviation (MAD)1566
Skewness6.8891464
Sum27971946
Variance44229869
MonotonicityNot monotonic
2023-12-12T10:44:35.881567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2610 363
 
5.3%
1305 327
 
4.7%
522 211
 
3.1%
5220 192
 
2.8%
783 191
 
2.8%
3915 179
 
2.6%
3130 176
 
2.6%
261 170
 
2.5%
0 162
 
2.3%
1565 148
 
2.1%
Other values (1520) 4780
69.3%
ValueCountFrequency (%)
0 162
2.3%
1 1
 
< 0.1%
2 6
 
0.1%
3 1
 
< 0.1%
4 5
 
0.1%
5 2
 
< 0.1%
8 2
 
< 0.1%
9 1
 
< 0.1%
10 12
 
0.2%
12 3
 
< 0.1%
ValueCountFrequency (%)
142146 1
< 0.1%
104320 1
< 0.1%
101095 1
< 0.1%
96274 1
< 0.1%
93926 1
< 0.1%
88740 1
< 0.1%
84510 1
< 0.1%
81395 1
< 0.1%
78250 1
< 0.1%
74296 1
< 0.1%

도서예산
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct1467
Distinct (%)21.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2497328.7
Minimum0
Maximum1.354075 × 108
Zeros1833
Zeros (%)26.6%
Negative0
Negative (%)0.0%
Memory size60.8 KiB
2023-12-12T10:44:36.062918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1500000
Q33300000
95-th percentile8000000
Maximum1.354075 × 108
Range1.354075 × 108
Interquartile range (IQR)3300000

Descriptive statistics

Standard deviation4383523.7
Coefficient of variation (CV)1.755285
Kurtosis192.09518
Mean2497328.7
Median Absolute Deviation (MAD)1500000
Skewness9.8169469
Sum1.7229071 × 1010
Variance1.921528 × 1013
MonotonicityNot monotonic
2023-12-12T10:44:36.264707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1833
26.6%
1000000 385
 
5.6%
3000000 330
 
4.8%
2000000 315
 
4.6%
4000000 231
 
3.3%
500000 200
 
2.9%
1500000 150
 
2.2%
1200000 130
 
1.9%
5000000 124
 
1.8%
2500000 90
 
1.3%
Other values (1457) 3111
45.1%
ValueCountFrequency (%)
0 1833
26.6%
50 1
 
< 0.1%
150 1
 
< 0.1%
170 1
 
< 0.1%
176 1
 
< 0.1%
200 1
 
< 0.1%
240 1
 
< 0.1%
300 1
 
< 0.1%
500 1
 
< 0.1%
1200 1
 
< 0.1%
ValueCountFrequency (%)
135407500 1
 
< 0.1%
90000000 1
 
< 0.1%
80000000 1
 
< 0.1%
72000000 1
 
< 0.1%
58302380 1
 
< 0.1%
51039630 1
 
< 0.1%
50000000 3
< 0.1%
44441600 1
 
< 0.1%
44229590 1
 
< 0.1%
40000000 2
< 0.1%

Interactions

2023-12-12T10:44:31.539628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:44:30.392784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:44:30.785403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:44:31.685390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:44:30.511410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:44:30.916161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:44:31.834159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:44:30.649829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:44:31.058550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T10:44:36.393391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정구역장서수사서수방문자수도서예산
행정구역1.0000.1710.1330.0800.000
장서수0.1711.0000.4160.2800.301
사서수0.1330.4161.0000.3760.247
방문자수0.0800.2800.3761.0000.293
도서예산0.0000.3010.2470.2931.000
2023-12-12T10:44:36.542778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정구역사서수
행정구역1.0000.069
사서수0.0691.000
2023-12-12T10:44:36.651248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
장서수방문자수도서예산행정구역사서수
장서수1.0000.4460.5120.0670.186
방문자수0.4461.0000.4460.0320.228
도서예산0.5120.4461.0000.0000.154
행정구역0.0670.0320.0001.0000.069
사서수0.1860.2280.1540.0691.000

Missing values

2023-12-12T10:44:32.015512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T10:44:32.196247image/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

평가년도도서관구분도서관명행정구역시군구장서수사서수방문자수도서예산
02022LIBTYPE000002003경희궁자이3단지 작은도서관서울종로구2671036500
12022LIBTYPE000002003꿈꾸는 평창동 작은도서관서울종로구5390044465478000
22022LIBTYPE000002003나무와 열매 어린이 도서관서울종로구6825031301500000
32022LIBTYPE000002003도담도담한옥도서관서울종로구6390093906301200
42022LIBTYPE000002003두산아파트문고서울종로구320003710
52022LIBTYPE000002003무악다솜방서울종로구5625044375336200
62022LIBTYPE000002003삼청공원 숲속도서관서울종로구95011281704080000
72022LIBTYPE000002003석천문화관서울종로구1690812525000000
82022LIBTYPE000002003숭인마루 작은도서관서울종로구7353065255007700
92022LIBTYPE000002003어린이도서관 꿈과쉼서울종로구11729012521849930
평가년도도서관구분도서관명행정구역시군구장서수사서수방문자수도서예산
68892022LIBTYPE000002003하례2리새마을작은도서관제주서귀포시133701050
68902022LIBTYPE000002003하모2리새마을작은도서관제주서귀포시1500026105000000
68912022LIBTYPE000002003하모3리새마을작은도서관제주서귀포시153003141000000
68922022LIBTYPE000002003하원애향새마을작은도서관제주서귀포시5096031304000000
68932022LIBTYPE000002003한라새마을작은도서관제주서귀포시4250010950
68942022LIBTYPE000002003호근새마을작은도서관제주서귀포시4974010951500000
68952022LIBTYPE000002003희망새마을작은도서관제주서귀포시3002020881000000
68962022LIBTYPE000002003(신례1리)예촌작은도서관제주서귀포시7002013052000000
68972022LIBTYPE00000200393대대독서대학제주서귀포시133607300
68982022LIBTYPE000002003LH강정작은도서관제주서귀포시2281013054000000