Overview

Dataset statistics

Number of variables7
Number of observations46
Missing cells5
Missing cells (%)1.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.7 KiB
Average record size in memory59.9 B

Variable types

Text4
Numeric1
DateTime2

Dataset

Description서울특별시 용산구 교육장정보 현황(강좌명, 교육장명, 우편번호, 주소1, 주소2, 등록일, 수정일)에 대한 데이터를 제공합니다.
Author서울특별시 용산구
URLhttps://www.data.go.kr/data/15070874/fileData.do

Alerts

주소2 has 5 (10.9%) missing valuesMissing
강좌명 has unique valuesUnique
등록일 has unique valuesUnique
수정일 has unique valuesUnique

Reproduction

Analysis started2023-12-12 22:57:20.994968
Analysis finished2023-12-12 22:57:21.787060
Duration0.79 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

강좌명
Text

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size500.0 B
2023-12-13T07:57:22.026651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length25
Mean length21.565217
Min length6

Characters and Unicode

Total characters992
Distinct characters257
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)100.0%

Sample

1st row나도 드론 조종사(2기)
2nd row방과후 역사 북아트 지도사 자격 과정
3rd row음악 심리 치료의 이해 온라인 과정
4th row나도 드론 조종사(1기)
5th row삼일회계법인과 함께하는 직장인을 위한 재무관리
ValueCountFrequency (%)
4기 4
 
2.2%
함께하는 3
 
1.7%
과정 3
 
1.7%
북스타트 3
 
1.7%
나도 2
 
1.1%
11월 2
 
1.1%
3단계 2
 
1.1%
용산구 2
 
1.1%
학부모 2
 
1.1%
드론 2
 
1.1%
Other values (150) 156
86.2%
2023-12-13T07:57:22.427279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
141
 
14.2%
( 36
 
3.6%
) 36
 
3.6%
1 21
 
2.1%
, 16
 
1.6%
기 14
 
1.4%
인 12
 
1.2%
2 12
 
1.2%
나 12
 
1.2%
이 12
 
1.2%
Other values (247) 680
68.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 661
66.6%
Space Separator 141
 
14.2%
Decimal Number 55
 
5.5%
Open Punctuation 37
 
3.7%
Close Punctuation 37
 
3.7%
Other Punctuation 24
 
2.4%
Uppercase Letter 18
 
1.8%
Lowercase Letter 11
 
1.1%
Dash Punctuation 5
 
0.5%
Math Symbol 1
 
0.1%
Other values (2) 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 14
 
2.1%
인 12
 
1.8%
나 12
 
1.8%
이 12
 
1.8%
실 11
 
1.7%
교 11
 
1.7%
용 11
 
1.7%
강 10
 
1.5%
는 10
 
1.5%
산 10
 
1.5%
Other values (209) 548
82.9%
Decimal Number
ValueCountFrequency (%)
1 21
38.2%
2 12
21.8%
0 7
 
12.7%
4 6
 
10.9%
3 4
 
7.3%
9 2
 
3.6%
6 1
 
1.8%
5 1
 
1.8%
7 1
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
S 6
33.3%
W 5
27.8%
O 2
 
11.1%
E 1
 
5.6%
Y 1
 
5.6%
D 1
 
5.6%
G 1
 
5.6%
L 1
 
5.6%
Lowercase Letter
ValueCountFrequency (%)
y 2
18.2%
a 2
18.2%
e 2
18.2%
n 1
9.1%
c 1
9.1%
r 1
9.1%
t 1
9.1%
i 1
9.1%
Other Punctuation
ValueCountFrequency (%)
, 16
66.7%
/ 6
 
25.0%
* 1
 
4.2%
. 1
 
4.2%
Open Punctuation
ValueCountFrequency (%)
( 36
97.3%
『 1
 
2.7%
Close Punctuation
ValueCountFrequency (%)
) 36
97.3%
』 1
 
2.7%
Space Separator
ValueCountFrequency (%)
141
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 661
66.6%
Common 302
30.4%
Latin 29
 
2.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 14
 
2.1%
인 12
 
1.8%
나 12
 
1.8%
이 12
 
1.8%
실 11
 
1.7%
교 11
 
1.7%
용 11
 
1.7%
강 10
 
1.5%
는 10
 
1.5%
산 10
 
1.5%
Other values (209) 548
82.9%
Common
ValueCountFrequency (%)
141
46.7%
( 36
 
11.9%
) 36
 
11.9%
1 21
 
7.0%
, 16
 
5.3%
2 12
 
4.0%
0 7
 
2.3%
4 6
 
2.0%
/ 6
 
2.0%
- 5
 
1.7%
Other values (12) 16
 
5.3%
Latin
ValueCountFrequency (%)
S 6
20.7%
W 5
17.2%
y 2
 
6.9%
O 2
 
6.9%
a 2
 
6.9%
e 2
 
6.9%
E 1
 
3.4%
Y 1
 
3.4%
n 1
 
3.4%
D 1
 
3.4%
Other values (6) 6
20.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 661
66.6%
ASCII 327
33.0%
None 2
 
0.2%
Punctuation 2
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
141
43.1%
( 36
 
11.0%
) 36
 
11.0%
1 21
 
6.4%
, 16
 
4.9%
2 12
 
3.7%
0 7
 
2.1%
S 6
 
1.8%
4 6
 
1.8%
/ 6
 
1.8%
Other values (24) 40
 
12.2%
Hangul
ValueCountFrequency (%)
기 14
 
2.1%
인 12
 
1.8%
나 12
 
1.8%
이 12
 
1.8%
실 11
 
1.7%
교 11
 
1.7%
용 11
 
1.7%
강 10
 
1.5%
는 10
 
1.5%
산 10
 
1.5%
Other values (209) 548
82.9%
None
ValueCountFrequency (%)
』 1
50.0%
『 1
50.0%
Punctuation
ValueCountFrequency (%)
’ 1
50.0%
‘ 1
50.0%

교육장명
Text

Distinct39
Distinct (%)84.8%
Missing0
Missing (%)0.0%
Memory size500.0 B
2023-12-13T07:57:22.632406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length17
Mean length11.695652
Min length4

Characters and Unicode

Total characters538
Distinct characters134
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)73.9%

Sample

1st row비대면 온라인 과정(각 자택에서 수업)
2nd row비대면 온라인(각 자택에서 수업)
3rd row비대면 온라인 과정 (각 자택에서 수업)
4th row아세아무인항공교육원
5th row삼일아카데미
ValueCountFrequency (%)
용산구청 5
 
5.6%
용산전자상상가 4
 
4.5%
3층 4
 
4.5%
주민센터 3
 
3.4%
수업 3
 
3.4%
자택에서 3
 
3.4%
비대면 3
 
3.4%
강의실(it창의교육 3
 
3.4%
용산구평생학습관 3
 
3.4%
인도문화원 2
 
2.2%
Other values (51) 56
62.9%
2023-12-13T07:57:22.946541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
45
 
8.4%
용 24
 
4.5%
산 23
 
4.3%
관 15
 
2.8%
구 13
 
2.4%
교 12
 
2.2%
( 12
 
2.2%
) 12
 
2.2%
자 10
 
1.9%
상 10
 
1.9%
Other values (124) 362
67.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 448
83.3%
Space Separator 45
 
8.4%
Open Punctuation 12
 
2.2%
Close Punctuation 12
 
2.2%
Decimal Number 12
 
2.2%
Uppercase Letter 8
 
1.5%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
용 24
 
5.4%
산 23
 
5.1%
관 15
 
3.3%
구 13
 
2.9%
교 12
 
2.7%
자 10
 
2.2%
상 10
 
2.2%
의 10
 
2.2%
실 10
 
2.2%
서 9
 
2.0%
Other values (114) 312
69.6%
Decimal Number
ValueCountFrequency (%)
2 5
41.7%
3 4
33.3%
1 2
 
16.7%
4 1
 
8.3%
Uppercase Letter
ValueCountFrequency (%)
T 4
50.0%
I 4
50.0%
Space Separator
ValueCountFrequency (%)
45
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 448
83.3%
Common 82
 
15.2%
Latin 8
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
용 24
 
5.4%
산 23
 
5.1%
관 15
 
3.3%
구 13
 
2.9%
교 12
 
2.7%
자 10
 
2.2%
상 10
 
2.2%
의 10
 
2.2%
실 10
 
2.2%
서 9
 
2.0%
Other values (114) 312
69.6%
Common
ValueCountFrequency (%)
45
54.9%
( 12
 
14.6%
) 12
 
14.6%
2 5
 
6.1%
3 4
 
4.9%
1 2
 
2.4%
, 1
 
1.2%
4 1
 
1.2%
Latin
ValueCountFrequency (%)
T 4
50.0%
I 4
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 448
83.3%
ASCII 90
 
16.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
45
50.0%
( 12
 
13.3%
) 12
 
13.3%
2 5
 
5.6%
T 4
 
4.4%
3 4
 
4.4%
I 4
 
4.4%
1 2
 
2.2%
, 1
 
1.1%
4 1
 
1.1%
Hangul
ValueCountFrequency (%)
용 24
 
5.4%
산 23
 
5.1%
관 15
 
3.3%
구 13
 
2.9%
교 12
 
2.7%
자 10
 
2.2%
상 10
 
2.2%
의 10
 
2.2%
실 10
 
2.2%
서 9
 
2.0%
Other values (114) 312
69.6%

우편번호
Real number (ℝ)

Distinct22
Distinct (%)47.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4350.5435
Minimum3760
Maximum4422
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-13T07:57:23.051430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3760
5-th percentile4312.5
Q14333.5
median4380
Q34393
95-th percentile4419.75
Maximum4422
Range662
Interquartile range (IQR)59.5

Descriptive statistics

Standard deviation105.4288
Coefficient of variation (CV)0.024233478
Kurtosis23.191127
Mean4350.5435
Median Absolute Deviation (MAD)20
Skewness-4.4918476
Sum200125
Variance11115.231
MonotonicityNot monotonic
2023-12-13T07:57:23.147194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
4390 10
21.7%
4366 5
10.9%
4400 5
10.9%
4316 4
 
8.7%
4360 2
 
4.3%
4317 2
 
4.3%
4420 2
 
4.3%
4314 2
 
4.3%
4374 1
 
2.2%
4419 1
 
2.2%
Other values (12) 12
26.1%
ValueCountFrequency (%)
3760 1
 
2.2%
4065 1
 
2.2%
4312 1
 
2.2%
4314 2
4.3%
4316 4
8.7%
4317 2
4.3%
4332 1
 
2.2%
4338 1
 
2.2%
4345 1
 
2.2%
4353 1
 
2.2%
ValueCountFrequency (%)
4422 1
 
2.2%
4420 2
 
4.3%
4419 1
 
2.2%
4410 1
 
2.2%
4400 5
10.9%
4399 1
 
2.2%
4394 1
 
2.2%
4390 10
21.7%
4386 1
 
2.2%
4374 1
 
2.2%

주소1
Text

Distinct25
Distinct (%)54.3%
Missing0
Missing (%)0.0%
Memory size500.0 B
2023-12-13T07:57:23.310475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length21
Mean length18.608696
Min length16

Characters and Unicode

Total characters856
Distinct characters53
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)43.5%

Sample

1st row서울특별시 용산구 녹사평대로 150
2nd row서울특별시 용산구 녹사평대로 150
3rd row서울특별시 용산구 녹사평대로 150
4th row서울특별시 용산구 원효로97길 37
5th row서울특별시 용산구 한강대로 92
ValueCountFrequency (%)
서울특별시 46
25.0%
용산구 44
23.9%
녹사평대로 11
 
6.0%
150 10
 
5.4%
이태원로 7
 
3.8%
224-19 5
 
2.7%
청파로 5
 
2.7%
77 5
 
2.7%
백범로 4
 
2.2%
329 4
 
2.2%
Other values (39) 43
23.4%
2023-12-13T07:57:23.611569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
138
16.1%
서 50
 
5.8%
특 46
 
5.4%
별 46
 
5.4%
시 46
 
5.4%
구 46
 
5.4%
울 46
 
5.4%
로 45
 
5.3%
용 44
 
5.1%
산 44
 
5.1%
Other values (43) 305
35.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 561
65.5%
Decimal Number 149
 
17.4%
Space Separator 138
 
16.1%
Dash Punctuation 8
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 50
 
8.9%
특 46
 
8.2%
별 46
 
8.2%
시 46
 
8.2%
구 46
 
8.2%
울 46
 
8.2%
로 45
 
8.0%
용 44
 
7.8%
산 44
 
7.8%
대 16
 
2.9%
Other values (31) 132
23.5%
Decimal Number
ValueCountFrequency (%)
2 27
18.1%
1 25
16.8%
9 18
12.1%
7 18
12.1%
0 15
10.1%
5 15
10.1%
3 12
8.1%
4 11
7.4%
8 4
 
2.7%
6 4
 
2.7%
Space Separator
ValueCountFrequency (%)
138
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 561
65.5%
Common 295
34.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 50
 
8.9%
특 46
 
8.2%
별 46
 
8.2%
시 46
 
8.2%
구 46
 
8.2%
울 46
 
8.2%
로 45
 
8.0%
용 44
 
7.8%
산 44
 
7.8%
대 16
 
2.9%
Other values (31) 132
23.5%
Common
ValueCountFrequency (%)
138
46.8%
2 27
 
9.2%
1 25
 
8.5%
9 18
 
6.1%
7 18
 
6.1%
0 15
 
5.1%
5 15
 
5.1%
3 12
 
4.1%
4 11
 
3.7%
- 8
 
2.7%
Other values (2) 8
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 561
65.5%
ASCII 295
34.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
138
46.8%
2 27
 
9.2%
1 25
 
8.5%
9 18
 
6.1%
7 18
 
6.1%
0 15
 
5.1%
5 15
 
5.1%
3 12
 
4.1%
4 11
 
3.7%
- 8
 
2.7%
Other values (2) 8
 
2.7%
Hangul
ValueCountFrequency (%)
서 50
 
8.9%
특 46
 
8.2%
별 46
 
8.2%
시 46
 
8.2%
구 46
 
8.2%
울 46
 
8.2%
로 45
 
8.0%
용 44
 
7.8%
산 44
 
7.8%
대 16
 
2.9%
Other values (31) 132
23.5%

주소2
Text

MISSING 

Distinct38
Distinct (%)92.7%
Missing5
Missing (%)10.9%
Memory size500.0 B
2023-12-13T07:57:23.815603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length22
Mean length15.878049
Min length8

Characters and Unicode

Total characters651
Distinct characters118
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)87.8%

Sample

1st row0 (이태원동)
2nd row3층 (청파동3가)
3rd row나래관 201호 (원효로1가)
4th row3층 (한강로3가)
5th row용산아트홀 1,2 강의실B3 (이태원동)
ValueCountFrequency (%)
한남동 10
 
7.9%
3층 9
 
7.1%
이태원동 8
 
6.3%
2층 6
 
4.8%
1층 6
 
4.8%
한강로3가 5
 
4.0%
원효로1가 5
 
4.0%
용산구평생학습관 3
 
2.4%
효창동 3
 
2.4%
강의실 3
 
2.4%
Other values (54) 68
54.0%
2023-12-13T07:57:24.215349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
85
 
13.1%
동 36
 
5.5%
층 27
 
4.1%
) 26
 
4.0%
( 26
 
4.0%
1 19
 
2.9%
원 19
 
2.9%
가 18
 
2.8%
산 17
 
2.6%
관 17
 
2.6%
Other values (108) 361
55.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 434
66.7%
Space Separator 85
 
13.1%
Decimal Number 66
 
10.1%
Close Punctuation 26
 
4.0%
Open Punctuation 26
 
4.0%
Other Punctuation 10
 
1.5%
Dash Punctuation 2
 
0.3%
Uppercase Letter 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 36
 
8.3%
층 27
 
6.2%
원 19
 
4.4%
가 18
 
4.1%
산 17
 
3.9%
관 17
 
3.9%
한 16
 
3.7%
효 15
 
3.5%
용 14
 
3.2%
이 11
 
2.5%
Other values (93) 244
56.2%
Decimal Number
ValueCountFrequency (%)
1 19
28.8%
3 17
25.8%
2 15
22.7%
6 4
 
6.1%
0 4
 
6.1%
7 3
 
4.5%
8 2
 
3.0%
4 1
 
1.5%
5 1
 
1.5%
Space Separator
ValueCountFrequency (%)
85
100.0%
Close Punctuation
ValueCountFrequency (%)
) 26
100.0%
Open Punctuation
ValueCountFrequency (%)
( 26
100.0%
Other Punctuation
ValueCountFrequency (%)
, 10
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 434
66.7%
Common 215
33.0%
Latin 2
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 36
 
8.3%
층 27
 
6.2%
원 19
 
4.4%
가 18
 
4.1%
산 17
 
3.9%
관 17
 
3.9%
한 16
 
3.7%
효 15
 
3.5%
용 14
 
3.2%
이 11
 
2.5%
Other values (93) 244
56.2%
Common
ValueCountFrequency (%)
85
39.5%
) 26
 
12.1%
( 26
 
12.1%
1 19
 
8.8%
3 17
 
7.9%
2 15
 
7.0%
, 10
 
4.7%
6 4
 
1.9%
0 4
 
1.9%
7 3
 
1.4%
Other values (4) 6
 
2.8%
Latin
ValueCountFrequency (%)
B 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 434
66.7%
ASCII 217
33.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
85
39.2%
) 26
 
12.0%
( 26
 
12.0%
1 19
 
8.8%
3 17
 
7.8%
2 15
 
6.9%
, 10
 
4.6%
6 4
 
1.8%
0 4
 
1.8%
7 3
 
1.4%
Other values (5) 8
 
3.7%
Hangul
ValueCountFrequency (%)
동 36
 
8.3%
층 27
 
6.2%
원 19
 
4.4%
가 18
 
4.1%
산 17
 
3.9%
관 17
 
3.9%
한 16
 
3.7%
효 15
 
3.5%
용 14
 
3.2%
이 11
 
2.5%
Other values (93) 244
56.2%

등록일
Date

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size500.0 B
Minimum2017-01-20 13:15:00
Maximum2020-09-21 09:20:00
2023-12-13T07:57:24.597242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:57:24.733152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)

수정일
Date

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size500.0 B
Minimum2017-01-20 13:15:00
Maximum2020-09-21 09:20:00
2023-12-13T07:57:24.857809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:57:24.987243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)

Interactions

2023-12-13T07:57:21.510383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:57:25.070976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
강좌명교육장명우편번호주소1주소2등록일수정일
강좌명1.0001.0001.0001.0001.0001.0001.000
교육장명1.0001.0000.9800.9931.0001.0001.000
우편번호1.0000.9801.0001.0001.0001.0001.000
주소11.0000.9931.0001.0001.0001.0001.000
주소21.0001.0001.0001.0001.0001.0001.000
등록일1.0001.0001.0001.0001.0001.0001.000
수정일1.0001.0001.0001.0001.0001.0001.000

Missing values

2023-12-13T07:57:21.623313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:57:21.743742image/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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강좌명교육장명우편번호주소1주소2등록일수정일
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