Overview

Dataset statistics

Number of variables7
Number of observations200
Missing cells400
Missing cells (%)28.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.7 KiB
Average record size in memory59.7 B

Variable types

Numeric1
Categorical2
Text2
Unsupported2

Dataset

DescriptionSample
Author코난테크놀로지
URLhttps://www.bigdata-telecom.kr/invoke/SOKBP2603/?goodsCode=KNTTWIT2019100000001

Alerts

SITENAME has constant value ""Constant
IDX is highly overall correlated with WRITE_DATEHigh correlation
WRITE_DATE is highly overall correlated with IDXHigh correlation
TITLE has 200 (100.0%) missing valuesMissing
MORPHEME has 200 (100.0%) missing valuesMissing
IDX has unique valuesUnique
URL has unique valuesUnique
TITLE is an unsupported type, check if it needs cleaning or further analysisUnsupported
MORPHEME is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 06:24:53.365462
Analysis finished2023-12-10 06:24:54.756071
Duration1.39 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

IDX
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct200
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean79109300
Minimum79109200
Maximum79109399
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:24:54.980854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum79109200
5-th percentile79109210
Q179109250
median79109300
Q379109349
95-th percentile79109389
Maximum79109399
Range199
Interquartile range (IQR)99.5

Descriptive statistics

Standard deviation57.879185
Coefficient of variation (CV)7.3163566 × 10-7
Kurtosis-1.2
Mean79109300
Median Absolute Deviation (MAD)50
Skewness0
Sum1.582186 × 1010
Variance3350
MonotonicityStrictly increasing
2023-12-10T15:24:55.269533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
79109200 1
 
0.5%
79109338 1
 
0.5%
79109328 1
 
0.5%
79109329 1
 
0.5%
79109330 1
 
0.5%
79109331 1
 
0.5%
79109332 1
 
0.5%
79109333 1
 
0.5%
79109334 1
 
0.5%
79109335 1
 
0.5%
Other values (190) 190
95.0%
ValueCountFrequency (%)
79109200 1
0.5%
79109201 1
0.5%
79109202 1
0.5%
79109203 1
0.5%
79109204 1
0.5%
79109205 1
0.5%
79109206 1
0.5%
79109207 1
0.5%
79109208 1
0.5%
79109209 1
0.5%
ValueCountFrequency (%)
79109399 1
0.5%
79109398 1
0.5%
79109397 1
0.5%
79109396 1
0.5%
79109395 1
0.5%
79109394 1
0.5%
79109393 1
0.5%
79109392 1
0.5%
79109391 1
0.5%
79109390 1
0.5%

SITENAME
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
트위터
200 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
트위터 200
100.0%

Length

2023-12-10T15:24:55.521360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:24:55.705572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
트위터 200
100.0%

WRITE_DATE
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2019-12-27 15:55:02
42 
2019-12-27 15:55:00
31 
2019-12-27 15:55:03
29 
2019-12-27 15:55:01
28 
2019-12-27 15:54:59
24 
Other values (10)
46 

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique6 ?
Unique (%)3.0%

Sample

1st row2019-12-27 15:54:58
2nd row2019-12-27 15:54:56
3rd row2019-12-27 15:54:58
4th row2019-12-27 15:54:58
5th row2019-12-27 15:54:58

Common Values

ValueCountFrequency (%)
2019-12-27 15:55:02 42
21.0%
2019-12-27 15:55:00 31
15.5%
2019-12-27 15:55:03 29
14.5%
2019-12-27 15:55:01 28
14.0%
2019-12-27 15:54:59 24
12.0%
2019-12-27 15:55:04 21
10.5%
2019-12-27 15:54:58 14
 
7.0%
2019-12-27 15:54:56 3
 
1.5%
2019-12-27 15:54:57 2
 
1.0%
2019-12-27 15:54:00 1
 
0.5%
Other values (5) 5
 
2.5%

Length

2023-12-10T15:24:55.871482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2019-12-27 199
49.8%
15:55:02 42
 
10.5%
15:55:00 31
 
7.8%
15:55:03 29
 
7.2%
15:55:01 28
 
7.0%
15:54:59 24
 
6.0%
15:55:04 21
 
5.2%
15:54:58 14
 
3.5%
15:54:56 3
 
0.8%
15:54:57 2
 
0.5%
Other values (7) 7
 
1.8%

URL
Text

UNIQUE 

Distinct200
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-10T15:24:56.351452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length66
Median length65
Mean length59.585
Min length55

Characters and Unicode

Total characters11917
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique200 ?
Unique (%)100.0%

Sample

1st rowhttps://twitter.com/889071471963783168/status/1210454005689667584
2nd rowhttps://twitter.com/451398646/status/1210453997720457217
3rd rowhttps://twitter.com/2287565970/status/1210454003542196229
4th rowhttps://twitter.com/2192038339/status/1210454003835785216
5th rowhttps://twitter.com/108470061/status/1210454006071353344
ValueCountFrequency (%)
https://twitter.com/889071471963783168/status/1210454005689667584 1
 
0.5%
https://twitter.com/2787797761/status/1210454021514752002 1
 
0.5%
https://twitter.com/726441918637309954/status/1210454023368630272 1
 
0.5%
https://twitter.com/1190245301283479552/status/1210454020906553345 1
 
0.5%
https://twitter.com/1082812769408307201/status/1210454022223564800 1
 
0.5%
https://twitter.com/1155423164026912768/status/1210454022781489152 1
 
0.5%
https://twitter.com/1024359694314270720/status/1210454021888102400 1
 
0.5%
https://twitter.com/535404020/status/1210454022777212928 1
 
0.5%
https://twitter.com/145651657/status/1210454022013931521 1
 
0.5%
https://twitter.com/734192915296059393/status/1210454021636407296 1
 
0.5%
Other values (190) 190
95.0%
2023-12-10T15:24:57.055803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 1400
 
11.7%
/ 1000
 
8.4%
1 975
 
8.2%
4 883
 
7.4%
0 883
 
7.4%
2 787
 
6.6%
s 600
 
5.0%
5 581
 
4.9%
8 468
 
3.9%
6 454
 
3.8%
Other values (16) 3886
32.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6317
53.0%
Lowercase Letter 4200
35.2%
Other Punctuation 1400
 
11.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 1400
33.3%
s 600
14.3%
u 200
 
4.8%
a 200
 
4.8%
h 200
 
4.8%
o 200
 
4.8%
c 200
 
4.8%
r 200
 
4.8%
e 200
 
4.8%
i 200
 
4.8%
Other values (3) 600
14.3%
Decimal Number
ValueCountFrequency (%)
1 975
15.4%
4 883
14.0%
0 883
14.0%
2 787
12.5%
5 581
9.2%
8 468
7.4%
6 454
7.2%
9 453
7.2%
3 424
6.7%
7 409
6.5%
Other Punctuation
ValueCountFrequency (%)
/ 1000
71.4%
. 200
 
14.3%
: 200
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Common 7717
64.8%
Latin 4200
35.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 1400
33.3%
s 600
14.3%
u 200
 
4.8%
a 200
 
4.8%
h 200
 
4.8%
o 200
 
4.8%
c 200
 
4.8%
r 200
 
4.8%
e 200
 
4.8%
i 200
 
4.8%
Other values (3) 600
14.3%
Common
ValueCountFrequency (%)
/ 1000
13.0%
1 975
12.6%
4 883
11.4%
0 883
11.4%
2 787
10.2%
5 581
7.5%
8 468
6.1%
6 454
5.9%
9 453
5.9%
3 424
5.5%
Other values (3) 809
10.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11917
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 1400
 
11.7%
/ 1000
 
8.4%
1 975
 
8.2%
4 883
 
7.4%
0 883
 
7.4%
2 787
 
6.6%
s 600
 
5.0%
5 581
 
4.9%
8 468
 
3.9%
6 454
 
3.8%
Other values (16) 3886
32.6%

TITLE
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing200
Missing (%)100.0%
Memory size1.9 KiB

BODY
Text

Distinct194
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-10T15:24:57.452375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length144
Median length113
Mean length87.72
Min length3

Characters and Unicode

Total characters17544
Distinct characters976
Distinct categories16 ?
Distinct scripts10 ?
Distinct blocks21 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique189 ?
Unique (%)94.5%

Sample

1st rowRT @kdohobh: 백호 강동호 작사작곡 강동호 프로듀싱 강동호 메인보컬 #강동호 #백호 https://t.co/HBfDy2kLWY
2nd rowRT @jangjo3016: 진중권 진짜 커밍아웃??? 뭐냐? 왤까??? 최성해에 보은 차원에서 입질하다가 유시민과 진짜 시민들에게 개욕을 쳐먹더니 제대로 꼴보로 줄을 갈아탄건가?? 아직도 정의당 당원이라네~ 뭐냐?? 노회찬 의원의 부재가 너무나…
3rd rowRT @Korseries: ต้นสังกัดเผยภาพถ่ายแบบเซ็ตแรกของ คิมอูบิน หลังจากที่เขาห่างหายจากวงการบันเทิงยาวนานกว่า 2 ปี ดีงามมากกก❤️�� #KimWooBin #김우빈…
4th row운동 인증서 (실패) 중국어 진정령스페셜 뭐하나 한게없군
5th rowRT @forsungwoon_: Sungwoon updated his instagram!! #하성운 #hasungwoon ������⛄️ is he recording for something? why is he wearing his in ears?…
ValueCountFrequency (%)
rt 143
 
4.6%
23
 
0.7%
수 10
 
0.3%
안 9
 
0.3%
다 8
 
0.3%
왜 7
 
0.2%
냥 7
 
0.2%
가요대전 6
 
0.2%
있는 6
 
0.2%
제대로 6
 
0.2%
Other values (2388) 2864
92.7%
2023-12-10T15:24:58.147166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3081
 
17.6%
t 445
 
2.5%
. 383
 
2.2%
/ 326
 
1.9%
: 277
 
1.6%
o 275
 
1.6%
s 242
 
1.4%
이 231
 
1.3%
a 216
 
1.2%
h 207
 
1.2%
Other values (966) 11861
67.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7417
42.3%
Lowercase Letter 3283
18.7%
Space Separator 3085
17.6%
Other Punctuation 1540
 
8.8%
Uppercase Letter 1284
 
7.3%
Decimal Number 584
 
3.3%
Other Symbol 125
 
0.7%
Connector Punctuation 83
 
0.5%
Open Punctuation 35
 
0.2%
Close Punctuation 35
 
0.2%
Other values (6) 73
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 231
 
3.1%
는 159
 
2.1%
다 150
 
2.0%
하 124
 
1.7%
고 120
 
1.6%
가 119
 
1.6%
에 105
 
1.4%
아 100
 
1.3%
ㅋ 89
 
1.2%
지 87
 
1.2%
Other values (831) 6133
82.7%
Lowercase Letter
ValueCountFrequency (%)
t 445
13.6%
o 275
 
8.4%
s 242
 
7.4%
a 216
 
6.6%
h 207
 
6.3%
e 200
 
6.1%
n 193
 
5.9%
c 189
 
5.8%
i 182
 
5.5%
p 158
 
4.8%
Other values (17) 976
29.7%
Uppercase Letter
ValueCountFrequency (%)
T 204
15.9%
R 188
14.6%
N 73
 
5.7%
E 59
 
4.6%
S 54
 
4.2%
A 52
 
4.0%
O 52
 
4.0%
I 50
 
3.9%
C 47
 
3.7%
K 44
 
3.4%
Other values (16) 461
35.9%
Other Punctuation
ValueCountFrequency (%)
. 383
24.9%
/ 326
21.2%
: 277
18.0%
@ 171
11.1%
# 144
 
9.4%
? 75
 
4.9%
… 56
 
3.6%
! 50
 
3.2%
' 24
 
1.6%
" 21
 
1.4%
Other values (8) 13
 
0.8%
Other Symbol
ValueCountFrequency (%)
� 96
76.8%
❤ 5
 
4.0%
★ 4
 
3.2%
▼ 2
 
1.6%
♡ 2
 
1.6%
△ 2
 
1.6%
꒦ 2
 
1.6%
⛄ 2
 
1.6%
➫ 1
 
0.8%
⏰ 1
 
0.8%
Other values (8) 8
 
6.4%
Nonspacing Mark
ValueCountFrequency (%)
️ 8
24.2%
่ 5
15.2%
ิ 4
12.1%
ั 4
12.1%
ี 4
12.1%
้ 2
 
6.1%
ู 1
 
3.0%
็ 1
 
3.0%
ີ 1
 
3.0%
̮ 1
 
3.0%
Other values (2) 2
 
6.1%
Decimal Number
ValueCountFrequency (%)
1 109
18.7%
2 98
16.8%
0 74
12.7%
7 55
9.4%
5 47
8.0%
8 46
7.9%
3 45
7.7%
9 43
 
7.4%
6 34
 
5.8%
4 33
 
5.7%
Math Symbol
ValueCountFrequency (%)
~ 12
50.0%
< 5
20.8%
+ 3
 
12.5%
> 2
 
8.3%
| 1
 
4.2%
↑ 1
 
4.2%
Open Punctuation
ValueCountFrequency (%)
( 26
74.3%
[ 7
 
20.0%
「 1
 
2.9%
『 1
 
2.9%
Close Punctuation
ValueCountFrequency (%)
) 26
74.3%
] 7
 
20.0%
」 1
 
2.9%
』 1
 
2.9%
Space Separator
ValueCountFrequency (%)
3081
99.9%
  4
 
0.1%
Modifier Symbol
ValueCountFrequency (%)
^ 6
85.7%
˙ 1
 
14.3%
Initial Punctuation
ValueCountFrequency (%)
“ 3
75.0%
‘ 1
 
25.0%
Final Punctuation
ValueCountFrequency (%)
” 3
75.0%
’ 1
 
25.0%
Connector Punctuation
ValueCountFrequency (%)
_ 83
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7256
41.4%
Common 5525
31.5%
Latin 4568
26.0%
Thai 119
 
0.7%
Han 47
 
0.3%
Katakana 12
 
0.1%
Inherited 10
 
0.1%
Hiragana 3
 
< 0.1%
Yi 2
 
< 0.1%
Lao 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 231
 
3.2%
는 159
 
2.2%
다 150
 
2.1%
하 124
 
1.7%
고 120
 
1.7%
가 119
 
1.6%
에 105
 
1.4%
아 100
 
1.4%
ㅋ 89
 
1.2%
지 87
 
1.2%
Other values (756) 5972
82.3%
Common
ValueCountFrequency (%)
3081
55.8%
. 383
 
6.9%
/ 326
 
5.9%
: 277
 
5.0%
@ 171
 
3.1%
# 144
 
2.6%
1 109
 
2.0%
2 98
 
1.8%
� 96
 
1.7%
_ 83
 
1.5%
Other values (59) 757
 
13.7%
Latin
ValueCountFrequency (%)
t 445
 
9.7%
o 275
 
6.0%
s 242
 
5.3%
a 216
 
4.7%
h 207
 
4.5%
T 204
 
4.5%
e 200
 
4.4%
n 193
 
4.2%
c 189
 
4.1%
R 188
 
4.1%
Other values (44) 2209
48.4%
Thai
ValueCountFrequency (%)
า 13
 
10.9%
ง 9
 
7.6%
ก 9
 
7.6%
น 6
 
5.0%
ว 6
 
5.0%
ย 5
 
4.2%
่ 5
 
4.2%
เ 5
 
4.2%
อ 4
 
3.4%
บ 4
 
3.4%
Other values (25) 53
44.5%
Han
ValueCountFrequency (%)
神 6
 
12.8%
威 3
 
6.4%
起 3
 
6.4%
方 3
 
6.4%
東 3
 
6.4%
通 1
 
2.1%
吧 1
 
2.1%
金 1
 
2.1%
俊 1
 
2.1%
勉 1
 
2.1%
Other values (24) 24
51.1%
Katakana
ValueCountFrequency (%)
ィ 2
16.7%
ウ 2
16.7%
ン 2
16.7%
ホ 1
8.3%
ス 1
8.3%
ジ 1
8.3%
ネ 1
8.3%
ュ 1
8.3%
ッ 1
8.3%
Inherited
ValueCountFrequency (%)
️ 8
80.0%
̮ 1
 
10.0%
̫ 1
 
10.0%
Hiragana
ValueCountFrequency (%)
い 1
33.3%
が 1
33.3%
の 1
33.3%
Lao
ValueCountFrequency (%)
ີ 1
50.0%
ິ 1
50.0%
Yi
ValueCountFrequency (%)
꒦ 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9885
56.3%
Hangul 7106
40.5%
Compat Jamo 150
 
0.9%
Thai 119
 
0.7%
Specials 96
 
0.5%
Punctuation 68
 
0.4%
CJK 47
 
0.3%
None 15
 
0.1%
Katakana 12
 
0.1%
VS 8
 
< 0.1%
Other values (11) 38
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3081
31.2%
t 445
 
4.5%
. 383
 
3.9%
/ 326
 
3.3%
: 277
 
2.8%
o 275
 
2.8%
s 242
 
2.4%
a 216
 
2.2%
h 207
 
2.1%
T 204
 
2.1%
Other values (76) 4229
42.8%
Hangul
ValueCountFrequency (%)
이 231
 
3.3%
는 159
 
2.2%
다 150
 
2.1%
하 124
 
1.7%
고 120
 
1.7%
가 119
 
1.7%
에 105
 
1.5%
아 100
 
1.4%
지 87
 
1.2%
한 86
 
1.2%
Other values (736) 5825
82.0%
Specials
ValueCountFrequency (%)
� 96
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅋ 89
59.3%
ㅠ 9
 
6.0%
ㄱ 8
 
5.3%
ㅡ 6
 
4.0%
ㅣ 5
 
3.3%
ㅇ 4
 
2.7%
ㄷ 4
 
2.7%
ㅜ 4
 
2.7%
ㅏ 3
 
2.0%
ㄴ 3
 
2.0%
Other values (10) 15
 
10.0%
Punctuation
ValueCountFrequency (%)
… 56
82.4%
• 3
 
4.4%
“ 3
 
4.4%
” 3
 
4.4%
’ 1
 
1.5%
‘ 1
 
1.5%
※ 1
 
1.5%
Thai
ValueCountFrequency (%)
า 13
 
10.9%
ง 9
 
7.6%
ก 9
 
7.6%
น 6
 
5.0%
ว 6
 
5.0%
ย 5
 
4.2%
่ 5
 
4.2%
เ 5
 
4.2%
อ 4
 
3.4%
บ 4
 
3.4%
Other values (25) 53
44.5%
VS
ValueCountFrequency (%)
️ 8
100.0%
CJK
ValueCountFrequency (%)
神 6
 
12.8%
威 3
 
6.4%
起 3
 
6.4%
方 3
 
6.4%
東 3
 
6.4%
通 1
 
2.1%
吧 1
 
2.1%
金 1
 
2.1%
俊 1
 
2.1%
勉 1
 
2.1%
Other values (24) 24
51.1%
Dingbats
ValueCountFrequency (%)
❤ 5
62.5%
➫ 1
 
12.5%
✨ 1
 
12.5%
➡ 1
 
12.5%
None
ValueCountFrequency (%)
  4
26.7%
＂ 2
13.3%
」 1
 
6.7%
「 1
 
6.7%
ª 1
 
6.7%
』 1
 
6.7%
『 1
 
6.7%
！ 1
 
6.7%
í 1
 
6.7%
， 1
 
6.7%
Misc Symbols
ValueCountFrequency (%)
★ 4
50.0%
♡ 2
25.0%
⛄ 2
25.0%
Geometric Shapes
ValueCountFrequency (%)
▼ 2
28.6%
△ 2
28.6%
□ 1
14.3%
◇ 1
14.3%
▦ 1
14.3%
Yi Radicals
ValueCountFrequency (%)
꒦ 2
100.0%
Katakana
ValueCountFrequency (%)
ィ 2
16.7%
ウ 2
16.7%
ン 2
16.7%
ホ 1
8.3%
ス 1
8.3%
ジ 1
8.3%
ネ 1
8.3%
ュ 1
8.3%
ッ 1
8.3%
Misc Technical
ValueCountFrequency (%)
⏰ 1
100.0%
Block Elements
ValueCountFrequency (%)
▒ 1
100.0%
Arrows
ValueCountFrequency (%)
↑ 1
33.3%
↖ 1
33.3%
↗ 1
33.3%
Hiragana
ValueCountFrequency (%)
い 1
33.3%
が 1
33.3%
の 1
33.3%
Lao
ValueCountFrequency (%)
ີ 1
50.0%
ິ 1
50.0%
Diacriticals
ValueCountFrequency (%)
̮ 1
50.0%
̫ 1
50.0%
Modifier Letters
ValueCountFrequency (%)
˙ 1
100.0%

MORPHEME
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing200
Missing (%)100.0%
Memory size1.9 KiB

Interactions

2023-12-10T15:24:54.208245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T15:24:58.300330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
IDXWRITE_DATE
IDX1.0000.904
WRITE_DATE0.9041.000
2023-12-10T15:24:58.452889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
IDXWRITE_DATE
IDX1.0000.615
WRITE_DATE0.6151.000

Missing values

2023-12-10T15:24:54.502861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T15:24:54.688684image/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

IDXSITENAMEWRITE_DATEURLTITLEBODYMORPHEME
079109200트위터2019-12-27 15:54:58https://twitter.com/889071471963783168/status/1210454005689667584<NA>RT @kdohobh: 백호 강동호 작사작곡 강동호 프로듀싱 강동호 메인보컬 #강동호 #백호 https://t.co/HBfDy2kLWY<NA>
179109201트위터2019-12-27 15:54:56https://twitter.com/451398646/status/1210453997720457217<NA>RT @jangjo3016: 진중권 진짜 커밍아웃??? 뭐냐? 왤까??? 최성해에 보은 차원에서 입질하다가 유시민과 진짜 시민들에게 개욕을 쳐먹더니 제대로 꼴보로 줄을 갈아탄건가?? 아직도 정의당 당원이라네~ 뭐냐?? 노회찬 의원의 부재가 너무나…<NA>
279109202트위터2019-12-27 15:54:58https://twitter.com/2287565970/status/1210454003542196229<NA>RT @Korseries: ต้นสังกัดเผยภาพถ่ายแบบเซ็ตแรกของ คิมอูบิน หลังจากที่เขาห่างหายจากวงการบันเทิงยาวนานกว่า 2 ปี ดีงามมากกก❤️�� #KimWooBin #김우빈…<NA>
379109203트위터2019-12-27 15:54:58https://twitter.com/2192038339/status/1210454003835785216<NA>운동 인증서 (실패) 중국어 진정령스페셜 뭐하나 한게없군<NA>
479109204트위터2019-12-27 15:54:58https://twitter.com/108470061/status/1210454006071353344<NA>RT @forsungwoon_: Sungwoon updated his instagram!! #하성운 #hasungwoon ������⛄️ is he recording for something? why is he wearing his in ears?…<NA>
579109205트위터2019-12-27 15:54:00https://twitter.com/922421498769371137/status/1210453762088689664<NA>Sungwoon updated his instagram!! #하성운 #hasungwoon ������⛄️ is he recording for something? why is he wearing his in… https://t.co/X4gQK0cwAt<NA>
679109206트위터2019-12-27 15:54:58https://twitter.com/837968480/status/1210454006125883392<NA>RT @Sniper_1028: 191227 #董思成 #윈윈 #winwin #ウィンウィン #WayV #WeiShenV #威神V https://t.co/IiNKI1AKhf<NA>
779109207트위터2019-12-27 15:54:56https://twitter.com/775677150196137984/status/1210453997489778689<NA>RT @bibibic_tt: 유해하고 가학적인 내용 무비판적으로 연성하는 것도 문제라면 문제인데 그게 유해하고 가학적인걸 빤히 알면서도 아무런 트리거 처리나 가리는 것 없이 캡쳐해서 알티돌리는거 존나 무슨심보인지모르겠음 야 저새끼 총들고있다 하면서…<NA>
879109208트위터2019-12-27 15:54:58https://twitter.com/2179620715/status/1210454006289457152<NA>RT @yomi_UR: 모두 편안한 연말 보내시기 바랍니다:) https://t.co/cfWssZQYGc<NA>
979109209트위터2019-12-27 15:54:59https://twitter.com/1113570986/status/1210454006834708481<NA>왜 그렇게 낑낑대고 있어요. 개목걸이가 답답해요? 하지만 어쩔 수 없죠. 산책 나갈때는 개목걸이를 채우는게 매너인걸요. 마음 같아서는 저도 자유롭게 키우고 싶지만 그래서야 버릇없는 펫인 당신이 멋대로 날뛸 거 아녜요. 그럼 별 수 없이 매를 들어야겠죠<NA>
IDXSITENAMEWRITE_DATEURLTITLEBODYMORPHEME
19079109390트위터2019-12-27 15:55:04https://twitter.com/726441918637309954/status/1210454029236498437<NA>RT @chy6085: @misangeos 그래서 내일 뭐 먹죠? 모여요?����<NA>
19179109391트위터2019-12-27 15:55:04https://twitter.com/824702024/status/1210454028670259205<NA>RT @taobao_beignet: 털찐참새+둥지인형 사이즈 3가지 https://t.co/JZA8eOJy2v<NA>
19279109392트위터2019-12-27 15:55:04https://twitter.com/703431530589196288/status/1210454028900954112<NA>RT @suntreewater: 윤석열이 언론사 사주를 만나고 다니더니 언플이 장난아니네 언론이 이번 판결이 잘못됬다고 몰아가고 있는데 우리도 대책을 세워야할듯 다음 실검에 대항할 실검이 시급합니다<NA>
19379109393트위터2019-12-27 15:55:04https://twitter.com/4168994539/status/1210454029320388610<NA>RT @Fromaple_1: 혜원이주려고 만든 만화그릴때 쓰는 폰트정리 상업적이용 불가인 폰트도있으니까 커뮤로그그릴때.. 아아.. 무슨폰트를 써야하지? 하고 고민에 잠겨계시던 분들은.. 참고하세요.. https://t.co/7fhQanuGU2<NA>
19479109394트위터2019-12-27 15:55:04https://twitter.com/998909644855693312/status/1210454029521678337<NA>RT @gakayanolja: 죄질 나쁘다는 주장은 검찰놈들이 영장청구하면 언론 플레이 한것. 구속 사유가 되거나 말거나 상관도 없음. 조국장관님 나쁜놈 만들기 대작전. 검찰이나 언론이나 개쓰레기 집단.<NA>
19579109395트위터2019-12-27 15:55:04https://twitter.com/294980022/status/1210454028410187777<NA>넘나 조쿠요 �� https://t.co/Vnc1nJUNE9<NA>
19679109396트위터2019-12-27 15:55:04https://twitter.com/2296782415/status/1210454029291028481<NA>오늘 확인된 택배분실건 비용이 제법 커서 물어주는 기사님도 속상하실것같아 어쨌든 비용 처리되는대로 연락주세요~하고 유하게 넘겼더니 갑자기 내가 운송장을 잘못뽑았던것같다느니 제대로 안붙인것같다고 태세전환하더라… https://t.co/RzuZErvceF<NA>
19779109397트위터2019-12-27 15:55:04https://twitter.com/1174166245400170496/status/1210454029823643648<NA>RT @insight_co_kr: '미친 슈트핏'으로 'SBS 가요대전'을 런웨이로 바꿔버린 방탄 진 #방탄소년단 #방탄 #진 #BTS #가요대전 https://t.co/5iAbOLdCap<NA>
19879109398트위터2019-12-27 15:55:04https://twitter.com/2412444637/status/1210454030163382273<NA>RT @MacJohnathan: 트위터 신기능을 써 보았다 톰 후퍼 너만 사활 건 줄 아냐? https://t.co/FATylkHcn8<NA>
19979109399트위터2019-12-27 15:55:04https://twitter.com/1027599408/status/1210454030738059264<NA>[할복 무사가 아니라 하츠라고 했다!]<NA>