Overview

Dataset statistics

Number of variables6
Number of observations10000
Missing cells9564
Missing cells (%)15.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory556.6 KiB
Average record size in memory57.0 B

Variable types

Numeric1
Categorical1
Text3
DateTime1

Dataset

Description국립국어원 공공언어 개선 지원(구 공공언어 통합 지원)의 공공용어 번역 정보 목록입니다.공공용어 번역 정보에서는 국립국어원의 번역 감수를 거친 표준 번역안과 서울특별시, 한국관광공사, 국토지리정보원 등에서 제공한 공공용어 번역 정보를 함께 제공하고 있습니다.공공용어에 대한 영어, 일본어, 중국어로의 번역 정보를 제공합니다.
Author문화체육관광부 국립국어원
URLhttps://www.data.go.kr/data/15123639/fileData.do

Alerts

연번 is highly overall correlated with 언어구분High correlation
언어구분 is highly overall correlated with 연번High correlation
로마자 표기 has 9564 (95.6%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 19:33:11.866936
Analysis finished2023-12-12 19:33:15.174103
Duration3.31 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47661.162
Minimum7
Maximum95756
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T04:33:15.276899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile4803.85
Q123671.25
median47597.5
Q371446.25
95-th percentile91088.2
Maximum95756
Range95749
Interquartile range (IQR)47775

Descriptive statistics

Standard deviation27653.196
Coefficient of variation (CV)0.58020398
Kurtosis-1.1950228
Mean47661.162
Median Absolute Deviation (MAD)23893
Skewness0.011676633
Sum4.7661162 × 108
Variance7.6469923 × 108
MonotonicityNot monotonic
2023-12-13T04:33:15.511910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34917 1
 
< 0.1%
74894 1
 
< 0.1%
13066 1
 
< 0.1%
33410 1
 
< 0.1%
70474 1
 
< 0.1%
36603 1
 
< 0.1%
4703 1
 
< 0.1%
28625 1
 
< 0.1%
1665 1
 
< 0.1%
31374 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
7 1
< 0.1%
13 1
< 0.1%
24 1
< 0.1%
42 1
< 0.1%
44 1
< 0.1%
51 1
< 0.1%
53 1
< 0.1%
58 1
< 0.1%
60 1
< 0.1%
64 1
< 0.1%
ValueCountFrequency (%)
95756 1
< 0.1%
95732 1
< 0.1%
95730 1
< 0.1%
95716 1
< 0.1%
95675 1
< 0.1%
95674 1
< 0.1%
95670 1
< 0.1%
95669 1
< 0.1%
95668 1
< 0.1%
95666 1
< 0.1%

언어구분
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
ENG
5149 
CHA
2458 
JPN
2393 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowENG
2nd rowENG
3rd rowJPN
4th rowCHA
5th rowENG

Common Values

ValueCountFrequency (%)
ENG 5149
51.5%
CHA 2458
24.6%
JPN 2393
23.9%

Length

2023-12-13T04:33:15.688538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:33:15.847304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
eng 5149
51.5%
cha 2458
24.6%
jpn 2393
23.9%

한글용어
Text

Distinct9191
Distinct (%)91.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T04:33:16.218456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length21
Mean length5.6188
Min length1

Characters and Unicode

Total characters56188
Distinct characters766
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8410 ?
Unique (%)84.1%

Sample

1st row한천로94길
2nd row(돼지)머릿고기
3rd row중앙로39길
4th row파로호
5th row어로리
ValueCountFrequency (%)
주민센터 204
 
2.0%
입구 6
 
0.1%
아현3동 4
 
< 0.1%
우체국 4
 
< 0.1%
양지15길 3
 
< 0.1%
신사2동 3
 
< 0.1%
나가는 3
 
< 0.1%
연희2동 3
 
< 0.1%
봉천6동 3
 
< 0.1%
신월1동 3
 
< 0.1%
Other values (9266) 10150
97.7%
2023-12-13T04:33:16.733879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
길 4440
 
7.9%
로 4300
 
7.7%
1 2024
 
3.6%
동 1534
 
2.7%
2 1400
 
2.5%
리 1150
 
2.0%
3 1035
 
1.8%
4 840
 
1.5%
대 774
 
1.4%
가 766
 
1.4%
Other values (756) 37925
67.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 46657
83.0%
Decimal Number 8767
 
15.6%
Space Separator 394
 
0.7%
Close Punctuation 127
 
0.2%
Open Punctuation 126
 
0.2%
Uppercase Letter 63
 
0.1%
Other Punctuation 41
 
0.1%
Lowercase Letter 10
 
< 0.1%
Math Symbol 2
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
길 4440
 
9.5%
로 4300
 
9.2%
동 1534
 
3.3%
리 1150
 
2.5%
대 774
 
1.7%
가 766
 
1.6%
산 761
 
1.6%
터 530
 
1.1%
원 493
 
1.1%
센 483
 
1.0%
Other values (699) 31426
67.4%
Uppercase Letter
ValueCountFrequency (%)
C 11
17.5%
O 6
 
9.5%
L 6
 
9.5%
A 5
 
7.9%
M 4
 
6.3%
J 4
 
6.3%
I 3
 
4.8%
S 3
 
4.8%
T 2
 
3.2%
H 2
 
3.2%
Other values (11) 17
27.0%
Decimal Number
ValueCountFrequency (%)
1 2024
23.1%
2 1400
16.0%
3 1035
11.8%
4 840
9.6%
5 752
 
8.6%
6 661
 
7.5%
7 552
 
6.3%
9 516
 
5.9%
8 495
 
5.6%
0 492
 
5.6%
Other Punctuation
ValueCountFrequency (%)
, 13
31.7%
. 13
31.7%
& 5
 
12.2%
/ 3
 
7.3%
' 2
 
4.9%
· 2
 
4.9%
･ 1
 
2.4%
・ 1
 
2.4%
• 1
 
2.4%
Lowercase Letter
ValueCountFrequency (%)
t 2
20.0%
a 2
20.0%
m 1
10.0%
b 1
10.0%
s 1
10.0%
w 1
10.0%
e 1
10.0%
r 1
10.0%
Space Separator
ValueCountFrequency (%)
387
98.2%
  7
 
1.8%
Close Punctuation
ValueCountFrequency (%)
) 126
99.2%
] 1
 
0.8%
Open Punctuation
ValueCountFrequency (%)
( 125
99.2%
[ 1
 
0.8%
Math Symbol
ValueCountFrequency (%)
+ 1
50.0%
~ 1
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 46657
83.0%
Common 9458
 
16.8%
Latin 73
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
길 4440
 
9.5%
로 4300
 
9.2%
동 1534
 
3.3%
리 1150
 
2.5%
대 774
 
1.7%
가 766
 
1.6%
산 761
 
1.6%
터 530
 
1.1%
원 493
 
1.1%
센 483
 
1.0%
Other values (699) 31426
67.4%
Latin
ValueCountFrequency (%)
C 11
15.1%
O 6
 
8.2%
L 6
 
8.2%
A 5
 
6.8%
M 4
 
5.5%
J 4
 
5.5%
I 3
 
4.1%
S 3
 
4.1%
T 2
 
2.7%
t 2
 
2.7%
Other values (19) 27
37.0%
Common
ValueCountFrequency (%)
1 2024
21.4%
2 1400
14.8%
3 1035
10.9%
4 840
8.9%
5 752
 
8.0%
6 661
 
7.0%
7 552
 
5.8%
9 516
 
5.5%
8 495
 
5.2%
0 492
 
5.2%
Other values (18) 691
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 46656
83.0%
ASCII 9519
 
16.9%
None 10
 
< 0.1%
Compat Jamo 1
 
< 0.1%
Katakana 1
 
< 0.1%
Punctuation 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
길 4440
 
9.5%
로 4300
 
9.2%
동 1534
 
3.3%
리 1150
 
2.5%
대 774
 
1.7%
가 766
 
1.6%
산 761
 
1.6%
터 530
 
1.1%
원 493
 
1.1%
센 483
 
1.0%
Other values (698) 31425
67.4%
ASCII
ValueCountFrequency (%)
1 2024
21.3%
2 1400
14.7%
3 1035
10.9%
4 840
8.8%
5 752
 
7.9%
6 661
 
6.9%
7 552
 
5.8%
9 516
 
5.4%
8 495
 
5.2%
0 492
 
5.2%
Other values (42) 752
 
7.9%
None
ValueCountFrequency (%)
  7
70.0%
· 2
 
20.0%
･ 1
 
10.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%
Katakana
ValueCountFrequency (%)
・ 1
100.0%
Punctuation
ValueCountFrequency (%)
• 1
100.0%

번역어
Text

Distinct9965
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T04:33:17.069291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length92
Median length67
Mean length13.5153
Min length1

Characters and Unicode

Total characters135153
Distinct characters1697
Distinct categories16 ?
Distinct scripts6 ?
Distinct blocks10 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9932 ?
Unique (%)99.3%

Sample

1st rowHancheon-ro 94-gil
2nd rowPork Head Meat
3rd rowチュンアンロ39ギル
4th row破虏湖
5th rowEoro-ri
ValueCountFrequency (%)
center 145
 
0.9%
of 114
 
0.7%
office 105
 
0.6%
and 97
 
0.6%
police 88
 
0.5%
park 83
 
0.5%
division 82
 
0.5%
service 81
 
0.5%
mountain 81
 
0.5%
75
 
0.5%
Other values (9537) 15571
94.2%
2023-12-13T04:33:17.628078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 8260
 
6.1%
n 7624
 
5.6%
a 6756
 
5.0%
e 6608
 
4.9%
6525
 
4.8%
g 6033
 
4.5%
i 6005
 
4.4%
r 4860
 
3.6%
- 4519
 
3.3%
l 3616
 
2.7%
Other values (1687) 74347
55.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 70969
52.5%
Other Letter 33484
24.8%
Decimal Number 9066
 
6.7%
Uppercase Letter 8275
 
6.1%
Space Separator 6529
 
4.8%
Dash Punctuation 4522
 
3.3%
Other Punctuation 714
 
0.5%
Open Punctuation 698
 
0.5%
Close Punctuation 698
 
0.5%
Modifier Letter 183
 
0.1%
Other values (6) 15
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
ン 2830
 
8.5%
ル 1758
 
5.3%
ギ 1504
 
4.5%
街 1494
 
4.5%
路 1442
 
4.3%
ロ 1394
 
4.2%
洞 745
 
2.2%
ョ 512
 
1.5%
チ 452
 
1.3%
中 414
 
1.2%
Other values (1593) 20939
62.5%
Lowercase Letter
ValueCountFrequency (%)
o 8260
11.6%
n 7624
10.7%
a 6756
9.5%
e 6608
9.3%
g 6033
 
8.5%
i 6005
 
8.5%
r 4860
 
6.8%
l 3616
 
5.1%
u 2675
 
3.8%
s 2548
 
3.6%
Other values (16) 15984
22.5%
Uppercase Letter
ValueCountFrequency (%)
S 1280
15.5%
D 664
 
8.0%
C 660
 
8.0%
G 603
 
7.3%
M 591
 
7.1%
P 564
 
6.8%
B 538
 
6.5%
H 472
 
5.7%
J 389
 
4.7%
N 284
 
3.4%
Other values (16) 2230
26.9%
Decimal Number
ValueCountFrequency (%)
1 2116
23.3%
2 1487
16.4%
3 1085
12.0%
4 868
9.6%
5 776
 
8.6%
6 671
 
7.4%
7 557
 
6.1%
9 515
 
5.7%
8 496
 
5.5%
0 490
 
5.4%
Other values (2) 5
 
0.1%
Other Punctuation
ValueCountFrequency (%)
/ 538
75.4%
& 52
 
7.3%
. 31
 
4.3%
, 27
 
3.8%
' 23
 
3.2%
* 16
 
2.2%
・ 13
 
1.8%
、 9
 
1.3%
＆ 3
 
0.4%
· 1
 
0.1%
Space Separator
ValueCountFrequency (%)
6525
99.9%
　 2
 
< 0.1%
  2
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 4519
99.9%
– 2
 
< 0.1%
― 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 655
93.8%
（ 43
 
6.2%
Close Punctuation
ValueCountFrequency (%)
) 654
93.7%
） 44
 
6.3%
Letter Number
ValueCountFrequency (%)
Ⅱ 4
80.0%
Ⅰ 1
 
20.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
50.0%
” 1
50.0%
Modifier Letter
ValueCountFrequency (%)
ー 183
100.0%
Other Symbol
ValueCountFrequency (%)
� 5
100.0%
Initial Punctuation
ValueCountFrequency (%)
“ 1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 79249
58.6%
Common 22420
 
16.6%
Han 17476
 
12.9%
Katakana 15797
 
11.7%
Hiragana 210
 
0.2%
Hangul 1
 
< 0.1%

Most frequent character per script

Han
ValueCountFrequency (%)
街 1494
 
8.5%
路 1442
 
8.3%
洞 745
 
4.3%
中 414
 
2.4%
山 303
 
1.7%
心 297
 
1.7%
民 296
 
1.7%
大 254
 
1.5%
安 196
 
1.1%
居 178
 
1.0%
Other values (1464) 11857
67.8%
Katakana
ValueCountFrequency (%)
ン 2830
17.9%
ル 1758
 
11.1%
ギ 1504
 
9.5%
ロ 1394
 
8.8%
ョ 512
 
3.2%
チ 452
 
2.9%
ク 406
 
2.6%
ム 363
 
2.3%
サ 332
 
2.1%
ド 331
 
2.1%
Other values (66) 5915
37.4%
Latin
ValueCountFrequency (%)
o 8260
 
10.4%
n 7624
 
9.6%
a 6756
 
8.5%
e 6608
 
8.3%
g 6033
 
7.6%
i 6005
 
7.6%
r 4860
 
6.1%
l 3616
 
4.6%
u 2675
 
3.4%
s 2548
 
3.2%
Other values (44) 24264
30.6%
Hiragana
ValueCountFrequency (%)
の 53
25.2%
り 16
 
7.6%
し 14
 
6.7%
き 12
 
5.7%
め 11
 
5.2%
も 7
 
3.3%
け 7
 
3.3%
え 7
 
3.3%
ご 6
 
2.9%
い 5
 
2.4%
Other values (42) 72
34.3%
Common
ValueCountFrequency (%)
6525
29.1%
- 4519
20.2%
1 2116
 
9.4%
2 1487
 
6.6%
3 1085
 
4.8%
4 868
 
3.9%
5 776
 
3.5%
6 671
 
3.0%
( 655
 
2.9%
) 654
 
2.9%
Other values (30) 3064
13.7%
Hangul
ValueCountFrequency (%)
ㆍ 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 101347
75.0%
CJK 17451
 
12.9%
Katakana 15993
 
11.8%
Hiragana 210
 
0.2%
None 110
 
0.1%
CJK Compat Ideographs 25
 
< 0.1%
Punctuation 6
 
< 0.1%
Specials 5
 
< 0.1%
Number Forms 5
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 8260
 
8.2%
n 7624
 
7.5%
a 6756
 
6.7%
e 6608
 
6.5%
6525
 
6.4%
g 6033
 
6.0%
i 6005
 
5.9%
r 4860
 
4.8%
- 4519
 
4.5%
l 3616
 
3.6%
Other values (64) 40541
40.0%
Katakana
ValueCountFrequency (%)
ン 2830
17.7%
ル 1758
 
11.0%
ギ 1504
 
9.4%
ロ 1394
 
8.7%
ョ 512
 
3.2%
チ 452
 
2.8%
ク 406
 
2.5%
ム 363
 
2.3%
サ 332
 
2.1%
ド 331
 
2.1%
Other values (68) 6111
38.2%
CJK
ValueCountFrequency (%)
街 1494
 
8.6%
路 1442
 
8.3%
洞 745
 
4.3%
中 414
 
2.4%
山 303
 
1.7%
心 297
 
1.7%
民 296
 
1.7%
大 254
 
1.5%
安 196
 
1.1%
居 178
 
1.0%
Other values (1449) 11832
67.8%
Hiragana
ValueCountFrequency (%)
の 53
25.2%
り 16
 
7.6%
し 14
 
6.7%
き 12
 
5.7%
め 11
 
5.2%
も 7
 
3.3%
け 7
 
3.3%
え 7
 
3.3%
ご 6
 
2.9%
い 5
 
2.4%
Other values (42) 72
34.3%
None
ValueCountFrequency (%)
） 44
40.0%
（ 43
39.1%
、 9
 
8.2%
１ 3
 
2.7%
＆ 3
 
2.7%
２ 2
 
1.8%
　 2
 
1.8%
  2
 
1.8%
· 1
 
0.9%
。 1
 
0.9%
Specials
ValueCountFrequency (%)
� 5
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 4
80.0%
Ⅰ 1
 
20.0%
CJK Compat Ideographs
ValueCountFrequency (%)
老 2
 
8.0%
六 2
 
8.0%
落 2
 
8.0%
丹 2
 
8.0%
良 2
 
8.0%
金 2
 
8.0%
若 2
 
8.0%
碌 2
 
8.0%
磻 2
 
8.0%
龍 2
 
8.0%
Other values (5) 5
20.0%
Punctuation
ValueCountFrequency (%)
– 2
33.3%
’ 1
16.7%
” 1
16.7%
“ 1
16.7%
― 1
16.7%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%

로마자 표기
Text

MISSING 

Distinct436
Distinct (%)100.0%
Missing9564
Missing (%)95.6%
Memory size156.2 KiB
2023-12-13T04:33:17.946263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length29
Mean length15.431193
Min length3

Characters and Unicode

Total characters6728
Distinct characters47
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique436 ?
Unique (%)100.0%

Sample

1st row(dwaeji)meoritgogi
2nd rowjeyuk deopbap
3rd rowhongeo hoe muchim
4th rowsausage tortilla roll
5th rowyukhoebibimbap
ValueCountFrequency (%)
gui 18
 
2.0%
udon 16
 
1.8%
haemul 12
 
1.3%
beoseot 11
 
1.2%
jjim 11
 
1.2%
hoe 10
 
1.1%
jeongsik 10
 
1.1%
tang 9
 
1.0%
ori 9
 
1.0%
cheese 8
 
0.9%
Other values (503) 799
87.5%
2023-12-13T04:33:18.522058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 681
 
10.1%
e 614
 
9.1%
o 567
 
8.4%
g 501
 
7.4%
n 492
 
7.3%
477
 
7.1%
u 405
 
6.0%
i 348
 
5.2%
k 325
 
4.8%
s 269
 
4.0%
Other values (37) 2049
30.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6198
92.1%
Space Separator 477
 
7.1%
Uppercase Letter 32
 
0.5%
Open Punctuation 5
 
0.1%
Close Punctuation 5
 
0.1%
Dash Punctuation 4
 
0.1%
Other Punctuation 4
 
0.1%
Other Symbol 2
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 681
 
11.0%
e 614
 
9.9%
o 567
 
9.1%
g 501
 
8.1%
n 492
 
7.9%
u 405
 
6.5%
i 348
 
5.6%
k 325
 
5.2%
s 269
 
4.3%
m 262
 
4.2%
Other values (15) 1734
28.0%
Uppercase Letter
ValueCountFrequency (%)
H 14
43.8%
S 3
 
9.4%
P 2
 
6.2%
G 2
 
6.2%
C 2
 
6.2%
N 2
 
6.2%
Y 1
 
3.1%
A 1
 
3.1%
U 1
 
3.1%
I 1
 
3.1%
Other values (3) 3
 
9.4%
Other Punctuation
ValueCountFrequency (%)
& 2
50.0%
, 1
25.0%
' 1
25.0%
Space Separator
ValueCountFrequency (%)
477
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Other Symbol
ValueCountFrequency (%)
� 2
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6230
92.6%
Common 498
 
7.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 681
 
10.9%
e 614
 
9.9%
o 567
 
9.1%
g 501
 
8.0%
n 492
 
7.9%
u 405
 
6.5%
i 348
 
5.6%
k 325
 
5.2%
s 269
 
4.3%
m 262
 
4.2%
Other values (28) 1766
28.3%
Common
ValueCountFrequency (%)
477
95.8%
( 5
 
1.0%
) 5
 
1.0%
- 4
 
0.8%
& 2
 
0.4%
� 2
 
0.4%
+ 1
 
0.2%
, 1
 
0.2%
' 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6726
> 99.9%
Specials 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 681
 
10.1%
e 614
 
9.1%
o 567
 
8.4%
g 501
 
7.4%
n 492
 
7.3%
477
 
7.1%
u 405
 
6.0%
i 348
 
5.2%
k 325
 
4.8%
s 269
 
4.0%
Other values (36) 2047
30.4%
Specials
ValueCountFrequency (%)
� 2
100.0%

등록일
Date

Distinct256
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2002-04-09 00:00:00
Maximum2023-09-15 00:00:00
2023-12-13T04:33:18.734830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:33:18.899296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-13T04:33:14.704967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T04:33:19.012838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번언어구분
연번1.0000.756
언어구분0.7561.000
2023-12-13T04:33:19.129205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번언어구분
연번1.0000.629
언어구분0.6291.000

Missing values

2023-12-13T04:33:14.934671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T04:33:15.096498image/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

연번언어구분한글용어번역어로마자 표기등록일
3491634917ENG한천로94길Hancheon-ro 94-gil<NA>2014-03-06
7727977280ENG(돼지)머릿고기Pork Head Meat(dwaeji)meoritgogi2017-05-30
6220562206JPN중앙로39길チュンアンロ39ギル<NA>2014-03-06
8780387804CHA파로호破虏湖<NA>2019-03-08
94619462ENG어로리Eoro-ri<NA>2004-08-23
442443JPN서초중앙로ソチョジュンアンロ<NA>2014-03-06
2732827329ENG명륜2길Myeongnyun 2-gil<NA>2014-03-06
9211492115CHA기상이변气候异变<NA>2020-01-17
7143971440ENG전국바다낚시대회 및 회진전어축제National Sea Fishing Competition and Hoejin Spotted Sardine Festival<NA>2016-04-11
6352063521JPN청룡7길チョンリョン7ギル<NA>2014-03-06
연번언어구분한글용어번역어로마자 표기등록일
2324723248ENG공항대로3길Gonghang-daero 3-gil<NA>2014-03-06
31673168CHA장흥동长兴洞/長興洞<NA>2003-01-15
1934319344JPN신길3동 주민센터シンギル3ドン(新吉3洞)住民センター<NA>2002-10-25
2541125412ENG덕릉로60차길Deongneung-ro 60cha-gil<NA>2014-03-06
4632446325CHA오금로50길梧琴路50街<NA>2014-03-06
4969249693JPN강서로52길カンソロ52ギル<NA>2014-03-06
4745147452CHA을지로16길乙支路16街<NA>2014-03-06
8246782468ENG도시기본계획Urban Planning<NA>2013-07-08
656657ENG4.19로21길4.19-ro 21-gil<NA>2014-03-06
443444JPN서울시립대로ソウルシリプテロ<NA>2014-03-06