Overview

Dataset statistics

Number of variables8
Number of observations4584
Missing cells844
Missing cells (%)2.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory286.6 KiB
Average record size in memory64.0 B

Variable types

Text5
Categorical2
DateTime1

Dataset

Description경기도 포천시에서 제공하는 지역화폐(포천사랑상품권) 지류 가맹점 정보(지정번호, 상호., 주소, 업태, 종목, 전화번호, 읍면동명, 데이터기준일자) 제공
Author경기도 포천시
URLhttps://www.data.go.kr/data/15090253/fileData.do

Alerts

데이터기준일 has constant value ""Constant
업태 is highly imbalanced (51.8%)Imbalance
전화번호 has 839 (18.3%) missing valuesMissing

Reproduction

Analysis started2023-12-12 08:40:41.879919
Analysis finished2023-12-12 08:40:43.690806
Duration1.81 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지정번호
Text

Distinct4578
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size35.9 KiB
2023-12-12T17:40:43.981602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length8.8062827
Min length6

Characters and Unicode

Total characters40368
Distinct characters31
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4577 ?
Unique (%)99.8%

Sample

1st rowJan-19
2nd rowMar-19
3rd rowMay-19
4th rowJul-19
5th rowAug-19
ValueCountFrequency (%)
2019-1276 7
 
0.2%
2020-0473 1
 
< 0.1%
2020-0479 1
 
< 0.1%
2020-0478 1
 
< 0.1%
2020-0477 1
 
< 0.1%
2020-0476 1
 
< 0.1%
2020-0482 1
 
< 0.1%
2020-0475 1
 
< 0.1%
2020-0472 1
 
< 0.1%
2020-0481 1
 
< 0.1%
Other values (4568) 4568
99.7%
2023-12-12T17:40:44.492673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 8921
22.1%
2 8781
21.8%
1 5819
14.4%
- 4584
11.4%
9 3759
9.3%
3 1837
 
4.6%
4 1418
 
3.5%
5 1355
 
3.4%
6 1348
 
3.3%
7 1294
 
3.2%
Other values (21) 1252
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 35757
88.6%
Dash Punctuation 4584
 
11.4%
Lowercase Letter 18
 
< 0.1%
Uppercase Letter 9
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 3
16.7%
c 2
11.1%
e 2
11.1%
u 2
11.1%
t 1
 
5.6%
o 1
 
5.6%
v 1
 
5.6%
p 1
 
5.6%
y 1
 
5.6%
g 1
 
5.6%
Other values (3) 3
16.7%
Decimal Number
ValueCountFrequency (%)
0 8921
24.9%
2 8781
24.6%
1 5819
16.3%
9 3759
10.5%
3 1837
 
5.1%
4 1418
 
4.0%
5 1355
 
3.8%
6 1348
 
3.8%
7 1294
 
3.6%
8 1225
 
3.4%
Uppercase Letter
ValueCountFrequency (%)
J 2
22.2%
M 2
22.2%
O 1
11.1%
N 1
11.1%
D 1
11.1%
S 1
11.1%
A 1
11.1%
Dash Punctuation
ValueCountFrequency (%)
- 4584
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 40341
99.9%
Latin 27
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 3
 
11.1%
J 2
 
7.4%
M 2
 
7.4%
c 2
 
7.4%
e 2
 
7.4%
u 2
 
7.4%
O 1
 
3.7%
t 1
 
3.7%
N 1
 
3.7%
o 1
 
3.7%
Other values (10) 10
37.0%
Common
ValueCountFrequency (%)
0 8921
22.1%
2 8781
21.8%
1 5819
14.4%
- 4584
11.4%
9 3759
9.3%
3 1837
 
4.6%
4 1418
 
3.5%
5 1355
 
3.4%
6 1348
 
3.3%
7 1294
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 40368
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 8921
22.1%
2 8781
21.8%
1 5819
14.4%
- 4584
11.4%
9 3759
9.3%
3 1837
 
4.6%
4 1418
 
3.5%
5 1355
 
3.4%
6 1348
 
3.3%
7 1294
 
3.2%
Other values (21) 1252
 
3.1%

상호
Text

Distinct4370
Distinct (%)95.3%
Missing0
Missing (%)0.0%
Memory size35.9 KiB
2023-12-12T17:40:44.865187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length20
Mean length6.0453752
Min length1

Characters and Unicode

Total characters27712
Distinct characters909
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4250 ?
Unique (%)92.7%

Sample

1st row모이모이
2nd row써니헤어
3rd row청화어페럴
4th row이화어패럴
5th row예원서점
ValueCountFrequency (%)
아모레카운셀러 72
 
1.4%
포천점 25
 
0.5%
송우점 17
 
0.3%
옛날통닭 10
 
0.2%
세븐일레븐 8
 
0.2%
주식회사 8
 
0.2%
포천시청점 8
 
0.2%
포천신읍점 7
 
0.1%
포천송우점 7
 
0.1%
미니스톱 7
 
0.1%
Other values (4639) 4899
96.7%
2023-12-12T17:40:45.393806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 571
 
2.1%
이 527
 
1.9%
천 527
 
1.9%
496
 
1.8%
포 489
 
1.8%
리 450
 
1.6%
스 364
 
1.3%
원 340
 
1.2%
동 307
 
1.1%
아 296
 
1.1%
Other values (899) 23345
84.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 25784
93.0%
Space Separator 496
 
1.8%
Uppercase Letter 446
 
1.6%
Decimal Number 314
 
1.1%
Lowercase Letter 184
 
0.7%
Close Punctuation 179
 
0.6%
Open Punctuation 177
 
0.6%
Other Punctuation 76
 
0.3%
Other Symbol 47
 
0.2%
Dash Punctuation 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 571
 
2.2%
이 527
 
2.0%
천 527
 
2.0%
포 489
 
1.9%
리 450
 
1.7%
스 364
 
1.4%
원 340
 
1.3%
동 307
 
1.2%
아 296
 
1.1%
사 293
 
1.1%
Other values (824) 21620
83.9%
Lowercase Letter
ValueCountFrequency (%)
c 19
 
10.3%
u 16
 
8.7%
e 14
 
7.6%
a 14
 
7.6%
s 14
 
7.6%
o 12
 
6.5%
i 12
 
6.5%
r 9
 
4.9%
p 9
 
4.9%
n 8
 
4.3%
Other values (16) 57
31.0%
Uppercase Letter
ValueCountFrequency (%)
S 74
16.6%
G 61
13.7%
C 48
 
10.8%
U 29
 
6.5%
O 25
 
5.6%
A 21
 
4.7%
B 19
 
4.3%
L 16
 
3.6%
K 15
 
3.4%
P 15
 
3.4%
Other values (14) 123
27.6%
Decimal Number
ValueCountFrequency (%)
2 93
29.6%
5 67
21.3%
1 40
12.7%
4 27
 
8.6%
9 26
 
8.3%
3 18
 
5.7%
8 15
 
4.8%
0 14
 
4.5%
6 11
 
3.5%
7 3
 
1.0%
Other Punctuation
ValueCountFrequency (%)
& 28
36.8%
. 26
34.2%
, 10
 
13.2%
' 4
 
5.3%
% 2
 
2.6%
? 2
 
2.6%
# 2
 
2.6%
/ 1
 
1.3%
· 1
 
1.3%
Space Separator
ValueCountFrequency (%)
496
100.0%
Close Punctuation
ValueCountFrequency (%)
) 179
100.0%
Open Punctuation
ValueCountFrequency (%)
( 177
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 47
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 25827
93.2%
Common 1251
 
4.5%
Latin 630
 
2.3%
Han 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 571
 
2.2%
이 527
 
2.0%
천 527
 
2.0%
포 489
 
1.9%
리 450
 
1.7%
스 364
 
1.4%
원 340
 
1.3%
동 307
 
1.2%
아 296
 
1.1%
사 293
 
1.1%
Other values (822) 21663
83.9%
Latin
ValueCountFrequency (%)
S 74
 
11.7%
G 61
 
9.7%
C 48
 
7.6%
U 29
 
4.6%
O 25
 
4.0%
A 21
 
3.3%
c 19
 
3.0%
B 19
 
3.0%
u 16
 
2.5%
L 16
 
2.5%
Other values (40) 302
47.9%
Common
ValueCountFrequency (%)
496
39.6%
) 179
 
14.3%
( 177
 
14.1%
2 93
 
7.4%
5 67
 
5.4%
1 40
 
3.2%
& 28
 
2.2%
4 27
 
2.2%
. 26
 
2.1%
9 26
 
2.1%
Other values (14) 92
 
7.4%
Han
ValueCountFrequency (%)
美 2
50.0%
牛 1
25.0%
秀 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25780
93.0%
ASCII 1880
 
6.8%
None 48
 
0.2%
CJK 4
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 571
 
2.2%
이 527
 
2.0%
천 527
 
2.0%
포 489
 
1.9%
리 450
 
1.7%
스 364
 
1.4%
원 340
 
1.3%
동 307
 
1.2%
아 296
 
1.1%
사 293
 
1.1%
Other values (821) 21616
83.8%
ASCII
ValueCountFrequency (%)
496
26.4%
) 179
 
9.5%
( 177
 
9.4%
2 93
 
4.9%
S 74
 
3.9%
5 67
 
3.6%
G 61
 
3.2%
C 48
 
2.6%
1 40
 
2.1%
U 29
 
1.5%
Other values (63) 616
32.8%
None
ValueCountFrequency (%)
㈜ 47
97.9%
· 1
 
2.1%
CJK
ValueCountFrequency (%)
美 2
50.0%
牛 1
25.0%
秀 1
25.0%

주소
Text

Distinct4010
Distinct (%)87.5%
Missing0
Missing (%)0.0%
Memory size35.9 KiB
2023-12-12T17:40:45.744181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length42
Mean length20.970113
Min length5

Characters and Unicode

Total characters96127
Distinct characters305
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

Unique3606 ?
Unique (%)78.7%

Sample

1st row경기도 포천시 포천로1585번길 31(신읍동)
2nd row경기도 포천시 신읍길 26, 1층(신읍동)
3rd row경기도 포천시 중앙로 148(신읍동)
4th row경기도 포천시 중앙로 146(신읍동)
5th row경기도 포천시 중앙로110번길 11(신읍동)
ValueCountFrequency (%)
경기도 4655
21.4%
포천시 4553
20.9%
소흘읍 1321
 
6.1%
호국로 478
 
2.2%
일동면 370
 
1.7%
영북면 331
 
1.5%
신북면 292
 
1.3%
가산면 246
 
1.1%
솔모루로 236
 
1.1%
화동로 232
 
1.1%
Other values (3490) 9051
41.6%
2023-12-12T17:40:46.273789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17270
18.0%
천 4947
 
5.1%
포 4867
 
5.1%
기 4757
 
4.9%
경 4697
 
4.9%
도 4658
 
4.8%
시 4593
 
4.8%
1 4286
 
4.5%
로 3769
 
3.9%
2 2221
 
2.3%
Other values (295) 40062
41.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 58442
60.8%
Decimal Number 17478
 
18.2%
Space Separator 17270
 
18.0%
Dash Punctuation 1272
 
1.3%
Close Punctuation 576
 
0.6%
Open Punctuation 574
 
0.6%
Other Punctuation 479
 
0.5%
Uppercase Letter 30
 
< 0.1%
Lowercase Letter 5
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 4947
 
8.5%
포 4867
 
8.3%
기 4757
 
8.1%
경 4697
 
8.0%
도 4658
 
8.0%
시 4593
 
7.9%
로 3769
 
6.4%
면 2034
 
3.5%
읍 1869
 
3.2%
동 1853
 
3.2%
Other values (262) 20398
34.9%
Decimal Number
ValueCountFrequency (%)
1 4286
24.5%
2 2221
12.7%
3 1779
10.2%
5 1511
 
8.6%
0 1479
 
8.5%
4 1354
 
7.7%
6 1261
 
7.2%
9 1260
 
7.2%
7 1188
 
6.8%
8 1139
 
6.5%
Uppercase Letter
ValueCountFrequency (%)
A 11
36.7%
B 9
30.0%
D 2
 
6.7%
S 2
 
6.7%
G 2
 
6.7%
P 1
 
3.3%
T 1
 
3.3%
F 1
 
3.3%
C 1
 
3.3%
Lowercase Letter
ValueCountFrequency (%)
a 1
20.0%
c 1
20.0%
w 1
20.0%
s 1
20.0%
b 1
20.0%
Other Punctuation
ValueCountFrequency (%)
. 294
61.4%
, 182
38.0%
@ 2
 
0.4%
/ 1
 
0.2%
Space Separator
ValueCountFrequency (%)
17270
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1272
100.0%
Close Punctuation
ValueCountFrequency (%)
) 576
100.0%
Open Punctuation
ValueCountFrequency (%)
( 574
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 58442
60.8%
Common 37650
39.2%
Latin 35
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 4947
 
8.5%
포 4867
 
8.3%
기 4757
 
8.1%
경 4697
 
8.0%
도 4658
 
8.0%
시 4593
 
7.9%
로 3769
 
6.4%
면 2034
 
3.5%
읍 1869
 
3.2%
동 1853
 
3.2%
Other values (262) 20398
34.9%
Common
ValueCountFrequency (%)
17270
45.9%
1 4286
 
11.4%
2 2221
 
5.9%
3 1779
 
4.7%
5 1511
 
4.0%
0 1479
 
3.9%
4 1354
 
3.6%
- 1272
 
3.4%
6 1261
 
3.3%
9 1260
 
3.3%
Other values (9) 3957
 
10.5%
Latin
ValueCountFrequency (%)
A 11
31.4%
B 9
25.7%
D 2
 
5.7%
S 2
 
5.7%
G 2
 
5.7%
P 1
 
2.9%
T 1
 
2.9%
a 1
 
2.9%
F 1
 
2.9%
c 1
 
2.9%
Other values (4) 4
 
11.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 58441
60.8%
ASCII 37685
39.2%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17270
45.8%
1 4286
 
11.4%
2 2221
 
5.9%
3 1779
 
4.7%
5 1511
 
4.0%
0 1479
 
3.9%
4 1354
 
3.6%
- 1272
 
3.4%
6 1261
 
3.3%
9 1260
 
3.3%
Other values (23) 3992
 
10.6%
Hangul
ValueCountFrequency (%)
천 4947
 
8.5%
포 4867
 
8.3%
기 4757
 
8.1%
경 4697
 
8.0%
도 4658
 
8.0%
시 4593
 
7.9%
로 3769
 
6.4%
면 2034
 
3.5%
읍 1869
 
3.2%
동 1853
 
3.2%
Other values (261) 20397
34.9%
Compat Jamo
ValueCountFrequency (%)
ㄹ 1
100.0%

업태
Categorical

IMBALANCE 

Distinct43
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size35.9 KiB
음식
1962 
소매
860 
서비스
654 
도소매
478 
교육서비스
 
146
Other values (38)
484 

Length

Max length8
Median length2
Mean length2.4611693
Min length2

Unique

Unique15 ?
Unique (%)0.3%

Sample

1st row음식
2nd row서비스
3rd row서비스
4th row소매
5th row소매

Common Values

ValueCountFrequency (%)
음식 1962
42.8%
소매 860
18.8%
서비스 654
 
14.3%
도소매 478
 
10.4%
교육서비스 146
 
3.2%
제조업 103
 
2.2%
보건업 77
 
1.7%
숙박 52
 
1.1%
부동산 45
 
1.0%
소매업 34
 
0.7%
Other values (33) 173
 
3.8%

Length

2023-12-12T17:40:46.465651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
음식 1965
42.8%
소매 861
18.8%
서비스 656
 
14.3%
도소매 479
 
10.4%
교육서비스 146
 
3.2%
제조업 103
 
2.2%
보건업 77
 
1.7%
숙박 52
 
1.1%
부동산 45
 
1.0%
소매업 35
 
0.8%
Other values (30) 170
 
3.7%

종목
Text

Distinct782
Distinct (%)17.1%
Missing5
Missing (%)0.1%
Memory size35.9 KiB
2023-12-12T17:40:46.809084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length2
Mean length3.2686176
Min length1

Characters and Unicode

Total characters14967
Distinct characters398
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique566 ?
Unique (%)12.4%

Sample

1st row커피 등
2nd row미용
3rd row스포츠
4th row스포츠
5th row서점
ValueCountFrequency (%)
한식 1350
26.8%
미용 233
 
4.6%
등 220
 
4.4%
편의점 171
 
3.4%
커피 134
 
2.7%
의류 114
 
2.3%
화장품 94
 
1.9%
잡화 94
 
1.9%
학원 88
 
1.7%
중식 79
 
1.6%
Other values (762) 2453
48.8%
2023-12-12T17:40:47.393659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 1716
 
11.5%
한 1374
 
9.2%
545
 
3.6%
의 370
 
2.5%
. 362
 
2.4%
용 338
 
2.3%
등 317
 
2.1%
화 308
 
2.1%
품 275
 
1.8%
미 265
 
1.8%
Other values (388) 9097
60.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13793
92.2%
Other Punctuation 564
 
3.8%
Space Separator 545
 
3.6%
Uppercase Letter 38
 
0.3%
Close Punctuation 9
 
0.1%
Open Punctuation 9
 
0.1%
Lowercase Letter 7
 
< 0.1%
Decimal Number 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 1716
 
12.4%
한 1374
 
10.0%
의 370
 
2.7%
용 338
 
2.5%
등 317
 
2.3%
화 308
 
2.2%
품 275
 
2.0%
미 265
 
1.9%
점 239
 
1.7%
장 234
 
1.7%
Other values (366) 8357
60.6%
Uppercase Letter
ValueCountFrequency (%)
P 13
34.2%
L 7
18.4%
G 7
18.4%
C 5
 
13.2%
O 2
 
5.3%
A 2
 
5.3%
V 1
 
2.6%
S 1
 
2.6%
Other Punctuation
ValueCountFrequency (%)
. 362
64.2%
, 199
35.3%
& 1
 
0.2%
· 1
 
0.2%
/ 1
 
0.2%
Lowercase Letter
ValueCountFrequency (%)
c 3
42.9%
v 1
 
14.3%
t 1
 
14.3%
p 1
 
14.3%
s 1
 
14.3%
Space Separator
ValueCountFrequency (%)
545
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Decimal Number
ValueCountFrequency (%)
5 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13793
92.2%
Common 1129
 
7.5%
Latin 45
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 1716
 
12.4%
한 1374
 
10.0%
의 370
 
2.7%
용 338
 
2.5%
등 317
 
2.3%
화 308
 
2.2%
품 275
 
2.0%
미 265
 
1.9%
점 239
 
1.7%
장 234
 
1.7%
Other values (366) 8357
60.6%
Latin
ValueCountFrequency (%)
P 13
28.9%
L 7
15.6%
G 7
15.6%
C 5
 
11.1%
c 3
 
6.7%
O 2
 
4.4%
A 2
 
4.4%
v 1
 
2.2%
t 1
 
2.2%
p 1
 
2.2%
Other values (3) 3
 
6.7%
Common
ValueCountFrequency (%)
545
48.3%
. 362
32.1%
, 199
 
17.6%
) 9
 
0.8%
( 9
 
0.8%
5 2
 
0.2%
& 1
 
0.1%
· 1
 
0.1%
/ 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13793
92.2%
ASCII 1173
 
7.8%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 1716
 
12.4%
한 1374
 
10.0%
의 370
 
2.7%
용 338
 
2.5%
등 317
 
2.3%
화 308
 
2.2%
품 275
 
2.0%
미 265
 
1.9%
점 239
 
1.7%
장 234
 
1.7%
Other values (366) 8357
60.6%
ASCII
ValueCountFrequency (%)
545
46.5%
. 362
30.9%
, 199
 
17.0%
P 13
 
1.1%
) 9
 
0.8%
( 9
 
0.8%
L 7
 
0.6%
G 7
 
0.6%
C 5
 
0.4%
c 3
 
0.3%
Other values (11) 14
 
1.2%
None
ValueCountFrequency (%)
· 1
100.0%

전화번호
Text

MISSING 

Distinct3555
Distinct (%)94.9%
Missing839
Missing (%)18.3%
Memory size35.9 KiB
2023-12-12T17:40:47.741448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length12
Mean length11.989052
Min length1

Characters and Unicode

Total characters44899
Distinct characters14
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3458 ?
Unique (%)92.3%

Sample

1st row031-535-2104
2nd row031-532-1470
3rd row031-533-3149
4th row031-535-8633
5th row031-531-0655
ValueCountFrequency (%)
031-531-9115 34
 
0.9%
031-542-7737 29
 
0.8%
031-538-2272 20
 
0.5%
031 14
 
0.4%
031-533-0002 5
 
0.1%
031-531-2518 2
 
0.1%
031-541-0880 2
 
0.1%
031-534-7750 2
 
0.1%
031-531-1649 2
 
0.1%
031-542-8051 2
 
0.1%
Other values (3543) 3628
97.0%
2023-12-12T17:40:48.302959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 8155
18.2%
- 7495
16.7%
1 5889
13.1%
5 5802
12.9%
0 5502
12.3%
4 3369
7.5%
2 2411
 
5.4%
7 1656
 
3.7%
8 1621
 
3.6%
9 1519
 
3.4%
Other values (4) 1480
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 37397
83.3%
Dash Punctuation 7495
 
16.7%
Space Separator 5
 
< 0.1%
Math Symbol 1
 
< 0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 8155
21.8%
1 5889
15.7%
5 5802
15.5%
0 5502
14.7%
4 3369
9.0%
2 2411
 
6.4%
7 1656
 
4.4%
8 1621
 
4.3%
9 1519
 
4.1%
6 1473
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 7495
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
F 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 44898
> 99.9%
Latin 1
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
3 8155
18.2%
- 7495
16.7%
1 5889
13.1%
5 5802
12.9%
0 5502
12.3%
4 3369
7.5%
2 2411
 
5.4%
7 1656
 
3.7%
8 1621
 
3.6%
9 1519
 
3.4%
Other values (3) 1479
 
3.3%
Latin
ValueCountFrequency (%)
F 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 44899
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 8155
18.2%
- 7495
16.7%
1 5889
13.1%
5 5802
12.9%
0 5502
12.3%
4 3369
7.5%
2 2411
 
5.4%
7 1656
 
3.7%
8 1621
 
3.6%
9 1519
 
3.4%
Other values (4) 1480
 
3.3%

읍면동명
Categorical

Distinct20
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size35.9 KiB
소흘읍
1370 
신읍동
751 
일동면
368 
영북면
336 
신북면
306 
Other values (15)
1453 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
소흘읍 1370
29.9%
신읍동 751
16.4%
일동면 368
 
8.0%
영북면 336
 
7.3%
신북면 306
 
6.7%
선단동 260
 
5.7%
가산면 249
 
5.4%
군내면 189
 
4.1%
이동면 172
 
3.8%
내촌면 155
 
3.4%
Other values (10) 428
 
9.3%

Length

2023-12-12T17:40:48.488256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
소흘읍 1370
29.9%
신읍동 751
16.4%
일동면 368
 
8.0%
영북면 336
 
7.3%
신북면 306
 
6.7%
선단동 260
 
5.7%
가산면 249
 
5.4%
군내면 189
 
4.1%
이동면 172
 
3.8%
내촌면 155
 
3.4%
Other values (10) 428
 
9.3%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size35.9 KiB
Minimum2021-08-31 00:00:00
Maximum2021-08-31 00:00:00
2023-12-12T17:40:48.603406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:40:48.744068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2023-12-12T17:40:48.852628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업태읍면동명
업태1.0000.281
읍면동명0.2811.000
2023-12-12T17:40:49.290417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업태읍면동명
업태1.0000.074
읍면동명0.0741.000
2023-12-12T17:40:49.391059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업태읍면동명
업태1.0000.074
읍면동명0.0741.000

Missing values

2023-12-12T17:40:43.333800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:40:43.488439image/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.
2023-12-12T17:40:43.618614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

지정번호상호주소업태종목전화번호읍면동명데이터기준일
0Jan-19모이모이경기도 포천시 포천로1585번길 31(신읍동)음식커피 등031-535-2104신읍동2021-08-31
1Mar-19써니헤어경기도 포천시 신읍길 26, 1층(신읍동)서비스미용031-532-1470신읍동2021-08-31
2May-19청화어페럴경기도 포천시 중앙로 148(신읍동)서비스스포츠<NA>신읍동2021-08-31
3Jul-19이화어패럴경기도 포천시 중앙로 146(신읍동)소매스포츠031-533-3149신읍동2021-08-31
4Aug-19예원서점경기도 포천시 중앙로110번길 11(신읍동)소매서점031-535-8633신읍동2021-08-31
5Sep-19꾸오레안경경기도 포천시 구절초로 33(신읍동)소매안경점031-531-0655신읍동2021-08-31
6Oct-19CU포천신읍점경기도 포천시 왕방로 157(신읍동)소매편의점031-533-7158신읍동2021-08-31
7Nov-19커피앤커피경기도 포천시 호병로 81, 나동 103호(신읍동)음식커피 등031-536-0901신읍동2021-08-31
8Dec-19자연식당경기도 포천시 중앙로98번길 10-4, 1층(신읍동)음식한식031-531-9939신읍동2021-08-31
92019-13소담경기도 포천시 신읍4길 4(신읍동)소매반찬031-533-9327신읍동2021-08-31
지정번호상호주소업태종목전화번호읍면동명데이터기준일
45742021-0194에그박스 포천송우점경기도 경기도 포천시 소흘읍 초가팔로58,1층음식업휴게음식점031-542-8096소흘읍2021-08-31
45752021-0195작은정육점경기도 경기도 포천시 소흘읍 호국로429번길8,엘프라자110호도소매정육점<NA>소흘읍2021-08-31
45762021-0196통통돼지경기도 경기도 포천시 호국로 997,1층(선단동)음식점업한식<NA>선단동2021-08-31
45772021-0197공감경기도 경기도 포천시 호국로1094,가동(자작동)건설업인테리어031-531-5150선단동2021-08-31
45782021-0198아이스캔디 솔모루경기도 경기도 포천시 소흘읍 솔모루로66-6,1층도매 및 소매업아이스크림판매<NA>소흘읍2021-08-31
45792021-0199모정칼국수경기도 경기 포천시 가산면 시우동길 49, 1층음식점업한식031-542-6616가산면2021-08-31
45802021-0200정훈건설기계경기도 경기도 포천시 중앙로 119번길21(신읍동)건설업건설기계도급및대여031-535-8916신읍동2021-08-31
45812021-0201배떡 포천시청점경기도 경기도 포천시 원앙로 79,가동1층(신읍동)일반음식점분식031-533-6789신읍동2021-08-31
45822021-0202오감낙곱새 포천점경기도 경기도 포천시 소흘읍 봉솔로1길26,1층음식점업한식031-543-5392소흘읍2021-08-31
45832021-0203산정원 흑염소경기도 경기도 포천시 영중면 성장로8음식한식031-531-7737영중면2021-08-31