Overview

Dataset statistics

Number of variables7
Number of observations5074
Missing cells3056
Missing cells (%)8.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory282.6 KiB
Average record size in memory57.0 B

Variable types

Numeric1
Categorical1
Text5

Dataset

Description광주광역시 서구 관내 음식점 현황에 대한 데이터로 업소명, 업종명, 소재지, 전화번호, 면적 등의 항목을 제공합니다.
Author광주광역시 서구
URLhttps://www.data.go.kr/data/3083730/fileData.do

Alerts

연번 is highly overall correlated with 업종명High correlation
업종명 is highly overall correlated with 연번High correlation
소재지전화번호 has 3053 (60.2%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-23 06:33:33.610711
Analysis finished2023-12-23 06:33:40.948414
Duration7.34 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct5074
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2537.5
Minimum1
Maximum5074
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size44.7 KiB
2023-12-23T06:33:41.523100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile254.65
Q11269.25
median2537.5
Q33805.75
95-th percentile4820.35
Maximum5074
Range5073
Interquartile range (IQR)2536.5

Descriptive statistics

Standard deviation1464.882
Coefficient of variation (CV)0.57729338
Kurtosis-1.2
Mean2537.5
Median Absolute Deviation (MAD)1268.5
Skewness0
Sum12875275
Variance2145879.2
MonotonicityStrictly increasing
2023-12-23T06:33:42.170472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
3382 1
 
< 0.1%
3389 1
 
< 0.1%
3388 1
 
< 0.1%
3387 1
 
< 0.1%
3386 1
 
< 0.1%
3385 1
 
< 0.1%
3384 1
 
< 0.1%
3383 1
 
< 0.1%
3381 1
 
< 0.1%
Other values (5064) 5064
99.8%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
5074 1
< 0.1%
5073 1
< 0.1%
5072 1
< 0.1%
5071 1
< 0.1%
5070 1
< 0.1%
5069 1
< 0.1%
5068 1
< 0.1%
5067 1
< 0.1%
5066 1
< 0.1%
5065 1
< 0.1%

업종명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.8 KiB
일반음식점
4035 
휴게음식점
1039 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반음식점 4035
79.5%
휴게음식점 1039
 
20.5%

Length

2023-12-23T06:33:43.092918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-23T06:33:43.617450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반음식점 4035
79.5%
휴게음식점 1039
 
20.5%

업소명
Text

Distinct4872
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Memory size39.8 KiB
2023-12-23T06:33:45.244298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length27
Mean length6.9306267
Min length1

Characters and Unicode

Total characters35166
Distinct characters973
Distinct categories11 ?
Distinct scripts5 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4730 ?
Unique (%)93.2%

Sample

1st row지하
2nd row영창
3rd row대호
4th row큰집
5th row광성회관
ValueCountFrequency (%)
상무점 98
 
1.4%
광주상무점 64
 
0.9%
세븐일레븐 62
 
0.9%
씨유 45
 
0.7%
쌍촌점 41
 
0.6%
풍암점 35
 
0.5%
화정점 33
 
0.5%
금호점 32
 
0.5%
광주금호점 31
 
0.5%
카페 29
 
0.4%
Other values (5214) 6418
93.2%
2023-12-23T06:33:47.809177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1816
 
5.2%
점 1433
 
4.1%
주 812
 
2.3%
이 672
 
1.9%
광 623
 
1.8%
( 602
 
1.7%
) 602
 
1.7%
스 529
 
1.5%
상 462
 
1.3%
리 450
 
1.3%
Other values (963) 27165
77.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 29369
83.5%
Space Separator 1816
 
5.2%
Lowercase Letter 989
 
2.8%
Uppercase Letter 954
 
2.7%
Decimal Number 673
 
1.9%
Open Punctuation 602
 
1.7%
Close Punctuation 602
 
1.7%
Other Punctuation 143
 
0.4%
Dash Punctuation 11
 
< 0.1%
Other Symbol 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 1433
 
4.9%
주 812
 
2.8%
이 672
 
2.3%
광 623
 
2.1%
스 529
 
1.8%
상 462
 
1.6%
리 450
 
1.5%
무 441
 
1.5%
피 313
 
1.1%
호 309
 
1.1%
Other values (882) 23325
79.4%
Lowercase Letter
ValueCountFrequency (%)
e 157
15.9%
a 104
 
10.5%
o 104
 
10.5%
r 56
 
5.7%
f 54
 
5.5%
i 51
 
5.2%
c 49
 
5.0%
l 47
 
4.8%
n 47
 
4.8%
s 39
 
3.9%
Other values (16) 281
28.4%
Uppercase Letter
ValueCountFrequency (%)
C 113
 
11.8%
B 66
 
6.9%
S 66
 
6.9%
O 65
 
6.8%
E 62
 
6.5%
G 59
 
6.2%
P 55
 
5.8%
A 54
 
5.7%
T 50
 
5.2%
N 38
 
4.0%
Other values (16) 326
34.2%
Other Punctuation
ValueCountFrequency (%)
& 55
38.5%
. 28
19.6%
, 21
 
14.7%
! 11
 
7.7%
· 9
 
6.3%
' 6
 
4.2%
: 4
 
2.8%
# 4
 
2.8%
; 2
 
1.4%
/ 1
 
0.7%
Other values (2) 2
 
1.4%
Decimal Number
ValueCountFrequency (%)
2 148
22.0%
1 102
15.2%
0 92
13.7%
5 89
13.2%
9 50
 
7.4%
3 46
 
6.8%
8 44
 
6.5%
4 38
 
5.6%
6 35
 
5.2%
7 29
 
4.3%
Math Symbol
ValueCountFrequency (%)
+ 2
66.7%
= 1
33.3%
Space Separator
ValueCountFrequency (%)
1816
100.0%
Open Punctuation
ValueCountFrequency (%)
( 602
100.0%
Close Punctuation
ValueCountFrequency (%)
) 602
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Other Symbol
ValueCountFrequency (%)
℃ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 29348
83.5%
Common 3854
 
11.0%
Latin 1943
 
5.5%
Han 18
 
0.1%
Hiragana 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 1433
 
4.9%
주 812
 
2.8%
이 672
 
2.3%
광 623
 
2.1%
스 529
 
1.8%
상 462
 
1.6%
리 450
 
1.5%
무 441
 
1.5%
피 313
 
1.1%
호 309
 
1.1%
Other values (863) 23304
79.4%
Latin
ValueCountFrequency (%)
e 157
 
8.1%
C 113
 
5.8%
a 104
 
5.4%
o 104
 
5.4%
B 66
 
3.4%
S 66
 
3.4%
O 65
 
3.3%
E 62
 
3.2%
G 59
 
3.0%
r 56
 
2.9%
Other values (42) 1091
56.2%
Common
ValueCountFrequency (%)
1816
47.1%
( 602
 
15.6%
) 602
 
15.6%
2 148
 
3.8%
1 102
 
2.6%
0 92
 
2.4%
5 89
 
2.3%
& 55
 
1.4%
9 50
 
1.3%
3 46
 
1.2%
Other values (19) 252
 
6.5%
Han
ValueCountFrequency (%)
家 3
16.7%
美 1
 
5.6%
秀 1
 
5.6%
林 1
 
5.6%
休 1
 
5.6%
味 1
 
5.6%
酒 1
 
5.6%
食 1
 
5.6%
溫 1
 
5.6%
娟 1
 
5.6%
Other values (6) 6
33.3%
Hiragana
ValueCountFrequency (%)
ゆ 1
33.3%
か 1
33.3%
い 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 29348
83.5%
ASCII 5784
 
16.4%
CJK 17
 
< 0.1%
None 9
 
< 0.1%
Letterlike Symbols 4
 
< 0.1%
Hiragana 3
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1816
31.4%
( 602
 
10.4%
) 602
 
10.4%
e 157
 
2.7%
2 148
 
2.6%
C 113
 
2.0%
a 104
 
1.8%
o 104
 
1.8%
1 102
 
1.8%
0 92
 
1.6%
Other values (69) 1944
33.6%
Hangul
ValueCountFrequency (%)
점 1433
 
4.9%
주 812
 
2.8%
이 672
 
2.3%
광 623
 
2.1%
스 529
 
1.8%
상 462
 
1.6%
리 450
 
1.5%
무 441
 
1.5%
피 313
 
1.1%
호 309
 
1.1%
Other values (863) 23304
79.4%
None
ValueCountFrequency (%)
· 9
100.0%
Letterlike Symbols
ValueCountFrequency (%)
℃ 4
100.0%
CJK
ValueCountFrequency (%)
家 3
17.6%
美 1
 
5.9%
秀 1
 
5.9%
林 1
 
5.9%
休 1
 
5.9%
味 1
 
5.9%
酒 1
 
5.9%
食 1
 
5.9%
溫 1
 
5.9%
娟 1
 
5.9%
Other values (5) 5
29.4%
CJK Compat Ideographs
ValueCountFrequency (%)
利 1
100.0%
Hiragana
ValueCountFrequency (%)
ゆ 1
33.3%
か 1
33.3%
い 1
33.3%

소재지도로명주소
Text

Distinct4633
Distinct (%)91.4%
Missing3
Missing (%)0.1%
Memory size39.8 KiB
2023-12-23T06:33:48.910496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length57
Mean length31.51548
Min length20

Characters and Unicode

Total characters159815
Distinct characters358
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4307 ?
Unique (%)84.9%

Sample

1st row광주광역시 서구 천변좌로 154, 209호 (양동)
2nd row광주광역시 서구 천변좌로 243, 양동복개상가 나동 2층 67호 (양동)
3rd row광주광역시 서구 천변좌로 262 (양동)
4th row광주광역시 서구 화운로 303 (광천동,(일층))
5th row광주광역시 서구 죽봉대로 113 (광천동,(일층))
ValueCountFrequency (%)
광주광역시 5071
 
16.1%
서구 5071
 
16.1%
1층 3024
 
9.6%
쌍촌동 856
 
2.7%
치평동 729
 
2.3%
화정동 621
 
2.0%
풍암동 416
 
1.3%
금호동 346
 
1.1%
2층 290
 
0.9%
농성동 214
 
0.7%
Other values (2505) 14763
47.0%
2023-12-23T06:33:51.077394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
26336
 
16.5%
광 10521
 
6.6%
1 9316
 
5.8%
( 6228
 
3.9%
) 6227
 
3.9%
동 5810
 
3.6%
, 5667
 
3.5%
시 5425
 
3.4%
주 5286
 
3.3%
서 5189
 
3.2%
Other values (348) 73810
46.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 87877
55.0%
Space Separator 26336
 
16.5%
Decimal Number 25913
 
16.2%
Open Punctuation 6228
 
3.9%
Close Punctuation 6227
 
3.9%
Other Punctuation 5686
 
3.6%
Dash Punctuation 1256
 
0.8%
Uppercase Letter 192
 
0.1%
Lowercase Letter 53
 
< 0.1%
Math Symbol 47
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 10521
 
12.0%
동 5810
 
6.6%
시 5425
 
6.2%
주 5286
 
6.0%
서 5189
 
5.9%
구 5109
 
5.8%
역 5076
 
5.8%
로 4948
 
5.6%
층 4790
 
5.5%
길 2606
 
3.0%
Other values (297) 33117
37.7%
Uppercase Letter
ValueCountFrequency (%)
B 58
30.2%
A 48
25.0%
C 15
 
7.8%
S 15
 
7.8%
G 8
 
4.2%
E 7
 
3.6%
I 7
 
3.6%
K 6
 
3.1%
L 5
 
2.6%
W 4
 
2.1%
Other values (9) 19
 
9.9%
Lowercase Letter
ValueCountFrequency (%)
a 8
15.1%
n 8
15.1%
e 7
13.2%
l 6
11.3%
r 4
7.5%
t 4
7.5%
i 2
 
3.8%
w 2
 
3.8%
o 2
 
3.8%
d 2
 
3.8%
Other values (4) 8
15.1%
Decimal Number
ValueCountFrequency (%)
1 9316
36.0%
2 3230
 
12.5%
0 2109
 
8.1%
3 2067
 
8.0%
4 1876
 
7.2%
5 1657
 
6.4%
6 1495
 
5.8%
8 1463
 
5.6%
7 1380
 
5.3%
9 1320
 
5.1%
Other Punctuation
ValueCountFrequency (%)
, 5667
99.7%
. 17
 
0.3%
& 2
 
< 0.1%
Space Separator
ValueCountFrequency (%)
26336
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6228
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6227
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1256
100.0%
Math Symbol
ValueCountFrequency (%)
~ 47
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 87877
55.0%
Common 71693
44.9%
Latin 245
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 10521
 
12.0%
동 5810
 
6.6%
시 5425
 
6.2%
주 5286
 
6.0%
서 5189
 
5.9%
구 5109
 
5.8%
역 5076
 
5.8%
로 4948
 
5.6%
층 4790
 
5.5%
길 2606
 
3.0%
Other values (297) 33117
37.7%
Latin
ValueCountFrequency (%)
B 58
23.7%
A 48
19.6%
C 15
 
6.1%
S 15
 
6.1%
a 8
 
3.3%
n 8
 
3.3%
G 8
 
3.3%
E 7
 
2.9%
I 7
 
2.9%
e 7
 
2.9%
Other values (23) 64
26.1%
Common
ValueCountFrequency (%)
26336
36.7%
1 9316
 
13.0%
( 6228
 
8.7%
) 6227
 
8.7%
, 5667
 
7.9%
2 3230
 
4.5%
0 2109
 
2.9%
3 2067
 
2.9%
4 1876
 
2.6%
5 1657
 
2.3%
Other values (8) 6980
 
9.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 87877
55.0%
ASCII 71938
45.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
26336
36.6%
1 9316
 
13.0%
( 6228
 
8.7%
) 6227
 
8.7%
, 5667
 
7.9%
2 3230
 
4.5%
0 2109
 
2.9%
3 2067
 
2.9%
4 1876
 
2.6%
5 1657
 
2.3%
Other values (41) 7225
 
10.0%
Hangul
ValueCountFrequency (%)
광 10521
 
12.0%
동 5810
 
6.6%
시 5425
 
6.2%
주 5286
 
6.0%
서 5189
 
5.9%
구 5109
 
5.8%
역 5076
 
5.8%
로 4948
 
5.6%
층 4790
 
5.5%
길 2606
 
3.0%
Other values (297) 33117
37.7%

소재지지번주소
Text

Distinct4765
Distinct (%)93.9%
Missing0
Missing (%)0.0%
Memory size39.8 KiB
2023-12-23T06:33:52.735651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length50
Mean length25.514584
Min length14

Characters and Unicode

Total characters129461
Distinct characters364
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4521 ?
Unique (%)89.1%

Sample

1st row광주광역시 서구 양동 438-209 (1층)
2nd row광주광역시 서구 양동 441 양동복개상가 2층 나동 67호
3rd row광주광역시 서구 양동 5
4th row광주광역시 서구 광천동 713-6 (일층)
5th row광주광역시 서구 광천동 98-3 (일층)
ValueCountFrequency (%)
광주광역시 5074
18.7%
서구 5074
18.7%
1층 3120
 
11.5%
쌍촌동 1095
 
4.0%
치평동 961
 
3.5%
화정동 785
 
2.9%
풍암동 555
 
2.0%
일층 507
 
1.9%
금호동 481
 
1.8%
2층 291
 
1.1%
Other values (4182) 9179
33.8%
2023-12-23T06:33:55.409730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
26718
20.6%
광 10480
 
8.1%
1 10254
 
7.9%
동 5712
 
4.4%
주 5167
 
4.0%
시 5139
 
4.0%
구 5086
 
3.9%
서 5085
 
3.9%
역 5079
 
3.9%
층 4568
 
3.5%
Other values (354) 46173
35.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 63351
48.9%
Decimal Number 30277
23.4%
Space Separator 26718
20.6%
Dash Punctuation 4132
 
3.2%
Open Punctuation 2143
 
1.7%
Close Punctuation 2142
 
1.7%
Other Punctuation 427
 
0.3%
Uppercase Letter 174
 
0.1%
Math Symbol 51
 
< 0.1%
Lowercase Letter 46
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 10480
16.5%
동 5712
9.0%
주 5167
 
8.2%
시 5139
 
8.1%
구 5086
 
8.0%
서 5085
 
8.0%
역 5079
 
8.0%
층 4568
 
7.2%
호 1595
 
2.5%
촌 1188
 
1.9%
Other values (299) 14252
22.5%
Uppercase Letter
ValueCountFrequency (%)
B 58
33.3%
A 48
27.6%
C 14
 
8.0%
S 9
 
5.2%
I 6
 
3.4%
E 6
 
3.4%
G 5
 
2.9%
L 4
 
2.3%
K 4
 
2.3%
P 3
 
1.7%
Other values (10) 17
 
9.8%
Lowercase Letter
ValueCountFrequency (%)
n 7
15.2%
a 7
15.2%
e 5
10.9%
l 5
10.9%
r 3
 
6.5%
t 3
 
6.5%
u 2
 
4.3%
j 2
 
4.3%
g 2
 
4.3%
w 2
 
4.3%
Other values (4) 8
17.4%
Decimal Number
ValueCountFrequency (%)
1 10254
33.9%
2 3909
 
12.9%
3 2522
 
8.3%
0 2372
 
7.8%
7 1902
 
6.3%
4 1880
 
6.2%
9 1878
 
6.2%
8 1857
 
6.1%
5 1857
 
6.1%
6 1846
 
6.1%
Other Punctuation
ValueCountFrequency (%)
, 411
96.3%
. 11
 
2.6%
& 2
 
0.5%
@ 1
 
0.2%
/ 1
 
0.2%
! 1
 
0.2%
Space Separator
ValueCountFrequency (%)
26718
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4132
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2143
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2142
100.0%
Math Symbol
ValueCountFrequency (%)
~ 51
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 65890
50.9%
Hangul 63351
48.9%
Latin 220
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 10480
16.5%
동 5712
9.0%
주 5167
 
8.2%
시 5139
 
8.1%
구 5086
 
8.0%
서 5085
 
8.0%
역 5079
 
8.0%
층 4568
 
7.2%
호 1595
 
2.5%
촌 1188
 
1.9%
Other values (299) 14252
22.5%
Latin
ValueCountFrequency (%)
B 58
26.4%
A 48
21.8%
C 14
 
6.4%
S 9
 
4.1%
n 7
 
3.2%
a 7
 
3.2%
I 6
 
2.7%
E 6
 
2.7%
e 5
 
2.3%
G 5
 
2.3%
Other values (24) 55
25.0%
Common
ValueCountFrequency (%)
26718
40.5%
1 10254
 
15.6%
- 4132
 
6.3%
2 3909
 
5.9%
3 2522
 
3.8%
0 2372
 
3.6%
( 2143
 
3.3%
) 2142
 
3.3%
7 1902
 
2.9%
4 1880
 
2.9%
Other values (11) 7916
 
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 66110
51.1%
Hangul 63351
48.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
26718
40.4%
1 10254
 
15.5%
- 4132
 
6.3%
2 3909
 
5.9%
3 2522
 
3.8%
0 2372
 
3.6%
( 2143
 
3.2%
) 2142
 
3.2%
7 1902
 
2.9%
4 1880
 
2.8%
Other values (45) 8136
 
12.3%
Hangul
ValueCountFrequency (%)
광 10480
16.5%
동 5712
9.0%
주 5167
 
8.2%
시 5139
 
8.1%
구 5086
 
8.0%
서 5085
 
8.0%
역 5079
 
8.0%
층 4568
 
7.2%
호 1595
 
2.5%
촌 1188
 
1.9%
Other values (299) 14252
22.5%

소재지전화번호
Text

MISSING 

Distinct1980
Distinct (%)98.0%
Missing3053
Missing (%)60.2%
Memory size39.8 KiB
2023-12-23T06:33:56.269449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.235527
Min length6

Characters and Unicode

Total characters24728
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1944 ?
Unique (%)96.2%

Sample

1st row062-366-7415
2nd row062-373-5907
3rd row062-365-7617
4th row062-382-4010
5th row062-368-7999
ValueCountFrequency (%)
062-373 30
 
1.2%
062-381 29
 
1.2%
062-382 25
 
1.0%
062-385 23
 
0.9%
062-375 22
 
0.9%
062-374 21
 
0.9%
062-383 20
 
0.8%
062-376 18
 
0.7%
062-681 16
 
0.7%
062-371 15
 
0.6%
Other values (2007) 2225
91.0%
2023-12-23T06:33:57.609278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 4042
16.3%
6 3481
14.1%
2 3413
13.8%
0 3248
13.1%
3 2700
10.9%
8 1524
 
6.2%
7 1493
 
6.0%
5 1389
 
5.6%
1 1217
 
4.9%
9 930
 
3.8%
Other values (2) 1291
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20263
81.9%
Dash Punctuation 4042
 
16.3%
Space Separator 423
 
1.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 3481
17.2%
2 3413
16.8%
0 3248
16.0%
3 2700
13.3%
8 1524
7.5%
7 1493
7.4%
5 1389
 
6.9%
1 1217
 
6.0%
9 930
 
4.6%
4 868
 
4.3%
Dash Punctuation
ValueCountFrequency (%)
- 4042
100.0%
Space Separator
ValueCountFrequency (%)
423
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24728
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 4042
16.3%
6 3481
14.1%
2 3413
13.8%
0 3248
13.1%
3 2700
10.9%
8 1524
 
6.2%
7 1493
 
6.0%
5 1389
 
5.6%
1 1217
 
4.9%
9 930
 
3.8%
Other values (2) 1291
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24728
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 4042
16.3%
6 3481
14.1%
2 3413
13.8%
0 3248
13.1%
3 2700
10.9%
8 1524
 
6.2%
7 1493
 
6.0%
5 1389
 
5.6%
1 1217
 
4.9%
9 930
 
3.8%
Other values (2) 1291
 
5.2%

면적
Text

Distinct2664
Distinct (%)52.5%
Missing0
Missing (%)0.0%
Memory size39.8 KiB
2023-12-23T06:33:58.986708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length3.9877808
Min length1

Characters and Unicode

Total characters20234
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2120 ?
Unique (%)41.8%

Sample

1st row23.03
2nd row62
3rd row19.32
4th row26.4
5th row46.8
ValueCountFrequency (%)
3.3 151
 
3.0%
30 66
 
1.3%
33 65
 
1.3%
66 54
 
1.1%
60 50
 
1.0%
40 45
 
0.9%
6.6 43
 
0.8%
50 38
 
0.7%
49.5 34
 
0.7%
45 32
 
0.6%
Other values (2654) 4496
88.6%
2023-12-23T06:34:00.899883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 3446
17.0%
1 2223
11.0%
2 2094
10.3%
3 2016
10.0%
5 1808
8.9%
6 1770
8.7%
4 1692
8.4%
9 1463
7.2%
8 1420
7.0%
7 1242
 
6.1%
Other values (2) 1060
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16771
82.9%
Other Punctuation 3463
 
17.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2223
13.3%
2 2094
12.5%
3 2016
12.0%
5 1808
10.8%
6 1770
10.6%
4 1692
10.1%
9 1463
8.7%
8 1420
8.5%
7 1242
7.4%
0 1043
6.2%
Other Punctuation
ValueCountFrequency (%)
. 3446
99.5%
, 17
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Common 20234
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 3446
17.0%
1 2223
11.0%
2 2094
10.3%
3 2016
10.0%
5 1808
8.9%
6 1770
8.7%
4 1692
8.4%
9 1463
7.2%
8 1420
7.0%
7 1242
 
6.1%
Other values (2) 1060
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20234
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 3446
17.0%
1 2223
11.0%
2 2094
10.3%
3 2016
10.0%
5 1808
8.9%
6 1770
8.7%
4 1692
8.4%
9 1463
7.2%
8 1420
7.0%
7 1242
 
6.1%
Other values (2) 1060
 
5.2%

Interactions

2023-12-23T06:33:38.397036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-23T06:34:01.174231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종명
연번1.0001.000
업종명1.0001.000
2023-12-23T06:34:01.590056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종명
연번1.0000.985
업종명0.9851.000

Missing values

2023-12-23T06:33:39.218508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-23T06:33:39.960747image/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.
2023-12-23T06:33:40.612993image/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

연번업종명업소명소재지도로명주소소재지지번주소소재지전화번호면적
01일반음식점지하광주광역시 서구 천변좌로 154, 209호 (양동)광주광역시 서구 양동 438-209 (1층)062-366-741523.03
12일반음식점영창광주광역시 서구 천변좌로 243, 양동복개상가 나동 2층 67호 (양동)광주광역시 서구 양동 441 양동복개상가 2층 나동 67호062-373-590762
23일반음식점대호광주광역시 서구 천변좌로 262 (양동)광주광역시 서구 양동 5062-365-761719.32
34일반음식점큰집광주광역시 서구 화운로 303 (광천동,(일층))광주광역시 서구 광천동 713-6 (일층)062-382-401026.4
45일반음식점광성회관광주광역시 서구 죽봉대로 113 (광천동,(일층))광주광역시 서구 광천동 98-3 (일층)062-368-799946.8
56일반음식점전통 나주곰탕광주광역시 서구 내방로 398 (농성동,(일층))광주광역시 서구 농성동 393-1 (일층)062-363-129230.93
67일반음식점토박이정광주광역시 서구 내방로 308 (내방동,(1층))광주광역시 서구 내방동 305-3 (1층)062-362-710559
78일반음식점선우광주광역시 서구 화운로303번길 5, 1층 (광천동)광주광역시 서구 광천동 713-18 (1층)062-362-494528.6
89일반음식점하림맥시칸치킨광주광역시 서구 독립로 193 (양동,(일층))광주광역시 서구 양동 69-1 (일층)062-374-05834.76
910일반음식점갈매기봉광주광역시 서구 경열로54번길 5 (농성동,(일층))광주광역시 서구 농성동 627-6 (일층)062-366-439663.42
연번업종명업소명소재지도로명주소소재지지번주소소재지전화번호면적
50645065휴게음식점캔디PC광주광역시 서구 상무민주로76번길 1, 안산빌딩 4층 (쌍촌동)광주광역시 서구 쌍촌동 1271-9 안산빌딩 4층<NA>9.9
50655066휴게음식점메고지고 떡창고광주광역시 서구 풍암2로 61, 1층 (풍암동)광주광역시 서구 풍암동 1088-3 1층<NA>90
50665067휴게음식점붕스타광주광역시 서구 화운로 17, 1층 (화정동)광주광역시 서구 화정동 1289 1층<NA>38
50675068휴게음식점지에스25 금호마륵점광주광역시 서구 금화로85번길 30-14, 1층 (금호동)광주광역시 서구 금호동 752-1 1층<NA>3.3
50685069휴게음식점카페 서빛광주광역시 서구 풍암공원로 30, 2층 (풍암동)광주광역시 서구 풍암동 산 13 2층<NA>31.74
50695070휴게음식점원티드711버거(농성점)광주광역시 서구 경열로 61, 2층 (농성동)광주광역시 서구 농성동 154-5 2층<NA>64
50705071휴게음식점오니기리봉봉 신세계광주점광주광역시 서구 무진대로 932, 신세계백화점 광주점 지하1층 (광천동)광주광역시 서구 광천동 49-1 신세계백화점 광주점 지하1층<NA>19.9
50715072휴게음식점세븐일레븐 광주쌍촌엘리체점광주광역시 서구 월드컵4강로197번길 5-4, 1층 (쌍촌동)광주광역시 서구 쌍촌동 951-19 1층<NA>3.3
50725073휴게음식점카페 미민(Cafe MIMIN)광주광역시 서구 풍금로3번길 6, 1층 (풍암동)광주광역시 서구 풍암동 924-3 1층<NA>109.03
50735074휴게음식점미미붕어빵광주광역시 서구 천변좌로 238, 양동시장 다A동 1층 457호 (양동)광주광역시 서구 양동 5-101 양동시장 다동A동 1층 457호<NA>8.25