Overview

Dataset statistics

Number of variables6
Number of observations2366
Missing cells1055
Missing cells (%)7.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory113.3 KiB
Average record size in memory49.1 B

Variable types

Numeric1
Categorical1
Text4

Dataset

Description인천광역시 남동구 공중위생업소현황에 대한 데이터로 연번, 업종, 업소명, 소재지, 전화번호 항목을 제공합니다.
Author인천광역시 남동구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=3077465&srcSe=7661IVAWM27C61E190

Alerts

연번 is highly overall correlated with 업종명High correlation
업종명 is highly overall correlated with 연번High correlation
소재지전화 has 1055 (44.6%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-01-28 09:11:18.480328
Analysis finished2024-01-28 09:11:19.418061
Duration0.94 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct2366
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1183.5
Minimum1
Maximum2366
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size20.9 KiB
2024-01-28T18:11:19.474811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile119.25
Q1592.25
median1183.5
Q31774.75
95-th percentile2247.75
Maximum2366
Range2365
Interquartile range (IQR)1182.5

Descriptive statistics

Standard deviation683.14969
Coefficient of variation (CV)0.5772283
Kurtosis-1.2
Mean1183.5
Median Absolute Deviation (MAD)591.5
Skewness0
Sum2800161
Variance466693.5
MonotonicityStrictly increasing
2024-01-28T18:11:19.581453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
1591 1
 
< 0.1%
1575 1
 
< 0.1%
1576 1
 
< 0.1%
1577 1
 
< 0.1%
1578 1
 
< 0.1%
1579 1
 
< 0.1%
1580 1
 
< 0.1%
1581 1
 
< 0.1%
1582 1
 
< 0.1%
Other values (2356) 2356
99.6%
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 (%)
2366 1
< 0.1%
2365 1
< 0.1%
2364 1
< 0.1%
2363 1
< 0.1%
2362 1
< 0.1%
2361 1
< 0.1%
2360 1
< 0.1%
2359 1
< 0.1%
2358 1
< 0.1%
2357 1
< 0.1%

업종명
Categorical

HIGH CORRELATION 

Distinct22
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
일반미용업
829 
미용업
278 
피부미용업
235 
세탁업
189 
네일미용업
156 
Other values (17)
679 

Length

Max length23
Median length5
Mean length5.6065089
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row숙박업(일반)
2nd row숙박업(일반)
3rd row숙박업(일반)
4th row숙박업(일반)
5th row숙박업(일반)

Common Values

ValueCountFrequency (%)
일반미용업 829
35.0%
미용업 278
 
11.7%
피부미용업 235
 
9.9%
세탁업 189
 
8.0%
네일미용업 156
 
6.6%
건물위생관리업 155
 
6.6%
이용업 122
 
5.2%
숙박업(일반) 79
 
3.3%
종합미용업 53
 
2.2%
화장ㆍ분장 미용업 47
 
2.0%
Other values (12) 223
 
9.4%

Length

2024-01-28T18:11:19.696091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반미용업 882
32.2%
미용업 437
15.9%
피부미용업 334
 
12.2%
네일미용업 292
 
10.6%
세탁업 189
 
6.9%
화장ㆍ분장 159
 
5.8%
건물위생관리업 155
 
5.7%
이용업 122
 
4.4%
숙박업(일반 79
 
2.9%
종합미용업 53
 
1.9%
Other values (2) 41
 
1.5%

업소명
Text

Distinct2237
Distinct (%)94.5%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
2024-01-28T18:11:19.939013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length25
Mean length5.9027895
Min length1

Characters and Unicode

Total characters13966
Distinct characters684
Distinct categories12 ?
Distinct scripts5 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2138 ?
Unique (%)90.4%

Sample

1st row주얼리 모텔
2nd row화승여관
3rd row산장여인숙
4th row옥수장여관
5th row광명장 여관
ValueCountFrequency (%)
헤어 34
 
1.3%
주식회사 31
 
1.1%
미용실 14
 
0.5%
hair 10
 
0.4%
네일 9
 
0.3%
nail 8
 
0.3%
리안헤어 7
 
0.3%
로이드밤 7
 
0.3%
헤어샵 7
 
0.3%
호텔 6
 
0.2%
Other values (2373) 2576
95.1%
2024-01-28T18:11:20.314765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
어 799
 
5.7%
헤 765
 
5.5%
이 382
 
2.7%
345
 
2.5%
스 330
 
2.4%
미 279
 
2.0%
리 276
 
2.0%
일 264
 
1.9%
네 229
 
1.6%
( 209
 
1.5%
Other values (674) 10088
72.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12302
88.1%
Uppercase Letter 378
 
2.7%
Space Separator 345
 
2.5%
Lowercase Letter 315
 
2.3%
Open Punctuation 209
 
1.5%
Close Punctuation 209
 
1.5%
Decimal Number 117
 
0.8%
Other Punctuation 75
 
0.5%
Dash Punctuation 10
 
0.1%
Connector Punctuation 3
 
< 0.1%
Other values (2) 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
어 799
 
6.5%
헤 765
 
6.2%
이 382
 
3.1%
스 330
 
2.7%
미 279
 
2.3%
리 276
 
2.2%
일 264
 
2.1%
네 229
 
1.9%
세 171
 
1.4%
용 153
 
1.2%
Other values (601) 8654
70.3%
Lowercase Letter
ValueCountFrequency (%)
a 49
15.6%
i 46
14.6%
l 33
10.5%
r 28
8.9%
n 26
8.3%
o 20
 
6.3%
e 19
 
6.0%
s 18
 
5.7%
h 15
 
4.8%
y 10
 
3.2%
Other values (15) 51
16.2%
Uppercase Letter
ValueCountFrequency (%)
A 39
 
10.3%
H 35
 
9.3%
N 33
 
8.7%
M 27
 
7.1%
S 27
 
7.1%
E 24
 
6.3%
O 23
 
6.1%
J 22
 
5.8%
L 22
 
5.8%
I 20
 
5.3%
Other values (14) 106
28.0%
Decimal Number
ValueCountFrequency (%)
1 29
24.8%
2 22
18.8%
0 12
10.3%
4 10
 
8.5%
3 10
 
8.5%
6 8
 
6.8%
5 8
 
6.8%
8 7
 
6.0%
7 6
 
5.1%
9 5
 
4.3%
Other Punctuation
ValueCountFrequency (%)
& 25
33.3%
. 16
21.3%
, 14
18.7%
# 12
16.0%
' 7
 
9.3%
/ 1
 
1.3%
Math Symbol
ValueCountFrequency (%)
> 1
50.0%
< 1
50.0%
Space Separator
ValueCountFrequency (%)
345
100.0%
Open Punctuation
ValueCountFrequency (%)
( 209
100.0%
Close Punctuation
ValueCountFrequency (%)
) 209
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%
Other Number
ValueCountFrequency (%)
₂ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12290
88.0%
Common 971
 
7.0%
Latin 692
 
5.0%
Han 12
 
0.1%
Greek 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
어 799
 
6.5%
헤 765
 
6.2%
이 382
 
3.1%
스 330
 
2.7%
미 279
 
2.3%
리 276
 
2.2%
일 264
 
2.1%
네 229
 
1.9%
세 171
 
1.4%
용 153
 
1.2%
Other values (594) 8642
70.3%
Latin
ValueCountFrequency (%)
a 49
 
7.1%
i 46
 
6.6%
A 39
 
5.6%
H 35
 
5.1%
l 33
 
4.8%
N 33
 
4.8%
r 28
 
4.0%
M 27
 
3.9%
S 27
 
3.9%
n 26
 
3.8%
Other values (38) 349
50.4%
Common
ValueCountFrequency (%)
345
35.5%
( 209
21.5%
) 209
21.5%
1 29
 
3.0%
& 25
 
2.6%
2 22
 
2.3%
. 16
 
1.6%
, 14
 
1.4%
# 12
 
1.2%
0 12
 
1.2%
Other values (14) 78
 
8.0%
Han
ValueCountFrequency (%)
美 6
50.0%
火 1
 
8.3%
月 1
 
8.3%
木 1
 
8.3%
秀 1
 
8.3%
裝 1
 
8.3%
休 1
 
8.3%
Greek
ValueCountFrequency (%)
π 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12290
88.0%
ASCII 1662
 
11.9%
CJK 12
 
0.1%
None 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
어 799
 
6.5%
헤 765
 
6.2%
이 382
 
3.1%
스 330
 
2.7%
미 279
 
2.3%
리 276
 
2.2%
일 264
 
2.1%
네 229
 
1.9%
세 171
 
1.4%
용 153
 
1.2%
Other values (594) 8642
70.3%
ASCII
ValueCountFrequency (%)
345
20.8%
( 209
 
12.6%
) 209
 
12.6%
a 49
 
2.9%
i 46
 
2.8%
A 39
 
2.3%
H 35
 
2.1%
l 33
 
2.0%
N 33
 
2.0%
1 29
 
1.7%
Other values (61) 635
38.2%
CJK
ValueCountFrequency (%)
美 6
50.0%
火 1
 
8.3%
月 1
 
8.3%
木 1
 
8.3%
秀 1
 
8.3%
裝 1
 
8.3%
休 1
 
8.3%
None
ValueCountFrequency (%)
π 1
50.0%
₂ 1
50.0%

영업소 주소(도로명)
Text

Distinct2307
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
2024-01-28T18:11:20.588882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length54
Mean length36.789941
Min length9

Characters and Unicode

Total characters87045
Distinct characters399
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2278 ?
Unique (%)96.3%

Sample

1st row인천광역시 남동구 남동대로921번길 21 (간석동,(남동대로 921번길 21))
2nd row인천광역시 남동구 경인로644번길 12-1 (간석동)
3rd row인천광역시 남동구 남동대로916번길 83 (간석동)
4th row인천광역시 남동구 만수로71번길 6 (만수동,89,90번지)
5th row인천광역시 남동구 호구포로889번길 16, 3층 (간석동)
ValueCountFrequency (%)
인천광역시 2335
 
14.1%
남동구 2335
 
14.1%
1층 900
 
5.4%
구월동 693
 
4.2%
간석동 452
 
2.7%
만수동 432
 
2.6%
논현동 307
 
1.9%
일부호 293
 
1.8%
2층 289
 
1.7%
서창동 128
 
0.8%
Other values (2361) 8417
50.8%
2024-01-28T18:11:20.991000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
14217
 
16.3%
동 5211
 
6.0%
1 4181
 
4.8%
구 3550
 
4.1%
남 2829
 
3.3%
인 2610
 
3.0%
, 2545
 
2.9%
) 2523
 
2.9%
( 2523
 
2.9%
로 2471
 
2.8%
Other values (389) 44385
51.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 49240
56.6%
Decimal Number 15037
 
17.3%
Space Separator 14217
 
16.3%
Other Punctuation 2554
 
2.9%
Close Punctuation 2523
 
2.9%
Open Punctuation 2523
 
2.9%
Uppercase Letter 458
 
0.5%
Dash Punctuation 397
 
0.5%
Math Symbol 87
 
0.1%
Lowercase Letter 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 5211
 
10.6%
구 3550
 
7.2%
남 2829
 
5.7%
인 2610
 
5.3%
로 2471
 
5.0%
시 2445
 
5.0%
천 2430
 
4.9%
역 2394
 
4.9%
광 2352
 
4.8%
호 1914
 
3.9%
Other values (340) 21034
42.7%
Uppercase Letter
ValueCountFrequency (%)
A 69
15.1%
B 67
14.6%
E 65
14.2%
C 53
11.6%
L 49
10.7%
R 34
7.4%
P 34
7.4%
H 15
 
3.3%
V 13
 
2.8%
G 12
 
2.6%
Other values (14) 47
10.3%
Decimal Number
ValueCountFrequency (%)
1 4181
27.8%
2 2309
15.4%
0 1729
11.5%
3 1410
 
9.4%
5 1137
 
7.6%
4 1089
 
7.2%
6 966
 
6.4%
7 874
 
5.8%
8 701
 
4.7%
9 641
 
4.3%
Other Punctuation
ValueCountFrequency (%)
, 2545
99.6%
@ 5
 
0.2%
/ 3
 
0.1%
. 1
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
e 3
33.3%
r 2
22.2%
w 2
22.2%
o 2
22.2%
Math Symbol
ValueCountFrequency (%)
> 31
35.6%
< 31
35.6%
~ 25
28.7%
Space Separator
ValueCountFrequency (%)
14217
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2523
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2523
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 397
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 49238
56.6%
Common 37338
42.9%
Latin 467
 
0.5%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 5211
 
10.6%
구 3550
 
7.2%
남 2829
 
5.7%
인 2610
 
5.3%
로 2471
 
5.0%
시 2445
 
5.0%
천 2430
 
4.9%
역 2394
 
4.9%
광 2352
 
4.8%
호 1914
 
3.9%
Other values (339) 21032
42.7%
Latin
ValueCountFrequency (%)
A 69
14.8%
B 67
14.3%
E 65
13.9%
C 53
11.3%
L 49
10.5%
R 34
7.3%
P 34
7.3%
H 15
 
3.2%
V 13
 
2.8%
G 12
 
2.6%
Other values (18) 56
12.0%
Common
ValueCountFrequency (%)
14217
38.1%
1 4181
 
11.2%
, 2545
 
6.8%
) 2523
 
6.8%
( 2523
 
6.8%
2 2309
 
6.2%
0 1729
 
4.6%
3 1410
 
3.8%
5 1137
 
3.0%
4 1089
 
2.9%
Other values (11) 3675
 
9.8%
Han
ValueCountFrequency (%)
內 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 49238
56.6%
ASCII 37805
43.4%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
14217
37.6%
1 4181
 
11.1%
, 2545
 
6.7%
) 2523
 
6.7%
( 2523
 
6.7%
2 2309
 
6.1%
0 1729
 
4.6%
3 1410
 
3.7%
5 1137
 
3.0%
4 1089
 
2.9%
Other values (39) 4142
 
11.0%
Hangul
ValueCountFrequency (%)
동 5211
 
10.6%
구 3550
 
7.2%
남 2829
 
5.7%
인 2610
 
5.3%
로 2471
 
5.0%
시 2445
 
5.0%
천 2430
 
4.9%
역 2394
 
4.9%
광 2352
 
4.8%
호 1914
 
3.9%
Other values (339) 21032
42.7%
CJK
ValueCountFrequency (%)
內 2
100.0%

영업소 주소(지번)
Text

Distinct2130
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
2024-01-28T18:11:21.266040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length45
Mean length26.801775
Min length9

Characters and Unicode

Total characters63413
Distinct characters378
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2003 ?
Unique (%)84.7%

Sample

1st row인천광역시 남동구 간석동 315-6 (남동대로 921번길 21)
2nd row인천광역시 남동구 간석동 110-4
3rd row인천광역시 남동구 간석동 124-13
4th row인천광역시 남동구 만수동 5-89 89,90번지
5th row인천광역시 남동구 간석동 916-12
ValueCountFrequency (%)
인천광역시 2365
19.2%
남동구 2365
19.2%
구월동 763
 
6.2%
만수동 524
 
4.3%
간석동 507
 
4.1%
논현동 331
 
2.7%
서창동 130
 
1.1%
1층일부 116
 
0.9%
1층 112
 
0.9%
상가동 80
 
0.7%
Other values (2742) 5008
40.7%
2024-01-28T18:11:21.661092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11657
18.4%
동 4996
 
7.9%
1 3836
 
6.0%
구 3212
 
5.1%
시 2466
 
3.9%
남 2458
 
3.9%
인 2405
 
3.8%
천 2382
 
3.8%
광 2382
 
3.8%
역 2366
 
3.7%
Other values (368) 25253
39.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 35542
56.0%
Decimal Number 13639
 
21.5%
Space Separator 11657
 
18.4%
Dash Punctuation 1958
 
3.1%
Open Punctuation 179
 
0.3%
Close Punctuation 179
 
0.3%
Uppercase Letter 177
 
0.3%
Other Punctuation 51
 
0.1%
Math Symbol 22
 
< 0.1%
Lowercase Letter 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 4996
14.1%
구 3212
 
9.0%
시 2466
 
6.9%
남 2458
 
6.9%
인 2405
 
6.8%
천 2382
 
6.7%
광 2382
 
6.7%
역 2366
 
6.7%
호 867
 
2.4%
월 832
 
2.3%
Other values (325) 11176
31.4%
Uppercase Letter
ValueCountFrequency (%)
B 30
16.9%
A 28
15.8%
C 20
11.3%
L 19
10.7%
H 15
8.5%
V 13
7.3%
G 12
 
6.8%
S 8
 
4.5%
T 8
 
4.5%
P 4
 
2.3%
Other values (8) 20
11.3%
Decimal Number
ValueCountFrequency (%)
1 3836
28.1%
2 1658
12.2%
0 1312
 
9.6%
3 1301
 
9.5%
4 1148
 
8.4%
6 1055
 
7.7%
5 961
 
7.0%
7 882
 
6.5%
9 759
 
5.6%
8 727
 
5.3%
Other Punctuation
ValueCountFrequency (%)
, 41
80.4%
@ 6
 
11.8%
/ 3
 
5.9%
. 1
 
2.0%
Lowercase Letter
ValueCountFrequency (%)
e 3
33.3%
r 2
22.2%
w 2
22.2%
o 2
22.2%
Math Symbol
ValueCountFrequency (%)
~ 20
90.9%
< 1
 
4.5%
> 1
 
4.5%
Space Separator
ValueCountFrequency (%)
11657
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1958
100.0%
Open Punctuation
ValueCountFrequency (%)
( 179
100.0%
Close Punctuation
ValueCountFrequency (%)
) 179
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 35540
56.0%
Common 27685
43.7%
Latin 186
 
0.3%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 4996
14.1%
구 3212
 
9.0%
시 2466
 
6.9%
남 2458
 
6.9%
인 2405
 
6.8%
천 2382
 
6.7%
광 2382
 
6.7%
역 2366
 
6.7%
호 867
 
2.4%
월 832
 
2.3%
Other values (324) 11174
31.4%
Latin
ValueCountFrequency (%)
B 30
16.1%
A 28
15.1%
C 20
10.8%
L 19
10.2%
H 15
8.1%
V 13
7.0%
G 12
 
6.5%
S 8
 
4.3%
T 8
 
4.3%
P 4
 
2.2%
Other values (12) 29
15.6%
Common
ValueCountFrequency (%)
11657
42.1%
1 3836
 
13.9%
- 1958
 
7.1%
2 1658
 
6.0%
0 1312
 
4.7%
3 1301
 
4.7%
4 1148
 
4.1%
6 1055
 
3.8%
5 961
 
3.5%
7 882
 
3.2%
Other values (11) 1917
 
6.9%
Han
ValueCountFrequency (%)
內 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 35540
56.0%
ASCII 27871
44.0%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11657
41.8%
1 3836
 
13.8%
- 1958
 
7.0%
2 1658
 
5.9%
0 1312
 
4.7%
3 1301
 
4.7%
4 1148
 
4.1%
6 1055
 
3.8%
5 961
 
3.4%
7 882
 
3.2%
Other values (33) 2103
 
7.5%
Hangul
ValueCountFrequency (%)
동 4996
14.1%
구 3212
 
9.0%
시 2466
 
6.9%
남 2458
 
6.9%
인 2405
 
6.8%
천 2382
 
6.7%
광 2382
 
6.7%
역 2366
 
6.7%
호 867
 
2.4%
월 832
 
2.3%
Other values (324) 11174
31.4%
CJK
ValueCountFrequency (%)
內 2
100.0%

소재지전화
Text

MISSING 

Distinct1297
Distinct (%)98.9%
Missing1055
Missing (%)44.6%
Memory size18.6 KiB
2024-01-28T18:11:21.885261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.047292
Min length11

Characters and Unicode

Total characters15794
Distinct characters11
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

Unique1283 ?
Unique (%)97.9%

Sample

1st row032-428-7779
2nd row032-434-5330
3rd row032-434-5437
4th row032-467-9962
5th row032-435-0113
ValueCountFrequency (%)
032-423-7715 2
 
0.2%
032-442-4207 2
 
0.2%
032-423-0843 2
 
0.2%
032-427-9000 2
 
0.2%
032-446-6484 2
 
0.2%
032-465-7244 2
 
0.2%
032-421-5050 2
 
0.2%
032-525-1640 2
 
0.2%
032-433-4448 2
 
0.2%
032-461-4780 2
 
0.2%
Other values (1287) 1291
98.5%
2024-01-28T18:11:22.202827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 2622
16.6%
2 2398
15.2%
3 2143
13.6%
0 2108
13.3%
4 1807
11.4%
6 1108
7.0%
7 863
 
5.5%
5 761
 
4.8%
1 731
 
4.6%
8 683
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13172
83.4%
Dash Punctuation 2622
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 2398
18.2%
3 2143
16.3%
0 2108
16.0%
4 1807
13.7%
6 1108
8.4%
7 863
 
6.6%
5 761
 
5.8%
1 731
 
5.5%
8 683
 
5.2%
9 570
 
4.3%
Dash Punctuation
ValueCountFrequency (%)
- 2622
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15794
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 2622
16.6%
2 2398
15.2%
3 2143
13.6%
0 2108
13.3%
4 1807
11.4%
6 1108
7.0%
7 863
 
5.5%
5 761
 
4.8%
1 731
 
4.6%
8 683
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15794
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 2622
16.6%
2 2398
15.2%
3 2143
13.6%
0 2108
13.3%
4 1807
11.4%
6 1108
7.0%
7 863
 
5.5%
5 761
 
4.8%
1 731
 
4.6%
8 683
 
4.3%

Interactions

2024-01-28T18:11:19.201585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T18:11:22.280190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종명
연번1.0000.960
업종명0.9601.000
2024-01-28T18:11:22.349237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종명
연번1.0000.796
업종명0.7961.000

Missing values

2024-01-28T18:11:19.288467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T18:11:19.378149image/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

연번업종명업소명영업소 주소(도로명)영업소 주소(지번)소재지전화
01숙박업(일반)주얼리 모텔인천광역시 남동구 남동대로921번길 21 (간석동,(남동대로 921번길 21))인천광역시 남동구 간석동 315-6 (남동대로 921번길 21)032-428-7779
12숙박업(일반)화승여관인천광역시 남동구 경인로644번길 12-1 (간석동)인천광역시 남동구 간석동 110-4032-434-5330
23숙박업(일반)산장여인숙인천광역시 남동구 남동대로916번길 83 (간석동)인천광역시 남동구 간석동 124-13032-434-5437
34숙박업(일반)옥수장여관인천광역시 남동구 만수로71번길 6 (만수동,89,90번지)인천광역시 남동구 만수동 5-89 89,90번지032-467-9962
45숙박업(일반)광명장 여관인천광역시 남동구 호구포로889번길 16, 3층 (간석동)인천광역시 남동구 간석동 916-12032-435-0113
56숙박업(일반)명성여관인천광역시 남동구 하촌로70번길 73 (만수동)인천광역시 남동구 만수동 961-22032-461-2237
67숙박업(일반)청운모텔인천광역시 남동구 구월말로 118 (만수동)인천광역시 남동구 만수동 896032-462-0285
78숙박업(일반)렉스리빙텔인천광역시 남동구 남동대로916번길 89 (간석동)인천광역시 남동구 간석동 124-4032-438-9700
89숙박업(일반)도원장인천광역시 남동구 남동대로921번길 23 (간석동)인천광역시 남동구 간석동 315-1032-424-5297
910숙박업(일반)새여인숙인천광역시 남동구 백범로214번길 6-6 (만수동,(백범로214번길 6-6))인천광역시 남동구 만수동 861-1 (백범로214번길 6-6)032-463-5441
연번업종명업소명영업소 주소(도로명)영업소 주소(지번)소재지전화
23562357피부미용업, 네일미용업, 화장ㆍ분장 미용업바나다네일(BANADA Nail)인천광역시 남동구 선수촌공원로 36, 구월아시아드더블루시티 지하층 B14호 (구월동)인천광역시 남동구 구월동 1527032-466-3620
23572358피부미용업, 네일미용업, 화장ㆍ분장 미용업리즈살롱인천광역시 남동구 용천로 20, 1층 104호 (구월동)인천광역시 남동구 구월동 1225-33 104호<NA>
23582359피부미용업, 네일미용업, 화장ㆍ분장 미용업솔뷰티인천광역시 남동구 서창남로 16-28, 3층 일부호 (서창동)인천광역시 남동구 서창동 723-1 3층일부호<NA>
23592360피부미용업, 네일미용업, 화장ㆍ분장 미용업네일난달라인천광역시 남동구 남동대로733번길 55-6, 1층 101호 (구월동, 도담로즈빌)인천광역시 남동구 구월동 201-196 도담로즈빌<NA>
23602361피부미용업, 네일미용업, 화장ㆍ분장 미용업소솜피부관리소인천광역시 남동구 논고개로123번길 35, 칼리오페 3층 A315호 일부호 (논현동)인천광역시 남동구 논현동 632-1 칼리오페<NA>
23612362피부미용업, 네일미용업, 화장ㆍ분장 미용업프레야인천광역시 남동구 선수촌공원로 26, 2층 211호 (구월동, 두플라스)인천광역시 남동구 구월동 1530 두플라스<NA>
23622363피부미용업, 네일미용업, 화장ㆍ분장 미용업두두네일인천광역시 남동구 서창남순환로215번길 27, 1층 102호 (서창동)인천광역시 남동구 서창동 691-1<NA>
23632364피부미용업, 네일미용업, 화장ㆍ분장 미용업이브로우인천광역시 남동구 논고개로123번길 35, 칼리오페 3층 306호 일부호 (논현동)인천광역시 남동구 논현동 632-1 칼리오페<NA>
23642365피부미용업, 네일미용업, 화장ㆍ분장 미용업틈네일인천광역시 남동구 남동대로799번길 34, D동 303호 (구월동, 신영구월지웰시티푸르지오)인천광역시 남동구 구월동 1608 신영구월지웰시티푸르지오<NA>
23652366피부미용업, 네일미용업, 화장ㆍ분장 미용업뷰티장인인천광역시 남동구 에코중앙로 165, 에코메트로7단지상가 204호 (논현동)인천광역시 남동구 논현동 757-1 에코메트로7단지상가 204호<NA>