Overview

Dataset statistics

Number of variables6
Number of observations2374
Missing cells1146
Missing cells (%)8.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory113.7 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
영업소 주소(도로명) has 28 (1.2%) missing valuesMissing
소재지전화 has 1117 (47.1%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-01-28 09:11:07.068232
Analysis finished2024-01-28 09:11:08.116587
Duration1.05 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct2374
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1187.5
Minimum1
Maximum2374
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.0 KiB
2024-01-28T18:11:08.170851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile119.65
Q1594.25
median1187.5
Q31780.75
95-th percentile2255.35
Maximum2374
Range2373
Interquartile range (IQR)1186.5

Descriptive statistics

Standard deviation685.45909
Coefficient of variation (CV)0.57722871
Kurtosis-1.2
Mean1187.5
Median Absolute Deviation (MAD)593.5
Skewness0
Sum2819125
Variance469854.17
MonotonicityStrictly increasing
2024-01-28T18:11:08.275214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
1579 1
 
< 0.1%
1581 1
 
< 0.1%
1582 1
 
< 0.1%
1583 1
 
< 0.1%
1584 1
 
< 0.1%
1585 1
 
< 0.1%
1586 1
 
< 0.1%
1587 1
 
< 0.1%
1588 1
 
< 0.1%
Other values (2364) 2364
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 (%)
2374 1
< 0.1%
2373 1
< 0.1%
2372 1
< 0.1%
2371 1
< 0.1%
2370 1
< 0.1%
2369 1
< 0.1%
2368 1
< 0.1%
2367 1
< 0.1%
2366 1
< 0.1%
2365 1
< 0.1%

업종명
Categorical

HIGH CORRELATION 

Distinct22
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size18.7 KiB
일반미용업
841 
미용업
270 
피부미용업
227 
세탁업
181 
건물위생관리업
161 
Other values (17)
694 

Length

Max length21
Median length5
Mean length5.5290649
Min length3

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
일반미용업 841
35.4%
미용업 270
 
11.4%
피부미용업 227
 
9.6%
세탁업 181
 
7.6%
건물위생관리업 161
 
6.8%
네일미용업 160
 
6.7%
이용업 117
 
4.9%
숙박업(일반) 78
 
3.3%
종합미용업 60
 
2.5%
네일미용업+화장ㆍ분장 미용업 50
 
2.1%
Other values (12) 229
 
9.6%

Length

2024-01-28T18:11:08.382810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반미용업 841
33.2%
미용업 429
16.9%
피부미용업 227
 
9.0%
세탁업 181
 
7.1%
건물위생관리업 161
 
6.4%
네일미용업 160
 
6.3%
이용업 117
 
4.6%
숙박업(일반 78
 
3.1%
종합미용업 60
 
2.4%
네일미용업+화장ㆍ분장 50
 
2.0%
Other values (12) 229
 
9.0%

업소명
Text

Distinct2253
Distinct (%)94.9%
Missing0
Missing (%)0.0%
Memory size18.7 KiB
2024-01-28T18:11:08.630670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length24
Mean length5.8727885
Min length1

Characters and Unicode

Total characters13942
Distinct characters690
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

Unique2163 ?
Unique (%)91.1%

Sample

1st row주얼리 모텔
2nd row화승여관
3rd row산장여인숙
4th row옥수장여관
5th row광명장 여관
ValueCountFrequency (%)
헤어 36
 
1.3%
주식회사 32
 
1.2%
미용실 14
 
0.5%
네일 11
 
0.4%
구월점 8
 
0.3%
hair 8
 
0.3%
제이헤어 7
 
0.3%
로이드밤 7
 
0.3%
nail 7
 
0.3%
살롱 7
 
0.3%
Other values (2392) 2591
95.0%
2024-01-28T18:11:09.010992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
어 795
 
5.7%
헤 768
 
5.5%
이 364
 
2.6%
356
 
2.6%
스 322
 
2.3%
미 279
 
2.0%
리 273
 
2.0%
일 266
 
1.9%
네 239
 
1.7%
( 203
 
1.5%
Other values (680) 10077
72.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12314
88.3%
Space Separator 356
 
2.6%
Uppercase Letter 332
 
2.4%
Lowercase Letter 309
 
2.2%
Open Punctuation 203
 
1.5%
Close Punctuation 203
 
1.5%
Decimal Number 126
 
0.9%
Other Punctuation 82
 
0.6%
Dash Punctuation 10
 
0.1%
Connector Punctuation 4
 
< 0.1%
Other values (2) 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
어 795
 
6.5%
헤 768
 
6.2%
이 364
 
3.0%
스 322
 
2.6%
미 279
 
2.3%
리 273
 
2.2%
일 266
 
2.2%
네 239
 
1.9%
세 165
 
1.3%
주 156
 
1.3%
Other values (606) 8687
70.5%
Lowercase Letter
ValueCountFrequency (%)
a 45
14.6%
i 40
12.9%
l 34
11.0%
n 28
9.1%
r 26
8.4%
o 24
7.8%
s 19
 
6.1%
e 19
 
6.1%
h 12
 
3.9%
y 11
 
3.6%
Other values (15) 51
16.5%
Uppercase Letter
ValueCountFrequency (%)
H 31
 
9.3%
A 31
 
9.3%
N 27
 
8.1%
M 25
 
7.5%
S 24
 
7.2%
E 21
 
6.3%
O 19
 
5.7%
J 18
 
5.4%
L 18
 
5.4%
B 18
 
5.4%
Other values (15) 100
30.1%
Decimal Number
ValueCountFrequency (%)
1 28
22.2%
2 22
17.5%
0 14
11.1%
5 13
10.3%
4 12
9.5%
3 10
 
7.9%
6 9
 
7.1%
8 7
 
5.6%
9 6
 
4.8%
7 5
 
4.0%
Other Punctuation
ValueCountFrequency (%)
& 29
35.4%
, 21
25.6%
. 15
18.3%
# 11
 
13.4%
' 5
 
6.1%
: 1
 
1.2%
Math Symbol
ValueCountFrequency (%)
> 1
50.0%
< 1
50.0%
Space Separator
ValueCountFrequency (%)
356
100.0%
Open Punctuation
ValueCountFrequency (%)
( 203
100.0%
Close Punctuation
ValueCountFrequency (%)
) 203
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%
Other Number
ValueCountFrequency (%)
₂ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12305
88.3%
Common 987
 
7.1%
Latin 640
 
4.6%
Han 9
 
0.1%
Greek 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
어 795
 
6.5%
헤 768
 
6.2%
이 364
 
3.0%
스 322
 
2.6%
미 279
 
2.3%
리 273
 
2.2%
일 266
 
2.2%
네 239
 
1.9%
세 165
 
1.3%
주 156
 
1.3%
Other values (601) 8678
70.5%
Latin
ValueCountFrequency (%)
a 45
 
7.0%
i 40
 
6.2%
l 34
 
5.3%
H 31
 
4.8%
A 31
 
4.8%
n 28
 
4.4%
N 27
 
4.2%
r 26
 
4.1%
M 25
 
3.9%
o 24
 
3.8%
Other values (39) 329
51.4%
Common
ValueCountFrequency (%)
356
36.1%
( 203
20.6%
) 203
20.6%
& 29
 
2.9%
1 28
 
2.8%
2 22
 
2.2%
, 21
 
2.1%
. 15
 
1.5%
0 14
 
1.4%
5 13
 
1.3%
Other values (14) 83
 
8.4%
Han
ValueCountFrequency (%)
美 5
55.6%
月 1
 
11.1%
火 1
 
11.1%
木 1
 
11.1%
裝 1
 
11.1%
Greek
ValueCountFrequency (%)
π 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12305
88.3%
ASCII 1626
 
11.7%
CJK 9
 
0.1%
None 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
어 795
 
6.5%
헤 768
 
6.2%
이 364
 
3.0%
스 322
 
2.6%
미 279
 
2.3%
리 273
 
2.2%
일 266
 
2.2%
네 239
 
1.9%
세 165
 
1.3%
주 156
 
1.3%
Other values (601) 8678
70.5%
ASCII
ValueCountFrequency (%)
356
21.9%
( 203
 
12.5%
) 203
 
12.5%
a 45
 
2.8%
i 40
 
2.5%
l 34
 
2.1%
H 31
 
1.9%
A 31
 
1.9%
& 29
 
1.8%
n 28
 
1.7%
Other values (62) 626
38.5%
CJK
ValueCountFrequency (%)
美 5
55.6%
月 1
 
11.1%
火 1
 
11.1%
木 1
 
11.1%
裝 1
 
11.1%
None
ValueCountFrequency (%)
π 1
50.0%
₂ 1
50.0%

영업소 주소(도로명)
Text

MISSING 

Distinct2319
Distinct (%)98.8%
Missing28
Missing (%)1.2%
Memory size18.7 KiB
2024-01-28T18:11:09.270650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length53
Mean length37.316283
Min length21

Characters and Unicode

Total characters87544
Distinct characters401
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

Unique2293 ?
Unique (%)97.7%

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 2346
 
14.1%
남동구 2346
 
14.1%
1층 920
 
5.5%
구월동 718
 
4.3%
만수동 441
 
2.6%
간석동 437
 
2.6%
논현동 306
 
1.8%
일부호 297
 
1.8%
2층 296
 
1.8%
서창동 129
 
0.8%
Other values (2383) 8451
50.6%
2024-01-28T18:11:09.647933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
14343
 
16.4%
동 5243
 
6.0%
1 4211
 
4.8%
구 3579
 
4.1%
남 2846
 
3.3%
인 2616
 
3.0%
) 2572
 
2.9%
( 2572
 
2.9%
, 2552
 
2.9%
로 2478
 
2.8%
Other values (391) 44532
50.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 49623
56.7%
Decimal Number 15194
 
17.4%
Space Separator 14343
 
16.4%
Close Punctuation 2572
 
2.9%
Open Punctuation 2572
 
2.9%
Other Punctuation 2560
 
2.9%
Dash Punctuation 399
 
0.5%
Uppercase Letter 240
 
0.3%
Math Symbol 25
 
< 0.1%
Lowercase Letter 16
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 5243
 
10.6%
구 3579
 
7.2%
남 2846
 
5.7%
인 2616
 
5.3%
로 2478
 
5.0%
시 2465
 
5.0%
천 2442
 
4.9%
역 2402
 
4.8%
광 2363
 
4.8%
호 2003
 
4.0%
Other values (340) 21186
42.7%
Uppercase Letter
ValueCountFrequency (%)
B 69
28.7%
A 37
15.4%
C 24
 
10.0%
L 17
 
7.1%
V 13
 
5.4%
H 13
 
5.4%
G 12
 
5.0%
S 9
 
3.8%
T 8
 
3.3%
D 6
 
2.5%
Other values (14) 32
13.3%
Decimal Number
ValueCountFrequency (%)
1 4211
27.7%
2 2332
15.3%
0 1751
11.5%
3 1431
 
9.4%
5 1164
 
7.7%
4 1088
 
7.2%
6 971
 
6.4%
7 899
 
5.9%
8 696
 
4.6%
9 651
 
4.3%
Lowercase Letter
ValueCountFrequency (%)
e 4
25.0%
r 3
18.8%
o 3
18.8%
w 2
12.5%
i 1
 
6.2%
n 1
 
6.2%
a 1
 
6.2%
s 1
 
6.2%
Other Punctuation
ValueCountFrequency (%)
, 2552
99.7%
@ 5
 
0.2%
/ 2
 
0.1%
. 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
14343
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2572
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2572
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 399
100.0%
Math Symbol
ValueCountFrequency (%)
~ 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 49621
56.7%
Common 37665
43.0%
Latin 256
 
0.3%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 5243
 
10.6%
구 3579
 
7.2%
남 2846
 
5.7%
인 2616
 
5.3%
로 2478
 
5.0%
시 2465
 
5.0%
천 2442
 
4.9%
역 2402
 
4.8%
광 2363
 
4.8%
호 2003
 
4.0%
Other values (339) 21184
42.7%
Latin
ValueCountFrequency (%)
B 69
27.0%
A 37
14.5%
C 24
 
9.4%
L 17
 
6.6%
V 13
 
5.1%
H 13
 
5.1%
G 12
 
4.7%
S 9
 
3.5%
T 8
 
3.1%
D 6
 
2.3%
Other values (22) 48
18.8%
Common
ValueCountFrequency (%)
14343
38.1%
1 4211
 
11.2%
) 2572
 
6.8%
( 2572
 
6.8%
, 2552
 
6.8%
2 2332
 
6.2%
0 1751
 
4.6%
3 1431
 
3.8%
5 1164
 
3.1%
4 1088
 
2.9%
Other values (9) 3649
 
9.7%
Han
ValueCountFrequency (%)
內 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 49621
56.7%
ASCII 37921
43.3%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
14343
37.8%
1 4211
 
11.1%
) 2572
 
6.8%
( 2572
 
6.8%
, 2552
 
6.7%
2 2332
 
6.1%
0 1751
 
4.6%
3 1431
 
3.8%
5 1164
 
3.1%
4 1088
 
2.9%
Other values (41) 3905
 
10.3%
Hangul
ValueCountFrequency (%)
동 5243
 
10.6%
구 3579
 
7.2%
남 2846
 
5.7%
인 2616
 
5.3%
로 2478
 
5.0%
시 2465
 
5.0%
천 2442
 
4.9%
역 2402
 
4.8%
광 2363
 
4.8%
호 2003
 
4.0%
Other values (339) 21184
42.7%
CJK
ValueCountFrequency (%)
內 2
100.0%

영업소 주소(지번)
Text

Distinct2090
Distinct (%)88.1%
Missing1
Missing (%)< 0.1%
Memory size18.7 KiB
2024-01-28T18:11:09.874605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length45
Mean length26.524652
Min length17

Characters and Unicode

Total characters62943
Distinct characters382
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

Unique1944 ?
Unique (%)81.9%

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 2373
19.4%
남동구 2373
19.4%
구월동 781
 
6.4%
만수동 529
 
4.3%
간석동 492
 
4.0%
논현동 327
 
2.7%
서창동 131
 
1.1%
1층일부 112
 
0.9%
1층 108
 
0.9%
상가동 74
 
0.6%
Other values (2721) 4913
40.2%
2024-01-28T18:11:10.226375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11646
18.5%
동 4988
 
7.9%
1 3767
 
6.0%
구 3244
 
5.2%
시 2481
 
3.9%
남 2461
 
3.9%
인 2415
 
3.8%
광 2390
 
3.8%
천 2388
 
3.8%
역 2374
 
3.8%
Other values (372) 24789
39.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 35370
56.2%
Decimal Number 13384
 
21.3%
Space Separator 11646
 
18.5%
Dash Punctuation 1955
 
3.1%
Open Punctuation 171
 
0.3%
Close Punctuation 171
 
0.3%
Uppercase Letter 162
 
0.3%
Other Punctuation 48
 
0.1%
Math Symbol 20
 
< 0.1%
Lowercase Letter 16
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 4988
14.1%
구 3244
 
9.2%
시 2481
 
7.0%
남 2461
 
7.0%
인 2415
 
6.8%
광 2390
 
6.8%
천 2388
 
6.8%
역 2374
 
6.7%
월 857
 
2.4%
호 780
 
2.2%
Other values (326) 10992
31.1%
Uppercase Letter
ValueCountFrequency (%)
B 28
17.3%
A 24
14.8%
C 19
11.7%
L 17
10.5%
H 14
8.6%
V 13
8.0%
G 12
7.4%
T 8
 
4.9%
S 8
 
4.9%
P 3
 
1.9%
Other values (9) 16
9.9%
Decimal Number
ValueCountFrequency (%)
1 3767
28.1%
2 1594
11.9%
3 1275
 
9.5%
0 1266
 
9.5%
4 1115
 
8.3%
6 1054
 
7.9%
5 956
 
7.1%
7 881
 
6.6%
9 759
 
5.7%
8 717
 
5.4%
Lowercase Letter
ValueCountFrequency (%)
e 4
25.0%
r 3
18.8%
o 3
18.8%
w 2
12.5%
n 1
 
6.2%
a 1
 
6.2%
i 1
 
6.2%
s 1
 
6.2%
Other Punctuation
ValueCountFrequency (%)
, 39
81.2%
@ 6
 
12.5%
/ 2
 
4.2%
. 1
 
2.1%
Space Separator
ValueCountFrequency (%)
11646
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1955
100.0%
Open Punctuation
ValueCountFrequency (%)
( 171
100.0%
Close Punctuation
ValueCountFrequency (%)
) 171
100.0%
Math Symbol
ValueCountFrequency (%)
~ 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 35368
56.2%
Common 27395
43.5%
Latin 178
 
0.3%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 4988
14.1%
구 3244
 
9.2%
시 2481
 
7.0%
남 2461
 
7.0%
인 2415
 
6.8%
광 2390
 
6.8%
천 2388
 
6.8%
역 2374
 
6.7%
월 857
 
2.4%
호 780
 
2.2%
Other values (325) 10990
31.1%
Latin
ValueCountFrequency (%)
B 28
15.7%
A 24
13.5%
C 19
10.7%
L 17
9.6%
H 14
7.9%
V 13
7.3%
G 12
 
6.7%
T 8
 
4.5%
S 8
 
4.5%
e 4
 
2.2%
Other values (17) 31
17.4%
Common
ValueCountFrequency (%)
11646
42.5%
1 3767
 
13.8%
- 1955
 
7.1%
2 1594
 
5.8%
3 1275
 
4.7%
0 1266
 
4.6%
4 1115
 
4.1%
6 1054
 
3.8%
5 956
 
3.5%
7 881
 
3.2%
Other values (9) 1886
 
6.9%
Han
ValueCountFrequency (%)
內 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 35368
56.2%
ASCII 27573
43.8%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11646
42.2%
1 3767
 
13.7%
- 1955
 
7.1%
2 1594
 
5.8%
3 1275
 
4.6%
0 1266
 
4.6%
4 1115
 
4.0%
6 1054
 
3.8%
5 956
 
3.5%
7 881
 
3.2%
Other values (36) 2064
 
7.5%
Hangul
ValueCountFrequency (%)
동 4988
14.1%
구 3244
 
9.2%
시 2481
 
7.0%
남 2461
 
7.0%
인 2415
 
6.8%
광 2390
 
6.8%
천 2388
 
6.8%
역 2374
 
6.7%
월 857
 
2.4%
호 780
 
2.2%
Other values (325) 10990
31.1%
CJK
ValueCountFrequency (%)
內 2
100.0%

소재지전화
Text

MISSING 

Distinct1242
Distinct (%)98.8%
Missing1117
Missing (%)47.1%
Memory size18.7 KiB
2024-01-28T18:11:10.442514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.043755
Min length11

Characters and Unicode

Total characters15139
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

Unique1227 ?
Unique (%)97.6%

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%
032-504-6505 2
 
0.2%
032-423-0843 2
 
0.2%
032-446-6484 2
 
0.2%
032-433-3246 2
 
0.2%
032-465-7244 2
 
0.2%
032-421-5050 2
 
0.2%
032-433-4448 2
 
0.2%
032-427-9000 2
 
0.2%
032-464-3625 2
 
0.2%
Other values (1232) 1237
98.4%
2024-01-28T18:11:10.765934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 2514
16.6%
2 2316
15.3%
3 2067
13.7%
0 2019
13.3%
4 1726
11.4%
6 1068
7.1%
7 815
 
5.4%
5 726
 
4.8%
1 689
 
4.6%
8 654
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12625
83.4%
Dash Punctuation 2514
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 2316
18.3%
3 2067
16.4%
0 2019
16.0%
4 1726
13.7%
6 1068
8.5%
7 815
 
6.5%
5 726
 
5.8%
1 689
 
5.5%
8 654
 
5.2%
9 545
 
4.3%
Dash Punctuation
ValueCountFrequency (%)
- 2514
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15139
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 2514
16.6%
2 2316
15.3%
3 2067
13.7%
0 2019
13.3%
4 1726
11.4%
6 1068
7.1%
7 815
 
5.4%
5 726
 
4.8%
1 689
 
4.6%
8 654
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15139
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 2514
16.6%
2 2316
15.3%
3 2067
13.7%
0 2019
13.3%
4 1726
11.4%
6 1068
7.1%
7 815
 
5.4%
5 726
 
4.8%
1 689
 
4.6%
8 654
 
4.3%

Interactions

2024-01-28T18:11:07.815412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T18:11:10.841114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종명
연번1.0000.961
업종명0.9611.000
2024-01-28T18:11:10.902202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종명
연번1.0000.799
업종명0.7991.000

Missing values

2024-01-28T18:11:07.905771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T18:11:07.998348image/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.
2024-01-28T18:11:08.074432image/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

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
23642365피부미용업+네일미용업+화장ㆍ분장 미용업리즈살롱인천광역시 남동구 용천로 20, 1층 104호 (구월동)인천광역시 남동구 구월동 1225-33 104호<NA>
23652366피부미용업+네일미용업+화장ㆍ분장 미용업솔뷰티인천광역시 남동구 서창남로 16-28, 3층 일부호 (서창동)인천광역시 남동구 서창동 723-1 3층일부호<NA>
23662367피부미용업+네일미용업+화장ㆍ분장 미용업유니네뷰티인천광역시 남동구 만수로45번길 16, 1층 6호 (만수동)인천광역시 남동구 만수동 72-2 6호<NA>
23672368피부미용업+네일미용업+화장ㆍ분장 미용업소솜피부관리소인천광역시 남동구 논고개로123번길 35, 칼리오페 3층 A315호 일부호 (논현동)인천광역시 남동구 논현동 632-1 칼리오페<NA>
23682369피부미용업+네일미용업+화장ㆍ분장 미용업프레야인천광역시 남동구 선수촌공원로 26, 2층 211호 (구월동, 두플라스)인천광역시 남동구 구월동 1530 두플라스<NA>
23692370피부미용업+네일미용업+화장ㆍ분장 미용업두두네일인천광역시 남동구 서창남순환로215번길 27, 1층 102호 (서창동)인천광역시 남동구 서창동 691-1<NA>
23702371피부미용업+네일미용업+화장ㆍ분장 미용업틈네일인천광역시 남동구 남동대로799번길 34, D동 303호 (구월동, 신영구월지웰시티푸르지오)인천광역시 남동구 구월동 1608 신영구월지웰시티푸르지오<NA>
23712372피부미용업+네일미용업+화장ㆍ분장 미용업뷰티장인인천광역시 남동구 에코중앙로 165, 에코메트로7단지상가 204호 (논현동)인천광역시 남동구 논현동 757-1 에코메트로7단지상가 204호<NA>
23722373피부미용업+네일미용업+화장ㆍ분장 미용업챙쓰네일인천광역시 남동구 남동대로799번길 34, 판매시설동 B동 220호 (구월동, 신영구월지웰시티푸르지오)인천광역시 남동구 구월동 1608 신영구월지웰시티푸르지오<NA>
23732374피부미용업+네일미용업+화장ㆍ분장 미용업헬로네일인천광역시 남동구 예술로 198, CGV 홈플러스 1층 35호 (구월동)인천광역시 남동구 구월동 1130 CGV 홈플러스<NA>