Overview

Dataset statistics

Number of variables6
Number of observations3191
Missing cells1051
Missing cells (%)5.5%
Duplicate rows3
Duplicate rows (%)0.1%
Total size in memory149.7 KiB
Average record size in memory48.0 B

Variable types

Categorical2
Text4

Dataset

Description경상북도 포항시 관내 공중위생업 현황에 관한 데이터로 공중위생업 업종, 업소명, 소재지도로명주소, 전화번호 등의 정보를 제공합니다.
Author경상북도 포항시
URLhttps://www.data.go.kr/data/15006900/fileData.do

Alerts

Dataset has 3 (0.1%) duplicate rowsDuplicates
데이터기준일자 is highly imbalanced (99.6%)Imbalance
전화번호 has 1051 (32.9%) missing valuesMissing

Reproduction

Analysis started2023-12-12 16:31:11.687211
Analysis finished2023-12-12 16:31:12.739824
Duration1.05 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

Distinct22
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size25.1 KiB
미용업
812 
일반미용업
619 
숙박업(일반)
346 
세탁업
296 
이용업
233 
Other values (17)
885 

Length

Max length23
Median length19
Mean length4.8806017
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
미용업 812
25.4%
일반미용업 619
19.4%
숙박업(일반) 346
10.8%
세탁업 296
 
9.3%
이용업 233
 
7.3%
피부미용업 233
 
7.3%
건물위생관리업 162
 
5.1%
네일미용업 137
 
4.3%
목욕장업 106
 
3.3%
종합미용업 90
 
2.8%
Other values (12) 157
 
4.9%

Length

2023-12-13T01:31:12.814591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
미용업 896
26.2%
일반미용업 678
19.8%
숙박업(일반 346
 
10.1%
세탁업 296
 
8.7%
피부미용업 283
 
8.3%
이용업 233
 
6.8%
네일미용업 217
 
6.3%
건물위생관리업 162
 
4.7%
목욕장업 106
 
3.1%
종합미용업 90
 
2.6%
Other values (2) 111
 
3.2%

업소명
Text

Distinct3007
Distinct (%)94.2%
Missing0
Missing (%)0.0%
Memory size25.1 KiB
2023-12-13T01:31:13.114465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length31
Mean length5.8279536
Min length1

Characters and Unicode

Total characters18597
Distinct characters745
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

Unique2878 ?
Unique (%)90.2%

Sample

1st row배넷머리
2nd row스윗데이즈펜션
3rd row극동장여관
4th row새서울여관
5th row코모도호텔포항송도
ValueCountFrequency (%)
미용실 31
 
0.8%
헤어 24
 
0.6%
hair 20
 
0.5%
네일 14
 
0.4%
주식회사 14
 
0.4%
세탁소 11
 
0.3%
헤어샵 9
 
0.2%
에스테틱 9
 
0.2%
salon 9
 
0.2%
모텔 9
 
0.2%
Other values (3191) 3550
95.9%
2023-12-13T01:31:13.919023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
어 864
 
4.6%
헤 820
 
4.4%
512
 
2.8%
용 505
 
2.7%
이 504
 
2.7%
미 473
 
2.5%
소 394
 
2.1%
스 382
 
2.1%
실 322
 
1.7%
리 319
 
1.7%
Other values (735) 13502
72.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15960
85.8%
Lowercase Letter 727
 
3.9%
Uppercase Letter 629
 
3.4%
Space Separator 512
 
2.8%
Close Punctuation 263
 
1.4%
Open Punctuation 261
 
1.4%
Decimal Number 129
 
0.7%
Other Punctuation 104
 
0.6%
Dash Punctuation 5
 
< 0.1%
Math Symbol 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
어 864
 
5.4%
헤 820
 
5.1%
용 505
 
3.2%
이 504
 
3.2%
미 473
 
3.0%
소 394
 
2.5%
스 382
 
2.4%
실 322
 
2.0%
리 319
 
2.0%
세 266
 
1.7%
Other values (659) 11111
69.6%
Uppercase Letter
ValueCountFrequency (%)
A 57
 
9.1%
H 50
 
7.9%
S 48
 
7.6%
N 42
 
6.7%
L 41
 
6.5%
M 41
 
6.5%
I 39
 
6.2%
O 38
 
6.0%
T 36
 
5.7%
J 30
 
4.8%
Other values (16) 207
32.9%
Lowercase Letter
ValueCountFrequency (%)
a 96
13.2%
e 85
11.7%
l 78
10.7%
i 68
9.4%
o 55
 
7.6%
n 52
 
7.2%
r 43
 
5.9%
y 40
 
5.5%
s 34
 
4.7%
h 33
 
4.5%
Other values (15) 143
19.7%
Decimal Number
ValueCountFrequency (%)
1 37
28.7%
2 35
27.1%
5 11
 
8.5%
9 8
 
6.2%
3 8
 
6.2%
4 7
 
5.4%
6 7
 
5.4%
0 7
 
5.4%
7 5
 
3.9%
8 4
 
3.1%
Other Punctuation
ValueCountFrequency (%)
& 36
34.6%
# 27
26.0%
. 23
22.1%
, 11
 
10.6%
: 3
 
2.9%
' 2
 
1.9%
/ 1
 
1.0%
! 1
 
1.0%
Math Symbol
ValueCountFrequency (%)
+ 3
60.0%
= 2
40.0%
Space Separator
ValueCountFrequency (%)
512
100.0%
Close Punctuation
ValueCountFrequency (%)
) 263
100.0%
Open Punctuation
ValueCountFrequency (%)
( 261
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15953
85.8%
Latin 1356
 
7.3%
Common 1281
 
6.9%
Han 7
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
어 864
 
5.4%
헤 820
 
5.1%
용 505
 
3.2%
이 504
 
3.2%
미 473
 
3.0%
소 394
 
2.5%
스 382
 
2.4%
실 322
 
2.0%
리 319
 
2.0%
세 266
 
1.7%
Other values (653) 11104
69.6%
Latin
ValueCountFrequency (%)
a 96
 
7.1%
e 85
 
6.3%
l 78
 
5.8%
i 68
 
5.0%
A 57
 
4.2%
o 55
 
4.1%
n 52
 
3.8%
H 50
 
3.7%
S 48
 
3.5%
r 43
 
3.2%
Other values (41) 724
53.4%
Common
ValueCountFrequency (%)
512
40.0%
) 263
20.5%
( 261
20.4%
1 37
 
2.9%
& 36
 
2.8%
2 35
 
2.7%
# 27
 
2.1%
. 23
 
1.8%
, 11
 
0.9%
5 11
 
0.9%
Other values (15) 65
 
5.1%
Han
ValueCountFrequency (%)
美 2
28.6%
秀 1
14.3%
日 1
14.3%
月 1
14.3%
手 1
14.3%
作 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15952
85.8%
ASCII 2637
 
14.2%
CJK 7
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
어 864
 
5.4%
헤 820
 
5.1%
용 505
 
3.2%
이 504
 
3.2%
미 473
 
3.0%
소 394
 
2.5%
스 382
 
2.4%
실 322
 
2.0%
리 319
 
2.0%
세 266
 
1.7%
Other values (652) 11103
69.6%
ASCII
ValueCountFrequency (%)
512
19.4%
) 263
 
10.0%
( 261
 
9.9%
a 96
 
3.6%
e 85
 
3.2%
l 78
 
3.0%
i 68
 
2.6%
A 57
 
2.2%
o 55
 
2.1%
n 52
 
2.0%
Other values (66) 1110
42.1%
CJK
ValueCountFrequency (%)
美 2
28.6%
秀 1
14.3%
日 1
14.3%
月 1
14.3%
手 1
14.3%
作 1
14.3%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%

소재지도로명주소
Text

Distinct2869
Distinct (%)89.9%
Missing0
Missing (%)0.0%
Memory size25.1 KiB
2023-12-13T01:31:14.273303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length84
Median length55
Mean length29.555312
Min length1

Characters and Unicode

Total characters94311
Distinct characters319
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

Unique2781 ?
Unique (%)87.2%

Sample

1st row
2nd row경상북도 포항시 남구 희망대로 1173-1 (송도동)
3rd row경상북도 포항시 남구 송도로 59 (송도동)
4th row경상북도 포항시 남구 오천읍 정몽주로 555-1
5th row경상북도 포항시 남구 송도로 71, 코모도비취관광호텔 A동 (송도동)
ValueCountFrequency (%)
경상북도 2958
 
14.4%
포항시 2958
 
14.4%
북구 1515
 
7.4%
남구 1443
 
7.0%
1층 1127
 
5.5%
오천읍 310
 
1.5%
2층 211
 
1.0%
죽도동 201
 
1.0%
장성동 188
 
0.9%
해도동 161
 
0.8%
Other values (2186) 9444
46.0%
2023-12-13T01:31:14.780263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17791
 
18.9%
1 4527
 
4.8%
북 4478
 
4.7%
도 3885
 
4.1%
상 3535
 
3.7%
포 3177
 
3.4%
구 3106
 
3.3%
항 3026
 
3.2%
시 3012
 
3.2%
경 2971
 
3.2%
Other values (309) 44803
47.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 53845
57.1%
Space Separator 17791
 
18.9%
Decimal Number 14577
 
15.5%
Open Punctuation 2480
 
2.6%
Close Punctuation 2479
 
2.6%
Other Punctuation 2124
 
2.3%
Dash Punctuation 847
 
0.9%
Uppercase Letter 116
 
0.1%
Math Symbol 46
 
< 0.1%
Lowercase Letter 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
북 4478
 
8.3%
도 3885
 
7.2%
상 3535
 
6.6%
포 3177
 
5.9%
구 3106
 
5.8%
항 3026
 
5.6%
시 3012
 
5.6%
경 2971
 
5.5%
동 2745
 
5.1%
로 2684
 
5.0%
Other values (270) 21226
39.4%
Uppercase Letter
ValueCountFrequency (%)
B 29
25.0%
A 27
23.3%
C 14
12.1%
K 9
 
7.8%
S 7
 
6.0%
E 6
 
5.2%
W 5
 
4.3%
H 4
 
3.4%
I 3
 
2.6%
V 3
 
2.6%
Other values (6) 9
 
7.8%
Decimal Number
ValueCountFrequency (%)
1 4527
31.1%
2 2074
14.2%
3 1409
 
9.7%
0 1199
 
8.2%
4 1162
 
8.0%
5 1060
 
7.3%
6 940
 
6.4%
7 839
 
5.8%
8 699
 
4.8%
9 668
 
4.6%
Other Punctuation
ValueCountFrequency (%)
, 2113
99.5%
. 8
 
0.4%
/ 2
 
0.1%
& 1
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
i 2
33.3%
n 2
33.3%
x 1
16.7%
y 1
16.7%
Space Separator
ValueCountFrequency (%)
17791
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2480
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2479
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 847
100.0%
Math Symbol
ValueCountFrequency (%)
~ 46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 53845
57.1%
Common 40344
42.8%
Latin 122
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
북 4478
 
8.3%
도 3885
 
7.2%
상 3535
 
6.6%
포 3177
 
5.9%
구 3106
 
5.8%
항 3026
 
5.6%
시 3012
 
5.6%
경 2971
 
5.5%
동 2745
 
5.1%
로 2684
 
5.0%
Other values (270) 21226
39.4%
Latin
ValueCountFrequency (%)
B 29
23.8%
A 27
22.1%
C 14
11.5%
K 9
 
7.4%
S 7
 
5.7%
E 6
 
4.9%
W 5
 
4.1%
H 4
 
3.3%
I 3
 
2.5%
V 3
 
2.5%
Other values (10) 15
12.3%
Common
ValueCountFrequency (%)
17791
44.1%
1 4527
 
11.2%
( 2480
 
6.1%
) 2479
 
6.1%
, 2113
 
5.2%
2 2074
 
5.1%
3 1409
 
3.5%
0 1199
 
3.0%
4 1162
 
2.9%
5 1060
 
2.6%
Other values (9) 4050
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 53845
57.1%
ASCII 40466
42.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17791
44.0%
1 4527
 
11.2%
( 2480
 
6.1%
) 2479
 
6.1%
, 2113
 
5.2%
2 2074
 
5.1%
3 1409
 
3.5%
0 1199
 
3.0%
4 1162
 
2.9%
5 1060
 
2.6%
Other values (29) 4172
 
10.3%
Hangul
ValueCountFrequency (%)
북 4478
 
8.3%
도 3885
 
7.2%
상 3535
 
6.6%
포 3177
 
5.9%
구 3106
 
5.8%
항 3026
 
5.6%
시 3012
 
5.6%
경 2971
 
5.5%
동 2745
 
5.1%
로 2684
 
5.0%
Other values (270) 21226
39.4%

소재지지번주소
Text

Distinct3070
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Memory size25.1 KiB
2023-12-13T01:31:15.121231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length80
Median length54
Mean length27.054842
Min length1

Characters and Unicode

Total characters86332
Distinct characters305
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

Unique2962 ?
Unique (%)92.8%

Sample

1st row경상북도 구미시 구평동 451 1층 104호
2nd row경상북도 포항시 남구 송도동 254-368
3rd row경상북도 포항시 남구 송도동 437-4
4th row경상북도 포항시 남구 오천읍 세계리 839-3
5th row경상북도 포항시 남구 송도동 311-268 외1(311-2,코모도비취관광호텔) A동
ValueCountFrequency (%)
경상북도 3189
16.4%
포항시 3188
16.4%
북구 1677
 
8.6%
남구 1511
 
7.8%
1층 791
 
4.1%
오천읍 321
 
1.6%
죽도동 239
 
1.2%
장성동 228
 
1.2%
해도동 186
 
1.0%
두호동 171
 
0.9%
Other values (3385) 7956
40.9%
2023-12-13T01:31:15.675859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19099
22.1%
북 4869
 
5.6%
1 4318
 
5.0%
도 4023
 
4.7%
상 3618
 
4.2%
구 3448
 
4.0%
포 3424
 
4.0%
항 3241
 
3.8%
시 3229
 
3.7%
경 3200
 
3.7%
Other values (295) 33863
39.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 46481
53.8%
Space Separator 19099
22.1%
Decimal Number 16587
 
19.2%
Dash Punctuation 2642
 
3.1%
Close Punctuation 576
 
0.7%
Open Punctuation 576
 
0.7%
Other Punctuation 170
 
0.2%
Uppercase Letter 158
 
0.2%
Math Symbol 34
 
< 0.1%
Lowercase Letter 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
북 4869
 
10.5%
도 4023
 
8.7%
상 3618
 
7.8%
구 3448
 
7.4%
포 3424
 
7.4%
항 3241
 
7.0%
시 3229
 
6.9%
경 3200
 
6.9%
동 2737
 
5.9%
남 1582
 
3.4%
Other values (255) 13110
28.2%
Uppercase Letter
ValueCountFrequency (%)
B 49
31.0%
A 29
18.4%
L 29
18.4%
S 10
 
6.3%
K 10
 
6.3%
C 8
 
5.1%
W 5
 
3.2%
E 4
 
2.5%
D 3
 
1.9%
V 3
 
1.9%
Other values (5) 8
 
5.1%
Decimal Number
ValueCountFrequency (%)
1 4318
26.0%
2 1949
11.8%
3 1774
10.7%
6 1468
 
8.9%
4 1436
 
8.7%
0 1402
 
8.5%
5 1335
 
8.0%
9 1039
 
6.3%
7 1011
 
6.1%
8 855
 
5.2%
Lowercase Letter
ValueCountFrequency (%)
n 3
33.3%
i 2
22.2%
x 1
 
11.1%
y 1
 
11.1%
j 1
 
11.1%
u 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
, 158
92.9%
. 7
 
4.1%
/ 4
 
2.4%
& 1
 
0.6%
Space Separator
ValueCountFrequency (%)
19099
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2642
100.0%
Close Punctuation
ValueCountFrequency (%)
) 576
100.0%
Open Punctuation
ValueCountFrequency (%)
( 576
100.0%
Math Symbol
ValueCountFrequency (%)
~ 34
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 46481
53.8%
Common 39684
46.0%
Latin 167
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
북 4869
 
10.5%
도 4023
 
8.7%
상 3618
 
7.8%
구 3448
 
7.4%
포 3424
 
7.4%
항 3241
 
7.0%
시 3229
 
6.9%
경 3200
 
6.9%
동 2737
 
5.9%
남 1582
 
3.4%
Other values (255) 13110
28.2%
Latin
ValueCountFrequency (%)
B 49
29.3%
A 29
17.4%
L 29
17.4%
S 10
 
6.0%
K 10
 
6.0%
C 8
 
4.8%
W 5
 
3.0%
E 4
 
2.4%
D 3
 
1.8%
V 3
 
1.8%
Other values (11) 17
 
10.2%
Common
ValueCountFrequency (%)
19099
48.1%
1 4318
 
10.9%
- 2642
 
6.7%
2 1949
 
4.9%
3 1774
 
4.5%
6 1468
 
3.7%
4 1436
 
3.6%
0 1402
 
3.5%
5 1335
 
3.4%
9 1039
 
2.6%
Other values (9) 3222
 
8.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 46481
53.8%
ASCII 39851
46.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19099
47.9%
1 4318
 
10.8%
- 2642
 
6.6%
2 1949
 
4.9%
3 1774
 
4.5%
6 1468
 
3.7%
4 1436
 
3.6%
0 1402
 
3.5%
5 1335
 
3.3%
9 1039
 
2.6%
Other values (30) 3389
 
8.5%
Hangul
ValueCountFrequency (%)
북 4869
 
10.5%
도 4023
 
8.7%
상 3618
 
7.8%
구 3448
 
7.4%
포 3424
 
7.4%
항 3241
 
7.0%
시 3229
 
6.9%
경 3200
 
6.9%
동 2737
 
5.9%
남 1582
 
3.4%
Other values (255) 13110
28.2%

전화번호
Text

MISSING 

Distinct2099
Distinct (%)98.1%
Missing1051
Missing (%)32.9%
Memory size25.1 KiB
2023-12-13T01:31:15.907241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.007944
Min length9

Characters and Unicode

Total characters25697
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

Unique2060 ?
Unique (%)96.3%

Sample

1st row070-8883-0167
2nd row054-256-9997
3rd row054-244-3321
4th row054-292-2509
5th row054-241-1400
ValueCountFrequency (%)
054-292-1190 3
 
0.1%
054-276-3011 3
 
0.1%
054-252-3075 2
 
0.1%
054-281-6950 2
 
0.1%
054-293-9994 2
 
0.1%
054-272-8239 2
 
0.1%
054-255-1155 2
 
0.1%
054-248-7799 2
 
0.1%
054-262-3232 2
 
0.1%
054-252-1112 2
 
0.1%
Other values (2089) 2118
99.0%
2023-12-13T01:31:16.333428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 4279
16.7%
4 3531
13.7%
2 3496
13.6%
5 3471
13.5%
0 3378
13.1%
7 1584
 
6.2%
8 1389
 
5.4%
1 1269
 
4.9%
3 1211
 
4.7%
6 1077
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 21418
83.3%
Dash Punctuation 4279
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 3531
16.5%
2 3496
16.3%
5 3471
16.2%
0 3378
15.8%
7 1584
7.4%
8 1389
 
6.5%
1 1269
 
5.9%
3 1211
 
5.7%
6 1077
 
5.0%
9 1012
 
4.7%
Dash Punctuation
ValueCountFrequency (%)
- 4279
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 25697
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 4279
16.7%
4 3531
13.7%
2 3496
13.6%
5 3471
13.5%
0 3378
13.1%
7 1584
 
6.2%
8 1389
 
5.4%
1 1269
 
4.9%
3 1211
 
4.7%
6 1077
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25697
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 4279
16.7%
4 3531
13.7%
2 3496
13.6%
5 3471
13.5%
0 3378
13.1%
7 1584
 
6.2%
8 1389
 
5.4%
1 1269
 
4.9%
3 1211
 
4.7%
6 1077
 
4.2%

데이터기준일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size25.1 KiB
2020-11-18
3190 
2020-11-18
 
1

Length

Max length11
Median length10
Mean length10.000313
Min length10

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row2020-11-18
2nd row2020-11-18
3rd row2020-11-18
4th row2020-11-18
5th row2020-11-18

Common Values

ValueCountFrequency (%)
2020-11-18 3190
> 99.9%
2020-11-18 1
 
< 0.1%

Length

2023-12-13T01:31:16.469336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:31:16.595136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-11-18 3191
100.0%

Correlations

2023-12-13T01:31:16.664241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명데이터기준일자
업종명1.0000.000
데이터기준일자0.0001.000
2023-12-13T01:31:16.749193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
데이터기준일자업종명
데이터기준일자1.0000.000
업종명0.0001.000
2023-12-13T01:31:16.834306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명데이터기준일자
업종명1.0000.000
데이터기준일자0.0001.000

Missing values

2023-12-13T01:31:12.573736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:31:12.695050image/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

업종명업소명소재지도로명주소소재지지번주소전화번호데이터기준일자
0일반미용업배넷머리경상북도 구미시 구평동 451 1층 104호070-8883-01672020-11-18
1숙박업(일반)스윗데이즈펜션경상북도 포항시 남구 희망대로 1173-1 (송도동)경상북도 포항시 남구 송도동 254-368054-256-99972020-11-18
2숙박업(일반)극동장여관경상북도 포항시 남구 송도로 59 (송도동)경상북도 포항시 남구 송도동 437-4054-244-33212020-11-18
3숙박업(일반)새서울여관경상북도 포항시 남구 오천읍 정몽주로 555-1경상북도 포항시 남구 오천읍 세계리 839-3054-292-25092020-11-18
4숙박업(일반)코모도호텔포항송도경상북도 포항시 남구 송도로 71, 코모도비취관광호텔 A동 (송도동)경상북도 포항시 남구 송도동 311-268 외1(311-2,코모도비취관광호텔) A동054-241-14002020-11-18
5숙박업(일반)금강장여관경상북도 포항시 남구 구룡포읍 구룡포길 89-3경상북도 포항시 남구 구룡포읍 구룡포리 461-26054-276-30112020-11-18
6숙박업(일반)청림경상북도 포항시 남구 청림서길 14-1, 2~3층 (청림동)경상북도 포항시 남구 청림동 3-161 (2~3층)054-292-55632020-11-18
7숙박업(일반)이화장경상북도 포항시 남구 송도로 53 (송도동)경상북도 포항시 남구 송도동 436-2054-247-30692020-11-18
8숙박업(일반)영동여관경상북도 포항시 남구 구룡포읍 호미로221번길 10-5경상북도 포항시 남구 구룡포읍 구룡포리 963-200054-276-38132020-11-18
9숙박업(일반)시드니모텔경상북도 포항시 남구 중앙로 58-1 (해도동)경상북도 포항시 남구 해도동 82-1054-272-00182020-11-18
업종명업소명소재지도로명주소소재지지번주소전화번호데이터기준일자
3181일반미용업, 네일미용업, 화장ㆍ분장 미용업리본(reborn)미용실경상북도 포항시 북구 법원로97번길 10, 1층 (장성동)경상북도 포항시 북구 장성동 1511-14 1층<NA>2020-11-18
3182일반미용업, 네일미용업, 화장ㆍ분장 미용업착한미용실경상북도 포항시 북구 양덕로44번길 15 (양덕동)경상북도 포항시 북구 양덕동 1749<NA>2020-11-18
3183일반미용업, 네일미용업, 화장ㆍ분장 미용업네일끌라베경상북도 포항시 북구 우창동로 39 (우현동)경상북도 포항시 북구 우현동 21-1<NA>2020-11-18
3184일반미용업, 네일미용업, 화장ㆍ분장 미용업살롱 드 슈비 SALON DE SYU B경상북도 포항시 북구 죽도로68번길 21, 1층 (죽도동)경상북도 포항시 북구 죽도동 557-85<NA>2020-11-18
3185일반미용업, 네일미용업, 화장ㆍ분장 미용업썬 미장경상북도 포항시 북구 아치로 9, 1층 (우현동)경상북도 포항시 북구 우현동 106-5<NA>2020-11-18
3186피부미용업, 네일미용업, 화장ㆍ분장 미용업코지네일경상북도 포항시 북구 장량로190번길 25, 1층 (양덕동)경상북도 포항시 북구 양덕동 1720<NA>2020-11-18
3187피부미용업, 네일미용업, 화장ㆍ분장 미용업daily lovely(데일리 러블리)경상북도 포항시 북구 대곡로 57, 주영빌딩 지하층 101호 (두호동)경상북도 포항시 북구 두호동 1094-2 주영빌딩<NA>2020-11-18
3188피부미용업, 네일미용업, 화장ㆍ분장 미용업쉘뷰티경상북도 포항시 북구 흥해읍 흥해로 50, 2층경상북도 포항시 북구 흥해읍 남성리 228-4<NA>2020-11-18
3189피부미용업, 네일미용업, 화장ㆍ분장 미용업언니따라경상북도 포항시 북구 흥해읍 초곡지구로 63, 102호경상북도 포항시 북구 흥해읍 초곡리 1341 102호<NA>2020-11-18
3190피부미용업, 네일미용업, 화장ㆍ분장 미용업온새미로경상북도 포항시 북구 법원로25번길 42-6, 2층 (장성동)경상북도 포항시 북구 장성동 1555-15 2층<NA>2020-11-18

Duplicate rows

Most frequently occurring

업종명업소명소재지도로명주소소재지지번주소전화번호데이터기준일자# duplicates
0미용업빈경상북도 포항시 북구 이동로 70 (득량동)경상북도 포항시 북구 득량동 303-3054-281-69502020-11-182
1미용업쿨미용실경상북도 포항시 남구 중앙로42번길 12 (해도동,대광타운101호)경상북도 포항시 남구 해도동 93-27 대광타운101호054-611-88972020-11-182
2일반미용업은설이네 네일 앤 속눈썹경상북도 포항시 북구 양학로32번길 3, 1층 (학잠동)경상북도 포항시 북구 학잠동 38-13<NA>2020-11-182