Overview

Dataset statistics

Number of variables8
Number of observations2673
Missing cells1393
Missing cells (%)6.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory169.8 KiB
Average record size in memory65.0 B

Variable types

Numeric1
Categorical3
Text4

Dataset

Description충청남도 천안시 공중위생업소(미용업, 숙박업 등)에 대한 데이터로 업소명, 소재지지번주소, 전화번호 등의 항목을 제공합니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=418&beforeMenuCd=DOM_000000201001001000&publicdatapk=3078571

Alerts

데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 위생업소구분 and 1 other fieldsHigh correlation
위생업소구분 is highly overall correlated with 연번High correlation
관리기관명 is highly overall correlated with 연번High correlation
전화번호 has 1376 (51.5%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-01-09 20:28:03.568520
Analysis finished2024-01-09 20:28:04.690032
Duration1.12 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct2673
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1337
Minimum1
Maximum2673
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.6 KiB
2024-01-10T05:28:04.752941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile134.6
Q1669
median1337
Q32005
95-th percentile2539.4
Maximum2673
Range2672
Interquartile range (IQR)1336

Descriptive statistics

Standard deviation771.77296
Coefficient of variation (CV)0.5772423
Kurtosis-1.2
Mean1337
Median Absolute Deviation (MAD)668
Skewness0
Sum3573801
Variance595633.5
MonotonicityStrictly increasing
2024-01-10T05:28:04.876892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
1777 1
 
< 0.1%
1779 1
 
< 0.1%
1780 1
 
< 0.1%
1781 1
 
< 0.1%
1782 1
 
< 0.1%
1783 1
 
< 0.1%
1784 1
 
< 0.1%
1785 1
 
< 0.1%
1786 1
 
< 0.1%
Other values (2663) 2663
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 (%)
2673 1
< 0.1%
2672 1
< 0.1%
2671 1
< 0.1%
2670 1
< 0.1%
2669 1
< 0.1%
2668 1
< 0.1%
2667 1
< 0.1%
2666 1
< 0.1%
2665 1
< 0.1%
2664 1
< 0.1%

위생업소구분
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size21.0 KiB
일반미용업
1197 
피부미용업
321 
숙박업(일반)
316 
네일미용업
228 
미용업
122 
Other values (13)
489 

Length

Max length23
Median length5
Mean length6.5297419
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반미용업 1197
44.8%
피부미용업 321
 
12.0%
숙박업(일반) 316
 
11.8%
네일미용업 228
 
8.5%
미용업 122
 
4.6%
종합미용업 112
 
4.2%
일반미용업, 화장ㆍ분장 미용업 82
 
3.1%
피부미용업, 네일미용업 60
 
2.2%
화장ㆍ분장 미용업 55
 
2.1%
네일미용업, 화장ㆍ분장 미용업 41
 
1.5%
Other values (8) 139
 
5.2%

Length

2024-01-10T05:28:05.000409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반미용업 1339
40.4%
피부미용업 472
 
14.2%
네일미용업 408
 
12.3%
미용업 390
 
11.8%
숙박업(일반 316
 
9.5%
화장ㆍ분장 268
 
8.1%
종합미용업 112
 
3.4%
숙박업(생활 9
 
0.3%

업소명
Text

Distinct2554
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Memory size21.0 KiB
2024-01-10T05:28:05.250121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length19
Mean length5.3183689
Min length1

Characters and Unicode

Total characters14216
Distinct characters673
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2461 ?
Unique (%)92.1%

Sample

1st row동궁여관
2nd row한양파크장여관
3rd row이화모텔
4th row성거여인숙
5th row금관여관
ValueCountFrequency (%)
헤어스토리 6
 
0.2%
가위소리 5
 
0.2%
수헤어 5
 
0.2%
앨리스헤어 4
 
0.1%
준헤어 4
 
0.1%
코코헤어 4
 
0.1%
헤어살롱제이 3
 
0.1%
민헤어 3
 
0.1%
봄헤어 3
 
0.1%
제이엠헤어 3
 
0.1%
Other values (2552) 2642
98.5%
2024-01-10T05:28:05.635273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
어 1056
 
7.4%
헤 989
 
7.0%
이 413
 
2.9%
스 378
 
2.7%
미 348
 
2.4%
리 339
 
2.4%
일 329
 
2.3%
네 306
 
2.2%
티 183
 
1.3%
텔 183
 
1.3%
Other values (663) 9692
68.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14006
98.5%
Decimal Number 129
 
0.9%
Lowercase Letter 30
 
0.2%
Close Punctuation 13
 
0.1%
Open Punctuation 13
 
0.1%
Uppercase Letter 12
 
0.1%
Space Separator 11
 
0.1%
Dash Punctuation 1
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
어 1056
 
7.5%
헤 989
 
7.1%
이 413
 
2.9%
스 378
 
2.7%
미 348
 
2.5%
리 339
 
2.4%
일 329
 
2.3%
네 306
 
2.2%
티 183
 
1.3%
텔 183
 
1.3%
Other values (624) 9482
67.7%
Lowercase Letter
ValueCountFrequency (%)
e 5
16.7%
a 4
13.3%
n 3
10.0%
o 3
10.0%
y 2
 
6.7%
r 2
 
6.7%
l 2
 
6.7%
s 2
 
6.7%
i 2
 
6.7%
p 1
 
3.3%
Other values (4) 4
13.3%
Uppercase Letter
ValueCountFrequency (%)
L 2
16.7%
N 1
8.3%
W 1
8.3%
I 1
8.3%
B 1
8.3%
F 1
8.3%
S 1
8.3%
H 1
8.3%
C 1
8.3%
J 1
8.3%
Decimal Number
ValueCountFrequency (%)
0 35
27.1%
1 24
18.6%
2 17
13.2%
5 11
 
8.5%
4 10
 
7.8%
9 10
 
7.8%
7 9
 
7.0%
3 7
 
5.4%
6 6
 
4.7%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Space Separator
ValueCountFrequency (%)
11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14006
98.5%
Common 168
 
1.2%
Latin 42
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
어 1056
 
7.5%
헤 989
 
7.1%
이 413
 
2.9%
스 378
 
2.7%
미 348
 
2.5%
리 339
 
2.4%
일 329
 
2.3%
네 306
 
2.2%
티 183
 
1.3%
텔 183
 
1.3%
Other values (624) 9482
67.7%
Latin
ValueCountFrequency (%)
e 5
 
11.9%
a 4
 
9.5%
n 3
 
7.1%
o 3
 
7.1%
y 2
 
4.8%
r 2
 
4.8%
L 2
 
4.8%
l 2
 
4.8%
s 2
 
4.8%
i 2
 
4.8%
Other values (15) 15
35.7%
Common
ValueCountFrequency (%)
0 35
20.8%
1 24
14.3%
2 17
10.1%
) 13
 
7.7%
( 13
 
7.7%
5 11
 
6.5%
11
 
6.5%
4 10
 
6.0%
9 10
 
6.0%
7 9
 
5.4%
Other values (4) 15
8.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14006
98.5%
ASCII 210
 
1.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
어 1056
 
7.5%
헤 989
 
7.1%
이 413
 
2.9%
스 378
 
2.7%
미 348
 
2.5%
리 339
 
2.4%
일 329
 
2.3%
네 306
 
2.2%
티 183
 
1.3%
텔 183
 
1.3%
Other values (624) 9482
67.7%
ASCII
ValueCountFrequency (%)
0 35
16.7%
1 24
11.4%
2 17
 
8.1%
) 13
 
6.2%
( 13
 
6.2%
5 11
 
5.2%
11
 
5.2%
4 10
 
4.8%
9 10
 
4.8%
7 9
 
4.3%
Other values (29) 57
27.1%

소재지도로명주소
Text

Distinct2550
Distinct (%)95.9%
Missing15
Missing (%)0.6%
Memory size21.0 KiB
2024-01-10T05:28:05.934580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length70
Median length63
Mean length35.060948
Min length23

Characters and Unicode

Total characters93192
Distinct characters400
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2450 ?
Unique (%)92.2%

Sample

1st row충청남도 천안시 서북구 성환읍 성환2로 134, 동궁장 2,3층
2nd row충청남도 천안시 서북구 봉정로 103 (성정동)
3rd row충청남도 천안시 서북구 차돌로 10 (쌍용동)
4th row충청남도 천안시 서북구 성거읍 성거길 129
5th row충청남도 천안시 서북구 입장면 입장로 144
ValueCountFrequency (%)
충청남도 2658
 
13.3%
천안시 2658
 
13.3%
서북구 1689
 
8.4%
1층 1274
 
6.4%
동남구 969
 
4.8%
두정동 356
 
1.8%
2층 344
 
1.7%
성정동 320
 
1.6%
쌍용동 281
 
1.4%
불당동 279
 
1.4%
Other values (2226) 9172
45.9%
2024-01-10T05:28:06.408801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17342
 
18.6%
1 4537
 
4.9%
동 3839
 
4.1%
남 3668
 
3.9%
천 2946
 
3.2%
청 2887
 
3.1%
안 2872
 
3.1%
시 2828
 
3.0%
충 2744
 
2.9%
구 2711
 
2.9%
Other values (390) 46818
50.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 53313
57.2%
Space Separator 17342
 
18.6%
Decimal Number 14113
 
15.1%
Other Punctuation 2645
 
2.8%
Close Punctuation 2450
 
2.6%
Open Punctuation 2450
 
2.6%
Dash Punctuation 638
 
0.7%
Uppercase Letter 172
 
0.2%
Math Symbol 37
 
< 0.1%
Lowercase Letter 23
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 3839
 
7.2%
남 3668
 
6.9%
천 2946
 
5.5%
청 2887
 
5.4%
안 2872
 
5.4%
시 2828
 
5.3%
충 2744
 
5.1%
구 2711
 
5.1%
도 2679
 
5.0%
층 1939
 
3.6%
Other values (339) 24200
45.4%
Uppercase Letter
ValueCountFrequency (%)
B 38
22.1%
A 27
15.7%
S 16
9.3%
K 12
 
7.0%
J 11
 
6.4%
I 10
 
5.8%
D 10
 
5.8%
E 7
 
4.1%
L 7
 
4.1%
P 5
 
2.9%
Other values (11) 29
16.9%
Decimal Number
ValueCountFrequency (%)
1 4537
32.1%
2 2343
16.6%
3 1413
 
10.0%
0 1331
 
9.4%
4 1068
 
7.6%
5 832
 
5.9%
6 826
 
5.9%
8 695
 
4.9%
7 608
 
4.3%
9 460
 
3.3%
Lowercase Letter
ValueCountFrequency (%)
s 6
26.1%
e 5
21.7%
l 2
 
8.7%
t 2
 
8.7%
i 2
 
8.7%
h 2
 
8.7%
r 2
 
8.7%
a 1
 
4.3%
j 1
 
4.3%
Other Punctuation
ValueCountFrequency (%)
, 2631
99.5%
. 7
 
0.3%
@ 5
 
0.2%
& 2
 
0.1%
Letter Number
ValueCountFrequency (%)
Ⅱ 5
55.6%
Ⅲ 4
44.4%
Space Separator
ValueCountFrequency (%)
17342
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2450
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2450
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 638
100.0%
Math Symbol
ValueCountFrequency (%)
~ 37
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 53313
57.2%
Common 39675
42.6%
Latin 204
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 3839
 
7.2%
남 3668
 
6.9%
천 2946
 
5.5%
청 2887
 
5.4%
안 2872
 
5.4%
시 2828
 
5.3%
충 2744
 
5.1%
구 2711
 
5.1%
도 2679
 
5.0%
층 1939
 
3.6%
Other values (339) 24200
45.4%
Latin
ValueCountFrequency (%)
B 38
18.6%
A 27
13.2%
S 16
 
7.8%
K 12
 
5.9%
J 11
 
5.4%
I 10
 
4.9%
D 10
 
4.9%
E 7
 
3.4%
L 7
 
3.4%
s 6
 
2.9%
Other values (22) 60
29.4%
Common
ValueCountFrequency (%)
17342
43.7%
1 4537
 
11.4%
, 2631
 
6.6%
) 2450
 
6.2%
( 2450
 
6.2%
2 2343
 
5.9%
3 1413
 
3.6%
0 1331
 
3.4%
4 1068
 
2.7%
5 832
 
2.1%
Other values (9) 3278
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 53313
57.2%
ASCII 39870
42.8%
Number Forms 9
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17342
43.5%
1 4537
 
11.4%
, 2631
 
6.6%
) 2450
 
6.1%
( 2450
 
6.1%
2 2343
 
5.9%
3 1413
 
3.5%
0 1331
 
3.3%
4 1068
 
2.7%
5 832
 
2.1%
Other values (39) 3473
 
8.7%
Hangul
ValueCountFrequency (%)
동 3839
 
7.2%
남 3668
 
6.9%
천 2946
 
5.5%
청 2887
 
5.4%
안 2872
 
5.4%
시 2828
 
5.3%
충 2744
 
5.1%
구 2711
 
5.1%
도 2679
 
5.0%
층 1939
 
3.6%
Other values (339) 24200
45.4%
Number Forms
ValueCountFrequency (%)
Ⅱ 5
55.6%
Ⅲ 4
44.4%

소재지지번주소
Text

Distinct2341
Distinct (%)87.6%
Missing2
Missing (%)0.1%
Memory size21.0 KiB
2024-01-10T05:28:06.717039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length53
Mean length26.587046
Min length20

Characters and Unicode

Total characters71014
Distinct characters410
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2123 ?
Unique (%)79.5%

Sample

1st row충청남도 천안시 서북구 성환읍 성환리 280-8 동궁장
2nd row충청남도 천안시 서북구 성정동 743-5
3rd row충청남도 천안시 서북구 쌍용동 533-5
4th row충청남도 천안시 서북구 성거읍 저리 52-3
5th row충청남도 천안시 서북구 입장면 하장리 63
ValueCountFrequency (%)
충청남도 2671
17.1%
천안시 2671
17.1%
서북구 1691
 
10.9%
동남구 980
 
6.3%
두정동 382
 
2.5%
1층 358
 
2.3%
성정동 326
 
2.1%
쌍용동 304
 
2.0%
불당동 285
 
1.8%
신부동 203
 
1.3%
Other values (2631) 5708
36.6%
2024-01-10T05:28:07.158144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15401
21.7%
남 3678
 
5.2%
동 3563
 
5.0%
1 2891
 
4.1%
천 2883
 
4.1%
안 2801
 
3.9%
청 2792
 
3.9%
시 2736
 
3.9%
구 2717
 
3.8%
도 2679
 
3.8%
Other values (400) 28873
40.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 42048
59.2%
Space Separator 15401
 
21.7%
Decimal Number 12059
 
17.0%
Dash Punctuation 1233
 
1.7%
Uppercase Letter 80
 
0.1%
Other Punctuation 57
 
0.1%
Close Punctuation 39
 
0.1%
Open Punctuation 39
 
0.1%
Lowercase Letter 31
 
< 0.1%
Math Symbol 22
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 3678
 
8.7%
동 3563
 
8.5%
천 2883
 
6.9%
안 2801
 
6.7%
청 2792
 
6.6%
시 2736
 
6.5%
구 2717
 
6.5%
도 2679
 
6.4%
충 2671
 
6.4%
서 1733
 
4.1%
Other values (352) 13795
32.8%
Uppercase Letter
ValueCountFrequency (%)
K 11
13.8%
S 11
13.8%
A 10
12.5%
B 10
12.5%
L 6
7.5%
J 4
 
5.0%
P 4
 
5.0%
T 4
 
5.0%
I 3
 
3.8%
E 3
 
3.8%
Other values (8) 14
17.5%
Lowercase Letter
ValueCountFrequency (%)
s 7
22.6%
e 6
19.4%
i 4
12.9%
t 3
9.7%
l 2
 
6.5%
h 2
 
6.5%
r 2
 
6.5%
p 1
 
3.2%
o 1
 
3.2%
n 1
 
3.2%
Other values (2) 2
 
6.5%
Decimal Number
ValueCountFrequency (%)
1 2891
24.0%
2 1340
11.1%
4 1193
9.9%
3 1058
 
8.8%
6 1036
 
8.6%
5 1003
 
8.3%
0 976
 
8.1%
7 886
 
7.3%
9 839
 
7.0%
8 837
 
6.9%
Other Punctuation
ValueCountFrequency (%)
, 51
89.5%
@ 6
 
10.5%
Space Separator
ValueCountFrequency (%)
15401
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1233
100.0%
Close Punctuation
ValueCountFrequency (%)
) 39
100.0%
Open Punctuation
ValueCountFrequency (%)
( 39
100.0%
Math Symbol
ValueCountFrequency (%)
~ 22
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 42048
59.2%
Common 28850
40.6%
Latin 116
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 3678
 
8.7%
동 3563
 
8.5%
천 2883
 
6.9%
안 2801
 
6.7%
청 2792
 
6.6%
시 2736
 
6.5%
구 2717
 
6.5%
도 2679
 
6.4%
충 2671
 
6.4%
서 1733
 
4.1%
Other values (352) 13795
32.8%
Latin
ValueCountFrequency (%)
K 11
 
9.5%
S 11
 
9.5%
A 10
 
8.6%
B 10
 
8.6%
s 7
 
6.0%
L 6
 
5.2%
e 6
 
5.2%
Ⅱ 5
 
4.3%
J 4
 
3.4%
P 4
 
3.4%
Other values (21) 42
36.2%
Common
ValueCountFrequency (%)
15401
53.4%
1 2891
 
10.0%
2 1340
 
4.6%
- 1233
 
4.3%
4 1193
 
4.1%
3 1058
 
3.7%
6 1036
 
3.6%
5 1003
 
3.5%
0 976
 
3.4%
7 886
 
3.1%
Other values (7) 1833
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 42048
59.2%
ASCII 28961
40.8%
Number Forms 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15401
53.2%
1 2891
 
10.0%
2 1340
 
4.6%
- 1233
 
4.3%
4 1193
 
4.1%
3 1058
 
3.7%
6 1036
 
3.6%
5 1003
 
3.5%
0 976
 
3.4%
7 886
 
3.1%
Other values (37) 1944
 
6.7%
Hangul
ValueCountFrequency (%)
남 3678
 
8.7%
동 3563
 
8.5%
천 2883
 
6.9%
안 2801
 
6.7%
청 2792
 
6.6%
시 2736
 
6.5%
구 2717
 
6.5%
도 2679
 
6.4%
충 2671
 
6.4%
서 1733
 
4.1%
Other values (352) 13795
32.8%
Number Forms
ValueCountFrequency (%)
Ⅱ 5
100.0%

전화번호
Text

MISSING 

Distinct1270
Distinct (%)97.9%
Missing1376
Missing (%)51.5%
Memory size21.0 KiB
2024-01-10T05:28:07.403144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.020046
Min length12

Characters and Unicode

Total characters15590
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

Unique1243 ?
Unique (%)95.8%

Sample

1st row041-581-9191
2nd row041-574-2002
3rd row041-572-7033
4th row041-622-0785
5th row041-583-5135
ValueCountFrequency (%)
041-584-9933 2
 
0.2%
041-555-1922 2
 
0.2%
041-577-5654 2
 
0.2%
041-532-1123 2
 
0.2%
041-556-5674 2
 
0.2%
041-562-5900 2
 
0.2%
041-556-0671 2
 
0.2%
041-571-1397 2
 
0.2%
041-573-0918 2
 
0.2%
041-571-7545 2
 
0.2%
Other values (1260) 1277
98.5%
2024-01-10T05:28:07.756833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 2594
16.6%
5 2253
14.5%
1 2051
13.2%
0 1982
12.7%
4 1819
11.7%
7 1061
6.8%
6 912
 
5.8%
2 885
 
5.7%
8 743
 
4.8%
3 737
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12996
83.4%
Dash Punctuation 2594
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 2253
17.3%
1 2051
15.8%
0 1982
15.3%
4 1819
14.0%
7 1061
8.2%
6 912
7.0%
2 885
 
6.8%
8 743
 
5.7%
3 737
 
5.7%
9 553
 
4.3%
Dash Punctuation
ValueCountFrequency (%)
- 2594
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15590
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 2594
16.6%
5 2253
14.5%
1 2051
13.2%
0 1982
12.7%
4 1819
11.7%
7 1061
6.8%
6 912
 
5.8%
2 885
 
5.7%
8 743
 
4.8%
3 737
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15590
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 2594
16.6%
5 2253
14.5%
1 2051
13.2%
0 1982
12.7%
4 1819
11.7%
7 1061
6.8%
6 912
 
5.8%
2 885
 
5.7%
8 743
 
4.8%
3 737
 
4.7%

관리기관명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.0 KiB
충청남도 천안시 서북구 환경위생과
1693 
충청남도 천안시 동남구 환경위생과
980 

Length

Max length18
Median length18
Mean length18
Min length18

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row충청남도 천안시 서북구 환경위생과
2nd row충청남도 천안시 서북구 환경위생과
3rd row충청남도 천안시 서북구 환경위생과
4th row충청남도 천안시 서북구 환경위생과
5th row충청남도 천안시 서북구 환경위생과

Common Values

ValueCountFrequency (%)
충청남도 천안시 서북구 환경위생과 1693
63.3%
충청남도 천안시 동남구 환경위생과 980
36.7%

Length

2024-01-10T05:28:07.896770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:28:07.995743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청남도 2673
25.0%
천안시 2673
25.0%
환경위생과 2673
25.0%
서북구 1693
15.8%
동남구 980
 
9.2%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size21.0 KiB
2022-09-19
2673 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-09-19
2nd row2022-09-19
3rd row2022-09-19
4th row2022-09-19
5th row2022-09-19

Common Values

ValueCountFrequency (%)
2022-09-19 2673
100.0%

Length

2024-01-10T05:28:08.090500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:28:08.175304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-09-19 2673
100.0%

Interactions

2024-01-10T05:28:04.319735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T05:28:08.224604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위생업소구분관리기관명
연번1.0000.8340.997
위생업소구분0.8341.0000.272
관리기관명0.9970.2721.000
2024-01-10T05:28:08.309075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리기관명위생업소구분
관리기관명1.0000.213
위생업소구분0.2131.000
2024-01-10T05:28:08.382253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위생업소구분관리기관명
연번1.0000.5120.949
위생업소구분0.5121.0000.213
관리기관명0.9490.2131.000

Missing values

2024-01-10T05:28:04.430903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T05:28:04.545568image/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.
2024-01-10T05:28:04.639993image/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

연번위생업소구분업소명소재지도로명주소소재지지번주소전화번호관리기관명데이터기준일자
01숙박업(일반)동궁여관충청남도 천안시 서북구 성환읍 성환2로 134, 동궁장 2,3층충청남도 천안시 서북구 성환읍 성환리 280-8 동궁장041-581-9191충청남도 천안시 서북구 환경위생과2022-09-19
12숙박업(일반)한양파크장여관충청남도 천안시 서북구 봉정로 103 (성정동)충청남도 천안시 서북구 성정동 743-5041-574-2002충청남도 천안시 서북구 환경위생과2022-09-19
23숙박업(일반)이화모텔충청남도 천안시 서북구 차돌로 10 (쌍용동)충청남도 천안시 서북구 쌍용동 533-5041-572-7033충청남도 천안시 서북구 환경위생과2022-09-19
34숙박업(일반)성거여인숙충청남도 천안시 서북구 성거읍 성거길 129충청남도 천안시 서북구 성거읍 저리 52-3041-622-0785충청남도 천안시 서북구 환경위생과2022-09-19
45숙박업(일반)금관여관충청남도 천안시 서북구 입장면 입장로 144충청남도 천안시 서북구 입장면 하장리 63041-583-5135충청남도 천안시 서북구 환경위생과2022-09-19
56숙박업(일반)성신장여관충청남도 천안시 서북구 성환읍 성환중앙로 18-1충청남도 천안시 서북구 성환읍 성환리 432-3041-581-2709충청남도 천안시 서북구 환경위생과2022-09-19
67숙박업(일반)아리랑모텔충청남도 천안시 서북구 직산읍 천안대로 1494충청남도 천안시 서북구 직산읍 삼은리 263-11041-583-0923충청남도 천안시 서북구 환경위생과2022-09-19
78숙박업(일반)미니모텔충청남도 천안시 서북구 서부역10길 31 (성정동)충청남도 천안시 서북구 성정동 193-32041-574-5566충청남도 천안시 서북구 환경위생과2022-09-19
89숙박업(일반)로얄파크장여관충청남도 천안시 서북구 양지8길 10-8 (성정동)충청남도 천안시 서북구 성정동 746-3041-574-3532충청남도 천안시 서북구 환경위생과2022-09-19
910숙박업(일반)호텔제이충청남도 천안시 서북구 양지17길 3 (성정동)충청남도 천안시 서북구 성정동 744-2041-577-7730충청남도 천안시 서북구 환경위생과2022-09-19
연번위생업소구분업소명소재지도로명주소소재지지번주소전화번호관리기관명데이터기준일자
26632664피부미용업, 네일미용업, 화장ㆍ분장 미용업살롱드에뚜왈충청남도 천안시 동남구 터미널1길 10, 1층 (신부동)충청남도 천안시 동남구 신부동 743 1층<NA>충청남도 천안시 동남구 환경위생과2022-09-19
26642665피부미용업, 네일미용업, 화장ㆍ분장 미용업네일조아나충청남도 천안시 동남구 청수로 99, 상가동 103호 (청수동, 극동1차아파트)충청남도 천안시 동남구 청수동 209 극동1차아파트 상가동 103호<NA>충청남도 천안시 동남구 환경위생과2022-09-19
26652666피부미용업, 네일미용업, 화장ㆍ분장 미용업수다네일충청남도 천안시 동남구 청수로 98, 상가동 1층 111호 (청수동, 청솔LG아파트)충청남도 천안시 동남구 청수동 262 청솔엘지,에스케이아파트 상가동 111호<NA>충청남도 천안시 동남구 환경위생과2022-09-19
26662667피부미용업, 네일미용업, 화장ㆍ분장 미용업리나뷰티충청남도 천안시 동남구 먹거리10길 5, 2층 (신부동)충청남도 천안시 동남구 신부동 455-6 2층<NA>충청남도 천안시 동남구 환경위생과2022-09-19
26672668피부미용업, 네일미용업, 화장ㆍ분장 미용업네일혜주충청남도 천안시 동남구 다가말2길 70, 1층 1104호 (다가동, 일봉산 해피트리)충청남도 천안시 동남구 다가동 578 1층 1104호<NA>충청남도 천안시 동남구 환경위생과2022-09-19
26682669피부미용업, 네일미용업, 화장ㆍ분장 미용업반하다충청남도 천안시 동남구 풍세로 798, 1층 105호 (청당동)충청남도 천안시 동남구 청당동 396-12<NA>충청남도 천안시 동남구 환경위생과2022-09-19
26692670피부미용업, 네일미용업, 화장ㆍ분장 미용업하늘연네일충청남도 천안시 동남구 터미널6길 9, 1층 (신부동)충청남도 천안시 동남구 신부동 804 1층<NA>충청남도 천안시 동남구 환경위생과2022-09-19
26702671피부미용업, 네일미용업, 화장ㆍ분장 미용업제이와이뷰티충청남도 천안시 동남구 통정8로 17, 1층 (신방동)충청남도 천안시 동남구 신방동 1385<NA>충청남도 천안시 동남구 환경위생과2022-09-19
26712672피부미용업, 네일미용업, 화장ㆍ분장 미용업더더네일충청남도 천안시 동남구 중앙로 213, 1층 (신부동)충청남도 천안시 동남구 신부동 371-25 1층<NA>충청남도 천안시 동남구 환경위생과2022-09-19
26722673피부미용업, 네일미용업, 화장ㆍ분장 미용업주니네일충청남도 천안시 동남구 목천읍 서리1길 54-10, 1층충청남도 천안시 동남구 목천읍 서리 24-10 1층<NA>충청남도 천안시 동남구 환경위생과2022-09-19