Overview

Dataset statistics

Number of variables5
Number of observations195
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.9 KiB
Average record size in memory41.7 B

Variable types

Numeric1
Categorical2
Text2

Dataset

Description충청북도 옥천군 공중위생업소 현황에 대한 데이터로 ( 업종명, 업소명, 소재지도로명 주소, 데이터기준일 등)을 제공합니다.
Author충청북도 옥천군
URLhttps://www.data.go.kr/data/15006904/fileData.do

Alerts

데이터기준일 has constant value ""Constant
연번 is highly overall correlated with 업종명High correlation
업종명 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 17:21:20.564257
Analysis finished2023-12-12 17:21:21.231761
Duration0.67 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct195
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean98
Minimum1
Maximum195
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-13T02:21:21.334569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10.7
Q149.5
median98
Q3146.5
95-th percentile185.3
Maximum195
Range194
Interquartile range (IQR)97

Descriptive statistics

Standard deviation56.435804
Coefficient of variation (CV)0.57587555
Kurtosis-1.2
Mean98
Median Absolute Deviation (MAD)49
Skewness0
Sum19110
Variance3185
MonotonicityStrictly increasing
2023-12-13T02:21:21.791198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
124 1
 
0.5%
126 1
 
0.5%
127 1
 
0.5%
128 1
 
0.5%
129 1
 
0.5%
130 1
 
0.5%
131 1
 
0.5%
132 1
 
0.5%
133 1
 
0.5%
Other values (185) 185
94.9%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 1
0.5%
7 1
0.5%
8 1
0.5%
9 1
0.5%
10 1
0.5%
ValueCountFrequency (%)
195 1
0.5%
194 1
0.5%
193 1
0.5%
192 1
0.5%
191 1
0.5%
190 1
0.5%
189 1
0.5%
188 1
0.5%
187 1
0.5%
186 1
0.5%

업종명
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)7.2%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
미용업
57 
숙박업(일반)
33 
일반미용업
30 
이용업
22 
피부미용업
14 
Other values (9)
39 

Length

Max length23
Median length12
Mean length4.8666667
Min length3

Unique

Unique2 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
미용업 57
29.2%
숙박업(일반) 33
16.9%
일반미용업 30
15.4%
이용업 22
 
11.3%
피부미용업 14
 
7.2%
세탁업 13
 
6.7%
네일미용업 9
 
4.6%
목욕장업 5
 
2.6%
종합미용업 4
 
2.1%
일반미용업, 피부미용업 2
 
1.0%
Other values (4) 6
 
3.1%

Length

2023-12-13T02:21:21.970916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
미용업 62
29.4%
일반미용업 36
17.1%
숙박업(일반 33
15.6%
이용업 22
 
10.4%
피부미용업 19
 
9.0%
세탁업 13
 
6.2%
네일미용업 12
 
5.7%
목욕장업 5
 
2.4%
화장ㆍ분장 5
 
2.4%
종합미용업 4
 
1.9%

업소명
Text

Distinct192
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-13T02:21:22.298363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length5.5179487
Min length1

Characters and Unicode

Total characters1076
Distinct characters265
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique189 ?
Unique (%)96.9%

Sample

1st row일봉모텔
2nd row행복여관
3rd row더플레인호텔 비원
4th row대흥모텔
5th row옥천관광호텔
ValueCountFrequency (%)
미용실 3
 
1.3%
네일 3
 
1.3%
옥천관광호텔 2
 
0.9%
더플레인호텔 2
 
0.9%
뷰티샵 2
 
0.9%
호텔 2
 
0.9%
헤어샵 2
 
0.9%
나나미용실 2
 
0.9%
수헤어샾 2
 
0.9%
369토탈세탁 1
 
0.4%
Other values (209) 209
90.9%
2023-12-13T02:21:22.785252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
어 48
 
4.5%
용 47
 
4.4%
헤 47
 
4.4%
미 40
 
3.7%
이 37
 
3.4%
35
 
3.3%
실 34
 
3.2%
텔 24
 
2.2%
리 18
 
1.7%
관 16
 
1.5%
Other values (255) 730
67.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 967
89.9%
Lowercase Letter 37
 
3.4%
Space Separator 35
 
3.3%
Uppercase Letter 13
 
1.2%
Other Punctuation 7
 
0.7%
Decimal Number 7
 
0.7%
Close Punctuation 5
 
0.5%
Open Punctuation 5
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
어 48
 
5.0%
용 47
 
4.9%
헤 47
 
4.9%
미 40
 
4.1%
이 37
 
3.8%
실 34
 
3.5%
텔 24
 
2.5%
리 18
 
1.9%
관 16
 
1.7%
샵 15
 
1.6%
Other values (220) 641
66.3%
Lowercase Letter
ValueCountFrequency (%)
a 6
16.2%
e 5
13.5%
i 4
10.8%
l 4
10.8%
n 3
8.1%
u 3
8.1%
r 2
 
5.4%
k 2
 
5.4%
o 1
 
2.7%
g 1
 
2.7%
Other values (6) 6
16.2%
Uppercase Letter
ValueCountFrequency (%)
B 4
30.8%
H 3
23.1%
T 2
15.4%
Y 1
 
7.7%
A 1
 
7.7%
S 1
 
7.7%
J 1
 
7.7%
Decimal Number
ValueCountFrequency (%)
2 2
28.6%
0 1
14.3%
1 1
14.3%
9 1
14.3%
6 1
14.3%
3 1
14.3%
Other Punctuation
ValueCountFrequency (%)
# 3
42.9%
, 2
28.6%
& 2
28.6%
Space Separator
ValueCountFrequency (%)
35
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 967
89.9%
Common 59
 
5.5%
Latin 50
 
4.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
어 48
 
5.0%
용 47
 
4.9%
헤 47
 
4.9%
미 40
 
4.1%
이 37
 
3.8%
실 34
 
3.5%
텔 24
 
2.5%
리 18
 
1.9%
관 16
 
1.7%
샵 15
 
1.6%
Other values (220) 641
66.3%
Latin
ValueCountFrequency (%)
a 6
12.0%
e 5
 
10.0%
i 4
 
8.0%
l 4
 
8.0%
B 4
 
8.0%
n 3
 
6.0%
u 3
 
6.0%
H 3
 
6.0%
r 2
 
4.0%
T 2
 
4.0%
Other values (13) 14
28.0%
Common
ValueCountFrequency (%)
35
59.3%
) 5
 
8.5%
( 5
 
8.5%
# 3
 
5.1%
, 2
 
3.4%
& 2
 
3.4%
2 2
 
3.4%
0 1
 
1.7%
1 1
 
1.7%
9 1
 
1.7%
Other values (2) 2
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 967
89.9%
ASCII 109
 
10.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
어 48
 
5.0%
용 47
 
4.9%
헤 47
 
4.9%
미 40
 
4.1%
이 37
 
3.8%
실 34
 
3.5%
텔 24
 
2.5%
리 18
 
1.9%
관 16
 
1.7%
샵 15
 
1.6%
Other values (220) 641
66.3%
ASCII
ValueCountFrequency (%)
35
32.1%
a 6
 
5.5%
e 5
 
4.6%
) 5
 
4.6%
( 5
 
4.6%
i 4
 
3.7%
l 4
 
3.7%
B 4
 
3.7%
n 3
 
2.8%
u 3
 
2.8%
Other values (25) 35
32.1%

영업소 주소(도로명)
Text

Distinct179
Distinct (%)91.8%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-13T02:21:23.160579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length42
Mean length21.85641
Min length18

Characters and Unicode

Total characters4262
Distinct characters121
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique165 ?
Unique (%)84.6%

Sample

1st row충청북도 옥천군 옥천읍 금장로 56
2nd row충청북도 옥천군 옥천읍 삼금로4길 2, 여관
3rd row충청북도 옥천군 옥천읍 중앙로1길 8
4th row충청북도 옥천군 옥천읍 금장로 5
5th row충청북도 옥천군 옥천읍 옥천로 1553
ValueCountFrequency (%)
충청북도 195
18.8%
옥천군 195
18.8%
옥천읍 163
15.7%
금장로 24
 
2.3%
중앙로 19
 
1.8%
옥천로 12
 
1.2%
삼금로 12
 
1.2%
2층 11
 
1.1%
1층 10
 
1.0%
성왕로 9
 
0.9%
Other values (222) 386
37.3%
2023-12-13T02:21:23.641711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
841
19.7%
옥 373
 
8.8%
천 373
 
8.8%
군 206
 
4.8%
청 205
 
4.8%
북 203
 
4.8%
충 195
 
4.6%
도 195
 
4.6%
읍 163
 
3.8%
로 148
 
3.5%
Other values (111) 1360
31.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2722
63.9%
Space Separator 841
 
19.7%
Decimal Number 593
 
13.9%
Dash Punctuation 55
 
1.3%
Other Punctuation 40
 
0.9%
Open Punctuation 4
 
0.1%
Close Punctuation 4
 
0.1%
Uppercase Letter 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
옥 373
13.7%
천 373
13.7%
군 206
 
7.6%
청 205
 
7.5%
북 203
 
7.5%
충 195
 
7.2%
도 195
 
7.2%
읍 163
 
6.0%
로 148
 
5.4%
길 89
 
3.3%
Other values (93) 572
21.0%
Decimal Number
ValueCountFrequency (%)
1 148
25.0%
2 81
13.7%
5 71
12.0%
3 64
10.8%
4 63
10.6%
6 43
 
7.3%
8 38
 
6.4%
0 34
 
5.7%
9 28
 
4.7%
7 23
 
3.9%
Other Punctuation
ValueCountFrequency (%)
, 39
97.5%
@ 1
 
2.5%
Uppercase Letter
ValueCountFrequency (%)
J 2
66.7%
B 1
33.3%
Space Separator
ValueCountFrequency (%)
841
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 55
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2722
63.9%
Common 1537
36.1%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
옥 373
13.7%
천 373
13.7%
군 206
 
7.6%
청 205
 
7.5%
북 203
 
7.5%
충 195
 
7.2%
도 195
 
7.2%
읍 163
 
6.0%
로 148
 
5.4%
길 89
 
3.3%
Other values (93) 572
21.0%
Common
ValueCountFrequency (%)
841
54.7%
1 148
 
9.6%
2 81
 
5.3%
5 71
 
4.6%
3 64
 
4.2%
4 63
 
4.1%
- 55
 
3.6%
6 43
 
2.8%
, 39
 
2.5%
8 38
 
2.5%
Other values (6) 94
 
6.1%
Latin
ValueCountFrequency (%)
J 2
66.7%
B 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2722
63.9%
ASCII 1540
36.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
841
54.6%
1 148
 
9.6%
2 81
 
5.3%
5 71
 
4.6%
3 64
 
4.2%
4 63
 
4.1%
- 55
 
3.6%
6 43
 
2.8%
, 39
 
2.5%
8 38
 
2.5%
Other values (8) 97
 
6.3%
Hangul
ValueCountFrequency (%)
옥 373
13.7%
천 373
13.7%
군 206
 
7.6%
청 205
 
7.5%
북 203
 
7.5%
충 195
 
7.2%
도 195
 
7.2%
읍 163
 
6.0%
로 148
 
5.4%
길 89
 
3.3%
Other values (93) 572
21.0%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2022-09-20
195 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-09-20
2nd row2022-09-20
3rd row2022-09-20
4th row2022-09-20
5th row2022-09-20

Common Values

ValueCountFrequency (%)
2022-09-20 195
100.0%

Length

2023-12-13T02:21:23.773971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:21:23.865829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-09-20 195
100.0%

Interactions

2023-12-13T02:21:20.865640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:21:23.933380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종명
연번1.0000.931
업종명0.9311.000
2023-12-13T02:21:24.011497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종명
연번1.0000.731
업종명0.7311.000

Missing values

2023-12-13T02:21:21.050135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:21:21.176810image/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)데이터기준일
01숙박업(일반)일봉모텔충청북도 옥천군 옥천읍 금장로 562022-09-20
12숙박업(일반)행복여관충청북도 옥천군 옥천읍 삼금로4길 2, 여관2022-09-20
23숙박업(일반)더플레인호텔 비원충청북도 옥천군 옥천읍 중앙로1길 82022-09-20
34숙박업(일반)대흥모텔충청북도 옥천군 옥천읍 금장로 52022-09-20
45숙박업(일반)옥천관광호텔충청북도 옥천군 옥천읍 옥천로 15532022-09-20
56숙박업(일반)칠성장충청북도 옥천군 옥천읍 중앙로11길 82022-09-20
67숙박업(일반)산수장여관충청북도 옥천군 청산면 청산관기로 132022-09-20
78숙박업(일반)대호모텔충청북도 옥천군 옥천읍 금장로 382022-09-20
89숙박업(일반)우림파크충청북도 옥천군 옥천읍 성왕로 13752022-09-20
910숙박업(일반)부암파크충청북도 옥천군 옥천읍 옥천로 16922022-09-20
연번업종명업소명영업소 주소(도로명)데이터기준일
185186네일미용업네일, 하는 날충청북도 옥천군 옥천읍 중앙로1길 42022-09-20
186187네일미용업네일박스충청북도 옥천군 옥천읍 중앙로 28-12022-09-20
187188일반미용업, 피부미용업권헤어살롱충청북도 옥천군 옥천읍 옥천로 1553, 숙박업소2022-09-20
188189일반미용업, 피부미용업다올헤어충청북도 옥천군 옥천읍 장야3길 19-6, 경은빌 1층 103호2022-09-20
189190피부미용업, 네일미용업Young Beauty(영뷰티)충청북도 옥천군 옥천읍 중앙로7길 9, 음식점 2층2022-09-20
190191화장ㆍ분장 미용업더나인 뷰티샵충청북도 옥천군 옥천읍 중앙로 57-3, 2층2022-09-20
191192일반미용업, 피부미용업, 화장ㆍ분장 미용업미용실충청북도 옥천군 옥천읍 성암1길 222022-09-20
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