Overview

Dataset statistics

Number of variables3
Number of observations25
Missing cells27
Missing cells (%)36.0%
Duplicate rows2
Duplicate rows (%)8.0%
Total size in memory732.0 B
Average record size in memory29.3 B

Variable types

Text3

Dataset

Description순창군 관내 문화유통업현황(2014. 9월 현재)
Author전라북도 순창군
URLhttps://www.data.go.kr/data/15055403/fileData.do

Alerts

Dataset has 2 (8.0%) duplicate rowsDuplicates
노래연습장 현황 has 5 (20.0%) missing valuesMissing
Unnamed: 1 has 7 (28.0%) missing valuesMissing
Unnamed: 2 has 15 (60.0%) missing valuesMissing

Reproduction

Analysis started2023-12-12 03:45:35.356339
Analysis finished2023-12-12 03:45:35.955189
Duration0.6 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

노래연습장 현황
Text

MISSING 

Distinct19
Distinct (%)95.0%
Missing5
Missing (%)20.0%
Memory size332.0 B
2023-12-12T12:45:36.196560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length7.35
Min length2

Characters and Unicode

Total characters147
Distinct characters78
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)90.0%

Sample

1st row상호명
2nd row앙코르노래연습장
3rd row만나 노래연습장
4th row불꽃노래연습장
5th row럭셔리노래연습장
ValueCountFrequency (%)
상호 2
 
6.9%
노래연습장 2
 
6.9%
현황 2
 
6.9%
pc 1
 
3.4%
밤 1
 
3.4%
이루는 1
 
3.4%
잠못 1
 
3.4%
마우스가 1
 
3.4%
청소년게임제공업 1
 
3.4%
사라방pc 1
 
3.4%
Other values (16) 16
55.2%
2023-12-12T12:45:36.774081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9
 
6.1%
C 7
 
4.8%
P 7
 
4.8%
방 6
 
4.1%
노 6
 
4.1%
래 6
 
4.1%
연 6
 
4.1%
습 6
 
4.1%
장 6
 
4.1%
호 3
 
2.0%
Other values (68) 85
57.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 117
79.6%
Uppercase Letter 21
 
14.3%
Space Separator 9
 
6.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
방 6
 
5.1%
노 6
 
5.1%
래 6
 
5.1%
연 6
 
5.1%
습 6
 
5.1%
장 6
 
5.1%
호 3
 
2.6%
상 3
 
2.6%
공 2
 
1.7%
사 2
 
1.7%
Other values (59) 71
60.7%
Uppercase Letter
ValueCountFrequency (%)
C 7
33.3%
P 7
33.3%
A 2
 
9.5%
S 1
 
4.8%
E 1
 
4.8%
H 1
 
4.8%
R 1
 
4.8%
F 1
 
4.8%
Space Separator
ValueCountFrequency (%)
9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 117
79.6%
Latin 21
 
14.3%
Common 9
 
6.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
방 6
 
5.1%
노 6
 
5.1%
래 6
 
5.1%
연 6
 
5.1%
습 6
 
5.1%
장 6
 
5.1%
호 3
 
2.6%
상 3
 
2.6%
공 2
 
1.7%
사 2
 
1.7%
Other values (59) 71
60.7%
Latin
ValueCountFrequency (%)
C 7
33.3%
P 7
33.3%
A 2
 
9.5%
S 1
 
4.8%
E 1
 
4.8%
H 1
 
4.8%
R 1
 
4.8%
F 1
 
4.8%
Common
ValueCountFrequency (%)
9
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 117
79.6%
ASCII 30
 
20.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9
30.0%
C 7
23.3%
P 7
23.3%
A 2
 
6.7%
S 1
 
3.3%
E 1
 
3.3%
H 1
 
3.3%
R 1
 
3.3%
F 1
 
3.3%
Hangul
ValueCountFrequency (%)
방 6
 
5.1%
노 6
 
5.1%
래 6
 
5.1%
연 6
 
5.1%
습 6
 
5.1%
장 6
 
5.1%
호 3
 
2.6%
상 3
 
2.6%
공 2
 
1.7%
사 2
 
1.7%
Other values (59) 71
60.7%

Unnamed: 1
Text

MISSING 

Distinct16
Distinct (%)88.9%
Missing7
Missing (%)28.0%
Memory size332.0 B
2023-12-12T12:45:37.050151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length22
Mean length18.777778
Min length8

Characters and Unicode

Total characters338
Distinct characters39
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)77.8%

Sample

1st row영업소지번소재지
2nd row전라북도 순창군 순창읍 순창로 226-2
3rd row전라북도 순창군 순창읍 남계로 98
4th row전라북도 순창군 순창읍 순창6길 10
5th row전라북도 순창군 순창읍 순창로 217
ValueCountFrequency (%)
순창군 15
19.2%
순창읍 15
19.2%
전라북도 15
19.2%
순창로 5
 
6.4%
장류로 2
 
2.6%
영업소소재지(도로명 2
 
2.6%
10 2
 
2.6%
순창6길 2
 
2.6%
98 1
 
1.3%
79 1
 
1.3%
Other values (18) 18
23.1%
2023-12-12T12:45:37.565552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
60
17.8%
순 40
11.8%
창 39
11.5%
도 17
 
5.0%
라 15
 
4.4%
읍 15
 
4.4%
군 15
 
4.4%
전 15
 
4.4%
북 15
 
4.4%
로 13
 
3.8%
Other values (29) 94
27.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 221
65.4%
Space Separator 60
 
17.8%
Decimal Number 48
 
14.2%
Dash Punctuation 5
 
1.5%
Close Punctuation 2
 
0.6%
Open Punctuation 2
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
순 40
18.1%
창 39
17.6%
도 17
7.7%
라 15
 
6.8%
읍 15
 
6.8%
군 15
 
6.8%
전 15
 
6.8%
북 15
 
6.8%
로 13
 
5.9%
소 6
 
2.7%
Other values (15) 31
14.0%
Decimal Number
ValueCountFrequency (%)
1 12
25.0%
2 10
20.8%
6 5
10.4%
5 5
10.4%
3 3
 
6.2%
9 3
 
6.2%
7 3
 
6.2%
8 3
 
6.2%
0 3
 
6.2%
4 1
 
2.1%
Space Separator
ValueCountFrequency (%)
60
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 221
65.4%
Common 117
34.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
순 40
18.1%
창 39
17.6%
도 17
7.7%
라 15
 
6.8%
읍 15
 
6.8%
군 15
 
6.8%
전 15
 
6.8%
북 15
 
6.8%
로 13
 
5.9%
소 6
 
2.7%
Other values (15) 31
14.0%
Common
ValueCountFrequency (%)
60
51.3%
1 12
 
10.3%
2 10
 
8.5%
6 5
 
4.3%
- 5
 
4.3%
5 5
 
4.3%
3 3
 
2.6%
9 3
 
2.6%
7 3
 
2.6%
8 3
 
2.6%
Other values (4) 8
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 221
65.4%
ASCII 117
34.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
60
51.3%
1 12
 
10.3%
2 10
 
8.5%
6 5
 
4.3%
- 5
 
4.3%
5 5
 
4.3%
3 3
 
2.6%
9 3
 
2.6%
7 3
 
2.6%
8 3
 
2.6%
Other values (4) 8
 
6.8%
Hangul
ValueCountFrequency (%)
순 40
18.1%
창 39
17.6%
도 17
7.7%
라 15
 
6.8%
읍 15
 
6.8%
군 15
 
6.8%
전 15
 
6.8%
북 15
 
6.8%
로 13
 
5.9%
소 6
 
2.7%
Other values (15) 31
14.0%

Unnamed: 2
Text

MISSING 

Distinct8
Distinct (%)80.0%
Missing15
Missing (%)60.0%
Memory size332.0 B
2023-12-12T12:45:37.777886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length6.8
Min length4

Characters and Unicode

Total characters68
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)70.0%

Sample

1st row전화번호
2nd row653-6830
3rd row653-1243
4th row653-7010
5th row전화번호
ValueCountFrequency (%)
전화번호 3
30.0%
653-6830 1
 
10.0%
653-1243 1
 
10.0%
653-7010 1
 
10.0%
653-9933 1
 
10.0%
652-0500 1
 
10.0%
653-3773 1
 
10.0%
653-8830 1
 
10.0%
2023-12-12T12:45:38.255818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 13
19.1%
6 8
11.8%
5 8
11.8%
- 7
10.3%
0 7
10.3%
전 3
 
4.4%
화 3
 
4.4%
번 3
 
4.4%
호 3
 
4.4%
8 3
 
4.4%
Other values (5) 10
14.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 49
72.1%
Other Letter 12
 
17.6%
Dash Punctuation 7
 
10.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 13
26.5%
6 8
16.3%
5 8
16.3%
0 7
14.3%
8 3
 
6.1%
7 3
 
6.1%
1 2
 
4.1%
2 2
 
4.1%
9 2
 
4.1%
4 1
 
2.0%
Other Letter
ValueCountFrequency (%)
전 3
25.0%
화 3
25.0%
번 3
25.0%
호 3
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 56
82.4%
Hangul 12
 
17.6%

Most frequent character per script

Common
ValueCountFrequency (%)
3 13
23.2%
6 8
14.3%
5 8
14.3%
- 7
12.5%
0 7
12.5%
8 3
 
5.4%
7 3
 
5.4%
1 2
 
3.6%
2 2
 
3.6%
9 2
 
3.6%
Hangul
ValueCountFrequency (%)
전 3
25.0%
화 3
25.0%
번 3
25.0%
호 3
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 56
82.4%
Hangul 12
 
17.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 13
23.2%
6 8
14.3%
5 8
14.3%
- 7
12.5%
0 7
12.5%
8 3
 
5.4%
7 3
 
5.4%
1 2
 
3.6%
2 2
 
3.6%
9 2
 
3.6%
Hangul
ValueCountFrequency (%)
전 3
25.0%
화 3
25.0%
번 3
25.0%
호 3
25.0%

Correlations

2023-12-12T12:45:38.448610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
노래연습장 현황Unnamed: 1Unnamed: 2
노래연습장 현황1.0001.0001.000
Unnamed: 11.0001.0001.000
Unnamed: 21.0001.0001.000

Missing values

2023-12-12T12:45:35.596948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:45:35.720034image/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.
2023-12-12T12:45:35.866036image/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

노래연습장 현황Unnamed: 1Unnamed: 2
0<NA><NA><NA>
1상호명영업소지번소재지전화번호
2앙코르노래연습장전라북도 순창군 순창읍 순창로 226-2653-6830
3만나 노래연습장전라북도 순창군 순창읍 남계로 98<NA>
4불꽃노래연습장전라북도 순창군 순창읍 순창6길 10653-1243
5럭셔리노래연습장전라북도 순창군 순창읍 순창로 217653-7010
6애플노래연습장전라북도 순창군 순창읍 순화로 25<NA>
7동원 노래연습장전라북도 순창군 순창읍 순창5길 21<NA>
8<NA><NA><NA>
9인터넷컴퓨터시설제공업 현황<NA><NA>
노래연습장 현황Unnamed: 1Unnamed: 2
15SHARP PC CAFE전라북도 순창군 순창읍 순창로 218<NA>
16지존피시방전라북도 순창군 순창읍 순창로 201653-3773
17휴먼스토리PC방전라북도 순창군 순창읍 옥천로 35-1<NA>
18게임매니아PC방전라북도 순창군 순창읍 순창11길 17-25<NA>
19사라방PC전라북도 순창군 순창읍 순창로 219<NA>
20<NA><NA><NA>
21청소년게임제공업 현황<NA><NA>
22<NA><NA><NA>
23상호영업소소재지(도로명)전화번호
24월드오락실전라북도 순창군 순창읍 장류로 358-1653-8830

Duplicate rows

Most frequently occurring

노래연습장 현황Unnamed: 1Unnamed: 2# duplicates
1<NA><NA><NA>5
0상호영업소소재지(도로명)전화번호2