Overview

Dataset statistics

Number of variables9
Number of observations200
Missing cells244
Missing cells (%)13.6%
Duplicate rows1
Duplicate rows (%)0.5%
Total size in memory14.2 KiB
Average record size in memory72.7 B

Variable types

Text7
Categorical2

Dataset

Description후원방문판매등록현황201510
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=202530

Alerts

Unnamed: 8 has constant value ""Constant
Dataset has 1 (0.5%) duplicate rowsDuplicates
Unnamed: 2 is highly overall correlated with Unnamed: 7High correlation
Unnamed: 7 is highly overall correlated with Unnamed: 2High correlation
전라북도 후원방문판매 등록현황(`15.10.12.기준) has 7 (3.5%) missing valuesMissing
Unnamed: 1 has 6 (3.0%) missing valuesMissing
Unnamed: 3 has 7 (3.5%) missing valuesMissing
Unnamed: 4 has 7 (3.5%) missing valuesMissing
Unnamed: 5 has 11 (5.5%) missing valuesMissing
Unnamed: 6 has 7 (3.5%) missing valuesMissing
Unnamed: 8 has 199 (99.5%) missing valuesMissing

Reproduction

Analysis started2024-03-14 02:24:22.070803
Analysis finished2024-03-14 02:24:22.803459
Duration0.73 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

전라북도 후원방문판매 등록현황(`15.10.12.기준)
Text

MISSING 

Distinct193
Distinct (%)100.0%
Missing7
Missing (%)3.5%
Memory size1.7 KiB
2024-03-14T11:24:23.083151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.4352332
Min length1

Characters and Unicode

Total characters470
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique193 ?
Unique (%)100.0%

Sample

1st row연번
2nd row1
3rd row2
4th row3
5th row4
ValueCountFrequency (%)
47 1
 
0.5%
98 1
 
0.5%
132 1
 
0.5%
123 1
 
0.5%
124 1
 
0.5%
125 1
 
0.5%
126 1
 
0.5%
127 1
 
0.5%
128 1
 
0.5%
129 1
 
0.5%
Other values (183) 183
94.8%
2024-03-14T11:24:23.578365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 133
28.3%
2 40
 
8.5%
4 39
 
8.3%
7 39
 
8.3%
3 39
 
8.3%
5 39
 
8.3%
6 39
 
8.3%
8 39
 
8.3%
9 32
 
6.8%
0 29
 
6.2%
Other values (2) 2
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 468
99.6%
Other Letter 2
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 133
28.4%
2 40
 
8.5%
4 39
 
8.3%
7 39
 
8.3%
3 39
 
8.3%
5 39
 
8.3%
6 39
 
8.3%
8 39
 
8.3%
9 32
 
6.8%
0 29
 
6.2%
Other Letter
ValueCountFrequency (%)
연 1
50.0%
번 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 468
99.6%
Hangul 2
 
0.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1 133
28.4%
2 40
 
8.5%
4 39
 
8.3%
7 39
 
8.3%
3 39
 
8.3%
5 39
 
8.3%
6 39
 
8.3%
8 39
 
8.3%
9 32
 
6.8%
0 29
 
6.2%
Hangul
ValueCountFrequency (%)
연 1
50.0%
번 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 468
99.6%
Hangul 2
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 133
28.4%
2 40
 
8.5%
4 39
 
8.3%
7 39
 
8.3%
3 39
 
8.3%
5 39
 
8.3%
6 39
 
8.3%
8 39
 
8.3%
9 32
 
6.8%
0 29
 
6.2%
Hangul
ValueCountFrequency (%)
연 1
50.0%
번 1
50.0%

Unnamed: 1
Text

MISSING 

Distinct189
Distinct (%)97.4%
Missing6
Missing (%)3.0%
Memory size1.7 KiB
2024-03-14T11:24:23.826680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length16
Mean length9.2835052
Min length2

Characters and Unicode

Total characters1801
Distinct characters180
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique186 ?
Unique (%)95.9%

Sample

1st row상 호
2nd row한국화장품 전북대리점
3rd row전주 진북지사
4th row녹십초 전주지사
5th row유니베라남전주대리점
ValueCountFrequency (%)
마임 27
 
9.0%
폐업 14
 
4.7%
김정문알로에 8
 
2.7%
오휘 8
 
2.7%
뉴랜드알로에 7
 
2.3%
5
 
1.7%
유니베라 5
 
1.7%
아모레 4
 
1.3%
뉴랜드 3
 
1.0%
알로에 3
 
1.0%
Other values (206) 216
72.0%
2024-03-14T11:24:24.146314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
107
 
5.9%
사 101
 
5.6%
지 100
 
5.6%
임 66
 
3.7%
마 63
 
3.5%
점 57
 
3.2%
) 50
 
2.8%
( 49
 
2.7%
업 42
 
2.3%
폐 37
 
2.1%
Other values (170) 1129
62.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1566
87.0%
Space Separator 107
 
5.9%
Close Punctuation 50
 
2.8%
Open Punctuation 49
 
2.7%
Other Punctuation 13
 
0.7%
Uppercase Letter 9
 
0.5%
Decimal Number 7
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 101
 
6.4%
지 100
 
6.4%
임 66
 
4.2%
마 63
 
4.0%
점 57
 
3.6%
업 42
 
2.7%
폐 37
 
2.4%
에 33
 
2.1%
산 32
 
2.0%
로 32
 
2.0%
Other values (153) 1003
64.0%
Other Punctuation
ValueCountFrequency (%)
: 5
38.5%
/ 3
23.1%
. 3
23.1%
※ 1
 
7.7%
, 1
 
7.7%
Decimal Number
ValueCountFrequency (%)
1 3
42.9%
4 1
 
14.3%
3 1
 
14.3%
5 1
 
14.3%
6 1
 
14.3%
Uppercase Letter
ValueCountFrequency (%)
G 4
44.4%
L 3
33.3%
C 1
 
11.1%
K 1
 
11.1%
Space Separator
ValueCountFrequency (%)
107
100.0%
Close Punctuation
ValueCountFrequency (%)
) 50
100.0%
Open Punctuation
ValueCountFrequency (%)
( 49
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1566
87.0%
Common 226
 
12.5%
Latin 9
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 101
 
6.4%
지 100
 
6.4%
임 66
 
4.2%
마 63
 
4.0%
점 57
 
3.6%
업 42
 
2.7%
폐 37
 
2.4%
에 33
 
2.1%
산 32
 
2.0%
로 32
 
2.0%
Other values (153) 1003
64.0%
Common
ValueCountFrequency (%)
107
47.3%
) 50
22.1%
( 49
21.7%
: 5
 
2.2%
/ 3
 
1.3%
. 3
 
1.3%
1 3
 
1.3%
4 1
 
0.4%
3 1
 
0.4%
5 1
 
0.4%
Other values (3) 3
 
1.3%
Latin
ValueCountFrequency (%)
G 4
44.4%
L 3
33.3%
C 1
 
11.1%
K 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1566
87.0%
ASCII 234
 
13.0%
Punctuation 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
107
45.7%
) 50
21.4%
( 49
20.9%
: 5
 
2.1%
G 4
 
1.7%
/ 3
 
1.3%
L 3
 
1.3%
. 3
 
1.3%
1 3
 
1.3%
4 1
 
0.4%
Other values (6) 6
 
2.6%
Hangul
ValueCountFrequency (%)
사 101
 
6.4%
지 100
 
6.4%
임 66
 
4.2%
마 63
 
4.0%
점 57
 
3.6%
업 42
 
2.7%
폐 37
 
2.4%
에 33
 
2.1%
산 32
 
2.0%
로 32
 
2.0%
Other values (153) 1003
64.0%
Punctuation
ValueCountFrequency (%)
※ 1
100.0%

Unnamed: 2
Categorical

HIGH CORRELATION 

Distinct39
Distinct (%)19.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2013.08.07
59 
2013.08.13
36 
2013.08.12
23 
2013.08.06
20 
2013.08.16
15 
Other values (34)
47 

Length

Max length11
Median length10
Mean length9.8
Min length3

Unique

Unique28 ?
Unique (%)14.0%

Sample

1st row등록일
2nd row2013.06.27
3rd row2013.07.19
4th row2013.07.26
5th row2013.08.05

Common Values

ValueCountFrequency (%)
2013.08.07 59
29.5%
2013.08.13 36
18.0%
2013.08.12 23
 
11.5%
2013.08.06 20
 
10.0%
2013.08.16 15
 
7.5%
<NA> 7
 
3.5%
2013.08.27 3
 
1.5%
2013.08.29 3
 
1.5%
2015.03.03 2
 
1.0%
2014.06.27. 2
 
1.0%
Other values (29) 30
15.0%

Length

2024-03-14T11:24:24.271719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2013.08.07 59
29.5%
2013.08.13 36
18.0%
2013.08.12 23
 
11.5%
2013.08.06 20
 
10.0%
2013.08.16 15
 
7.5%
na 7
 
3.5%
2013.08.27 3
 
1.5%
2013.08.29 3
 
1.5%
2015.03.03 2
 
1.0%
2014.06.27 2
 
1.0%
Other values (29) 30
15.0%

Unnamed: 3
Text

MISSING 

Distinct193
Distinct (%)100.0%
Missing7
Missing (%)3.5%
Memory size1.7 KiB
2024-03-14T11:24:24.460498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.170984
Min length4

Characters and Unicode

Total characters2349
Distinct characters19
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique193 ?
Unique (%)100.0%

Sample

1st row등록번호
2nd row전북 2013-제1호
3rd row전북 2013-제2호
4th row전북 2013-제3호
5th row전북 2013-제4호
ValueCountFrequency (%)
전북 192
49.9%
2013-제144호 1
 
0.3%
2013-제122호 1
 
0.3%
2013-제132호 1
 
0.3%
2013-제123호 1
 
0.3%
2013-제124호 1
 
0.3%
2013-제125호 1
 
0.3%
2013-제126호 1
 
0.3%
2013-제127호 1
 
0.3%
2013-제128호 1
 
0.3%
Other values (184) 184
47.8%
2024-03-14T11:24:24.795423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 307
13.1%
2 232
9.9%
0 220
9.4%
3 207
8.8%
호 193
8.2%
전 192
8.2%
192
8.2%
- 192
8.2%
제 192
8.2%
북 192
8.2%
Other values (9) 230
9.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1193
50.8%
Other Letter 772
32.9%
Space Separator 192
 
8.2%
Dash Punctuation 192
 
8.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 307
25.7%
2 232
19.4%
0 220
18.4%
3 207
17.4%
5 55
 
4.6%
4 50
 
4.2%
6 37
 
3.1%
7 29
 
2.4%
8 28
 
2.3%
9 28
 
2.3%
Other Letter
ValueCountFrequency (%)
호 193
25.0%
전 192
24.9%
제 192
24.9%
북 192
24.9%
등 1
 
0.1%
록 1
 
0.1%
번 1
 
0.1%
Space Separator
ValueCountFrequency (%)
192
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 192
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1577
67.1%
Hangul 772
32.9%

Most frequent character per script

Common
ValueCountFrequency (%)
1 307
19.5%
2 232
14.7%
0 220
14.0%
3 207
13.1%
192
12.2%
- 192
12.2%
5 55
 
3.5%
4 50
 
3.2%
6 37
 
2.3%
7 29
 
1.8%
Other values (2) 56
 
3.6%
Hangul
ValueCountFrequency (%)
호 193
25.0%
전 192
24.9%
제 192
24.9%
북 192
24.9%
등 1
 
0.1%
록 1
 
0.1%
번 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1577
67.1%
Hangul 772
32.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 307
19.5%
2 232
14.7%
0 220
14.0%
3 207
13.1%
192
12.2%
- 192
12.2%
5 55
 
3.5%
4 50
 
3.2%
6 37
 
2.3%
7 29
 
1.8%
Other values (2) 56
 
3.6%
Hangul
ValueCountFrequency (%)
호 193
25.0%
전 192
24.9%
제 192
24.9%
북 192
24.9%
등 1
 
0.1%
록 1
 
0.1%
번 1
 
0.1%

Unnamed: 4
Text

MISSING 

Distinct191
Distinct (%)99.0%
Missing7
Missing (%)3.5%
Memory size1.7 KiB
2024-03-14T11:24:25.070687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length41
Mean length30.875648
Min length7

Characters and Unicode

Total characters5959
Distinct characters187
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 (%)97.9%

Sample

1st row사업장 소재지
2nd row전라북도 김제시 요촌동 288번지 38호
3rd row전라북도 전주시 완산구 서노송동 642번지 13호
4th row전라북도 전주시 완산구 서노송동 568번지 88호 용호빌딩
5th row전라북도 전주시 완산구 중화산동2가 744번지 6호
ValueCountFrequency (%)
전라북도 186
 
16.6%
전주시 80
 
7.1%
완산구 52
 
4.6%
익산시 33
 
2.9%
덕진구 28
 
2.5%
군산시 25
 
2.2%
1호 19
 
1.7%
김제시 14
 
1.2%
2층 14
 
1.2%
정읍시 13
 
1.2%
Other values (411) 656
58.6%
2024-03-14T11:24:25.670662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1801
30.2%
전 275
 
4.6%
북 195
 
3.3%
라 192
 
3.2%
도 188
 
3.2%
1 185
 
3.1%
동 182
 
3.1%
시 177
 
3.0%
2 163
 
2.7%
호 151
 
2.5%
Other values (177) 2450
41.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3091
51.9%
Space Separator 1801
30.2%
Decimal Number 924
 
15.5%
Close Punctuation 46
 
0.8%
Open Punctuation 46
 
0.8%
Other Punctuation 39
 
0.7%
Dash Punctuation 11
 
0.2%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 275
 
8.9%
북 195
 
6.3%
라 192
 
6.2%
도 188
 
6.1%
동 182
 
5.9%
시 177
 
5.7%
호 151
 
4.9%
지 143
 
4.6%
산 134
 
4.3%
번 132
 
4.3%
Other values (158) 1322
42.8%
Decimal Number
ValueCountFrequency (%)
1 185
20.0%
2 163
17.6%
3 110
11.9%
4 94
10.2%
5 81
8.8%
0 75
8.1%
8 64
 
6.9%
6 62
 
6.7%
7 50
 
5.4%
9 40
 
4.3%
Other Punctuation
ValueCountFrequency (%)
, 35
89.7%
@ 2
 
5.1%
/ 1
 
2.6%
. 1
 
2.6%
Space Separator
ValueCountFrequency (%)
1801
100.0%
Close Punctuation
ValueCountFrequency (%)
) 46
100.0%
Open Punctuation
ValueCountFrequency (%)
( 46
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Uppercase Letter
ValueCountFrequency (%)
K 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3091
51.9%
Common 2867
48.1%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 275
 
8.9%
북 195
 
6.3%
라 192
 
6.2%
도 188
 
6.1%
동 182
 
5.9%
시 177
 
5.7%
호 151
 
4.9%
지 143
 
4.6%
산 134
 
4.3%
번 132
 
4.3%
Other values (158) 1322
42.8%
Common
ValueCountFrequency (%)
1801
62.8%
1 185
 
6.5%
2 163
 
5.7%
3 110
 
3.8%
4 94
 
3.3%
5 81
 
2.8%
0 75
 
2.6%
8 64
 
2.2%
6 62
 
2.2%
7 50
 
1.7%
Other values (8) 182
 
6.3%
Latin
ValueCountFrequency (%)
K 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3091
51.9%
ASCII 2868
48.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1801
62.8%
1 185
 
6.5%
2 163
 
5.7%
3 110
 
3.8%
4 94
 
3.3%
5 81
 
2.8%
0 75
 
2.6%
8 64
 
2.2%
6 62
 
2.2%
7 50
 
1.7%
Other values (9) 183
 
6.4%
Hangul
ValueCountFrequency (%)
전 275
 
8.9%
북 195
 
6.3%
라 192
 
6.2%
도 188
 
6.1%
동 182
 
5.9%
시 177
 
5.7%
호 151
 
4.9%
지 143
 
4.6%
산 134
 
4.3%
번 132
 
4.3%
Other values (158) 1322
42.8%

Unnamed: 5
Text

MISSING 

Distinct169
Distinct (%)89.4%
Missing11
Missing (%)5.5%
Memory size1.7 KiB
2024-03-14T11:24:25.924664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.962963
Min length4

Characters and Unicode

Total characters2261
Distinct characters17
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique150 ?
Unique (%)79.4%

Sample

1st row연락처1
2nd row063-544-1060
3rd row063-285-4123
4th row063-231-0947
5th row063-286-2753
ValueCountFrequency (%)
063-283-0002 3
 
1.6%
063-231-8030 2
 
1.1%
063-835-4123 2
 
1.1%
063-544-8275 2
 
1.1%
063-253-0900 2
 
1.1%
063-212-8876 2
 
1.1%
063-291-9177 2
 
1.1%
063-236-3371 2
 
1.1%
063-543-3653 2
 
1.1%
063-532-2875 2
 
1.1%
Other values (159) 168
88.9%
2024-03-14T11:24:26.219862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 374
16.5%
3 336
14.9%
0 301
13.3%
6 297
13.1%
2 218
9.6%
5 170
7.5%
8 143
 
6.3%
4 143
 
6.3%
7 108
 
4.8%
1 107
 
4.7%
Other values (7) 64
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1880
83.1%
Dash Punctuation 374
 
16.5%
Other Letter 5
 
0.2%
Other Punctuation 2
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 336
17.9%
0 301
16.0%
6 297
15.8%
2 218
11.6%
5 170
9.0%
8 143
7.6%
4 143
7.6%
7 108
 
5.7%
1 107
 
5.7%
9 57
 
3.0%
Other Letter
ValueCountFrequency (%)
연 1
20.0%
락 1
20.0%
처 1
20.0%
현 1
20.0%
재 1
20.0%
Dash Punctuation
ValueCountFrequency (%)
- 374
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2256
99.8%
Hangul 5
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
- 374
16.6%
3 336
14.9%
0 301
13.3%
6 297
13.2%
2 218
9.7%
5 170
7.5%
8 143
 
6.3%
4 143
 
6.3%
7 108
 
4.8%
1 107
 
4.7%
Other values (2) 59
 
2.6%
Hangul
ValueCountFrequency (%)
연 1
20.0%
락 1
20.0%
처 1
20.0%
현 1
20.0%
재 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2256
99.8%
Hangul 5
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 374
16.6%
3 336
14.9%
0 301
13.3%
6 297
13.2%
2 218
9.7%
5 170
7.5%
8 143
 
6.3%
4 143
 
6.3%
7 108
 
4.8%
1 107
 
4.7%
Other values (2) 59
 
2.6%
Hangul
ValueCountFrequency (%)
연 1
20.0%
락 1
20.0%
처 1
20.0%
현 1
20.0%
재 1
20.0%

Unnamed: 6
Text

MISSING 

Distinct180
Distinct (%)93.3%
Missing7
Missing (%)3.5%
Memory size1.7 KiB
2024-03-14T11:24:26.521942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters579
Distinct characters120
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique169 ?
Unique (%)87.6%

Sample

1st row대표자
2nd row김용우
3rd row유종숙
4th row국건웅
5th row황점옥
ValueCountFrequency (%)
이진숙 3
 
1.5%
문경숙 3
 
1.5%
양현기 2
 
1.0%
백남환 2
 
1.0%
변상완 2
 
1.0%
최을숙 2
 
1.0%
배효장 2
 
1.0%
민병기 2
 
1.0%
이문순 2
 
1.0%
강옥선 2
 
1.0%
Other values (171) 172
88.7%
2024-03-14T11:24:26.976132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 42
 
7.3%
이 33
 
5.7%
숙 27
 
4.7%
정 17
 
2.9%
영 17
 
2.9%
경 15
 
2.6%
희 14
 
2.4%
순 12
 
2.1%
자 12
 
2.1%
박 12
 
2.1%
Other values (110) 378
65.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 578
99.8%
Space Separator 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 42
 
7.3%
이 33
 
5.7%
숙 27
 
4.7%
정 17
 
2.9%
영 17
 
2.9%
경 15
 
2.6%
희 14
 
2.4%
순 12
 
2.1%
자 12
 
2.1%
박 12
 
2.1%
Other values (109) 377
65.2%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 578
99.8%
Common 1
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 42
 
7.3%
이 33
 
5.7%
숙 27
 
4.7%
정 17
 
2.9%
영 17
 
2.9%
경 15
 
2.6%
희 14
 
2.4%
순 12
 
2.1%
자 12
 
2.1%
박 12
 
2.1%
Other values (109) 377
65.2%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 578
99.8%
ASCII 1
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 42
 
7.3%
이 33
 
5.7%
숙 27
 
4.7%
정 17
 
2.9%
영 17
 
2.9%
경 15
 
2.6%
희 14
 
2.4%
순 12
 
2.1%
자 12
 
2.1%
박 12
 
2.1%
Other values (109) 377
65.2%
ASCII
ValueCountFrequency (%)
1
100.0%

Unnamed: 7
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
건강식품, 화장품/미용용품
110 
건강식품, 화장품/미용용품, 기타
30 
건강식품, 화장품/미용용품, 생활용품/세제류, 기타
24 
건강식품, 화장품/미용용품, 생활용품/세제류
 
9
<NA>
 
8
Other values (9)
19 

Length

Max length28
Median length14
Mean length15.86
Min length2

Unique

Unique6 ?
Unique (%)3.0%

Sample

1st row취급품목
2nd row화장품/미용용품
3rd row건강식품, 화장품/미용용품
4th row건강식품, 화장품/미용용품, 생활용품/세제류
5th row건강식품, 화장품/미용용품, 생활용품/세제류

Common Values

ValueCountFrequency (%)
건강식품, 화장품/미용용품 110
55.0%
건강식품, 화장품/미용용품, 기타 30
 
15.0%
건강식품, 화장품/미용용품, 생활용품/세제류, 기타 24
 
12.0%
건강식품, 화장품/미용용품, 생활용품/세제류 9
 
4.5%
<NA> 8
 
4.0%
기타 7
 
3.5%
의류/패션, 기타 4
 
2.0%
화장품/미용용품, 교육/도서, 회원권/상품권 2
 
1.0%
취급품목 1
 
0.5%
화장품/미용용품 1
 
0.5%
Other values (4) 4
 
2.0%

Length

2024-03-14T11:24:27.093906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
화장품/미용용품 177
37.5%
건강식품 175
37.1%
기타 65
 
13.8%
생활용품/세제류 35
 
7.4%
na 8
 
1.7%
의류/패션 4
 
0.8%
교육/도서 2
 
0.4%
회원권/상품권 2
 
0.4%
취급품목 1
 
0.2%
기타(이온수기 1
 
0.2%
Other values (2) 2
 
0.4%

Unnamed: 8
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing199
Missing (%)99.5%
Memory size1.7 KiB
2024-03-14T11:24:27.159964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row비고
ValueCountFrequency (%)
비고 1
100.0%
2024-03-14T11:24:27.329182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
비 1
50.0%
고 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
비 1
50.0%
고 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
비 1
50.0%
고 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
비 1
50.0%
고 1
50.0%

Correlations

2024-03-14T11:24:27.415995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 2Unnamed: 7
Unnamed: 21.0000.955
Unnamed: 70.9551.000
2024-03-14T11:24:27.491916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 7Unnamed: 2
Unnamed: 71.0000.659
Unnamed: 20.6591.000
2024-03-14T11:24:27.567460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 2Unnamed: 7
Unnamed: 21.0000.659
Unnamed: 70.6591.000

Missing values

2024-03-14T11:24:22.468913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T11:24:22.611349image/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.
2024-03-14T11:24:22.722965image/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

전라북도 후원방문판매 등록현황(`15.10.12.기준)Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8
0연번상 호등록일등록번호사업장 소재지연락처1대표자취급품목비고
11한국화장품 전북대리점2013.06.27전북 2013-제1호전라북도 김제시 요촌동 288번지 38호063-544-1060김용우화장품/미용용품<NA>
22전주 진북지사2013.07.19전북 2013-제2호전라북도 전주시 완산구 서노송동 642번지 13호063-285-4123유종숙건강식품, 화장품/미용용품<NA>
33녹십초 전주지사2013.07.26전북 2013-제3호전라북도 전주시 완산구 서노송동 568번지 88호 용호빌딩063-231-0947국건웅건강식품, 화장품/미용용품, 생활용품/세제류<NA>
44유니베라남전주대리점2013.08.05전북 2013-제4호전라북도 전주시 완산구 중화산동2가 744번지 6호063-286-2753황점옥건강식품, 화장품/미용용품, 생활용품/세제류<NA>
55유니베라신전주2013.08.06전북 2013-제5호전라북도 전주시 완산구 팔달로 244(서노송동, 2층)063-252-4946김현성화장품/미용용품, 교육/도서, 회원권/상품권<NA>
66유니베라 효자대리점2013.08.06전북 2013-제6호전라북도 전주시 완산구 효자동1가 157번지 76호063-228-7373김명희화장품/미용용품, 교육/도서, 회원권/상품권<NA>
77유니베라남양알로에전주중부대리점2013.08.06전북 2013-제7호전라북도 전주시 덕진구 금암동 1589번지 2호 2층063-272-3434이영희건강식품, 화장품/미용용품, 생활용품/세제류<NA>
88유니베라 군산제일대리점(폐업)2013.08.06전북 2013-제8호전라북도 군산시 문화동 533번지 6호063-451-0848김희녀건강식품, 화장품/미용용품, 생활용품/세제류<NA>
99유니베라익산대리점2013.08.06전북 2013-제9호전라북도 익산시 모현동1가 186번지 19호063-857-1441조복례건강식품, 화장품/미용용품, 생활용품/세제류<NA>
전라북도 후원방문판매 등록현황(`15.10.12.기준)Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8
190190유한회사 오휘중앙지사2015.08.12전북 2015-제13호전라북도 전주시 완산구 팔달로 225(고사동)063-283-0002민병기건강식품, 화장품/미용용품<NA>
191191오휘 영등지사2015.08.21전북 2015-제14호전라북도 익산시 고봉로 32길 15(영등동)063-834-4545형수옥건강식품, 화장품/미용용품<NA>
192192새찬2015.10.12전북 2015-제15호전라북도 전주시 덕진구 기린대로1018-7, 101동 1302호(여의동, 푸른솔아파트)063-228-6912이상희<NA><NA>
193<NA><NA><NA><NA><NA><NA><NA><NA><NA>
194<NA><NA><NA><NA><NA><NA><NA><NA><NA>
195<NA><NA><NA><NA><NA><NA><NA><NA><NA>
196<NA><NA><NA><NA><NA><NA><NA><NA><NA>
197<NA><NA><NA><NA><NA><NA><NA><NA><NA>
198<NA><NA><NA><NA><NA><NA><NA><NA><NA>
199<NA>※ 정상영업 : 154개소 / 폐업 : 36개소 / 휴업 : 1개소/ 등록취소: 1개소<NA><NA><NA>15.10.12현재<NA><NA><NA>

Duplicate rows

Most frequently occurring

전라북도 후원방문판매 등록현황(`15.10.12.기준)Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8# duplicates
0<NA><NA><NA><NA><NA><NA><NA><NA><NA>6