Overview

Dataset statistics

Number of variables5
Number of observations613
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory24.1 KiB
Average record size in memory40.2 B

Variable types

Text4
Categorical1

Dataset

Description비영리 민간단체란 영리가 아닌 공익활동을 수행하는 것을 목적으로 하는 민간단체로써 관련법에 따라 등록된 단체로 비영리 민간단체 등록현황을 제공함
Author전라남도
URLhttps://www.data.go.kr/data/3036079/fileData.do

Alerts

단체명칭 has unique valuesUnique

Reproduction

Analysis started2023-12-12 02:49:33.084616
Analysis finished2023-12-12 02:49:33.895554
Duration0.81 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

단체명칭
Text

UNIQUE 

Distinct613
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2023-12-12T11:49:34.093773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length22
Mean length11.350734
Min length3

Characters and Unicode

Total characters6958
Distinct characters377
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique613 ?
Unique (%)100.0%

Sample

1st row사)여수시새마을회
2nd row사)전남장애인재활협회
3rd row완도군 청년회
4th row전국산림보호협회 광주ㆍ전남협의회
5th row참여와 자치를 위한 여수시민모임 협의회
ValueCountFrequency (%)
바르게살기운동 10
 
1.1%
전라남도지부 8
 
0.8%
모임 7
 
0.7%
사)범국민예의생활실천 7
 
0.7%
한국자유총연맹 6
 
0.6%
새마을운동 5
 
0.5%
해병대전우회 5
 
0.5%
운동본부 5
 
0.5%
전남지부 5
 
0.5%
협의회 4
 
0.4%
Other values (795) 880
93.4%
2023-12-12T11:49:34.535654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
회 403
 
5.8%
339
 
4.9%
전 223
 
3.2%
지 202
 
2.9%
남 188
 
2.7%
사 179
 
2.6%
협 145
 
2.1%
부 132
 
1.9%
연 130
 
1.9%
의 119
 
1.7%
Other values (367) 4898
70.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6416
92.2%
Space Separator 339
 
4.9%
Close Punctuation 75
 
1.1%
Uppercase Letter 44
 
0.6%
Decimal Number 40
 
0.6%
Open Punctuation 20
 
0.3%
Other Punctuation 16
 
0.2%
Lowercase Letter 7
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
회 403
 
6.3%
전 223
 
3.5%
지 202
 
3.1%
남 188
 
2.9%
사 179
 
2.8%
협 145
 
2.3%
부 132
 
2.1%
연 130
 
2.0%
의 119
 
1.9%
국 103
 
1.6%
Other values (333) 4592
71.6%
Uppercase Letter
ValueCountFrequency (%)
C 9
20.5%
Y 8
18.2%
A 6
13.6%
M 3
 
6.8%
O 3
 
6.8%
K 3
 
6.8%
W 3
 
6.8%
G 2
 
4.5%
N 2
 
4.5%
E 2
 
4.5%
Other values (3) 3
 
6.8%
Decimal Number
ValueCountFrequency (%)
1 16
40.0%
2 10
25.0%
8 5
 
12.5%
5 4
 
10.0%
6 2
 
5.0%
9 2
 
5.0%
3 1
 
2.5%
Other Punctuation
ValueCountFrequency (%)
. 8
50.0%
· 5
31.2%
, 2
 
12.5%
& 1
 
6.2%
Lowercase Letter
ValueCountFrequency (%)
o 2
28.6%
g 2
28.6%
n 2
28.6%
a 1
14.3%
Close Punctuation
ValueCountFrequency (%)
) 74
98.7%
」 1
 
1.3%
Open Punctuation
ValueCountFrequency (%)
( 19
95.0%
「 1
 
5.0%
Space Separator
ValueCountFrequency (%)
339
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6416
92.2%
Common 491
 
7.1%
Latin 51
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
회 403
 
6.3%
전 223
 
3.5%
지 202
 
3.1%
남 188
 
2.9%
사 179
 
2.8%
협 145
 
2.3%
부 132
 
2.1%
연 130
 
2.0%
의 119
 
1.9%
국 103
 
1.6%
Other values (333) 4592
71.6%
Common
ValueCountFrequency (%)
339
69.0%
) 74
 
15.1%
( 19
 
3.9%
1 16
 
3.3%
2 10
 
2.0%
. 8
 
1.6%
· 5
 
1.0%
8 5
 
1.0%
5 4
 
0.8%
6 2
 
0.4%
Other values (7) 9
 
1.8%
Latin
ValueCountFrequency (%)
C 9
17.6%
Y 8
15.7%
A 6
11.8%
M 3
 
5.9%
O 3
 
5.9%
K 3
 
5.9%
W 3
 
5.9%
G 2
 
3.9%
o 2
 
3.9%
g 2
 
3.9%
Other values (7) 10
19.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6414
92.2%
ASCII 535
 
7.7%
None 7
 
0.1%
Compat Jamo 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
회 403
 
6.3%
전 223
 
3.5%
지 202
 
3.1%
남 188
 
2.9%
사 179
 
2.8%
협 145
 
2.3%
부 132
 
2.1%
연 130
 
2.0%
의 119
 
1.9%
국 103
 
1.6%
Other values (332) 4590
71.6%
ASCII
ValueCountFrequency (%)
339
63.4%
) 74
 
13.8%
( 19
 
3.6%
1 16
 
3.0%
2 10
 
1.9%
C 9
 
1.7%
. 8
 
1.5%
Y 8
 
1.5%
A 6
 
1.1%
8 5
 
0.9%
Other values (21) 41
 
7.7%
None
ValueCountFrequency (%)
· 5
71.4%
」 1
 
14.3%
「 1
 
14.3%
Compat Jamo
ValueCountFrequency (%)
ㆍ 2
100.0%

사무소의 소재지
Text

Distinct590
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2023-12-12T11:49:34.985496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length32
Mean length22.057096
Min length10

Characters and Unicode

Total characters13521
Distinct characters266
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

Unique572 ?
Unique (%)93.3%

Sample

1st row전라남도 여수시 장성마을길 5(안산동)
2nd row전라남도 나주시 중앙동 85번지 3호
3rd row전남 완도군 완도읍 장보고대로 142-2
4th row전라남도 화순군 화순읍 광덕리 7번지 9호
5th row전라남도 여수시 학동 68-19
ValueCountFrequency (%)
전라남도 322
 
10.8%
전남 267
 
9.0%
목포시 135
 
4.5%
여수시 78
 
2.6%
순천시 73
 
2.4%
나주시 46
 
1.5%
광양시 35
 
1.2%
2층 31
 
1.0%
화순군 27
 
0.9%
무안군 25
 
0.8%
Other values (1115) 1944
65.2%
2023-12-12T11:49:35.553018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2952
21.8%
남 692
 
5.1%
전 601
 
4.4%
1 496
 
3.7%
도 385
 
2.8%
시 383
 
2.8%
2 355
 
2.6%
라 332
 
2.5%
동 316
 
2.3%
3 273
 
2.0%
Other values (256) 6736
49.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7670
56.7%
Space Separator 2952
 
21.8%
Decimal Number 2326
 
17.2%
Dash Punctuation 233
 
1.7%
Close Punctuation 121
 
0.9%
Open Punctuation 121
 
0.9%
Other Punctuation 85
 
0.6%
Uppercase Letter 11
 
0.1%
Lowercase Letter 1
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 692
 
9.0%
전 601
 
7.8%
도 385
 
5.0%
시 383
 
5.0%
라 332
 
4.3%
동 316
 
4.1%
군 241
 
3.1%
읍 221
 
2.9%
번 200
 
2.6%
로 197
 
2.6%
Other values (229) 4102
53.5%
Decimal Number
ValueCountFrequency (%)
1 496
21.3%
2 355
15.3%
3 273
11.7%
4 203
8.7%
5 198
 
8.5%
6 181
 
7.8%
7 173
 
7.4%
9 154
 
6.6%
0 149
 
6.4%
8 144
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
C 2
18.2%
B 2
18.2%
K 2
18.2%
T 2
18.2%
A 1
9.1%
D 1
9.1%
G 1
9.1%
Other Punctuation
ValueCountFrequency (%)
, 79
92.9%
. 3
 
3.5%
/ 2
 
2.4%
@ 1
 
1.2%
Space Separator
ValueCountFrequency (%)
2952
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 233
100.0%
Close Punctuation
ValueCountFrequency (%)
) 121
100.0%
Open Punctuation
ValueCountFrequency (%)
( 121
100.0%
Lowercase Letter
ValueCountFrequency (%)
a 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7670
56.7%
Common 5839
43.2%
Latin 12
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 692
 
9.0%
전 601
 
7.8%
도 385
 
5.0%
시 383
 
5.0%
라 332
 
4.3%
동 316
 
4.1%
군 241
 
3.1%
읍 221
 
2.9%
번 200
 
2.6%
로 197
 
2.6%
Other values (229) 4102
53.5%
Common
ValueCountFrequency (%)
2952
50.6%
1 496
 
8.5%
2 355
 
6.1%
3 273
 
4.7%
- 233
 
4.0%
4 203
 
3.5%
5 198
 
3.4%
6 181
 
3.1%
7 173
 
3.0%
9 154
 
2.6%
Other values (9) 621
 
10.6%
Latin
ValueCountFrequency (%)
C 2
16.7%
B 2
16.7%
K 2
16.7%
T 2
16.7%
A 1
8.3%
a 1
8.3%
D 1
8.3%
G 1
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7670
56.7%
ASCII 5851
43.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2952
50.5%
1 496
 
8.5%
2 355
 
6.1%
3 273
 
4.7%
- 233
 
4.0%
4 203
 
3.5%
5 198
 
3.4%
6 181
 
3.1%
7 173
 
3.0%
9 154
 
2.6%
Other values (17) 633
 
10.8%
Hangul
ValueCountFrequency (%)
남 692
 
9.0%
전 601
 
7.8%
도 385
 
5.0%
시 383
 
5.0%
라 332
 
4.3%
동 316
 
4.1%
군 241
 
3.1%
읍 221
 
2.9%
번 200
 
2.6%
로 197
 
2.6%
Other values (229) 4102
53.5%

지역
Categorical

Distinct25
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
목포
135 
여수
78 
순천
74 
나주
46 
광양
36 
Other values (20)
244 

Length

Max length3
Median length2
Mean length2.0032626
Min length2

Unique

Unique2 ?
Unique (%)0.3%

Sample

1st row여수
2nd row나주
3rd row완도
4th row화순
5th row여수

Common Values

ValueCountFrequency (%)
목포 135
22.0%
여수 78
12.7%
순천 74
12.1%
나주 46
 
7.5%
광양 36
 
5.9%
화순 26
 
4.2%
무안 25
 
4.1%
영광 23
 
3.8%
영암 17
 
2.8%
장흥 16
 
2.6%
Other values (15) 137
22.3%

Length

2023-12-12T11:49:35.722744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
목포 136
22.2%
여수 78
12.7%
순천 74
12.1%
나주 46
 
7.5%
광양 36
 
5.9%
화순 27
 
4.4%
무안 25
 
4.1%
영광 23
 
3.8%
영암 17
 
2.8%
장흥 16
 
2.6%
Other values (13) 135
22.0%

등록연월일
Text

Distinct316
Distinct (%)51.5%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2023-12-12T11:49:36.051201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters6130
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

Unique203 ?
Unique (%)33.1%

Sample

1st row2000-05-01
2nd row2000-05-08
3rd row2000-05-08
4th row2000-05-08
5th row2000-05-08
ValueCountFrequency (%)
2000-05-08 97
 
15.8%
2000-05-01 17
 
2.8%
2007-05-09 8
 
1.3%
2001-12-31 6
 
1.0%
2008-10-23 6
 
1.0%
2000-04-28 5
 
0.8%
2005-03-19 5
 
0.8%
2007-02-20 5
 
0.8%
2007-04-18 5
 
0.8%
2007-07-24 5
 
0.8%
Other values (306) 454
74.1%
2023-12-12T11:49:36.545619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2016
32.9%
- 1226
20.0%
2 1032
16.8%
1 629
 
10.3%
5 243
 
4.0%
8 237
 
3.9%
3 211
 
3.4%
7 146
 
2.4%
9 137
 
2.2%
4 130
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4904
80.0%
Dash Punctuation 1226
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2016
41.1%
2 1032
21.0%
1 629
 
12.8%
5 243
 
5.0%
8 237
 
4.8%
3 211
 
4.3%
7 146
 
3.0%
9 137
 
2.8%
4 130
 
2.7%
6 123
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 1226
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6130
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2016
32.9%
- 1226
20.0%
2 1032
16.8%
1 629
 
10.3%
5 243
 
4.0%
8 237
 
3.9%
3 211
 
3.4%
7 146
 
2.4%
9 137
 
2.2%
4 130
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6130
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2016
32.9%
- 1226
20.0%
2 1032
16.8%
1 629
 
10.3%
5 243
 
4.0%
8 237
 
3.9%
3 211
 
3.4%
7 146
 
2.4%
9 137
 
2.2%
4 130
 
2.1%

주된사업
Text

Distinct574
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2023-12-12T11:49:36.788205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length154
Median length97
Mean length37.389886
Min length6

Characters and Unicode

Total characters22920
Distinct characters459
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique558 ?
Unique (%)91.0%

Sample

1st row생활의식개혁/새마을국민교육/민간사회안전망 운동
2nd row장애인복지증진과 권익보호
3rd row지역봉사/청년의식개혁
4th row산림 식수원보호
5th row시정감시/교통문화 확립/관광문화개선
ValueCountFrequency (%)
및 382
 
7.6%
등 319
 
6.3%
위한 198
 
3.9%
사업 135
 
2.7%
추진 73
 
1.4%
교육 57
 
1.1%
필요한 54
 
1.1%
대한 41
 
0.8%
목적 40
 
0.8%
단체의 36
 
0.7%
Other values (2166) 3723
73.6%
2023-12-12T11:49:37.236199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4612
 
20.1%
사 880
 
3.8%
/ 493
 
2.2%
업 480
 
2.1%
한 416
 
1.8%
동 410
 
1.8%
및 395
 
1.7%
등 357
 
1.6%
의 357
 
1.6%
지 353
 
1.5%
Other values (449) 14167
61.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 17369
75.8%
Space Separator 4612
 
20.1%
Other Punctuation 867
 
3.8%
Decimal Number 20
 
0.1%
Close Punctuation 14
 
0.1%
Open Punctuation 14
 
0.1%
Uppercase Letter 11
 
< 0.1%
Lowercase Letter 7
 
< 0.1%
Dash Punctuation 2
 
< 0.1%
Final Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 880
 
5.1%
업 480
 
2.8%
한 416
 
2.4%
동 410
 
2.4%
및 395
 
2.3%
등 357
 
2.1%
의 357
 
2.1%
지 353
 
2.0%
활 343
 
2.0%
교 267
 
1.5%
Other values (416) 13111
75.5%
Uppercase Letter
ValueCountFrequency (%)
W 2
18.2%
C 1
9.1%
A 1
9.1%
Y 1
9.1%
D 1
9.1%
N 1
9.1%
G 1
9.1%
O 1
9.1%
T 1
9.1%
I 1
9.1%
Lowercase Letter
ValueCountFrequency (%)
l 2
28.6%
n 1
14.3%
g 1
14.3%
y 1
14.3%
e 1
14.3%
i 1
14.3%
Other Punctuation
ValueCountFrequency (%)
/ 493
56.9%
, 305
35.2%
· 43
 
5.0%
. 25
 
2.9%
; 1
 
0.1%
Decimal Number
ValueCountFrequency (%)
1 7
35.0%
8 5
25.0%
5 5
25.0%
2 3
15.0%
Close Punctuation
ValueCountFrequency (%)
) 13
92.9%
」 1
 
7.1%
Open Punctuation
ValueCountFrequency (%)
( 13
92.9%
「 1
 
7.1%
Space Separator
ValueCountFrequency (%)
4612
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 2
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 17369
75.8%
Common 5533
 
24.1%
Latin 18
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 880
 
5.1%
업 480
 
2.8%
한 416
 
2.4%
동 410
 
2.4%
및 395
 
2.3%
등 357
 
2.1%
의 357
 
2.1%
지 353
 
2.0%
활 343
 
2.0%
교 267
 
1.5%
Other values (416) 13111
75.5%
Common
ValueCountFrequency (%)
4612
83.4%
/ 493
 
8.9%
, 305
 
5.5%
· 43
 
0.8%
. 25
 
0.5%
) 13
 
0.2%
( 13
 
0.2%
1 7
 
0.1%
8 5
 
0.1%
5 5
 
0.1%
Other values (7) 12
 
0.2%
Latin
ValueCountFrequency (%)
W 2
 
11.1%
l 2
 
11.1%
C 1
 
5.6%
n 1
 
5.6%
g 1
 
5.6%
A 1
 
5.6%
Y 1
 
5.6%
y 1
 
5.6%
e 1
 
5.6%
D 1
 
5.6%
Other values (6) 6
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 17365
75.8%
ASCII 5502
 
24.0%
None 45
 
0.2%
Compat Jamo 4
 
< 0.1%
Punctuation 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4612
83.8%
/ 493
 
9.0%
, 305
 
5.5%
. 25
 
0.5%
) 13
 
0.2%
( 13
 
0.2%
1 7
 
0.1%
8 5
 
0.1%
5 5
 
0.1%
2 3
 
0.1%
Other values (18) 21
 
0.4%
Hangul
ValueCountFrequency (%)
사 880
 
5.1%
업 480
 
2.8%
한 416
 
2.4%
동 410
 
2.4%
및 395
 
2.3%
등 357
 
2.1%
의 357
 
2.1%
지 353
 
2.0%
활 343
 
2.0%
교 267
 
1.5%
Other values (415) 13107
75.5%
None
ValueCountFrequency (%)
· 43
95.6%
」 1
 
2.2%
「 1
 
2.2%
Compat Jamo
ValueCountFrequency (%)
ㆍ 4
100.0%
Punctuation
ValueCountFrequency (%)
’ 2
50.0%
‘ 2
50.0%

Missing values

2023-12-12T11:49:33.733075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:49:33.847567image/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

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