Overview

Dataset statistics

Number of variables6
Number of observations284
Missing cells39
Missing cells (%)2.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.0 KiB
Average record size in memory50.5 B

Variable types

Numeric2
Categorical2
Text2

Dataset

Description서울특별시 노원구에서 운영중이 지역화폐 노원을 사용할수 있는 가맹점의 정보로써, 행정동, 상호명, 전화번호, 사용기준율,기준일자의 정보를 포함합니다.
Author서울특별시 노원구
URLhttps://www.data.go.kr/data/15105674/fileData.do

Alerts

기준일자 has constant value ""Constant
연락처 has 39 (13.7%) missing valuesMissing
가맹점 번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 04:11:48.765350
Analysis finished2023-12-12 04:11:49.827611
Duration1.06 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

가맹점 번호
Real number (ℝ)

UNIQUE 

Distinct284
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean211.89085
Minimum32
Maximum429
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2023-12-12T13:11:49.929147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum32
5-th percentile52.15
Q1121.75
median212.5
Q3295.25
95-th percentile370.55
Maximum429
Range397
Interquartile range (IQR)173.5

Descriptive statistics

Standard deviation101.93776
Coefficient of variation (CV)0.48108617
Kurtosis-1.0798789
Mean211.89085
Median Absolute Deviation (MAD)86
Skewness0.013106795
Sum60177
Variance10391.306
MonotonicityStrictly increasing
2023-12-12T13:11:50.116523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
32 1
 
0.4%
267 1
 
0.4%
276 1
 
0.4%
275 1
 
0.4%
273 1
 
0.4%
272 1
 
0.4%
270 1
 
0.4%
269 1
 
0.4%
266 1
 
0.4%
278 1
 
0.4%
Other values (274) 274
96.5%
ValueCountFrequency (%)
32 1
0.4%
33 1
0.4%
34 1
0.4%
36 1
0.4%
37 1
0.4%
38 1
0.4%
39 1
0.4%
41 1
0.4%
42 1
0.4%
43 1
0.4%
ValueCountFrequency (%)
429 1
0.4%
415 1
0.4%
410 1
0.4%
402 1
0.4%
395 1
0.4%
393 1
0.4%
389 1
0.4%
388 1
0.4%
380 1
0.4%
378 1
0.4%

지역
Categorical

Distinct5
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
상계동
149 
월계동
43 
중계동
41 
공릉동
32 
하계동
19 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row상계동
2nd row상계동
3rd row상계동
4th row상계동
5th row상계동

Common Values

ValueCountFrequency (%)
상계동 149
52.5%
월계동 43
 
15.1%
중계동 41
 
14.4%
공릉동 32
 
11.3%
하계동 19
 
6.7%

Length

2023-12-12T13:11:50.269849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:11:50.379825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상계동 149
52.5%
월계동 43
 
15.1%
중계동 41
 
14.4%
공릉동 32
 
11.3%
하계동 19
 
6.7%

가맹점 이름
Text

Distinct283
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2023-12-12T13:11:50.712333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length18
Mean length8.6267606
Min length3

Characters and Unicode

Total characters2450
Distinct characters412
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique282 ?
Unique (%)99.3%

Sample

1st row상계숲속작은도서관카페
2nd row영생흑염소
3rd row맑은숲요가명상마을
4th row문화플랫폼더숲
5th row남송주스킨케어
ValueCountFrequency (%)
자치회관(프로그램 19
 
5.7%
카페 3
 
0.9%
노원센터 2
 
0.6%
되살림가게 2
 
0.6%
상계5동 2
 
0.6%
하계점 2
 
0.6%
한신공인중개사사무소 2
 
0.6%
1호선공인중개사 1
 
0.3%
궁노래방 1
 
0.3%
돌뫼꽃농장 1
 
0.3%
Other values (297) 297
89.5%
2023-12-12T13:11:51.309556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
332
 
13.6%
원 68
 
2.8%
( 38
 
1.6%
) 38
 
1.6%
관 35
 
1.4%
계 33
 
1.3%
로 30
 
1.2%
스 30
 
1.2%
동 29
 
1.2%
학 29
 
1.2%
Other values (402) 1788
73.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1982
80.9%
Space Separator 332
 
13.6%
Open Punctuation 38
 
1.6%
Close Punctuation 38
 
1.6%
Decimal Number 36
 
1.5%
Uppercase Letter 12
 
0.5%
Other Punctuation 10
 
0.4%
Lowercase Letter 1
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 68
 
3.4%
관 35
 
1.8%
계 33
 
1.7%
로 30
 
1.5%
스 30
 
1.5%
동 29
 
1.5%
학 29
 
1.5%
그 28
 
1.4%
프 28
 
1.4%
사 28
 
1.4%
Other values (373) 1644
82.9%
Decimal Number
ValueCountFrequency (%)
1 10
27.8%
2 8
22.2%
4 4
 
11.1%
3 3
 
8.3%
5 3
 
8.3%
8 2
 
5.6%
9 2
 
5.6%
0 2
 
5.6%
7 1
 
2.8%
6 1
 
2.8%
Uppercase Letter
ValueCountFrequency (%)
K 2
16.7%
F 2
16.7%
T 1
8.3%
A 1
8.3%
D 1
8.3%
I 1
8.3%
W 1
8.3%
C 1
8.3%
O 1
8.3%
B 1
8.3%
Other Punctuation
ValueCountFrequency (%)
. 4
40.0%
, 3
30.0%
& 2
20.0%
· 1
 
10.0%
Space Separator
ValueCountFrequency (%)
332
100.0%
Open Punctuation
ValueCountFrequency (%)
( 38
100.0%
Close Punctuation
ValueCountFrequency (%)
) 38
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1982
80.9%
Common 455
 
18.6%
Latin 13
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 68
 
3.4%
관 35
 
1.8%
계 33
 
1.7%
로 30
 
1.5%
스 30
 
1.5%
동 29
 
1.5%
학 29
 
1.5%
그 28
 
1.4%
프 28
 
1.4%
사 28
 
1.4%
Other values (373) 1644
82.9%
Common
ValueCountFrequency (%)
332
73.0%
( 38
 
8.4%
) 38
 
8.4%
1 10
 
2.2%
2 8
 
1.8%
4 4
 
0.9%
. 4
 
0.9%
3 3
 
0.7%
5 3
 
0.7%
, 3
 
0.7%
Other values (8) 12
 
2.6%
Latin
ValueCountFrequency (%)
K 2
15.4%
F 2
15.4%
e 1
7.7%
T 1
7.7%
A 1
7.7%
D 1
7.7%
I 1
7.7%
W 1
7.7%
C 1
7.7%
O 1
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1982
80.9%
ASCII 467
 
19.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
332
71.1%
( 38
 
8.1%
) 38
 
8.1%
1 10
 
2.1%
2 8
 
1.7%
4 4
 
0.9%
. 4
 
0.9%
3 3
 
0.6%
5 3
 
0.6%
, 3
 
0.6%
Other values (18) 24
 
5.1%
Hangul
ValueCountFrequency (%)
원 68
 
3.4%
관 35
 
1.8%
계 33
 
1.7%
로 30
 
1.5%
스 30
 
1.5%
동 29
 
1.5%
학 29
 
1.5%
그 28
 
1.4%
프 28
 
1.4%
사 28
 
1.4%
Other values (373) 1644
82.9%
None
ValueCountFrequency (%)
· 1
100.0%

연락처
Text

MISSING 

Distinct240
Distinct (%)98.0%
Missing39
Missing (%)13.7%
Memory size2.3 KiB
2023-12-12T13:11:51.675457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.228571
Min length12

Characters and Unicode

Total characters2996
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique235 ?
Unique (%)95.9%

Sample

1st row02-3391-7889
2nd row02-937-9267
3rd row02-930-2992
4th row02-951-0206
5th row02-931-1116
ValueCountFrequency (%)
02-3391-9691 2
 
0.8%
02-2116-4432 2
 
0.8%
02-972-5105 2
 
0.8%
02-931-3001 2
 
0.8%
02-938-8488 2
 
0.8%
02-3391-7889 1
 
0.4%
02-979-0953 1
 
0.4%
02-913-6400 1
 
0.4%
02-909-3500 1
 
0.4%
02-933-0940 1
 
0.4%
Other values (230) 230
93.9%
2023-12-12T13:11:52.221420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 490
16.4%
2 421
14.1%
0 412
13.8%
9 346
11.5%
245
8.2%
3 231
7.7%
1 190
 
6.3%
7 144
 
4.8%
6 138
 
4.6%
5 136
 
4.5%
Other values (2) 243
8.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2261
75.5%
Dash Punctuation 490
 
16.4%
Space Separator 245
 
8.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 421
18.6%
0 412
18.2%
9 346
15.3%
3 231
10.2%
1 190
8.4%
7 144
 
6.4%
6 138
 
6.1%
5 136
 
6.0%
8 127
 
5.6%
4 116
 
5.1%
Dash Punctuation
ValueCountFrequency (%)
- 490
100.0%
Space Separator
ValueCountFrequency (%)
245
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2996
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 490
16.4%
2 421
14.1%
0 412
13.8%
9 346
11.5%
245
8.2%
3 231
7.7%
1 190
 
6.3%
7 144
 
4.8%
6 138
 
4.6%
5 136
 
4.5%
Other values (2) 243
8.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2996
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 490
16.4%
2 421
14.1%
0 412
13.8%
9 346
11.5%
245
8.2%
3 231
7.7%
1 190
 
6.3%
7 144
 
4.8%
6 138
 
4.6%
5 136
 
4.5%
Other values (2) 243
8.1%

사용기준율(퍼센트)
Real number (ℝ)

Distinct11
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.6478873
Minimum1
Maximum50
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2023-12-12T13:11:52.409982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q15
median5
Q310
95-th percentile20
Maximum50
Range49
Interquartile range (IQR)5

Descriptive statistics

Standard deviation7.747515
Coefficient of variation (CV)0.8030271
Kurtosis5.072156
Mean9.6478873
Median Absolute Deviation (MAD)2
Skewness1.9317485
Sum2740
Variance60.023988
MonotonicityNot monotonic
2023-12-12T13:11:52.553837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
5 137
48.2%
10 59
20.8%
20 52
 
18.3%
2 17
 
6.0%
30 7
 
2.5%
3 6
 
2.1%
50 2
 
0.7%
7 1
 
0.4%
15 1
 
0.4%
40 1
 
0.4%
ValueCountFrequency (%)
1 1
 
0.4%
2 17
 
6.0%
3 6
 
2.1%
5 137
48.2%
7 1
 
0.4%
10 59
20.8%
15 1
 
0.4%
20 52
 
18.3%
30 7
 
2.5%
40 1
 
0.4%
ValueCountFrequency (%)
50 2
 
0.7%
40 1
 
0.4%
30 7
 
2.5%
20 52
 
18.3%
15 1
 
0.4%
10 59
20.8%
7 1
 
0.4%
5 137
48.2%
3 6
 
2.1%
2 17
 
6.0%

기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2022-08-29
284 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-08-29
2nd row2022-08-29
3rd row2022-08-29
4th row2022-08-29
5th row2022-08-29

Common Values

ValueCountFrequency (%)
2022-08-29 284
100.0%

Length

2023-12-12T13:11:52.709745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:11:52.830556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-08-29 284
100.0%

Interactions

2023-12-12T13:11:49.337876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:11:49.080284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:11:49.472412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:11:49.206465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:11:52.910728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가맹점 번호지역사용기준율(퍼센트)
가맹점 번호1.0000.4920.457
지역0.4921.0000.000
사용기준율(퍼센트)0.4570.0001.000
2023-12-12T13:11:53.029798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가맹점 번호사용기준율(퍼센트)지역
가맹점 번호1.000-0.2340.224
사용기준율(퍼센트)-0.2341.0000.000
지역0.2240.0001.000

Missing values

2023-12-12T13:11:49.638866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:11:49.776621image/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

가맹점 번호지역가맹점 이름연락처사용기준율(퍼센트)기준일자
032상계동상계숲속작은도서관카페02-3391-7889102022-08-29
133상계동영생흑염소02-937-9267102022-08-29
234상계동맑은숲요가명상마을02-930-2992102022-08-29
336상계동문화플랫폼더숲02-951-0206102022-08-29
437상계동남송주스킨케어02-931-1116102022-08-29
538상계동전주가02-930-953652022-08-29
639상계동원동갈비02-933-488452022-08-29
741상계동터줏대감02-3391-454652022-08-29
842상계동수락골풍천민물장어02-930-797652022-08-29
943상계동상계해물탕02-938-999852022-08-29
가맹점 번호지역가맹점 이름연락처사용기준율(퍼센트)기준일자
274378중계동철수네떡방아간02-6225-149552022-08-29
275380중계동부엉이공인중개사사무소<NA>52022-08-29
276388공릉동공릉평생교육원<NA>202022-08-29
277389하계동장미실습장<NA>202022-08-29
278393공릉동노원구마을공동체지원센터02-978-4281202022-08-29
279395월계동소문난코다리<NA>22022-08-29
280402월계동월계문화복지센터(달빛아래핀카페)02-909-3273102022-08-29
281410상계동백경약국029529545--22022-08-29
282415상계동제뉴어리퍼스트02-951-425152022-08-29
283429공릉동평생학습포털테스트<NA>12022-08-29